National Library of Energy BETA

Sample records for total cloud cover

  1. Estimation of total cloud cover from solar radiation observations at Lake Rotorua, New Zealand

    SciTech Connect (OSTI)

    Luo, Liancong; Hamilton, David; Han, Boping

    2010-03-15

    The DYRESM-CAEDYM model is a valuable tool for simulating water temperature for biochemical studies in aquatic ecosystem. The model requires inputs of surface short-wave radiation and long-wave radiation or total cloud cover fraction (TC). Long-wave radiation is often not measured directly so a method to determine TC from commonly measured short-wave solar irradiance (E{sub 0}) and theoretical short-wave solar irradiance under a clear sky (E{sub c}) has broad application. A more than 17-year (15 November 1991 to 20 February 2009) hourly solar irradiance data set was used to estimate the peak solar irradiance for each ordinal date over one year, which was assumed to be representative of solar irradiance in the absence of cloud. Comparison between these daily observed values and the modelled clear-sky solar radiation over one year was in close agreement (Pearson correlation coefficient, r = 0.995 and root mean squared error, RMSE = 12.54 W m{sup -2}). The downloaded hourly cloudiness measurements from 15 November 1991 to 20 February 2009 was used to calculate the daily values for this period and then the calculated daily values over the 17 years were used to calculate the average values for each ordinal date over one year. A regression equation between (1 - E{sub 0}/E{sub c}) and TC produced a correlation coefficient value of 0.99 (p > 0.01, n = 71). The validation of this cloud cover estimation model was conducted with observed short-wave solar radiation and TC at two sites. Values of TC derived from the model at the Lake Rotorua site gave a reasonable prediction of the observed values (RMSE = 0.10, r = 0.86, p > 0.01, n = 61). The model was also tested at Queenstown (South Island of New Zealand) and it provided satisfactory results compared to the measurements (RMSE = 0.16, r = 0.67, p > 0.01, n = 61). Therefore the model's good performance and broad applicability will contribute to the DYRESM-CAEDYM accuracy of water temperature simulation when long-wave radiation is not available. (author)

  2. ARM - Measurement - Total cloud water

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    cloud water ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total cloud water The total concentration (mass/vol) of ice and liquid water particles in a cloud; this includes condensed water content (CWC). Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a

  3. ARM: Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Krista Gaustad; Laura Riihimaki

    1997-01-01

    Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.

  4. ARM: Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Krista Gaustad; Laura Riihimaki

    Fractional cloud cover, clear-sky and all-sky shortwave flux for each of 25 individual SGP facilities.

  5. Climatological data for clouds over the globe from surface observations, 1982--1991: The total cloud edition

    SciTech Connect (OSTI)

    Hahn, C.J.; Warren, S.G.; London, J.

    1994-10-01

    Routine, surface synoptic weather reports from ships and land stations over the entire globe, for the ten-year period December 1981 through November 1991, were processed for total cloud cover and the frequencies of occurrence of clear sky, precipitation, and sky-obscured due to fog. Archived data, consisting of various annual, seasonal and monthly averages, are provided in grid boxes that are typically 2.5{degrees} {times} 2.5{degrees} for land and 5{degrees} {times} 5{degrees} for ocean. Day and nighttime averages are also given separately for each season. Several derived quantities, such as interannual variations and annual and diurnal harmonics, are provided as well. This data set incorporates an improved representation of nighttime cloudiness by utilizing only those nighttime observations for which the illuminance due to moonlight exceeds a specified threshold. This reduction in the night-detection bias increases the computed global average total cloud cover by about 2%. The impact on computed diurnal cycles is even greater, particularly over the oceans where is found, in contrast to previous surface-based climatologies, that cloudiness is often greater at night than during the day.

  6. Distribution and Validation of Cloud Cover Derived from AVHRR Data Over the Arctic Ocean During the SHEBA Year

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    and Validation of Cloud Cover Derived from AVHRR Data Over the Arctic Ocean During the SHEBA Year P. Minnis National Aeronautics and Space Administration Langley Research Center Hampton, Virginia D. A. Spangenberg and V. Chakrapani Analytical Services and Materials, Inc. Hampton, Virginia Introduction Determination of cloud radiation interactions over large areas of the Arctic is possible only with the use of data from polar orbiting satellites. Cloud detection using satellite data is difficult

  7. Accounting for Circumsolar and Horizon Cloud Determination Errors in Sky Image Inferral of Sky Cover

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Accounting for Circumsolar and Horizon Cloud Determination Errors in Sky Image Inferral of Sky Cover. C. N. Long, Pacific Northwest National Laboratory 1) Introduction In observing the cloudless sky, one can often notice that the area near the sun is whiter and brighter than the rest of the hemisphere. Additionally, even a slight haze will make a large angular area of the horizon whiter and brighter when the sun is low on the horizon. The human eye has an amazing ability to handle a range of

  8. Saharan dust as a causal factor of hemispheric asymmetry in aerosols and cloud cover over the tropical Atlantic Ocean

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Kishcha, Pavel; Da Sliva, Arlindo; Starobinets, Boris; Long, Charles N.; Kalashnikova, Olga; Alpert, Pinhas

    2015-07-09

    Meridional distribution of aerosol optical thickness (AOT) over the tropical Atlantic Ocean (30°N – 30°S) was analyzed to assess seasonal variations of meridional AOT asymmetry. Ten-year MERRA Aerosol Reanalysis (MERRAero) data (July 2002 – June 2012) confirms that the Sahara desert emits a significant amount of dust into the atmosphere over the Atlantic Ocean. Only over the Atlantic Ocean did MERRAero show that desert dust dominates other aerosol species and is responsible for meridional aerosol asymmetry between the tropical North and South Atlantic. Over the 10-year period under consideration, both MISR measurements and MERRAero data showed a pronounced meridional AOTmore » asymmetry. The meridional AOT asymmetry, characterized by the hemispheric ratio (RAOT) of AOT averaged separately over the North and over the South Atlantic, was about 1.7. Seasonally, meridional AOT asymmetry over the Atlantic was the most pronounced between March and July, when dust presence is maximal (RAOT ranged from 2 to 2.4). There was no noticeable meridional aerosol asymmetry in total AOT from September to October. During this period the contribution of carbonaceous aerosols to total AOT in the South Atlantic was comparable to the contribution of dust aerosols to total AOT in the North Atlantic. During the same 10-year period, MODIS cloud fraction (CF) data showed that there was no noticeable asymmetry in meridional CF distribution in different seasons (the hemispheric ratio of CF ranged from 1.0 to 1.2). MODIS CF data illustrated significant cloud cover (CF of 0.7 – 0.9) with limited precipitation ability along the Saharan Air Layer.« less

  9. Saharan dust as a causal factor of hemispheric asymmetry in aerosols and cloud cover over the tropical Atlantic Ocean

    SciTech Connect (OSTI)

    Kishcha, Pavel; Da Sliva, Arlindo; Starobinets, Boris; Long, Charles N.; Kalashnikova, Olga; Alpert, Pinhas

    2015-07-09

    Meridional distribution of aerosol optical thickness (AOT) over the tropical Atlantic Ocean (30°N – 30°S) was analyzed to assess seasonal variations of meridional AOT asymmetry. Ten-year MERRA Aerosol Reanalysis (MERRAero) data (July 2002 – June 2012) confirms that the Sahara desert emits a significant amount of dust into the atmosphere over the Atlantic Ocean. Only over the Atlantic Ocean did MERRAero show that desert dust dominates other aerosol species and is responsible for meridional aerosol asymmetry between the tropical North and South Atlantic. Over the 10-year period under consideration, both MISR measurements and MERRAero data showed a pronounced meridional AOT asymmetry. The meridional AOT asymmetry, characterized by the hemispheric ratio (RAOT) of AOT averaged separately over the North and over the South Atlantic, was about 1.7. Seasonally, meridional AOT asymmetry over the Atlantic was the most pronounced between March and July, when dust presence is maximal (RAOT ranged from 2 to 2.4). There was no noticeable meridional aerosol asymmetry in total AOT from September to October. During this period the contribution of carbonaceous aerosols to total AOT in the South Atlantic was comparable to the contribution of dust aerosols to total AOT in the North Atlantic. During the same 10-year period, MODIS cloud fraction (CF) data showed that there was no noticeable asymmetry in meridional CF distribution in different seasons (the hemispheric ratio of CF ranged from 1.0 to 1.2). MODIS CF data illustrated significant cloud cover (CF of 0.7 – 0.9) with limited precipitation ability along the Saharan Air Layer.

  10. ARM: Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Krista Gaustad; Laura Riihimaki

    1997-01-01

    Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.

  11. ARM: Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Krista Gaustad; Laura Riihimaki

    Gridded (0.25 x 0.25 lat/lon) fractional cloud cover, clear-sky and all-sky shortwave flux over the SGP site.

  12. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    Floorspace (Square Feet) Total Floorspace 2 Fewer than 500... 3.2 Q 0.8 0.9 0.8 0.5 500 to 999......

  13. Total..........................................................

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500... 3.2 357 336 113 188 177 59 500 to 999......

  14. Total..........................................................

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500... 3.2 0.9 0.5 0.4 500 to 999......

  15. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500... 3.2 0.9 0.5 0.9 1.0 500 to 999......

  16. Total..........................................................

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    5.6 17.7 7.9 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500... 3.2 0.5 0.3 Q 500 to 999......

  17. Total............................................................

    Gasoline and Diesel Fuel Update (EIA)

    Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592

  18. Total

    U.S. Energy Information Administration (EIA) Indexed Site

    Product: Total Crude Oil Liquefied Petroleum Gases Propane/Propylene Normal Butane/Butylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending Components Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur

  19. Total

    U.S. Energy Information Administration (EIA) Indexed Site

    Product: Total Crude Oil Liquefied Petroleum Gases Propane/Propylene Normal Butane/Butylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending Components Petroleum Products Finished Motor Gasoline Reformulated Gasoline Conventional Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate Fuel Oil, 15 ppm Sulfur and Under Distillate Fuel Oil, Greater than 15 ppm to 500 ppm Sulfur

  20. Total..........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7

  1. Total..........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1

  2. Total................................................

    Gasoline and Diesel Fuel Update (EIA)

    .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to

  3. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7

  4. Total..........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4

  5. Total...........................................................

    Gasoline and Diesel Fuel Update (EIA)

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9

  6. Final report (Grant No. DOE DE-FG02-97ER62366) [Retrieval of cloud fraction and type using broadband diffuse and total shortwave irradiance measurements

    SciTech Connect (OSTI)

    Clothiaux, Eugene

    2001-05-17

    The primary research effort supported by Grant No. DOE DEFG02-97ER62366 titled ''Retrieval of Cloud Fraction and Type Using Broadband Diffuse and Total Shortwave Irradiance Measurements'' was application of clear-sky identification and cloud fraction estimation algorithms developed by Charles N. Long and Thomas P. Ackerman to the downwelling total, direct and diffuse shortwave irradiance measurements made at all of the central, boundary, and extended facilities of the DOE Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SOP) site. Goals of the research were finalization and publication of the two algorithms in the peer-reviewed literature and operational application of them to all of aforementioned data streams from the ARM SGP site. The clear-sky identification algorithm was published as Long and Ackerman (2000) in the Journal of Geophysical Research, while a description of the cloud fraction estimation algorithm made it to the scientific literature as Long et al. (1999) in the Proceedings of the 10th American Meteorological Association Conference on Atmospheric Radiation held in Madison, Wisconsin. The cloud fraction estimation algorithm relies on empirical relationships between the outputs of the clear-sky identification algorithm and cloud fraction; as such, the cloud fraction estimation algorithm requires significant amounts of data both to properly develop the empirical relationships and to thoroughly test them. With this perspective in mind the major focus of our research efforts in the later half of the project became the operational implementation of the clear-sky identification algorithm on DOE ARM SGP data so that we could develop the data set necessary for final tuning of the cloud fraction estimation algorithm in research extending beyond the lifetime of the project.

  7. Testing a New Cirrus Cloud Parameterizaton

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Institute of Oceanography La Jolla, California Introduction Cirrus cloud cover and ice water content (IWC) are the two most important properties of cirrus clouds. However, in...

  8. ARM - Measurement - Cloud fraction

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    fraction ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud fraction Fraction of sky covered by clouds. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those recorded for diagnostic or quality assurance

  9. Journal Covers

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Journal Covers Journal Covers The Crystallization of PEDOT:PSS Polymeric Electrodes Probed In Situ during Printing Print Thursday, 18 June 2015 11:53 Organic electronics have...

  10. front cover

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Preferred Provider Option (PPO) Medical Program For Active Employees and Their Covered Family Members and Non- Medicare Eligible Retirees and Their Covered Family Members Administered by: N113794 01/15 CUSTOMER ASSISTANCE Customer Service: Medical/Surgical Claims and Prescription Drugs-The 24/7 Nurseline can help when you have a health problem or concern. The 24/7 Nurseline is staffed by registered nurses who are available 24 hours a day, 7 days a week. 24/7 Nurseline toll-free telephone number:

  11. front cover

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Preferred Provider Option (PPO) Medical Program For Medicare Retirees and Their Covered Family Members Administered by: N113794 01/15 CUSTOMER ASSISTANCE Customer Service: Medical/Surgical Claims and Prescription Drugs-The 24/7 Nurseline can help when you have a health problem or concern. The 24/7 Nurseline is staffed by registered nurses who are available 24 hours a day, 7 days a week. 24/7 Nurseline toll-free telephone number: 1-800-973-6329 When you have a non- medical benefit question or

  12. ARM - Measurement - Cloud size

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    measurements as cloud thickness, cloud area, and cloud aspect ratio. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  13. Precipitating clouds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    processes, especially related ice. * Very large differences between observed IN number concentration and ice concentration in a given clouds. * Many ice nucleation modes are...

  14. PAGE Cover: Top Photo

    Energy Savers [EERE]

    PAGE Cover: Top Photo Energy Sciences Building. Elevation of the recently completed Energy Sciences Building (ESB) project at Argonne National Laboratory in Lemont, Illinois. The ESB was a capital line-item project funded by the Science Laboratories Infrastructure program at a total cost of $96 million and was completed on August 6, 2014. The ESB project provided 173,000 gross square feet of interdisciplinary research and collaborative space to accommodate a range of physical sciences research

  15. ARM - Measurement - Cloud type

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Measurement : Cloud type Cloud type such as cirrus, stratus, cumulus etc Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  16. Posters Cloud Parameterizations in Global Climate Models: The Role of Aerosols

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    3 Posters Cloud Parameterizations in Global Climate Models: The Role of Aerosols J. E. Penner and C. C. Chuang Lawrence Livermore National Laboratory Livermore, California Introduction Aerosols influence warm clouds in two ways. First, they determine initial drop size distributions, thereby influencing the albedo of clouds. Second, they determine the lifetime of clouds, thereby possibly changing global cloud cover statistics. At the present time, neither effect of aerosols on clouds is included

  17. Dispelling Clouds of Uncertainty

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Lewis, Ernie; Teixeira, João

    2015-06-15

    How do you build a climate model that accounts for cloud physics and the transitions between cloud regimes? Use MAGIC.

  18. ARM - Measurement - Cloud particle number concentration

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    number concentration ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle number concentration The total number of cloud particles present in any given volume of air. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available

  19. Transforming the representation of the boundary layer and low clouds for high-resolution regional climate modeling: Final report

    SciTech Connect (OSTI)

    Huang, Hsin-Yuan; Hall, Alex

    2013-07-24

    Stratocumulus and shallow cumulus clouds in subtropical oceanic regions (e.g., Southeast Pacific) cover thousands of square kilometers and play a key role in regulating global climate (e.g., Klein and Hartmann, 1993). Numerical modeling is an essential tool to study these clouds in regional and global systems, but the current generation of climate and weather models has difficulties in representing them in a realistic way (e.g., Siebesma et al., 2004; Stevens et al., 2007; Teixeira et al., 2011). While numerical models resolve the large-scale flow, subgrid-scale parameterizations are needed to estimate small-scale properties (e.g. boundary layer turbulence and convection, clouds, radiation), which have significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. To represent the contribution of these fine-scale processes to the resolved scale, climate models use various parameterizations, which are the main pieces in the model that contribute to the low clouds dynamics and therefore are the major sources of errors or approximations in their representation. In this project, we aim to 1) improve our understanding of the physical processes in thermal circulation and cloud formation, 2) examine the performance and sensitivity of various parameterizations in the regional weather model (Weather Research and Forecasting model; WRF), and 3) develop, implement, and evaluate the advanced boundary layer parameterization in the regional model to better represent stratocumulus, shallow cumulus, and their transition. Thus, this project includes three major corresponding studies. We find that the mean diurnal cycle is sensitive to model domain in ways that reveal the existence of different contributions originating from the Southeast Pacific land-masses. The experiments suggest that diurnal variations in circulations and thermal structures over this region are influenced by convection over the Peruvian sector of the Andes cordillera, while the mostly dry mountain-breeze circulations force an additional component that results in semi-diurnal variations near the coast. A series of numerical tests, however, reveal sensitivity of the simulations to the choice of vertical grid, limiting the possibility of solid quantitative statements on the amplitudes and phases of the diurnal and semidiurnal components across the domain. According to our experiments, the Mellor-Yamada-Nakanishi-Niino (MYNN) boundary layer scheme and the WSM6 microphysics scheme is the combination of schemes that performs best. For that combination, mean cloud cover, liquid water path, and cloud depth are fairly wellsimulated, while mean cloud top height remains too low in comparison to observations. Both microphysics and boundary layer schemes contribute to the spread in liquid water path and cloud depth, although the microphysics contribution is slightly more prominent. Boundary layer schemes are the primary contributors to cloud top height, degree of adiabaticity, and cloud cover. Cloud top height is closely related to surface fluxes and boundary layer structure. Thus, our study infers that an appropriate tuning of cloud top height would likely improve the low-cloud representation in the model. Finally, we show that entrainment governs the degree of adiabaticity, while boundary layer decoupling is a control on cloud cover. In the intercomparison study using WRF single-column model experiments, most parameterizations show a poor agreement of the vertical boundary layer structure when compared with large-eddy simulation models. We also implement a new Total-Energy/Mass- Flux boundary layer scheme into the WRF model and evaluate its ability to simulate both stratocumulus and shallow cumulus clouds. Result comparisons against large-eddy simulation show that this advanced parameterization based on the new Eddy-Diffusivity/Mass-Flux approach provides a better performance than other boundary layer parameterizations.

  20. Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Prather, M. J.

    2015-05-27

    A new approach for modeling photolysis rates (J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations. Cloud-Jmore » is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.« less

  1. Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Prather, M. J.

    2015-08-14

    A new approach for modeling photolysis rates (J values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations by four quadrature atmospheres produces mean J values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 % errorsmore » using simpler approximations. Cloud-J is practical for chemistry–climate models, requiring only an average of 2.8 Fast-J calls per atmosphere vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections, is also incorporated into Cloud-J.« less

  2. ARM - Measurement - Cloud location

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    point in space and time, typically expressed as a binary cloud mask. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  3. ARM - Measurement - Cloud extinction

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    an incident beam by the process of cloud absorption andor scattering. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  4. Dispelling Clouds of Uncertainty

    SciTech Connect (OSTI)

    Lewis, Ernie; Teixeira, João

    2015-06-15

    How do you build a climate model that accounts for cloud physics and the transitions between cloud regimes? Use MAGIC.

  5. Multiple layer insulation cover

    DOE Patents [OSTI]

    Farrell, James J.; Donohoe, Anthony J.

    1981-11-03

    A multiple layer insulation cover for preventing heat loss in, for example, a greenhouse, is disclosed. The cover is comprised of spaced layers of thin foil covered fabric separated from each other by air spaces. The spacing is accomplished by the inflation of spaced air bladders which are integrally formed in the cover and to which the layers of the cover are secured. The bladders are inflated after the cover has been deployed in its intended use to separate the layers of the foil material. The sizes of the material layers are selected to compensate for sagging across the width of the cover so that the desired spacing is uniformly maintained when the cover has been deployed. The bladders are deflated as the cover is stored thereby expediting the storage process and reducing the amount of storage space required.

  6. Providing Diurnal Sky Cover Data at ARM Sites

    SciTech Connect (OSTI)

    Klebe, Dimitri I.

    2015-03-06

    The Solmirus Corporation was awarded two-year funding to perform a comprehensive data analysis of observations made during Solmirus 2009 field campaign (conducted from May 21 to July 27, 2009 at the ARM SGP site) using their All Sky Infrared Visible Analyzer (ASIVA) instrument. The objective was to develop a suite of cloud property data products for the ASIVA instrument that could be implemented in real time and tailored for cloud modelers. This final report describes Solmirus research and findings enabled by this grant. The primary objective of this award was to develop a diurnal sky cover (SC) data product utilizing the ASIVAs infrared (IR) radiometrically-calibrated data and is described in detail. Other data products discussed in this report include the sky cover derived from ASIVAs visible channel and precipitable water vapor, cloud temperature (both brightness and color), and cloud height inferred from ASIVAs IR channels.

  7. ARM - Cover Competition Winners

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    MeetingsCover Competition Winners Science Team Meetings 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 Cover Competition Winners In order to gather more ARM science images, the ARM Science Team Meeting began a competition for the coveted meeting program cover. From 2004-2009, ARM principal investigators were invited to share their research images with meeting organizers for selection by the ARM Chief Scientist. Covers were selected based on their

  8. ARM - Cloud Memory

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Memory Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Cloud Memory Now you can make your own cloud memory game to practice recognizing clouds at home or share with your class. Example (not to scale) of cloud memory card available for download. Example (not to scale) of cloud memory card

  9. Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties

    SciTech Connect (OSTI)

    Wang, Zhien

    2010-06-29

    The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processes is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model simulations. The ultimate goal is to improve our cloud classification algorithm into a VAP.

  10. Shafts Temporarily Covered

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    3, 2014 Shafts Temporarily Covered Today, workers continued physical preparations for the filter replacement. The Air Intake Shaft and Salt Handling Shaft openings were temporarily covered to further reduce the amount of air entering the underground. Covering these opening helps maintain ventilation balance while continuing to draw surface air down to the waste shaft, and prevents unfiltered air from exiting the underground. Workers not directly involved in the filter replacement efforts

  11. Journal Cover Stories

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Journal Cover Stories Journal Cover Stories Here are papers authored by NERSC users that were featured on the cover of the scientific journal in which they were published. You can sort according to any of the headings below. Sort by: Default | Name | Date (low-high) | Date (high-low) | Source | Category JBEIJPCB-2015.png Molecular Dynamics Simulation study on the Dissolution of Cellulose in Ionic Liquid-Water Mixture November 12, 2015 | Author(s): R. Parthasarathi, K. Balamurugan, Jian Shi, V.

  12. Cover Heated, Open Vessels

    Broader source: Energy.gov [DOE]

    This tip sheet on covering heated, open vessels provides how-to advice for improving industrial steam systems using low-cost, proven practices and technologies.

  13. NERSC Journal Cover Stories

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    | png | 729 KB AGU-WRR2015Cover.png Numerical simulation of the environmental impact of hydraulic fracturing of tightshale gas reservoirs on near-surface groundwater:...

  14. cover_booked.indd

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    This Real Property Asset Management Plan covers the Department of Energy including the National Nuclear Security Administration, the Energy Information Administration, and the ...

  15. Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Shupe, Matthew

    2013-05-22

    Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files are available for manually-selected, stratiform, mixed-phase cloud cases observed at the North Slope of Alaska (NSA) site during periods covering the Mixed-Phase Arctic Cloud Experiment (MPACE, late September through early November 2004) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC, April-early May 2008). These time periods will be expanded in a future submission.

  16. Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Shupe, Matthew

    Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files are available for manually-selected, stratiform, mixed-phase cloud cases observed at the North Slope of Alaska (NSA) site during periods covering the Mixed-Phase Arctic Cloud Experiment (MPACE, late September through early November 2004) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC, April-early May 2008). These time periods will be expanded in a future submission.

  17. The Effect of Precipitation on Variability of Low Stratiform Clouds Over ARM SGP Site

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Precipitation on Variability of Low Stratiform Clouds Over ARM SGP Site Z. N. Kogan, D. B. Mechem, and Y. L. Kogan Cooperative Institute for Mesoscale Metorological Studies University of Oklahoma Norman, Oklahoma Introduction Continental low stratiform clouds cover the sky about 23% of the time during the fall, winter, and spring months and play a significant role in the Earth' radiation budget. Information about cloud structure and variability is crucial in determining areal averages of cloud

  18. Journal Cover Stories

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    NatureCoverLarge.png High-quality electron beams from a laser wakefield accelerator using plasma-channel guiding September 30, 2004 | Author(s): C. G. R. Geddes, Cs. Toth, J. van Tilborg, E. Esarey, C. B. Schroeder, D. Bruhwiler, C. Nieter, J. Cary & W. P. Leemans | Source: Nature | Category: Fusion Energy | URL: http://dx.doi.org/10.1038/nature02900 Download Image: NatureCoverLarge.png | png | 2.7 MB 30 September 2004, Vol. 431, pp. 541-544 PhysTodayCoverLarge.png Integrated Simulation of

  19. Journal Cover Stories

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    CEN-Cover.png Graphene Moves Toward Applications November 21, 2011 | Author(s): Donghai Mei, et al. | Category: Chemistry | URL: http://dx.doi.org/10.1021/nl203332e Download Image: CEN-Cover.png | png | 986 KB Hierarchically Porous Graphene as a Lithium-Air Battery Electrode. See also http://pubs.acs.org/NanoLett (2011) 11, 5071-5078 SotirisCoverJPCBLarge.jpg Computational Investigation of the First Solvation Shell Structure of Interfacial and Bulk Aqueous Chloride and Iodide Ions November 14,

  20. Unnumbered in cover letter

    Office of Legacy Management (LM)

    A John McCray, Colorado Oil and Gas Conservation Commission Unnumbered in cover letter The DOE report demonstrates a high level of technical competence; the modeling work and analysis are technically sound. No obviously serious flaws were discovered in the analysis described in the report. We thank the reviewer for sharing his observations in this regard. Unnumbered in cover letter However, I have identified some technical weaknesses that should be considered when evaluating the results in the

  1. Reusable pipe flange covers

    DOE Patents [OSTI]

    Holden, James Elliott (Simpsonville, SC); Perez, Julieta (Houston, TX)

    2001-01-01

    A molded, flexible pipe flange cover for temporarily covering a pipe flange and a pipe opening includes a substantially round center portion having a peripheral skirt portion depending from the center portion, the center portion adapted to engage a front side of the pipe flange and to seal the pipe opening. The peripheral skirt portion is formed to include a plurality of circumferentially spaced tabs, wherein free ends of the flexible tabs are formed with respective through passages adapted to receive a drawstring for pulling the tabs together on a back side of the pipe flange.

  2. Finance Idol Word Cloud

    Broader source: Energy.gov [DOE]

    This word cloud represents the topics discussed during the Big and Small Ideas: How to Lower Solar Financing Costs breakout session at the SunShot Grand Challenge.

  3. ARM - Measurement - Cloud phase

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    that involves property descriptors such as stratus, cumulus, and cirrus. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  4. Journal Cover Stories

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Darmon Chem Science 2015 cover page Increasing the rate of hydrogen oxidation without increasing the overpotential: a bio-inspired iron molecular electrocatalyst with an outer coordination sphere proton relay March 5, 2015 | Author(s): Jonathan M. Darmon, Neeraj Kumar, Elliott B. Hulley, Charles J. Weiss, Simone Raugei, R. Morris Bullocka and Monte L. Helm* Center for Molecular Electrocatalysis, Physical Sciences Division, Pacific Northwest National Laboratory, P.O. Box 999, K2-57, Richland, USA

  5. cover_booked.indd

    Broader source: Energy.gov (indexed) [DOE]

    DOE/ME-0060 Editors Notes: This Real Property Asset Management Plan covers the Department of Energy including the National Nuclear Security Administration, the Energy Information Administration, and the Power Marketing Administrations. As an independent regulatory agency, the Federal Energy Regulatory Commission (FERC) prepares separate documents. This document is also available on the Department of Energy's web site: http://www.energy.gov. This plan was produced by the Office of Engineering

  6. Parameterizing Size Distribution in Ice Clouds

    SciTech Connect (OSTI)

    DeSlover, Daniel; Mitchell, David L.

    2009-09-25

    PARAMETERIZING SIZE DISTRIBUTIONS IN ICE CLOUDS David L. Mitchell and Daniel H. DeSlover ABSTRACT An outstanding problem that contributes considerable uncertainty to Global Climate Model (GCM) predictions of future climate is the characterization of ice particle sizes in cirrus clouds. Recent parameterizations of ice cloud effective diameter differ by a factor of three, which, for overcast conditions, often translate to changes in outgoing longwave radiation (OLR) of 55 W m-2 or more. Much of this uncertainty in cirrus particle sizes is related to the problem of ice particle shattering during in situ sampling of the ice particle size distribution (PSD). Ice particles often shatter into many smaller ice fragments upon collision with the rim of the probe inlet tube. These small ice artifacts are counted as real ice crystals, resulting in anomalously high concentrations of small ice crystals (D < 100 m) and underestimates of the mean and effective size of the PSD. Half of the cirrus cloud optical depth calculated from these in situ measurements can be due to this shattering phenomenon. Another challenge is the determination of ice and liquid water amounts in mixed phase clouds. Mixed phase clouds in the Arctic contain mostly liquid water, and the presence of ice is important for determining their lifecycle. Colder high clouds between -20 and -36 oC may also be mixed phase but in this case their condensate is mostly ice with low levels of liquid water. Rather than affecting their lifecycle, the presence of liquid dramatically affects the cloud optical properties, which affects cloud-climate feedback processes in GCMs. This project has made advancements in solving both of these problems. Regarding the first problem, PSD in ice clouds are uncertain due to the inability to reliably measure the concentrations of the smallest crystals (D < 100 m), known as the small mode. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of ice cloud optical properties formulated in terms of PSD parameters in combination with remote measurements of thermal radiances to characterize the small mode. This is possible since the absorption efficiency (Qabs) of small mode crystals is larger at 12 m wavelength relative to 11 m wavelength due to the process of wave resonance or photon tunneling more active at 12 m. This makes the 12/11 m absorption optical depth ratio (or equivalently the 12/11 m Qabs ratio) a means for detecting the relative concentration of small ice particles in cirrus. Using this principle, this project tested and developed PSD schemes that can help characterize cirrus clouds at each of the three ARM sites: SGP, NSA and TWP. This was the main effort of this project. These PSD schemes and ice sedimentation velocities predicted from them have been used to test the new cirrus microphysics parameterization in the GCM known as the Community Climate Systems Model (CCSM) as part of an ongoing collaboration with NCAR. Regarding the second problem, we developed and did preliminary testing on a passive thermal method for retrieving the total water path (TWP) of Arctic mixed phase clouds where TWPs are often in the range of 20 to 130 g m-2 (difficult for microwave radiometers to accurately measure). We also developed a new radar method for retrieving the cloud ice water content (IWC), which can be vertically integrated to yield the ice water path (IWP). These techniques were combined to determine the IWP and liquid water path (LWP) in Arctic clouds, and hence the fraction of ice and liquid water. We have tested this approach using a case study from the ARM field campaign called M-PACE (Mixed-Phase Arctic Cloud Experiment). This research led to a new satellite remote sensing method that appears promising for detecting low levels of liquid water in high clouds typically between -20 and -36 oC. We hope to develop this method in future research.

  7. Boundary Layer Cloud Turbulence Characteristics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    (10) Modeling Need (10) Cloud Boundaries 9 9 Cloud Fraction Variance Skewness UpDowndraft coverage Dominant Freq. signal Dissipation rate ??? Observation-Modeling Interface...

  8. TC_CLOUD_REGIME.cdr

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    intensity (e.g. May and Ballinger, 2007) Resulting Cloud Properties Examine rain DSD using polarimetric radar Examine ice cloud properties using MMCR and MPL Expect...

  9. ARM - Measurement - Cloud droplet size

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    droplet size Linear size (e.g. radius or diameter) of a cloud particle Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  10. ARM - Measurement - Cloud effective radius

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    the number size distribution of cloud particles, whether liquid or ice. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the...

  11. Cloud computing security.

    SciTech Connect (OSTI)

    Shin, Dongwan; Claycomb, William R.; Urias, Vincent E.

    2010-10-01

    Cloud computing is a paradigm rapidly being embraced by government and industry as a solution for cost-savings, scalability, and collaboration. While a multitude of applications and services are available commercially for cloud-based solutions, research in this area has yet to fully embrace the full spectrum of potential challenges facing cloud computing. This tutorial aims to provide researchers with a fundamental understanding of cloud computing, with the goals of identifying a broad range of potential research topics, and inspiring a new surge in research to address current issues. We will also discuss real implementations of research-oriented cloud computing systems for both academia and government, including configuration options, hardware issues, challenges, and solutions.

  12. Journal Cover Stories

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Liu2010.jpg Methanol Synthesis from H2 and CO2 on a Mo6S8 Cluster: A Density Functional Study October 30, 2009 | Author(s): Ping Liu, YongMan Choi, Y. Yang and M. G. White | Source: J. Phys. Chem. A | Category: Chemistry | URL: http://dx.doi.org/10.1021/jp906780a Download Image: Liu2010.jpg | jpg | 2.1 MB J. Phys. Chem. A, 2010, 114 (11), pp 3888-3895 ChingCoverPaper.png A Genomic Approach to the Stability, Elastic, and Electronic Properties of the MAX Phases June 24, 2014 | Author(s): S. Aryal,

  13. The relationship between interannual and long-term cloud feedbacks

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Zhou, Chen; Zelinka, Mark D.; Dessler, Andrew E.; Klein, Stephen A.

    2015-12-11

    The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual andmore » long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.« less

  14. CoverSheet

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    4 Triphenylmethane: a new neutron moderator? Measuring the total kinetic energy release in fission 5 High energy neutron computed tomography at LANSCE 7 Neutron scattering en- ables structural charac- terization of multifunc- tional materials 8 Heads UP! P2 recipients recognized for environmental successes " We are measuring quantities of nature and there is one correct answer-if we have the wherewithal to find it and know that we found it. " Shea Mosby holds a scintillating crystal,

  15. ARM - Cloud and Rain

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ListCloud and Rain Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Cloud and Rain Water vapor is an invisible gas that is always present in the troposphere. However, the amount of water vapor which the air can hold depends directly on the air temperature. Warm air can hold much more water

  16. Magellan: A Cloud Computing Testbed

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Magellan News & Announcements Archive Petascale Initiative Exascale Computing APEX Home » R & D » Archive » Magellan: A Cloud Computing Testbed Magellan: A Cloud Computing Testbed Cloud computing is gaining a foothold in the business world, but can clouds meet the specialized needs of scientists? That was one of the questions NERSC's Magellan cloud computing testbed explored between 2009 and 2011. The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Oce

  17. ARM - Measurement - Cloud base height

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    base height ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud base height For a given cloud or cloud layer, the lowest level of the atmosphere where cloud properties are detectable. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all

  18. ARM - Measurement - Cloud top height

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    top height ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud top height For a given cloud or cloud layer, the highest level of the atmosphere where cloud properties are detectable. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all

  19. First observations of tracking clouds using scanning ARM cloud radars

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (first echo). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.

  20. First observations of tracking clouds using scanning ARM cloud radars

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.

  1. Identifying clouds over the Pierre Auger Observatory using infrared satellite data

    SciTech Connect (OSTI)

    Abreu, Pedro; et al.,

    2013-12-01

    We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

  2. Opaque cloud detection

    DOE Patents [OSTI]

    Roskovensky, John K. (Albuquerque, NM)

    2009-01-20

    A method of detecting clouds in a digital image comprising, for an area of the digital image, determining a reflectance value in at least three discrete electromagnetic spectrum bands, computing a first ratio of one reflectance value minus another reflectance value and the same two values added together, computing a second ratio of one reflectance value and another reflectance value, choosing one of the reflectance values, and concluding that an opaque cloud exists in the area if the results of each of the two computing steps and the choosing step fall within three corresponding predetermined ranges.

  3. Bringing Clouds into Focus

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Bringing Clouds into Focus Bringing Clouds into Focus A New Global Climate Model May Reduce the Uncertainty of Climate Forecasting May 11, 2010 Contact: John Hules, JAHules@lbl.gov , +1 510 486 6008 Randall-fig4.png The large data sets generated by the GCRM require new analysis and visualization capabilities. This 3D plot of vorticity isosurfaces was developed using VisIt, a 3D visualization tool with a parallel distributed architecture, which is being extended to support the geodesic grid used

  4. ARM - Cloud Twist

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Twist Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Cloud Twist Want to make your own version of Cloud Twist? Here are the files you will need. Floor Mat A low resolution image (7.3 MB) and high resolution image (53.2 MB) are available. Spinner Board A low resolution image (992.6 KB) and

  5. Cloud Based Applications and Platforms (Presentation)

    SciTech Connect (OSTI)

    Brodt-Giles, D.

    2014-05-15

    Presentation to the Cloud Computing East 2014 Conference, where we are highlighting our cloud computing strategy, describing the platforms on the cloud (including Smartgrid.gov), and defining our process for implementing cloud based applications.

  6. SUPERGIANT SHELLS AND MOLECULAR CLOUD FORMATION IN THE LARGE MAGELLANIC CLOUD

    SciTech Connect (OSTI)

    Dawson, J. R.; Dickey, John M.; McClure-Griffiths, N. M.; Wong, T.; Hughes, A.; Fukui, Y.; Kawamura, A.

    2013-01-20

    We investigate the influence of large-scale stellar feedback on the formation of molecular clouds in the Large Magellanic Cloud (LMC). Examining the relationship between H I and {sup 12}CO(J = 1-0) in supergiant shells (SGSs), we find that the molecular fraction in the total volume occupied by SGSs is not enhanced with respect to the rest of the LMC disk. However, the majority of objects ({approx}70% by mass) are more molecular than their local surroundings, implying that the presence of a supergiant shell does on average have a positive effect on the molecular gas fraction. Averaged over the full SGS sample, our results suggest that {approx}12%-25% of the molecular mass in supergiant shell systems was formed as a direct result of the stellar feedback that created the shells. This corresponds to {approx}4%-11% of the total molecular mass of the galaxy. These figures are an approximate lower limit to the total contribution of stellar feedback to molecular cloud formation in the LMC, and constitute one of the first quantitative measurements of feedback-triggered molecular cloud formation in a galactic system.

  7. A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.

    SciTech Connect (OSTI)

    Luke,E.; Kollias, P.

    2007-08-06

    The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phase cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.

  8. Covered Product Category: Commercial Griddles

    Broader source: Energy.gov [DOE]

    The Federal Energy Management Program (FEMP) provides acquisition guidance for commercial griddles, which is a product category covered by the ENERGY STAR program

  9. Covered Product Category: Commercial Fryers

    Broader source: Energy.gov [DOE]

    The Federal Energy Management Program (FEMP) provides acquisition guidance for commercial fryers, which is a product category covered by the ENERGY STAR program.

  10. ARM - Measurement - Images of Clouds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govMeasurementsImages of Clouds ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Images of Clouds Digital images of cloud scenes (various formats) from satellite, aircraft, and ground-based platforms. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a

  11. Barge Truck Total

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over...

  12. Center for Nanophase Materials Sciences (CNMS) - Journal Cover Gallery

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    JOURNAL COVER GALLERY

  13. ARM - Cloud Word Seek

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Word Seek Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Cloud Word Seek

  14. First observations of tracking clouds using scanning ARM cloud radars

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud fieldmore » and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.« less

  15. ARM - Midlatitude Continental Convective Clouds (jensen-sonde)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

    2012-01-19

    A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment.

  16. Analysis of global radiation budgets and cloud forcing using three-dimensional cloud nephanalysis data base. Master's thesis

    SciTech Connect (OSTI)

    Mitchell, B.

    1990-12-01

    A one-dimensional radiative transfer model was used to compute the global radiative budget at the top of the atmosphere (TOA) and the surface for January and July. 1979. The model was also used to determine the global cloud radiative forcing for all clouds and for high and low cloud layers. In the computations. the authors used the monthly cloud data derived from the Air Force Three-Dimensional Cloud Nephanalysis (3DNEPH). These data were used in conjunction with conventional temperature and humidity profiles analyzed during the 1979 First GARP (Global Atmospheric Research Program) Global Experiment (FGGE) year. Global surface albedos were computed from available data and were included in the radiative transfer analysis. Comparisons of the model-produced outgoing solar and infrared fluxes with those derived from Nimbus 7 Earth Radiation Budget (ERS) data were made to validate the radiative model and cloud cover. For reflected solar and emitted infrared (IR) flux, differences within 20 w/sq m meters were shown.

  17. cover

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

  18. Cover

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... originally planned for service are discontinued due to political andor economic reasons. ... contractual obligations with third-party power providers in 2007. Under the terms ...

  19. COVER

    Office of Environmental Management (EM)

    The Requirements-Based Surveillance and Maintenance Review Guide Washington, D.C. Office of Environmental Management Office Nuclear Material and Facility Stabilization DOE/EM-0341 Requirements-Based Surveillance and Maintenance Review Guideline

  20. Cover

    Office of Environmental Management (EM)

    Uranium Enrichment Decontamination and Decommissioning Fund's Fiscal Year 2011 Financial Statement Audit OAS-FS-13-01 October 2012 UNITED STATES DEPARTMENT OF ENERGY OFFICE OF ENVIRONMENTAL MANAGEMENT URANIUM ENRICHMENT DECONTAMINATION AND DECOMMISSIONING FUND Financial Statements September 30, 2011 and 2010 (With Independent Auditors' Reports Thereon) UNITED STATES DEPARTMENT OF ENERGY OFFICE OF ENVIRONMENTAL MANAGEMENT URANIUM ENRICHMENT DECONTAMINATION AND DECOMMISSIONING FUND Table of

  1. Cover Stories | Argonne National Laboratory

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    In Situ Characterization of Li-ion Battery Electrochemistry via Scanning Ion Conductance Microscopy," Adv. Mater., 23, 5613-5617 (2011). Click to view cover V. G. Pol and...

  2. Journal Cover Gallery | The Ames Laboratory

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Journal Cover Gallery Image Image ACS Victor SunJALA2011_cover Image Image Image Image Image Image

  3. Covered Product Category: Residential Electric Resistance Water...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Covered Product Category: Residential Electric Resistance Water Heaters Covered Product Category: Residential Electric Resistance Water Heaters The Federal Energy Management ...

  4. Total Crude by Pipeline

    U.S. Energy Information Administration (EIA) Indexed Site

    Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign

  5. TURBULENCE DECAY AND CLOUD CORE RELAXATION IN MOLECULAR CLOUDS

    SciTech Connect (OSTI)

    Gao, Yang; Law, Chung K.; Xu, Haitao

    2015-02-01

    The turbulent motion within molecular clouds is a key factor controlling star formation. Turbulence supports molecular cloud cores from evolving to gravitational collapse and hence sets a lower bound on the size of molecular cloud cores in which star formation can occur. On the other hand, without a continuous external energy source maintaining the turbulence, such as in molecular clouds, the turbulence decays with an energy dissipation time comparable to the dynamic timescale of clouds, which could change the size limits obtained from Jean's criterion by assuming constant turbulence intensities. Here we adopt scaling relations of physical variables in decaying turbulence to analyze its specific effects on the formation of stars. We find that the decay of turbulence provides an additional approach for Jeans' criterion to be achieved, after which gravitational infall governs the motion of the cloud core. This epoch of turbulence decay is defined as cloud core relaxation. The existence of cloud core relaxation provides a more complete understanding of the effect of the competition between turbulence and gravity on the dynamics of molecular cloud cores and star formation.

  6. ,"Total Natural Gas Consumption

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Consumption (billion cubic feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  7. Clouds' Role in Sunlight Stopping

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Clouds' Role in Sunlight Stopping For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight Clouds are energy traffic cops, controlling how much sunlight reaches Earth. Pacific Northwest National Laboratory (PNNL) researchers used long-term observations to show that the sunlight stopping power of each type of typical tropical cloud, and how frequently they occur, must be accurately simulated in climate models. Otherwise,

  8. ARM - Measurement - Cloud ice particle

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ice particle ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud ice particle Particles made of ice found in clouds. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those recorded for diagnostic or

  9. ARM - Measurement - Cloud optical depth

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    optical depth ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud optical depth Amount of light cloud droplets or ice particles prevent from passing through a column of atmosphere. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all

  10. Final Scientific/Technical Report Grant title: Use of ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes and Aerosol-Cloud Interaction This is a collaborative project with the NASA GSFC project of Dr. A. Marshak and W. Wiscombe (PIs). This report covers BU activities from February 2011 to June 2011 and BU "œno-cost extension" activities from June 2011 to June 2012. This report summarizes results that complement a final technical report submitted by the PIs in 2011.

    SciTech Connect (OSTI)

    Knyazikhin, Y

    2012-09-10

    Main results are summarized for work in these areas: spectrally-invariant approximation within atmospheric radiative transfer; spectral invariance of single scattering albedo for water droplets and ice crystals at weakly absorbing wavelengths; seasonal changes in leaf area of Amazon forests from leaf flushing and abscission; and Cloud droplet size and liquid water path retrievals from zenith radiance measurements.

  11. TWP Island Cloud Trail Studies

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    a key to understanding boundary layer cloud formation in the tropics. Except during El Nio periods, Nauru represents a divergent region of the ocean upwind from the...

  12. ARM - Measurement - Cloud condensation nuclei

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AOS : Aerosol Observing System CCN : Cloud Condensation Nuclei Particle Counter TDMA : Tandem Differential Mobility Analyzer Field Campaign Instruments AMT : Aerosol Modeling...

  13. Widget:LogoCloud | Open Energy Information

    Open Energy Info (EERE)

    LogoCloud Jump to: navigation, search This widget adds css selectors and javascript for the Template:LogoCloud. For example: Widget:LogoCloud Retrieved from "http:...

  14. Zenith Radiance Retrieval of Cloud Properties

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    retrievals of cloud properties from the AMF/COPS campaign Preliminary retrievals of cloud properties from the AMF/COPS campaign Christine Chiu, UMBC/JCET Alexander Marshak, GSFC Yuri Knyazikhin, Boston University Warren Wiscombe, GSFC Christine Chiu, UMBC/JCET Alexander Marshak, GSFC Yuri Knyazikhin, Boston University Warren Wiscombe, GSFC The cloud optical properties of interest are: The cloud optical properties of interest are: * Cloud optical depth τ - the great unknown * Radiative cloud

  15. ARM - Measurement - Net broadband total irradiance

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govMeasurementsNet broadband total irradiance ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Net broadband total irradiance The difference between upwelling and downwelling, covering longwave and shortwave radiation. Categories Radiometric Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each

  16. Perturbed Physics Ensemble Simulations of Cirrus on the Cloud System-resolving Scale

    SciTech Connect (OSTI)

    Muhlbauer, Andreas; Berry, Elizabeth; Comstock, Jennifer M.; Mace, Gerald G.

    2014-04-16

    In this study, the effect of uncertainties in the parameterization of ice microphysical processes and initial conditions on the variability of cirrus microphysical and radiative properties are investigated in a series of cloud system-resolving perturbed physics ensemble (PPE) and initial condition ensemble (ICE) simulations. Three cirrus cases representative of mid-latitude, subtropical and tropical cirrus are examined. It is found that the variability in cirrus properties induced by perturbing uncertain parameters in ice microphysics parameterizations outweighs the variability induced by perturbing the initial conditions in midlatitude and subtropical cirrus. However, in tropical anvil cirrus the variability in the PPE and ICE simulations is about the same order of magnitude. The cirrus properties showing the largest sensitivity are ice water content (IWC) and cloud thickness whereas the averaged high cloud cover is only marginally affected. Changes in cirrus ice water path and outgoing longwave radiation are controlled primarily by changes in IWC and cloud thickness but not by changes is the averaged high cloud cover. The change in the vertical distribution of cloud fraction and cloud thickness is caused by changes in cirrus cloud base whereas cloud top is not sensitive to either perturbed physics or perturbed initial conditions. In all cirrus cases, the top three parameters controlling the microphysical variability and radiative impact of cirrus clouds are ice fall speeds, ice autoconversion size thresholds and heterogeneous ice nucleation. Changes in the ice deposition coefficient do not affect the ice water path and outgoing longwave radiation. Similarly, changes in the number concentration of aerosols available for homogeneous freezing have virtually no effect on the microphysical and radiative properties of midlatitude and subtropical cirrus but only little impact on tropical anvil cirrus. Overall, the sensitivity of cirrus microphysical and radiative properties to uncertainties in ice microphysics is largest for midlatitude cirrus and smallest for tropical anvil cirrus.

  17. Dynamics of Molecular Clouds: Observations, Simulations, and...

    Office of Scientific and Technical Information (OSTI)

    Conference: Dynamics of Molecular Clouds: Observations, Simulations, and NIF Experiments Citation Details In-Document Search Title: Dynamics of Molecular Clouds: Observations,...

  18. Clouds Environmental Ltd | Open Energy Information

    Open Energy Info (EERE)

    Clouds Environmental Ltd Jump to: navigation, search Name: Clouds Environmental Ltd Place: Portsmouth, United Kingdom Zip: PO3 5EG Product: Independent consultancy specialising in...

  19. Cloud Properties Working Group Break Out Session

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    relation to fall speeds, implications for previous measurements. (Mitchell) Q8: Geoengineering of cirrus clouds (Mitchell) Q9: Cold cloud phase partitioning: Roles of...

  20. Corrugated cover plate for flat plate collector

    DOE Patents [OSTI]

    Hollands, K. G. Terry (Elora, CA); Sibbitt, Bruce (Waterloo, CA)

    1978-01-01

    A flat plate radiant energy collector is providing having a transparent cover. The cover has a V-corrugated shape which reduces the amount of energy reflected by the cover away from the flat plate absorber of the collector.

  1. BioChem Cover story

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    LSU Researcher discovers a key step in photosynthesis at CAMD, earns cover on Journal of Biological Chemistry Photosynthesis is the process that plants use to convert light into chemical energy for plant growth. This process produces all of the oxygen present on earth and virtually all of the carbohydrate which lies at the base of all food chains. Photosystem II is a protein complex that captures light and begins the first step in this biological chemistry: breaking apart water molecules. At the

  2. Microsoft Word - Cover Sheet - 020711

    National Nuclear Security Administration (NNSA)

    II: Comment Response Document COVER SHEET RESPONSIBLE AGENCY: United States (U.S.) Department of Energy (DOE), National Nuclear Security Administration (NNSA) TITLE: Final Site-Wide Environmental Impact Statement for the Y-12 National Security Complex (DOE/EIS-0387) (Final Y-12 SWEIS) CONTACT: For further information on this SWEIS, For general information on the DOE contact: National Environmental Policy Act (NEPA) process, contact: Pam Gorman Carol Borgstrom, Director Y-12 SWEIS Document

  3. Household Vehicles Energy Use Cover Page

    U.S. Energy Information Administration (EIA) Indexed Site

    Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback * PrivacySecurity *...

  4. Evaluation of high‐level clouds in cloud resolving model...

    Office of Scientific and Technical Information (OSTI)

    ... Res., 104, 24,527-24,545. Rasmussen, R. M., I. Geresdi, G. Thompson, K. Manning, and E. Karplus (2002), Freezing drizzle formation in stably stratified layer clouds: The role of ...

  5. ARM - Field Campaign - Cloud IOP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsCloud IOP ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Cloud IOP 1998.04.27 - 1998.05.17 Lead Scientist : Gerald Mace For data sets, see below. Summary Monday, April 27, 1998 IOP Opening Activities: Heavy rain (nearly 2.5" since 12Z 4/26/98) at the central facility (CF) dominated the first day of the Cloud Physics/Single Column Model IOP and limited the daily activities. A 1430 GMT

  6. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration...

  7. ,"Total Fuel Oil Expenditures

    U.S. Energy Information Administration (EIA) Indexed Site

    . Fuel Oil Expenditures by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per...

  8. ,"Total Fuel Oil Consumption

    U.S. Energy Information Administration (EIA) Indexed Site

    0. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  9. ,"Total Fuel Oil Expenditures

    U.S. Energy Information Administration (EIA) Indexed Site

    4. Fuel Oil Expenditures by Census Region, 1999" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per Square Foot"...

  10. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

  11. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

  12. ,"Total Fuel Oil Expenditures

    U.S. Energy Information Administration (EIA) Indexed Site

    A. Fuel Oil Expenditures by Census Region for All Buildings, 2003" ,"Total Fuel Oil Expenditures (million dollars)",,,,"Fuel Oil Expenditures (dollars)" ,,,,,"per Gallon",,,,"per...

  13. ,"Total Fuel Oil Consumption

    U.S. Energy Information Administration (EIA) Indexed Site

    A. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  14. Water-Balance Cover Performance

    Broader source: Energy.gov (indexed) [DOE]

    1 Conference, February 27-March 3, 2011, Phoenix, AZ Design and Installation of a Disposal Cell Cover Field Test C.H. Benson University of Wisconsin-Madison, Madison, Wisconsin W.J. Waugh S.M. Stoller Corporation, Grand Junction, Colorado W.H. Albright Desert Research Institute, Reno, Nevada G.M. Smith Geo-Smith Engineering, Grand Junction, Colorado R.P. Bush U.S. Department of Energy, Grand Junction, Colorado ABSTRACT The U.S. Department of Energy's Office of Legacy Management (LM) initiated a

  15. COLORS OF A SECOND EARTH. II. EFFECTS OF CLOUDS ON PHOTOMETRIC CHARACTERIZATION OF EARTH-LIKE EXOPLANETS

    SciTech Connect (OSTI)

    Fujii, Yuka; Suto, Yasushi; Turner, Edwin L. [Department of Physics, The University of Tokyo, Tokyo 113-0033 (Japan); Kawahara, Hajime [Department of Physics, Tokyo Metropolitan University, Hachioji, Tokyo 192-0397 (Japan); Fukuda, Satoru; Nakajima, Teruyuki [Center of Climate System Research, The University of Tokyo, Kashiwa 277-8568 (Japan); Livengood, Timothy A., E-mail: yuka.fujii@utap.phys.s.u-tokyo.ac.jp [NASA/Goddard Space Flight Center Greenbelt, MD 20771 (United States)

    2011-09-10

    As a test bed for future investigations of directly imaged terrestrial exoplanets, we present the recovery of the surface components of the Earth from multi-band diurnal light curves obtained with the EPOXI spacecraft. We find that the presence and longitudinal distribution of ocean, soil, and vegetation are reasonably well reproduced by fitting the observed color variations with a simplified model composed of a priori known albedo spectra of ocean, soil, vegetation, snow, and clouds. The effect of atmosphere, including clouds, on light scattered from surface components is modeled using a radiative transfer code. The required noise levels for future observations of exoplanets are also determined. Our model-dependent approach allows us to infer the presence of major elements of the planet (in the case of the Earth, clouds, and ocean) with observations having signal-to-noise ratio (S/N) {approx}> 10 in most cases and with high confidence if S/N {approx}> 20. In addition, S/N {approx}> 100 enables us to detect the presence of components other than ocean and clouds in a fairly model-independent way. Degradation of our inversion procedure produced by cloud cover is also quantified. While cloud cover significantly dilutes the magnitude of color variations compared with the cloudless case, the pattern of color changes remains. Therefore, the possibility of investigating surface features through light-curve fitting remains even for exoplanets with cloud cover similar to Earth's.

  16. cloud | OpenEI Community

    Open Energy Info (EERE)

    - 13:42 How cleantech-as-a-service will drive renewable energy adoption 2015 adoption Big Data clean tech clean-tech cleantech cleantech forum cleantech-as-a-service cloud...

  17. Parallel Total Energy

    Energy Science and Technology Software Center (OSTI)

    2004-10-21

    This is a total energy electronic structure code using Local Density Approximation (LDA) of the density funtional theory. It uses the plane wave as the wave function basis set. It can sue both the norm conserving pseudopotentials and the ultra soft pseudopotentials. It can relax the atomic positions according to the total energy. It is a parallel code using MP1.

  18. Millimeter Wave Cloud Radar (MMCR) Handbook

    SciTech Connect (OSTI)

    KB Widener; K Johnson

    2005-01-30

    The millimeter cloud radar (MMCR) systems probe the extent and composition of clouds at millimeter wavelengths. The MMCR is a zenith-pointing radar that operates at a frequency of 35 GHz. The main purpose of this radar is to determine cloud boundaries (e.g., cloud bottoms and tops). This radar will also report radar reflectivity (dBZ) of the atmosphere up to 20 km. The radar possesses a doppler capability that will allow the measurement of cloud constituent vertical velocities.

  19. Influence of Arctic cloud thermodynamic phase on surface shortwave flux

    SciTech Connect (OSTI)

    Lubin, D.; Vogelmann, A.

    2010-03-15

    As part of the Indirect and Semi-Direct Aerosol Campaign (ISDAC) an Analytical Spectral Devices (ASD, Inc.) spectroradiometer was deployed at the Barrow NSA site during April and May of 2008, and in April-October of 2009. This instrument recorded one-minute averages of surface downwelling spectral flux in the wavelength interval 350-2200 nm, thus sampling the two major near infrared windows (1.6 and 2.2 microns) in which the flux is influenced by cloud microphysical properties including thermodynamic phase and effective particle size. Aircraft in situ measurements of cloud properties show mostly mixed-phase clouds over Barrow during the campaign, but with wide variability in relative liquid versus ice water content. At fixed total optical depth, this variability in phase composition can yield of order 5-10 Watts per square meter in surface flux variability, with greater cloud attenuation of the surface flux usually occurring under higher ice water content. Thus our data show that changes in cloud phase properties, even within the 'mixed-phase' category, can affect the surface energy balance at the same order of magnitude as greenhouse gas increases. Analysis of this spectral radiometric data provides suggestions for testing new mixed-phase parameterizations in climate models.

  20. Total aerosol effect: forcing or radiative flux perturbation?

    SciTech Connect (OSTI)

    Lohmann, Ulrike; Storelvmo, Trude; Jones, Andy; Rotstayn, Leon; Menon, Surabi; Quaas, Johannes; Ekman, Annica; Koch, Dorothy; Ruedy, Reto

    2009-09-25

    Uncertainties in aerosol forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. Traditionally these feedbacks were not included in estimates of total aerosol forcing. Here we argue that they should be included because these feedbacks act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Thus we propose replacing the direct and indirect aerosol forcing in the IPCC forcing chart with RFP estimates. This implies that it is better to evaluate the total anthropogenic aerosol effect as a whole.

  1. Evaluation of high-level clouds in cloud resolving model simulations...

    Office of Scientific and Technical Information (OSTI)

    Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations: HIGH CLOUD IN CRM Citation Details In-Document Search This content will ...

  2. Summary Max Total Units

    Energy Savers [EERE]

    Summary Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water

  3. Total Space Heat-

    Gasoline and Diesel Fuel Update (EIA)

    Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other...

  4. Dispersion of Cloud Droplet Size Distributions, Cloud Parameterizations and Indirect Aerosol Effects

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Dispersion of Cloud Droplet Size Distributions, Cloud Parameterizations, and Indirect Aerosol Effects P. H. Daum and Y. Liu Brookhaven National Laboratory Upton, New York Introduction Most studies of the effect of aerosols on cloud radiative properties have considered only changes in the cloud droplet concentration, neglecting changes in the spectral shape of the cloud droplet size distribution. However, it has been shown that that the spectral dispersion of the cloud droplet size distribution

  5. ARM - Measurement - Total carbon

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    carbon ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Total carbon The total concentration of carbon in all its organic and non-organic forms. Categories Aerosols, Atmospheric Carbon Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including

  6. Intercomparison of model simulations of mixed-phase clouds observed...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. I: Single layer cloud Citation Details ...

  7. Active probing of cloud thickness and optical depth using wide-angle imaging LIDAR.

    SciTech Connect (OSTI)

    Love, Steven P.; Davis, A. B.; Rohde, C. A.; Tellier, L. L.; Ho, Cheng,

    2002-01-01

    At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60{sup o} full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Section 2 covers the up-to-date evolution of the nighttime WAIL instrument at LANL. Section 3 reports our progress towards daytime capability for WAIL, an important extension to full diurnal cycle monitoring by means of an ultra-narrow magneto-optic atomic line filter. Section 4 describes briefly how the important cloud properties can be inferred from WAIL signals.

  8. Posters Brightness Fields of Broken Clouds V. E. Zuev, G. A. Titov, E. I. Kasyanov, and D. A. Zimin

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    1 Posters Brightness Fields of Broken Clouds V. E. Zuev, G. A. Titov, E. I. Kasyanov, and D. A. Zimin Institute of Atmospheric Optics, Siberian Branch Russian Academy of Sciences Tomsk, Russia Introduction The radiation budget and brightness field of the system "atmosphere-underlying surface" are controlled, to a considerable degree, by the variety of forms and the strong space-time variability of cloud cover. The space and angle structure of the radiation fields of cloudy atmosphere

  9. Sustainable Disposal Cell Covers: Legacy Management Practices,

    Energy Savers [EERE]

    Improvements, and Long-Term Performance | Department of Energy Sustainable Disposal Cell Covers: Legacy Management Practices, Improvements, and Long-Term Performance Sustainable Disposal Cell Covers: Legacy Management Practices, Improvements, and Long-Term Performance Sustainable Disposal Cell Covers: Legacy Management Practices, Improvements, and Long-Term Performance PDF icon Sustainable Disposal Cell Covers: Legacy Management Practices, Improvements, and Long-Term Performance More

  10. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  11. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  12. Wheelspace windage cover plate for turbine

    DOE Patents [OSTI]

    Lathrop, Norman Douglas (Ballston Lake, NY)

    2002-01-01

    Windage cover plates are secured between the wheels and spacer of a turbine rotor to prevent hot flow path gas ingestion into the wheelspace cavities. Each cover plate includes a linear, axially extending body curved circumferentially with a radially outwardly directed wall at one axial end. The wall defines a axially opening recess for receiving a dovetail lug. The cover plate includes an axially extending tongue received in a circumferential groove of the spacer. The cover plate is secured with the tongue in the groove and dovetail lug in the recess. Lap joints between circumferentially adjacent cover plates are provided.

  13. Swimming Pool Covers | Department of Energy

    Energy Savers [EERE]

    Swimming Pool Covers Swimming Pool Covers Covering a pool when it is not in use is the single most effective means of reducing pool heating costs. | Photo courtesy of Aquatherm Industries. Covering a pool when it is not in use is the single most effective means of reducing pool heating costs. | Photo courtesy of Aquatherm Industries. You can significantly reduce swimming pool heating costs by using a pool cover. On the following pages, see the tables showing the costs of heating pools with and

  14. What Makes Clouds Form, Grow and Die?

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Makes Clouds Form, Grow and Die? What Makes Clouds Form, Grow and Die? Simulations Show Raindrops Physics May Affect Climate Model Accuracy February 19, 2015 thunderstorm Brazil shuttle NASA 1984 540 PNNL scientists used real-world observations to simulate how small clouds are likely to stay shallow, while larger clouds grow deeper because they mix with less dry air. Pictured are small and large thunderstorms growing over southern Brazil, taken from the space shuttle. Image: NASA Johnson Space

  15. Radiative Effects of Cloud Inhomogeneity and

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Radiative Effects of Cloud Inhomogeneity and Geometric Association Over the Tropical Western Pacific Warm Pool X. Wu National Center for Atmospheric Research (a) Boulder, Colorado X. -Z. Liang Illinois State Water Survey Champaign, Illinois Introduction The representation of cloud systems and cloud-radiation interaction is considered to be one of major uncertainties in general circulation models (GCMs). This arises because (1) complete observations of cloud systems are impossible and available

  16. Layered Atlantic Smoke Interactions with Clouds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Layered Atlantic Smoke Interactions with Clouds Island in the South Atlantic Ocean. Warm African winds combine with the cool sea surface temperatures and form a large stratocumulus deck, transitioning to year-round trade-wind shallow cumulus at the location of Ascension Island. These clouds and myriad aerosol-cloud-radiation interactions will be studied. Using a portable observatory, or ARM Mobile Facility (AMF), that contains some of most advanced atmospheric research instrumentation for cloud,

  17. 21 briefing pages total

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law

  18. ARM Data for Cloud Parameterization

    SciTech Connect (OSTI)

    Xu, Kuan-Man

    2006-10-02

    The PI's ARM investigation (DE-IA02-02ER633 18) developed a physically-based subgrid-scale saturation representation that fully considers the direct interactions of the parameterized subgrid-scale motions with subgrid-scale cloud microphysical and radiative processes. Major accomplishments under the support of that interagency agreement are summarized in this paper.

  19. Unlocking the Secrets of Clouds

    Office of Energy Efficiency and Renewable Energy (EERE)

    Clouds may look soft, fluffy and harmless to the untrained eye, but to an expert climate model scientist they represent great challenges. Fortunately the Atmospheric Radiation Measurement (ARM) Climate and Research Facility is kicking off a five-month study which should significantly clear the air.

  20. Cover Page of Household Vehicles Energy Use: Latest Data & Trends

    Gasoline and Diesel Fuel Update (EIA)

    Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

  1. ARM - Field Campaign - Cloud Radar IOP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsCloud Radar IOP ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Cloud Radar IOP 1997.04.02 - 1997.04.22 Lead Scientist : Brooks Martner Data Availability MMCR Quick Look Data For data sets, see below. Abstract The objectives of the Cloud Radar IOP are to: support the calibration of the ARM millimeter cloud radar and evaluate the spatial versus temporal variability of cloud properties as seen

  2. Estimation of the cloud transmittance from radiometric measurements at the ground level

    SciTech Connect (OSTI)

    Costa, Dario; Mares, Oana

    2014-11-24

    The extinction of solar radiation due to the clouds is more significant than due to any other atmospheric constituent, but it is always difficult to be modeled because of the random distribution of clouds on the sky. Moreover, the transmittance of a layer of clouds is in a very complex relation with their type and depth. A method for estimating cloud transmittance was proposed in Paulescu et al. (Energ. Convers. Manage, 75 690697, 2014). The approach is based on the hypothesis that the structure of the cloud covering the sun at a time moment does not change significantly in a short time interval (several minutes). Thus, the cloud transmittance can be calculated as the estimated coefficient of a simple linear regression for the computed versus measured solar irradiance in a time interval ?t. The aim of this paper is to optimize the length of the time interval ?t. Radiometric data measured on the Solar Platform of the West University of Timisoara during 2010 at a frequency of 1/15 seconds are used in this study.

  3. Covered Product Category: Displays | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Displays Covered Product Category: Displays The Federal Energy Management Program (FEMP) provides acquisition guidance for displays, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies buy ENERGY STAR qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S. Environmental Protection Agency (EPA)

  4. Covered Product Category: Computers | Department of Energy

    Office of Environmental Management (EM)

    Computers Covered Product Category: Computers The Federal Energy Management Program (FEMP) provides acquisition guidance for computers, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies buy ENERGY STAR-qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S. Environmental Protection Agency (EPA)

  5. Covered Product Category: Displays | Department of Energy

    Office of Environmental Management (EM)

    Displays Covered Product Category: Displays The Federal Energy Management Program (FEMP) provides acquisition guidance for displays, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies buy ENERGY STAR qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S. Environmental Protection Agency (EPA)

  6. Covered Product Category: Commercial Steam Cookers

    Broader source: Energy.gov [DOE]

    The Federal Energy Management Program (FEMP) provides acquisition guidance for commercial steam cookers, which are covered by the ENERGY STAR program.

  7. Covered Product Category: Commercial Refrigerators and Freezers

    Office of Energy Efficiency and Renewable Energy (EERE)

    The Federal Energy Management Program (FEMP) provides acquisition guidance for commercial refrigerators and freezers, which are covered by the ENERGY STAR program.

  8. Covered Product Category: Hot Food Holding Cabinets

    Broader source: Energy.gov [DOE]

    The Federal Energy Management Program (FEMP) provides acquisition guidance for hot food holding cabinets, which are covered by the ENERGY STAR program.

  9. Total Sales of Kerosene

    U.S. Energy Information Administration (EIA) Indexed Site

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  10. Cloud Optical Properties from the Multifilter Shadowband Radiometer (MFRSRCLDOD): An ARM Value-Added Product

    SciTech Connect (OSTI)

    Turner, DD; McFarlane, SA; Riihimaki, L; Shi, Y; Lo, C; Min, Q

    2014-02-01

    The microphysical properties of clouds play an important role in studies of global climate change. Observations from satellites and surface-based systems have been used to infer cloud optical depth and effective radius. Min and Harrison (1996) developed an inversion method to infer the optical depth of liquid water clouds from narrow band spectral Multifilter Rotating Shadowband Radiometer (MFRSR) measurements (Harrison et al. 1994). Their retrieval also uses the total liquid water path (LWP) measured by a microwave radiometer (MWR) to obtain the effective radius of the warm cloud droplets. Their results were compared with Geostationary Operational Environmental Satellite (GOES) retrieved values at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site (Min and Harrison 1996). Min et al. (2003) also validated the retrieved cloud optical properties against in situ observations, showing that the retrieved cloud effective radius agreed well with the in situ forward scattering spectrometer probe observations. The retrieved cloud optical properties from Min et al. (2003) were used also as inputs to an atmospheric shortwave model, and the computed fluxes were compared with surface pyranometer observations.

  11. Quantifying Diurnal Cloud Radiative Effects by Cloud Type in the Tropical Western Pacific

    SciTech Connect (OSTI)

    Burleyson, Casey D.; Long, Charles N.; Comstock, Jennifer M.

    2015-06-01

    Cloud radiative effects are examined using long-term datasets collected at the three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facilities in the tropical western Pacific. We quantify the surface radiation budget, cloud populations, and cloud radiative effects by partitioning the data by cloud type, time of day, and as a function of large scale modes of variability such as El Niño Southern Oscillation (ENSO) phase and wet/dry seasons at Darwin. The novel facet of our analysis is that we break aggregate cloud radiative effects down by cloud type across the diurnal cycle. The Nauru cloud populations and subsequently the surface radiation budget are strongly impacted by ENSO variability whereas the cloud populations over Manus only shift slightly in response to changes in ENSO phase. The Darwin site exhibits large seasonal monsoon related variations. We show that while deeper convective clouds have a strong conditional influence on the radiation reaching the surface, their limited frequency reduces their aggregate radiative impact. The largest source of shortwave cloud radiative effects at all three sites comes from low clouds. We use the observations to demonstrate that potential model biases in the amplitude of the diurnal cycle and mean cloud frequency would lead to larger errors in the surface energy budget compared to biases in the timing of the diurnal cycle of cloud frequency. Our results provide solid benchmarks to evaluate model simulations of cloud radiative effects in the tropics.

  12. Indirect and Semi-Direct Aerosol Campaign: The Impact of Arctic Aerosols on Clouds

    SciTech Connect (OSTI)

    McFarquhar, Greg; Ghan, Steven J.; Verlinde, J.; Korolev, Alexei; Strapp, J. Walter; Schmid, Beat; Tomlinson, Jason M.; Wolde, Mengistu; Brooks, Sarah D.; Cziczo, Daniel J.; Dubey, Manvendra K.; Fan, Jiwen; Flynn, Connor J.; Gultepe, Ismail; Hubbe, John M.; Gilles, Mary K.; Laskin, Alexander; Lawson, Paul; Leaitch, W. R.; Liu, Peter S.; Liu, Xiaohong; Lubin, Dan; Mazzoleni, Claudio; Macdonald, A. M.; Moffet, Ryan C.; Morrison, H.; Ovchinnikov, Mikhail; Shupe, Matthew D.; Turner, David D.; Xie, Shaocheng; Zelenyuk, Alla; Bae, Kenny; Freer, Matthew; Glen, Andrew

    2011-02-01

    A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the arctic boundary layer in the vicinity of Barrow, Alaska was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) sponsored by the Department of Energy Atmospheric Radiation Measurement (ARM) and Atmospheric Science Programs. The primary aim of ISDAC was to examine indirect effects of aerosols on clouds that contain both liquid and ice water. The experiment utilized the ARM permanent observational facilities at the North Slope of Alaska (NSA) in Barrow. These include a cloud radar, a polarized micropulse lidar, and an atmospheric emitted radiance interferometer as well as instruments specially deployed for ISDAC measuring aerosol, ice fog, precipitation and spectral shortwave radiation. The National Research Council of Canada Convair-580 flew 27 sorties during ISDAC, collecting data using an unprecedented 42 cloud and aerosol instruments for more than 100 hours on 12 different days. Data were obtained above, below and within single-layer stratus on 8 April and 26 April 2008. These data enable a process-oriented understanding of how aerosols affect the microphysical and radiative properties of arctic clouds influenced by different surface conditions. Observations acquired on a heavily polluted day, 19 April 2008, are enhancing this understanding. Data acquired in cirrus on transit flights between Fairbanks and Barrow are improving our understanding of the performance of cloud probes in ice. Ultimately the ISDAC data will be used to improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and to determine the extent to which long-term surface-based measurements can provide retrievals of aerosols, clouds, precipitation and radiative heating in the Arctic.

  13. ARM Cloud Aerosol Precipitation Experiment

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Aerosol Precipitation Experiment a NOAA ship in the Pacific Ocean and on a DOE- sponsored plane over land and sea. These researchers will study: (1) water sources, evolution and structure of atmospheric rivers over the Pacific Ocean (2) long range transport of aerosols over the Pacific Ocean between Hawaii and the U.S. West Coast, and how aerosols interact with atmospheric rivers (3) the point where atmospheric rivers make landfall on the U.S. West Coast, especially how clouds form where

  14. Clouds, Aerosols and Precipitation in

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    the Marine Boundary Layer (CAP-MBL) Graciosa Island, Azores, NE Atlantic Ocean Graciosa Island, Azores, NE Atlantic Ocean May 2009-December 2010 May 2009-December 2010 Rob Wood, University of Washington Rob Wood, University of Washington AMF Deployment Team Thanks to Mark Miller: AMF Site Scientist Mark Miller: AMF Site Scientist Kim Nitschke: AMF Site Manager CAP-MBL Proposal Team Importance of Low-Clouds for Climate Imperative that we understand the processes controlling the formation,

  15. Covered Sites/Populations | Department of Energy

    Energy Savers [EERE]

    Covered Sites/Populations Covered Sites/Populations Construction Worker Screening Projects Construction Worker Projects, Former Worker Medical Screening Program (FWP) Production Worker Screening Projects Production Worker Projects, Former Worker Medical Screening Program (FWP) National Supplemental Screening Program National Supplemental Screening Program Beryllium Vendor Screening Program Defunct Beryllium Vendor Screening Program

  16. Determination of Total Solids and Ash in Algal Biomass: Laboratory Analytical Procedure (LAP)

    SciTech Connect (OSTI)

    Van Wychen, S.; Laurens, L. M. L.

    2013-12-01

    This procedure describes the methods used to determine the amount of moisture or total solids present in a freeze-dried algal biomass sample, as well as the ash content. A traditional convection oven drying procedure is covered for total solids content, and a dry oxidation method at 575?C is covered for ash content.

  17. TotalView Training 2015

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    TotalView Training 2015 TotalView Training 2015 NERSC will host an in-depth training course on TotalView, a graphical parallel debugger developed by Rogue Wave Software, on...

  18. Evaluation of Cloud Type Occurrences and Radiative Forcings Simulated by a Cloud Resolving Model Using Observations from Sa...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Cloud Type Occurrences and Radiative Forcings Simulated by a Cloud Resolving Model Using Observations from Satellite and Cloud Radar Y. Luo and S. K. Krueger University of Utah Salt Lake City, Utah Introduction Because of both the various effects clouds exert on the earth-atmospheric system and the cloud feedback, correct representations of clouds in numerical models are critical for accurate climate modeling and weather forecast. Unfortunately, determination of clouds and their radiative

  19. Global and regional modeling of clouds and aerosols in the marine boundary layer during VOCALS: the VOCA intercomparison

    SciTech Connect (OSTI)

    Wyant, M. C.; Bretherton, Christopher S.; Wood, Robert; Carmichael, Gregory; Clarke, A. D.; Fast, Jerome D.; George, R.; Gustafson, William I.; Hannay, Cecile; Lauer, Axel; Lin, Yanluan; Morcrette, J. -J.; Mulcahay, Jane; Saide, Pablo; Spak, S. N.; Yang, Qing

    2015-01-09

    A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the OctoberNovember 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20 S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar to observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosolcloud interactions in the MBL, though quantitative estimation of aerosolcloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.

  20. Global and regional modeling of clouds and aerosols in the marine boundary layer during VOCALS: the VOCA intercomparison

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Wyant, M. C.; Bretherton, Christopher S.; Wood, Robert; Carmichael, Gregory; Clarke, A. D.; Fast, Jerome D.; George, R.; Gustafson, William I.; Hannay, Cecile; Lauer, Axel; et al

    2015-01-09

    A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the October–November 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20° S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar tomore » observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosol–cloud interactions in the MBL, though quantitative estimation of aerosol–cloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.« less

  1. DOE-L.__ PROPOSAL PREPARATION INSTRUCTIONS - COVER LETTER AND

    Office of Environmental Management (EM)

    L. PROPOSAL PREPARATION INSTRUCTIONS - COVER LETTER AND VOLUME I, OFFER AND OTHER DOCUMENTS (a) Instruction - Cover Letter. The cover letter shall include, but not be limited to,...

  2. Graphical methods for evaluating covering arrays

    SciTech Connect (OSTI)

    Kim, Youngil; Jang, Dae -Heung; Anderson-Cook, Christine M.

    2015-08-10

    Covering arrays relax the condition of orthogonal arrays by only requiring that all combination of levels be covered but not requiring that the appearance of all combination of levels be balanced. This allows for a much larger number of factors to be simultaneously considered but at the cost of poorer estimation of the factor effects. To better understand patterns between sets of columns and evaluate the degree of coverage to compare and select between alternative arrays, we suggest several new graphical methods that show some of the patterns of coverage for different designs. These graphical methods for evaluating covering arrays are illustrated with a few examples.

  3. Storm Clouds Take Rain on Rollercoaster Ride

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Clouds Take Rain on Rollercoaster Ride For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight Most of us think that when rain forms in a cloud, it will instantly fall down. That's what climate models typically assume, too. But in reality, rising plumes that form turbulent storm clouds can often carry raindrops, snowflakes, and even hailstones upward before they fall out. This lengthened journey prolongs their growth stage and

  4. A Global Cloud Resolving Model Goals

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Global Cloud Resolving Model Goals Uniform global horizontal grid spacing of 4 km or better ("cloud permitting") 100 or more layers up to at least the stratopause Parameterizations of microphysics, turbulence (including small clouds), and radiation Execution speed of at least several simulated days per wall-clock day on immediately available systems Annual cycle simulation by end of 2011. Motivations Parameterizations are still problematic. There are no spectral gaps. The equations

  5. Exploring Stratocumulus Cloud-Top Entrainment Processes

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Stratocumulus Cloud-Top Entrainment Processes and Parameterizations by Using Doppler For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight Stratocumulus clouds are a particularly important component of the Earth's climate system due to their large impact on the radiation budget. But the parameterization of entrainment in these clouds is yet to be fully resolved, which leads to uncertainties in numerical model forecasts ranging

  6. ARM - Measurement - Cloud particle size distribution

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    size distribution ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle size distribution The number of cloud particles present in any given volume of air within a specified size range, including liquid and ice. Categories Cloud Properties Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each

  7. Midlatitude Continental Convective Clouds Experiment Science Objective

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Midlatitude Continental Convective Clouds Experiment Science Objective Despite improvements in computing power, current weather and climate models are unable to accurately reproduce the formation, growth, and decay of clouds and precipitation associated with storm systems. Not only is this due to a lack of data about precipitation, but also about the 3-dimensional environment of the surrounding clouds, winds, and moisture, and how that affects the transfer of energy between the sun and Earth. To

  8. Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis

    SciTech Connect (OSTI)

    Ekechukwu, A.A.

    2002-05-10

    Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

  9. ARM - Field Campaign - Fall 1997 Cloud IOP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsFall 1997 Cloud IOP ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Fall 1997 Cloud IOP 1997.09.15 - 1997.10.05 Lead Scientist : Gerald Mace For data sets, see below. Summary The primary objective of the Cloud IOP was to generate a multi-platform data set that can be used as validation for cloud property retrieval algorithms that are being implemented on the operational MMCR data stream.

  10. Ground-based Microwave Cloud Tomography

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Microwave Cloud Tomography Experiment, SGP, May 15-June 15, 2009 Lead Scientist Dong Huang, BNL Co-Investigators Al Gasiewski, UC Boulder Maria Cadeddu, ANL Warren Wiscombe, BNL Radiation Processes Working Group March 30, 2009 multiple radiometers All good cloud radiation modelers should close their airplane window shades so as not to be corrupted by the spectacle of real 3D clouds. - Roger Davies In case you forget to do this, you see 3/30/2009 ARM RPWG 2 Effects of cloud structure on radiation

  11. RACORO continental boundary layer cloud investigations. Part...

    Office of Scientific and Technical Information (OSTI)

    RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings Citation Details In-Document Search This content will ...

  12. ARM - Field Campaign - Spring Cloud IOP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    respectively. From these measurements, cloud condensed water content (CVIcwc) and number concentration (CVInum) are determined. CVInum may be artificially enhanced due to breakup...

  13. What Makes Clouds Form, Grow and Die?

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    were born and grew. Those formulas did not always reflect reality. With more advanced computers came the ability to explicitly simulate large-cloud systems instead of approximating...

  14. Mountain-induced Dynamics Influence Cloud Phase

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    2010-2011 via coordinated projects targeting clouds, precipitation, and dynamics in the Park Range of Colorado. The National Science Foundation sponsored aircraft measurements as...

  15. Fragmentation in rotating isothermal protostellar clouds

    SciTech Connect (OSTI)

    Bodenheimer, P.; Tohline, J.E.; Black, D.C.

    1980-01-01

    Results of an extensive set of 3-D hydrodynamic calculations that have been performed to investigate the susceptibility of rotating clouds to gravitational fragmentation are presented. (GHT)

  16. Characterizing Arctic Mixed-phase Cloud Structure

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    have two distinguished cloud base heights (CBHs) that can be defined by both ceilometer (black dots) and micropulse lidar (MPL; pink dots) measurements (Figure 1). For a...

  17. DOE Research and Development Accomplishments Tag Cloud

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Database Tag Cloud This tag cloud is a specific type of weighted list that provides a quick look at the content of the DOE R&D Accomplishments database. It can be easily browsed because terms are in alphabetical order. With this tag cloud, there is a direct correlation between font size and quantity. The more times a term appears in the bibliographic citations, the larger the font size. This tag cloud is also interactive. Clicking on a term will activate a search for that term. Search

  18. CHARACTERIZATION OF CLOUDS IN TITAN'S TROPICAL ATMOSPHERE

    SciTech Connect (OSTI)

    Griffith, Caitlin A.; Penteado, Paulo; Rodriguez, Sebastien; Baines, Kevin H.; Buratti, Bonnie; Sotin, Christophe; Clark, Roger; Nicholson, Phil; Jaumann, Ralf

    2009-09-10

    Images of Titan's clouds, possible over the past 10 years, indicate primarily discrete convective methane clouds near the south and north poles and an immense stratiform cloud, likely composed of ethane, around the north pole. Here we present spectral images from Cassini's Visual Mapping Infrared Spectrometer that reveal the increasing presence of clouds in Titan's tropical atmosphere. Radiative transfer analyses indicate similarities between summer polar and tropical methane clouds. Like their southern counterparts, tropical clouds consist of particles exceeding 5 {mu}m. They display discrete structures suggestive of convective cumuli. They prevail at a specific latitude band between 8 deg. - 20 deg. S, indicative of a circulation origin and the beginning of a circulation turnover. Yet, unlike the high latitude clouds that often reach 45 km altitude, these discrete tropical clouds, so far, remain capped to altitudes below 26 km. Such low convective clouds are consistent with the highly stable atmospheric conditions measured at the Huygens landing site. Their characteristics suggest that Titan's tropical atmosphere has a dry climate unlike the south polar atmosphere, and despite the numerous washes that carve the tropical landscape.

  19. ARM - Field Campaign - Midlatitude Continental Convective Clouds...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Experiment (MC3E) Campaign Links Science Plan MC3E Website Field Campaign Report ARM Data Discovery Browse Data Related Campaigns Midlatitude Continental Convective Clouds...

  20. The LANL Cloud-Aerosol Model

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    that incorporates two unique aspects in its formulation. First, the model employs a nonlinear solver that requires cloud-aerosol parameterizations be smooth or contain reasonable...

  1. An Analysis of Cloud Absorption During

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Analysis of Cloud Absorption During ARESE II (Spring 2000) D. M. Powell, R. T. Marchand, and T. P. Ackerman Pacific Northwest National Laboratory Richland, Washington Introduction...

  2. ARM - Evaluation Product - Cloud Classification VAP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    properties includes cloud boundaries, thickness, phase, type, and precipitation information, and hence provides a useful tool for evaluation of model simulations and...

  3. Dynamics of Molecular Clouds: Observations, Simulations, and...

    Office of Scientific and Technical Information (OSTI)

    Simulations, and NIF Experiments Citation Details In-Document Search Title: Dynamics of Molecular Clouds: Observations, Simulations, and NIF Experiments Authors: Kane, J ...

  4. Swimming Pool Covers | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    of heating pools with and without pool covers in different U.S. cities: Estimating Heat Pump Swimming Pool Heater Costs and Savings Estimating Swimming Pool Gas Heating Costs...

  5. Swimming Pool Covers | Department of Energy

    Office of Environmental Management (EM)

    Gas Heating Costs and Savings Use of a pool cover also can help reduce the size of a solar pool heating system, which can save money. How They Work Swimming pools lose energy in...

  6. The Thermal Collector With Varied Glass Covers

    SciTech Connect (OSTI)

    Luminosu, I.; Pop, N.

    2010-08-04

    The thermal collector with varied glass covers represents an innovation realized in order to build a collector able to reach the desired temperature by collecting the solar radiation from the smallest surface, with the highest efficiency. In the case of the thermal collector with variable cover glasses, the number of the glass plates covering the absorber increases together with the length of the circulation pipe for the working fluid. The thermal collector with varied glass covers compared to the conventional collector better meet user requirements because: for the same temperature increase, has the collecting area smaller; for the same collection area, realizes the highest temperature increase and has the highest efficiency. This works is addressed to researchers in the solar energy and to engineers responsible with air-conditioning systems design or industrial and agricultural products drying.

  7. Covered Product Category: Commercial Refrigerators and Freezers |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Refrigerators and Freezers Covered Product Category: Commercial Refrigerators and Freezers The Federal Energy Management Program (FEMP) provides acquisition guidance for commercial refrigerators and freezers, which are covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies meet these efficiency requirements in all procurement and acquisition actions that are not specifically exempted by law. Meeting Efficiency Requirements for Commercial

  8. Covered Product Category: Refrigerated Beverage Vending Machines |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Refrigerated Beverage Vending Machines Covered Product Category: Refrigerated Beverage Vending Machines The Federal Energy Management Program (FEMP) provides acquisition guidance for refrigerated beverage vending machines, which are covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies meet these efficiency requirements in all procurement and acquisition actions that are not specifically exempted by law. Meeting Efficiency Requirements

  9. Repositioning of Covered Stents: The Grip Technique

    SciTech Connect (OSTI)

    Kirby, John Martin; Guo Xiaofeng; Midia, Mehran

    2011-06-15

    Introduction: Retrieval and repositioning of a stent deployed beyond its intended target region may be a difficult technical challenge. Materials and Methods: A balloon-mounted snare technique, a variant of the coaxial loop snare technique, is described. Results: The technique is described for the repositioning of a covered transjugular intrahepatic portosystemic shunt stent and a covered biliary stent. Conclusion: The balloon-mounted snare technique is a useful technique for retrieval of migrated stents.

  10. 2014 Water Power Peer Review Report Cover | Department of Energy

    Office of Environmental Management (EM)

    Peer Review Report Cover 2014 Water Power Peer Review Report Cover 2014 Water Power Peer Review Report Cover.JPG More Documents & Publications NOWEGIS Report Cover Water Power For...

  11. Electron Cloud Effects in Accelerators

    SciTech Connect (OSTI)

    Furman, M.A.

    2012-11-30

    Abstract We present a brief summary of various aspects of the electron-cloud effect (ECE) in accelerators. For further details, the reader is encouraged to refer to the proceedings of many prior workshops, either dedicated to EC or with significant EC contents, including the entire ?ECLOUD? series [1?22]. In addition, the proceedings of the various flavors of Particle Accelerator Conferences [23] contain a large number of EC-related publications. The ICFA Beam Dynamics Newsletter series [24] contains one dedicated issue, and several occasional articles, on EC. An extensive reference database is the LHC website on EC [25].

  12. Intercomparison of model simulations of mixed-phase clouds observed...

    Office of Scientific and Technical Information (OSTI)

    Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The ...

  13. ARM - Field Campaign - Measuring Clouds at SGP with Stereo Photogramme...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    the form of the Point Cloud of Cloud Points Product (PCCPP). The PCCPP will: provide context on life-cycle stage and cloud position for vertically pointing radars, lidars, and...

  14. U.S. Total Exports

    U.S. Energy Information Administration (EIA) Indexed Site

    Warroad, MN Babb, MT Havre, MT Port of Morgan, MT Sherwood, ND Pittsburg, NH Buffalo, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt Freeport, TX Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Freeport, TX Kenai, AK Port Nikiski, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Sasabe, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA San

  15. U.S. Total Exports

    U.S. Energy Information Administration (EIA) Indexed Site

    Babb, MT Havre, MT Port of Morgan, MT Sherwood, ND Pittsburg, NH Buffalo, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to Egypt Freeport, TX Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Sasabe, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass,

  16. Fine-scale Horizontal Structure of Arctic Mixed-Phase Clouds.

    SciTech Connect (OSTI)

    Rambukkange,M.; Verlinde, J.; Elorante, E.; Luke, E.; Kollias, P.; Shupe, M.

    2006-07-10

    Recent in situ observations in stratiform clouds suggest that mixed phase regimes, here defined as limited cloud volumes containing both liquid and solid water, are constrained to narrow layers (order 100 m) separating all-liquid and fully glaciated volumes (Hallett and Viddaurre, 2005). The Department of Energy Atmospheric Radiation Measurement Program's (DOE-ARM, Ackerman and Stokes, 2003) North Slope of Alaska (NSA) ARM Climate Research Facility (ACRF) recently started collecting routine measurement of radar Doppler velocity power spectra from the Millimeter Cloud Radar (MMCR). Shupe et al. (2004) showed that Doppler spectra has potential to separate the contributions to the total reflectivity of the liquid and solid water in the radar volume, and thus to investigate further Hallett and Viddaurre's findings. The Mixed-Phase Arctic Cloud Experiment (MPACE) was conducted along the NSA to investigate the properties of Arctic mixed phase clouds (Verlinde et al., 2006). We present surface based remote sensing data from MPACE to discuss the fine-scale structure of the mixed-phase clouds observed during this experiment.

  17. Total Eolica | Open Energy Information

    Open Energy Info (EERE)

    Eolica Jump to: navigation, search Name: Total Eolica Place: Spain Product: Project developer References: Total Eolica1 This article is a stub. You can help OpenEI by expanding...

  18. The Sensitivity of Radiative Fluxes to Parameterized Cloud Microphysic...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    these fields include cloud altitude, cloud amount, liquid and ice content, particle size spectra, and radiative fluxes at the surface and the TOA. Comparisons with Atmospheric...

  19. Towards a Characterization of Arctic Mixed-Phase Clouds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    manual classification of cloud phase. Using collocated cloud radar and depolarization lidar observations, it is shown that mixed-phase conditions have a high correlation with a...

  20. An Improved Cloud Classification Algorithm Based on the SGP CART...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    in the world. The millimeter wave cloud radar (MMCR) provides radar reflectivity and mean Doppler velocity profiles for most of clouds in the troposphere. Raman lidar provide not...

  1. ARM - Field Campaign - Azores: Clouds, Aerosol and Precipitation...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Campaigns Azores: Above-Cloud Radiation Budget near Graciosa Island 2010.04.15, Miller, AMF Azores: Extension to Clouds, Aerosol and Precipitation in the Marine Boundary...

  2. Stratus Cloud Structure from MM-Radar Transects and Satellite...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    modeling: * cloud-radiation interaction where correlations can trigger three-dimensional (3D) radiative transfer effects; and * dynamical cloud modeling where the goal is to...

  3. City of Red Cloud, Nebraska (Utility Company) | Open Energy Informatio...

    Open Energy Info (EERE)

    Red Cloud, Nebraska (Utility Company) Jump to: navigation, search Name: Red Cloud Municipal Power Place: Nebraska Phone Number: 402-746-2215 Website: www.redcloudnebraska.comgover...

  4. BALTEX BRIDGE cloud liquid water network project: CLIWA-NET

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    cloud types 432008 ARM-08 (Simplified) Working Strategy of GCSS Large Eddy Simulation (LES) Models Cloud Resolving Models (CRM) Single Column Model Versions of Climate Models...

  5. Direct Numerical Simulations and Robust Predictions of Cloud...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    cloud. Credit: Computational Science and Engineering Laboratory, ETH Zurich, Switzerland Direct Numerical Simulations and Robust Predictions of Cloud Cavitation Collapse PI Name:...

  6. ARM - Field Campaign - Marine ARM GPCI Investigation of Clouds...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsMarine ARM GPCI Investigation of Clouds (MAGIC) Campaign Links MAGIC Website ARM Data Discovery Browse Data Related Campaigns Marine ARM GPCI Investigation of Clouds...

  7. ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    relevant to DOE's goals in understanding the impact of clouds and aerosols on climate change. TWST contributes significantly to the body of data used for extracting cloud...

  8. Can Cloud Computing Address the Scientific Computing Requirements...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    achieve energy efficiency levels comparable to commercial cloud centers. Cloud is a business model and can be applied at DOE supercomputing centers. The progress of the...

  9. Assessing Cloud Spatial and Vertical Distribution with Infrared...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    on assessing cloud spatial and vertical distribution with a recently developed infrared (IR) cloud analyzer, named Nephelo. The experiment took place at the ARM's central facility,...

  10. Summary of workshop session F on electron-cloud instabilities...

    Office of Scientific and Technical Information (OSTI)

    Conference: Summary of workshop session F on electron-cloud instabilities Citation Details In-Document Search Title: Summary of workshop session F on electron-cloud instabilities ...

  11. Graphical methods for evaluating covering arrays

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Kim, Youngil; Jang, Dae -Heung; Anderson-Cook, Christine M.

    2015-08-10

    Covering arrays relax the condition of orthogonal arrays by only requiring that all combination of levels be covered but not requiring that the appearance of all combination of levels be balanced. This allows for a much larger number of factors to be simultaneously considered but at the cost of poorer estimation of the factor effects. To better understand patterns between sets of columns and evaluate the degree of coverage to compare and select between alternative arrays, we suggest several new graphical methods that show some of the patterns of coverage for different designs. As a result, these graphical methods formore » evaluating covering arrays are illustrated with a few examples.« less

  12. Total........................................................

    Gasoline and Diesel Fuel Update (EIA)

    111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351

  13. Total...........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space

  14. Total...........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing

  15. Total............................................................

    Gasoline and Diesel Fuel Update (EIA)

  16. Total.............................................................

    Gasoline and Diesel Fuel Update (EIA)

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer....................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Most-Used Personal Computer Type of PC Desk-top Model.................................. 58.6 7.6 14.2 13.1 9.2 14.6 5.0 14.5 Laptop Model...................................... 16.9 2.0 3.8 3.3 2.1 5.7 1.3 3.5 Hours Turned on Per Week Less than 2 Hours..............................

  17. Total..............................................................

    Gasoline and Diesel Fuel Update (EIA)

    ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269

  18. Total..............................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat

  19. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    20.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer ........... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs

  20. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs

  1. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2

  2. Total...............................................................

    Gasoline and Diesel Fuel Update (EIA)

    47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs

  3. Total.................................................................

    Gasoline and Diesel Fuel Update (EIA)

    49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat

  4. Total.................................................................

    Gasoline and Diesel Fuel Update (EIA)

    14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Space Heating Equipment........ 1.2 N Q Q 0.2 0.4 0.2 0.2 Q Have Main Space Heating Equipment........... 109.8 14.7 7.4 12.4 12.2 18.5 18.3 17.1 9.2 Use Main Space Heating Equipment............. 109.1 14.6 7.3 12.4 12.2 18.2 18.2 17.1 9.1 Have Equipment But Do Not Use It............... 0.8 Q Q Q Q 0.3 Q N Q Main Heating Fuel and Equipment Natural Gas................................................... 58.2 9.2 4.9 7.8 7.1 8.8 8.4 7.8 4.2 Central

  5. Total..................................................................

    Gasoline and Diesel Fuel Update (EIA)

    78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat

  6. Total..................................................................

    Gasoline and Diesel Fuel Update (EIA)

    33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat

  7. Total..................................................................

    Gasoline and Diesel Fuel Update (EIA)

    . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central

  8. Total...................................................................

    Gasoline and Diesel Fuel Update (EIA)

    15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing

  9. Total...................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Air-Conditioning Equipment 1, 2 Central System............................................... 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump.................................. 53.5 37.8 3.4 2.2 7.0 3.1 With a Heat Pump....................................... 12.3 9.7 0.6 0.5 1.0 0.6 Window/Wall Units.......................................... 28.9 14.9 2.3 3.5 6.0 2.1 1 Unit........................................................... 14.5 6.6 1.0 1.6 4.2 1.2 2

  10. Total...................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump.................................. 53.5 37.8 3.4 2.2 7.0 3.1 With a Heat Pump....................................... 12.3 9.7 0.6 0.5 1.0 0.6 Window/Wall Units........................................ 28.9 14.9 2.3 3.5 6.0 2.1 1 Unit........................................................... 14.5 6.6 1.0 1.6 4.2 1.2 2

  11. Total.......................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.6 15.1 5.5 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.9 5.3 1.6 Use a Personal Computer................................ 75.6 13.7 9.8 3.9 Number of Desktop PCs 1.................................................................. 50.3 9.3 6.8 2.5 2.................................................................. 16.2 2.9 1.9 1.0 3 or More..................................................... 9.0 1.5 1.1 0.4 Number of Laptop PCs

  12. Total.......................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer ................... 35.5 8.1 5.6 2.5 Use a Personal Computer................................ 75.6 17.5 12.1 5.4 Number of Desktop PCs 1.................................................................. 50.3 11.9 8.4 3.4 2.................................................................. 16.2 3.5 2.2 1.3 3 or More..................................................... 9.0 2.1 1.5 0.6 Number of Laptop PCs

  13. Total.......................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs

  14. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1

  15. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing

  16. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing

  17. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q N Q Have Main Space Heating Equipment.................. 109.8 40.3 21.4 6.9 12.0 Use Main Space Heating Equipment.................... 109.1 40.1 21.2 6.9 12.0 Have Equipment But Do Not Use It...................... 0.8 Q Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 13.6 5.6 2.3 5.7 Central Warm-Air Furnace................................ 44.7 11.0 4.4

  18. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One

  19. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0

  20. Total........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7

  1. Total...........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat

  2. Total...........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Do Not Have Cooling Equipment............................. 17.8 2.1 1.8 0.3 Have Cooling Equipment.......................................... 93.3 23.5 16.0 7.5 Use Cooling Equipment........................................... 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it.......................... 1.9 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat

  3. Total...........................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Do Not Have Cooling Equipment............................. 17.8 10.3 3.1 7.3 Have Cooling Equipment.......................................... 93.3 13.9 4.5 9.4 Use Cooling Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

  4. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................ 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................ 1.9 0.3 Q 0.5 1.0 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 17.3 32.1 10.5 Without a Heat

  5. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a

  6. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a

  7. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 2.1 1.8 0.3 Have Cooling Equipment............................................ 93.3 23.5 16.0 7.5 Use Cooling Equipment............................................. 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it............................ 1.9 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat

  8. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat

  9. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a

  10. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 10.3 3.1 7.3 Have Cooling Equipment............................................ 93.3 13.9 4.5 9.4 Use Cooling Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat

  11. Total.............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat

  12. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    20.6 25.6 40.7 24.2 Do Not Have Cooling Equipment................................ 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................. 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment.............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................. 1.9 0.3 Q 0.5 1.0 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 6.0 17.3 32.1 10.5

  13. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    0.7 21.7 6.9 12.1 Do Not Have Cooling Equipment................................ 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................. 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment.............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................. 1.9 0.5 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 32.1 17.6 5.2 9.3 Without a

  14. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer .......................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer....................................... 75.6 4.2 5.0 5.3 9.0 Number of Desktop PCs 1......................................................................... 50.3 3.1 3.4 3.4 5.4 2......................................................................... 16.2 0.7 1.1 1.2 2.2 3 or More............................................................ 9.0 0.3

  15. Total..............................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 19.0 22.7 22.3 Do Not Have Cooling Equipment................................ 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................. 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment.............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................. 1.9 0.9 0.3 0.3 0.4 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 25.8 10.9 16.6 12.5

  16. Total.................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment................................. 17.8 4.0 2.4 1.7 Have Cooling Equipment............................................. 93.3 16.5 12.8 3.8 Use Cooling Equipment............................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it............................. 1.9 0.3 Q Q Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat

  17. Total.................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    7.1 7.0 8.0 12.1 Do Not Have Cooling Equipment................................... 17.8 1.8 Q Q 4.9 Have Cooling Equipment................................................ 93.3 5.3 7.0 7.8 7.2 Use Cooling Equipment................................................. 91.4 5.3 7.0 7.7 6.6 Have Equipment But Do Not Use it............................... 1.9 Q N Q 0.6 Air-Conditioning Equipment 1, 2 Central System.............................................................. 65.9 1.1 6.4 6.4 5.4 Without a

  18. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2

  19. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2

  20. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2

  1. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2

  2. Total....................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2

  3. Total.........................................................................................

    Gasoline and Diesel Fuel Update (EIA)

    ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less

  4. Total..........................................................

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    ... 2.0 0.4 Q 0.3 Basements Basement in Single-Family Homes and Apartments in 2-4 Unit Buildings Yes......

  5. Total..........................................................

    Gasoline and Diesel Fuel Update (EIA)

    Housing Units Living Space Characteristics Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Single-Family Units Detached...

  6. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ... Living Space Characteristics Below Poverty Line Eligible for Federal Assistance 1 Million ...

  7. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More 60,000 to 79,999 ...

  8. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Table HC7.4 Space Heating Characteristics by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 80,000 or More Space Heating ...

  9. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ... Below Poverty Line Eligible for Federal Assistance 1 40,000 to 59,999 60,000 to 79,999 ...

  10. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent......1.3 1.2 0.8 0.4 1. Below 150 percent of poverty line or 60 percent of median State ...

  11. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005 Million U.S. Housing Units South Census Region Home Appliances Usage Indicators South Atlantic East ...

  12. Total..........................................................

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Table HC8.10 Home Appliances Usage Indicators by UrbanRural Location, 2005 Million U.S. Housing Units UrbanRural Location (as Self-Reported) Housing Units (millions) Home ...

  13. Total..............................................

    U.S. Energy Information Administration (EIA) Indexed Site

    ... 14.8 10.5 2,263 1,669 1,079 1,312 1,019 507 N N N ConcreteConcrete Block... 5.3 3.4 2,393 1,660 1,614 Q Q Q Q Q Q Composition...

  14. Land Use and Land Cover Change

    SciTech Connect (OSTI)

    Brown, Daniel; Polsky, Colin; Bolstad, Paul V.; Brody, Samuel D.; Hulse, David; Kroh, Roger; Loveland, Thomas; Thomson, Allison M.

    2014-05-01

    A contribution to the 3rd National Climate Assessment report, discussing the following key messages: 1. Choices about land-use and land-cover patterns have affected and will continue to affect how vulnerable or resilient human communities and ecosystems are to the effects of climate change. 2. Land-use and land-cover changes affect local, regional, and global climate processes. 3. Individuals, organizations, and governments have the capacity to make land-use decisions to adapt to the effects of climate change. 4. Choices about land use and land management provide a means of reducing atmospheric greenhouse gas levels.

  15. Covered Product Category: Light Fixtures (Luminaires)

    Broader source: Energy.gov [DOE]

    FEMP provides acquisition guidance and Federal efficiency requirements across a variety of product categories, including luminaires, or light fixtures. The luminaires product category is very broad and covers a wide variety of lighting products. Both ENERGY STAR® and FEMP provide programmatic guidance for various types of luminaires. See table 2 for more information about which types of light fixtures are covered by which program (FEMP or ENERGY STAR). Federal laws and requirements mandate that agencies meet these efficiency requirements in all procurement and acquisition actions that are not specifically exempted by law.

  16. Scanning ARM Cloud Radar Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N; Johnson, K

    2012-06-18

    The scanning ARM cloud radar (SACR) is a polarimetric Doppler radar consisting of three different radar designs based on operating frequency. These are designated as follows: (1) X-band SACR (X-SACR); (2) Ka-band SACR (Ka-SACR); and (3) W-band SACR (W-SACR). There are two SACRs on a single pedestal at each site where SACRs are deployed. The selection of the operating frequencies at each deployed site is predominantly determined by atmospheric attenuation at the site. Because RF attenuation increases with atmospheric water vapor content, ARM's Tropical Western Pacific (TWP) sites use the X-/Ka-band frequency pair. The Southern Great Plains (SGP) and North Slope of Alaska (NSA) sites field the Ka-/W-band frequency pair. One ARM Mobile Facility (AMF1) has a Ka/W-SACR and the other (AMF2) has a X/Ka-SACR.

  17. ARM - Midlatitude Continental Convective Clouds

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

    2012-01-19

    Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

  18. ARM - Midlatitude Continental Convective Clouds

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos

    Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.

  19. Modeling Incoherent Electron Cloud Effects

    SciTech Connect (OSTI)

    Vay, Jean-Luc; Benedetto, E.; Fischer, W.; Franchetti, G.; Ohmi, K.; Schulte, D.; Sonnad, K.; Tomas, R.; Vay, J.-L.; Zimmermann, F.; Rumolo, G.; Pivi, M.; Raubenheimer, T.

    2007-06-18

    Incoherent electron effects could seriously limit the beam lifetime in proton or ion storage rings, such as LHC, SPS, or RHIC, or blow up the vertical emittance of positron beams, e.g., at the B factories or in linear-collider damping rings. Different approaches to modeling these effects each have their own merits and drawbacks. We describe several simulation codes which simplify the descriptions of the beam-electron interaction and of the accelerator structure in various different ways, and present results for a toy model of the SPS. In addition, we present evidence that for positron beams the interplay of incoherent electron-cloud effects and synchrotron radiation can lead to a significant increase in vertical equilibrium emittance. The magnitude of a few incoherent e+e- scattering processes is also estimated. Options for future code development are reviewed.

  20. Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas

    2015-11-05

    In this paper, we evaluate high-level clouds in a cloud resolving model during two convective cases, ARM9707 and KWAJEX. The simulated joint histograms of cloud occurrence and radar reflectivity compare well with cloud radar and satellite observations when using a two-moment microphysics scheme. However, simulations performed with a single moment microphysical scheme exhibit low biases of approximately 20 dB. During convective events, two-moment microphysical overestimate the amount of high-level cloud and one-moment microphysics precipitate too readily and underestimate the amount and height of high-level cloud. For ARM9707, persistent large positive biases in high-level cloud are found, which are not sensitivemore » to changes in ice particle fall velocity and ice nuclei number concentration in the two-moment microphysics. These biases are caused by biases in large-scale forcing and maintained by the periodic lateral boundary conditions. The combined effects include significant biases in high-level cloud amount, radiation, and high sensitivity of cloud amount to nudging time scale in both convective cases. The high sensitivity of high-level cloud amount to the thermodynamic nudging time scale suggests that thermodynamic nudging can be a powerful ‘‘tuning’’ parameter for the simulated cloud and radiation but should be applied with caution. The role of the periodic lateral boundary conditions in reinforcing the biases in cloud and radiation suggests that reducing the uncertainty in the large-scale forcing in high levels is important for similar convective cases and has far reaching implications for simulating high-level clouds in super-parameterized global climate models such as the multiscale modeling framework.« less

  1. Covered Product Category: Refrigerated Beverage Vending Machines

    Broader source: Energy.gov [DOE]

    FEMP provides acquisition guidance and Federal efficiency requirements across a variety of product categories, including refrigerated beverage vending machines, which are covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies meet these efficiency requirements in all procurement and acquisition actions that are not specifically exempted by law.

  2. Covered Product Category: Commercial Gas Water Heaters

    Broader source: Energy.gov [DOE]

    FEMP provides acquisition guidance and Federal efficiency requirements across a variety of product categories, including commercial gas water heaters, which are covered by the ENERGY STAR® program. Federal laws and requirements mandate that agencies meet these efficiency requirements in all procurement and acquisition actions that are not specifically exempted by law.

  3. Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing applications

    SciTech Connect (OSTI)

    Kollias, P.; Luke, E.; Rmillard, J.; Szyrmer, W.

    2011-07-02

    Several aspects of spectral broadening and drizzle growth in shallow liquid clouds remain not well understood. Detailed, cloud-scale observations of microphysics and dynamics are essential to guide and evaluate corresponding modeling efforts. Profiling, millimeter-wavelength (cloud) radars can provide such observations. In particular, the first three moments of the recorded cloud radar Doppler spectra, the radar reflectivity, mean Doppler velocity, and spectrum width, are often used to retrieve cloud microphysical and dynamical properties. Such retrievals are subject to errors introduced by the assumptions made in the inversion process. Here, we introduce two additional morphological parameters of the radar Doppler spectrum, the skewness and kurtosis, in an effort to reduce the retrieval uncertainties. A forward model that emulates observed radar Doppler spectra is constructed and used to investigate these relationships. General, analytical relationships that relate the five radar observables to cloud and drizzle microphysical parameters and cloud turbulence are presented. The relationships are valid for cloud-only, cloud mixed with drizzle, and drizzle-only particles in the radar sampling volume and provide a seamless link between observations and cloud microphysics and dynamics. The sensitivity of the five observed parameters to the radar operational parameters such as signal-to-noise ratio and Doppler spectra velocity resolution are presented. The predicted values of the five observed radar parameters agree well with the output of the forward model. The novel use of the skewness of the radar Doppler spectrum as an early qualitative predictor of drizzle onset in clouds is introduced. It is found that skewness is a parameter very sensitive to early drizzle generation. In addition, the significance of the five parameters of the cloud radar Doppler spectrum for constraining drizzle microphysical retrievals is discussed.

  4. 2009 ECR Report Cover Letter | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    9 ECR Report Cover Letter 2009 ECR Report Cover Letter PDF icon 2009_ECR_Report_Cover_Letter.pdf More Documents & Publications DOE_ECR_Report_2006_(2).pdf DOE ECR Report 2006 2009 ECR FINAL REPORT 2010

  5. Developing and Evaluating Ice Cloud Parameterizations by

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    by remote sensing is that the transfer functions which relate the observables (e. g., radar Doppler spectrum) to cloud properties (e. g., ice water content, or IWC) are not...

  6. HPC CLOUD APPLIED TO LATTICE OPTIMIZATION

    SciTech Connect (OSTI)

    Sun, Changchun; Nishimura, Hiroshi; James, Susan; Song, Kai; Muriki, Krishna; Qin, Yong

    2011-03-18

    As Cloud services gain in popularity for enterprise use, vendors are now turning their focus towards providing cloud services suitable for scientific computing. Recently, Amazon Elastic Compute Cloud (EC2) introduced the new Cluster Compute Instances (CCI), a new instance type specifically designed for High Performance Computing (HPC) applications. At Berkeley Lab, the physicists at the Advanced Light Source (ALS) have been running Lattice Optimization on a local cluster, but the queue wait time and the flexibility to request compute resources when needed are not ideal for rapid development work. To explore alternatives, for the first time we investigate running the Lattice Optimization application on Amazon's new CCI to demonstrate the feasibility and trade-offs of using public cloud services for science.

  7. QER- Comment of Cloud Peak Energy Inc

    Broader source: Energy.gov [DOE]

    Dear Ms Pickett Please find attached comments from Cloud Peak Energy as input to the Department of Energy’s Quadrennial Energy Review. If possible I would appreciate a confirmation that this email has been received Thank you.

  8. Building a private cloud with Open Nebula

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Short Ryan Glenn Ross Nordeen Mentors: Andree Jacobson ISTI-OFF David Kennel DCS-1 LA-UR 10-05197 Why use Virtualized Cloud Computing for HPC? * Support Legacy Software Stacks *...

  9. Evaluating the MMF Using CloudSat

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    its cloud simulations simulations Borrowed from Dave Randall, CSU The big picture The big picture ... ... . . Data ARM A-Train, MISR etc. MMF 4 km runs (CAM) Compare Run CRM...

  10. ARM - Field Campaign - Midlatitude Continental Convective Clouds...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency...

  11. ARM - Field Campaign - Boundary Layer Cloud IOP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsBoundary Layer Cloud IOP Campaign Links Campaign Images ARM Data Discovery Browse Data Comments? We would love to hear from you Send us a note below or call us at...

  12. ARM - Field Campaign - Arctic Cloud Infrared Imaging

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Arctic Cloud Infrared Imaging 2012.07.16 - 2014.07.31 Lead Scientist : Joseph Shaw...

  13. ARM Cloud Retrieval Ensemble Data Set (ACRED)

    SciTech Connect (OSTI)

    Zhao, C; Xie, S; Klein, SA; McCoy, R; Comstock, JM; Delanoë, J; Deng, M; Dunn, M; Hogan, RJ; Jensen, MP; Mace, GG; McFarlane, SA; O’Connor, EJ; Protat, A; Shupe, MD; Turner, D; Wang, Z

    2011-09-12

    This document describes a new Atmospheric Radiation Measurement (ARM) data set, the ARM Cloud Retrieval Ensemble Data Set (ACRED), which is created by assembling nine existing ground-based cloud retrievals of ARM measurements from different cloud retrieval algorithms. The current version of ACRED includes an hourly average of nine ground-based retrievals with vertical resolution of 45 m for 512 layers. The techniques used for the nine cloud retrievals are briefly described in this document. This document also outlines the ACRED data availability, variables, and the nine retrieval products. Technical details about the generation of ACRED, such as the methods used for time average and vertical re-grid, are also provided.

  14. Final Technical Report for "Radiative Heating Associated with Tropical Convective Cloud Systems: Its Importance at Meso and Global Scales"

    SciTech Connect (OSTI)

    Schumacher, Courtney

    2012-12-13

    Heating associated with tropical cloud systems drive the global circulation. The overall research objectives of this project were to i) further quantify and understand the importance of heating in tropical convective cloud systems with innovative observational techniques, and ii) use global models to determine the large-scale circulation response to variability in tropical heating profiles, including anvil and cirrus cloud radiative forcing. The innovative observational techniques used a diversity of radar systems to create a climatology of vertical velocities associated with the full tropical convective cloud spectrum along with a dissection of the of the total heating profile of tropical cloud systems into separate components (i.e., the latent, radiative, and eddy sensible heating). These properties were used to validate storm-scale and global climate models (GCMs) and were further used to force two different types of GCMs (one with and one without interactive physics). While radiative heating was shown to account for about 20% of the total heating and did not have a strong direct response on the global circulation, the indirect response was important via its impact on convection, esp. in how radiative heating impacts the tilt of heating associated with the Madden-Julian Oscillation (MJO), a phenomenon that accounts for most tropical intraseasonal variability. This work shows strong promise in determining the sensitivity of climate models and climate processes to heating variations associated with cloud systems.

  15. Reconstruction of Intensity From Covered Samples

    SciTech Connect (OSTI)

    Barabash, Rozaliya; Watkins, Thomas R; Meisner, Roberta Ann; Burchell, Timothy D; Rosseel, Thomas M

    2015-01-01

    The safe handling of activated samples requires containment and covering the sample to eliminate any potential for contamination. Subsequent characterization of the surface with x-rays ideally necessitates a thin film. While many films appear visually transparent, they are not necessarily x-ray transparent. Each film material has a unique beam attenuation and sometimes have amorphous peaks that can superimpose with those of the sample. To reconstruct the intensity of the underlying activated sample, the x-ray attenuation and signal due to the film needs to be removed from that of the sample. This requires the calculation of unique deconvolution parameters for the film. The development of a reconstruction procedure for a contained/covered sample is described.

  16. Retrievals of Cloud Fraction and Cloud Albedo from Surface-based Shortwave Radiation Measurements: A Comparison of 16 Year Measurements

    SciTech Connect (OSTI)

    Xie, Yu; Liu, Yangang; Long, Charles N.; Min, Qilong

    2014-07-27

    Ground-based radiation measurements have been widely conducted to gain information on clouds and the surface radiation budget; here several different techniques for retrieving cloud fraction (Long2006, Min2008 and XL2013) and cloud albedo (Min2008, Liu2011 and XL2013) from ground-based shortwave broadband and spectral radiation measurements are examined, and sixteen years of retrievals collected at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are compared. The comparison shows overall good agreement between the retrievals of both cloud fraction and cloud albedo, with noted differences however. The Long2006 and Min2008 cloud fractions are greater on average than the XL2013 values. Compared to Min2008 and Liu2011, the XL2013 retrieval of cloud albedo tends to be greater for thin clouds but smaller for thick clouds, with the differences decreasing with increasing cloud fraction. Further analysis reveals that the approaches that retrieve cloud fraction and cloud albedo separately may suffer from mutual contamination of errors in retrieved cloud fraction and cloud albedo. Potential influences of cloud absorption, land-surface albedo, cloud structure, and measurement instruments are explored.

  17. New Facility Will Test Disposal Cell Cover Renovation | Department of

    Office of Environmental Management (EM)

    Energy Services » New Facility Will Test Disposal Cell Cover Renovation New Facility Will Test Disposal Cell Cover Renovation New Facility Will Test Disposal Cell Cover Renovation PDF icon New Facility Will Test Disposal Cell Cover Renovation More Documents & Publications Design and Installation of a Disposal Cell Cover Field Test Sustainable Disposal Cell Covers: Legacy Management Practices, Improvements, and Long-Term Performance Long-Term Surveillance Operations and Maintenance

  18. Atmospheric State, Cloud Microphysics and Radiative Flux

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Mace, Gerald

    2008-01-15

    Atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates for the ARM Southern Great Plains (SGP) site. The data represent a characterization of the physical state of the atmospheric column compiled on a five-minute temporal and 90m vertical grid. Sources for this information include raw measurements, cloud property and radiative retrievals, retrievals and derived variables from other third-party sources, and radiative calculations using the derived quantities.

  19. Electron-Cloud Build-Up: Summary

    SciTech Connect (OSTI)

    Furman, M.A.

    2007-06-18

    I present a summary of topics relevant to the electron-cloud build-up and dissipation that were presented at the International Workshop on Electron-Cloud Effects 'ECLOUD 07' (Daegu, S. Korea, April 9-12, 2007). This summary is not meant to be a comprehensive review of the talks. Rather, I focus on those developments that I found, in my personal opinion, especially interesting. The contributions, all excellent, are posted in http://chep.knu.ac.kr/ecloud07/.

  20. Ignition of Aluminum Particles and Clouds

    SciTech Connect (OSTI)

    Kuhl, A L; Boiko, V M

    2010-04-07

    Here we review experimental data and models of the ignition of aluminum (Al) particles and clouds in explosion fields. The review considers: (i) ignition temperatures measured for single Al particles in torch experiments; (ii) thermal explosion models of the ignition of single Al particles; and (iii) the unsteady ignition Al particles clouds in reflected shock environments. These are used to develop an empirical ignition model appropriate for numerical simulations of Al particle combustion in shock dispersed fuel explosions.

  1. Posters Sensitivity of Cirrus Cloud Radiative

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    7 Posters Sensitivity of Cirrus Cloud Radiative Properties to Ice Crystal Size and Shape in General Circulation Model Simulations D. L. Mitchell Desert Research Institute Reno, Nevada J. E. Kristjánsson Department of Geophysics University of Oslo, Norway M. J. Newman Los Alamos National Laboratory Los Alamos, New Mexico Introduction Recent research (e.g., Mitchell and Arnott 1994) has shown that the radiative properties of cirrus clouds (i.e., optical depth, albedo, emissivity) depend on the

  2. ARM Cloud Properties Working Group: Meeting Logistics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Cloud Properties WG Breakout Session 2008 ARM Science Team Meeting Mar. 10, 2008, Norfolk, VA Monday March 10, 2008 1500 to 1515: R. Hogan - A Proposal for ARM support of Cloudnet Activities 1515 to 1530: M. Jensen - Cloud Properties Value- Added Product Development 1530 to 1545: C. Long - Instrument Group Report 1545 to 1600: S. Matrosov - WSR-88D data for ARM science 1600 to 1615: Y. Zhao - A BimodalParticle Distribution Assumption in Cirrus: Comparison of retrieval results with in situ

  3. Atmospheric State, Cloud Microphysics and Radiative Flux

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Mace, Gerald

    Atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates for the ARM Southern Great Plains (SGP) site. The data represent a characterization of the physical state of the atmospheric column compiled on a five-minute temporal and 90m vertical grid. Sources for this information include raw measurements, cloud property and radiative retrievals, retrievals and derived variables from other third-party sources, and radiative calculations using the derived quantities.

  4. Simulating Arctic mixed-phase clouds: Sensitivity to environmental

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    conditions and cloud microphysics processes Simulating Arctic mixed-phase clouds: Sensitivity to environmental conditions and cloud microphysics processes Sednev, Igor Lawrence Berkeley National Laboratory Menon, Surabi Lawrence Berkeley National Laboratory McFarquhar, Greg University of Illinois Category: Field Campaigns The importance of Arctic mixed-phase clouds on radiation and the Arctic climate are evaluated using the NASA GISS single column model (SCM) and cloud microphysics and radar

  5. ARM - Publications: Science Team Meeting Documents: Day and Night cloud

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    fraction - Cloud Inter-Compariosn IOP results Day and Night cloud fraction - Cloud Inter-Compariosn IOP results Genkova, Iliana University of Illinois-Champaign Long, Chuck Pacific Northwest National Laboratory Turner, David Pacific Northwest National Laboratory We present results from the CIC IOP from March-may, 2003. Day time and night time cloud fraction retrieval algorithms have been presented and intercompared. Amount of low, middle and high cloud have been estimated and compared to

  6. Icy Cirrus Clouds to Be Studied This Spring

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Icy Cirrus Clouds to Be Studied This Spring Mid-latitude cirrus clouds, which are composed solely of ice crystals, will be the focus of an intensive operational period (IOP) in April and May 2004 at the ARM Climate Research Facility (ACRF) SGP site. Researchers will be probing the clouds with aircraft-based instruments to gather detailed information about the clouds' physical characteristics. To make measurements in cirrus clouds, which generally form in the atmosphere at and above 20,000 feet

  7. Climate Effects of Global Land Cover Change

    SciTech Connect (OSTI)

    Gibbard, S G; Caldeira, K; Bala, G; Phillips, T; Wickett, M

    2005-08-24

    There are two competing effects of global land cover change on climate: an albedo effect which leads to heating when changing from grass/croplands to forest, and an evapotranspiration effect which tends to produce cooling. It is not clear which effect would dominate in a global land cover change scenario. We have performed coupled land/ocean/atmosphere simulations of global land cover change using the NCAR CAM3 atmospheric general circulation model. We find that replacement of current vegetation by trees on a global basis would lead to a global annual mean warming of 1.6 C, nearly 75% of the warming produced under a doubled CO{sub 2} concentration, while global replacement by grasslands would result in a cooling of 0.4 C. These results suggest that more research is necessary before forest carbon storage should be deployed as a mitigation strategy for global warming. In particular, high latitude forests probably have a net warming effect on the Earth's climate.

  8. Star formation relations in nearby molecular clouds

    SciTech Connect (OSTI)

    Evans, Neal J. II; Heiderman, Amanda; Vutisalchavakul, Nalin

    2014-02-20

    We test some ideas for star formation relations against data on local molecular clouds. On a cloud by cloud basis, the relation between the surface density of star formation rate and surface density of gas divided by a free-fall time, calculated from the mean cloud density, shows no significant correlation. If a crossing time is substituted for the free-fall time, there is even less correlation. Within a cloud, the star formation rate volume and surface densities increase rapidly with the corresponding gas densities, faster than predicted by models using the free-fall time defined from the local density. A model in which the star formation rate depends linearly on the mass of gas above a visual extinction of 8 mag describes the data on these clouds, with very low dispersion. The data on regions of very massive star formation, with improved star formation rates based on free-free emission from ionized gas, also agree with this linear relation.

  9. First-ever Hydropower Market Report Covers Hydropower Generation...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    First-ever Hydropower Market Report Covers Hydropower Generation Infrastructure First-ever Hydropower Market Report Covers Hydropower Generation Infrastructure May 28, 2015 -...

  10. EISA Federal Covered Facility Management and Benchmarking Data...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Independence & Security Act, Section 432 EISA Federal Covered Facility Management and Benchmarking Data EISA Federal Covered Facility Management and Benchmarking Data The ...

  11. Microsoft Word - FOA cover sheet.doc | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Microsoft Word - FOA cover sheet.doc Recovery Act, Office of the Biomass Program,Funding Opportunity Announcements Special Notice Microsoft Word - FOA cover sheet.doc...

  12. Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

    SciTech Connect (OSTI)

    Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.; Turner, David D.; Comstock, Jennifer M.

    2015-11-01

    A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.

  13. Month-Long 2D Cloud-Resolving Model Simulation and Resultant Statistics of Cloud Systems Over the ARM SGP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Month-Long 2D Cloud-Resolving Model Simulation and Resultant Statistics of Cloud Systems Over the ARM SGP X. Wu Department of Geological and Atmospheric Sciences Iowa State University Ames, Iowa X.-Z. Liang Illinois State Water Survey University of Illinois Urbana-Champaign, Illinois Introduction The cloud-resolving model (CRM) has recently emerged as a useful tool to develop improved representations of convections, clouds, and cloud-radiation interactions in general circulation models (GCMs).

  14. Optimization of the Area 5 Radioactive Waste Management Site Closure Cover

    SciTech Connect (OSTI)

    Shott, Greg; Yucel, Vefa

    2009-04-01

    The U.S. Department of Energy Manual DOE M 435.1-1, Radioactive Waste Management Manual, requires that performance assessments demonstrate that releases of radionuclides to the environment are as low as reasonably achievable (ALARA). Quantitative cost benefit analysis of radiation protection options is one component of the ALARA process. This report summarizes a quantitative cost benefit analysis of closure cover thickness for the Area 5 Radioactive Waste Management Site (RWMS) on the Nevada Test Site. The optimum cover thickness that maintains doses ALARA is shown to be the thickness with the minimum total closure cost. Total closure cost is the sum of cover construction cost and the health detriment cost. Cover construction cost is estimated based on detailed cost estimates for closure of the 92-acre Low-Level Waste Management Unit (LLWMU). The health detriment cost is calculated as the product of collective dose and a constant monetary value of health detriment in units of dollars per unit collective dose. Collective dose is the sum of all individual doses in an exposed population and has units of person-sievert (Sv). Five discrete cover thickness options ranging from 2.5 to 4.5 meters (m) (8.2 to 15 feet [ft]) are evaluated. The optimization was subject to the constraints that (1) options must meet all applicable regulatory requirements and that (2) individual doses be a small fraction of background radiation dose. Total closure cost is found to be a monotonically increasing function of cover thickness for the 92-ac LLWMU, the Northern Expansion Area, and the entire Area 5 RWMS. The cover construction cost is orders of magnitude greater than the health detriment cost. Two-thousand Latin hypercube sampling realizations of the relationship between total closure cost and cover thickness are generated. In every realization, the optimum cover thickness is 2.5 m (8.2 ft) for the 92-ac Low-Level Waste Management Unit, the Northern Expansion Area, and the entire Area 5 RWMS. The conclusions of the optimization are found to be insensitive to all input parameters, the monetary value of the health detriment over a range of values from $200,000 to $15,000,000 per person-Sv, and the period of integration of collective dose. A 2.5 m (8.2 ft) closure cover at the Area 5 RWMS can meet all applicable regulatory requirements and maintain radionuclide releases ALARA.

  15. Characteristics RSE Column Factor: Total

    U.S. Energy Information Administration (EIA) Indexed Site

    and 1994 Vehicle Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...

  16. Posters Climate Zones for Maritime Clouds A. B. White and D....

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    power (15-m resolution) is analyzed to detect cloud layers using a specified cloud detection limit. In addition to measurements of cloud base, the ceilometer can also provide...

  17. ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scm_forcing)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Xie, Shaocheng; McCoy, Renata; Zhang, Yunyan

    2012-10-25

    The constrained variational objective analysis approach described in Zhang and Lin [1997] and Zhang et al. [2001]was used to derive the large-scale single-column/cloud resolving model forcing and evaluation data set from the observational data collected during Midlatitude Continental Convective Clouds Experiment (MC3E), which was conducted during April to June 2011 near the ARM Southern Great Plains (SGP) site. The analysis data cover the period from 00Z 22 April - 21Z 6 June 2011. The forcing data represent an average over the 3 different analysis domains centered at central facility with a diameter of 300 km (standard SGP forcing domain size), 150 km and 75 km, as shown in Figure 1. This is to support modeling studies on various-scale convective systems.

  18. Product Categories Covered by Efficiency Programs | Department of Energy

    Energy Savers [EERE]

    Categories Covered by Efficiency Programs Product Categories Covered by Efficiency Programs Document shows a list of energy- and water-efficient product categories covered by various efficiency programs, including ENERGY STAR, Federal Energy Management Program (FEMP), Electronic Product Environmental Assessment Tool (EPEAT), FEMP Low Standby Power, and WaterSense. File Download FEMP's list of product categories covered by federal efficiency programs

  19. Magellan: experiences from a Science Cloud

    SciTech Connect (OSTI)

    Ramakrishnan, Lavanya; Zbiegel, Piotr; Campbell, Scott; Bradshaw, Rick; Canon, Richard; Coghlan, Susan; Sakrejda, Iwona; Desai, Narayan; Declerck, Tina; Liu, Anping

    2011-02-02

    Cloud resources promise to be an avenue to address new categories of scientific applications including data-intensive science applications, on-demand/surge computing, and applications that require customized software environments. However, there is a limited understanding on how to operate and use clouds for scientific applications. Magellan, a project funded through the Department of Energy?s (DOE) Advanced Scientific Computing Research (ASCR) program, is investigating the use of cloud computing for science at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing Facility (NERSC). In this paper, we detail the experiences to date at both sites and identify the gaps and open challenges from both a resource provider as well as application perspective.

  20. Cloud-based Architecture Capabilities Summary Report

    SciTech Connect (OSTI)

    Vang, Leng; Prescott, Steven R; Smith, Curtis

    2014-09-01

    In collaborating scientific research arena it is important to have an environment where analysts have access to a shared of information documents, software tools and be able to accurately maintain and track historical changes in models. A new cloud-based environment would be accessible remotely from anywhere regardless of computing platforms given that the platform has available of Internet access and proper browser capabilities. Information stored at this environment would be restricted based on user assigned credentials. This report reviews development of a Cloud-based Architecture Capabilities (CAC) as a web portal for PRA tools.

  1. ARM - Field Campaign - Thin Cloud Rotating Shadowband Radiometer

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Thin Cloud Rotating Shadowband Radiometer 2008.01.08 - 2008.07.18 Lead Scientist : Mary Jane Bartholomew For data sets, see below. Abstract The Thin-Cloud Rotating Shadowband...

  2. E-Cloud Build-up in Grooved Chambers

    SciTech Connect (OSTI)

    Venturini, Marco

    2007-05-01

    We simulate electron cloud build-up in a grooved vacuumchamber including the effect of space charge from the electrons. Weidentify conditions for e-cloud suppression and make contact withprevious estimates of an effective secondary electron yield for groovedsurfaces.

  3. Treatments of Inhomogeneous Clouds in a GCM Column Radiation...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    of fractal stratocumulus clouds. J. Atmos. Sci., 51, 2434 -2455. Chou, M.-D., M. J. Suarez, C.-H. Ho, M. M.-H. Yan, and K.-T. Lee, 1998: Parameterizations for cloud...

  4. Simulation of E-Cloud Driven Instability And Its Attenuation...

    Office of Scientific and Technical Information (OSTI)

    of E-Cloud Driven Instability And Its Attenuation Using a Feedback System in the CERN SPS Citation Details In-Document Search Title: Simulation of E-Cloud Driven Instability...

  5. Observations of the Madden Julian Oscillation for Cloud Modeling...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Dyn.) Manus MJO signal in downwelling SW cloud radiative forcing GRL paper submitted Y. Wang, C. Long, and J. Mather Manus MJO signal in retrieved cloud amount GRL paper...

  6. Radiosonde observations at Pt. Reyes and cloud properties retrieved...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Radiosonde observations at Pt. Reyes and cloud properties retrieved from GOES-WEST Inoue, Toshiro MRIJMA Category: Field Campaigns Low-level cloud formed off the west coast of...

  7. ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Marine ARM GPCI Investigations of Clouds (MAGIC): Cloud Properties from Zenith...

  8. ARM - Field Campaign - DC-8 Cloud Radar Campaign

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsDC-8 Cloud Radar Campaign Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : DC-8 Cloud Radar Campaign...

  9. ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Climate Campaign Links BAECC Website ARM Data Discovery Browse Data Related Campaigns Biogenic Aerosols - Effects on Clouds and Climate: Cloud OD Sensor TWST 2014.06.15, Scott, AMF...

  10. A TWP-ICE High-Level Cloud Case Study

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    A TWP-ICE High-Level Cloud Case Study Mace, Gerald University of Utah Category: Field Campaigns The Tropical Warm Pool International Cloud Experiment (TWP ICE) was conducted near...

  11. Microsoft Word - Group3Cloud Properties(RS).docx

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... for (a) column clouds and (b) circle clouds. 2.0 References Clothiaux, EE, TP Ackerman, GG Mace, KP Moran, RT Marchand, MA Miller, and BE Martner. 2000. "Objective determination ...

  12. Intercomparison of model simulations of mixed-phase clouds observed during

    Office of Scientific and Technical Information (OSTI)

    the ARM Mixed-Phase Arctic Cloud Experiment. I: Single layer cloud (Journal Article) | SciTech Connect Journal Article: Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. I: Single layer cloud Citation Details In-Document Search Title: Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. I: Single layer cloud Results are presented from an intercomparison of

  13. The dependence of cloud particle size and precipitation probability...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    effect Hongfei Shao and Guosheng Liu Meteorology Department, Florida State University INTRODUCTION INTRODUCTION Anthropogenic aerosols enhance cloud reflectance of solar...

  14. ARM - Publications: Science Team Meeting Documents: Cloud Radiative Forcing

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    at the ARM Climate Research Facility: Part 2. The Vertical Redistribution of Radiant Energy by Clouds. Cloud Radiative Forcing at the ARM Climate Research Facility: Part 2. The Vertical Redistribution of Radiant Energy by Clouds. Mace, Gerald University of Utah Benson, Sally University of Utah Kato, Seiji Hampton University/NASA Langley Research Center Documentation with data of the effects of clouds on the radiant energy balance of the surface and atmosphere represent a critical shortcoming

  15. ARSCL Cloud Statistics - A Value-Added Product

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ARSCL Cloud Statistics - A Value-Added Product Y. Shi Pacific Northwest National Laboratory Richland, Washington M. A. Miller Brookhaven National Laboratory Upton, New York Introduction The active remote sensing of cloud layers (ARSCLs) value-added product (VAP) combines data from active remote sensors to produce an objective determination of cloud location, radar reflectivity, vertical velocity, and Doppler spectral width. Information about the liquid water path (LWP) in these clouds and the

  16. Direct Numerical Simulations and Robust Predictions of Cloud Cavitation

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Collapse | Argonne Leadership Computing Facility Initiation of cloud cavitation collapse for 50,000 bubbles Initiation of cloud cavitation collapse for 50,000 bubbles. Jonas Sukys, ETH Zurich Direct Numerical Simulations and Robust Predictions of Cloud Cavitation Collapse PI Name: Petros Koumoutsakos PI Email: petros@ethz.ch Institution: ETH Zurich Allocation Program: INCITE Allocation Hours at ALCF: 72 Million Year: 2016 Research Domain: Engineering Cloud cavitation collapse-the evolution

  17. ARM - PI Product - Tropical Cloud Properties and Radiative Heating Profiles

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ProductsTropical Cloud Properties and Radiative Heating Profiles ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Tropical Cloud Properties and Radiative Heating Profiles We have generated a suite of products that includes merged soundings, cloud microphysics, and radiative fluxes and heating profiles. The cloud microphysics is strongly based on the ARM Microbase value added product (Miller et al.,

  18. Limiting Factors for Convective Cloud Top Height in the Tropics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Limiting Factors for Convective Cloud Top Height in the Tropics M. P. Jensen and A. D. Del Genio National Aeronautics and Space Administration Goddard Institute for Space Studies Columbia University New York, New York Introduction Populations of tropical convective clouds are mainly comprised of three types: shallow trade cumulus, mid-level cumulus congestus and deep convective clouds (Johnson et al. 1999). Each of these cloud types has different impacts on the local radiation and water budgets.

  19. LES Modeling of High Resolution Satellite Cloud Spatial and Thermal

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Structure at ARM-SGP site: How well can we Simulate Clouds from Space? LES Modeling of High Resolution Satellite Cloud Spatial and Thermal Structure at ARM-SGP site: How well can we Simulate Clouds from Space? Dubey, Manvendra DOE/Los Alamos National Laboratory Chylek, Petr DOE/Los Alamos National Laboratory Reisner, Jon Los Alamos National Laboratory Porch, William Los Alamos National Laboratory Category: Cloud Properties We report high fidelity observations of the spatial and thermal

  20. To the Cloud! Apidae Helps Modelers Turn Information into Knowledge |

    Energy Savers [EERE]

    Department of Energy To the Cloud! Apidae Helps Modelers Turn Information into Knowledge To the Cloud! Apidae Helps Modelers Turn Information into Knowledge October 26, 2015 - 2:41pm Addthis Apidae is a collection of cloud-based simulation and data analysis tools that help modelers better understand their models. Image credit: BUILDlab. Apidae is a collection of cloud-based simulation and data analysis tools that help modelers better understand their models. Image credit: BUILDlab. Apidae

  1. Total Number of Operable Refineries

    U.S. Energy Information Administration (EIA) Indexed Site

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  2. Total Energy Outcome City Pilot

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Total Energy Outcome City Pilot 2014 Building Technologies Office Peer Review Targeted Energy Outcomes A New City Energy Policy for Buildings Ken Baker - kbaker@neea.org Northwest Energy Efficiency Alliance Project Summary Timeline: Key Partners: Start date: 09/01/2012 Planned end date: 08/31/2015 Key Milestones 1. Produce outcome based marketing collateral; 04/03/14 New Buildings Institute Two to three NW cities 2. Quantify and define participating city actions; 04/03/14 3. Quantify ongoing

  3. Total Estimated Contract Cost: Performance Period Total Fee Paid

    Office of Environmental Management (EM)

    Total Fee Paid FY2008 $134,832 FY2009 $142,578 FY2010 $299,878 FY2011 $169,878 Cumulative Fee Paid $747,166 Contract Period: September 2007 - October 2012 $31,885,815 C/P/E Environmental Services, LLC DE-AM09-05SR22405/DE-AT30-07CC60011/SL14 Contractor: Contract Number: Contract Type: Cost Plus Award Fee $357,223 $597,797 $894,699 EM Contractor Fee Site: Stanford Linear Accelerator Center (SLAC) Contract Name: SLAC Environmental Remediation December 2012 $1,516,646 Fee Available $208,620 Fee

  4. Cloud Property Retrieval Products for Graciosa Island, Azores

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Dong, Xiquan

    2014-05-05

    The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.

  5. Cloud Property Retrieval Products for Graciosa Island, Azores

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Dong, Xiquan

    The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.

  6. Argonne's Magellan Cloud Computing Research Project

    ScienceCinema (OSTI)

    Beckman, Pete

    2013-04-19

    Pete Beckman, head of Argonne's Leadership Computing Facility (ALCF), discusses the Department of Energy's new $32-million Magellan project, which designed to test how cloud computing can be used for scientific research. More information: http://www.anl.gov/Media_Center/News/2009/news091014a.html

  7. The Tropical Warm Pool International Cloud Experiment

    SciTech Connect (OSTI)

    May, Peter T.; Mather, James H.; Vaughan, Geraint; Jakob, Christian; McFarquhar, Greg; Bower, Keith; Mace, Gerald G.

    2008-05-01

    One of the most complete data sets describing tropical convection ever collected will result from the upcoming Tropical Warm Pool International Cloud Experiment (TWP-ICE) in the area around Darwin, Northern Australia in January and February 2006. The aims of the experiment, which will be operated in conjunction with the DOE Atmospheric Radiation Measurement (ARM) site in Darwin, will be to examine convective cloud systems from their initial stages through to the decay of the cirrus generated and to measure their impact on the environment. The experiment will include an unprecedented network of ground-based observations (soundings, active and passive remote sensors) combined with low, mid and high altitude aircraft for in-situ and remote sensing measurements. A crucial outcome of the experiment will be a data set suitable to provide the forcing and evaluation data required by cloud resolving and single column models as well as global climate models (GCMs) with the aim to contribute to parameterization development. This data set will provide the necessary link between the observed cloud properties and the models that are attempting to simulate them. The experiment is a large multi-agency experiment including substantial contributions from the United States DOE ARM program, ARM-UAV program, NASA, the Australian Bureau of Meteorology, CSIRO, EU programs and many universities.

  8. The Magellan Final Report on Cloud Computing

    SciTech Connect (OSTI)

    ,; Coghlan, Susan; Yelick, Katherine

    2011-12-21

    The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR), was to investigate the potential role of cloud computing in addressing the computing needs for the DOE Office of Science (SC), particularly related to serving the needs of mid- range computing and future data-intensive computing workloads. A set of research questions was formed to probe various aspects of cloud computing from performance, usability, and cost. To address these questions, a distributed testbed infrastructure was deployed at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing Center (NERSC). The testbed was designed to be flexible and capable enough to explore a variety of computing models and hardware design points in order to understand the impact for various scientific applications. During the project, the testbed also served as a valuable resource to application scientists. Applications from a diverse set of projects such as MG-RAST (a metagenomics analysis server), the Joint Genome Institute, the STAR experiment at the Relativistic Heavy Ion Collider, and the Laser Interferometer Gravitational Wave Observatory (LIGO), were used by the Magellan project for benchmarking within the cloud, but the project teams were also able to accomplish important production science utilizing the Magellan cloud resources.

  9. Detecting and Evaluating the Effect of Overlaying Thin Cirrus Cloud on MODIS Retrieved Water-Cloud Droplet Effective Radius

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Detecting and Evaluating the Effect of Overlaying Thin Cirrus Cloud on MODIS Retrieved Water-Cloud Droplet Effective Radius F.-L Chang and Z. Li Earth System Science Interdisciplinary Center University of Maryland College Park, Maryland Z. Li Department of Meteorology University of Maryland College Park, Maryland Introduction Cirrus clouds can largely modify the solar reflected and terrestrial emitted radiances. The ubiquitous presence of cirrus clouds has a global coverage of about 20% to30%

  10. Infrared Cloud Imager Measurements of Cloud Statistics from the 2003 Cloudiness Intercomparison Campaign

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Infrared Cloud Imager Measurements of Cloud Statistics from the 2003 Cloudiness Intercomparison Campaign B. Thurairajah and J. A. Shaw Department of Electrical and Computer Engineering Montana State University Bozeman, Montana Introduction The Cloudiness Inter-Comparison Intensive Operational Period (CIC IOP) occurred at the Atmospheric Radiation Measurement (ARM), Southern Great Plains (SGP) central facility site in Lamont, Oklahoma from mid-February to mid-April 2003 (Kassianov et al. 2004).

  11. HIGH-VELOCITY CLOUDS IN THE GALACTIC ALL SKY SURVEY. I. CATALOG

    SciTech Connect (OSTI)

    Moss, V. A.; Kummerfeld, J. K.; McClure-Griffiths, N. M.; Murphy, T.; Pisano, D. J.; Curran, J. R.

    2013-11-01

    We present a catalog of high-velocity clouds (HVCs) from the Galactic All Sky Survey (GASS) of southern sky neutral hydrogen, which has 57 mK sensitivity and 1 km s{sup 1} velocity resolution and was obtained with the Parkes Telescope. Our catalog has been derived from the stray-radiation-corrected second release of GASS. We describe the data and our method of identifying HVCs and analyze the overall properties of the GASS population. We catalog a total of 1693 HVCs at declinations <0, including 1111 positive velocity HVCs and 582 negative velocity HVCs. Our catalog also includes 295 anomalous velocity clouds (AVCs). The cloud line-widths of our HVC population have a median FWHM of ?19 km s{sup 1}, which is lower than that found in previous surveys. The completeness of our catalog is above 95% based on comparison with the HIPASS catalog of HVCs upon which we improve by an order of magnitude in spectral resolution. We find 758 new HVCs and AVCs with no HIPASS counterpart. The GASS catalog will shed unprecedented light on the distribution and kinematic structure of southern sky HVCs, as well as delve further into the cloud populations that make up the anomalous velocity gas of the Milky Way.

  12. Monitoring the Performance of an Alternative Cover Using Caisson Lysimeters

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    | Department of Energy Monitoring the Performance of an Alternative Cover Using Caisson Lysimeters Monitoring the Performance of an Alternative Cover Using Caisson Lysimeters Proceedings of the Waste Management 2004 Symposium. 2004, University of Arizona, Tucson, Arizona. W.J. Waugh, G.M. Smith , P. Mushovic PDF icon Monitoring the Performance of an Alternative Cover Using Caisson Lysimeters More Documents & Publications Design, Performance, and Sustainability of Engineered Covers for

  13. Performance Evaluation of the Engineered Cover at the Lakeview, Oregon,

    Energy Savers [EERE]

    Uranium Mill Tailings Site | Department of Energy Evaluation of the Engineered Cover at the Lakeview, Oregon, Uranium Mill Tailings Site Performance Evaluation of the Engineered Cover at the Lakeview, Oregon, Uranium Mill Tailings Site Performance Evaluation of the Engineered Cover at the Lakeview, Oregon, Uranium Mill Tailings Site PDF icon Performance Evaluation of the Engineered Cover at the Lakeview, Oregon, Uranium Mill Tailings Site More Documents & Publications Applied Science and

  14. Landfill Cover Revegetation at the Rocky Flats Environmental Technology

    Office of Environmental Management (EM)

    Site | Department of Energy Landfill Cover Revegetation at the Rocky Flats Environmental Technology Site Landfill Cover Revegetation at the Rocky Flats Environmental Technology Site Landfill Cover Revegetation at the Rocky Flats Environmental Technology Site PDF icon Landfill Cover Revegetation at the Rocky Flats Environmental Technology Site More Documents & Publications Revegetation of the Rocky Flats Site Smooth Brome Monitoring at Rocky Flats-2005 Results Monitoring the Performance

  15. Water clouds in Y dwarfs and exoplanets

    SciTech Connect (OSTI)

    Morley, Caroline V.; Fortney, Jonathan J.; Marley, Mark S.; Lupu, Roxana; Greene, Tom; Saumon, Didier; Lodders, Katharina

    2014-05-20

    The formation of clouds affects brown dwarf and planetary atmospheres of nearly all effective temperatures. Iron and silicate condense in L dwarf atmospheres and dissipate at the L/T transition. Minor species such as sulfides and salts condense in mid- to late T dwarfs. For brown dwarfs below T {sub eff} ? 450 K, water condenses in the upper atmosphere to form ice clouds. Currently, over a dozen objects in this temperature range have been discovered, and few previous theoretical studies have addressed the effect of water clouds on brown dwarf or exoplanetary spectra. Here we present a new grid of models that include the effect of water cloud opacity. We find that they become optically thick in objects below T {sub eff} ? 350-375 K. Unlike refractory cloud materials, water-ice particles are significantly nongray absorbers; they predominantly scatter at optical wavelengths through the J band and absorb in the infrared with prominent features, the strongest of which is at 2.8 ?m. H{sub 2}O, NH{sub 3}, CH{sub 4}, and H{sub 2} CIA are dominant opacity sources; less abundant species may also be detectable, including the alkalis, H{sub 2}S, and PH{sub 3}. PH{sub 3}, which has been detected in Jupiter, is expected to have a strong signature in the mid-infrared at 4.3 ?m in Y dwarfs around T {sub eff} = 450 K; if disequilibrium chemistry increases the abundance of PH{sub 3}, it may be detectable over a wider effective temperature range than models predict. We show results incorporating disequilibrium nitrogen and carbon chemistry and predict signatures of low gravity in planetary mass objects. Finally, we make predictions for the observability of Y dwarfs and planets with existing and future instruments, including the James Webb Space Telescope and Gemini Planet Imager.

  16. CloudSat as a Global Radar Calibrator

    SciTech Connect (OSTI)

    Protat, Alain; Bouniol, Dominique; O'Connor, E. J.; Baltink, Henk K.; Verlinde, J.; Widener, Kevin B.

    2011-03-01

    The calibration of the CloudSat spaceborne cloud radar has been thoroughly assessed using very accurate internal link budgets before launch, comparisons with predicted ocean surface backscatter at 94 GHz, direct comparisons with airborne cloud radars, and statistical comparisons with ground-based cloud radars at different locations of the world. It is believed that the calibration of CloudSat is accurate to within 0.5 to 1 dB. In the present paper it is shown that an approach similar to that used for the statistical comparisons with ground-based radars can now be adopted the other way around to calibrate other ground-based or airborne radars against CloudSat and / or detect anomalies in long time series of ground-based radar measurements, provided that the calibration of CloudSat is followed up closely (which is the case). The power of using CloudSat as a Global Radar Calibrator is demonstrated using the Atmospheric Radiation Measurement cloud radar data taken at Barrow, Alaska, the cloud radar data from the Cabauw site, The Netherlands, and airborne Doppler cloud radar measurements taken along the CloudSat track in the Arctic by the RASTA (Radar SysTem Airborne) cloud radar installed in the French ATR-42 aircraft for the first time. It is found that the Barrow radar data in 2008 are calibrated too high by 9.8 dB, while the Cabauw radar data in 2008 are calibrated too low by 8.0 dB. The calibration of the RASTA airborne cloud radar using direct comparisons with CloudSat agrees well with the expected gains and losses due to the change in configuration which required verification of the RASTA calibration.

  17. U.S. Total Stocks

    Gasoline and Diesel Fuel Update (EIA)

    Stock Type: Total Stocks Strategic Petroleum Reserve Non-SPR Refinery Tank Farms and Pipelines Leases Alaskan in Transit Bulk Terminal Pipeline Natural Gas Processing Plant Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Stock Type Area Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History Crude Oil and Petroleum Products 1,968,618 1,991,182 2,001,135 2,009,097 2,021,553 2,014,788 1956-2015 Crude Oil

  18. U.S. Total Exports

    U.S. Energy Information Administration (EIA) Indexed Site

    International Falls, MN Noyes, MN Warroad, MN Babb, MT Havre, MT Port of Del Bonita, MT Port of Morgan, MT Sweetgrass, MT Whitlash, MT Portal, ND Sherwood, ND Pittsburg, NH Champlain, NY Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Highgate Springs, VT North Troy, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Alamo, TX El Paso, TX Galvan Ranch, TX Hidalgo, TX McAllen, TX Penitas, TX LNG Imports from Algeria Cove Point, MD Everett, MA Lake Charles, LA LNG

  19. Microsoft Word - FOA cover sheet.doc | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    cover sheet.doc Microsoft Word - FOA cover sheet.doc PDF icon Microsoft Word - FOA cover sheet.doc More Documents & Publications Recovery Act: Wind Energy Consortia between Institutions of Higher Learning and Industry Microsoft Word - kDE-FOA-0000090.rtf DISCLAIMER:

  20. Covered Product Category: Uninterruptible Power Supplies (for Data Center,

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Computer, and Telecommunication Applications) | Department of Energy Categories » Covered Product Category: Uninterruptible Power Supplies (for Data Center, Computer, and Telecommunication Applications) Covered Product Category: Uninterruptible Power Supplies (for Data Center, Computer, and Telecommunication Applications) The Federal Energy Management Program (FEMP) provides acquisition guidance for uninterruptible power supplies (UPS), a product category covered by the ENERGY STAR program.

  1. Covered Product Category: Uninterruptible Power Supplies (for Data Center,

    Office of Environmental Management (EM)

    Computer, and Telecommunication Applications) | Department of Energy Categories » Covered Product Category: Uninterruptible Power Supplies (for Data Center, Computer, and Telecommunication Applications) Covered Product Category: Uninterruptible Power Supplies (for Data Center, Computer, and Telecommunication Applications) The Federal Energy Management Program (FEMP) provides acquisition guidance for uninterruptible power supplies (UPS), a product category covered by the ENERGY STAR program.

  2. Microsoft Word - FOA cover sheet.doc | Department of Energy

    Office of Environmental Management (EM)

    cover sheet.doc Microsoft Word - FOA cover sheet.doc PDF icon Microsoft Word - FOA cover sheet.doc More Documents & Publications Vehicle Technologies Office Merit Review 2014: Moving North Texas Forward by Addressing Alternative Fuel Barriers Clean Cities Regional Support & Petroleum Displacement Awards Clean Cities 2009 Petroleum Displacement Awards

  3. The influence of clouds and diffuse radiation on ecosystem-atmosphere CO2 and CO18O exhanges

    SciTech Connect (OSTI)

    Still, C.J.; Riley, W.J.; Biraud, S.C.; Noone, D.C.; Buenning, N.H.; Randerson, J.T.; Torn, M.S.; Welker, J.; White, J.W.C.; Vachon, R.; Farquhar, G.D.; Berry, J.A.

    2009-05-01

    This study evaluates the potential impact of clouds on ecosystem CO{sub 2} and CO{sub 2} isotope fluxes ('isofluxes') in two contrasting ecosystems (a broadleaf deciduous forest and a C{sub 4} grassland), in a region for which cloud cover, meteorological, and isotope data are available for driving the isotope-enabled land surface model, ISOLSM. Our model results indicate a large impact of clouds on ecosystem CO{sub 2} fluxes and isofluxes. Despite lower irradiance on partly cloudy and cloudy days, predicted forest canopy photosynthesis was substantially higher than on clear, sunny days, and the highest carbon uptake was achieved on the cloudiest day. This effect was driven by a large increase in light-limited shade leaf photosynthesis following an increase in the diffuse fraction of irradiance. Photosynthetic isofluxes, by contrast, were largest on partly cloudy days, as leaf water isotopic composition was only slightly depleted and photosynthesis was enhanced, as compared to adjacent clear sky days. On the cloudiest day, the forest exhibited intermediate isofluxes: although photosynthesis was highest on this day, leaf-to-atmosphere isofluxes were reduced from a feedback of transpiration on canopy relative humidity and leaf water. Photosynthesis and isofluxes were both reduced in the C{sub 4} grass canopy with increasing cloud cover and diffuse fraction as a result of near-constant light limitation of photosynthesis. These results suggest that some of the unexplained variation in global mean {delta}{sup 18}O of CO{sub 2} may be driven by large-scale changes in clouds and aerosols and their impacts on diffuse radiation, photosynthesis, and relative humidity.

  4. ARM - Evaluation Product - ARM Cloud Retrieval Ensemble Data

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ProductsARM Cloud Retrieval Ensemble Data ARM Data Discovery Browse Data Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Evaluation Product : ARM Cloud Retrieval Ensemble Data The ARM Cloud Retrieval Ensemble Data (ACRED) set is a multi-year cloud microphysical property ensemble data set created by assembling existing ARM cloud retrievals, which are based

  5. ARM - PI Product - Cloud Property Retrieval Products for Graciosa Island,

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Azores ProductsCloud Property Retrieval Products for Graciosa Island, Azores ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Cloud Property Retrieval Products for Graciosa Island, Azores [ research data - ASR funded ] The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets

  6. pCloud: A Cloud-based Power Market Simulation Environment

    SciTech Connect (OSTI)

    Rudkevich, Aleksandr; Goldis, Evgeniy

    2012-12-02

    This research conducted by the Newton Energy Group, LLC (NEG) is dedicated to the development of pCloud: a Cloud-based Power Market Simulation Environment. pCloud is offering power industry stakeholders the capability to model electricity markets and is organized around the Software as a Service (SaaS) concept -- a software application delivery model in which software is centrally hosted and provided to many users via the internet. During the Phase I of this project NEG developed a prototype design for pCloud as a SaaS-based commercial service offering, system architecture supporting that design, ensured feasibility of key architecture's elements, formed technological partnerships and negotiated commercial agreements with partners, conducted market research and other related activities and secured funding for continue development of pCloud between the end of Phase I and beginning of Phase II, if awarded. Based on the results of Phase I activities, NEG has established that the development of a cloud-based power market simulation environment within the Windows Azure platform is technologically feasible, can be accomplished within the budget and timeframe available through the Phase II SBIR award with additional external funding. NEG believes that pCloud has the potential to become a game-changing technology for the modeling and analysis of electricity markets. This potential is due to the following critical advantages of pCloud over its competition: - Standardized access to advanced and proven power market simulators offered by third parties. - Automated parallelization of simulations and dynamic provisioning of computing resources on the cloud. This combination of automation and scalability dramatically reduces turn-around time while offering the capability to increase the number of analyzed scenarios by a factor of 10, 100 or even 1000. - Access to ready-to-use data and to cloud-based resources leading to a reduction in software, hardware, and IT costs. - Competitive pricing structure, which will make high-volume usage of simulation services affordable. - Availability and affordability of high quality power simulators, which presently only large corporate clients can afford, will level the playing field in developing regional energy policies, determining prudent cost recovery mechanisms and assuring just and reasonable rates to consumers. - Users that presently do not have the resources to internally maintain modeling capabilities will now be able to run simulations. This will invite more players into the industry, ultimately leading to more transparent and liquid power markets.

  7. Operation Greenhouse. Scientific Director's report of atomic-weapon tests at Eniwetok, 1951. Annex 4. 1. Cloud studies. Part 1. Cloud physics. Part 2. Development of the atomic cloud. Part 3. Cloud-tracking photography

    SciTech Connect (OSTI)

    Anderson, C.E.; Gustafson, P.E.; Kellogg, W.W.; McKown, R.E.; McPherson, D.E.

    1985-09-01

    The cloud-physics project was primarily intended to fulfill a requirements for detailed information on the meteorological microstructure of atomic clouds. By means of a tracking and photographic network extending halfway around Eniwetok Atoll, the behavior of the first three clouds of Operation Greenhouse were observed and recorded. The rise of the fourth cloud was observed visually from only one site. The analysis of these observations, combined with information about the local weather conditions, gives a fairly complete picture of the development of each of the clouds. Particular emphasis was placed on the earlier phases of development, and the heights and sizes of the cloud parts have been determined as functions of time. A summary of important features of some previous atomic clouds are included for comparison.

  8. Total Imports of Residual Fuel

    Gasoline and Diesel Fuel Update (EIA)

    Jul-15 Aug-15 Sep-15 Oct-15 Nov-15 Dec-15 View History U.S. Total 4,471 6,479 7,281 4,217 5,941 6,842 1936-2015 PAD District 1 1,854 1,956 4,571 2,206 2,952 3,174 1981-2015 Connecticut 1995-2015 Delaware 204 678 85 1995-2015 Florida 677 351 299 932 836 1995-2015 Georgia 232 138 120 295 1995-2015 Maine 50 1995-2015 Maryland 1995-2015 Massachusetts 1995-2015 New Hampshire 1995-2015 New Jersey 1,328 780 1,575 400 1,131 1,712 1995-2015 New York 7 6 1,475 998 350 322 1995-2015 North Carolina

  9. 2014 Total Electric Industry- Customers

    Gasoline and Diesel Fuel Update (EIA)

    Customers (Data from forms EIA-861- schedules 4A, 4B, 4D, EIA-861S and EIA-861U) State Residential Commercial Industrial Transportation Total New England 6,243,013 862,269 28,017 8 7,133,307 Connecticut 1,459,239 155,372 4,648 4 1,619,263 Maine 706,952 91,541 3,023 0 801,516 Massachusetts 2,720,128 398,717 14,896 3 3,133,744 New Hampshire 606,883 105,840 3,342 0 716,065 Rhode Island 438,879 58,346 1,884 1 499,110 Vermont 310,932 52,453 224 0 363,609 Middle Atlantic 15,806,914 2,247,455 44,397 17

  10. Total Adjusted Sales of Kerosene

    U.S. Energy Information Administration (EIA) Indexed Site

    End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2009 2010 2011 2012 2013 2014 View History U.S. 269,010 305,508 187,656 81,102 79,674 137,928 1984-2014 East Coast (PADD 1) 198,762 237,397 142,189 63,075 61,327 106,995 1984-2014 New England (PADD 1A) 56,661 53,363 38,448 15,983 15,991 27,500 1984-2014 Connecticut 8,800 7,437

  11. Total Imports of Residual Fuel

    U.S. Energy Information Administration (EIA) Indexed Site

    2010 2011 2012 2013 2014 2015 View History U.S. Total 133,646 119,888 93,672 82,173 63,294 68,265 1936-2015 PAD District 1 88,999 79,188 59,594 33,566 30,944 33,789 1981-2015 Connecticut 220 129 1995-2015 Delaware 748 1,704 510 1,604 2,479 1995-2015 Florida 15,713 11,654 10,589 8,331 5,055 7,013 1995-2015 Georgia 5,648 7,668 6,370 4,038 2,037 1,629 1995-2015 Maine 1,304 651 419 75 317 135 1995-2015 Maryland 3,638 1,779 1,238 433 938 539 1995-2015 Massachusetts 123 50 78 542 88 1995-2015 New

  12. Cirrus clouds in a global climate model with a statistical cirrus cloud scheme

    SciTech Connect (OSTI)

    Wang, Minghuai; Penner, Joyce E.

    2010-06-21

    A statistical cirrus cloud scheme that accounts for mesoscale temperature perturbations is implemented in a coupled aerosol and atmospheric circulation model to better represent both subgrid-scale supersaturation and cloud formation. This new scheme treats the effects of aerosol on cloud formation and ice freezing in an improved manner, and both homogeneous freezing and heterogeneous freezing are included. The scheme is able to better simulate the observed probability distribution of relative humidity compared to the scheme that was implemented in an older version of the model. Heterogeneous ice nuclei (IN) are shown to decrease the frequency of occurrence of supersaturation, and improve the comparison with observations at 192 hPa. Homogeneous freezing alone can not reproduce observed ice crystal number concentrations at low temperatures (<205 K), but the addition of heterogeneous IN improves the comparison somewhat. Increases in heterogeneous IN affect both high level cirrus clouds and low level liquid clouds. Increases in cirrus clouds lead to a more cloudy and moist lower troposphere with less precipitation, effects which we associate with the decreased convective activity. The change in the net cloud forcing is not very sensitive to the change in ice crystal concentrations, but the change in the net radiative flux at the top of the atmosphere is still large because of changes in water vapor. Changes in the magnitude of the assumed mesoscale temperature perturbations by 25% alter the ice crystal number concentrations and the net radiative fluxes by an amount that is comparable to that from a factor of 10 change in the heterogeneous IN number concentrations. Further improvements on the representation of mesoscale temperature perturbations, heterogeneous IN and the competition between homogeneous freezing and heterogeneous freezing are needed.

  13. ARM - Midlatitude Continental Convective Clouds Microwave Radiometer Profiler (jensen-mwr)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Jensen, Mike

    2012-02-01

    A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

  14. ARM - Midlatitude Continental Convective Clouds - Ultra High Sensitivity Aerosol Spectrometer(tomlinson-uhsas)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Tomlinson, Jason; Jensen, Mike

    2012-02-28

    Ultra High Sensitivity Aerosol Spectrometer (UHSASA) A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

  15. Using Unmanned Aerial Vehicles to Assess Vegetative Cover in Sagebrush Steppe Ecosytstems

    SciTech Connect (OSTI)

    Robert P. Breckenridge

    2005-09-01

    The Idaho National Laboratory (INL), in conjunction with the University of Idaho, is evaluating novel approaches for using unmanned aerial vehicles (UAVs) as a quicker and safer method for monitoring biotic resources. Evaluating vegetative cover is an important factor in understanding the sustainability of many ecosystems. In assessing vegetative cover, methods that improve accuracy and cost efficiency could revolutionize how biotic resources are monitored on western federal lands. Sagebrush steppe ecosystems provide important habitat for a variety of species, some of which are important indicator species (e.g., sage grouse). Improved methods are needed to support monitoring these habitats because there are not enough resource specialists or funds available for comprehensive ground evaluation of these ecosystems. In this project, two types of UAV platforms (fixed wing and helicopter) were used to collect still-frame imagery to assess cover in sagebrush steppe ecosystems. This paper discusses the process for collecting and analyzing imagery from the UAVs to (1) estimate total percent cover, (2) estimate percent cover for six different types of vegetation, and (3) locate sage grouse based on representative decoys. The field plots were located on the INL site west of Idaho Falls, Idaho, in areas with varying amounts and types of vegetative cover. A software program called SamplePoint developed by the U.S. Department of Agriculture, Agricultural Research Service (USDA-ARS) was used to evaluate the imagery for percent cover for the six vegetation types (bare ground, litter, shrubs, dead shrubs, grasses, and forbs). Results were compared against standard field measurements to assess accuracy.

  16. Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

    SciTech Connect (OSTI)

    Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; Somerville, Richard C.; Zhang, Kai; Liu, Xiaohong; Li, J-L F.

    2014-11-06

    In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice number is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 ?m for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.

  17. Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; Somerville, Richard C.; Zhang, Kai; Liu, Xiaohong; Li, J-L F.

    2014-11-06

    In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice numbermore » is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.« less

  18. Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

    SciTech Connect (OSTI)

    Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; Somerville, Richard C.; Zhang, Kai; Liu, Xiaohong; Li, J-L F.

    2014-12-01

    In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice number is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 ?m for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.

  19. Tropical Cloud Properties and Radiative Heating Profiles

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Mather, James

    2008-01-15

    We have generated a suite of products that includes merged soundings, cloud microphysics, and radiative fluxes and heating profiles. The cloud microphysics is strongly based on the ARM Microbase value added product (Miller et al., 2003). We have made a few changes to the microbase parameterizations to address issues we observed in our initial analysis of the tropical data. The merged sounding product is not directly related to the product developed by ARM but is similar in that it uses the microwave radiometer to scale the radiosonde column water vapor. The radiative fluxes also differ from the ARM BBHRP (Broadband Heating Rate Profile) product in terms of the radiative transfer model and the sampling interval.

  20. Experiment to Characterize Tropical Cloud Systems

    SciTech Connect (OSTI)

    May, Peter T.; Mather, Jim H.; Jakob, Christian

    2005-08-02

    A major experiment to study tropical convective cloud systems and their impacts will take place around Darwin, Northern Australia in early 2006. The Tropical Warm Pool International Cloud Experiment (TWP-ICE) is a collaboration including the DOE ARM (Atmospheric Radiation Measurement) and ARM-UAV programs, NASA centers, the Australian Bureau of Meteorology, CSIRO, and universities in the USA, Australia, Japan, the UK, and Canada. TWP-ICE will be preceded in November/December 2004 by a collaborating European aircraft campaign involving the EU SCOUT-O3 and UK NERC ACTIVE projects. Detailed atmospheric measurements will be made in the Darwin area through the whole Austral summer, giving unprecedented coverage through the pre-monsoon and monsoon periods.

  1. Tropical Cloud Properties and Radiative Heating Profiles

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Mather, James

    We have generated a suite of products that includes merged soundings, cloud microphysics, and radiative fluxes and heating profiles. The cloud microphysics is strongly based on the ARM Microbase value added product (Miller et al., 2003). We have made a few changes to the microbase parameterizations to address issues we observed in our initial analysis of the tropical data. The merged sounding product is not directly related to the product developed by ARM but is similar in that it uses the microwave radiometer to scale the radiosonde column water vapor. The radiative fluxes also differ from the ARM BBHRP (Broadband Heating Rate Profile) product in terms of the radiative transfer model and the sampling interval.

  2. MAGIC: Marine ARM GPCI Investigation of Clouds

    SciTech Connect (OSTI)

    Lewis, ER; Wiscombe, WJ; Albrecht, BA; Bland, GL; Flagg, CN; Klein, SA; Kollias, P; Mace, G; Reynolds, RM; Schwartz, SE; Siebesma, AP; Teixeira, J; Wood, R; Zhang, M

    2012-10-03

    The second Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF2) will be deployed aboard the Horizon Lines cargo container ship merchant vessel (M/V) Spirit for MAGIC, the Marine ARM GPCI1 Investigation of Clouds. The Spirit will traverse the route between Los Angeles, California, and Honolulu, Hawaii, from October 2012 through September 2013 (except for a few months in the middle of this time period when the ship will be in dry dock). During this field campaign, AMF2 will observe and characterize the properties of clouds and precipitation, aerosols, and atmospheric radiation; standard meteorological and oceanographic variables; and atmospheric structure. There will also be two intensive observational periods (IOPs), one in January 2013 and one in July 2013, during which more detailed measurements of the atmospheric structure will be made.

  3. Scanning Cloud Radar Observations at Azores: Preliminary 3D Cloud Products

    SciTech Connect (OSTI)

    Kollias, P.; Johnson, K.; Jo, I.; Tatarevic, A.; Giangrande, S.; Widener, K.; Bharadwaj, N.; Mead, J.

    2010-03-15

    The deployment of the Scanning W-Band ARM Cloud Radar (SWACR) during the AMF campaign at Azores signals the first deployment of an ARM Facility-owned scanning cloud radar and offers a prelude for the type of 3D cloud observations that ARM will have the capability to provide at all the ARM Climate Research Facility sites by the end of 2010. The primary objective of the deployment of Scanning ARM Cloud Radars (SACRs) at the ARM Facility sites is to map continuously (operationally) the 3D structure of clouds and shallow precipitation and to provide 3D microphysical and dynamical retrievals for cloud life cycle and cloud-scale process studies. This is a challenging task, never attempted before, and requires significant research and development efforts in order to understand the radar's capabilities and limitations. At the same time, we need to look beyond the radar meteorology aspects of the challenge and ensure that the hardware and software capabilities of the new systems are utilized for the development of 3D data products that address the scientific needs of the new Atmospheric System Research (ASR) program. The SWACR observations at Azores provide a first look at such observations and the challenges associated with their analysis and interpretation. The set of scan strategies applied during the SWACR deployment and their merit is discussed. The scan strategies were adjusted for the detection of marine stratocumulus and shallow cumulus that were frequently observed at the Azores deployment. Quality control procedures for the radar reflectivity and Doppler products are presented. Finally, preliminary 3D-Active Remote Sensing of Cloud Locations (3D-ARSCL) products on a regular grid will be presented, and the challenges associated with their development discussed. In addition to data from the Azores deployment, limited data from the follow-up deployment of the SWACR at the ARM SGP site will be presented. This effort provides a blueprint for the effort required for the development of 3D cloud products from all new SACRs that the program will deploy at all fixed and mobile sites by the end of 2010.

  4. The Dark Side of Cold Clouds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Dark Side of Cold Clouds For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight In research led by Pacific Northwest National Laboratory (PNNL), scientists sought to understand the atmospheric implications of tiny, highly irregular and chemically complex soot particles. The laboratory investigation, called the Soot Aerosol Aging Study (SAAS), examined the interactions of soot and a mix of other atmospheric particles using a

  5. Pollution Changes Clouds' Ice Crystal Genesis

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Pollution Changes Clouds' Ice Crystal Genesis For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight Suspended high in the atmosphere, plentiful dust particles are fertile turf for growing ice. But, what are the optimal conditions for this crop? Researchers at Pacific Northwest National Laboratory (PNNL) found that miniscule particles of airborne dust, thought to be a perfect landing site for water vapor, are altered by the

  6. Filaments in simulations of molecular cloud formation

    SciTech Connect (OSTI)

    Gmez, Gilberto C.; Vzquez-Semadeni, Enrique

    2014-08-20

    We report on the filaments that develop self-consistently in a new numerical simulation of cloud formation by colliding flows. As in previous studies, the forming cloud begins to undergo gravitational collapse because it rapidly acquires a mass much larger than the average Jeans mass. Thus, the collapse soon becomes nearly pressureless, proceeding along its shortest dimension first. This naturally produces filaments in the cloud and clumps within the filaments. The filaments are not in equilibrium at any time, but instead are long-lived flow features through which the gas flows from the cloud to the clumps. The filaments are long-lived because they accrete from their environment while simultaneously accreting onto the clumps within them; they are essentially the locus where the flow changes from accreting in two dimensions to accreting in one dimension. Moreover, the clumps also exhibit a hierarchical nature: the gas in a filament flows onto a main, central clump but other, smaller-scale clumps form along the infalling gas. Correspondingly, the velocity along the filament exhibits a hierarchy of jumps at the locations of the clumps. Two prominent filaments in the simulation have lengths ?15 pc and masses ?600 M {sub ?} above density n ? 10{sup 3} cm{sup 3} (?2 10{sup 3} M {sub ?} at n > 50 cm{sup 3}). The density profile exhibits a central flattened core of size ?0.3 pc and an envelope that decays as r {sup 2.5} in reasonable agreement with observations. Accretion onto the filament reaches a maximum linear density rate of ?30 M {sub ?} Myr{sup 1} pc{sup 1}.

  7. Clouds Re-gathered by Wind Shear

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Re-gathered by Wind Shear For original submission and image(s), see ARM Research Highlights http://www.arm.gov/science/highlights/ Research Highlight When Pacific Northwest National Laboratory (PNNL) scientists looked for the culprit responsible for organizing storm clouds into strong weather systems, they pinned it on a fickle force. It turns out that wind shear at different vertical levels of the troposphere, well known for batting planes off their course, has strong and erratic effects on

  8. Total-derivative supersymmetry breaking

    SciTech Connect (OSTI)

    Haba, Naoyuki; Uekusa, Nobuhiro

    2010-05-15

    On an interval compactification in supersymmetric theory, boundary conditions for bulk fields must be treated carefully. If they are taken arbitrarily following the requirement that a theory is supersymmetric, the conditions could give redundant constraints on the theory. We construct a supersymmetric action integral on an interval by introducing brane interactions with which total-derivative terms under the supersymmetry transformation become zero due to a cancellation. The variational principle leads equations of motion and also boundary conditions for bulk fields, which determine boundary values of bulk fields. By estimating mass spectrum, spontaneous supersymmetry breaking in this simple setup can be realized in a new framework. This supersymmetry breaking does not induce a massless R axion, which is favorable for phenomenology. It is worth noting that fermions in hyper-multiplet, gauge bosons, and the fifth-dimensional component of gauge bosons can have zero-modes (while the other components are all massive as Kaluza-Klein modes), which fits the gauge-Higgs unification scenarios.

  9. Embracing the Cloud for Better Cyber Security

    SciTech Connect (OSTI)

    Shue, Craig A; Lagesse, Brent J

    2011-01-01

    The future of cyber security is inextricably tied to the future of computing. Organizational needs and economic factors will drive computing outcomes. Cyber security researchers and practitioners must recognize the path of computing evolution and position themselves to influence the process to incorporate security as an inherent property. The best way to predict future computing trends is to look at recent developments and their motivations. Organizations are moving towards outsourcing their data storage, computation, and even user desktop environments. This trend toward cloud computing has a direct impact on cyber security: rather than securing user machines, preventing malware access, and managing removable media, a cloud-based security scheme must focus on enabling secure communication with remote systems. This change in approach will have profound implications for cyber security research efforts. In this work, we highlight existing and emerging technologies and the limitations of cloud computing systems. We then discuss the cyber security efforts that would support these applications. Finally, we discuss the implications of these computing architecture changes, in particular with respect to malware and social engineering.

  10. PROPER-MOTION STUDY OF THE MAGELLANIC CLOUDS USING SPM MATERIAL

    SciTech Connect (OSTI)

    Vieira, Katherine; Girard, Terrence M.; Van Altena, William F.; Casetti-Dinescu, Dana I.; Korchagin, Vladimir I.; Herrera, David, E-mail: kvieira@cida.v, E-mail: terry.girard@yale.ed, E-mail: william.vanaltena@yale.ed [Astronomy Department, Yale University, P.O. Box 208101, New Haven, CT 06520 (United States)

    2010-12-15

    Absolute proper motions are determined for stars and galaxies to V = 17.5 over a 450 deg{sup 2} area that encloses both Magellanic Clouds. The proper motions are based on photographic and CCD observations of the Yale/San Juan Southern Proper Motion program, which span a baseline of 40 years. Multiple, local relative proper-motion measures are combined in an overlap solution using photometrically selected Galactic disk stars to define a global relative system that is then transformed to absolute using external galaxies and Hipparcos stars to tie into the ICRS. The resulting catalog of 1.4 million objects is used to derive the mean absolute proper motions of the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC); ({mu}{sub {alpha}}cos {delta}, {mu}{sub {delta}}){sub LMC} = (1.89, + 0.39) {+-} (0.27, 0.27) masyr{sup -1} and ({mu}{sub {alpha}}cos {delta}, {mu}{sub {delta}}){sub SMC} = (0.98, - 1.01) {+-} (0.30, 0.29) masyr{sup -1}. These mean motions are based on best-measured samples of 3822 LMC stars and 964 SMC stars. A dominant portion (0.25 mas yr{sup -1}) of the formal errors is due to the estimated uncertainty in the inertial system of the Hipparcos Catalog stars used to anchor the bright end of our proper motion measures. A more precise determination can be made for the proper motion of the SMC relative to the LMC; ({mu}{sub {alpha}cos {delta}}, {mu}{sub {delta}}){sub SMC-LMC} = (-0.91, - 1.49) {+-} (0.16, 0.15) masyr{sup -1}. This differential value is combined with measurements of the proper motion of the LMC taken from the literature to produce new absolute proper-motion determinations for the SMC, as well as an estimate of the total velocity difference of the two clouds to within {+-}54 km s{sup -1}. The absolute proper-motion results are consistent with the Clouds' orbits being marginally bound to the Milky Way, albeit on an elongated orbit. The inferred relative velocity between the Clouds places them near their binding energy limit and, thus, no definitive conclusion can be made as to whether or not the Clouds are bound to one another.

  11. Intercomparison of the Cloud Water Phase among Global Climate Models

    SciTech Connect (OSTI)

    Komurcu, Muge; Storelvmo, Trude; Tan, Ivy; Lohmann, U.; Yun, Yuxing; Penner, Joyce E.; Wang, Yong; Liu, Xiaohong; Takemura, T.

    2014-03-27

    Mixed-phase clouds (clouds that consist of both cloud droplets and ice crystals) are frequently present in the Earths atmosphere and influence the Earths energy budget through their radiative properties, which are highly dependent on the cloud water phase. In this study, the phase partitioning of cloud water is compared among six global climate models (GCMs) and with Cloud and Aerosol Lidar with Orthogonal Polarization retrievals. It is found that the GCMs predict vastly different distributions of cloud phase for a given temperature, and none of them are capable of reproducing the spatial distribution or magnitude of the observed phase partitioning. While some GCMs produced liquid water paths comparable to satellite observations, they all failed to preserve sufficient liquid water at mixed-phase cloud temperatures. Our results suggest that validating GCMs using only the vertically integrated water contents could lead to amplified differences in cloud radiative feedback. The sensitivity of the simulated cloud phase in GCMs to the choice of heterogeneous ice nucleation parameterization is also investigated. The response to a change in ice nucleation is quite different for each GCM, and the implementation of the same ice nucleation parameterization in all models does not reduce the spread in simulated phase among GCMs. The results suggest that processes subsequent to ice nucleation are at least as important in determining phase and should be the focus of future studies aimed at understanding and reducing differences among the models.

  12. Performance of Evapotranspirative Covers Under Enhanced Precipitation: Preliminary Data

    SciTech Connect (OSTI)

    David C. Anderson, Lloyd T. Desotell, David B. Hudson, Gregory J. Shott, Vefa Yucel

    2007-02-01

    Since January 2001, drainage lysimeter studies have been conducted at Yucca Flat, on the Nevada Test Site, in support of an evapotranspirative cover design. Yucca Flat has an arid climate with average precipitation of 16.5 cm annually. The facility consists of six drainage lysimeters 3 m in diameter, 2.4 m deep, and backfilled with a single layer of native soil. The bottom of each lysimeter is sealed and equipped with a small drain that enables direct measurement of saturated drainage. Each lysimeter has eight time-domain reflectometer probes to measure moisture content-depth profiles paired with eight heat-dissipation probes to measure soil-water potential depth profiles. Sensors are connected to dataloggers which are remotely accessed via a phone line. The six lysimeters have three different surface treatments: two are bare-soil; two were revegetated with native species (primarily shadscale, winterfat, ephedra, and Indian rice grass); and two were allowed to revegetate naturally with such species as Russian thistle, halogeton, tumblemustard and cheatgrass. Beginning in October 2003, one half of the paired cover treatments (one bare soil, one invader species, and one native species) were irrigated with an amount of water equal to two times the natural precipitation to achieve a three times natural precipitation treatment. From October 2003 through December 2005, all lysimeters received 52.8 cm precipitation, and the four irrigated lysimeters received an extra 105.6 cm of irrigation. No drainage has occurred from any of the nonirrigated lysimeters, but moisture has accumulated at the bottom of the bare-soil lysimeter and the native-plant lysimeter. All irrigated lysimeters had some drainage. The irrigated baresoil lysimeter had 48.3 cm of drainage or 26.4 percent of the combined precipitation and applied irrigation for the entire monitoring record. The irrigated invader species lysimeter had 5.8 cm of drainage, about 3.2 percent of the combined precipitation and applied irrigation. An irrigation valve failure caused an additional 50.8 cm of irrigation to be applied to the irrigated native plant lysimeter. There has been 29.3 cm of drainage from this lysimeter, which is 11.5 percent of the total applied water. Approximately 40 percent of the drainage from the irrigated native plant lysimeter occurred within four weeks of the valve failure.

  13. Total Space Heating Water Heating Cook-

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Commercial Buildings Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing...

  14. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,870 1,276...

  15. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Energy Consumption Survey: Energy End-Use Consumption Tables Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All...

  16. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings* ... 1,602 1,397...

  17. Total Space Heating Water Heating Cook-

    Gasoline and Diesel Fuel Update (EIA)

    Released: September, 2008 Total Space Heating Water Heating Cook- ing Other Total Space Heating Water Heating Cook- ing Other All Buildings ... 2,037...

  18. 2008 Annual Merit Review Results Summary - Disclaimer and Back Cover |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Disclaimer and Back Cover 2008 Annual Merit Review Results Summary - Disclaimer and Back Cover DOE Vehicle Technologies Annual Merit Review PDF icon 2008_merit_review_back.pdf More Documents & Publications FY 2009 Progress Report for Lightweighting Materials - disclaimer and back cover 2011 Annual Progress Report for Lightweighting Materials FY 2012 Annual Progress Report for Energy Storage R&D

  19. Covered Product Category: Commercial Ovens | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Ovens Covered Product Category: Commercial Ovens The Federal Energy Management Program (FEMP) provides acquisition guidance for commercial ovens, which is a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies purchase products that are covered by ENERGY STAR or FEMP in all acquisitions that are not specifically exempted by law. Meeting Energy Efficiency Requirements for Commercial Ovens ENERGY STAR sets efficiency requirements for commercial

  20. Covered Product Category: Imaging Equipment | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Imaging Equipment Covered Product Category: Imaging Equipment The Federal Energy Management Program (FEMP) provides acquisition guidance for imaging equipment, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies buy ENERGY STAR qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S. Environmental

  1. Covered Product Category: Room Air Conditioners | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Room Air Conditioners Covered Product Category: Room Air Conditioners The Federal Energy Management Program (FEMP) provides acquisition guidance for room air conditioners, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies purchase ENERGY STAR-qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The

  2. DOE Proposes Requirement for Certification of Admissibility for Covered

    Energy Savers [EERE]

    Products and Equipment | Department of Energy Proposes Requirement for Certification of Admissibility for Covered Products and Equipment DOE Proposes Requirement for Certification of Admissibility for Covered Products and Equipment February 22, 2016 - 6:26pm Addthis DOE has issued a Notice of Proposed Rulemaking (NOPR) in which it proposes to require that a person importing into the United States any covered product or equipment subject to an applicable energy conservation standard provide,

  3. FY 2008 Progress Report for Lightweighting Materials - Cover, Title Page,

    Office of Environmental Management (EM)

    and Contents | Department of Energy 08 Progress Report for Lightweighting Materials - Cover, Title Page, and Contents FY 2008 Progress Report for Lightweighting Materials - Cover, Title Page, and Contents Lightweighting Materials focuses on the development and validation of advanced materials and manufacturing technologies to reduce automobile weight without compromising other attributes. PDF icon cover_tp_toc.pdf More Documents & Publications FY 2009 Progress Report for Lightweighting

  4. First-ever Hydropower Market Report Covers Hydropower Generation

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Infrastructure | Department of Energy First-ever Hydropower Market Report Covers Hydropower Generation Infrastructure First-ever Hydropower Market Report Covers Hydropower Generation Infrastructure May 28, 2015 - 2:41pm Addthis First-ever Hydropower Market Report Covers Hydropower Generation Infrastructure The Energy Department's 2014 Hydropower Market Report was released last month in an effort to provide taxpayers and industry professionals with a snapshot of the growing hydropower

  5. Covered Product Category: Data Center Storage | Department of Energy

    Office of Environmental Management (EM)

    Data Center Storage Covered Product Category: Data Center Storage The Federal Energy Management Program (FEMP) provides acquisition guidance for data center storage, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies buy ENERGY STAR-qualified products in all product categories covered by this program and any acquisitions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S. Environmental

  6. Covered Product Category: Enterprise Servers | Department of Energy

    Office of Environmental Management (EM)

    Enterprise Servers Covered Product Category: Enterprise Servers The Federal Energy Management Program (FEMP) provides acquisition guidance for enterprise servers, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies buy ENERGY STAR-qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S.

  7. Covered Product Category: Imaging Equipment | Department of Energy

    Office of Environmental Management (EM)

    Imaging Equipment Covered Product Category: Imaging Equipment The Federal Energy Management Program (FEMP) provides acquisition guidance for imaging equipment, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies buy ENERGY STAR qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S. Environmental

  8. Covered Product Category: Residential Dishwashers | Department of Energy

    Office of Environmental Management (EM)

    Dishwashers Covered Product Category: Residential Dishwashers The Federal Energy Management Program (FEMP) provides acquisition guidance for residential dishwashers, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies purchase ENERGY STAR-qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S.

  9. Covered Product Category: Residential Freezers | Department of Energy

    Office of Environmental Management (EM)

    Freezers Covered Product Category: Residential Freezers The Federal Energy Management Program (FEMP) provides acquisition guidance for residential freezers, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies purchase ENERGY STAR-qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The U.S.

  10. Covered Product Category: Residential Refrigerators | Department of Energy

    Office of Environmental Management (EM)

    Refrigerators Covered Product Category: Residential Refrigerators The Federal Energy Management Program (FEMP) provides acquisition guidance for residential refrigerators, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies purchase ENERGY STAR-qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The

  11. Covered Product Category: Room Air Conditioners | Department of Energy

    Office of Environmental Management (EM)

    Room Air Conditioners Covered Product Category: Room Air Conditioners The Federal Energy Management Program (FEMP) provides acquisition guidance for room air conditioners, a product category covered by the ENERGY STAR program. Federal laws and requirements mandate that agencies purchase ENERGY STAR-qualified products in all product categories covered by this program and any acquisition actions that are not specifically exempted by law. MEETING EFFICIENCY REQUIREMENTS FOR FEDERAL PURCHASES The

  12. Monitoring the Performance of an Alternative Landfill Cover at the

    Office of Environmental Management (EM)

    Monticello, Utah, Uranium Mill Tailings Disposal Site | Department of Energy the Performance of an Alternative Landfill Cover at the Monticello, Utah, Uranium Mill Tailings Disposal Site Monitoring the Performance of an Alternative Landfill Cover at the Monticello, Utah, Uranium Mill Tailings Disposal Site Monitoring the Performance of an Alternative Landfill Cover at the Monticello, Utah, Uranium Mill Tailings Disposal Site PDF icon Monitoring the Performance of an Alternative Landfill

  13. Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings

    SciTech Connect (OSTI)

    Rosenfeld, Daniel

    2015-12-23

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Developing and validating this methodology was possible thanks to the ASR/ARM measurements of CCN and vertical updraft profiles. Validation against ground-based CCN instruments at the ARM sites in Oklahoma, Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25º restricts the satellite coverage to ~25% of the world area in a single day. This methodology will likely allow overcoming the challenge of quantifying the aerosol indirect effect and facilitate a substantial reduction of the uncertainty in anthropogenic climate forcing.

  14. Cloud radar Doppler spectra in drizzling stratiform clouds: 2. Observations and microphysical modeling of drizzle evolution

    SciTech Connect (OSTI)

    Kollias, P.; Luke, E.; Szyrmer, W.; Rmillard, J.

    2011-07-02

    In part I, the influence of cloud microphysics and dynamics on the shape of cloud radar Doppler spectra in warm stratiform clouds was discussed. The traditional analysis of radar Doppler moments was extended to include skewness and kurtosis as additional descriptors of the Doppler spectrum. Here, a short climatology of observed Doppler spectra moments as a function of the radar reflectivity at continental and maritime ARM sites is presented. The evolution of the Doppler spectra moments is consistent with the onset and growth of drizzle particles and can be used to assist modeling studies of drizzle onset and growth. Time-height radar observations are used to exhibit the coherency of the Doppler spectra shape parameters and demonstrate their potential to improve the interpretation and use of radar observations. In addition, a simplified microphysical approach to modeling the vertical evolution of the drizzle particle size distribution in warm stratiform clouds is described and used to analyze the observations. The formation rate of embryonic drizzle droplets due to the autoconversion process is not calculated explicitly; however, accretion and evaporation processes are explicitly modeled. The microphysical model is used as input to a radar Doppler spectrum forward model, and synthetic radar Doppler spectra moments are generated. Three areas of interest are studied in detail: early drizzle growth near the cloud top, growth by accretion of the well-developed drizzle, and drizzle depletion below the cloud base due to evaporation. The modeling results are in good agreement with the continental and maritime observations. This demonstrates that steady state one-dimensional explicit microphysical models coupled with a forward model and comprehensive radar Doppler spectra observations offer a powerful method to explore the vertical evolution of the drizzle particle size distribution.

  15. Evaluation of tropical cloud and precipitation statistics of CAM3 using CloudSat and CALIPSO data

    SciTech Connect (OSTI)

    Zhang, Y; Klein, S; Boyle, J; Mace, G G

    2008-11-20

    The combined CloudSat and CALIPSO satellite observations provide the first simultaneous measurements of cloud and precipitation vertical structure, and are used to examine the representation of tropical clouds and precipitation in the Community Atmosphere Model Version 3 (CAM3). A simulator package utilizing a model-to-satellite approach facilitates comparison of model simulations to observations, and a revised clustering method is used to sort the subgrid-scale patterns of clouds and precipitation into principal cloud regimes. Results from weather forecasts performed with CAM3 suggest that the model underestimates the horizontal extent of low and mid-level clouds in subsidence regions, but overestimates that of high clouds in ascending regions. CAM3 strongly overestimates the frequency of occurrence of the deep convection with heavy precipitation regime, but underestimates the horizontal extent of clouds and precipitation at low and middle levels when this regime occurs. This suggests that the model overestimates convective precipitation and underestimates stratiform precipitation consistent with a previous study that used only precipitation observations. Tropical cloud regimes are also evaluated in a different version of the model, CAM3.5, which uses a highly entraining plume in the parameterization of deep convection. While the frequency of occurrence of the deep convection with heavy precipitation regime from CAM3.5 forecasts decreases, the incidence of the low clouds with precipitation and congestus regimes increases. As a result, the parameterization change does not reduce the frequency of precipitating convection that is far too high relative to observations. For both versions of CAM, clouds and precipitation are overly reflective at the frequency of the CloudSat radar and thin clouds that could be detected by the lidar only are underestimated.

  16. FEMP First Thursday Update Covers Strategies for Renewable Energy...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Addthis FEMP First Thursday Update Covers Strategies for Renewable Energy Deployment The U.S. Department of Energy's (DOE) Federal Energy Management Program (FEMP) will present ...

  17. Vegetation Cover Analysis of Hazardous Waste Sites in Utah and...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... vegetation from AVIRIS data: Decomposing biochemical from structural signals. Remote Sens. ... J. Multiple criteria for evaluating machine learning algorithms for land cover ...

  18. Microsoft Word - DOE_Staffing_Study_Cover.doc | Department of...

    Office of Environmental Management (EM)

    Word - DOEStaffingStudyCover.doc More Documents & Publications 2010 DOE Strategic Sustainability Performance Plan - Report to the White House Council on Environmental...

  19. "List of Covered Electric Utilities" under the Public Utility...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    6 Revised "List of Covered Electric Utilities" under the Public Utility Regulatory Policies Act of 1978 (PURPA) - 2006 Revised Under Title I of the Public Utility Regulatory...

  20. Residential Windows and Window Coverings: A Detailed View of...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    View of the Installed Base and User Behavior Residential Windows and Window Coverings: A Detailed View of the Installed Base and User Behavior Includes information about the ...

  1. Covered Product Category: Air-Cooled Ice Machines

    Broader source: Energy.gov [DOE]

    The Federal Energy Management Program (FEMP) provides acquisition guidance for air-cooled ice machines, which are covered by the ENERGY STAR program.

  2. Six-Year Review of Covered Products | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Six-Year Review of Covered Products Six-Year Review of Covered Products This memorandum explains that the Energy Independence and Security Act of 2007 (EISA) requires the Department of Energy to re-evaluate efficiency standards for all covered appliances and products every six years. PDF icon Appendix_A_six-year_review_provision_memo.pdf More Documents & Publications Energy Independence and Security Act Six-Year Review of Covered Products 15th Semi-Annual Report to Congress on Appliance

  3. USGS-Land Cover Institute (LCI) | Open Energy Information

    Open Energy Info (EERE)

    USGS currently houses the institute at the Center for Earth Resources Observation and Science (EROS) in Sioux Falls, South Dakota. The LCI will address land cover topics from...

  4. Covered Product Category: Residential Heat Pump Water Heaters...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Heat Pump Water Heaters Covered Product Category: Residential Heat Pump Water Heaters The Federal Energy Management Program (FEMP) provides acquisition guidance and Federal ...

  5. Covered Product Category: Residential Whole-Home Gas Tankless...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Whole-Home Gas Tankless Water Heaters Covered Product Category: Residential Whole-Home Gas Tankless Water Heaters The Federal Energy Management Program (FEMP) provides acquisition ...

  6. Savings Project: Attic Stairs Cover Box | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Attic Stairs Cover Box Savings Project: Attic Stairs Cover Box Addthis Project Level EASY (KIT OR PRE-BUILT) TO MODERATE (DO-IT-YOURSELF) Energy Savings Savings depend on energy cost and airtightness of new cover box. Can be significant if there are open gaps in existing stair hatch. Time to Complete 1-4 HOURS Overall Cost $50-$150 Sealing gaps in the opening and installing an insulating cover box on your attic stairs access can improve comfort and save energy and money. | Photo courtesy of U.S.

  7. ARM - Publications: Science Team Meeting Documents: Cirrus Cloud

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Measurements by the UAF Polarization Diversity Lidar during M-PACE Cirrus Cloud Measurements by the UAF Polarization Diversity Lidar during M-PACE Sassen, Kenneth University of Alaska Fairbanks Zhu, Jiang UAF During the final week of the September-October 2004 Mixed-Phase Cloud Experiment (M-PACE) conducted in and around the North Slope of Alaska (NSA) Atmospheric Radiation Measurement (ARM) site in Barrow, Alaska, cirrus clouds were unexpectedly prevalent. Overcoming earlier adversity, the

  8. Clearing up concerns about cloud computing and genomics research | Argonne

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    National Laboratory Clearing up concerns about cloud computing and genomics research November 5, 2013 Tweet EmailPrint Cloud computing has become a popular option for scientists wanting on-demand access to increased capacity and capabilities, without having to invest in costly new hardware, storage, or other infrastructure. Genomics researchers, who produce enormous amounts of data thanks to new DNA sequencing technology, have begun to recognize the potential benefits of moving to the cloud.

  9. Comparison of Parameterized Cloud Variability to ARM Data

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Comparison of Parameterized Cloud Variability to ARM Data S. A. Klein National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory Princeton, New Jersey J. R. Norris Scripps Institute of Oceanography University of California La Jolla, California Abstract Cloud parameterizations in large-scale models often try to predict the amount of sub-grid scale variability in cloud properties to address the significant non-linear effects of radiation and precipitation. Statistical

  10. Continental Liquid-phase Stratus Clouds at SGP: Meteorological Influences

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    and Relationship to Adiabacity Continental Liquid-phase Stratus Clouds at SGP: Meteorological Influences and Relationship to Adiabacity Kim, Byung-Gon Kangnung National University Schwartz, Stephen Brookhaven National Laboratory Miller, Mark Brookhaven National Laboratory Min, Qilong State University of New York at Albany Category: Cloud Properties The microphysical properties of continental stratus clouds observed over SGP appear to be substantially influenced by micrometeorological

  11. Can Cloud Computing Address the Scientific Computing Requirements for DOE

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Researchers? Well, Yes, No and Maybe Can Cloud Computing Address the Scientific Computing Requirements for DOE Researchers? Well, Yes, No and Maybe Can Cloud Computing Address the Scientific Computing Requirements for DOE Researchers? Well, Yes, No and Maybe January 30, 2012 Jon Bashor, Jbashor@lbl.gov, +1 510-486-5849 Magellan1.jpg Magellan at NERSC After a two-year study of the feasibility of cloud computing systems for meeting the ever-increasing computational needs of scientists,

  12. ARM - Evaluation Product - Scanning ARM Cloud Radar Corrections (SACRCOR)

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ProductsScanning ARM Cloud Radar Corrections (SACRCOR) ARM Data Discovery Browse Data Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Evaluation Product : Scanning ARM Cloud Radar Corrections (SACRCOR) [ ARM research - evaluation data product ] This dataset contains moments from the Scanning ARM Cloud Radars (SACRs) which have been filtered and corrected

  13. ARM - PI Product - Atmospheric State, Cloud Microphysics & Radiative Flux

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ProductsAtmospheric State, Cloud Microphysics & Radiative Flux ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Atmospheric State, Cloud Microphysics & Radiative Flux [ ARM Principal Investigator (PI) Data Product ] Atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates for the ARM Southern Great Plains (SGP) site. The data represent a characterization of the

  14. Mixed-Phase Cloud Retrievals Using Doppler Radar Spectra

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Mixed-Phase Cloud Retrievals Using Doppler Radar Spectra M. D. Shupe, S. Y. Matrosov, and T. L. Schneider National Oceanic and Atmospheric Administration Environmental Technology Laboratory Boulder, Colorado P. Kollias Rosentiel School of Marine Atmospheric Sciences University of Miami Miami, Florida Introduction The radar Doppler spectrum contains a wealth of information on cloud microphysical properties. Typically, radar-based cloud retrievals use only the zeroth or first moments of the

  15. ARM - Field Campaign - Macquarie Island Cloud and Radiation Experiment

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    (MICRE) govCampaignsMacquarie Island Cloud and Radiation Experiment (MICRE) Campaign Links Science Plan Backgrounder Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Macquarie Island Cloud and Radiation Experiment (MICRE) 2016.03.01 - 2018.03.31 Lead Scientist : Roger Marchand Abstract Clouds over the Southern Ocean are poorly represented in present day reanalysis products and global climate model simulations. Errors in

  16. Cloud-Based Transportation Management System Delivers Savings | Department

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    of Energy Cloud-Based Transportation Management System Delivers Savings Cloud-Based Transportation Management System Delivers Savings October 21, 2014 - 1:53pm Addthis DOE's cloud based transportation management system (ATLAS) offers dramatically enhanced capabilities and modernization. ATLAS provides a powerful user-friendly system built to allow access to information to meet transportation needs. Its processes promote regulatory compliance, while providing access to qualified carriers and

  17. MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary

    SciTech Connect (OSTI)

    Chiu, J. -Y.C.; Gregory, L.; Wagener, R.

    2016-01-01

    Cloud droplet size and optical depth are the most fundamental properties for understanding cloud formation, dissipation and interactions with aerosol and drizzle. They are also a crucial determinant of Earth’s radiative and water-energy balances. However, these properties are poorly predicted in climate models. As a result, the response of clouds to climate change is one of the major sources of uncertainty in climate prediction.

  18. SPECIAL ANALYSIS OF OPERATIONAL STORMWATER RUNOFF COVERS OVER SLIT TRENCHES

    SciTech Connect (OSTI)

    Collard, L; Luther Hamm, L

    2008-12-18

    Solid Waste Management (SWM) commissioned this Special Analysis (SA) to determine the effects of placing operational stormwater runoff covers (referred to as covers in the remainder of this document) over slit trench (ST) disposal units ST1 through ST7 (the center set of slit trenches). Previously the United States Department of Energy (DOE) entered into an agreement with the United States Environmental Protection Agency (EPA) and the South Carolina Department of Health and Environmental Control (SCDHEC) to place covers over Slit Trenches 1 and 2 to be able to continue disposing Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) solid waste (see USDOE 2008). Because the covers changed the operating conditions, DOE Order 435.1 (DOE 1999) required that an SA be performed to assess the impact. This Special Analysis has been prepared to determine the effects of placing covers over slit trenches at about years 5, 10 and 15 of the 30-year operational period. Because some slit trenches have already been operational for about 15 years, results from analyzing covers at 5 years and 10 years provide trend analysis information only. This SA also examined alternatives of covering Slit Trenches 1 and 2 with one cover and Slit Trenches 3 and 4 with a second cover versus covering them all with a single cover. Based on modeling results, minimal differences exist between covering Slit Trench groups 1-2 and 3-4 with two covers or one large cover. This SA demonstrates that placement of covers over slit trenches will slow the subsequent release and transport of radionuclides in the vadose zone in the early time periods (from time of placement until about 100 years). Release and transport of some radionuclides in the vadose zone beyond 100 years were somewhat higher than for the case without covers. The sums-of-fractions (SOFs) were examined for the current waste inventory in ST1 and ST2 and for estimated inventories at closure for ST3 through ST7. In all cases SOFs were less than one (except for one SOF for ST5 that remained at one), indicating that there should be no unacceptable impacts on operations from placing covers for the cover alternatives that were analyzed. Minimal operational limits provided in Table 4 should be used as the new set of limits for Slit Trenches 1 through 7. ST1 and ST2 are expected to be covered about 15 years after the first disposal in ST1. Because the time of actual placement of covers over the other slit trenches is unknown, this SA did not consider limit increases, only limit decreases. Thus, each minimal operational limit is the minimum of the Performance Assessment (PA) final limit and the limit calculated in this SA if covers were placed at about 5, 10 or 15 years. If other cover times are desired, further analysis will be required.

  19. ARM - Field Campaign - Aerosol and Cloud Experiments in the Eastern...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol,...

  20. Chameleon: A Computer Science Testbed as Application of Cloud...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Chameleon: A Computer Science Testbed as Application of Cloud Computing Event Sponsor: Mathematics and Computing Science Brownbag Lunch Start Date: Dec 15 2015 - 12:00pm Building...

  1. Liquid Water the Key to Arctic Cloud Radiative Closure

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Water the Key to Arctic Cloud Radiative Closure For original submission and image(s), see ARM Research Highlights http:www.arm.govsciencehighlights Research Highlight...

  2. Stereo Photogrammetry Reveals Substantial Drag on Cloud Thermals

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    sciencehighlights Research Highlight Fast updrafts within clouds can generate hail, lightning, and tornadoes at the surface, as well as clear-air turbulence that pose...

  3. Cloud Properties and Radiative Heating Rates for TWP

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Comstock, Jennifer

    2013-11-07

    A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

  4. ARM - Publications: Science Team Meeting Documents: Interpretation of cloud

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    structure anomalies over the tropical Pacific during the 1997/98 El Nino Interpretation of cloud structure anomalies over the tropical Pacific during the 1997/98 El Nino Cess, Robert State University of New York at Stony Brook Sun, Moguo State University of New York at Stony Brook The CERES/TRMM single satellite footprint (SSF) dataset, available for January 1998 to August 1998, provides not only radiometric data, but also data for cloud fraction, cloud top pressure and cloud optical depth.

  5. ARM - Field Campaign - Remote Cloud Sensing (RCS) Field Evaluation

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsRemote Cloud Sensing (RCS) Field Evaluation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Remote Cloud Sensing (RCS) Field Evaluation 1994.04.01 - 1994.05.31 Lead Scientist : Robert Kropfli Data Availability CPRS Cloud Data (from the University of Massachusetts Cloud Profiling Radar System (CPRS)) For data sets, see below. Abstract The primary purpose of the field evaluation and calibration

  6. ARM - Field Campaign - Remote Cloud Sensing (RCS) Field Evaluation

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsRemote Cloud Sensing (RCS) Field Evaluation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Remote Cloud Sensing (RCS) Field Evaluation 1995.04.01 - 1995.05.31 Lead Scientist : Robert Kropfli Data Availability CPRS Cloud Data (from the University of Massachusetts Cloud Profiling Radar System (CPRS)) For data sets, see below. Abstract The primary purpose of the field evaluation and calibration

  7. ARM - Field Campaign - FIRE-Arctic Cloud Experiment/SHEBA

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    in the Arctic, to measure the BRDF and albedos of various surfaces (ice, snow and tundra) and various cloud types, and to obtain these measurements whenever possible either...

  8. ARM - Publications: Science Team Meeting Documents: Clouds in...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Clouds in the Darwin area and their relation to large-scale conditions Jakob, Christian BMRC Hoeglund, Sofia Lulea University of Technology This poster shows a climatological...

  9. Posters Ship-Based Measurements of Cloud Optical Properties

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    the optical properties of MBL clouds using measurements taken on the NOAA research vessel Malcom Baldrige. We seek the relationship between optical depth and liquid water because...

  10. The relationship between interannual and long-term cloud feedbacks...

    Office of Scientific and Technical Information (OSTI)

    The relationship between interannual and long-term cloud feedbacks Citation Details In-Document Search This content will become publicly available on December 11, 2016 Title: The ...

  11. RACORO continental boundary layer cloud investigations. 2. Large-eddy

    Office of Scientific and Technical Information (OSTI)

    simulations of cumulus clouds and evaluation with in-situ and ground-based observations (Journal Article) | SciTech Connect 2. Large-eddy simulations of cumulus clouds and evaluation with in-situ and ground-based observations Citation Details In-Document Search This content will become publicly available on June 19, 2016 Title: RACORO continental boundary layer cloud investigations. 2. Large-eddy simulations of cumulus clouds and evaluation with in-situ and ground-based observations A

  12. Single-Column Modeling A Stratiform Cloud Parameterization for...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    parameterization originally developed for mesoscale cloud models (Tripoli and Cotton 1980, Cotton et al. 1982 and 1986, Meyers et al. 1992). These approximations are...

  13. Surface based remote sensing of aerosol-cloud interactions

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    of a range of proxies for cloud condensation nuclei, ranging from surface measurements of light scattering and accumulation mode number concentration, to lidar-measured extinction...

  14. The Tropical Warm Pool International Cloud Experiment: Overview

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Tropical Warm Pool International Cloud Experiment: Overview May, Peter Bureau or Meteorology Research Centre Mather, James Pacific Northwest National Laboratory Jakob,...

  15. Sensitivity of Boundary-layer and Deep Convective Cloud Simulations...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Cloud Simulations to Vertical Resolution Cheng, Anning Langley Research Center Xu, Kuan-Man NASA Langley Research Center Category: Modeling This study investigates the effects of...

  16. Testing Statistical Cloud Scheme Ideas in the GFDL Climate Model

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Testing Statistical Cloud Scheme Ideas in the GFDL Climate Model Klein, Stephen Lawrence Livermore National Laboratory Pincus, Robert NOAA-CIRES Climate Diagnostics Center...

  17. Atmospheric Rivers Coming to a Cloud Near You

    SciTech Connect (OSTI)

    Leung, Ruby

    2014-03-29

    Learn about the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) field campaign in this short video. Ruby Leung, PNNL's lead scientist on this campaign's observational strategy to monitor precipitation.

  18. Preliminary Studies on the Variational Assimilation of Cloud...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    for both cloud properties and surface radiative fluxes have been used in our feasibility studies. The assimilation of those observations has shown the capability of the...

  19. Fundamental to the Cloud Land Surface Interaction Campaign (CLASIC...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    in agriculture ranging from more accurate weather forecasting to improved water management decisions and crop yield estimation. CLASIC CLASIC - - LAND LAND Cloud and Land...

  20. A Comparison of Cirrus Cloud Visible Optical Depth Derived from...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Comparison of Cirrus Cloud Visible Optical Depth Derived from Lidar Lo, Chaomei Pacific Northwest National Laboratory Comstock, Jennifer Pacific Northwest National Laboratory...

  1. Layered Atlantic Smoke Interactions with Clouds (LASIC) Science...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... Colocated smoke and clouds over the remote ocean represent a regime of significant ... that will be helpful in resolving current uncertainties in the aging and transport ...

  2. ARM - Field Campaign - Cloud, Aerosol, and Complex Terrain Interaction...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    This range of environmental conditions and cloud properties coupled with a high frequency of events makes this an ideal location for improving our understanding of...

  3. Simulations of Midlatitude Frontal Clouds by Single-Column and...

    Office of Scientific and Technical Information (OSTI)

    condensates due to differences in parameterizations, however, the differences among inter-compared models are smaller in the CRMs than the SCMs. While the CRM-produced clouds...

  4. Examining How Radiative Fluxes Are Affected by Cloud and Particle...

    Office of Science (SC) Website

    the Earth will change as emissions from fossil fuel combustion change, climate models calculate a complex and changing mix of clouds and emissions that interact with solar energy. ...

  5. Cluster Analysis of Cloud Regimes and Characteristic Dynamics...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Cluster Analysis of Cloud Regimes and Characteristic Dynamics of Mid-Latitude Synoptic Systems N. D. Gordon and J. R. Norris Scripps Institution of Oceanography University of...

  6. Clouds, Aerosols and Precipitation in the Marine Boundary Layer...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Framework, extend to investigation of aerosol-cloud interactions in models - Ensemble Kalman Filter (DART) Satellite activities with CAP-MBL Minnis: CAP-MBL subset MBL depth,...

  7. Intersecting Cold Pools: Convective Cloud Organization by Cold...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Intersecting Cold Pools: Convective Cloud Organization by Cold Pools over Tropical Ocean For original submission and image(s), see ARM Research Highlights http:www.arm.gov...

  8. ARM - Field Campaign - MASRAD: Cloud Condensate Nuclei Chemistry...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Cloud Condensate Nuclei Chemistry Measurements Campaign Links AMF Point Reyes Website ARM Data Discovery Browse Data Related Campaigns MArine Stratus Radiation Aerosol and Drizzle...

  9. ARM - Field Campaign - Cirrus Clouds and Aerosol Properties Campaign

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsCirrus Clouds and Aerosol Properties Campaign ARM Data Discovery Browse Data Related Campaigns Vaisala Laser Ceilometer CL51 Demonstration 2013.11.14, Winston, SGP...

  10. ARM - Field Campaign - MASRAD: Pt. Reyes Stratus Cloud and Drizzle...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsMASRAD: Pt. Reyes Stratus Cloud and Drizzle Study Campaign Links AMF Point Reyes Website ARM Data Discovery Browse Data Related Campaigns MArine Stratus Radiation...

  11. ARM - Field Campaign - Colorado: The Storm Peak Lab Cloud Property...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Storm Peak Lab Cloud Property Validation Experiment (STORMVEX) Campaign Links STORMVEX Website ARM Data Discovery Browse Data Related Campaigns Colorado: CFHCMH Deployment to...

  12. Cloud Properties and Radiative Heating Rates for TWP

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Comstock, Jennifer

    A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

  13. Remote Spectroscopic Sounding of Liquid Water Path in Thick Clouds...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, the original methodology of sounding of dense clouds has been under development 1-3. The methodology...

  14. MBL Drizzle Properties and Their Impact on Cloud Property Retrieval

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    layer drizzle properties and their impact on cloud property retrieval." Atmospheric Measurement Techniques, 8, doi:10.5194amt-8-3555-2015. Contributors Xiquan Dong,...

  15. Testing a Cloud Condensation Nuclei Remote Sensing Method

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    a Cloud Condensation Nuclei Remote Sensing Method S. J. Ghan Climate Physics Pacific Northwest National Laboratory Richland, Washington D. R. Collin Department of Atmospheric...

  16. arm_stm_2007_revercomb_poster_cloud.ppt

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    AERI Derived Cloud Properties David Tobin, Lori Borg, David Turner, Robert Holz, Daniel DeSlover, Hank Revercomb, Bob Knuteson, Leslie Moy, Ed Eloranta, Jun Li Space Science...

  17. A Lidar View of Clouds in Southeastern China

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Lidar View of Clouds in Southeastern China For original submission and image(s), see ARM Research Highlights http:www.arm.govsciencehighlights Research Highlight From May 2008...

  18. Sensitivity of Radiative Fluxes and Heating Rates to Cloud Microphysic...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Sensitivity of Radiative Fluxes and Heating Rates to Cloud Microphysics S. F. Iacobellis and R. C. J. Somerville Scripps Institution of Oceanography University of California, San...

  19. The Radiative Role of Free Tropospheric Aerosols and Marine Clouds...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: The Radiative Role of Free Tropospheric Aerosols and Marine Clouds over the Central North Atlantic Citation Details In-Document Search Title: The Radiative Role...

  20. Cloud Lake, Florida: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Cloud Lake, Florida: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 26.6761772, -80.0739308 Show Map Loading map... "minzoom":false,"mappingse...