Sample records for arm cloud radar

  1. 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

    2014-12-01T23:59:59.000Z

    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

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

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

    Borque, Paloma [McGill Univ., Montreal, QC (Canada); Giangrande, Scott [Brookhaven National Lab. (BNL), Upton, NY (United States); Kollias, Pavlos [McGill Univ., Montreal, QC (Canada)

    2014-12-01T23:59:59.000Z

    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.

  3. ARM: W-Band Scanning ARM Cloud Radar (W-SACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

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

    Widener, Kevin; Nelson, Dan; Bharadwaj, Nitin; Lindenmaier, Iosif [Andrei; Johnson, Karen

    W-Band Scanning ARM Cloud Radar (W-SACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

  4. ARM: X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

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

    Widener, Kevin; Nelson, Dan; Bharadwaj, Nitin; Lindenmaier, Iosif [Andrei; Johnson, Karen

    X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals)

  5. ARM: Ka-Band Scanning ARM Cloud Radar (KASACR) Hemispherical Sky RHI Scan (6 horizon-to-horizon scans at 30-degree azimuth intervals)

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

    Bharadwaj, Nitin; Widener, Kevin

    Ka-Band Scanning ARM Cloud Radar (KASACR) Hemispherical Sky RHI Scan (6 horizon-to-horizon scans at 30-degree azimuth intervals)

  6. Cloud Effects on Radiative Heating Rate Profiles over Darwin using ARM and A-train Radar/Lidar Observations

    SciTech Connect (OSTI)

    Thorsen, Tyler J.; Fu, Qiang; Comstock, Jennifer M.

    2013-06-11T23:59:59.000Z

    Observations of clouds from the ground-based U.S. Department of Energy Atmospheric Radiation Measurement program (ARM) and satellite-based A-train are used to compute cloud radiative forcing profiles over the ARM Darwin, Australia site. Cloud properties are obtained from both radar (the ARM Millimeter Cloud Radar (MMCR) and the CloudSat satellite in the A-train) and lidar (the ARM Micropulse lidar (MPL) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the A-train) observations. Cloud microphysical properties are taken from combined radar and lidar retrievals for ice clouds and radar only or lidar only retrievals for liquid clouds. Large, statistically significant differences of up to 1.43 K/day exist between the mean ARM and A-train net cloud radiative forcing profiles. The majority of the difference in cloud radiative forcing profiles is shown to be due to a large difference in the cloud fraction above 12 km. Above this altitude the A-train cloud fraction is significantly larger because more clouds are detected by CALIPSO than by the ground-based MPL. It is shown that the MPL is unable to observe as many high clouds as CALIPSO due to being more frequently attenuated and a poorer sensitivity even in otherwise clear-sky conditions. After accounting for cloud fraction differences and instrument sampling differences due to viewing platform we determined that differences in cloud radiative forcing due to the retrieved ice cloud properties is relatively small. This study demonstrates that A-train observations are better suited for the calculation cloud radiative forcing profiles. In addition, we find that it is necessary to supplement CloudSat with CALIPSO observations to obtain accurate cloud radiative forcing profiles since a large portion of clouds at Darwin are detected by CALIPSO only.

  7. W-band ARM Cloud Radar (WACR) Update and Status

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  8. Scanning ARM Cloud Radars Part II: Data Quality Control and Processing

    SciTech Connect (OSTI)

    Kollias, Pavlos; Jo, Ieng; Borque, Paloma; Tatarevic, Aleksandra; Lamer, Katia; Bharadwaj, Nitin; Widener, Kevin B.; Johnson, Karen; Clothiaux, Eugene E.

    2014-03-01T23:59:59.000Z

    The Scanning ARM Cloud Radars (SACR’s) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20-30 km radius from the ARM fixed and mobile sites. Here, the post-processing of the calibrated SACR measurements is discussed. First, a feature mask algorithm that objectively determines the presence of significant radar returns is described. The feature mask algorithm is based on the statistical properties of radar receiver noise. It accounts for atmospheric emission and is applicable even for SACR profiles with few or no signal-free range gates. Using the nearest-in-time atmospheric sounding, the SACR radar reflectivities are corrected for gaseous attenuation (water vapor and oxygen) using a line-by-line absorption model. Despite having a high pulse repetition frequency, the SACR has a narrow Nyquist velocity limit and thus Doppler velocity folding is commonly observed. An unfolding algorithm that makes use of a first guess for the true Doppler velocity using horizontal wind measurements from the nearest sounding is described. The retrieval of the horizontal wind profile from the Hemispherical Sky – Range Height Indicator SACR scan observations and/or nearest sounding is described. The retrieved horizontal wind profile can be used to adaptively configure SACR scan strategies that depend on wind direction. Several remaining challenges are discussed, including the removal of insect and second-trip echoes. The described algorithms significantly enhance SACR data quality and constitute an important step towards the utilization of SACR measurements for cloud research.

  9. ARM - Publications: Science Team Meeting Documents: W-Band ARM Cloud Radar

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  10. SCANNING CLOUD RADAR OBSERVATIONS AT AZORES: PRELIMINARY 3D CLOUD PRODUCTS

    E-Print Network [OSTI]

    SCANNING CLOUD RADAR OBSERVATIONS AT AZORES: PRELIMINARY 3D CLOUD PRODUCTS P. Kollias, I. Jo, A, NY www.bnl.gov ABSTRACT 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

  11. Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface Radar and Satellite Data in Support of ARM SCM Activities

    SciTech Connect (OSTI)

    Liu, Guosheng

    2013-03-15T23:59:59.000Z

    Single-column modeling (SCM) is one of the key elements of Atmospheric Radiation Measurement (ARM) research initiatives for the development and testing of various physical parameterizations to be used in general circulation models (GCMs). The data required for use with an SCM include observed vertical profiles of temperature, water vapor, and condensed water, as well as the large-scale vertical motion and tendencies of temperature, water vapor, and condensed water due to horizontal advection. Surface-based measurements operated at ARM sites and upper-air sounding networks supply most of the required variables for model inputs, but do not provide the horizontal advection term of condensed water. Since surface cloud radar and microwave radiometer observations at ARM sites are single-point measurements, they can provide the amount of condensed water at the location of observation sites, but not a horizontal distribution of condensed water contents. Consequently, observational data for the large-scale advection tendencies of condensed water have not been available to the ARM cloud modeling community based on surface observations alone. This lack of advection data of water condensate could cause large uncertainties in SCM simulations. Additionally, to evaluate GCMsâ�� cloud physical parameterization, we need to compare GCM results with observed cloud water amounts over a scale that is large enough to be comparable to what a GCM grid represents. To this end, the point-measurements at ARM surface sites are again not adequate. Therefore, cloud water observations over a large area are needed. The main goal of this project is to retrieve ice water contents over an area of 10 x 10 deg. surrounding the ARM sites by combining surface and satellite observations. Built on the progress made during previous ARM research, we have conducted the retrievals of 3-dimensional ice water content by combining surface radar/radiometer and satellite measurements, and have produced 3-D cloud ice water contents in support of cloud modeling activities. The approach of the study is to expand a (surface) point measurement to an (satellite) area measurement. That is, the study takes the advantage of the high quality cloud measurements (particularly cloud radar and microwave radiometer measurements) at the point of the ARM sites. We use the cloud ice water characteristics derived from the point measurement to guide/constrain a satellite retrieval algorithm, then use the satellite algorithm to derive the 3-D cloud ice water distributions within an 10�° (latitude) x 10�° (longitude) area. During the research period, we have developed, validated and improved our cloud ice water retrievals, and have produced and archived at ARM website as a PI-product of the 3-D cloud ice water contents using combined satellite high-frequency microwave and surface radar observations for SGP March 2000 IOP and TWP-ICE 2006 IOP over 10 deg. x 10 deg. area centered at ARM SGP central facility and Darwin sites. We have also worked on validation of the 3-D ice water product by CloudSat data, synergy with visible/infrared cloud ice water retrievals for better results at low ice water conditions, and created a long-term (several years) of ice water climatology in 10 x 10 deg. area of ARM SGP and TWP sites and then compared it with GCMs.

  12. ARM Climate Research Facility Radar Operations Plan

    SciTech Connect (OSTI)

    Voyles, JW

    2012-05-18T23:59:59.000Z

    Roles, responsibilities, and processes associated with Atmospheric Radiation Measurement (ARM) Radar Operations.

  13. ARM: Millimeter Wave Cloud Radar (MMCR), replaces mmcrcal and mmcrmoments datastreams following C-40 processor upgrade of 2003.09.09

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

    Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen

    Millimeter Wave Cloud Radar (MMCR), replaces mmcrcal and mmcrmoments datastreams following C-40 processor upgrade of 2003.09.09

  14. ARM - Measurement - Radar polarization

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  15. ARM - Measurement - Radar reflectivity

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  16. ARM Scanning Radar

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  17. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, S-band Radar (williams-s_band)

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

    Williams, Christopher

    This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

  18. ARM - Measurement - Cloud phase

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  19. ARM - Measurement - Cloud type

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

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

    Marine Ice Nuclei Collections ARM Data Discovery Browse Data Related Campaigns Marine ARM GPCI Investigation of Clouds (MAGIC) 2012.10.01, Lewis, AMF Comments? We would love to...

  1. ARM - Measurement - Cloud location

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  2. ARM - Measurement - Cloud size

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  3. NNSA Completes its Critical Radar Arming and Fuzing Test for...

    National Nuclear Security Administration (NNSA)

    its Critical Radar Arming and Fuzing Test for the W88 ALT 370 | National Nuclear Security Administration Facebook Twitter Youtube Flickr RSS People Mission Managing the Stockpile...

  4. Cloud radar Doppler spectra in drizzling stratiform clouds: 2. Observations and microphysical modeling of drizzle evolution

    E-Print Network [OSTI]

    Cloud radar Doppler spectra in drizzling stratiform clouds: 2. Observations and microphysical I, the influence of cloud microphysics and dynamics on the shape of cloud radar Doppler spectra in warm stratiform clouds was discussed. The traditional analysis of radar Doppler moments was extended

  5. ARM Cloud Retrieval Ensemble Data Set (ACRED)

    SciTech Connect (OSTI)

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

    2011-09-12T23:59:59.000Z

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

  6. X-band Scanning ARM Precipitation Radar (X-SAPR) Instrument Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N

    2012-10-29T23:59:59.000Z

    The X-band scanning ARM cloud radar (X-SAPR) is a full-hemispherical scanning polarimetric Doppler radar transmitting simultaneously in both H and V polarizations. With a 200 kW magnetron transmitter, this puts 100 kW of transmitted power for each polarization. The receiver for the X-SAPR is a Vaisala Sigmet RVP-900 operating in a coherent-on-receive mode. Three X-SAPRs are deployed around the Southern Great Plains (SGP) Central Facility in a triangular array. A fourth X-SAPR is deployed near Barrow, Alaska on top of the Barrow Arctic Research Center.

  7. ARM - Measurement - Cloud base height

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  8. ARM - Measurement - Total cloud water

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

    E-Print Network [OSTI]

    Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing broadening and drizzle growth in shallow liquid clouds remain not well understood. Detailed, cloudscale. Profiling, millimeterwavelength (cloud) radars can provide such observations. In particular, the first three

  10. ARM - Measurement - Cloud ice particle

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  11. ARM - Measurement - Cloud optical depth

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  12. ARM - Measurement - Cloud top height

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  13. MAGIC: Marine ARM GPCI Investigation of Clouds

    SciTech Connect (OSTI)

    Lewis, ER; Wiscombe, WJ; Albrecht, BA; Bland, GL; Flagg, CN; Klein, SA; Kollias, P; Mace, G; Reynolds, RM; Schwartz, SE; Siebesma, AP; Teixeira, J; Wood, R; Zhang, M

    2012-10-03T23:59:59.000Z

    The second Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF2) will be deployed aboard the Horizon Lines cargo container ship merchant vessel (M/V) Spirit for MAGIC, the Marine ARM GPCI1 Investigation of Clouds. The Spirit will traverse the route between Los Angeles, California, and Honolulu, Hawaii, from October 2012 through September 2013 (except for a few months in the middle of this time period when the ship will be in dry dock). During this field campaign, AMF2 will observe and characterize the properties of clouds and precipitation, aerosols, and atmospheric radiation; standard meteorological and oceanographic variables; and atmospheric structure. There will also be two intensive observational periods (IOPs), one in January 2013 and one in July 2013, during which more detailed measurements of the atmospheric structure will be made.

  14. ARM - Lesson Plans: Making Clouds

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  15. 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.

  16. ARM - Field Campaign - Boundary Layer Cloud IOP

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  17. ARM - Field Campaign - Fall 1997 Cloud IOP

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  18. ARM - Field Campaign - Cloud Radar IOP

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  19. Analysis of cloud layer structure in Shouxian, China using RS92 radiosonde aided by 95 GHz cloud radar

    E-Print Network [OSTI]

    Li, Zhanqing

    Analysis of cloud layer structure in Shouxian, China using RS92 radiosonde aided by 95 GHz cloud to analyze cloud vertical structure over this area by taking advantage of the first direct measurements of cloud vertical layers from the 95 GHz radar. Singlelayer, twolayer, and threelayer clouds account for 28

  20. ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):

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  1. An annual cycle of Arctic cloud characteristics observed by radar and lidar at SHEBA

    E-Print Network [OSTI]

    Shupe, Matthew

    distribution of cloud boundary heights, and occurrence of liquid phase in clouds are determined from radar-observed clouds containing liquid was 73% for the year. The least amount of liquid water phase was observed during-detected clouds. Liquid was distributed in a combination of all-liquid and mixed phase clouds, and was detected

  2. ARM - Measurement - Cloud particle number concentration

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDC documentationBarrow,ice particle ARM Data Discovery

  3. ARM - Measurement - Cloud particle size distribution

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

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  4. On the Feasibility of Precisely Measuring the Properties of a Precipitating Cloud with a Weather Radar

    E-Print Network [OSTI]

    Runnels, R.C.

    In this paper the results of an investigation are presented that are concerned with the feasibility of employing a weather radar to make precise measurements of the properties of a precipitating cloud. A schematic cloud is proposed as a model...

  5. ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:

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

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  6. C-Band Scanning ARM Precipitation Radar (C-SAPR) Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N

    2012-11-13T23:59:59.000Z

    The C-band scanning ARM precipitation radar (C-SAPR) is a scanning polarimetric Doppler radar transmitting simultaneously in both H and V polarizations. With a 350-kW magnetron transmitter, this puts 125 kW of transmitted power for each polarization. The receiver for the C-SAPR is a National Center for Atmospheric Research (NCAR) -developed Hi-Q system operating in a coherent-on-receive mode. The ARM Climate Research Facility operates two C-SAPRs; one of them is deployed near the Southern Great Plains (SGP) Central Facility near the triangular array of X-SAPRs, and the second C-SAPR is deployed at ARM’s Tropical Western Pacific (TWP) site on Manus Island in Papua New Guinea.

  7. 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.

    2008-03-10T23:59:59.000Z

    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 cloud with a low optical depth are prevalent; the radiative closure studies using Microbase demonstrated significant residuals. As an alternative to Microbase at NSA, the Shupe-Turner cloud property retrieval algorithm, aimed at improving the partitioning of cloud phase and incorporating more constrained, conditional microphysics retrievals, also has been evaluated using the BBHRP data set.

  8. Prospects of the WSR-88D Radar for Cloud Studies

    E-Print Network [OSTI]

    Melnikov, Valery M.; Zrni?, Dusan S.; Doviak, Richard J.; Chilson, Phillip B.; Mechem, David B.; Kogan, Yefim L.

    2011-04-01T23:59:59.000Z

    - flectivity field at 908 azimuth. APRIL 2011 M E L N I K O V E T A L . 863 compared measured solar radiation with model results. The Bird model (Bird and Hulstrom 1981) has been used to estimate the solar flux on the ground in the absence of clouds....S. Department of Commerce). REFERENCES Battan, L. J., 1973: Radar Observation of the Atmosphere. Uni- versity of Chicago, 324 pp. Bird, R. E., and R. L. Hulstrom, 1981: A simplified clear sky model for direct and diffuse insolation on horizontal surfaces. Solar...

  9. 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.

  10. Retrieval of optical and microphysical properties of ice clouds using Atmospheric Radiation Measurement (ARM) data 

    E-Print Network [OSTI]

    Kinney, Jacqueline Anne

    2005-11-01T23:59:59.000Z

    The research presented here retrieves the cloud optical thickness and particle effective size of cirrus clouds using surface radiation measurements obtained during the Atmospheric Radiation Measurement (ARM) field campaign. The algorithm used...

  11. Radiation Parameterization for Three-Dimensional Inhomogeneous Cirrus Clouds Applied to ARM Data and Climate Models

    SciTech Connect (OSTI)

    Kuo-Nan Liou

    2003-12-29T23:59:59.000Z

    OAK-B135 (a) We developed a 3D radiative transfer model to simulate the transfer of solar and thermal infrared radiation in inhomogeneous cirrus clouds. The model utilized a diffusion approximation approach (four-term expansion in the intensity) employing Cartesian coordinates. The required single-scattering parameters, including the extinction coefficient, single-scattering albedo, and asymmetry factor, for input to the model, were parameterized in terms of the ice water content and mean effective ice crystal size. The incorporation of gaseous absorption in multiple scattering atmospheres was accomplished by means of the correlated k-distribution approach. In addition, the strong forward diffraction nature in the phase function was accounted for in each predivided spatial grid based on a delta-function adjustment. The radiation parameterization developed herein is applied to potential cloud configurations generated from GCMs to investigate broken clouds and cloud-overlapping effects on the domain-averaged heating rate. Cloud inhomogeneity plays an important role in the determination of flux and heating rate distributions. Clouds with maximum overlap tend to produce less heating than those with random overlap. Broken clouds show more solar heating as well as more IR cooling as compared to a continuous cloud field (Gu and Liou, 2001). (b) We incorporated a contemporary radiation parameterization scheme in the UCLA atmospheric GCM in collaboration with the UCLA GCM group. In conjunction with the cloud/radiation process studies, we developed a physically-based cloud cover formation scheme in association with radiation calculations. The model clouds were first vertically grouped in terms of low, middle, and high types. Maximum overlap was then used for each cloud type, followed by random overlap among the three cloud types. Fu and Liou's 1D radiation code with modification was subsequently employed for pixel-by-pixel radiation calculations in the UCLA GCM. We showed that the simulated cloud cover and OLR fields without special tuning are comparable to those of ISCCP dataset and the results derived from radiation budget experiments. Use of the new radiation and cloud schemes enhances the radiative warming in the middle to upper tropical troposphere and alleviates the cold bias in the UCLA atmospheric GCM. We also illustrated that ice crystal size and cloud inhomogeneous are significant factors affecting the radiation budgets at the top of the atmosphere and the surface (Gu et al. 2003). (c) An innovative approach has been developed to construct a 3D field of inhomogeneous clouds in general and cirrus in particular in terms of liquid/ice water content and particle size on the basis of a unification of satellite and ground-based cloud radar data. Satellite remote sensing employing the current narrow-band spectro-radiometers has limitation and only the vertically integrated cloud parameters (optical depth and mean particle size) can be determined. However, by combining the horizontal cloud mapping inferred from satellites with the vertical structure derived from the profiling Doppler cloud radar, a 3D cloud field can be constructed. This represents a new conceptual approach to 3D remote sensing and imaging and offers a new perspective in observing the cloud structure. We applied this novel technique to AVHRR/NOAA satellite and mm-wave cloud radar data obtained from the ARM achieve and assessed the 3D cirrus cloud field with the ice crystal size distributions independently derived from optical probe measurements aboard the University of North Dakota Citation. The retrieved 3D ice water content and mean effective ice crystal size involving an impressive cirrus cloud occurring on April 18, 1997, are shown to be comparable to those derived from the analysis of collocated and coincident in situ aircraft measurements (Liou et al. 2002). (d) Detection of thin cirrus with optical depths less than 0.5, particularly those occurring i n the tropics remains a fundamental problem in remote sensing. We developed a new detection scheme for the

  12. ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:

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

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  13. ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM2,govCampaignsAircraftCloud OD Sensor

  14. ARM - Field Campaign - Biogenic Aerosols - Effects on Clouds and Climate:

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

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  15. ARM - Publications: Science Team Meeting Documents: Interpretation of cloud

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

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  16. GFDL ARM Project Technical Report: Using ARM Observations to Evaluate Cloud and Convection Parameterizations & Cloud-Convection-Radiation Interactions in the GFDL Atmospheric General Circulation Model

    SciTech Connect (OSTI)

    V. Ramaswamy; L. J. Donner; J-C. Golaz; S. A. Klein

    2010-06-17T23:59:59.000Z

    This report briefly summarizes the progress made by ARM postdoctoral fellow, Yanluan Lin, at GFDL during the period from October 2008 to present. Several ARM datasets have been used for GFDL model evaluation, understanding, and improvement. This includes a new ice fall speed parameterization with riming impact and its test in GFDL AM3, evaluation of model cloud and radiation diurnal and seasonal variation using ARM CMBE data, model ice water content evaluation using ARM cirrus data, and coordination of the TWPICE global model intercomparison. The work illustrates the potential and importance of ARM data for GCM evaluation, understanding, and ultimately, improvement of GCM cloud and radiation parameterizations. Future work includes evaluation and improvement of the new dynamicsPDF cloud scheme and aerosol activation in the GFDL model.

  17. Use of the ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes & Aerosol-Cloud Interaction

    SciTech Connect (OSTI)

    Chiu, Jui-Yuan Christine [University of Reading] [University of Reading

    2014-04-10T23:59:59.000Z

    This project focuses on cloud-radiation processes in a general three-dimensional cloud situation, with particular emphasis on cloud optical depth and effective particle size. The proposal has two main parts. Part one exploits the large number of new wavelengths offered by the Atmospheric Radiation Measurement (ARM) zenith-pointing ShortWave Spectrometer (SWS), to develop better retrievals not only of cloud optical depth but also of cloud particle size. We also take advantage of the SWS’ high sampling resolution to study the “twilight zone” around clouds where strong aerosol-cloud interactions are taking place. Part two involves continuing our cloud optical depth and cloud fraction retrieval research with ARM’s 2-channel narrow vield-of-view radiometer and sunphotometer instrument by, first, analyzing its data from the ARM Mobile Facility deployments, and second, making our algorithms part of ARM’s operational data processing.

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

    SciTech Connect (OSTI)

    Wang, Zhien

    2010-06-29T23:59:59.000Z

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

  19. ARM - Field Campaign - 2001 Multi-Frequency Radar IOP

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

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

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

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  1. W-Band ARM Cloud Radar - Specifications and Design

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

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  2. A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II: Cloud Fraction and Surface Radiative Forcing

    E-Print Network [OSTI]

    Dong, Xiquan

    at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility and for single-layered low (0­3 km), middle (3­6 km), and high clouds ( 6 km) using ARM SCF ground-based paired-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties

  3. Long-term Observations of the Convective Boundary Layer Using Insect Radar Returns at the SGP ARM Climate Research Facility

    SciTech Connect (OSTI)

    Chandra, A S; Kollias, P; Giangrande, S E; Klein, S A

    2009-08-20T23:59:59.000Z

    A long-term study of the turbulent structure of the convective boundary layer (CBL) at the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Climate Research Facility is presented. Doppler velocity measurements from insects occupying the lowest 2 km of the boundary layer during summer months are used to map the vertical velocity component in the CBL. The observations cover four summer periods (2004-08) and are classified into cloudy and clear boundary layer conditions. Profiles of vertical velocity variance, skewness, and mass flux are estimated to study the daytime evolution of the convective boundary layer during these conditions. A conditional sampling method is applied to the original Doppler velocity dataset to extract coherent vertical velocity structures and to examine plume dimension and contribution to the turbulent transport. Overall, the derived turbulent statistics are consistent with previous aircraft and lidar observations. The observations provide unique insight into the daytime evolution of the convective boundary layer and the role of increased cloudiness in the turbulent budget of the subcloud layer. Coherent structures (plumes-thermals) are found to be responsible for more than 80% of the total turbulent transport resolved by the cloud radar system. The extended dataset is suitable for evaluating boundary layer parameterizations and testing large-eddy simulations (LESs) for a variety of surface and cloud conditions.

  4. Ice iron/sodium film as cause for high noctilucent cloud radar reflectivity

    E-Print Network [OSTI]

    Bellan, Paul M.

    Ice iron/sodium film as cause for high noctilucent cloud radar reflectivity P. M. Bellan1 Received] Noctilucent clouds, tiny cold electrically charged ice grains located at about 85 km altitude, exhibit by assuming the ice grains are coated by a thin metal film; substantial evidence exists indicating

  5. DOE/SC-ARM-13-008 First ARM/ASR Radar Workshop: Workshop

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

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

    SciTech Connect (OSTI)

    Luke,E.; Kollias, P.

    2007-08-06T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Wu, Xiaoqing

    2014-02-25T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2012-01-19T23:59:59.000Z

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

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

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

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

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

  10. DOE/SC-ARM-12-006 ARM Climate Research Facility Radar Operations Plan

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  11. DOE/SC-ARM-12-009 ARM Radar Organization JW Voyles

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  12. DOE/SC-ARM-12-010 Science Goals for the ARM Recovery Act Radars

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

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  13. Comparison between active sensor and radiosonde cloud boundaries over the ARM Southern Great Plains site

    E-Print Network [OSTI]

    to test the strengths and limitations of cloud boundary retrievals from radiosonde profiles, 4 yearsComparison between active sensor and radiosonde cloud boundaries over the ARM Southern Great Plains radiosonde-based methods applied to 200 m resolution profiles obtained at the same site. The lidar

  14. Constructing a Merged Cloud-Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll

    SciTech Connect (OSTI)

    Feng, Zhe; McFarlane, Sally A.; Schumacher, Courtney; Ellis, Scott; Comstock, Jennifer M.; Bharadwaj, Nitin

    2014-05-16T23:59:59.000Z

    To improve understanding of the convective processes key to the Madden-Julian-Oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and Atmospheric Radiation Measurement MJO Investigation Experiment (AMIE) collected four months of observations from three radars, the S-band Polarization Radar (S-Pol), the C-band Shared Mobile Atmospheric Research & Teaching Radar (SMART-R), and Ka-band Zenith Radar (KAZR) on Addu Atoll in the tropical Indian Ocean. This study compares the measurements from the S-Pol and SMART-R to those from the more sensitive KAZR in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars. Frequency comparisons for precipitating convective clouds and non-precipitating high clouds agree much better than non-precipitating low clouds for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high cloud tops by 0.3 to 1.1 km, while S-Pol underestimates cloud tops by less than 0.4 km for these cloud types. S-Pol shows excellent dynamic range in detecting various types of clouds and therefore its data are well suited for characterizing the evolution of the 3D cloud structures, complementing the profiling KAZR measurements. For detecting non-precipitating low clouds and thin cirrus clouds, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates cloud top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR cloud top heights is described, and a merged radar dataset is produced to provide improved cloud boundary estimates, microphysics and radiative heating retrievals.

  15. Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data

    E-Print Network [OSTI]

    Stoffelen, Ad

    Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data ERWIN L. A. WOLTERS, ROBERT A. ROEBELING, AND ARNOUT J. FEIJT Royal Netherlands 2007) ABSTRACT Three cloud-phase determination algorithms from passive satellite imagers are explored

  16. Arctic-Winter Climatology and Radiative Effects of Clouds and Aerosols Based on Lidar and Radar Measurements at PEARL

    E-Print Network [OSTI]

    Eloranta, Edwin W.

    Arctic-Winter Climatology and Radiative Effects of Clouds and Aerosols Based on Lidar and Radar Atmospheric Radiative Transfer (SBDART) code. Results on the climatology and radiative effects of clouds, arctic regions are the site of interactions between aerosols, clouds, radiation and precipitations

  17. arm remote clouds: Topics by E-print Network

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

    with the Milky Way galaxy. Using the Parkes Galactic All-Sky Survey (GASS) of atomic hydrogen we explore the role of drag on the evolution of the so-called Leading Arm (LA). We...

  18. Constructing a Merged CloudPrecipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll

    E-Print Network [OSTI]

    of observations from three radars--the S-band dual-polarization Doppler radar (S-Pol), the C-band Shared Mobile, and radiative heating rate retrievals. With this dataset the full spectrum of tropical convective clouds during, U.S. Department of Energy, Washington, D.C. Corresponding author address: Dr. Zhe Feng, Pacific

  19. Evaluation of A New Mixed-Phase Cloud Microphysics Parameterization with the NCAR Climate Atmospheric Model (CAM3) and ARM Observations Fourth Quarter 2007 ARM Metric Report

    SciTech Connect (OSTI)

    X Liu; SJ Ghan; S Xie; J Boyle; SA Klein

    2007-09-30T23:59:59.000Z

    Mixed-phase clouds are composed of a mixture of cloud droplets and ice crystals. The cloud microphysics in mixed-phase clouds can significantly impact cloud optical depth, cloud radiative forcing, and cloud coverage. However, the treatment of mixed-phase clouds in most current climate models is crude and the partitioning of condensed water into liquid droplets and ice crystals is prescribed as temperature dependent functions. In our previous 2007 ARM metric reports a new mixed-phase cloud microphysics parameterization (for ice nucleation and water vapor deposition) was documented and implemented in the NCAR Community Atmospheric Model Version 3 (CAM3). The new scheme was tested against the Atmospheric Radiation Measurement (ARM) Mixed-phase Arctic Cloud Experiment (M-PACE) observations using the single column modeling and short-range weather forecast approaches. In this report this new parameterization is further tested with CAM3 in its climate simulations. It is shown that the predicted ice water content from CAM3 with the new parameterization is in better agreement with the ARM measurements at the Southern Great Plain (SGP) site for the mixed-phase clouds.

  20. A Comparison of ARM Cloud Radar Profiles with MMF Simulated Radar Profiles

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032) -Less isNFebruaryOctober 2, AlgeriaQ1 Q2 Q3(SC) ANeutronPastAARM

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMs toairat the ARM

  2. Continuous Profiles of Cloud Microphysical Properties for the Fixed Atmospheric Radiation Measurement Sites

    SciTech Connect (OSTI)

    Jensen, M; Jensen, K

    2006-06-01T23:59:59.000Z

    The Atmospheric Radiation Measurement (ARM) Program defined a specific metric for the third quarter of Fiscal Year 2006 to produce and refine a one-year continuous time series of cloud microphysical properties based on cloud radar measurements for each of the fixed ARM sites. To accomplish this metric, we used a combination of recently developed algorithms that interpret radar reflectivity profiles, lidar backscatter profiles, and microwave brightness temperatures into the context of the underlying cloud microphysical structure.

  3. Application of Stochastic Radiative Transfer Theory to the ARM Cloud-Radiative Parameterization Problem

    SciTech Connect (OSTI)

    Dana E. Veron

    2012-04-09T23:59:59.000Z

    This project had two primary goals: (1) development of stochastic radiative transfer as a parameterization that could be employed in an AGCM environment, and (2) exploration of the stochastic approach as a means for representing shortwave radiative transfer through mixed-phase layer clouds. To achieve these goals, climatology of cloud properties was developed at the ARM CART sites, an analysis of the performance of the stochastic approach was performed, a simple stochastic cloud-radiation parameterization for an AGCM was developed and tested, a statistical description of Arctic mixed phase clouds was developed and the appropriateness of stochastic approach for representing radiative transfer through mixed-phase clouds was assessed. Significant progress has been made in all of these areas and is detailed in the final report.

  4. NOTES AND CORRESPONDENCE CloudSat as a Global Radar Calibrator

    E-Print Network [OSTI]

    Protat, Alain

    Research, Melbourne, Victoria, Australia 1 Laboratoire Atmosphe`re, Milieux, et Observations Spatiales, Ve is the case). The power of using CloudSat as a global radar calibrator is demonstrated using the Atmospheric, Melbourne, VIC 3008, Australia. E-mail: a.protat@bom.gov.au MARCH 2011 N O T E S A N D C O R R E S P O N D E

  5. Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part II: Multi-layered cloud

    SciTech Connect (OSTI)

    Morrison, H; McCoy, R B; Klein, S A; Xie, S; Luo, Y; Avramov, A; Chen, M; Cole, J; Falk, M; Foster, M; Genio, A D; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; McFarquhar, G; Poellot, M; Shipway, B; Shupe, M; Sud, Y; Turner, D; Veron, D; Walker, G; Wang, Z; Wolf, A; Xu, K; Yang, F; Zhang, G

    2008-02-27T23:59:59.000Z

    Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a deep, multi-layered, mixed-phase cloud system observed during the ARM Mixed-Phase Arctic Cloud Experiment. This cloud system was associated with strong surface turbulent sensible and latent heat fluxes as cold air flowed over the open Arctic Ocean, combined with a low pressure system that supplied moisture at mid-level. The simulations, performed by 13 single-column and 4 cloud-resolving models, generally overestimate the liquid water path and strongly underestimate the ice water path, although there is a large spread among the models. This finding is in contrast with results for the single-layer, low-level mixed-phase stratocumulus case in Part I of this study, as well as previous studies of shallow mixed-phase Arctic clouds, that showed an underprediction of liquid water path. The overestimate of liquid water path and underestimate of ice water path occur primarily when deeper mixed-phase clouds extending into the mid-troposphere were observed. These results suggest important differences in the ability of models to simulate Arctic mixed-phase clouds that are deep and multi-layered versus shallow and single-layered. In general, models with a more sophisticated, two-moment treatment of the cloud microphysics produce a somewhat smaller liquid water path that is closer to observations. The cloud-resolving models tend to produce a larger cloud fraction than the single-column models. The liquid water path and especially the cloud fraction have a large impact on the cloud radiative forcing at the surface, which is dominated by the longwave flux for this case.

  6. ARM - Field Campaign - Remote Cloud Sensing (RCS) Field Evaluation

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

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  7. ARM - Field Campaign - Remote Cloud Sensing (RCS) Field Evaluation

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization DiversityPolarization Radar govCampaignsRain Microphysics

  8. ARM - Field Campaign - SUbsonic Aircraft: Contrail & Cloud Effects Special

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

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323

  10. Cloud Occurrence Frequency at the Barrow, Alaska, ARM Climate Research Facility for 2008 Third Quarter 2009 ARM and Climate Change Prediction Program Metric Report

    SciTech Connect (OSTI)

    M Jensen; K Johnson; JH Mather

    2009-07-14T23:59:59.000Z

    Clouds represent a critical component of the Earth’s atmospheric energy balance as a result of their interactions with solar and terrestrial radiation and a redistribution of heat through convective processes and latent heating. Despite their importance, clouds and the processes that control their development, evolution and lifecycle remain poorly understood. Consequently, the simulation of clouds and their associated feedbacks is a primary source of inter-model differences in equilibrium climate sensitivity. An important step in improving the representation of cloud process simulations is an improved high-resolution observational data set of the cloud systems including their time evolution. The first order quantity needed to understand the important role of clouds is the height of cloud occurrence and how it changes as a function of time. To this end, the Atmospheric Radiation Measurement (ARM) Climate Research Facilities (ACRF) suite of instrumentation has been developed to make the observations required to improve the representation of cloud systems in atmospheric models.

  11. ARM - Field Campaign - Azores: Clouds, Aerosol and Precipitation in the

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

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  12. ARM - Field Campaign - Colorado: The Storm Peak Lab Cloud Property

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8LigovCampaignsCLEX-5 CampaignSP2 Deployment at StormVEx ARM

  13. ARM - Field Campaign - MASRAD: Cloud Condensate Nuclei Chemistry

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL) Campaign Links M-PACE Website ARM

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- PolarizationgovCampaignsSummer Single Column Model IOP ARM(PROBE)govCampaignsThin

  15. ARM - Publications: Science Team Meeting Documents: A Climatology of Clouds

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheACloudStatus,New ConceptsARMand Radiative

  16. ARM - Publications: Science Team Meeting Documents: Cirrus Cloud

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMs to

  17. ARM - Publications: Science Team Meeting Documents: Cloud Property

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMs toair

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMs toairat the

  19. ARM - Publications: Science Team Meeting Documents: Clouds and radiation in

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMs toairat thethe

  20. ARM - Publications: Science Team Meeting Documents: Clouds in the Darwin

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMs toairat

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMsModel

  2. ARM - Publications: Science Team Meeting Documents: Increasing Cloud

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

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  3. ARM - Publications: Science Team Meeting Documents: Tropical Cloud Overlap

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

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  4. ARM - Field Campaign - Cloud LAnd Surface Interaction Campaign (CLASIC)

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

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  5. ARM - Field Campaign - FIRE-Arctic Cloud Experiment/SHEBA

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

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  6. ARM - Field Campaign - Mixed-Phase Arctic Cloud Experiment

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL)govCampaignsMixed-Phase Arctic Cloud Experiment

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

    SciTech Connect (OSTI)

    Minnis, Patrick [NASA Langley Research Center, Hampton, VA

    2013-06-28T23:59:59.000Z

    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.

  8. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, 449 MHz Profiler(williams-449_prof)

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

    Williams, Christopher; Jensen, Mike

    This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

  9. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Vertical Air Motion (williams-vertair)

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

    Williams, Christopher; Jensen, Mike

    This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

  10. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Parcivel Disdrometer (williams-disdro)

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

    Williams, Christopher; Jensen, Mike

    This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

  11. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Surface Meteorology (williams-surfmet)

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

    Williams, Christopher; Jensen, Mike

    This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forof several GCMs toairatNetwork

  13. DOE/SC-ARM-12-020 MAGIC: Marine ARM GPCI Investigation of Clouds

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract Management Fermi SitePARTOffice ofHale Plan24,7,INL is6 ARM20 MAGIC:

  14. ARM - Employment Opportunities Article

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

    August 19, 2014 Employment Opportunities Radar Engineer for ARM Facility at PNNL Bookmark and Share Pacific Northwest National Laboratory is currently seeking a radar engineer...

  15. ARM - Employment Opportunities Article

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

    7, 2014 Employment Opportunities LANL Seeking Radar Engineer for ARM Facility Bookmark and Share Los Alamos National Laboratory (LANL) is currently seeking a radar engineer...

  16. Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave radiometer data are systematically compared to models to quantify and

    E-Print Network [OSTI]

    Hogan, Robin

    Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave a systematic evaluation of clouds in forecast models. Clouds and their associated microphysical processes for end users of weather forecasts, who may be interested not only in cloud cover, but in other variables

  17. ARM - Midlatitude Continental Convective Clouds (comstock-hvps)

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

    Jensen, Mike; Comstock, Jennifer; 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.

  18. OAK 270 - The use of Lidar/radiometer (LIRAD) in the ARM program to obtain optical properties and microphysics of high and midlevel clouds

    SciTech Connect (OSTI)

    C.M.R. Platt; R.T. Austin; S.A. Young; and G.L. Stephens

    2002-12-13T23:59:59.000Z

    OAK 270 - The use of Lidar/Radiometer (LIRAD) in the ARM program to obtain optical properties and microphysics of high and midlevel clouds

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

    SciTech Connect (OSTI)

    Klein, S A; McCoy, R B; Morrison, H; Ackerman, A; Avramov, A; deBoer, G; Chen, M; Cole, J; DelGenio, A; Golaz, J; Hashino, T; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; Luo, Y; McFarquhar, G; Menon, S; Neggers, R; Park, S; Poellot, M; von Salzen, K; Schmidt, J; Sednev, I; Shipway, B; Shupe, M; Spangenberg, D; Sud, Y; Turner, D; Veron, D; Falk, M; Foster, M; Fridlind, A; Walker, G; Wang, Z; Wolf, A; Xie, S; Xu, K; Yang, F; Zhang, G

    2008-02-27T23:59:59.000Z

    Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics indicate that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is some evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics. This case study, which has been well observed from both aircraft and ground-based remote sensors, could be a benchmark for model simulations of mixed-phase clouds.

  20. Use of the ARM Measurement of Spectral Zenith Radiance For Better Understanding Of 3D Cloud-Radiation Processes and Aerosol-Cloud Interaction

    SciTech Connect (OSTI)

    D. Jui-Yuan Chiu

    2010-10-19T23:59:59.000Z

    Our proposal focuses on cloud-radiation processes in a general 3D cloud situation, with particular emphasis on cloud optical depth and effective particle size. We also focus on zenith radiance measurements, both active and passive. The proposal has three main parts. Part One exploits the �¢����solar-background�¢��� mode of ARM lidars to allow them to retrieve cloud optical depth not just for thin clouds but for all clouds. This also enables the study of aerosol cloud interactions with a single instrument. Part Two exploits the large number of new wavelengths offered by ARM�¢����s zenith-pointing ShortWave Spectrometer (SWS), especially during CLASIC, to develop better retrievals not only of cloud optical depth but also of cloud particle size. We also propose to take advantage of the SWS�¢���� 1 Hz sampling to study the �¢����twilight zone�¢��� around clouds where strong aerosol-cloud interactions are taking place. Part Three involves continuing our cloud optical depth and cloud fraction retrieval research with ARM�¢����s 2NFOV instrument by, first, analyzing its data from the AMF-COPS/CLOWD deployment, and second, making our algorithms part of ARM�¢����s operational data processing.

  1. GALACTIC ALL-SKY SURVEY HIGH-VELOCITY CLOUDS IN THE REGION OF THE MAGELLANIC LEADING ARM

    SciTech Connect (OSTI)

    For, Bi-Qing; Staveley-Smith, Lister [International Centre for Radio Astronomy Research, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 (Australia)] [International Centre for Radio Astronomy Research, University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009 (Australia); McClure-Griffiths, N. M., E-mail: biqing.for@uwa.edu.au [Australia Telescope National Facility, CSIRO Astronomy and Space Science, PO Box 76, Epping, NSW 1710 (Australia)

    2013-02-10T23:59:59.000Z

    We present a catalog of high-velocity clouds in the region of the Magellanic Leading Arm. The catalog is based on neutral hydrogen (H I) observations from the Parkes Galactic All-Sky Survey. Excellent spectral resolution allows clouds with narrow-line components to be resolved. The total number of detected clouds is 419. We describe the method of cataloging and present the basic parameters of the clouds. We discuss the general distribution of the high-velocity clouds and classify the clouds based on their morphological type. The presence of a significant number of head-tail clouds and their distribution in the region is discussed in the context of Magellanic System simulations. We suggest that ram-pressure stripping is a more important factor than tidal forces for the morphology and formation of the Magellanic Leading Arm and that different environmental conditions might explain the morphological difference between the Magellanic Leading Arm and Magellanic Stream. We also discuss a newly identified population of clouds that forms the LA IV and a new diffuse bridge-like feature connecting the LA II and III complexes.

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

    SciTech Connect (OSTI)

    Klein, Stephen A.; McCoy, Renata B.; Morrison, Hugh; Ackerman, Andrew S.; Avramov, Alexander; de Boer, Gijs; Chen, Mingxuan; Cole, Jason N.S.; Del Genio, Anthony D.; Falk, Michael; Foster, Michael J.; Fridlind, Ann; Golaz, Jean-Christophe; Hashino, Tempei; Harrington, Jerry Y.; Hoose, Corinna; Khairoutdinov, Marat F.; Larson, Vincent E.; Liu, Xiaohong; Luo, Yali; McFarquhar, Greg M.; Menon, Surabi; Neggers, Roel A. J.; Park, Sungsu; Poellot, Michael R.; Schmidt, Jerome M.; Sednev, Igor; Shipway, Ben J.; Shupe, Matthew D.; Spangenberg, Douglas A.; Sud, Yogesh C.; Turner, David D.; Veron, Dana E.; von Salzen, Knut; Walker, Gregory K.; Wang, Zhien; Wolf, Audrey B.; Xie, Shaocheng; Xu, Kuan-Man; Yang, Fanglin; Zhang, Gong

    2009-02-02T23:59:59.000Z

    Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed average liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the average mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics suggest that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics.

  3. Stratus cloud structure from MM-radar transects and satellite images: scaling properties and artifact detection with semi-discrete wavelet analysis

    SciTech Connect (OSTI)

    Davis, A. B. (Anthony B.); Petrov, N. P. (Nikola P.); Clothiaux, E. E. (Eugene E.); Marshak, A. (Alexander)

    2002-01-01T23:59:59.000Z

    Spatial and/or temporal variabilities of clouds is of paramount importance for at least two in tensely researched sub-problems in global and regional climate modeling: (1) cloud-radiation interaction where correlations can trigger 3D radiative transfer effects; and (2) dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets as a simple yet powerful way of quantifying cloud variability. More precisely, we use 'semi-discrete' wavelet transforms which, at least in the present statistical applications, have advantages over both its continuous and discrete counterparts found in the bulk of the wavelet literature. With the particular choice of normalization we adopt, the scale-dependence of the variance of the wavelet coefficients (i.e,, the wavelet energy spectrum) is always a better discriminator of transition from 'stationary' to 'nonstationary' behavior than conventional methods based on auto-correlation analysis, second-order structure function (a.k.a. the semi-variogram), or Fourier analysis. Indeed, the classic statistics go at best from monotonically scale- or wavenumber-dependent to flat at such a transition; by contrast, the wavelet spectrum changes the sign of its derivative with respect to scale. We apply 1D and 2D semi-discrete wavelet transforms to remote sensing data on cloud structure from two sources: (1) an upward-looking milli-meter cloud radar (MMCR) at DOE's climate observation site in Oklahoma deployed as part of the Atmospheric Radiation Measurement (ARM) Progrm; and (2) DOE's Multispectral Thermal Imager (MTI), a high-resolution space-borne instrument in sunsynchronous orbit that is described in sufficient detail for our present purposes by Weber et al. (1999). For each type of data, we have at least one theoretical prediction - with empirical validation already in existence - for a power-law relation for wavelet statistics with respect to scale. This is what is expected in physical (i.e., finite scaling range) fractal phenomena. In particular, we find long-range correlations in cloud structure coming from the important nonstationary regime. More surprisingly, we also uncover artifacts the data that are traceable either to instrumental noise (in the satellite data) or to smoothing assumptions (in the MMCR data processing). Finally, we discuss the potentially damaging ramifications the smoothing artifact can have on both cloud-radiation and cloud-modeling studies using MMCR data.

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

    SciTech Connect (OSTI)

    Xie, Shaocheng; McCoy, Renata; Zhang, Yunyan

    2012-10-25T23:59:59.000Z

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

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

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

    Xie, Shaocheng; McCoy, Renata; Zhang, Yunyan

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

  6. B,V Photometry of Variable Stars in the Northeast Arm of the Small Magellanic Cloud

    E-Print Network [OSTI]

    Brian Sharpee; Michele Stark; Barton Pritzl; Horace Smith; Nancy Silbermann; Ronald Wilhelm; Alistair Walker

    2002-02-22T23:59:59.000Z

    B and V photometry has been obtained for variable stars in the northeast arm of the Small Magellanic Cloud (SMC). Periods and lightcurves have been determined for 237 periodic variables, including 201 Cepheids, 68 of which are newly discovered. Fundamental mode Cepheids and first overtone mode Cepheids are generally well separated in the B,V color-magnitude diagram, with the latter having bluer mean colors than the former. The Cepheid period-color relationship for this outlying SMC field is indistinguishable from that seen in more centrally located SMC fields, and is bluer than theoretical predictions. The red edge to the populated portion of the instability strip shifts to bluer colors for fainter Cepheids. There is support from our sample for a previously reported steepening in the slope of the period-luminosity relation for fundamental mode Cepheids near a period of 2 days. The Cepheids of the northeast arm may be closer to us than are those of the main body of the SMC, but the difference is smaller than or equal to about 4 kpc, comparable to the tidal radius of the SMC.

  7. COLLABORATIVE RESEARCH:USING ARM OBSERVATIONS & ADVANCED STATISTICAL TECHNIQUES TO EVALUATE CAM3 CLOUDS FOR DEVELOPMENT OF STOCHASTIC CLOUD-RADIATION

    SciTech Connect (OSTI)

    Somerville, Richard

    2013-08-22T23:59:59.000Z

    The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key step in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been a collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen).

  8. Atmospheric Radiation Measurement (ARM) Data from Los Angeles, California, to Honolulu, Hawaii for the Marine ARM GPCI Investigation of Clouds (MAGIC) Field Campaign (an AMF2 Deployment)

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

    From October 2012 through September 2013, the second ARM Mobile Facility (AMF2) was deployed on the container ship Spirit, operated by Horizon Lines, for the Marine ARM GPCI* Investigation of Clouds (MAGIC) field campaign. During approximately 20 round trips between Los Angeles, California, and Honolulu, Hawaii, AMF2 obtained continuous on-board measurements of cloud and precipitation, aerosols, and atmospheric radiation; surface meteorological and oceanographic variables; and atmospheric profiles from weather balloons launched every six hours. During two two-week intensive observational periods in January and July 2013, additional instruments were deployed and balloon soundings were be increased to every three hours. These additional data provided a more detailed characterization of the state of the atmosphere and its daily cycle during two distinctly different seasons. The primary objective of MAGIC was to improve the representation of the stratocumulus-to-cumulus transition in climate models. AMF2 data documented the small-scale physical processes associated with turbulence, convection, and radiation in a variety of marine cloud types.

  9. Evaluation of Mixed-Phase Cloud Microphysics Parameterizations with the NCAR Single Column Climate Model (SCAM) and ARM Observations

    SciTech Connect (OSTI)

    Liu, X; Ghan, SJ; Xie, S

    2007-04-01T23:59:59.000Z

    Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate models have generally proven unsuccessful at simulating 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. An ice nucleation parameterization and a vapor deposition scheme were developed that together provide a physically-consistent treatment of mixed-phase clouds in global climate models. These schemes have been implemented in the National Center for Atmospheric Research (NCAR) Community Atmospheric Model Version 3 (CAM3). This report documents the performance of these schemes against ARM Mixed-phase Arctic Cloud Experiment (M-PACE) observations using the CAM single column model version (SCAM). SCAM with our new schemes has a more realistic simulation of the cloud phase structure and the partitioning of condensed water into liquid droplets against observations during the M-PACE than the standard CAM simulations.

  10. ARRA-funded Cloud Radar Development for the Department of Energy's ARM Climate Research Facility

    E-Print Network [OSTI]

    percent of all expenses on this contract will be required to purchase components and subsystems from US Power Industries (CPI) of Beverly, MA will be building 27 high voltage power supply-modulator units

  11. STUDY OF CLOUD LIFETIME EFFECTS USING THE SGP HETEROGENEOUS DISTRIBUTED RADAR NETWORK: PRELIMINARY CONSIDERATIONS

    E-Print Network [OSTI]

    stages of cloud development. Here, we express cloud life cycle in terms of the temporal evolution-dimensional morphology and life cycle of clouds. Detailing key cloud processes as they transit from the formation stage National Laboratory For presentation at The Second Science Team Meeting of the Atmospheric System Research

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

    E-Print Network [OSTI]

    Klein, Stephen A.

    2009-01-01T23:59:59.000Z

    cloud has the correct effect on surface fluxes of radiation.radiation is 200 W m –2 in clear-sky STREAMER calculations, the longwave cloud radiative effect

  13. Using MSG-SEVIRI Cloud Physical Properties and Weather Radar Observations for the Detection of Cb/TCu Clouds

    E-Print Network [OSTI]

    Schmeits, Maurice

    . The presence of associated severe weather can be rel- evant to, for example, the transport industry, tourism, the energy supply industry, the construction industry, and farmers. The Cb and TCu clouds may pose a serious Society #12;wind shear, heavy precipitation, and lightning, that is associated with these clouds. Also

  14. ARM - Midlatitude Continental Convective Clouds Microwave Radiometer Profiler (jensen-mwr)

    SciTech Connect (OSTI)

    Jensen, Mike

    2012-02-01T23:59:59.000Z

    A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

  15. ARM - Midlatitude Continental Convective Clouds - Ultra High Sensitivity Aerosol Spectrometer(tomlinson-uhsas)

    SciTech Connect (OSTI)

    Tomlinson, Jason; Jensen, Mike

    2012-02-28T23:59:59.000Z

    Ultra High Sensitivity Aerosol Spectrometer (UHSASA) A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

  16. ARM - Midlatitude Continental Convective Clouds Microwave Radiometer Profiler (jensen-mwr)

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

    Jensen, Mike

    A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

  17. ARM - Midlatitude Continental Convective Clouds - Ultra High Sensitivity Aerosol Spectrometer(tomlinson-uhsas)

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

    Tomlinson, Jason; Jensen, Mike

    Ultra High Sensitivity Aerosol Spectrometer (UHSASA) A major component of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was the deployment of an enhanced radiosonde array designed to capture the vertical profile of atmospheric state variables (pressure, temperature, humidity wind speed and wind direction) for the purpose of deriving the large-scale forcing for use in modeling studies. The radiosonde array included six sites (enhanced Central Facility [CF-1] plus five new sites) launching radiosondes at 3-6 hour sampling intervals. The network will cover an area of approximately (300)2 km2 with five outer sounding launch sites and one central launch location. The five outer sounding launch sites are: S01 Pratt, KS [ 37.7oN, 98.75oW]; S02 Chanute, KS [37.674, 95.488]; S03 Vici, Oklahoma [36.071, -99.204]; S04 Morris, Oklahoma [35.687, -95.856]; and S05 Purcell, Oklahoma [34.985, -97.522]. Soundings from the SGP Central Facility during MC3E can be retrieved from the regular ARM archive. During routine MC3E operations 4 radiosondes were launched from each of these sites (approx. 0130, 0730, 1330 and 1930 UTC). On days that were forecast to be convective up to four additional launches were launched at each site (approx. 0430, 1030, 1630, 2230 UTC). There were a total of approximately 14 of these high frequency launch days over the course of the experiment. These files contain brightness temperatures observed at Purcell during MC3E. The measurements were made with a 5 channel (22.235, 23.035, 23.835, 26.235, 30.000GHz) microwave radiometer at one minute intervals. The results have been separated into daily files and the day of observations is indicated in the file name. All observations were zenith pointing. Included in the files are the time variables base_time and time_offset. These follow the ARM time conventions. Base_time is the number seconds since January 1, 1970 at 00:00:00 for the first data point of the file and time_offset is the offset in seconds from base_time.

  18. ARM: Microwave Radiometer data (MWR Profiles - QME), water vapor, temp, cloud liquid water, precip water retrievals

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

    Cadeddu, Maria

    Microwave Radiometer data (MWR Profiles - QME), water vapor, temp, cloud liquid water, precip water retrievals

  19. Ice cloud microphysics retrievals from millimeter radar and visible optical depth using an estimation theory approach

    E-Print Network [OSTI]

    Stephens, Graeme L.

    of the planet. These effects occur as a consequence of the way cloud particles scatter and absorb radiation, 0325); 1655 Global Change: Water cycles (1836); KEYWORDS: ice water content retrieval, cirrus cloud), 4335, doi:10.1029/2002JD002693, 2003. 1. Introduction [2] Clouds profoundly affect the radiation budget

  20. Environmental assessment for the Atmospheric Radiation Measurement (ARM) Program: Southern Great Plains Cloud and Radiation Testbed (CART) site

    SciTech Connect (OSTI)

    Policastro, A.J.; Pfingston, J.M.; Maloney, D.M.; Wasmer, F.; Pentecost, E.D.

    1992-03-01T23:59:59.000Z

    The Atmospheric Radiation Measurement (ARM) Program is aimed at supplying improved predictive capability of climate change, particularly the prediction of cloud-climate feedback. The objective will be achieved by measuring the atmospheric radiation and physical and meteorological quantities that control solar radiation in the earth`s atmosphere and using this information to test global climate and related models. The proposed action is to construct and operate a Cloud and Radiation Testbed (CART) research site in the southern Great Plains as part of the Department of Energy`s Atmospheric Radiation Measurement Program whose objective is to develop an improved predictive capability of global climate change. The purpose of this CART research site in southern Kansas and northern Oklahoma would be to collect meteorological and other scientific information to better characterize the processes controlling radiation transfer on a global scale. Impacts which could result from this facility are described.

  1. Using Radar, Lidar and Radiometer Data from NSA and SHEBA to Quantify Cloud Property Effects on the Surface Heat Budget in the Arctic

    SciTech Connect (OSTI)

    Janet Intrieri; Mathhew Shupe

    2005-01-01T23:59:59.000Z

    Cloud and radiation data from two distinctly different Arctic areas are analyzed to study the differences between coastal Alaskan and open Arctic Ocean region clouds and their respective influence on the surface radiation budget. The cloud and radiation datasets were obtained from (1) the DOE North Slope of Alaska (NSA) facility in the coastal town of Barrow, Alaska, and (2) the SHEBA field program, which was conducted from an icebreaker frozen in, and drifting with, the sea-ice for one year in the Western Arctic Ocean. Radar, lidar, radiometer, and sounding measurements from both locations were used to produce annual cycles of cloud occurrence and height, atmospheric temperature and humidity, surface longwave and shortwave broadband fluxes, surface albedo, and cloud radiative forcing. In general, both regions revealed a similar annual trend of cloud occurrence fraction with minimum values in winter (60-75%) and maximum values during spring, summer and fall (80-90%). However, the annual average cloud occurrence fraction for SHEBA (76%) was lower than the 6-year average cloud occurrence at NSA (92%). Both Arctic areas also showed similar annual cycle trends of cloud forcing with clouds warming the surface through most of the year and a period of surface cooling during the summer, when cloud shading effects overwhelm cloud greenhouse effects. The greatest difference between the two regions was observed in the magnitude of the cloud cooling effect (i.e., shortwave cloud forcing), which was significantly stronger at NSA and lasted for a longer period of time than at SHEBA. This is predominantly due to the longer and stronger melt season at NSA (i.e., albedo values that are much lower coupled with Sun angles that are somewhat higher) than the melt season observed over the ice pack at SHEBA. Longwave cloud forcing values were comparable between the two sites indicating a general similarity in cloudiness and atmospheric temperature and humidity structure between the two regions.

  2. Detection of supercooled liquid in mixedphase clouds using radar Doppler spectra

    E-Print Network [OSTI]

    Shupe, Matthew

    in the temperature range from 0 to -40°C, where both liquid and ice hydrometeor phases are sustainable of their hydrometeors (i.e., liquid or ice). Current cloud parameterizations that parti- tion water into liquid and ice 2010; published 1 October 2010. [1] Cloud phase identification from active remote sensors

  3. ARM - Measurement - Radar Doppler

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowband upwelling

  4. ARM - Radar Backgrounder

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP :ProductsVaisala CL51Instruments Related Links RHUBC-II

  5. Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia

    SciTech Connect (OSTI)

    Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.; Delanoe, Julien; Deng, Min

    2013-05-22T23:59:59.000Z

    Ground-based radar and lidar observations obtained at the Department of Energy’s Atmospheric Radiation Measurement Program’s Tropical Western Pacific site located in Darwin, Australia are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar-lidar and two radar only algorithms) are compared by examining mean profiles and probability density functions of effective radius (Re), ice water content (IWC), extinction, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on the cloud radiative effect and radiative heating rates are presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which is attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes-large differences in cloud radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m-2 on average. These differences, which we believe are primarily driven by the uncertainty in Re, can cause up to 2 K/day difference in the radiative heating rates between algorithms.

  6. Collaborative Research: ARM observations for the development and evaluation of models and parameterizations of cloudy boundary layers

    SciTech Connect (OSTI)

    Albrecht, Bruce,

    2013-07-12T23:59:59.000Z

    This is a collaborative project with Dr. Ping Zhu at Florida International University. It was designed to address key issues regarding the treatment of boundary layer cloud processes in climate models with UM’s research focusing on the analyses of ARM cloud radar observations from MMCR and WACR and FIU’s research focusing on numerical simulations of boundary layer clouds. This project capitalized on recent advancements in the ARM Millimeter Cloud Radar (MMCR) processing and the development of the WACR (at the SGP) to provide high temporal and spatial resolution Doppler cloud radar measurements for characterizing in-cloud turbulence, large-eddy circulations, and high resolution cloud structures of direct relevance to high resolution numerical modeling studies. The principal focus of the observational component of this collaborative study during this funding period was on stratocumulus clouds over the SGP site and fair-weather cumuli over the Nauru site. The statistical descriptions of the vertical velocity structures in continental stratocumulus clouds and in the Nauru shallow cumuli that are part of this study represents the most comprehensive observations of the vertical velocities in boundary layer clouds to date and were done in collaboration with Drs. Virendra Ghate and Pavlos Kollias.

  7. Application of Stochastic Radiative Transfer Theory to the ARM Cloud-Radiative Parameterization Problem

    SciTech Connect (OSTI)

    Veron, Dana E

    2009-03-12T23:59:59.000Z

    This project had two primary goals: 1) development of stochastic radiative transfer as a parameterization that could be employed in an AGCM environment, and 2) exploration of the stochastic approach as a means for representing shortwave radiative transfer through mixed-phase layer clouds. To achieve these goals, an analysis of the performance of the stochastic approach was performed, a simple stochastic cloud-radiation parameterization for an AGCM was developed and tested, a statistical description of Arctic mixed phase clouds was developed and the appropriateness of stochastic approach for representing radiative transfer through mixed-phase clouds was assessed. Significant progress has been made in all of these areas and is detailed below.

  8. SGP and TWP (Manus) Ice Cloud Vertical Velocities

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

    Kalesse, Heike

    Daily netcdf-files of ice-cloud dynamics observed at the ARM sites at SGP (Jan1997-Dec2010) and Manus (Jul1999-Dec2010). The files include variables at different time resolution (10s, 20min, 1hr). Profiles of radar reflectivity factor (dbz), Doppler velocity (vel) as well as retrieved vertical air motion (V_air) and reflectivity-weighted particle terminal fall velocity (V_ter) are given at 10s, 20min and 1hr resolution. Retrieved V_air and V_ter follow radar notation, so positive values indicate downward motion. Lower level clouds are removed, however a multi-layer flag is included.

  9. The use of Doppler radar to predict cloud-to-ground lightning

    E-Print Network [OSTI]

    Aclin, Keith Andrew

    1995-01-01T23:59:59.000Z

    during the spring of 1993 for squall line activity. These data will then be combined with the cloud-to-ground lightning that occurred within the six minutes of the scan time. Three sets of linear correlations will be generated. The first...

  10. ARM - Employment Opportunities Article

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

    26, 2014 Employment Opportunities Supporting Scientist Positon for ARM at Lawrence Livermore National Laboratory Bookmark and Share llnl-logo The Cloud Processes Research (CPR)...

  11. Retrieval of optical and microphysical properties of ice clouds using Atmospheric Radiation Measurement (ARM) data

    E-Print Network [OSTI]

    Kinney, Jacqueline Anne

    2005-11-01T23:59:59.000Z

    is based on a method proposed by Yang et al. (2005). The research examines single-layer ice clouds in the midlatitude and polar regions. The retrieved information in the midlatitudes is then verified using retrievals from the Moderate-resolution Imaging...

  12. Atmospheric Radiation Measurement (ARM) Data from the Eastern North Atlantic Site (ENA), Graciosa Island, Azores

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

    Wood, Robert

    From May 2009 through December 2010, the ARM Mobile Facility obtained data from a location near the airport on Graciosa Island to support the Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) field campaign. The campaign was led by principal investigator Robert Wood. Results from this campaign confirmed that the Azores have the ideal mix of conditions to study how clouds, aerosols, and precipitation interact. This new observation site will have significant enhancements to instruments previously deployed to the Azores, including a Ka-/W-band scanning cloud radar, precipitation radar, and Doppler lidar. It has the full support of the Azorean government and collaborators at the University of the Azores. Los Alamos National Laboratory will operate the site for the ARM Facility.

  13. The Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured Fluxes and Lidar/Radar Profiles at SIRTA Atmospheric Observatory

    SciTech Connect (OSTI)

    Chiriaco, M.; Vautard, R.; Chepfer, H.; Haeffelin, M.; Wanherdrick, Y.; Morille, Y.; Protat, A.; Dudhia, J.

    2005-03-18T23:59:59.000Z

    Ice clouds play a major role in the radiative energy budget of the Earth-atmosphere system (Liou 1986). Their radiative effect is governed primarily by the equilibrium between their albedo and greenhouse effects. Both macrophysical and microphysical properties of ice clouds regulate this equilibrium. For quantifying the effect of these clouds onto climate and weather systems, they must be properly characterized in atmospheric models. In this paper we use remote-sensing measurements from the SIRTA ground based atmospheric observatory (Site Instrumental de Recherche par Teledetection Atmospherique, http://sirta.lmd.polytechnique.fr). Lidar and radar observations taken over 18 months are used, in order to gain statistical confidence in the model evaluation. Along this period of time, 62 days are selected for study because they contain parts of ice clouds. We use the ''model to observations'' approach by simulating lidar and radar signals from MM5 outputs. Other more classical variables such as shortwave and longwave radiative fluxes are also used. Four microphysical schemes, among which that proposed by Reisner et al. (1998) with original or modified parameterizations of particle terminal fall velocities (Zurovac-Jevtic and Zhang 2003, Heymsfield and Donner 1990), and the simplified Dudhia (1989) scheme are evaluated in this study.

  14. ARM - Field Campaign - 2008 VAMOS Ocean-Cloud-Atmos-Land Study (VOCALS)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM2, 2006 [FacilityMission Under52 NEAQS (New7 Cumulus8

  15. ARM - Field Campaign - Azores: Above-Cloud Radiation Budget near Graciosa

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM2,govCampaignsAircraft IntegrationIsland

  16. DOE/SC-ARM-P-07-006 Evaluation of Mixed-Phase Cloud Microphysics

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration wouldDECOMPOSITION OF CALCIUMCOSTDOENuclear1382 THEDOE0-354-1502 ARM63173006

  17. ARM - Publications: Science Team Meeting Documents: The impact of Cloud and

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facilityandof tropical convective

  18. Cloud Properties and Radiative Heating Rates for TWP

    SciTech Connect (OSTI)

    Comstock, Jennifer

    2013-11-07T23:59:59.000Z

    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. ARM - Evaluation Product - MicroPulse LIDAR Cloud Optical Depth (MPLCOD)

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

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

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

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  2. Validation of Cloud Properties Derived from GOES-9 Over the ARM TWP Region

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron SpinPrincetonUsing Maps toValidatingCloud Properties Derived from GOES-9

  3. Evaluation of Long-Term Cloud-Resolving Modeling with ARM Data

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power AdministrationField8,Dist. Category UC-l 1, 13Evacuation EmergencyCloudSat,Evaluation of

  4. Parameterizing the Difference in Cloud Fraction Defined by Area and by Volume as Observed with Radar and Lidar

    E-Print Network [OSTI]

    Reading, University of

    partially cloudy grid boxes by weighting clear and cloudy fluxes by the fractional area of cloud cover (Ca cloud cover from 53% to 63%, and so is of similar importance to the cloud overlap assumption. A simple for calculating the radiative effect of cloud (Stephens 1984; Edwards and Slingo 1996) and the representation

  5. Comparing Clouds Using Cloud Radar

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration would like submit the followingth Lomonosov1Compact highDepartmentIntensity

  6. Thunderstorm characteristics of cloud-to-ground lightning at the Kennedy Space Center, Florida: a study of lightning initiation signatures as indicated by Doppler radar

    E-Print Network [OSTI]

    Gremillion, Michael Shane

    1998-01-01T23:59:59.000Z

    , except for 1806-1824 UTC 58 29 Same as Fig. 27, except for 1830-1847 UTC 59 30 Radar echo tops for all categories of storms 95 31 Scatter diagram of mixed-phase reflectivity lapse rate and maximum reflectivity at the freezing level for all storms... Mexico. Taylor (1978) also found the center of activity to be associated with the supercooled cloud layer between the regions of ? 5'C and ? 20'C. One theory of thunderstorm electrification supports the idea of an ice-related precipitation...

  7. FINAL REPORT FOR THE DOE/ARM PROJECT TITLED Representation of the Microphysical and Radiative Properties of Ice Clouds in SCMs and GCMs

    SciTech Connect (OSTI)

    Mitchell, David L.

    2005-08-08T23:59:59.000Z

    The broad goal of this research is to improve climate prediction through better representation of cirrus cloud microphysical and radiative properties in global climate models (GCMs). Clouds still represent the greatest source of uncertainty in climate prediction, and the representation of ice clouds is considerably more challenging than liquid water clouds. While about 40% of cloud condensate may be in the form of ice by some estimates, there have been no credible means of representing the ice particle size distribution and mass removal rates from ice clouds in GCMs. Both factors introduce large uncertainties regarding the global net flux, the latter factor alone producing a change of 10 W/m2 in the global net flux due to plausible changes in effective ice particle fallspeed. In addition, the radiative properties of ice crystals themselves are in question. This research provides GCMs with a credible means of representing the full (bimodal) ice particle size distribution (PSD) in ice clouds, including estimates of the small crystal (D < 65 microns) mode of the PSD. It also provides realistic estimates of mass sedimentation rates from ice clouds, which have a strong impact on their ice contents and radiative properties. This can be done through proper analysis of ice cloud microphysical data from ARM and other field campaigns. In addition, this research tests the ice cloud radiation treatment developed under two previous ARM projects by comparing it against laboratory measurements of ice cloud extinction efficiency and by comparing it with explicit theoretical calculations of ice crystal optical properties. The outcome of this project includes two PSD schemes for ice clouds; one appropriate for mid-latitude cirrus clouds and another for tropical anvil cirrus. Cloud temperature and ice water content (IWC) are the inputs for these PSD schemes, which are based on numerous PSD observations. The temperature dependence of the small crystal mode of the PSD for tropical anvils is opposite to that of mid-latitude cirrus, and this results in very different radiative properties for these two types of cirrus at temperatures less than about 50 C for a given ice water path. In addition, the representative PSD fall velocity is strongly influenced by the small crystal mode, and for temperatures less than 52 C, this fall velocity for mid-latitude cirrus is 2-8 times greater than for tropical anvil cirrus. Finally, the treatment of ice cloud optical properties was found to agree with laboratory measurements and exact theory within 15% for any given wavelength, PSD and ice particle shape. This treatment is analytical, formulated in terms of the PSD and ice particle shape properties. It thus provides the means for explicitly coupling the ice cloud microphysical and radiative properties, and can treat any combination of ice particle shape. It is very inexpensive regarding computer time. When these three deliverables were incorporated into the GCM at the National Center for Atmospheric Research (NCAR) under another project, it was found that the sunlight reflected and the amount of upwelling heat absorbed by cirrus clouds depended strongly on the PSD scheme used (i.e. mid-latitude or tropical anvil). This was largely due to the fall velocities associated with the two PSD schemes, although the PSD shape was also important.

  8. ARM: ARSCL: cloud boundaries from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

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

    Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

    ARSCL: cloud boundaries from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

  9. Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models

    SciTech Connect (OSTI)

    Houze, Jr., Robert A. [University of Washington Dept. of Atmospheric Sciences

    2013-11-13T23:59:59.000Z

    We examined cloud radar data in monsoon climates, using cloud radars at Darwin in the Australian monsoon, on a ship in the Bay of Bengal in the South Asian monsoon, and at Niamey in the West African monsoon. We followed on with a more in-depth study of the continental MCSs over West Africa. We investigated whether the West African anvil clouds connected with squall line MCSs passing over the Niamey ARM site could be simulated in a numerical model by comparing the observed anvil clouds to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model at high resolution using six different ice-phase microphysical schemes. We carried out further simulations with a cloud-resolving model forced by sounding network budgets over the Niamey region and over the northern Australian region. We have devoted some of the effort of this project to examining how well satellite data can determine the global breadth of the anvil cloud measurements obtained at the ARM ground sites. We next considered whether satellite data could be objectively analyzed to so that their large global measurement sets can be systematically related to the ARM measurements. Further differences were detailed between the land and ocean MCS anvil clouds by examining the interior structure of the anvils with the satellite-detected the CloudSat Cloud Profiling Radar (CPR). The satellite survey of anvil clouds in the Indo-Pacific region was continued to determine the role of MCSs in producing the cloud pattern associated with the MJO.

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

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

    Gaustad, Krista; Gaustad, Krista; McFarlane, Sally; McFarlane, Sally

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

  11. ARM: ARSCL: cloud base height from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

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

    Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

    ARSCL: cloud base height from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

  12. ARM: 10-minute Raman Lidar: aerosol depolarization profiles and single layer cloud optical depths from first Turner algorithm

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

    Newsom, Rob; Goldsmith, John

    10-minute Raman Lidar: aerosol depolarization profiles and single layer cloud optical depths from first Turner algorithm

  13. Radiative Energy Balance in the Tropical Tropopause Layer: An Investigation with ARM Data

    SciTech Connect (OSTI)

    Fu, Qiang

    2013-10-22T23:59:59.000Z

    The overall objective of this project is to use the ARM observational data to improve our understanding of cloud-radiation effects in the tropical tropopause layer (TTL), which is crucial for improving the simulation and prediction of climate and climate change. In last four and half years, we have been concentrating on (i) performing the comparison of the ice cloud properties from the ground-based lidar observations with those from the satellite CALIPSO lidar observations at the ARM TWP sites; (ii) analyzing TTL cirrus and its relation to the tropical planetary waves; (iii) calculating the radiative heating rates using retrieved cloud microphysical properties by combining the ground-based lidar and radar observations at the ARM TWP sites and comparing the results with those using cloud properties retrieved from CloudSat and CALIPSO observations; (iv) comparing macrophysical properties of tropical cirrus clouds from the CALIPSO satellite and from ground-based micropulse and Raman lidar observations; (v) improving the parameterization of optical properties of cirrus clouds with small effective ice particle sizes; and (vi) evaluating the enhanced maximum warming in the tropical upper troposphere simulated by the GCMs. The main results of our research efforts are reported in the 12 referred journal publications that acknowledge the DOE Grant No. DE-FG02-09ER64769.

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

    SciTech Connect (OSTI)

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

    2006-07-10T23:59:59.000Z

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

  15. Real-Time C-Band Radar Observations of 1992 Eruption Clouds from Crater Peak, Mount Spurr Volcano, Alaska

    E-Print Network [OSTI]

    Rose, William I.

    Survey (USGS), and the Federal Aviation Administration (FAA) at Anchorage provides for the exchange of the eruptions has had a considerable impact on commercial aviation in south- central Alaska, particularly of measuring and tracking ash clouds, in order to advise the aviation community about how to avoid ash clouds

  16. ARM - Cloud Memory

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  17. ARM - Cloud Twist

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

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  18. ARM - Cloud Word Seek

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

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  19. ARM - Cloud and Rain

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  20. ARM - Measurement - Cloud extinction

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  1. ARM - Measurement - Cloud fraction

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

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  2. 4A.5 DERIVING TURBULENT KINETIC ENERGY DISSIPATION RATE WITHIN CLOUDS USING GROUND BASED 94 GHZ RADAR

    E-Print Network [OSTI]

    Hogan, Robin

    Terrestre et Plan´etaire, V´elizy, France University of Reading, Reading, United Kingdom 1. INTRODUCTION. The variance 1 #12;v 2 of the mean wind is an indicator of the kinetic energy in turbulent scales4A.5 DERIVING TURBULENT KINETIC ENERGY DISSIPATION RATE WITHIN CLOUDS USING GROUND BASED 94 GHZ

  3. SGP Cloud and Land Surface Interaction Campaign (CLASIC): Measurement Platforms

    SciTech Connect (OSTI)

    MA Miller; R Avissar; LK Berg; SA Edgerton; ML Fischer; TJ Jackson; B. Kustas; PJ Lamb; G McFarquhar; Q Min; B Schmid; MS Torn; DD Tuner

    2007-06-01T23:59:59.000Z

    The Cloud and Land Surface Interaction Campaign (CLASIC) will be conducted from June 8 to June 30, 2007, at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. Data will be collected using eight aircraft equipped with a variety of specialized sensors, four specially instrumented surface sites, and two prototype surface radar systems. The architecture of CLASIC includes a high-altitude surveillance aircraft and enhanced vertical thermodynamic and wind profile measurements that will characterize the synoptic scale structure of the clouds and the land surface within the ACRF SGP site. Mesoscale and microscale structures will be sampled with a variety of aircraft, surface, and radar observations. An overview of the measurement platforms that will be used during the CLASIC are described in this report. The coordination of measurements, especially as it relates to aircraft flight plans, will be discussed in the CLASIC Implementation Plan.

  4. The Mid-latitude Continental Convective Clouds (MC3E) Experiment Final Campaign Report

    SciTech Connect (OSTI)

    Jensen, Michael [Brookhaven National Laboratory; Kollias, Pavlos [McGill University; Giangrande, Scott

    2014-04-01T23:59:59.000Z

    The Mid-latitude Continental Convective Clouds Experiment (MC3E) took place from April 22 through June 6, 2011, centered at the ARM Southern Great Plains site (http://www.arm.gov/sites/sgp) in northcentral Oklahoma. MC3E was a collaborative effort between the ARM Climate Research Facility and the National Aeronautics and Space Administration’s (NASA’s) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program. The campaign leveraged the largest ground-based observing infrastructure available in the central United States, including recent upgrades through the American Recovery and Reinvestment Act of 2009, combined with an extensive sounding array, remote sensing and in situ aircraft observations, and additional radar and in situ precipitation instrumentation. The overarching goal of the campaign was to provide a three-dimensional characterization of convective clouds and precipitation for the purpose of improving the representation of convective lifecycle in atmospheric models and the reliability of satellite-based retrievals of precipitation.

  5. Validation of MODIS-Retrieved Cloud Fractions Using Whole Sky Imager Measurements at the Three ARM Sites

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  6. The ARM Climate Research Facility: A Review of Structure and Capabilities

    SciTech Connect (OSTI)

    Mather, James H.; Voyles, Jimmy W.

    2013-03-01T23:59:59.000Z

    The Atmospheric Radiation Measurement (ARM) program (www.arm.gov) is a Department of Energy, Office of Science, climate research user facility that provides atmospheric observations from diverse climatic regimes around the world. Use of ARM data is free and available to anyone through the ARM data archive. ARM is approaching 20 years of operations. In recent years, the facility has grown to add two mobile facilities and an aerial facility to its network of fixed-location sites. Over the past year, ARM has enhanced its observational capabilities with a broad array of new instruments at its fixed and mobile sites and the aerial facility. Instruments include scanning millimeter- and centimeter-wavelength radars; water vapor, cloud/aerosol extinction, and Doppler lidars; a suite of aerosol instruments for measuring optical, physical, and chemical properties; instruments including eddy correlation systems to expand measurements of the surface and boundary layer; and aircraft probes for measuring cloud and aerosol properties. Taking full advantage of these instruments will involve the development of complex data products. This work is underway but will benefit from engagement with the broader scientific community. In this article we will describe the current status of the ARM program with an emphasis on developments over the past eight years since ARM was designated a DOE scientific user facility. We will also describe the new measurement capabilities and provide thoughts for how these new measurements can be used to serve the climate research community with an invitation to the community to engage in the development and use of these data products.

  7. ARM - Facility News Article

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

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  8. ARM - Facility News Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM EducationAugustMultifilterAugustRadarARM Archive

  9. ARM - Facility News Article

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

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  10. ARM - Facility News Article

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

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  11. ARM - Facility News Article

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

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  12. ARM - Facility News Article

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

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  13. ARM - Facility News Article

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

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  14. ARM TR-006

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM7 The ARM

  15. ARM TR-008

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  16. The Microbase Value-Added Product: A Baseline Retrieval of Cloud Microphysical Properties

    SciTech Connect (OSTI)

    Dunn, M; Johnson, K; Jensen, M

    2011-05-31T23:59:59.000Z

    This report describes the Atmospheric Radiation Measurement (ARM) Climate Research Facility baseline cloud microphysical properties (MICROBASE) value-added product (VAP). MICROBASE uses a combination of millimeter-wavelength cloud radar, microwave radiometer, and radiosonde observations to estimate the vertical profiles of the primary microphysical parameters of clouds including the liquid/ice water content and liquid/ice cloud particle effective radius. MICROBASE is a baseline algorithm designed to apply to most conditions and locations using a single set of parameterizations and a simple determination of water phase based on temperature. This document provides the user of this product with guidelines to assist in determining the accuracy of the product under certain conditions. Quality control flags are designed to identify outliers and indicate instances where the retrieval assumptions may not be met. The overall methodology is described in this report through a detailed description of the input variables, algorithms, and output products.

  17. Comparison of Simulated and Observed Continental Tropical Anvil Clouds and Their Radiative Heating Profiles

    SciTech Connect (OSTI)

    Powell, Scott W.; Houze, R.; Kumar, Anil; McFarlane, Sally A.

    2012-09-06T23:59:59.000Z

    Vertically pointing millimeter-wavelength radar observations of anvil clouds extending from mesoscale convective systems (MCSs) that pass over an Atmospheric Radiation Measurement Program (ARM) field site in Niamey, Niger, are compared to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model using six different microphysical schemes. The radar data provide the statistical distribution of the radar reflectivity values as a function of height and anvil thickness. These statistics are compared to the statistics of the modeled anvil cloud reflectivity at all altitudes. Requiring the model to be statistically accurate at all altitudes is a stringent test of the model performance. The typical vertical profile of radiative heating in the anvil clouds is computed from the radar observations. Variability of anvil structures from the different microphysical schemes provides an estimate of the inherent uncertainty in anvil radiative heating profiles. All schemes underestimate the optical thickness of thin anvils and cirrus, resulting in a bias of excessive net anvil heating in all of the simulations.

  18. The Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured Fluxes and Lidar/Radar Profiles at the

    E-Print Network [OSTI]

    Protat, Alain

    distribution are critical to the global radiative effect of ice clouds. One of the main uncertainties. To quantify the effect of these clouds onto climate and weather systems, their global coverage, altitude, tem effect. Both macrophysical and microphysical properties of ice clouds regulate this equilibrium

  19. Using Surface Remote Sensors to Derive Radiative Characteristics of Mixed-Phase Clouds: An Example from M-PACE

    SciTech Connect (OSTI)

    de Boer, Gijs; Collins, William D.; Menon, Surabi; Long, Charles N.

    2011-12-02T23:59:59.000Z

    Measurements from ground-based cloud radar, high spectral resolution lidar and microwave radiometer are used in conjunction with a column version of the Rapid Radiative Transfer Model (RRTMG) and radiosonde measurements to derive the surface radiative properties under mixed-phase cloud conditions. These clouds were observed during the United States Department of Energy (US DOE) Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Clouds Experiment (M-PACE) between September and November of 2004. In total, sixteen half hour time periods are reviewed due to their coincidence with radiosonde launches. Cloud liquid (ice) water paths are found to range between 11.0-366.4 (0.5-114.1) gm-2, and cloud physical thicknesses fall between 286-2075 m. Combined with temperature and hydrometeor size estimates, this information is used to calculate surface radiative flux densities using RRTMG, which are demonstrated to generally agree with measured flux densities from surface-based radiometric instrumentation. Errors in longwave flux density estimates are found to be largest for thin clouds, while shortwave flux density errors are generally largest for thicker clouds. A sensitivity study is performed to understand the impact of retrieval assumptions and uncertainties on derived surface radiation estimates. Cloud radiative forcing is calculated for all profiles, illustrating longwave dominance during this time of year, with net cloud forcing generally between 50 and 90 Wm-2.

  20. Calibration of the groundbased radars during CLARE'98 Robin J. Hogan

    E-Print Network [OSTI]

    Hogan, Robin

    Calibration of the ground­based radars during CLARE'98 Robin J. Hogan Department of Meteorology. The approach used to calibrate the radars is to start with the absolute calibration provided by the Rabelais radar in Rayleigh­scattering light rain or cloud. Finally the W­band radars are calibrated

  1. ARM - Facility News Article

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  2. ARM - Facility News Article

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  3. Parameterizing Size Distribution in Ice Clouds

    SciTech Connect (OSTI)

    DeSlover, Daniel; Mitchell, David L.

    2009-09-25T23:59:59.000Z

    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 µm) 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 µm), known as the “small mode”. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of ice cloud optical properties formulated in terms of PSD parameters in combination with remote measurements of thermal radiances to characterize the small mode. This is possible since the absorption efficiency (Qabs) of small mode crystals is larger at 12 µm wavelength relative to 11 µm wavelength due to the process of wave resonance or photon tunneling more active at 12 µm. This makes the 12/11 µm absorption optical depth ratio (or equivalently the 12/11 µm Qabs ratio) a means for detecting the relative concentration of small ice particles in cirrus. Using this principle, this project tested and developed PSD schemes that can help characterize cirrus clouds at each of the three ARM sites: SGP, NSA and TWP. This was the main effort of this project. These PSD schemes and ice sedimentation velocities predicted from them have been used to test the new cirrus microphysics parameterization in the GCM known as the Community Climate Systems Model (CCSM) as part of an ongoing collaboration with NCAR. Regarding the second problem, we developed and did preliminary testing on a passive thermal method for retrieving the total water path (TWP) of Arctic mixed phase clouds where TWPs are often in the range of 20 to 130 g m-2 (difficult for microwave radiometers to accurately measure). We also developed a new radar method for retrieving the cloud ice water content (IWC), which can be vertically integrated to yield the ice water path (IWP). These techniques were combined to determine the IWP and liquid water path (LWP) in Arctic clouds, and hence the fraction of ice and liquid water. We have tested this approach using a case study from the ARM field campaign called M-PACE (Mixed-Phase Arctic Cloud Experiment). This research led to a new satellite remote sensing method that appears promising for detecting low levels of liquid water in high clouds typically between -20 and -36 oC. We hope to develop this method in future research.

  4. ARM - Field Campaign - Cloud IOP

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  5. ARM - Measurement - Cloud condensation nuclei

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  6. ARM - Measurement - Cloud droplet size

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  7. ARM - Measurement - Cloud effective radius

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  8. ARM - Measurement - Images of Clouds

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  9. Cloud Services Cloud Services

    E-Print Network [OSTI]

    Cloud Services Cloud Services In 2012 UCD IT Services launched an exciting new set of cloud solutions called CloudEdu, which includes cloud servers, cloud storage, cloud hosting and cloud network. The CloudEdu package includes a consultancy service in design, deployment, management and utilisation

  10. Ice Formation in Arctic Mixed-Phase Clouds: Insights from a 3-D Cloud-Resolving Model with Size-Resolved Aerosol and Cloud Microphysics

    SciTech Connect (OSTI)

    Fan, Jiwen; Ovtchinnikov, Mikhail; Comstock, Jennifer M.; McFarlane, Sally A.; Khain, Alexander

    2009-02-27T23:59:59.000Z

    The single-layer mixed-phase clouds observed during the Atmospheric Radiation Measurement (ARM) program’s Mixed-Phase Arctic Cloud Experiment (MPACE) are simulated with a 3-dimensional cloud-resolving model the System for Atmospheric Modeling (SAM) coupled with an explicit bin microphysics scheme and a radar-lidar simulator. Two possible ice enhancement mechanisms – activation of droplet evaporation residues by condensation-followed-by-freezing and droplet freezing by contact freezing inside-out, are scrutinized by extensive comparisons with aircraft and radar and lidar measurements. The locations of ice initiation associated with each mechanism and the role of ice nuclei (IN) in the evolution of mixed-phase clouds are mainly addressed. Simulations with either mechanism agree well with the in-situ and remote sensing measurements on ice microphysical properties but liquid water content is slightly underpredicted. These two mechanisms give very similar cloud microphysical, macrophysical, dynamical, and radiative properties, although the ice nucleation properties (rate, frequency and location) are completely different. Ice nucleation from activation of evaporation nuclei is most efficient near cloud top areas concentrated on the edges of updrafts, while ice initiation from the drop freezing process has no significant location preference (occurs anywhere that droplet evaporation is significant). Both enhanced nucleation mechanisms contribute dramatically to ice formation with ice particle concentration of 10-15 times higher relative to the simulation without either of them. The contribution of ice nuclei (IN) recycling from ice particle evaporation to IN and ice particle concentration is found to be very significant in this case. Cloud can be very sensitive to IN initially and form a nonquilibrium transition condition, but become much less sensitive as cloud evolves to a steady mixed-phase condition. The parameterization of Meyers et al. [1992] with the observed MPACE IN concentration is able to predict the observed mixed-phase clouds reasonably well. This validation may facilitate the application of this parameterization in the cloud and climate models to simulate Arctic clouds.

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

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

    Gaustad, Krista; Gaustad, Krista; McFarlane, Sally; McFarlane, Sally

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

  12. The Accuracy of Radar Estimates of Ice Terminal Fall Speed from Vertically Pointing Doppler Radar Measurements

    E-Print Network [OSTI]

    Protat, Alain

    The Accuracy of Radar Estimates of Ice Terminal Fall Speed from Vertically Pointing Doppler Radar and 2835 MHz) are used to characterize the terminal fall speed of hydrometeors and the vertical air motion air velocity in ice clouds is small on average, as is assumed in terminal fall speed retrieval methods

  13. The Mid-Latitude Continental Convective Clouds Experiment (MC3E)

    SciTech Connect (OSTI)

    Petersen,W.; Jensen,M.; Genio, A. D.; Giangrande, S.; Heymsfield, A.; Heymsfield, G.; Hou, A.; Kollias, P.; Orr, B.; Rutledge, S.; Schwaller, M.; Zipser, E.

    2010-03-15T23:59:59.000Z

    The Midlatitude Continental Convective Cloud Experiment (MC3E) will take place in central Oklahoma during the April-May 2011 period. The experiment is a collaborative effort between the U.S. Department of Energy Atmospheric Radition Measurement Program and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation program. The Intensive Observation Period leverages the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding. The overarching goal is to provide the most complete characterization of convective cloud systems, precipitation and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall observations over land that have never before been available. Several different components of convective processes tangible to the convective parameterization problem are targeted such as, pre-convective environment and convective initiation, updraft / downdraft dynamics, condensate transport and detrainment, precipitation and cloud microphysics, influence on the environment and radiation and a detailed description of the large-scale forcing. MC3E will use a new multi-scale observing strategy with the participation of a network of distributed sensors (both passive and active). The approach is to document in 3-D not only the full spectrum of precipitation rates, but also clouds, winds and moisture in an attempt to provide a holistic view of convective clouds and their feedback with the environment. A goal is to measure cloud and precipitation transitions and environmental quantities that are important for satellite retrieval algorithms, convective parameterization in large-scale models and cloud-resolving model simulations. This will be accomplished through the deployment of several different elements that complement the existing (and soon to become available) ARM facilities: a network of radiosonde stations, NASA scanning multi-frequency/parameter radar systems at three different frequencies (Ka/Ku/S), high-altitude remote sensing and in situ aircraft, wind profilers and a network of surface disdrometers. In addition to these special MC3E instruments, there will be important new instrumentation deployed by DOE at the ARM site including: 3 networked scanning X-band radar systems, a C-band scanning radar, a dual wavelength (Ka/W) scanning cloud radar, a Doppler lidar and upgraded vertically pointing millimeter cloud radar (MMCR) and micropulse lidar (MPL).To fully describe the properties of precipitating cloud systems, both in situ and remote sensing airborne observations are necessary. The NASA GPM-funded University of North Dakota (UND) Citation will provide in situ observations of precipitation-sized particles, ice freezing nuclei and aerosol concentrations. As a complement to the UND Citation's in situ observations, the NASA ER-2 will provide a high altitude satellite simulator platform that carrying a Ka/Ku band radar and passive microwave radiometers (10-183 GHZ).

  14. ARM - Facility News Article

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

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  15. ARM - Facility News Article

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

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  16. ARM - Facility News Article

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

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  17. ARM TR-008

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

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  18. ARM TR-008

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

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  19. ARM TR-008

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

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  20. ARM TR-008

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

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  1. ARM TR-008

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

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  2. ARM TR-008

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

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  3. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM7

  4. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM710

  5. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM7101 ACRF

  6. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM7101 ACRF2

  7. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM7101

  8. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM71014 ACRF

  9. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM71014

  10. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM71014

  11. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM710144

  12. ARM TR-008

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

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  13. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM71014456

  14. ARM TR-008

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

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  15. ARM Water Vapor IOP

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323ARM Water Vapor IOP

  16. ARM XDC Datastreams

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323ARM Water Vapor

  17. ARM XDC Datastreams

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323ARM Water

  18. ARM XDC Datastreams

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323ARM

  19. Final Report on the Development of an Improved Cloud Microphysical Product for Model and Remote Sensing Evaluation using RACORO Observations

    SciTech Connect (OSTI)

    McFarquhar, Greg

    2012-09-19T23:59:59.000Z

    We proposed to analyze data collected during the Routine Aerial Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) in order to develop an integrated product of cloud microphysical properties (number concentration of drops in different size bins, total liquid drop concentration integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds bw, effective radius of water drops re, and radar reflectivity factor) that could be used to evaluate large-eddy simulations (LES), general circulation models (GCMs) and ground-based remote sensing retrievals, and to develop cloud parameterizations with the end goal of improving the modeling of cloud processes and properties and their impact on atmospheric radiation. We have completed the development of this microphysical database and have submitted it to ARM for consideration of its inclusion on the ARM database as a PI product. This report describes the development of this database, and also describes research that has been conducted on cloud-aerosol interactions using the data obtained during RACORO. A list of conference proceedings and publications is also included.

  20. ARM - About ARM

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  1. ARM - ARM Priorities Navigation

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

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  2. ARM - About ARM

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACTOperationsYearSafety PolicyCenterARM

  3. ARM - Field Campaign - NSA Scanning Radar IOP

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL)govCampaignsMixed-Phase Arctic CloudgovCampaignsNSA

  4. ARM Installs Aircraft Detection Radar System

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

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  5. Robotic arm

    DOE Patents [OSTI]

    Kwech, Horst (Lake Bluff, IL)

    1989-04-18T23:59:59.000Z

    A robotic arm positionable within a nuclear vessel by access through a small diameter opening and having a mounting tube supported within the vessel and mounting a plurality of arm sections for movement lengthwise of the mounting tube as well as for movement out of a window provided in the wall of the mounting tube. An end effector, such as a grinding head or welding element, at an operating end of the robotic arm, can be located and operated within the nuclear vessel through movement derived from six different axes of motion provided by mounting and drive connections between arm sections of the robotic arm. The movements are achieved by operation of remotely-controllable servo motors, all of which are mounted at a control end of the robotic arm to be outside the nuclear vessel.

  6. Clouds, Aerosol, and Precipitation in the Marine Boundary Layer: Analysis of Results from the ARM Mobile Facility Deployment to the Azores (2009/2010)

    SciTech Connect (OSTI)

    Wood, Robert [University of Washington, Dept of Atmos Sci

    2013-05-31T23:59:59.000Z

    The project focuses upon dataset analysis and synthesis of datasets from the AMF deployment entitled “Clouds, Aerosols, and Precipitation in the Marine Boundary Layer (CAP?MBL)” at Graciosa Island in the Azores. Wood is serving a PI for this AMF deployment.

  7. Testing IWC Retrieval Methods using Radar and Ancillary Measurements with In-Situ Andrew J. Heymsfield1

    E-Print Network [OSTI]

    Hogan, Robin

    profiles of ice water content (IWC) can now be derived globally from spaceborne cloud radar (CloudSat) data energy to space. Because of their height in the atmosphere, ice clouds have a dominant effect on longwave (), and ice particle shape, significantly affect ice cloud radiative properties. CloudSat, with an onboard

  8. MEASUREMENT BASED DETERMINATION OF AEROSOL FORCINGS AT ARM SITES: PROPOSED JOINT ASP-ARM STUDY

    E-Print Network [OSTI]

    of aerosol forcings. The dimmed forcings would not be determined -- no indirect aerosol effect in cloud free Stephen E. Schwartz For presentation at the Atmospheric Radiation Measurement (ARM) Program Science Team) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. There are numerous aerosol forcings

  9. Use of ARM/NSA Data to Validate and Improve the Remote Sensing Retrieval of Cloud and Surface Properties in the Arctic from AVHRR Data

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

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  10. Kinematical relations among radar-observed water concentrations, vertical motions, and liquid-water drop-size spectra in convective clouds

    E-Print Network [OSTI]

    Runnels, Robert Clayton

    1962-01-01T23:59:59.000Z

    of return settling are often cloudless or consist of cumulus clouds which have had their growth impeded. If conditions in the atmosphere are favorable, convection cells form and the updraft areas associated with these cells develop into cumulonimbus... and time, M & M(x, y, z, t). The x- and y-directions are horizontal and z-direction is positive toward the zenith. If the quantity M is conservative, the local rate of change at a fixed locality (the local change) can be represented by the following...

  11. A Model Evaluation Data Set for the Tropical ARM Sites

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

    Jakob, Christian

    This data set has been derived from various ARM and external data sources with the main aim of providing modelers easy access to quality controlled data for model evaluation. The data set contains highly aggregated (in time) data from a number of sources at the tropical ARM sites at Manus and Nauru. It spans the years of 1999 and 2000. The data set contains information on downward surface radiation; surface meteorology, including precipitation; atmospheric water vapor and cloud liquid water content; hydrometeor cover as a function of height; and cloud cover, cloud optical thickness and cloud top pressure information provided by the International Satellite Cloud Climatology Project (ISCCP).

  12. Atmospheric Rivers Coming to a Cloud Near You

    ScienceCinema (OSTI)

    Leung, Ruby

    2014-06-12T23:59:59.000Z

    Learn about the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) field campaign in this short video. Ruby Leung, PNNL's lead scientist on this campaign's observational strategy to monitor precipitation.

  13. Atmospheric Rivers Coming to a Cloud Near You

    SciTech Connect (OSTI)

    Leung, Ruby

    2014-03-29T23:59:59.000Z

    Learn about the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) field campaign in this short video. Ruby Leung, PNNL's lead scientist on this campaign's observational strategy to monitor precipitation.

  14. ARM - Employment Opportunities Article

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

    5, 2014 Employment Opportunities Seeking Lead Mentor for the ARM Soil Water and Temperature System (SWATS) Bookmark and Share The ARM Climate Research Facility is seeking an ARM...

  15. ARM - Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76) (SeeCenterARM Mobile Facility 1ARM Mobile Facility 118,

  16. ARM - Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76) (SeeCenterARM Mobile Facility 1ARM Mobile Facility

  17. ARM - Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76) (SeeCenterARM Mobile Facility 1ARM Mobile FacilityMay 1,

  18. ARM - Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76) (SeeCenterARM Mobile Facility 1ARM Mobile FacilityMay

  19. ARM - Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76) (SeeCenterARM Mobile Facility 1ARM Mobile

  20. Atmospheric Radiation Measurement (ARM) Data from the ARM Aerial Facility

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

    The Atmospheric Radiation Measurement (ARM) Program is the largest global change research program supported by the U.S. Department of Energy. The primary goal of the ARM Program is to improve the treatment of cloud and radiation physics in global climate models in order to improve the climate simulation capabilities of these models. ARM data is collected both through permanent monitoring stations and field campaigns around the world. Airborne measurements required to answer science questions from researchers or to validate ground data are also collected. To find data from all categories of aerial operations, follow the links from the AAF information page at http://www.arm.gov/sites/aaf. Tables of information will provide start dates, duration, lead scientist, and the research site for each of the named campaigns. The title of a campaign leads, in turn, to a project description, contact information, and links to the data. Users will be requested to create a password, but the data files are free for viewing and downloading. The ARM Archive physically resides at the Oak Ridge National Laboratory.

  1. 7, 80878111, 2007 Influence of cloud top

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    ACPD 7, 8087­8111, 2007 Influence of cloud top variability on radiative transfer Richter, Barfus top variability from radar measurements on 3-D radiative transfer F. Richter 1 , K. Barfus 1 , F. H.richter@awi.de) 8087 #12;ACPD 7, 8087­8111, 2007 Influence of cloud top variability on radiative transfer Richter

  2. The ARM Aerial Facility in the Biomass Burn

    E-Print Network [OSTI]

    Ohta, Shigemi

    VDC (incl. 85A @ 115 VAC, 60 Hz) Ceiling: 7.6 km G-1 (BMI owned, ARM base funded, PNNL based. Kleinman & A. Sedlacek (BNL) Twin Column Aerosol Project (TCAP II) Cape Cod, MA PI: Larry Berg (PNNL) ARM Cloud Aerosol Precipitation Experiment (ACAPEX) California PI: Ruby Leung (PNNL) 1 2 3 4 5 6 7 8 9 10 11

  3. Radiative Heating of the ISCCP Upper Level Cloud Regimes and its Impact on the Large-scale Tropical Circulation

    SciTech Connect (OSTI)

    Li, Wei; Schumacher, Courtney; McFarlane, Sally A.

    2013-01-31T23:59:59.000Z

    Radiative heating profiles of the International Satellite Cloud Climatology Project (ISCCP) cloud regimes (or weather states) were estimated by matching ISCCP observations with radiative properties derived from cloud radar and lidar measurements from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) sites at Manus, Papua New Guinea, and Darwin, Australia. Focus was placed on the ISCCP cloud regimes containing the majority of upper level clouds in the tropics, i.e., mesoscale convective systems (MCSs), deep cumulonimbus with cirrus, mixed shallow and deep convection, and thin cirrus. At upper levels, these regimes have average maximum cloud occurrences ranging from 30% to 55% near 12 km with variations depending on the location and cloud regime. The resulting radiative heating profiles have maxima of approximately 1 K/day near 12 km, with equal heating contributions from the longwave and shortwave components. Upper level minima occur near 15 km, with the MCS regime showing the strongest cooling of 0.2 K/day and the thin cirrus showing no cooling. The gradient of upper level heating ranges from 0.2 to 0.4 K/(day?km), with the most convectively active regimes (i.e., MCSs and deep cumulonimbus with cirrus) having the largest gradient. When the above heating profiles were applied to the 25-year ISCCP data set, the tropics-wide average profile has a radiative heating maximum of 0.45Kday-1 near 250 hPa. Column-integrated radiative heating of upper level cloud accounts for about 20% of the latent heating estimated by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The ISCCP radiative heating of tropical upper level cloud only slightly modifies the response of an idealized primitive equation model forced with the tropics-wide TRMM PR latent heating, which suggests that the impact of upper level cloud is more important to large-scale tropical circulation variations because of convective feedbacks rather than direct forcing by the cloud radiative heating profiles. However, the height of the radiative heating maxima and gradient of the heating profiles are important to determine the sign and patterns of the horizontal circulation anomaly driven by radiative heating at upper levels.

  4. ARM - Measurements

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat flux ARM DatagovMeasurementsVisibility ARMProject

  5. ARM - Measurements

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat flux ARM DatagovMeasurementsVisibility

  6. ARM - Measurements

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat flux ARM DatagovMeasurementsVisibilityMeasurements

  7. ARM - Measurements

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat flux ARM

  8. Retrieval of Cloud Ice Water Content Profiles from Advanced Microwave Sounding Unit-B Brightness Temperatures Near the Atmospheric Radiation Measurement Southern Great Plains Site

    SciTech Connect (OSTI)

    Seo, E-K.; Liu, G.

    2005-03-18T23:59:59.000Z

    One of the Atmospheric Radiation Measurement (ARM) Program important goals is to develop and test radiation and cloud parameterizations of climate models using single column modeling (SCMs) (Randall et al. 1996). As forcing terms, SCMs need advection tendency of cloud condensates besides the tendencies of temperature, moisture and momentum. To compute the tendency terms of cloud condensates, 3D distribution of cloud condensates over a scale much larger than the climate model's grid scale is needed. Since they can cover a large area within a short time period, satellite measurements are useful utilities to provide advection tendency of cloud condensates for SCMs. However, so far, most satellite retrieval algorithms only retrieve vertically integrated quantities, for example, in the case of cloud ice, ice water path (IWP). To fulfill the requirement of 3D ice water content field for computing ice water advection, in this study, we develop an ice water content profile retrieval algorithm by combining the vertical distribution characteristics obtained from long-term surface radar observations and satellite high-frequency microwave observations that cover a large area. The algorithm is based on the Bayesian theorem using a priori database derived from analyzing cloud radar observations at the Southern Great Plains (SGP) site. The end product of the algorithm is a 3D ice water content covering 10{sup o} x 10{sup o} surrounding the SGP site during the passage of the satellite. This 3D ice water content, together with wind field analysis, can be used to compute the advection tendency of ice water for SCMs.

  9. Shipboard measurements of the cloud-capped marine boundary layer during FIRE/ASTEX

    SciTech Connect (OSTI)

    NONE

    1997-09-01T23:59:59.000Z

    Results are reported on measurements of the cloud-capped marine boundary layer during FIRE/ASTEX. A method was developed from the ASTEX dataset for measuring profiles of liquid water content, droplet size and concentration from cloud radar/microwave radiometer data in marine boundary layer clouds. Profiles were also determined from the first three moments of the Doppler spectrum measured in drizzle with the ETL cloud radar during ASTEX.

  10. Using Doppler spectra to separate hydrometeor populations and analyze ice precipitation in multilayered mixed-phase clouds

    SciTech Connect (OSTI)

    Rambukkange, Mahlon P.; Verlinde, J.; Eloranta, E. W.; Flynn, Connor J.; Clothiaux, Eugene E.

    2011-01-31T23:59:59.000Z

    Multimodality of cloud radar Doppler spectra is used to partition cloud particle phases and to separate distinct ice populations in the radar sample volume, thereby facilitating analysis of individual ice showers in multilayered mixed-phase clouds. A 35-GHz cloud radar located at Barrow, Alaska, during the Mixed-Phase Arctic Cloud Experiment collected the Doppler spectra. Data from a pair of collocated depolarization lidars confirmed the presence of two liquid cloud layers reported in this study. Surprisingly, both of these cloud layers were embedded in ice precipitation yet maintained their liquid. Our spectral separation of the ice precipitation yielded two distinct ice populations: ice initiated within the two liquid cloud layers and ice precipitation formed in higher cloud layers. Comparisons of ice fall velocity versus radar reflectivity relationships derived for distinct showers reveal that a single relationship might not properly represent the ice showers during this period.

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

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

    Sunshine Pyranometer is one sensor with three output channels: (1) Total (global) solar radiation, (2) Diffuse radiation, and (3) sunshine status. The SPN1 measures short wave...

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006Datastreamstwrcam40m Documentation DataDatastreamsxsaprhsrhi

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006Datastreamstwrcam40m Documentation DataDatastreamsxsaprhsrhi1-min (NAVBE1M)Doppler

  14. ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006Datastreamstwrcam40m DocumentationJanuary 9, 2009 [Events, Feature Stories and8,3,9, 20153,7,8,24,Aerial

  15. ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006Datastreamstwrcam40m DocumentationJanuary 9, 2009 [Events, Feature Stories and8,3,9,

  16. ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006Datastreamstwrcam40m DocumentationJanuary 9, 2009 [Events, Feature Stories and8,3,9,Ship-Based Ice Nuclei

  17. ARM - Field Campaign - Marine ARM GPCI Investigation of Clouds (MAGIC)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL) Campaign Links

  18. ARM - Field Campaign - Marine ARM GPCI Investigation of Clouds (MAGIC):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL) Campaign LinksUltra-High Sensitivity Aerosol

  19. ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL) Campaign LinksUltra-High Sensitivity

  20. ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL) Campaign LinksUltra-High SensitivityBridge

  1. ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL) Campaign LinksUltra-High

  2. ARM - Field Campaign - Marine ARM GPCI Investigations of Clouds (MAGIC):

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa- Polarization Diversity Lidar (PDL) Campaign LinksUltra-HighParsivel Disdrometer

  3. ARM - Field Campaign - ARM Cloud Aerosol Precipitation Experiment (ACAPEX)

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItem NotEnergy, science,SpeedingWu,IntelligenceYouQualityAirborne Carbon

  4. ARM MJO Investigation Experiment on Gan Island (AMIE-Gan) Science Plan

    SciTech Connect (OSTI)

    Long, CL; Del Genio, A; Deng, M; Fu, X; Gustafson, W; Houze, R; Jakob, C; Jensen, M; Johnson, R; Liu, X; Luke, E; May, P; McFarlane, S; Minnis, P; Schumacher, C; Vogelmann, A; Wang, Y; Webster, P; Xie, S; Zhang, C

    2011-04-11T23:59:59.000Z

    The overarching campaign, which includes the ARM Mobile Facility 2 (AMF2) deployment in conjunction with the Dynamics of the Madden-Julian Oscillation (DYNAMO) and the Cooperative Indian Ocean experiment on intraseasonal variability in the Year 2011 (CINDY2011) campaigns, is designed to test several current hypotheses regarding the mechanisms responsible for Madden-Julian Oscillation (MJO) initiation and propagation in the Indian Ocean area. The synergy between the proposed AMF2 deployment with DYNAMO/CINDY2011, and the corresponding funded experiment on Manus, combine for an overarching ARM MJO Investigation Experiment (AMIE) with two components: AMF2 on Gan Island in the Indian Ocean (AMIE-Gan), where the MJO initiates and starts its eastward propagation; and the ARM Manus site (AMIE-Manus), which is in the general area where the MJO usually starts to weaken in climate models. AMIE-Gan will provide measurements of particular interest to Atmospheric System Research (ASR) researchers relevant to improving the representation of MJO initiation in climate models. The framework of DYNAMO/CINDY2011 includes two proposed island-based sites and two ship-based locations forming a square pattern with sonde profiles and scanning precipitation and cloud radars at both island and ship sites. These data will be used to produce a Variational Analysis data set coinciding with the one produced for AMIE-Manus. The synergy between AMIE-Manus and AMIE-Gan will allow studies of the initiation, propagation, and evolution of the convective cloud population within the framework of the MJO. As with AMIE-Manus, AMIE-Gan/DYNAMO also includes a significant modeling component geared toward improving the representation of MJO initiation and propagation in climate and forecast models. This campaign involves the deployment of the second, marine-capable, AMF; all of the included measurement systems; and especially the scanning and vertically pointing radars. The campaign will include sonde launches at a rate of eight per day for the duration of the deployment. The increased sonde launches for the entire period matches that of the AMIE-Manus campaign and makes possible a far more robust Variational Analysis forcing data set product for the entire campaign, and thus better capabilities for modeling studies and synergistic research using the data from both AMIE sites.

  5. ARM - ARM at AGU 2011

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACTOperationsYearSafety PolicyCenterARM at

  6. A census of precipitation features in the tropics using TRMM: radar, ice scattering, and lightning observations

    E-Print Network [OSTI]

    Nesbitt, Stephen William

    1999-01-01T23:59:59.000Z

    and two ocean regions during August, September and October 1998, this study used radar retrievals and 85 GHz Polarization Corrected Temperatures (PCTs, which passively measure relative concentrations of precipitation-sized ice particles within a cloud...

  7. Young stars and clouds in Camelopardalis

    E-Print Network [OSTI]

    V. Straizys; V. Laugalys

    2008-11-18T23:59:59.000Z

    Star formation in the Local spiral arm in the direction of the Galactic longitudes 132--158 deg is reviewed. Recent star-forming activity in this Milky Way direction is evidenced by the presence here of the Cam OB1 association and dense dust and molecular clouds containing H$\\alpha$ emission stars, young irregular variables and infrared stellar objects. The clouds of the Local arm concentrate in two layers at 150-300 pc and at about 900 pc from the Sun. The Perseus arm objects in this direction are at a distance of about 2 kpc.

  8. Simulating mixed-phase Arctic stratus clouds: Sensitivity to ice initiationmechanisms

    SciTech Connect (OSTI)

    Sednev, I.; Menon, S.; McFarquhar, G.

    2009-04-10T23:59:59.000Z

    The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during October 9th-10th, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-hour simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and subsaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

  9. Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

    SciTech Connect (OSTI)

    Sednev, Igor; Sednev, I.; Menon, S.; McFarquhar, G.

    2008-02-18T23:59:59.000Z

    The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9th-10th October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and undersaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

  10. 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.

  11. ARM - Evaluation Product - Cloud Classification VAP

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

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  12. ARM - Field Campaign - Spring Cloud IOP

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

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  13. ARM Cloud Properties Working Group: Meeting Logistics

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new, existing, and futureAn

  14. MMCR Calibration Report

    SciTech Connect (OSTI)

    Mead, D

    2010-03-23T23:59:59.000Z

    Calibration report for the Millimeter Wavelength Cloud Radar performed for the ARM Climate Research Facility by ProSensing Inc.

  15. China's Space Robotic Arms Programs

    E-Print Network [OSTI]

    POLLPETER, Kevin

    2013-01-01T23:59:59.000Z

    2013 China’s Space Robotic Arm Programs Kevin POLLPETERdebris observation and space robotic arm technologies. Thelikely equipped with a robotic arm, grappling the target

  16. The DOE ARM Aerial Facility

    SciTech Connect (OSTI)

    Schmid, Beat; Tomlinson, Jason M.; Hubbe, John M.; Comstock, Jennifer M.; Mei, Fan; Chand, Duli; Pekour, Mikhail S.; Kluzek, Celine D.; Andrews, Elisabeth; Biraud, S.; McFarquhar, Greg

    2014-05-01T23:59:59.000Z

    The Department of Energy Atmospheric Radiation Measurement (ARM) Program is a climate research user facility operating stationary ground sites that provide long-term measurements of climate relevant properties, mobile ground- and ship-based facilities to conduct shorter field campaigns (6-12 months), and the ARM Aerial Facility (AAF). The airborne observations acquired by the AAF enhance the surface-based ARM measurements by providing high-resolution in-situ measurements for process understanding, retrieval-algorithm development, and model evaluation that are not possible using ground- or satellite-based techniques. Several ARM aerial efforts were consolidated into the AAF in 2006. With the exception of a small aircraft used for routine measurements of aerosols and carbon cycle gases, AAF at the time had no dedicated aircraft and only a small number of instruments at its disposal. In this "virtual hangar" mode, AAF successfully carried out several missions contracting with organizations and investigators who provided their research aircraft and instrumentation. In 2009, AAF started managing operations of the Battelle-owned Gulfstream I (G-1) large twin-turboprop research aircraft. Furthermore, the American Recovery and Reinvestment Act of 2009 provided funding for the procurement of over twenty new instruments to be used aboard the G-1 and other AAF virtual-hangar aircraft. AAF now executes missions in the virtual- and real-hangar mode producing freely available datasets for studying aerosol, cloud, and radiative processes in the atmosphere. AAF is also engaged in the maturation and testing of newly developed airborne sensors to help foster the next generation of airborne instruments.

  17. ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)

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

    McCoy, Renata; Xie, Shaocheng

    The ARM CMBE-CLDRAD [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected cloud and radiation relevant quantities from ACRF observations

  18. Evaluation of convection-permitting model simulations of cloud populations associated with the Madden-Julian Oscillation using data collected during the AMIE/DYNAMO field campaign

    SciTech Connect (OSTI)

    Hagos, Samson M.; Feng, Zhe; Burleyson, Casey D.; Lim, Kyo-Sun; Long, Charles N.; Wu, Di; Thompson, Gregory

    2014-11-12T23:59:59.000Z

    Regional cloud permitting model simulations of cloud populations observed during the 2011 ARM Madden Julian Oscillation Investigation Experiment/ Dynamics of Madden-Julian Experiment (AMIE/DYNAMO) field campaign are evaluated against radar and ship-based measurements. Sensitivity of model simulated surface rain rate statistics to parameters and parameterization of hydrometeor sizes in five commonly used WRF microphysics schemes are examined. It is shown that at 2 km grid spacing, the model generally overestimates rain rate from large and deep convective cores. Sensitivity runs involving variation of parameters that affect rain drop or ice particle size distribution (more aggressive break-up process etc) generally reduce the bias in rain-rate and boundary layer temperature statistics as the smaller particles become more vulnerable to evaporation. Furthermore significant improvement in the convective rain-rate statistics is observed when the horizontal grid-spacing is reduced to 1 km and 0.5 km, while it is worsened when run at 4 km grid spacing as increased turbulence enhances evaporation. The results suggest modulation of evaporation processes, through parameterization of turbulent mixing and break-up of hydrometeors may provide a potential avenue for correcting cloud statistics and associated boundary layer temperature biases in regional and global cloud permitting model simulations.

  19. ARM Climate Research Facility Annual Report 2004

    SciTech Connect (OSTI)

    Voyles, J.

    2004-12-31T23:59:59.000Z

    Like a rock that slowly wears away beneath the pressure of a waterfall, planet earth?s climate is almost imperceptibly changing. Glaciers are getting smaller, droughts are lasting longer, and extreme weather events like fires, floods, and tornadoes are occurring with greater frequency. Why? Part of the answer is clouds and the amount of solar radiation they reflect or absorb. These two factors clouds and radiative transfer represent the greatest source of error and uncertainty in the current generation of general circulation models used for climate research and simulation. The U.S. Global Change Research Act of 1990 established an interagency program within the Executive Office of the President to coordinate U.S. agency-sponsored scientific research designed to monitor, understand, and predict changes in the global environment. To address the need for new research on clouds and radiation, the U.S. Department of Energy (DOE) established the Atmospheric Radiation Measurement (ARM) Program. As part of the DOE?s overall Climate Change Science Program, a primary objective of the ARM Program is improved scientific understanding of the fundamental physics related to interactions between clouds and radiative feedback processes in the atmosphere.

  20. ARM - 2000 ARM Science Team Meeting

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

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  1. ARM - 2001 ARM Science Team Meeting

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

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  2. PROGRESS REPORT OF FY 2004 ACTIVITIES: IMPROVED WATER VAPOR AND CLOUD RETRIEVALS AT THE NSA/AAO

    SciTech Connect (OSTI)

    E. R. Westwater; V. V. Leuskiy; M. Klein; A. J. Gasiewski; and J. A. Shaw

    2004-11-01T23:59:59.000Z

    The basic goals of the research are to develop and test algorithms and deploy instruments that improve measurements of water vapor, cloud liquid, and cloud coverage, with a focus on the Arctic conditions of cold temperatures and low concentrations of water vapor. The importance of accurate measurements of column amounts of water vapor and cloud liquid has been well documented by scientists within the Atmospheric Radiation Measurement Program. Although several technologies have been investigated to measure these column amounts, microwave radiometers (MWR) have been used operationally by the ARM program for passive retrievals of these quantities: precipitable water vapor (PWV) and integrated water liquid (IWL). The technology of PWV and IWL retrievals has advanced steadily since the basic 2-channel MWR was first deployed at ARM CART sites Important advances are the development and refinement of the tipcal calibration method [1,2], and improvement of forward model radiative transfer algorithms [3,4]. However, the concern still remains that current instruments deployed by ARM may be inadequate to measure low amounts of PWV and IWL. In the case of water vapor, this is especially important because of the possibility of scaling and/or quality control of radiosondes by the water amount. Extremely dry conditions, with PWV less than 3 mm, commonly occur in Polar Regions during the winter months. Accurate measurements of the PWV during such dry conditions are needed to improve our understanding of the regional radiation energy budgets. The results of a 1999 experiment conducted at the ARM North Slope of Alaska/Adjacent Arctic Ocean (NSA/AAO) site during March of 1999 [5] have shown that the strength associated with the 183 GHz water vapor absorption line makes radiometry in this frequency regime suitable for measuring low amounts of PWV. As a portion of our research, we conducted another millimeter wave radiometric experiment at the NSA/AAO in March-April 2004. This experiment relied heavily on our experiences of the 1999 experiment. Particular attention was paid to issues of radiometric calibration and radiosonde intercomparisons. Our theoretical and experimental work also supplements efforts by industry (F. Solheim, Private Communication) to develop sub-millimeter radiometers for ARM deployment. In addition to quantitative improvement of water vapor measurements at cold temperature, the impact of adding millimeter-wave window channels to improve the sensitivity to arctic clouds was studied. We also deployed an Infrared Cloud Imager (ICI) during this experiment, both for measuring continuous day-night statistics of the study of cloud coverage and identifying conditions suitable for tipcal analysis. This system provided the first capability of determining spatial cloud statistics continuously in both day and night at the NSA site and has been used to demonstrate that biases exist in inferring cloud statistics from either zenith-pointing active sensors (lidars or radars) or sky imagers that rely on scattered sunlight in daytime and star maps at night [6].

  3. Sandia National Laboratories: Radar Friendly Blades

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

    MitigationRadar Friendly Blades Radar Friendly Blades Some wind farms have the potential to cause interference with the normal operation of radar systems used for security, weather...

  4. Tripleclouds: An Efficient Method for Representing Horizontal Cloud Inhomogeneity in 1D Radiation Schemes by Using Three Regions at Each Height

    E-Print Network [OSTI]

    Hogan, Robin

    that a mere 4% increase in global cloud cover could counter- act the warming caused by a doubling of carbon the effect of in- homogeneity on the radiative properties of high cloud. They used cloud radar data to inferTripleclouds: An Efficient Method for Representing Horizontal Cloud Inhomogeneity in 1D Radiation

  5. Atmospheric Radiation Measurement Program Science Plan Current Status and Future Directions of the ARM Science Program

    SciTech Connect (OSTI)

    TP Ackerman; AD Del Genio; RG Ellingson; RA Ferrare; SA Klein; GM McFarquhar; PJ Lamb; CN Long; J Verlinde

    2004-10-30T23:59:59.000Z

    The Atmospheric Radiation Measurement (ARM) Program has matured into one of the key programs in the U.S. Climate Change Science Program. The ARM Program has achieved considerable scientific success in a broad range of activities, including site and instrument development, atmospheric radiative transfer, aerosol science, determination of cloud properties, cloud modeling, and cloud parameterization testing and development. The focus of ARM science has naturally shifted during the last few years to an increasing emphasis on modeling and parameterization studies to take advantage of the long time series of data now available. During the next 5 years, the principal focus of the ARM science program will be to: • Maintain the data record at the fixed ARM sites for at least the next five years. • Improve significantly our understanding of and ability to parameterize the 3-D cloud-radiation problem at scales from the local atmospheric column to the global climate model (GCM) grid square. • Continue developing techniques to retrieve the properties of all clouds, with a special focus on ice clouds and mixed-phase clouds. • Develop a focused research effort on the indirect aerosol problem that spans observations, physical models, and climate model parameterizations. • Implement and evaluate an operational methodology to calculate broad-band heating rates in the atmospheric columns at the ARM sites. • Develop and implement methodologies to use ARM data more effectively to test atmospheric models, both at the cloud-resolving model scale and the GCM scale. • Use these methodologies to diagnose cloud parameterization performance and then refine these parameterizations to improve the accuracy of climate model simulations. In addition, the ARM Program is actively developing a new ARM Mobile Facility (AMF) that will be available for short deployments (several months to a year or more) in climatically important regions. The AMF will have much of the same instrumentation as the remote facilities at ARM’s Tropical Western Pacific and the North Slope of Alaska sites. Over time, this new facility will extend ARM science to a much broader range of conditions for model testing.

  6. Atmospheric Radiation Measurement (ARM) Data from Specific Instruments Used in the ARM Program

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

    ARM is known for its comprehensive set of world-class, and in some cases, unique, instruments available for use by the global scientific community. In addition to the ARM instruments, the ARM Climate Research Facility identifies and acquires a wide variety of data including model, satellite, and surface data, from "external instruments," to augment the data being generated within the program. External instruments belong to organizations that are outside of the ARM Program. Field campaign instruments are another source of data used to augment routine observations. The huge archive of ARM data can be organized by instrument categories into twelve "collections:" Aerosols, Airborne Observations, Atmospheric Carbon, Atmospheric Profiling, Cloud Properties, Derived Quantities and Models, Ocean Observations, Radiometric, Satellite Observations, Surface Meteorology, Surface/Subsurface Properties, and Other. Clicking on one of the instrument categories leads to a page that breaks that category down into sub-categories. For example, "Atmospheric Profiling" is broken down into ARM instruments (with 11 subsets), External Instruments (with 6 subsets), and Field Campaign Instruments (with 42 subsets). Each of the subset links, in turn, leads to detailed information pages and links to specific data streams. Users will be requested to create a password, but the data files are free for viewing and downloading.

  7. Atmospheric State, Cloud Microphysics and Radiative Flux

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

    Mace, Gerald

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

  8. ARM - Evaluation Product - Corrected Precipitation Radar Moments in Antenna

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

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  9. ARM - Evaluation Product - Precipitation Radar Moments Mapped to a

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

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  10. Properties of tropical convection observed by ARM millimeter-radars

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

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  11. Cloud Computing

    SciTech Connect (OSTI)

    Pete Beckman and Ian Foster

    2009-12-04T23:59:59.000Z

    Chicago Matters: Beyond Burnham (WTTW). Chicago has become a world center of "cloud computing." Argonne experts Pete Beckman and Ian Foster explain what "cloud computing" is and how you probably already use it on a daily basis.

  12. ARM Science Team Meeting Scheduled The 11th Annual ARM Science

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

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  13. ARM Mobile Facilities

    ScienceCinema (OSTI)

    Orr, Brad; Coulter, Rich

    2014-09-15T23:59:59.000Z

    This video provides an overview of the ARM Mobile Facilities, two portable climate laboratories that can deploy anywhere in the world for campaigns of at least six months.

  14. ARM - Employment Opportunities Article

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

    Needed in ARM Data Quality Office Bookmark and Share The Cooperative Institute for Mesoscale Meteorological Studies at the University of Oklahoma is seeking a research associate...

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

    SciTech Connect (OSTI)

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

    2014-07-27T23:59:59.000Z

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

  16. Quantifying uncertainties of cloud microphysical property retrievals with a perturbation method

    E-Print Network [OSTI]

    Ohta, Shigemi

    to their modification effects on global radiation balance and atmospheric water cycle. However, representation of clouds Radiation Measurement (ARM) facility, whose primary goal is to carry out long-term observations of cloudsQuantifying uncertainties of cloud microphysical property retrievals with a perturbation method

  17. ARM - 1999 ARM Science Team Meeting

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

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  18. ARM - 2002 ARM Science Team Meeting

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

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  19. ARM - ARM Mobile Facility 1 Article

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

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  20. Darwin : The Third DOE ARM TWP ARCS Site /

    SciTech Connect (OSTI)

    Clements, William E.; Jones, L. A. (Larry A.); Baldwin, T. (Tony); Nitschke, K. (Kim)

    2002-01-01T23:59:59.000Z

    The United States Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Program began operations in its Tropical Western Pacific (TWP) locale in October 1996 when the first Atmospheric Radiation and Cloud Station (ARCS) began collecting data on Manus Island in Papua New Guinea (PNG). Two years later, in November 1998, a second ARCS began operations on the island of Nauru in the Central Pacific. Now a third ARCS has begun collecting data in Darwin, Australia. The Manus, Nauru, and Darwin sites are operated through collaborative agreements with the PNG National Weather Service, The Nauru Department of Industry and Economic Development (IED), and the Australian Bureau of Meteorology's (BOM) Special Services Unit (SSU) respectively. All ARM TWP activities in the region are coordinated with the South Pacific Regional Environment Programme (SPREP) based in Apia, Samoa. The Darwin ARM site and its role in the ARM TWP Program are discussed.

  1. Tropical Cloud Properties and Radiative Heating Profiles

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

    Mather, James

    We have generated a suite of products that includes merged soundings, cloud microphysics, and radiative fluxes and heating profiles. The cloud microphysics is strongly based on the ARM Microbase value added product (Miller et al., 2003). We have made a few changes to the microbase parameterizations to address issues we observed in our initial analysis of the tropical data. The merged sounding product is not directly related to the product developed by ARM but is similar in that it uses the microwave radiometer to scale the radiosonde column water vapor. The radiative fluxes also differ from the ARM BBHRP (Broadband Heating Rate Profile) product in terms of the radiative transfer model and the sampling interval.

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

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

    Shupe, Matthew

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

  3. Contribution to the development of DOE ARM Climate Modeling Best Estimate Data (CMBE) products: Satellite data over the ARM permanent and AMF sites: Final Report

    SciTech Connect (OSTI)

    Xie, B; Dong, X; Xie, S

    2012-05-18T23:59:59.000Z

    To support the LLNL ARM infrastructure team Climate Modeling Best Estimate (CMBE) data development, the University of North Dakota (UND)'s group will provide the LLNL team the NASA CERES and ISCCP satellite retrieved cloud and radiative properties for the periods when they are available over the ARM permanent research sites. The current available datasets, to date, are as follows: the CERES/TERRA during 200003-200812; the CERES/AQUA during 200207-200712; and the ISCCP during 199601-200806. The detailed parameters list below: (1) CERES Shortwave radiative fluxes (net and downwelling); (2) CERES Longwave radiative fluxes (upwelling) - (items 1 & 2 include both all-sky and clear-sky fluxes); (3) CERES Layered clouds (total, high, middle, and low); (4) CERES Cloud thickness; (5) CERES Effective cloud height; (6) CERES cloud microphysical/optical properties; (7) ISCCP optical depth cloud top pressure matrix; (8) ISCCP derived cloud types (r.g., cirrus, stratus, etc.); and (9) ISCCP infrared derived cloud top pressures. (10) The UND group shall apply necessary quality checks to the original CERES and ISCCP data to remove suspicious data points. The temporal resolution for CERES data should be all available satellite overpasses over the ARM sites; for ISCCP data, it should be 3-hourly. The spatial resolution is the closest satellite field of view observations to the ARM surface sites. All the provided satellite data should be in a format that is consistent with the current ARM CMBE dataset so that the satellite data can be easily merged into the CMBE dataset.

  4. Torras: Robot Arm Control 1 Robot Arm Control

    E-Print Network [OSTI]

    Torras, Carme

    Torras: Robot Arm Control 1 Robot Arm Control Carme Torras Institut de Rob#18;otica i Inform#18;atica Industrial (CSIC-UPC) Llorens i Artigas 4-6, 08028-Barcelona. RUNNING HEAD: Robot Arm Control: 34-93-401.57.50 e-mail: ctorras@iri.upc.es #12; Torras: Robot Arm Control 2 INTRODUCTION A robot

  5. ARM - Field Campaign - Fall 1997 SCM IOP

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

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  6. ARM - Publications: Science Team Meeting Documents

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

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  7. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative Absorption and Unbounded Cascade Models of CloudThe ARM

  8. ARM - Publications: Science Team Meeting Documents

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

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  9. ARM - Publications: Science Team Meeting Documents

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

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  10. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative Absorption and UnboundedComparison of ARM CloudInfrared

  11. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative Absorption and UnboundedComparison of ARM CloudInfraredInferring

  12. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In The Classroom: Developing anTropical Anvil Cloud

  13. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation Study ofFullCloud Structure

  14. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation Study ofFullCloud StructureThe

  15. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation Study ofFullCloud

  16. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation Study ofFullCloudScanning High

  17. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation Study ofFullCloudScanning HighThe

  18. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation Study ofFullCloudScanning

  19. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation Study ofFullCloudScanningInferring

  20. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation StudyRelationships BetweenCloud

  1. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA Simulation StudyRelationships BetweenCloudThe

  2. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA SimulationARMValidation of TERRA MODIS Cloud

  3. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA SimulationARMValidation of TERRAASingle Cloud

  4. ARM - Publications: Science Team Meeting Documents

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM In TheA SimulationARMValidationThe March 2000 Cloud

  5. ARM - Publications: Science Team Meeting Documents: Identifying

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa-Anomalous Radiative AbsorptionARM InArctic Facility forofCloud

  6. ARM - Facility News Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM Education TeamARM CapabilitiesOctober 6,ARM Climate

  7. ARM - Facility News Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM Education TeamARM CapabilitiesOctober 6,ARM

  8. Atmospheric Radiation Measurement (ARM) Data from the North Slope Alaska (NSA) Site

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

    The Atmospheric Radiation Measurement (ARM) Program is the largest global change research program supported by the U.S. Department of Energy. The primary goal of the ARM Program is to improve the treatment of cloud and radiation physics in global climate models in order to improve the climate simulation capabilities of these models. To achieve this goal, ARM scientists and researchers around the world use continuous data obtained through the ARM Climate Research Facility. ARM maintains four major, permanent sites for data collection and deploys the ARM Mobile Facility to other sites as determined. The North Slope of Alaska (NSA) site is a permanent site providing data about cloud and radiative processes at high latitudes. These data are being used to refine models and parameterizations as they relate to the Arctic. Centered at Barrow and extending to the south (to the vicinity of Atqasuk), west (to the vicinity of Wainwright), and east (towards Oliktok), the NSA site has become a focal point for atmospheric and ecological research activity on the North Slope. Approximately 300,000 NSA data sets from 1993 to the present reside in the ARM Archive at http://www.archive.arm.gov/. Users will need to register for a password, but all files are then free for viewing or downloading. The ARM Archive physically resides at the Oak Ridge National Laboratory.

  9. Impulse radar studfinder

    DOE Patents [OSTI]

    McEwan, Thomas E. (Livermore, CA)

    1995-01-01T23:59:59.000Z

    An impulse radar studfinder propagates electromagnetic pulses and detects reflected pulses from a fixed range. Unmodulated pulses, about 200 ps wide, are emitted. A large number of reflected pulses are sampled and averaged. Background reflections are subtracted. Reflections from wall studs or other hidden objects are detected and displayed using light emitting diodes.

  10. FINAL REPORT (DE-FG02-97ER62338): Single-column modeling, GCM parameterizations, and ARM data

    SciTech Connect (OSTI)

    Richard C. J. Somerville

    2009-02-27T23:59:59.000Z

    Our overall goal is the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have compared SCM (single-column model) output with ARM observations at the SGP, NSA and TWP sites. We focus on the predicted cloud amounts and on a suite of radiative quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art three-dimensional atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable.

  11. ARM - Employment Opportunities Article

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

    3, 2014 Employment Opportunities LecturerAssociate Professor in Clouds available at the University of Reading Bookmark and Share The University of Reading is seeking a scientist...

  12. ARM - Employment Opportunities Article

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

    9, 2014 Employment Opportunities Postdoctoral Position Available at LLNL Bookmark and Share The Cloud Processes Research Group at Lawrence Livermore National Laboratory (LLNL)...

  13. Atmospheric Radiation Measurement (ARM) Data from the ARM Specific Measurement Categories

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

    The ARM Program gathers a wide variety of measurements from many different sources. Each day, the Data Archive stores and distributes large quantities of data collected from these sources. Scientists then use these data to research atmospheric radiation balance and cloud feedback processes, which are critical elements of global climate change. The huge archive of ARM data can be organized by measurement categories into six "collections:" Aerosols, Atmospheric Carbon, Atmospheric State, Cloud Properties, Radiometric, and Surface Properties. Clicking on one of the measurement categories leads to a page that breaks that category down into sub-categories. For example, "Aerosols" is broken down into Microphysical and Chemical Properties (with 9 subsets) and Optical and Radiative Properties (with 7 subsets). Each of the subset links, in turn, leads to detailed information pages and links to specific data streams. Users will be requested to create a password, but the data files are free for viewing and downloading. The ARM Archive physically resides at the Oak Ridge National Laboratory.

  14. At this meeting: Oral presentation: Cloud Properties From (A)ATSR (Caroline Poulsen)

    E-Print Network [OSTI]

    Oxford, University of

    sensors including radars, an infrared and microwave sounder unit, and microwave radiometer integrated vertically over each layer separated by cloud base. This strategy makes it possible to evaluate. Recent progress in satellite sensor technology, exempli- fied by hyperspectral sounders and cloud

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

    SciTech Connect (OSTI)

    Shupe, Matthew D

    2007-10-01T23:59:59.000Z

    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.

  16. Retrieval of Cloud Phase Using the Moderate Resolution Imaging Spectroradiometer Data during the Mixed-Phase Arctic Cloud Experiment

    SciTech Connect (OSTI)

    Spangenberg, D.; Minnis, P.; Shupe, M.; Uttal, T.; Poellot, M.

    2005-03-18T23:59:59.000Z

    Improving climate model predictions over Earth's polar regions requires a comprehensive knowledge of polar cloud microphysics. Over the Arctic, there is minimal contrast between the clouds and background snow surface, making it difficult to detect clouds and retrieve their phase from space. Snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds make it even more difficult to determine cloud phase. Also, since determining cloud phase is the first step toward analyzing cloud optical depth, particle size, and water content, it is vital that the phase be correct in order to obtain accurate microphysical and bulk properties. Changes in these cloud properties will, in turn, affect the Arctic climate since clouds are expected to play a critical role in the sea ice albedo feedback. In this paper, the IR trispectral technique (IRTST) is used as a starting point for a WV and 11-{micro}m brightness temperature (T11) parameterization (WVT11P) of cloud phase using MODIS data. In addition to its ability to detect mixed-phase clouds, the WVT11P also has the capability to identify thin cirrus clouds overlying mixed or liquid phase clouds (multiphase ice). Results from the Atmospheric Radiation Measurement (ARM) MODIS phase model (AMPHM) are compared to the surface-based cloud phase retrievals over the ARM North Slope of Alaska (NSA) Barrow site and to in-situ data taken from University of North Dakota Citation (CIT) aircraft which flew during the Mixed-Phase Arctic Cloud Experiment (MPACE). It will be shown that the IRTST and WVT11P combined to form the AMPHM can achieve a relative high accuracy of phase discrimination compared to the surface-based retrievals. Since it only uses MODIS WV and IR channels, the AMPHM is robust in the sense that it can be applied to daytime, twilight, and nighttime scenes with no discontinuities in the output phase.

  17. Anvil characteristics as seen by C-POL during the Tropical Warm Pool International Cloud Experiment (TWP-ICE)

    E-Print Network [OSTI]

    Frederick, Kaycee Loretta

    2007-04-25T23:59:59.000Z

    The Tropical Pacific Warm Pool International Cloud Experiment (TWP-ICE) took place in Darwin, Australia in early 2006. C-band radar data from this experiment were used to characterize tropical anvil areal coverage, height, and thickness during...

  18. Cloud climatology at the Southern Great Plains and the layer structure, drizzle, and atmospheric modes of continental stratus

    E-Print Network [OSTI]

    of cloud layers, an issue that is important in calculating both the radiative and the hydro- logic effects.5 years) cloud observations from the Atmospheric Radiation Measurements (ARM) program Southern Great in Global Climate Models (GCMs) remains a source of uncertainty in climate simulations. Cloud climatologies

  19. Imaging synthetic aperture radar

    DOE Patents [OSTI]

    Burns, Bryan L. (Tijeras, NM); Cordaro, J. Thomas (Albuquerque, NM)

    1997-01-01T23:59:59.000Z

    A linear-FM SAR imaging radar method and apparatus to produce a real-time image by first arranging the returned signals into a plurality of subaperture arrays, the columns of each subaperture array having samples of dechirped baseband pulses, and further including a processing of each subaperture array to obtain coarse-resolution in azimuth, then fine-resolution in range, and lastly, to combine the processed subapertures to obtain the final fine-resolution in azimuth. Greater efficiency is achieved because both the transmitted signal and a local oscillator signal mixed with the returned signal can be varied on a pulse-to-pulse basis as a function of radar motion. Moreover, a novel circuit can adjust the sampling location and the A/D sample rate of the combined dechirped baseband signal which greatly reduces processing time and hardware. The processing steps include implementing a window function, stabilizing either a central reference point and/or all other points of a subaperture with respect to doppler frequency and/or range as a function of radar motion, sorting and compressing the signals using a standard fourier transforms. The stabilization of each processing part is accomplished with vector multiplication using waveforms generated as a function of radar motion wherein these waveforms may be synthesized in integrated circuits. Stabilization of range migration as a function of doppler frequency by simple vector multiplication is a particularly useful feature of the invention; as is stabilization of azimuth migration by correcting for spatially varying phase errors prior to the application of an autofocus process.

  20. ARM - Field Campaign - ARM LBNL Carbon Project

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM2, 2006Observations of the

  1. ARM - ARM Education and Outreach Contact Information

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItem NotEnergy, science,SpeedingWu,IntelligenceYou are70 Years ofAA-ZHomeroomARM

  2. ARM - ARM Summer Training and Science Applications

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItem NotEnergy, science,SpeedingWu,IntelligenceYou are70 YearsPlainsARM Summer Training

  3. ARM - 1993 ARM Science Team Meeting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1 OTATI OEP AEGraphic3 ARM Science

  4. ARM - 1994 ARM Science Team Meeting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1 OTATI OEP AEGraphic3 ARM Science4

  5. ARM - 1995 ARM Science Team Meeting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1 OTATI OEP AEGraphic3 ARM Science45

  6. ARM - 1996 ARM Science Team Meeting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1 OTATI OEP AEGraphic3 ARM Science456

  7. ARM - 1997 ARM Science Team Meeting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1 OTATI OEP AEGraphic3 ARM Science4567

  8. ARM - 1998 ARM Science Team Meeting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1 OTATI OEP AEGraphic3 ARM

  9. ARM - 2003 ARM Science Team Meeting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1 OTATI OEP AEGraphic3 ARM9Meeting

  10. ARM - AGU Presentations Featuring ARM Data

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OF CONTRACT 1CenterAGU Presentations Featuring ARM

  11. Performance limits for exo-clutter Ground Moving Target Indicator (GMTI) radar.

    SciTech Connect (OSTI)

    Doerry, Armin Walter

    2010-09-01T23:59:59.000Z

    The performance of a Ground Moving Target Indicator (GMTI) radar system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to 'get your arms around' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall GMTI radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'.

  12. Retrieval of cloud properties using SCIAMACHY on ENVISAT

    E-Print Network [OSTI]

    Kuligowski, Bob

    ;2 AGENDA 1. Rationale 2. SCIAMACHY and its calibration 3. Algorithms 4. SCIMACHY cloud retrievals 5 Synthetic Aperture Radar (ASAR), operating at C-band, ASAR ensures continuity with the image mode (SAR;13 VICARIOUS CALIBRATION USING MERIS #12;14 MERIS on ENVISAT spacecraft /1.03.2002-present/ · Instrument bands

  13. ARM - Facility News Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM2, 2006 [Facility News]SPARTICUSJune 30, 2010ARM31,

  14. ARM - Facility News Article

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032)8Li (59AJ76)ARM2, 2006 [Facility News]SPARTICUSJune 30, 2010ARM31,5,

  15. ARM - Measurement - Atmospheric moisture

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

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  16. ARM - Measurement - Visibility

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  17. ARM Climate Research Facility

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  18. ARM Climate Research Facility

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWP TWP Related Links Facilities andPastWritten Records5 ARM Climate3 ARM

  19. ARM Summer Training Schedule

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  20. ARM - Blog Article

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  1. ARM - Blog Article

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  2. ARM - Blog Article

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  3. ARM - Blog Article

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  4. ARM - Blog Article

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  5. ARM - Blog Article

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  6. ARM - Facility News Article

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  7. ARM - Facility News Article

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  8. ARM - Facility News Article

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  9. ARM - Facility News Article

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  10. ARM - Facility News Article

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  11. ARM - Facility News Article

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  12. ARM - Facility News Article

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  13. ARM - Facility News Article

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  14. ARM - Facility News Article

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  15. ARM - Facility News Article

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  16. ARM - Facility News Article

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  17. ARM - Facility News Article

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  18. ARM - Facility News Article

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  19. ARM - Facility News Article

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  20. ARM - Facility News Article

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  1. ARM - Facility News Article

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  2. ARM - Facility News Article

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  3. ARM - Facility News Article

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  4. ARM - Facility News Article

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  5. ARM - Facility News Article

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  6. ARM - Facility News Article

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  7. ARM - Facility News Article

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  8. ARM - Facility News Article

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  9. ARM - Facility News Article

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  10. ARM - Facility News Article

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  11. ARM - Facility News Article

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  12. ARM - Facility News Article

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  13. ARM - Facility News Article

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  14. ARM Site Atmospheric State Best Estimates for AIRS Validation

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1 ARM

  15. Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Imager Data over the Atmospheric Radiation Measurement Sites

    SciTech Connect (OSTI)

    Trepte, Q.Z.; Minnis, P.; Heck, P.W.; Palikonda, R.

    2005-03-18T23:59:59.000Z

    Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 {micro}m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-{micro}m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60{sup o}N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).

  16. Triggered star formation in the Magellanic Clouds

    E-Print Network [OSTI]

    B. G. Elmegreen; J. Palous; Kenji Bekki

    2006-01-01T23:59:59.000Z

    Abstract. We discuss how tidal interaction between the Large Magellanic Cloud (LMC), the Small Magellanic Cloud (SMC), and the Galaxy triggers galaxy-wide star formation in the Clouds for the last ? 0.2 Gyr based on our chemodynamical simulations on the Clouds. Our simulations demonstrate that the tidal interaction induces the formation of asymmetric spiral arms with high gas densities and consequently triggers star formation within the arms in the LMC. Star formation rate in the present LMC is significantly enhanced just above the eastern edge of the LMC’s stellar bar owing to the tidal interaction. The location of the enhanced star formation is very similar to the observed location of 30 Doradus, which suggests that the formation of 30 Doradus is closely associated with the last Magellanic collision about 0.2 Gyr ago. The tidal interaction can dramatically compress gas initially within the outer part of the SMC so that new stars can be formed from the gas to become intergalactic young stars in the inter-Cloud region (e.g., the Magellanic Bridge). The metallicity distribution function of the newly formed stars in the Magellanic Bridge has a peak of [Fe/H] ? ?0.8, which is significantly lower than the stellar metallicity of the SMC.

  17. Application Study: Robot Arm Control

    E-Print Network [OSTI]

    Visser, Arnoud

    Application Study: Robot Arm Control An experience using distributed AIM Arnoud Visser Michiel Wiedijk Frank Tuijnman Hamideh Afsarmanesh November 1993 u University of Amsterdam #12;2 1. The Robot Arm application at UvA In the robot arm application we deal with three agents that are heterogeneous

  18. Radar | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ | Roadmap Jump to:b <RGS Development BV JumpRTEV IncRadar

  19. Data Quality Assessment and Control for the ARM Climate Research Facility

    SciTech Connect (OSTI)

    Peppler, R

    2012-06-26T23:59:59.000Z

    The mission of the Atmospheric Radiation Measurement (ARM) Climate Research Facility is to provide observations of the earth climate system to the climate research community for the purpose of improving the understanding and representation, in climate and earth system models, of clouds and aerosols as well as their coupling with the Earth's surface. In order for ARM measurements to be useful toward this goal, it is important that the measurements are of a known and reasonable quality. The ARM data quality program includes several components designed to identify quality issues in near-real-time, track problems to solutions, assess more subtle long-term issues, and communicate problems to the user community.

  20. Cloud Computing Adam Barker

    E-Print Network [OSTI]

    St Andrews, University of

    Cloud Computing 1 Adam Barker #12;Overview · Introduction to Cloud computing · Enabling technologies · Di erent types of cloud: IaaS, PaaS and SaaS · Cloud terminology · Interacting with a cloud: management consoles · Launching an instance · Connecting to an instance · Running your application · Clouds

  1. The Radiative Properties of Small Clouds: Multi-Scale Observations and Modeling

    SciTech Connect (OSTI)

    Feingold, Graham [NOAA ESRL; McComiskey, Allison [CIRES, University of Colorado

    2013-09-25T23:59:59.000Z

    Warm, liquid clouds and their representation in climate models continue to represent one of the most significant unknowns in climate sensitivity and climate change. Our project combines ARM observations, LES modeling, and satellite imagery to characterize shallow clouds and the role of aerosol in modifying their radiative effects.

  2. Ground-Based Radar

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power AdministrationField8,Dist.NewofGeothermal Heaton Armed ServicesGround-Based Microwave

  3. Study of Multi-Scale Cloud Processes Over the Tropical Western Pacific Using Cloud-Resolving Models Constrained by Satellite Data

    SciTech Connect (OSTI)

    Dudhia, Jimy

    2013-03-12T23:59:59.000Z

    Clouds in the tropical western Pacific are an integral part of the large scale environment. An improved understanding of the multi-scale structure of clouds and their interactions with the environment is critical to the ARM (Atmospheric Radiation Measurement) program for developing and evaluating cloud parameterizations, understanding the consequences of model biases, and providing a context for interpreting the observational data collected over the ARM Tropical Western Pacific (TWP) sites. Three-dimensional cloud resolving models (CRMs) are powerful tools for developing and evaluating cloud parameterizations. However, a significant challenge in using CRMs in the TWP is that the region lacks conventional data, so large uncertainty exists in defining the large-scale environment for clouds. This project links several aspects of the ARM program, from measurements to providing improved analyses, and from cloud-resolving modeling to climate-scale modeling and parameterization development, with the overall objective to improve the representations of clouds in climate models and to simulate and quantify resolved cloud effects on the large-scale environment. Our objectives will be achieved through a series of tasks focusing on the use of the Weather Research and Forecasting (WRF) model and ARM data. Our approach includes: -- Perform assimilation of COSMIC GPS radio occultation and other satellites products using the WRF Ensemble Kalman Filter assimilation system to represent the tropical large-scale environment at 36 km grid resolution. This high-resolution analysis can be used by the community to derive forcing products for single-column models or cloud-resolving models. -- Perform cloud-resolving simulations using WRF and its nesting capabilities, driven by the improved regional analysis and evaluate the simulations against ARM datasets such as from TWP-ICE to optimize the microphysics parameters for this region. A cirrus study (Mace and co-authors) already exists for TWP-ICE using satellite and ground-based observations. -- Perform numerical experiments using WRF to investigate how convection over tropical islands in the Maritime Continent interacts with large-scale circulation and affects convection in nearby regions. -- Evaluate and apply WRF as a testbed for GCM cloud parameterizations, utilizing the ability of WRF to run on multiple scales (from cloud resolving to global) to isolate resolution and physics issues from dynamical and model framework issues. Key products will be disseminated to the ARM and larger community through distribution of data archives, including model outputs from the data assimilation products and cloud resolving simulations, and publications.

  4. ARM User Survey Report

    SciTech Connect (OSTI)

    Roeder, LR

    2010-06-22T23:59:59.000Z

    The objective of this survey was to obtain user feedback to, among other things, determine how to organize the exponentially growing data within the Atmospheric Radiation Measurement (ARM) Climate Research Facility, and identify users’ preferred data analysis system. The survey findings appear to have met this objective, having received approximately 300 responses that give insight into the type of work users perform, usage of the data, percentage of data analysis users might perform on an ARM-hosted computing resource, downloading volume level where users begin having reservations, opinion about usage if given more powerful computing resources (including ability to manipulate data), types of tools that would be most beneficial to them, preferred programming language and data analysis system, level of importance for certain types of capabilities, and finally, level of interest in participating in a code-sharing community.

  5. Robot arm apparatus

    DOE Patents [OSTI]

    Nachbar, Henry D. (Ballston Lake, NY)

    1992-01-01T23:59:59.000Z

    A robot arm apparatus is provided for inspecting and/or maintaining an interior of a steam generator which has an outside wall and a port for accessing the interior of the steam generator. The robot arm apparatus includes a flexible movable conduit for conveying inspection and/or maintenance apparatus from outside the steam generator to the interior of the steam generator. The flexible conduit has a terminal working end which is translated into and around the interior of the steam generator. Three motors located outside the steam generator are employed for moving the terminal working end inside the steam generator in "x", "y", and "z" directions, respectively. Commonly conducted inspection and maintenance operations include visual inspection for damaged areas, water jet lancing for cleaning sludge deposits, core boring for obtaining sludge deposits, and scrubbing of internal parts.

  6. Robot arm apparatus

    DOE Patents [OSTI]

    Nachbar, Henry D.

    1992-12-01T23:59:59.000Z

    A robot arm apparatus is provided for inspecting and/or maintaining an interior of a steam generator which has an outside wall and a port for accessing the interior of the steam generator. The robot arm apparatus includes a flexible movable conduit for conveying inspection and/or maintenance apparatus from outside the steam generator to the interior of the steam generator. The flexible conduit has a terminal working end which is translated into and around the interior of the steam generator. Three motors located outside the steam generator are employed for moving the terminal working end inside the steam generator in "x", "y", and "z" directions, respectively. Commonly conducted inspection and maintenance operations include visual inspection for damaged areas, water jet lancing for cleaning sludge deposits, core boring for obtaining sludge deposits, and scrubbing of internal parts.

  7. Lecture Ch. 8 Cloud Classification

    E-Print Network [OSTI]

    Russell, Lynn

    clouds Middle clouds Grayish, block the sun, sometimes patchy Sharp outlines, rising, bright white1 Lecture Ch. 8 · Cloud Classification ­ Descriptive approach to clouds · Drop Growth and Precipitation Processes ­ Microphysical characterization of clouds · Complex (i.e. Real) Clouds ­ Examples

  8. Radar polarimetry for geoscience applications

    SciTech Connect (OSTI)

    Elachi, C.; Kuga, Y.; McDonald, K.; Sarabandi, K.; Ulaby, F.T.; Whitt, M.; Zebker, H.; van Zyl, J.J.

    1990-01-01T23:59:59.000Z

    A source book for remote sensing and radar design engineers, this text covers wave polarization, polarization synthesis, scattering matrices, SAR polarization systems, and an array of applications It covers: an introduction to the different mathematical representations used to describe scattering properties, a review of scatterometer system design and calibration techniques for use in polarimetric measurements, a study of specific polarimetric radar systems, such as the shuttle imaging radar C (SIR-C), that includes calibration and compression techniques, data processing guidelines, and design approaches.

  9. Worldwide report, arms control

    SciTech Connect (OSTI)

    NONE

    1987-03-18T23:59:59.000Z

    This report contains translations/transcriptions of articles and/or broadcasts on Arms Control. Titles include: USSR Journal Review of French Book on SDI; Moscow Talk Show Considers Possibility of Dealing with U.S.; Thatcher, Gorbachev Talks Anticipated; U.S. Presents Draft Treaty to Eliminate INF from Europe; TASS: White House Rejects Treaty of Tatotonga; Soviet Paper on Congressional Divisions on Moratorium; Turkish Officials on Deployment of Nuclear Weapons; and others.

  10. ARM - Instrument - tlcv

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  11. ARM - Instrument - toms

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  12. ARM - Instrument - tracegas

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  13. ARM - Instrument - tsi

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  14. ARM - Instrument - twr

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  15. ARM - Instrument - twrcam

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  16. ARM - Instrument - uhsas

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  17. ARM - Instrument - usdarad

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  18. ARM - Instrument - vdis

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

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  19. ARM - Instrument - wacr

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  20. ARM - Instrument - wpdn

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

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  1. ARM - Instrument - wsacr

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDC documentation ARM

  2. ARM - Measurement - Atmospheric temperature

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDC documentationBarrow, AlaskaWhenimage ARM

  3. ARM - Measurement - Convection

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDC documentationBarrow,ice particle ARM

  4. ARM - Measurement - Methane flux

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowband upwelling irradiance ARM Data Discovery

  5. ARM - Measurement - Nitrogen

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowband upwelling irradiance ARM

  6. ARM - Measurement - Soil moisture

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat flux ARM Data Discovery Browse Data Comments?

  7. ARM - Measurement - Surface albedo

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat flux ARM Data Discovery Browse Datasurfacealbedo

  8. ARM - Measurement - Surface condition

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat flux ARM Data Discovery Browse

  9. ARM - Measurement - Total carbon

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  10. ARM - Measurement - Vertical velocity

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  11. ARM - Measurement - Virtual temperature

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

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  12. ARM Science Meeting

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores

  13. ARM TR-008

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores1

  14. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores19 Evaluation

  15. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores19 Evaluation10

  16. ARM TR-008

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    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores19

  17. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar Azores195 Atmospheric

  18. ARM TR-008

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  19. ARM TR-008

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  20. ARM TR-008

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  1. ARM TR-008

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  2. ARM TR-008

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

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  3. ARM TR-008

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  4. ARM TR-008

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

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  5. ARM TR-008

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

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  6. ARM TR-008

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

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  7. ARM TR-008

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

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  8. ARM TR-008

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  9. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror Dew8

  10. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror

  11. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror5

  12. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror55

  13. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror555

  14. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror555

  15. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror5558

  16. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Mirror55586

  17. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled

  18. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled Disdrometer

  19. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled

  20. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled51 Rotating

  1. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled51

  2. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled516 SKYRAD

  3. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled516

  4. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled5161 Surface

  5. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled5161

  6. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled516162

  7. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled5161627

  8. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32 Chilled516162764

  9. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar32

  10. ARM TR-008

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323 Whole-Sky Imager

  11. ARM TR-009

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323 Whole-Sky Imager9

  12. ARM TR-047

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323 Whole-Sky Imager97

  13. ARM XDC Datastreams

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProducts (VAP) VAP Update Information on new,Scanning Radar323ARMStreamsC-Band

  14. Evaluation of GCM Column Radiation Models Under Cloudy Conditions with The Arm BBHRP Value Added Product

    SciTech Connect (OSTI)

    Dr. Lazaros Oreopoulos and Dr. Peter M. Norris

    2010-03-14T23:59:59.000Z

    The overarching goal of the project was to improve the transfer of solar and thermal radiation in the most sophisticated computer tools that are currently available for climate studies, namely Global Climate Models (GCMs). This transfer can be conceptually separated into propagation of radiation under cloudy and under cloudless conditions. For cloudless conditions, the factors that affect radiation propagation are gaseous absorption and scattering, aerosol particle absorption and scattering and surface albedo and emissivity. For cloudy atmospheres the factors are the various cloud properties such as cloud fraction, amount of cloud condensate, the size of the cloud particles, and morphological cloud features such as cloud vertical location, cloud horizontal and vertical inhomogeneity and cloud shape and size. The project addressed various aspects of the influence of the above contributors to atmospheric radiative transfer variability. In particular, it examined: (a) the quality of radiative transfer for cloudless and non-complex cloudy conditions for a substantial number of radiation algorithms used in current GCMs; (b) the errors in radiative fluxes from neglecting the horizontal variabiity of cloud extinction; (c) the statistical properties of cloud horizontal and vertical cloud inhomogeneity that can be incorporated into radiative transfer codes; (d) the potential albedo effects of changes in the particle size of liquid clouds; (e) the gaseous radiative forcing in the presence of clouds; and (f) the relative contribution of clouds of different sizes to the reflectance of a cloud field. To conduct the research in the various facets of the project, data from both the DOE ARM project and other sources were used. The outcomes of the project will have tangible effects on how the calculation of radiative energy will be approached in future editions of GCMs. With better calculations of radiative energy in GCMs more reliable predictions of future climate states will be attainable, thus affecting public policy decisions with great impact to public life.

  15. Cloud Controlling Factors --Low Clouds BJORN STEVENS,

    E-Print Network [OSTI]

    Stevens, Bjorn

    Cloud Controlling Factors -- Low Clouds BJORN STEVENS, Department of Atmospheric and Oceanic) clouds is reviewed, with an emphasis on factors that may be expected to change in a changing climate of low-cloud control- ling processes are offered: these include renewing our focus on theory, model

  16. Cloud Controlling Factors --Low Clouds BJORN STEVENS,

    E-Print Network [OSTI]

    Stevens, Bjorn

    Cloud Controlling Factors -- Low Clouds BJORN STEVENS, Department of Atmospheric and Oceanic conspire to determine the statistics and cli- matology of layers of shallow (boundary layer) clouds of low-cloud control- ling processes are offered: these include renewing our focus on theory, model

  17. Cloud Tracking in Cloud-Resolving Models

    E-Print Network [OSTI]

    Plant, Robert

    Cloud Tracking in Cloud-Resolving Models RMetS Conference 4th September 2007 Bob Plant Department of Meteorology, University of Reading, UK #12;Introduction Obtain life cycle statistics for clouds in CRM simulations What is the distribution of cloud lifetimes? What factors determine the lifetime of an individual

  18. Contributions of the Atmospheric Radiation Measurement (ARM) Program and the ARM Climate Research Facility to the U.S. Climate Change Science Program

    SciTech Connect (OSTI)

    SA Edgerton; LR Roeder

    2008-09-30T23:59:59.000Z

    The Earth’s surface temperature is determined by the balance between incoming solar radiation and thermal (or infrared) radiation emitted by the Earth back to space. Changes in atmospheric composition, including greenhouse gases, clouds, and aerosols can alter this balance and produce significant climate change. Global climate models (GCMs) are the primary tool for quantifying future climate change; however, there remain significant uncertainties in the GCM treatment of clouds, aerosol, and their effects on the Earth’s energy balance. The 2007 assessment (AR4) by the Intergovernmental Panel on Climate Change (IPCC) reports a substantial range among GCMs in climate sensitivity to greenhouse gas emissions. The largest contributor to this range lies in how different models handle changes in the way clouds absorb or reflect radiative energy in a changing climate (Solomon et al. 2007). In 1989, the U.S. Department of Energy (DOE) Office of Science created the Atmospheric Radiation Measurement (ARM) Program within the Office of Biological and Environmental Research (BER) to address scientific uncertainties related to global climate change, with a specific focus on the crucial role of clouds and their influence on the transfer of radiation in the atmosphere. To address this problem, BER has adopted a unique two-pronged approach: * The ARM Climate Research Facility (ACRF), a scientific user facility for obtaining long-term measurements of radiative fluxes, cloud and aerosol properties, and related atmospheric characteristics in diverse climate regimes. * The ARM Science Program, focused on the analysis of ACRF data to address climate science issues associated with clouds, aerosols, and radiation, and to improve GCMs. This report describes accomplishments of the BER ARM Program toward addressing the primary uncertainties related to climate change prediction as identified by the IPCC.

  19. Posters Radar/Radiometer Retrievals of Cloud Liquid Water and

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible forPortsmouth/Paducah Project Office PressPostdoctoraldecadal observations71971 Posters

  20. Mixed-Phase Cloud Retrievals Using Doppler Radar Spectra

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA / USACE625DataNeutrinoMissionMissionJenningsMixed-Phase