National Library of Energy BETA

Sample records for lbtm cloud products

  1. ARM - VAP Product - lbtm3minnisdar

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

    below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNISDAR Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Darwin Active Dates 2002.04.01...

  2. ARM - VAP Product - lbtm3minnisman

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

    minnisman Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : LBTM3MINNISMAN Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Manus

  3. ARM - VAP Product - lbtm3minnisnau

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

    minnisnau Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : LBTM3MINNISNAU Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Nauru

  4. ARM - VAP Product - lbtm3minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : LBTM3MINNIS Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5 Active Dates 1998.01.03 - 2003.05.21 Originating VAP Process Minnis Cloud Products Using LBTM Algorithm : LBTM-MINNIS Measurements The measurements below provided by this

  5. ARM - VAP Process - lbtm-minnis

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

    : Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Darwin lbtm3minnisman : Layered Bispectral Threshold Method (LBTM) cloud products derived...

  6. ARM - Campaign Instrument - lbtm-minnis

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

    govInstrumentslbtm-minnis Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign Instrument : Minnis Cloud Products Using LBTM Algorithm (LBTM-MINNIS) Instrument Categories Cloud Properties, Satellite Observations Campaigns ARESE II IOP [ Download Data ] Southern Great Plains, 2000.02.01 - 2000.04.05 Nauru99 Campaign [ Download Data ] Tropical Western Pacific, 1999.06.16 - 1999.07.15 Primary Measurements Taken The following measurements are

  7. ARM - Measurement - Cloud optical depth

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

    TWST : Three Waveband Spectrally-agile Technique Sensor WRF-CHEM : Weather Research and Forecasting (WRF) Model Output Value-Added Products LBTM-MINNIS : Minnis Cloud Products...

  8. ARM - VAP Product - goes12minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : GOES12MINNIS GOES-12: 0.5 degree cloud products Active Dates 2003.04.01 - 2003.08.31 Originating VAP Process Minnis Cloud Products Using LBTM Algorithm : LBTM-MINNIS Measurements The measurements below provided by this product are those considered

  9. ARM - VAP Product - goes7minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : GOES7MINNIS GOES-7: 0.5 degree cloud products

  10. ARM - VAP Product - goes8minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : GOES8MINNIS GOES-8: 0.5 degree cloud products

  11. ARM - VAP Product - goes7minnis-acf

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

    minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : GOES7MINNIS-ACF GOES-7: 0.3 degree cloud products, ARM Central Facility

  12. ARM - VAP Product - goes8minnis-acf

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

    minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : GOES8MINNIS-ACF GOES-8: 0.3 degree cloud products, ARM Central Facility

  13. ARM - VAP Product - goes12minnis-acf

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

    minnisgoes12minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : GOES12MINNIS-ACF GOES-12: 0.3 degree cloud products, ARM Central Facility Active Dates 2003.04.01 - 2003.08.31

  14. ARM - VAP Product - goes7minnis-scm

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

    scm Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) 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 VAP Output : GOES7MINNIS-SCM GOES-7: 0.5 degree cloud products, Single Column Model Active Dates 1994.07.01 - 1994.07.31

  15. 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

  16. 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.,

  17. Cloud Property Retrieval Products for Graciosa Island, Azores

    SciTech Connect (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.

  18. 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.

  19. 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

  20. 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...

  1. ARM - Evaluation Product - MWR Retrievals of Cloud Liquid Water...

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

    ProductsMWR Retrievals of Cloud Liquid Water and Water Vapor ARM Data Discovery Browse Data Documentation Use the Data File Inventory tool to view data availability at the file...

  2. ARM - PI Product - AERIoe Thermodynamic Profile and Cloud Retrieval for

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

    MC3E Garber X-band site (I5) Garber X-band site (I5) 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 : AERIoe Thermodynamic Profile and Cloud Retrieval for MC3E Garber X-band site (I5) [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared

  3. ARM - PI Product - AERIoe Thermodynamic Profile and Cloud Retrieval for

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

    MC3E Lamont X-band site (I6) Lamont X-band site (I6) 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 : AERIoe Thermodynamic Profile and Cloud Retrieval for MC3E Lamont X-band site (I6) [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared

  4. ARM - Evaluation Product - Cloud Microbase-kazr Profiles (ka) VAP

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

    ProductsCloud Microbase-kazr Profiles (ka) VAP 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 : Cloud Microbase-kazr Profiles (ka) VAP The KAZR radars have recently replaced the MMCR at ARM sites, and so the new KAZR-based radar products will now serve as input to Microbase. All of the historic Microbase

  5. 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

  6. ARM - Evaluation Product - ISCCP Cloud Data Around the ARM Sites

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

    ProductsISCCP Cloud Data Around the ARM Sites 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 : ISCCP Cloud Data Around the ARM Sites ISCCP data (Rossow and Schiffer, 1999 and Rossow, et.al. 2005) are widely used in the climate modeling community. Within our LLNL CCPP-ARM Parameterization Testbed (CAPT)

  7. ARM - Evaluation Product - CMWG Data - SCM-Forcing Data, Cloud...

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

    data. Cloud microphysical properties derived from Mace's data of atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates are regridded to a...

  8. ARM - Evaluation Product - ARM Cloud Retrieval Ensemble Data

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

    cloud microphysical property ensemble data set created by assembling existing ARM cloud ... One purpose of developing such an ensemble data set is to provide a rough estimate of the ...

  9. Microbase Cloud Products and Associated Heating Rates in the Tropical Western Pacific

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

    Microbase Cloud Products and Associated Heating Rates in the Tropical Western Pacific J. H. Mather and S. A. McFarlane Pacific Northwest National Laboratory Richland, Washington Introduction The microbase value added product (Miller et al. 2003) provides a standardized framework for calculating and storing continuous retrievals of cloud microphysical properties including liquid water content (LWC), ice water content (IWC), and cloud droplet size. Microbase is part of the larger broadband heating

  10. ARM - PI Product - Cloud Properties and Radiative Heating Rates for TWP

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

    ProductsCloud Properties and Radiative Heating Rates for TWP 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 Properties and Radiative Heating Rates for TWP 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

  11. ARM - PI Product - Cloud-Scale Vertical Velocity and Turbulent Dissipation

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

    Rate Retrievals ProductsCloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals 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-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals 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

  12. ARSCL Cloud Statistics - A Value-Added Product

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

    data from active remote sensors to produce an objective determination of cloud location, radar reflectivity, vertical velocity, and Doppler spectral width. Information about the...

  13. ARM Value-Added Cloud Products: Description and Status

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

    This VAP combines the data from the millimeter cloud radar (MMCR), micropulse lidar (MPL), laser ceilometer, microwave radiometer (MWR), and surface measurements. It produces a ...

  14. Cloud Property Retrieval Products for Graciosa Island, Azores...

    Office of Scientific and Technical Information (OSTI)

    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. ...

  15. ARM - PI Product - MWR Retrievals of Cloud Liquid Water and Water...

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

    govDataPI Data ProductsMWR Retrievals of Cloud Liquid Water and Water Vapor ARM Data Discovery Browse Data Comments? We would love to hear from you Send us a note below or call us...

  16. ARM - PI Product - AERIoe Thermodynamic Profile and Cloud Retrieval for SGP

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

    CF during LABLE-2012 2 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 : AERIoe Thermodynamic Profile and Cloud Retrieval for SGP CF during LABLE-2012 [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The method is a

  17. ARM - PI Product - AERIoe Thermodynamic Profile and Cloud Retrieval for SGP

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

    CF during LABLE-2013 3 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 : AERIoe Thermodynamic Profile and Cloud Retrieval for SGP CF during LABLE-2013 [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The method is a

  18. DOE/SC-ARM/TR-098 Micropulse Lidar Cloud Mask Value-Added Product Technical Report

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

    8 Micropulse Lidar Cloud Mask Value-Added Product Technical Report C Sivaraman J Comstock July 2011 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would

  19. The effect of acidity variations in cloud droplet populations on aqueous-phase sulfate production

    SciTech Connect (OSTI)

    Gurciullo, C.S.; Pandis, S.N.

    1995-12-31

    The majority of global atmospheric sulfate production occurs in clouds. Experimental evidence suggests that significant chemical heterogeneities exist in cloud droplet populations. Both theoretical and field studies suggest that the acidity of a cloud droplet population can differ by 1 pH unit or more between the smallest and largest droplets. Traditionally, cloud chemistry has been studied using bulk models that assume that the aqueous- phase chemistry can be accurately modeled using {open_quotes}mean droplet{close_quotes} properties. The average droplet population pH is then used as the basis for calculating reaction rates. Using this bulk chemistry approach in cloud or fog models may lead to significant errors in the predicted aqueous-phase reaction rates. We prove analytically that the use of a droplet Population`s average pH always results in the underestimation of the rate of sulfate production. In order to examine the magnitude of this error, we have developed two aqueous-phase chemistry models: a droplet size-resolved model and a bulk chemistry model. The discrepancy between the results of these two models indicates the degree of error introduced by assuming bulk aqueous-phase properties. The magnitude of this error depends on the availability of SO{sub 2}, H{sub 2}O{sub 2}, NH{sub 3}, and acidity, and can range from zero to a factor of three for reasonable ambient conditions. A modeling approach that combines the accuracy of the size-resolved model and the low computing requirements of the bulk model is developed.

  20. DOE/SC-ARM/TR-095 The Microbase Value-Added Product: A Baseline Retrieval of Cloud

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

    5 The Microbase Value-Added Product: A Baseline Retrieval of Cloud Microphysical Properties M Dunn K Johnson M Jensen May 2011 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or

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

    SciTech Connect (OSTI)

    Turner, D. D.; McFarlane, S. A.; 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.

  2. Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies

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

    Xie, Shaocheng; McCoy, Renata B.; Klein, Stephen A.; Cederwall, Richard T.; Wiscombe, Warren J.; Clothiaux, Eugene E.; Gaustad, Krista L.; Golaz, Jean -Christophe; Hall, Stephanie D.; Jensen, Michael P.; et al

    2010-01-01

    The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation atmosphere. Here, a central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement.

  3. ARM - Measurement - Cloud fraction

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

    Flux Analysis SWFLUXANAL : Shortwave Flux Analysis TSI : Total Sky Imager UAV-EGRETT : UAV-Egrett WSI : Whole Sky Imager WSICLOUD : Whole Sky Imager Cloud Products ...

  4. 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...

  5. Acidity dependence on cloud drop sizes, enhancement of sulfate production in clouds and its climatic implications from cloud water collected at a remote eastern US site. Master`s thesis

    SciTech Connect (OSTI)

    Logie, B.D.

    1995-09-10

    Two different cloud water collectors were operated simultaneously on a mountain-top platform in Mt. Mitchell State Park, North Carolina (35 deg 44` 05 N 82 deg 17` 15W) to assess differences, if any, in measured acidity, ionic concentrations, and liquid water collection efficiencies during the summer, 1994. The cloud water collectors used were the Daube California Institute of Technology active-string collector (CALTECH) and the non-rotating passive Atmospheric Sciences Research Center string collector. Both collectors transfer cloud water into their sampling bottles by a process analogous to the collision-coalescence process in precipitation initiation by which cloud droplets accumulate on the collector strings and are then transferred to collection bottles as the droplets become large enough to fall. These large drops, in turn, acquire smaller droplets along their path.

  6. Precipitating clouds

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

    A suggestion for a new focus on cloud microphysical process study in the ARM program 1. Retrieving precipitating mixed- phase cloud properties Zhien Wang University of Wyoming zwang@uwyo.edu Retrieving Precipitating Mixed-phase Cloud Properties Global distribution of supercooled water topped stratiform clouds (top > 1 km and length> 14km) Most of them are mixed-phase with precipitation or virga An multiple sensor based approach to provide water phase as well as ice phase properties

  7. 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...

  8. 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...

  9. 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...

  10. ARM - Publications: Science Team Meeting Documents

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

    GOES-8 cloud and radiative properties data set. The ARM GOES-8 data set is derived using the Layered Bispectral Threshold Method (LBTM, see Khaiyer et al., 2001 this conference). ...

  11. 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.

  12. 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.

  13. 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...

  14. Science Cloud 2011

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

    Science Cloud 2011 Science Cloud 2011 June 17, 2011 The Magellan teams at NERSC and Argonne recently presented a joint paper detailing their progress and conclusions. At Science Cloud 2011: The Second Workshop on Scientific Cloud Computing, in a paper titled "Magellan: Experiences from a Science Cloud" (PDF, 320KB), lead author Lavanya Ramakrishnan outlined the groups' most recent achievements and conclusions, including a successful run of real-time data analysis for the STAR

  15. 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

  16. Cloud Properties Working Group Low Clouds Update

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

    Cloud Properties Working Group Low Clouds Update Low Clouds Update Jennifer Comstock Jennifer Comstock Dave Turner Dave Turner Andy Andy Vogelmann Vogelmann Instruments Instruments 90/150 GHz microwave radiometer 90/150 GHz microwave radiometer Deployed during COPS AMF Deployed during COPS AMF Exploring calibration w/ DPR ( Exploring calibration w/ DPR ( Crewell Crewell & & L L ö ö hnert hnert ) ) See COPS Breakout, Wednesday evening See COPS Breakout, Wednesday evening 183 GHz (GVR)

  17. ARM - Measurement - Cloud extinction

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

    Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud extinction The removal of radiant energy from an incident beam by the process of cloud absorption andor ...

  18. Scientific Cloud Computing Misconceptions

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

    Scientific Cloud Computing Misconceptions Scientific Cloud Computing Misconceptions July 1, 2011 Part of the Magellan project was to understand both the possibilities and the limitations of cloud computing in the pursuit of science. At a recent conference, Magellan investigator Shane Canon outlined some persistent misconceptions about doing science in the cloud - and what Magellan has taught us about them. » Read the ISGTW story. » Download the slides (PDF, 4.1MB

  19. ARM - VAP Product - arsclbnd1cloth

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

    Process Active Remotely-Sensed Cloud Locations : ARSCL Measurements The measurements below provided by this product are those considered scientifically relevant. Cloud base height...

  20. ARM - VAP Product - arsclcbh1cloth

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

    Process Active Remotely-Sensed Cloud Locations : ARSCL Measurements The measurements below provided by this product are those considered scientifically relevant. Cloud base height...

  1. ARM - VAP Product - arsclwacr1kollias

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

    The measurements below provided by this product are those considered scientifically relevant. Cloud base height Cloud top height Radar Doppler Radar polarization Radar reflectivity...

  2. 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...

  3. 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.

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

    SciTech Connect (OSTI)

    Wang, Zhien

    2006-01-04

    The project is concerned with the characterization of cloud macrophysical and microphysical properties by combining radar, lidar, and radiometer measurements available from the U.S. Department of Energy's ARM Climate Research Facility (ACRF). To facilitate the production of integrated cloud product by applying different algorithms to the ARM data streams, an advanced cloud classification algorithm was developed to classified clouds into eight types at the SGP site based on ground-based active and passive measurements. Cloud type then can be used as a guidance to select an optimal retrieval algorithm for cloud microphysical property retrieval. The ultimate goal of the effort is to develop an operational cloud classification algorithm for ARM data streams. The vision 1 IDL code of the cloud classification algorithm based on the SGP ACRF site observations was delivered to the ARM cloud translator during 2004 ARM science team meeting. Another goal of the project is to study midlevel clouds, especially mixed-phase clouds, by developing new retrieval algorithms using integrated observations at the ACRF sites. Mixed-phase clouds play a particular role in the Arctic climate system. A multiple remote sensor based algorithm, which can provide ice water content and effective size profiles, liquid water path, and layer-mean effective radius of water droplet, was developed to study arctic mixed-phase clouds. The algorithm is applied to long-term ARM observations at the NSA ACRF site. Based on these retrieval results, we are studying seasonal and interannual variations of arctic mixed-phase cloud macro- and micro-physical properties.

  5. Macquarie Island Cloud and Radiation Experiment (MICRE) Science Plan

    Office of Scientific and Technical Information (OSTI)

    (Program Document) | SciTech Connect Macquarie Island Cloud and Radiation Experiment (MICRE) Science Plan Citation Details In-Document Search Title: Macquarie Island Cloud and Radiation Experiment (MICRE) Science Plan Clouds over the Southern Ocean are poorly represented in present day reanalysis products and global climate model simulations. Errors in top-of-atmosphere (TOA) broadband radiative fluxes in this region are among the largest globally, with large implications for modeling both

  6. Boundary Layer Cloud Turbulence Characteristics

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

    Boundary Layer Cloud Turbulence Characteristics Virendra Ghate Bruce Albrecht Parameter Observational Readiness (/10) Modeling Need (/10) Cloud Boundaries 9 9 Cloud Fraction Variance Skewness Up/Downdraft coverage Dominant Freq. signal Dissipation rate ??? Observation-Modeling Interface

  7. 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.

  8. Temperature, Water Vapor, and Clouds"

    Office of Scientific and Technical Information (OSTI)

    Radiometric Studies of Temperature, Water Vapor, and Clouds" Project ID: 0011106 ... measurements of column amounts of water vapor and cloud liquid has been well ...

  9. 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...

  10. 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...

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. ARM Cloud Retrieval Ensemble Data Set (ACRED) (Technical Report...

    Office of Scientific and Technical Information (OSTI)

    Citation Details In-Document Search Title: ARM Cloud Retrieval Ensemble Data Set (ACRED) ... This site is a product of DOE's Office of Scientific and Technical Information (OSTI) and ...

  17. ER2 Instrumentation and Measurements for CLASIC (Cloud Land Surface...

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

    ER2 Desired Measurements for CLASIC June 2007 SGP May 31, 2007 1 MEASUREMENT SOURCE DESIRED MEASUREMENTS AND PRODUCTS INSTRUMENT SYSTEMS Cloud Radar System (CRS), W-Band (95 GHz)...

  18. 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.

  19. 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.

  20. Science on the Hill: Methane cloud hunting

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

    Methane cloud hunting Science on the Hill: Methane cloud hunting Los Alamos researchers go ... Science on the Hill: Methane cloud hunting When our team from Los Alamos National ...

  1. The diverse use of clouds by CMS

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

    Andronis, Anastasios; Bauer, Daniela; Chaze, Olivier; Colling, David; Dobson, Marc; Fayer, Simon; Girone, Maria; Grandi, Claudio; Huffman, Adam; Hufnagel, Dirk; et al

    2015-01-01

    The resources CMS is using are increasingly being offered as clouds. In Run 2 of the LHC the majority of CMS CERN resources, both in Meyrin and at the Wigner Computing Centre, will be presented as cloud resources on which CMS will have to build its own infrastructure. This infrastructure will need to run all of the CMS workflows including: Tier 0, production and user analysis. In addition, the CMS High Level Trigger will provide a compute resource comparable in scale to the total offered by the CMS Tier 1 sites, when it is not running as part of themore » trigger system. During these periods a cloud infrastructure will be overlaid on this resource, making it accessible for general CMS use. Finally, CMS is starting to utilise cloud resources being offered by individual institutes and is gaining experience to facilitate the use of opportunistically available cloud resources. Lastly, we present a snap shot of this infrastructure and its operation at the time of the CHEP2015 conference.« less

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

    Office of Scientific and Technical Information (OSTI)

    Evaluation of high-level clouds in cloud resolving model 10.10022015MS000478 simulations with ARM and KWAJEX observations Key Points: * Two-moment microphysics improves simulated ...

  3. Opaque cloud detection

    DOE Patents [OSTI]

    Roskovensky, John K.

    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.

  4. 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

  5. Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations

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

    Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu

    2016-05-12

    Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine stratocumulus clouds and their radiative properties respond to changes in large-scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum and thereby acts on cloud liquid water path (LWP) and cloud radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus clouds to different wind speeds over the course of a diurnal cycle, all else equal. In cloud-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and strongermore » entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in cloud updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning–afternoon contrast. The higher LWP at higher wind speed does not, however, enhance cloud top cooling because in clouds with LWP ≳50 gm–2, longwave emissions are insensitive to LWP. This leads to the general conclusion that in sufficiently thick stratocumulus clouds, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in cloud updrafts, rather than from enhanced longwave cooling. Here, we find that large-scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment and in part because shear from large-scale wind in the sub-cloud layer hinders vertical moisture transport between the surface and cloud base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large-scale wind takes over from

  6. Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations

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

    Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu

    2016-05-12

    Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine stratocumulus clouds and their radiative properties respond to changes in large-scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum and thereby acts on cloud liquid water path (LWP) and cloud radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus clouds to different wind speeds over the course of a diurnal cycle, all else equal. In cloud-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and strongermore » entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in cloud updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning–afternoon contrast. The higher LWP at higher wind speed does not, however, enhance cloud top cooling because in clouds with LWP ⪆ 50 g m−2, longwave emissions are insensitive to LWP. This leads to the general conclusion that in sufficiently thick stratocumulus clouds, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in cloud updrafts, rather than from enhanced longwave cooling. We find that large-scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment and in part because shear from large-scale wind in the sub-cloud layer hinders vertical moisture transport between the surface and cloud base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large-scale wind takes over

  7. Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations

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

    Kazil, J.; Feingold, G.; Yamaguchi, T.

    2015-10-21

    Observed and projected trends in large scale wind speed over the oceans prompt the question: how might marine stratocumulus clouds and their radiative properties respond to future changes in large scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum, and thereby acts on cloud liquid water path (LWP) and cloud radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus clouds to different wind speeds, all else equal. In cloud-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and stronger entrainment. The dynamicalmoredriver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in cloud updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning afternoon contrast. The higher LWP at higher wind speed does not, however, enhance cloud top cooling because in clouds with LWP ⪆ 50 g m?2, long wave emissions are very insensitive to LWP. This leads to the more general conclusion that in sufficiently thick stratocumulus clouds, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in cloud updrafts, rather than from enhanced longwave cooling. We find furthermore that large scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment, and in part because circulation driven by shear from large scale wind in the sub-cloud layer hinders vertical moisture transport between the surface and cloud base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large scale

  8. 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.

  9. TWP Island Cloud Trail Studies

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

    These island cloud trails have been observed from both the islands of Nauru and Manus, Papua New Guinea. Figure 2 shows an island cloud at Manus observed from MTI and from the ...

  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. 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

  12. FINAL REPORT: An Investigation of the Microphysical, Radiative, and Dynamical Properties of Mixed-Phase Clouds

    SciTech Connect (OSTI)

    Shupe, Matthew D

    2007-10-01

    This final report summarizes the major accomplishments and products resulting from a three-year grant funded by the DOE, Office of Science, Atmospheric Radiation Measurement Program titled: An Investigation of the Microphysical, Radiative, and Dynamical Properties of Mixed-Phase Clouds. Accomplishments are listed under the following subcategories: Mixed-phase cloud retrieval method development; Mixed-phase cloud characterization; ARM mixed-phase cloud retrieval review; and New ARM MICROBASE product. In addition, lists are provided of service to the Atmospheric Radiation Measurement Program, data products provided to the broader research community, and publications resulting from this grant.

  13. 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

  14. Tropical Warm Pool International Cloud Experiment TWP-ICE Cloud and rain characteristics in the Australian Monsoon

    SciTech Connect (OSTI)

    May, P.T., Jakob, C., and Mather, J.H.

    2004-05-31

    The impact of oceanic convection on its environment and the relationship between the characteristics of the convection and the resulting cirrus characteristics is still not understood. An intense airborne measurement campaign combined with an extensive network of ground-based observations is being planned for the region near Darwin, Northern Australia, during January-February, 2006, to address these questions. The Tropical Warm Pool International Cloud Experiment (TWP-ICE) will be the first field program in the tropics that attempts to describe the evolution of tropical convection, including the large scale heat, moisture, and momentum budgets, while at the same time obtaining detailed observations of cloud properties and the impact of the clouds on the environment. The emphasis will be on cirrus for the cloud properties component of the experiment. Cirrus clouds are ubiquitous in the tropics and have a large impact on their environment but the properties of these clouds are poorly understood. A crucial product from this experiment will be a dataset suitable to provide the forcing and testing required by cloud-resolving models and parameterizations in global climate models. This dataset will provide the necessary link between cloud properties and the models that are attempting to simulate them.

  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 Baseline Instruments and Data Plots 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

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

    Office of Scientific and Technical Information (OSTI)

    Title: Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations: HIGH CLOUD IN CRM Authors: Liu, Zheng 1 ; Muhlbauer, Andreas 2 ; ...

  17. Cloud Condensation Nuclei Counter (CCN) Instrument Handbook

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

    8 Cloud Condensation Nuclei Particle Counter Instrument Handbook J. Uin April 2016 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe

  18. Cloud Properties Working Group Break Out Session

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

    Break Out Session ARM Science Team Meeting Louisville, KY 30 March 2009 The Chair's Objectives for CPWG *Maintain continuity of "base" instruments - We're building a climatology! *Advocate for sufficient programmatic support to make our measurements useful. *Better retrieval vetting framework - moving towards Cloud Properties Best Estimate *Build a stronger connection with the modeling community - Producing the products they want. CPWG Breakout Agenda 30 March 2009, 3-5 pm *3:00-3:15

  19. 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.

  20. Assessing Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer

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

    Cloud Spatial and Vertical Distribution with Infrared Cloud Analyzer I. Genkova and C. N. Long Pacific Northwest National Laboratory Richland, Washington T. Besnard ATMOS SARL Le Mans, France D. Gillotay Institute d'Aeronomie Spatiale de Belgique Brussels, Belgium Introduction In the effort to resolve uncertainties about global climate change, the Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) is improving the treatment of cloud radiative forcing and feedbacks in general

  1. First observations of tracking clouds using scanning ARM cloud...

    Office of Scientific and Technical Information (OSTI)

    These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator ...

  2. 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.

  3. Macquarie Island Cloud and Radiation Experiment (MICRE) Science Plan

    SciTech Connect (OSTI)

    Marchand, RT; Protat, A; Alexander, SP

    2015-12-01

    Clouds over the Southern Ocean are poorly represented in present day reanalysis products and global climate model simulations. Errors in top-of-atmosphere (TOA) broadband radiative fluxes in this region are among the largest globally, with large implications for modeling both regional and global scale climate responses (e.g., Trenberth and Fasullo 2010, Ceppi et al. 2012). Recent analyses of model simulations suggest that model radiative errors in the Southern Ocean are due to a lack of low-level postfrontal clouds (including clouds well behind the front) and perhaps a lack of supercooled liquid water that contribute most to the model biases (Bodas-Salcedo et al. 2013, Huang et al. 2014). These assessments of model performance, as well as our knowledge of cloud and aerosol properties over the Southern Ocean, rely heavily on satellite data sets. Satellite data sets are incomplete in that the observations are not continuous (i.e., they are acquired only when the satellite passes nearby), generally do not sample the diurnal cycle, and view primarily the tops of cloud systems (especially for the passive instruments). This is especially problematic for retrievals of aerosol, low-cloud properties, and layers of supercooled water embedded within (rather than at the top of) clouds, as well as estimates of surface shortwave and longwave fluxes based on these properties.

  4. Holistic Interactions of Shallow Clouds,

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

    Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems Research Instrumentation HI-SCALE will utilize the ARM Aerial Facility's Gulfstream-159 (G-1), as well as ground instrumentation located at the SGP megasite. 7e G-1 will complete transects over the site at multiple altitudes within the boundary layer, within clouds, and above clouds. 7e payload on the G-1 includes: * high frequency meteorological and radiation (both up and downwelling) measurements that also permit computing

  5. Cumulus Clouds and Reflected Sunlight

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

    Cumulus Clouds and Reflected Sunlight from Landsat ETM+ G. Wen and L. Oreopoulos National Aeronautics and Space Administration Goddard Space Flight Center University of Maryland Baltimore County Joint Center of Earth System Technology Greenbelt, Maryland R. F. Cahalan and S. C. Tsay National Aeronautics and Space Administration Goddard Space Flight Center Greenbelt, Maryland Introduction Cumulus clouds attenuate solar radiation casting shows on the ground. Cumulus clouds can also enhance solar

  6. ARM - Measurement - Cloud top height

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

    RUC : Rapid Update Cycle Model Data Field Campaign Instruments CO2LIDAR : Carbon Dioxide Doppler Lidar MPLCMASK : Cloud mask from Micropulse Lidar VARANAL : Constrained...

  7. 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...

  8. ARM - Measurement - Cloud ice particle

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

    : Lear Jet PARTIMG : Particle imager UAV-PROTEUS-MICRO : Proteus Cloud Microphysics ... particle imager MET : Surface Meteorological Instrumentation UAV-PROTEUS : UAV Proteus

  9. ARM - Measurement - Cloud droplet size

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

    Impactor MIRAI : JAMSTEC Research Vessel Mirai PDI : Phase Doppler Interferometer UAV-PROTEUS-MICRO : Proteus Cloud Microphysics Instruments SPEC-CPI : Stratton Park ...

  10. Effects of Ocean Ecosystem on Marine Aerosol-Cloud Interaction

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

    Meskhidze, Nicholas; Nenes, Athanasios

    2010-01-01

    Using smore » atellite data for the surface ocean, aerosol optical depth (AOD), and cloud microphysical parameters, we show that statistically significant positive correlations exist between ocean ecosystem productivity, the abundance of submicron aerosols, and cloud microphysical properties over different parts of the remote oceans. The correlation coefficient for remotely sensed surface chlorophyll a concentration ([Chl- a ]) and liquid cloud effective radii over productive areas of the oceans varies between − 0.2 and − 0.6 . Special attention is given to identifying (and addressing) problems from correlation analysis used in the previous studies that can lead to erroneous conclusions. A new approach (using the difference between retrieved AOD and predicted sea salt aerosol optical depth, AOD diff ) is developed to explore causal links between ocean physical and biological systems and the abundance of cloud condensation nuclei (CCN) in the remote marine atmosphere. We have found that over multiple time periods, 550 nm AOD diff (sensitive to accumulation mode aerosol, which is the prime contributor to CCN) correlates well with [Chl- a ] over the productive waters of the Southern Ocean. Since [Chl- a ] can be used as a proxy of ocean biological productivity, our analysis demonstrates the role of ocean ecology in contributing CCN, thus shaping the microphysical properties of low-level marine clouds.« less

  11. 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:...

  12. 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

  13. Study of Mechanisms of Aerosol Indirect Effects on Glaciated Clouds: Progress during the Project Final Technical Report

    SciTech Connect (OSTI)

    2013-10-18

    This 3-year project has studied how aerosol pollution influences glaciated clouds. The tool applied has been an 'aerosol-cloud model'. It is a type of Cloud-System Resolving Model (CSRM) modified to include 2-moment bulk microphysics and 7 aerosol species, as described by Phillips et al. (2009, 2013). The study has been done by, first, improving the model and then performing sensitivity studies with validated simulations of a couple of observed cases from ARM. These are namely the Tropical Warm Pool International Cloud Experiment (TWP-ICE) over the tropical west Pacific and the Cloud and Land Surface Interaction Campaign (CLASIC) over Oklahoma. During the project, sensitivity tests with the model showed that in continental clouds, extra liquid aerosols (soluble aerosol material) from pollution inhibited warm rain processes for precipitation production. This promoted homogeneous freezing of cloud droplets and aerosols. Mass and number concentrations of cloud-ice particles were boosted. The mean sizes of cloud-ice particles were reduced by the pollution. Hence, the lifetime of glaciated clouds, especially ice-only clouds, was augmented due to inhibition of sedimentation and ice-ice aggregation. Latent heat released from extra homogeneous freezing invigorated convective updrafts, and raised their maximum cloud-tops, when aerosol pollution was included. In the particular cases simulated in the project, the aerosol indirect effect of glaciated clouds was twice than of (warm) water clouds. This was because glaciated clouds are higher in the troposphere than water clouds and have the first interaction with incoming solar radiation. Ice-only clouds caused solar cooling by becoming more extensive as a result of aerosol pollution. This 'lifetime indirect effect' of ice-only clouds was due to higher numbers of homogeneously nucleated ice crystals causing a reduction in their mean size, slowing the ice-crystal process of snow production and slowing sedimentation. In addition

  14. Production

    Broader source: Energy.gov [DOE]

    Algae production R&D focuses on exploring resource use and availability, algal biomass development and improvements, characterizing algal biomass components, and the ecology and engineering of cultivation systems.

  15. [Multifractal cloud properties data assessment

    SciTech Connect (OSTI)

    Gautier, C.; Ricchiazzi, P.; Peterson, P.; Lavallee, D. ); Frouin, R.; Lubin, D. ); Lovejoy, S. ); Schertzer, D. )

    1992-05-06

    Our group has been very active over the last year, analyzing a number of data sets to characterize multifractal cloud properties and assess the effects of clouds on surface radiation properties (spectral and broadband). The data sets analyzed include: AVHRR observations of clouds over the ocean, SPOT observations of clouds over the ocean, SSM/I observations of clouds over the ocean, pyranometer data with all-sky photographs, pyrgeometer data all-sky photographs, and spectral surface irradiance all-sky photographs. A number of radiative transfer computations have been performed to help in the interpretation of these observations or provide theoretical guidance for their analysis. Finally 4 number of radiative transfer models have been acquired and tested to prepare for the interpretation of ARM/CART data.

  16. Satellite determination of stratus cloud microphysical properties...

    Office of Scientific and Technical Information (OSTI)

    of liquid water path from SSMI, broadband albedo from ERBE, and cloud characteristics from ISCCP are used to study stratus regions. An average cloud liquid water path of ...

  17. Radiative Effects of Cloud Inhomogeneity and

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

    Ackerman et al. 1999), to develop cloud statistics and improve the treatment of subgrid ... and Curry 1989; Liang and Wang 1997). Statistics of Subgrid Cloud Variability We have ...

  18. Biogenic Aerosols - Effects on Climate and Clouds. Cloud Optical...

    Office of Scientific and Technical Information (OSTI)

    A good range of cloud conditions were observed from clear sky to heavy rainfall. Authors: Niple, E. R. 1 ; Scott, H. E. 1 + Show Author Affiliations Aerodyne Research, Inc., ...

  19. Operation Greenhouse. Scientific Director's report of atomic weapon tests at Eniwetok, 1951. Annex 6. 8. cloud radiation field

    SciTech Connect (OSTI)

    Koch, G.E.

    1985-04-01

    The object of this study was to measure the relationship between the spatial distribution of the radioactive fission products and the resultant radioactive field in an atomic-bomb cloud. Data obtained by the high-intensity rate meters and the jet impactors lead to the following conclusions: (1) There is a definite correlation between the particulate fission-particle density and the gamma-radiation intensity measured within the cloud; (2) The effective energy of the gamma radiation within the atomic bomb cloud is quite low, being of the order of 200 keV; (3) The structure of the atomic bomb cloud resembles a chimney with puffs of radioactive matter in the flue of the chimney; (4) The average roentgen dose accumulated by a plane passing through a cloud of the type tested in the Dog and Easy Shots 210 sec after bomb detonation is approximately 125 r. The average contamination on a plane after passing through a cloud is between 10 and 20 r/hr; no contamination could be detected within the plane; (5) The gamma-radiation effects extend beyond the limits of the particulate radioactive fission products; and, (6) The visible cloud adn the fission-product particulate cloud from the bomb do not coincide exactly; the visible cloud extended beyond the fission-product-cloud in those instances where data were obtained.

  20. Evaluating cloud retrieval algorithms with the ARM BBHRP framework

    SciTech Connect (OSTI)

    Mlawer,E.; Dunn,M.; Mlawer, E.; Shippert, T.; Troyan, D.; Johnson, K. L.; Miller, M. A.; Delamere, J.; Turner, D. D.; Jensen, M. P.; Flynn, C.; Shupe, M.; Comstock, J.; Long, C. N.; Clough, S. T.; Sivaraman, C.; Khaiyer, M.; Xie, S.; Rutan, D.; Minnis, P.

    2008-03-10

    Climate and weather prediction models require accurate calculations of vertical profiles of radiative heating. Although heating rate calculations cannot be directly validated due to the lack of corresponding observations, surface and top-of-atmosphere measurements can indirectly establish the quality of computed heating rates through validation of the calculated irradiances at the atmospheric boundaries. The ARM Broadband Heating Rate Profile (BBHRP) project, a collaboration of all the working groups in the program, was designed with these heating rate validations as a key objective. Given the large dependence of radiative heating rates on cloud properties, a critical component of BBHRP radiative closure analyses has been the evaluation of cloud microphysical retrieval algorithms. This evaluation is an important step in establishing the necessary confidence in the continuous profiles of computed radiative heating rates produced by BBHRP at the ARM Climate Research Facility (ACRF) sites that are needed for modeling studies. This poster details the continued effort to evaluate cloud property retrieval algorithms within the BBHRP framework, a key focus of the project this year. A requirement for the computation of accurate heating rate profiles is a robust cloud microphysical product that captures the occurrence, height, and phase of clouds above each ACRF site. Various approaches to retrieve the microphysical properties of liquid, ice, and mixed-phase clouds have been processed in BBHRP for the ACRF Southern Great Plains (SGP) and the North Slope of Alaska (NSA) sites. These retrieval methods span a range of assumptions concerning the parameterization of cloud location, particle density, size, shape, and involve different measurement sources. We will present the radiative closure results from several different retrieval approaches for the SGP site, including those from Microbase, the current 'reference' retrieval approach in BBHRP. At the NSA, mixed-phase clouds and

  1. 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...

  2. 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.

  3. ARM - VAP Product - rhbarscl1cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP X1...

  4. ARM - VAP Product - arscl1cloth

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

    Measurements The measurements below provided by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity...

  5. 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 Citation Details In-Document Search Title: Evaluation of high-level clouds in ...

  6. DE/SC-ARM/TR-130 Aerosol Observing System Cloud Condensation...

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

    DESC-ARMTR-130 Aerosol Observing System Cloud Condensation Nuclei Average (AOSCCNAVG) Value-Added Product Y Shi A Jefferson C Flynn July 2013 DOESC-ARMTR-130 DISCLAIMER This ...

  7. Evaluation of Mixed-Phase Cloud Microphysics Parameterizations...

    Office of Scientific and Technical Information (OSTI)

    the partitioning of condensed water into liquid droplets and ice crystals in these Arctic clouds, which affect modeled cloud phase, cloud lifetime and radiative properties. ...

  8. Preliminary Studies on the Variational Assimilation of Cloud...

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

    Studies on the Variational Assimilation of Cloud-Radiation Observations Using ARM ... A linearized cloud scheme and a radiation scheme including cloud effects have been ...

  9. MAGIC Cloud Properties from Zenith Radiance Data Final Campaign...

    Office of Scientific and Technical Information (OSTI)

    Title: MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary Cloud droplet size and optical depth are the most fundamental properties for understanding cloud ...

  10. A novel approach for introducing cloud spatial structure into...

    Office of Scientific and Technical Information (OSTI)

    A novel approach for introducing cloud spatial structure into cloud radiative transfer ... Sponsoring Org: USDOE Country of Publication: United Kingdom Language: English Word Cloud ...

  11. The role of ice nuclei recycling in the maintenance of cloud ice in Arctic mixed-phase stratocumulus

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

    Solomon, A.; Feingold, G.; Shupe, M. D.

    2015-04-21

    This study investigates the maintenance of cloud ice production in Arctic mixed phase stratocumulus in large-eddy simulations that include a prognostic ice nuclei (IN) formulation and a diurnal cycle. Balances derived from a mixed-layer model and phase analyses are used to provide insight into buffering mechanisms that maintain ice in these cloud systems. We find that for the case under investigation, IN recycling through subcloud sublimation considerably prolongs ice production over a multi-day integration. This effective source of IN to the cloud dominates over mixing sources from above or below the cloud-driven mixed layer. Competing feedbacks between dynamical mixing andmore » recycling are found to slow the rate of ice lost from the mixed layer when a diurnal cycle is simulated. The results of this study have important implications for maintaining phase partitioning of cloud ice and liquid that determine the radiative forcing of Arctic mixed-phase clouds.« less

  12. The role of ice nuclei recycling in the maintenance of cloud ice in Arctic mixed-phase stratocumulus

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

    Solomon, A.; Feingold, G.; Shupe, M. D.

    2015-09-25

    This study investigates the maintenance of cloud ice production in Arctic mixed-phase stratocumulus in large eddy simulations that include a prognostic ice nuclei (IN) formulation and a diurnal cycle. Balances derived from a mixed-layer model and phase analyses are used to provide insight into buffering mechanisms that maintain ice in these cloud systems. We find that, for the case under investigation, IN recycling through subcloud sublimation considerably prolongs ice production over a multi-day integration. This effective source of IN to the cloud dominates over mixing sources from above or below the cloud-driven mixed layer. Competing feedbacks between dynamical mixing andmore » recycling are found to slow the rate of ice lost from the mixed layer when a diurnal cycle is simulated. The results of this study have important implications for maintaining phase partitioning of cloud ice and liquid that determine the radiative forcing of Arctic mixed-phase clouds.« less

  13. ARM KAZR-ARSCL Value Added Product

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

    Jensen, Michael

    The Ka-band ARM Zenith Radars (KAZRs) have replaced the long-serving Millimeter Cloud Radars, or MMCRs. Accordingly, the primary MMCR Value Added Product (VAP), the Active Remote Sensing of CLouds (ARSCL) product, is being replaced by a KAZR-based version, the KAZR-ARSCL VAP. KAZR-ARSCL provides cloud boundaries and best-estimate time-height fields of radar moments.

  14. ARM KAZR-ARSCL Value Added Product

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

    Jensen, Michael

    2012-09-28

    The Ka-band ARM Zenith Radars (KAZRs) have replaced the long-serving Millimeter Cloud Radars, or MMCRs. Accordingly, the primary MMCR Value Added Product (VAP), the Active Remote Sensing of CLouds (ARSCL) product, is being replaced by a KAZR-based version, the KAZR-ARSCL VAP. KAZR-ARSCL provides cloud boundaries and best-estimate time-height fields of radar moments.

  15. ARM Cloud Properties Working Group: Meeting Logistics

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

    to 1630: J. Comstock - Clouds with Low Optical Water Depth (CLOWD) 1630 to 1645: B. Albrecht - Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CLAP-MBL) 1645 to ...

  16. ARM - Field Campaign - Fall 1997 Cloud IOP

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

    The primary objective of the Cloud IOP was to generate a multi-platform data set that can ... Given the diversity of cloud types sampled during the IOP, the analysis of this data set ...

  17. Researching Impact of Clouds on Solar Plants

    Office of Energy Efficiency and Renewable Energy (EERE)

    Sandia National Laboratories (SNL) researchers developed a new system to monitor how clouds affect large-scale solar photovoltaic (PV) power plants. By observing cloud shape, size and movement, the...

  18. ARM - Measurement - Cloud particle size distribution

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

    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...

  19. ARM - Measurement - Cloud particle number concentration

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

    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...

  20. Evaluating the MMF Using CloudSat

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

    its cloud Evaluate the MMF and improve its cloud simulations simulations Borrowed from Dave Randall, CSU The big picture The big picture ... ... . . Data ARM A-Train, MISR etc. ...

  1. 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

  2. Tropical Warm Pool International Cloud Experiment (TWP-ICE): Cloud and Rain Characteristics in the Australian Monsoon

    SciTech Connect (OSTI)

    PT May; C Jakob; JH Mather

    2004-05-30

    The impact of oceanic convection on its environment and the relationship between the characteristics of the convection and the resulting cirrus characteristics is still not understood. An intense airborne measurement campaign combined with an extensive network of ground-based observations is being planned for the region near Darwin, Northern Australia, during January-February, 2006, to address these questions. The Tropical Warm Pool – International Cloud Experiment (TWP-ICE) will be the first field program in the tropics that attempts to describe the evolution of tropical convection, including the large scale heat, moisture, and momentum budgets, while at the same time obtaining detailed observations of cloud properties and the impact of the clouds on the environment. The emphasis will be on cirrus for the cloud properties component of the experiment. Cirrus clouds are ubiquitous in the tropics and have a large impact on their environment but the properties of these clouds are poorly understood. A crucial product from this experiment will be a dataset suitable to provide the forcing and testing required by cloud-resolving models and parameterizations in global climate models. This dataset will provide the necessary link between cloud properties and the models that are attempting to simulate them. The experiment is a collaboration between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program, the Bureau of Meteorology (BoM), the National Aeronautics and Space Administration (NASA), the European Commission DG RTD-1.2, and several United States, Australian, Canadian, and European Universities. This experiment will be undertaken over a 4-week period in early 2006. January and February corresponds to the wet phase of the Australia monsoon. This season has been selected because, despite Darwin’s coastal location, the convection that occurs over and near Darwin at this time is largely of maritime origin with a large fetch over water

  3. ARM - VAP Product - wsicloud

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

    Productswsicloudwsicloud Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027762 [ What is this? ] Generate Citation 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 VAP Output : WSICLOUD WSI: derived, cloud numbers, area, perimeter, & more Active Dates 1995.09.20 - 2004.01.12 Originating VAP Process Whole Sky Imager Cloud Products : WSICLOUD Measurements The measurements below

  4. Unlocking the Secrets of Clouds

    Broader source: Energy.gov [DOE]

    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.

  5. 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.

  6. Properties of the electron cloud in a high-energy positron and electron storage ring

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

    Harkay, K. C.; Rosenberg, R. A.

    2003-03-20

    Low-energy, background electrons are ubiquitous in high-energy particle accelerators. Under certain conditions, interactions between this electron cloud and the high-energy beam can give rise to numerous effects that can seriously degrade the accelerator performance. These effects range from vacuum degradation to collective beam instabilities and emittance blowup. Although electron-cloud effects were first observed two decades ago in a few proton storage rings, they have in recent years been widely observed and intensely studied in positron and proton rings. Electron-cloud diagnostics developed at the Advanced Photon Source enabled for the first time detailed, direct characterization of the electron-cloud properties in amore » positron and electron storage ring. From in situ measurements of the electron flux and energy distribution at the vacuum chamber wall, electron-cloud production mechanisms and details of the beam-cloud interaction can be inferred. A significant longitudinal variation of the electron cloud is also observed, due primarily to geometrical details of the vacuum chamber. Furthermore, such experimental data can be used to provide realistic limits on key input parameters in modeling efforts, leading ultimately to greater confidence in predicting electron-cloud effects in future accelerators.« less

  7. New Mexico cloud super cooled liquid water survey final report 2009.

    SciTech Connect (OSTI)

    Beavis, Nick; Roskovensky, John K.; Ivey, Mark D.

    2010-02-01

    Los Alamos and Sandia National Laboratories are partners in an effort to survey the super-cooled liquid water in clouds over the state of New Mexico in a project sponsored by the New Mexico Small Business Assistance Program. This report summarizes the scientific work performed at Sandia National Laboratories during the 2009. In this second year of the project a practical methodology for estimating cloud super-cooled liquid water was created. This was accomplished through the analysis of certain MODIS sensor satellite derived cloud products and vetted parameterizations techniques. A software code was developed to analyze multiple cases automatically. The eighty-one storm events identified in the previous year effort from 2006-2007 were again the focus. Six derived MODIS products were obtained first through careful MODIS image evaluation. Both cloud and clear-sky properties from this dataset were determined over New Mexico. Sensitivity studies were performed that identified the parameters which most influenced the estimation of cloud super-cooled liquid water. Limited validation was undertaken to ensure the soundness of the cloud super-cooled estimates. Finally, a path forward was formulized to insure the successful completion of the initial scientific goals which include analyzing different of annual datasets, validation of the developed algorithm, and the creation of a user-friendly and interactive tool for estimating cloud super-cooled liquid water.

  8. A New WRF-Chem Treatment for Studying Regional Scale Impacts of Cloud-Aerosol Interactions in Parameterized Cumuli

    SciTech Connect (OSTI)

    Berg, Larry K.; Shrivastava, ManishKumar B.; Easter, Richard C.; Fast, Jerome D.; Chapman, Elaine G.; Liu, Ying

    2015-01-01

    A new treatment of cloud-aerosol interactions within parameterized shallow and deep convection has been implemented in WRF-Chem that can be used to better understand the aerosol lifecycle over regional to synoptic scales. The modifications to the model to represent cloud-aerosol interactions include treatment of the cloud dropletnumber mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. Thesechanges have been implemented in both the WRF-Chem chemistry packages as well as the Kain-Fritsch cumulus parameterization that has been modified to better represent shallow convective clouds. Preliminary testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS) as well as a high-resolution simulation that does not include parameterized convection. The simulation results are used to investigate the impact of cloud-aerosol interactions on the regional scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column integrated BC can be as large as -50% when cloud-aerosol interactions are considered (due largely to wet removal), or as large as +35% for sulfate in non-precipitating conditions due to the sulfate production in the parameterized clouds. The modifications to WRF-Chem version 3.2.1 are found to account for changes in the cloud drop number concentration (CDNC) and changes in the chemical composition of cloud-drop residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to WRF-Chem version 3.5, and it is anticipated that they

  9. 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.

  10. Macquarie Island Cloud and Radiation Experiment (MICRE) Science Plan

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

    82 Macquarie Island Cloud and Radiation Experiment (MICRE) Science Plan RT Marchand SP Alexander A Protat December 2015 DISCLAIMER This report was prepared as an account of work sponsored by the U.S. Government. Neither the United States nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents

  11. ARM - Publications: Science Team Meeting Documents: Clouds over the ARM SGP

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

    Network area - 3D prospective Clouds over the ARM SGP Network area - 3D prospective Genkova, Iliana University of Illinois-Champaign Long, Chuck Pacific Northwest National Laboratory Minnis, Patrick NASA Langley Research Center Heck, Patrick University of Wisconsin Khaiyer, Mandana Analytical Services and Material, Inc. The poster will present the final product of a 3-dimentional characterization of the clouds over the ARM SGP network area. We have aquired various ground-based and satellite

  12. Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations

    SciTech Connect (OSTI)

    Wu, Xiaoqing

    2014-02-25

    The works supported by this ASR project lay the solid foundation for improving the parameterization of convection and clouds in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and ARM observations to produce thermodynamically and dynamically consistent multi-year cloud and radiative properties; improve the GCM simulations of convection, clouds and radiative heating rate and fluxes using the ARM observations and CRM simulations; and understand the seasonal and annual variation of cloud systems and their impacts on climate mean state and variability. We conducted multi-year simulations over the ARM SGP site using the CRM with multi-year ARM forcing data. The statistics of cloud and radiative properties from the long-term CRM simulations were compared and validated with the ARM measurements and value added products (VAP). We evaluated the multi-year climate simulations produced by the GCM with the modified convection scheme. We used multi-year ARM observations and CRM simulations to validate and further improve the trigger condition and revised closure assumption in NCAR GCM simulations that demonstrate the improvement of climate mean state and variability. We combined the improved convection scheme with the mosaic treatment of subgrid cloud distributions in the radiation scheme of the GCM. The mosaic treatment of cloud distributions has been implemented in the GCM with the original convection scheme and enables the use of more realistic cloud amounts as well as cloud water contents in producing net radiative fluxes closer to observations. A physics-based latent heat (LH) retrieval algorithm was developed by parameterizing the physical linkages of observed hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water.

  13. 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,

  14. Vertical microphysical profiles of convective clouds as a tool for

    Office of Scientific and Technical Information (OSTI)

    obtaining aerosol cloud-mediated climate forcings (Technical Report) | SciTech Connect Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings Citation Details In-Document Search Title: Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud

  15. Engineering microbes for efficient production of chemicals (Patent...

    Office of Scientific and Technical Information (OSTI)

    that are selected during metabolic evolution and contribute to improved production of ... Country of Publication: United States Language: English Word Cloud More Like This Full ...

  16. ARM - VAP Product - mmcrmode3ge200408121cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Southern Great Plains SGP C1 Browse...

  17. ARM - VAP Product - mmcrmode3ge200404141cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations North Slope Alaska NSA C1 Browse...

  18. ARM - VAP Product - mmcrmode2ci200712011cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations North Slope Alaska NSA C1 Browse...

  19. ARM - VAP Product - mmcrmode3ge200511041cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C3...

  20. ARM - VAP Product - mmcrmode4pr200511041cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C3...

  1. ARM - VAP Product - mmcrmode3ge200608161cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C2...

  2. ARM - VAP Product - mmcrmode4pr200608161cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C2...

  3. ARM - VAP Product - mmcrmode1bl200606161cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C1...

  4. ARM - VAP Product - mmcrmode4pr200606161cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C1...

  5. ARM - VAP Product - mmcrmode1st200404151cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations North Slope Alaska NSA C1 Browse...

  6. ARM - VAP Product - mmcrmode2ci200309091cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Southern Great Plains SGP C1 Browse...

  7. ARM - VAP Product - mmcrmode2ci200608161cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C2...

  8. ARM - VAP Product - mmcrmode3ge200712011cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations North Slope Alaska NSA C1 Browse...

  9. ARM - VAP Product - mmcrmode1bl200608121cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C2...

  10. ARM - VAP Product - mmcrmode2ci200404141cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations North Slope Alaska NSA C1 Browse...

  11. ARM - VAP Product - mmcrmode3ge200606161cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C1...

  12. ARM - VAP Product - mmcrmode2ci200606161cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C1...

  13. ARM - VAP Product - mmcrmode2ci200511041cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C3...

  14. ARM - VAP Product - mmcrmode2ci200408121cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Southern Great Plains SGP C1 Browse...

  15. ARM - VAP Product - mmcrmode1bl200712011cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations North Slope Alaska NSA C1 Browse...

  16. ARM - VAP Product - mmcrmode1bl200511041cloth

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

    by this product are those considered scientifically relevant. Cloud base height Radar Doppler Radar reflectivity Vertical velocity Locations Tropical Western Pacific TWP C3...

  17. 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

  18. ARM - Value-Added Products - Status

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

    - Status Report Expand Orange | Expand Blue | Expand Green | Collapse All See Legend for Data Availability explanation. ARM - Value-Added Products - Status Last Update: March 21 2016 19:00:50 +/- Vap Name Translator Developer Frequency Tier Producer Data Availability ACRED (ARM Cloud Retrieval Ensemble Data) Shaocheng Xie Chuanfeng Zhao, Renata Mc Coy Periodically Evaluation Developer ARM Overview: Developer Description: The ARM Cloud Retrieval Ensemble Dataset (ACRED) is a multi-year cloud

  19. 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.

  20. Storm Peak Lab Cloud Property Validation

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

    Peak Lab Cloud Property Validation Experiment (STORMVEX) Operated by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for the U.S. Department of Energy, the second ARM Mobile Facility (AMF2) begins its inaugural deployment November 2010 in Steamboat Springs, Colorado, for the Storm Peak Lab Cloud Property Validation Experiment, or STORMVEX. For six months, the comprehensive suite of AMF2 instruments will obtain measurements of cloud and aerosol properties at various sites

  1. Testing a New Cirrus Cloud Parameterizaton

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

    Testing a New Cirrus Cloud Parameterization in NCAR CCM3 D. Zurovac-Jevtic, G. J. Zhang, and V. Ramanathan Center for Atmospheric Sciences Scripps 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 general circulation models (GCMs), their treatment is very crude. For example, in the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3), IWC is

  2. 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

  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 You are ...

  4. 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...

  5. 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...

  6. 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)

  7. 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...

  8. ARM - Field Campaign - Spring Cloud IOP

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

    govCampaignsSpring 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 : Spring Cloud IOP 2000.03.01 - 2000.03.26 Lead Scientist : Gerald Mace For data sets, see below. Summary The Atmospheric Radiation Measurement (ARM) Program conducted a Cloud Intensive Operational Period (IOP) in March 2000 that was the first-ever effort to document the 3-dimensional cloud field from observational data. Prior

  9. ARM - Field Campaign - Cloud Radar IOP

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

    of aerosol properties during clear-sky conditions. The ETL Radar Meteorology and Oceanography Division will field their NOAAK scanning cloud radar near the new ARM millimeter...

  10. 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.

  11. Tropical Cloud Life Cycle and Overlap Structure

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

    Tropical Cloud Life Cycle and Overlap Structure Vogelmann, Andrew Brookhaven National Laboratory Jensen, Michael Brookhaven National Laboratory Kollias, Pavlos Brookhaven National ...

  12. ARM - Midlatitude Continental Convective Clouds - Single Column...

    Office of Scientific and Technical Information (OSTI)

    - Single Column Model Forcing (xie-scmforcing) Title: ARM - Midlatitude Continental Convective Clouds - Single Column Model Forcing (xie-scmforcing) The constrained variational ...

  13. Ground-based Microwave Cloud Tomography

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

    Courtesy of Bernhard Mayer Cloud structure important to radiation - Cumulus (Benner & Evans 2001, Pincus et al. 2005), deep convection (DiGiuseppe & Tompkins 2003) - Horizontal...

  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. 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

  16. 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].

  17. VOCALS: The VAMOS Ocean-Cloud-Atmosphere-Land Study () | Data...

    Office of Scientific and Technical Information (OSTI)

    VOCALS: The VAMOS Ocean-Cloud-Atmosphere-Land Study Title: VOCALS: The VAMOS Ocean-Cloud-Atmosphere-Land Study VOCALS (VAMOS* Ocean-Cloud-Atmosphere-Land Study) is an international ...

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

    Office of Scientific and Technical Information (OSTI)

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

  19. DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING OF CLOUDS AND RADIATION USING ARM DATA, FINAL REPORT

    SciTech Connect (OSTI)

    Minnis, Patrick

    2013-06-28

    During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products and raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.

  20. A boundary-layer cloud study using Southern Great Plains Cloud and radiation testbed (CART) data

    SciTech Connect (OSTI)

    Albrecht, B.; Mace, G.; Dong, X.; Syrett, W.

    1996-04-01

    Boundary layer clouds-stratus and fairweather cumulus - are closely coupled involves the radiative impact of the clouds on the surface energy budget and the strong dependence of cloud formation and maintenance on the turbulent fluxes of heat and moisture in the boundary layer. The continuous data collection at the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site provides a unique opportunity to study components of the coupling processes associated with boundary layer clouds and to provide descriptions of cloud and boundary layer structure that can be used to test parameterizations used in climate models. But before the CART data can be used for process studies and parameterization testing, it is necessary to evaluate and validate data and to develop techniques for effectively combining the data to provide meaningful descriptions of cloud and boundary layer characteristics. In this study we use measurements made during an intensive observing period we consider a case where low-level stratus were observed at the site for about 18 hours. This case is being used to examine the temporal evolution of cloud base, cloud top, cloud liquid water content, surface radiative fluxes, and boundary layer structure. A method for inferring cloud microphysics from these parameters is currently being evaluated.

  1. 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...

  2. Tropical Cloud Properties and Radiative Heating Profiles (Dataset...

    Office of Scientific and Technical Information (OSTI)

    Tropical Cloud Properties and Radiative Heating Profiles Title: Tropical Cloud Properties ... in that it uses the microwave radiometer to scale the radiosonde column water vapor. ...

  3. USING CLOUD CLASSIFICATION TO MODEL SOLAR VARIABILITY Matthew...

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

    Hourly cloud classified satellite images are compared to multiple years of ground measured ... type of cloud or weather pattern, as classified by NOAA. Instinctively, the type of ...

  4. 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...

  5. Determination of Large-Scale Cloud Ice Water Concentration by...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Determination of Large-Scale Cloud Ice Water Concentration by Combining ... Title: Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface ...

  6. ARM: Aerosol Observing System (AOS): cloud condensation nuclei...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: Aerosol Observing System (AOS): cloud condensation nuclei data Aerosol Observing System (AOS): cloud condensation nuclei data Authors: Scott Smith ; Cynthia Salwen ; ...

  7. Humidity trends imply increased sensitivity to clouds in a warming...

    Office of Scientific and Technical Information (OSTI)

    is modulated by cloud properties; however, CRE also depends on humidity because clouds emit at wavelengths that are semi-transparent to greenhouse gases, most notably water vapour. ...

  8. ARM - Publications: Science Team Meeting Documents: Cloud Radiative...

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

    Research Facility: Part 2. The Vertical Redistribution of Radiant Energy by Clouds. ... Documentation with data of the effects of clouds on the radiant energy balance of the ...

  9. Effective Radius of Cloud Droplets Derived from Ground-based...

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

    which could eventually facilitate aerosol-cloud interactions. (Kim, Klein, Norris, JGR, 2005) SD z (m) SD LWP (g m -2 ) Efficacy of Aerosol-Cloud Interactions - ...

  10. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

  11. ARM: AOS: Cloud Condensation Nuclei Counter (Dataset) | Data...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: AOS: Cloud Condensation Nuclei Counter AOS: Cloud Condensation Nuclei Counter Authors: Scott Smith ; Cynthia Salwen ; Janek Uin ; Gunnar Senum ; Stephen Springston ; ...

  12. 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:...

  13. 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...

  14. ARM: Millimeter Wavelength Cloud Radar (MMCR): transmitted RF...

    Office of Scientific and Technical Information (OSTI)

    transmitted RF power Title: ARM: Millimeter Wavelength Cloud Radar (MMCR): transmitted RF power Millimeter Wavelength Cloud Radar (MMCR): transmitted RF power Authors: Karen ...

  15. ARM: Microwave Radiometer Retrievals (MWRRET) of Cloud Liquid...

    Office of Scientific and Technical Information (OSTI)

    Microwave Radiometer Retrievals (MWRRET) of Cloud Liquid Water and Precipitable Water Vapor Title: ARM: Microwave Radiometer Retrievals (MWRRET) of Cloud Liquid Water and ...

  16. Final Report on the Development of an Improved Cloud Microphysical...

    Office of Scientific and Technical Information (OSTI)

    Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative ... integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds ...

  17. Thin Liquid Water Clouds: Their Importance and Our Challenge...

    Office of Scientific and Technical Information (OSTI)

    Thin Liquid Water Clouds: Their Importance and Our Challenge Citation Details In-Document Search Title: Thin Liquid Water Clouds: Their Importance and Our Challenge Many of the ...

  18. Positive low cloud and dust feedbacks amplify tropical North...

    Office of Scientific and Technical Information (OSTI)

    amplify tropical North Atlantic Multidecadal Oscillation: CLOUD AND DUST FEEDBACK AND AMO Title: Positive low cloud and dust feedbacks amplify tropical North Atlantic ...

  19. Cloud microphysical relationships and their implication on entrainment...

    Office of Scientific and Technical Information (OSTI)

    Cloud microphysical relationships and their implication on entrainment and mixing mechanism for the stratocumulus clouds measured during the VOCALS project Citation Details ...

  20. 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 ...

  1. Understanding and Improving CRM and GCM Simulations of Cloud...

    Office of Scientific and Technical Information (OSTI)

    of convection, clouds and radiative heating rate and fluxes using the ARM ... as well as cloud water contents in producing net radiative fluxes closer to observations. ...

  2. Monitoring of Precipitable Water Vapor and Cloud Liquid Path...

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

    Monitoring of Precipitable Water Vapor and Cloud Liquid Path from Scanning Microwave ... used to measure atmospheric precipitable water vapor (PWV) and cloud liquid path (CLP). ...

  3. Determining Cloud Ice Water Path from High-Frequency Microwave...

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

    Determining Cloud Ice Water Path from High-Frequency Microwave Measurements G. Liu ... A better understanding of cloud water content and its large-scale distribution ...

  4. HOT HYDROGEN IN DIFFUSE CLOUDS

    SciTech Connect (OSTI)

    Cecchi-Pestellini, Cesare; Duley, Walt W.; Williams, David A. E-mail: wwduley@uwaterloo.ca

    2012-08-20

    Laboratory evidence suggests that recombination of adsorbed radicals may cause an abrupt temperature excursion of a dust grain to about 1000 K. One consequence of this is the rapid desorption of adsorbed H{sub 2} molecules with excitation temperatures of this magnitude. We compute the consequences of injection of hot H{sub 2} into cold diffuse interstellar gas at a rate of 1% of the canonical H{sub 2} formation rate. We find that the level populations of H{sub 2} in J = 3, 4, and 5 are close to observed values, and that the abundances of CH{sup +} and OH formed in reactions with hot hydrogen are close to the values obtained from observations of diffuse clouds.

  5. 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.

  6. 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.

  7. Radiative properties of ice clouds

    SciTech Connect (OSTI)

    Mitchell, D.L.; Koracin, D.; Carter, E.

    1996-04-01

    A new treatment of cirrus cloud radiative properties has been developed, based on anomalous diffraction theory (ADT), which does not parameterize size distributions in terms of an effective radius. Rather, is uses the size distribution parameters directly, and explicitly considers the ice particle shapes. There are three fundamental features which characterize this treatment: (1) the ice path radiation experiences as it travels through an ice crystal is parameterized, (2) only determines the amount of radiation scattered and absorbed, and (3) as in other treatments, the projected area of the size distribution is conserved. The first two features are unique to this treatment, since it does not convert the ice particles into equivalent volume or area spheres in order to apply Mie theory.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. Absorption of solar radiation in broken clouds

    SciTech Connect (OSTI)

    Zuev, V.E.; Titov, G.A.; Zhuravleva, T.B.

    1996-04-01

    It is recognized now that the plane-parallel model unsatisfactorily describes the transfer of radiation through broken clouds and that, consequently, the radiation codes of general circulation models (GCMs) must be refined. However, before any refinement in a GCM code is made, it is necessary to investigate the dependence of radiative characteristics on the effects caused by the random geometry of cloud fields. Such studies for mean fluxes of downwelling and upwelling solar radiation in the visible and near-infrared (IR) spectral range were performed by Zuev et al. In this work, we investigate the mean spectral and integrated absorption of solar radiation by broken clouds (in what follows, the term {open_quotes}mean{close_quotes} will be implied but not used, for convenience). To evaluate the potential effect of stochastic geometry, we will compare the absorption by cumulus (0.5 {le} {gamma} {le} 2) to that by equivalent stratus ({gamma} <<1) clouds; here {gamma} = H/D, H is the cloud layer thickness and D the characteristic horizontal cloud size. The equivalent stratus clouds differ from cumulus only in the aspect ratio {gamma}, all the other parameters coinciding.

  14. ARM - Field Campaign - Arctic Cloud Infrared Imaging

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

    govCampaignsArctic Cloud Infrared Imaging Campaign Links Field Campaign Report 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 : Arctic Cloud Infrared Imaging 2012.07.16 - 2014.07.31 Lead Scientist : Joseph Shaw For data sets, see below. Abstract The 3rd-generation Infrared Cloud Imager (ICI) instrument was deployed close to the Great White facility at the North Slope of Alaska site and operated as

  15. Albedo and transmittance of inhomogeneous stratus clouds

    SciTech Connect (OSTI)

    Zuev, V.E.; Kasyanov, E.I.; Titov, G.A.

    1996-04-01

    A highly important topic is the study of the relationship between the statistical parameters of optical and radiative charactertistics of inhomogeneous stratus clouds. This is important because the radiation codes of general circulation models need improvement, and it is important for geophysical information. A cascade model has been developed at the Goddard Space Flight Center to treat stratocumulus clouds with the simplest geometry and horizontal fluctuations of the liquid water path (optical thickness). The model evaluates the strength with which the stochastic geometry of clouds influences the statistical characteristics of albedo and the trnasmittance of solar radiation.

  16. 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

  17. 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.

  18. Cloud-Resolving Model Simulation and Mosaic Treatment of Subgrid Cloud-Radiation Interaction

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

    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

  19. X.509 Authentication/Authorization in FermiCloud

    SciTech Connect (OSTI)

    Kim, Hyunwoo; Timm, Steven

    2014-11-11

    We present a summary of how X.509 authentication and authorization are used with OpenNebula in FermiCloud. We also describe a history of why the X.509 authentication was needed in FermiCloud, and review X.509 authorization options, both internal and external to OpenNebula. We show how these options can be and have been used to successfully run scientific workflows on federated clouds, which include OpenNebula on FermiCloud and Amazon Web Services as well as other community clouds. We also outline federation options being used by other commercial and open-source clouds and cloud research projects.

  20. QER- Comment of Cloud Peak Energy Inc

    Office of Energy Efficiency and Renewable Energy (EERE)

    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.

  1. 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...

  2. Parameterizations of Cloud Microphysics and Indirect Aerosol...

    Office of Scientific and Technical Information (OSTI)

    A recent report published by the National Academy of Science states "The greatest ... 1977 and the "semi-direct" effect on cloud coverage e.g., Ackerman et al., 2000. ...

  3. 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.

  4. Posters Sensitivity of Cirrus Cloud Radiative

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

    ... Takahashi, T., and K. Kuhara. 1993. Precipitation mechanisms of cumulonimbus clouds at Pohnpei, Micronesia. Meteor. Soc. Japan 71:21-31. Takano, Y., and K. N. Liou. 1989. Radiative ...

  5. 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 *...

  6. Drizzle production in stratocumulus

    SciTech Connect (OSTI)

    Feingold, G.; Frisch, A.S.; Stevens, B.; Cotton, W.R.

    1996-04-01

    Although stratocumulus clouds are not prodigious producers of precipitation, the small amounts of drizzle they do produce have an important impact on both cloud macrophysical properties (e.g., spatial coverage, depth and liquid water content) and microphysical properties (e.g., droplet size distributions, effective radii). The radiative effects of stratocumulus are intimately connected to both these macro- and microphysical properties, and it is thus essential that we understand the mechanisms of droplet growth which generate precipitation sized droplets. Drizzle production is closely related to cloud condensation nucleus (CCN) number and size, as well as to cloud dynamics and the ability of clouds to support droplets within their bounds and allow for repeated collision-coalesence cycles. In order to address both the microphysical and dynamical aspects of drizzle formation (and their close coupling), we have adapted a large eddy simulation (LES) model to include explicit (size-resolving) microphysical treatment of the CCN and droplet spectra. By directly calculating processes such as droplet growth by condensation and stochastic collection, evaporation, and sedimentation in the LES framework, we are in a position to elucidate the drizzle formation process.

  7. 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/.

  8. Science on the Hill: Methane cloud hunting

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

    Methane cloud hunting Methane cloud hunting Los Alamos researchers go hunting for methane gas over the Four Corners area of northwest New Mexico and find a strange daily pattern. July 12, 2015 methane map Methane, the primary component of natural gas, is also a potent greenhouse gas, trapping energy in the atmosphere. Last year NASA released satellite images showing a hot spot in the area where New Mexico, Colorado, Utah and Arizona meet, prompting scientists to go in search of the sources.

  9. 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.

  10. 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.