Sample records for w-band arm cloud

  1. W-band ARM Cloud Radar (WACR) Handbook

    SciTech Connect (OSTI)

    Widener, KB; Johnson, K

    2005-01-05T23:59:59.000Z

    The W-band Atmospheric Radiation Measurement (ARM) Program Cloud Radar (WACR) systems are zenith pointing Doppler radars that probe the extent and composition of clouds at 95.04 GHz. The main purpose of this radar is to determine cloud boundaries (e.g., cloud bottoms and tops). This radar reports estimates for the first three spectra moments for each range gate up to 15 km. The 0th moment is reflectivity, the 1st moment is radial velocity, and the 2nd moment is spectral width. Also available are the raw spectra files. Unlike the millimeter wavelength cloud radar (MMCR), the WACR does not use pulse coding and operates in only copolarization and cross-polarization modes.

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

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

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  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. Scanning ARM Cloud Radar Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N; Johnson, K

    2012-06-18T23:59:59.000Z

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

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

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

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  7. Observing Warm Clouds in 3D Using ARM Scanning Cloud

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

    Observing Warm Clouds in 3D Using ARM Scanning Cloud Radars and a Novel Ensemble Method For original submission and image(s), see ARM Research Highlights http:www.arm.gov...

  8. ARM - Measurement - Cloud size

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  9. ARM - Measurement - Cloud extinction

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  10. ARM - Measurement - Cloud fraction

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  11. ARM - Measurement - Cloud location

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

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  12. ARM - Measurement - Cloud phase

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  13. ARM - Measurement - Cloud type

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

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  14. ARM - Field Campaign - Cloud IOP

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  15. ARM - Cloud and Rain

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

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  16. 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.

  17. ARM - Measurement - Cloud ice particle

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  18. ARM - Measurement - Cloud top height

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

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  20. ARM - Measurement - Cloud droplet size

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

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  1. ARM - Measurement - Cloud effective radius

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  2. ARM - Measurement - Cloud optical depth

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  3. ARM - Measurement - Total cloud water

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  4. ARM Cloud Properties Working Group: Meeting Logistics

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  5. ARM - Lesson Plans: Making Clouds

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

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  6. 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.

  7. 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.

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

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  9. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery Browse DataCloud

  10. Scanning ARM Cloud Radars Part I: Operational Sampling Strategies

    SciTech Connect (OSTI)

    Kollias, Pavlos; Bharadwaj, Nitin; Widener, Kevin B.; Jo, Ieng; Johnson, Karen

    2014-03-01T23:59:59.000Z

    Probing clouds in three-dimensions has never been done with scanning millimeter-wavelength (cloud) radars in a continuous operating environment. The acquisition of scanning cloud radars by the Atmospheric Radiation Measurement (ARM) program and research institutions around the world generate the need for developing operational scan strategies for cloud radars. Here, the first generation of sampling strategies for the Scanning ARM Cloud Radars (SACRs) is discussed. These scan strategies are designed to address the scientific objectives of the ARM program, however, they introduce an initial framework for operational scanning cloud radars. While the weather community uses scan strategies that are based on a sequence of scans at constant elevations, the SACRs scan strategies are based on a sequence of scans at constant azimuth. This is attributed to the cloud properties that are vastly different for rain and snow shafts that are the primary target of precipitation radars. A “cloud surveillance” scan strategy is introduced (HS-RHI) based on a sequence of horizon-to-horizon Range Height Indicator (RHI) scans that sample the hemispherical sky (HS). The HS-RHI scan strategy is repeated every 30 min to provide a static view of the cloud conditions around the SACR location. Between HS-RHI scan strategies other scan strategies are introduced depending on the cloud conditions. The SACRs are pointing vertically in the case of measurable precipitation at the ground. The radar reflectivities are corrected for water vapor attenuation and non-meteorological detection are removed. A hydrometeor detection mask is introduced based on the difference of cloud and noise statistics is discussed.

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

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

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

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

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

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

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

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

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  15. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data Discovery BrowseMeasuring

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

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

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  17. ARM - Field Campaign - Boundary Layer Cloud IOP

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  18. ARM - Field Campaign - Cloud Radar IOP

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  19. High Field W-Band (95 GHz) EPR | EMSL

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    High Field W-Band (95 GHz) EPR High Field W-Band (95 GHz) EPR The W-band pulsed EPR spectrometer, introduced in 2011, is one of only two of its design worldwide. It uses a...

  20. ARM - Measurement - Cloud particle number concentration

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  1. ARM - Measurement - Cloud particle size distribution

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

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

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

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

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  6. ARM - Evaluation Product - Cloud Classification VAP

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

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  7. ARM - Field Campaign - Fall 1997 Cloud 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3,Cloud ODgovCampaignsFIRE-Arctic CloudgovCampaignsFall

  8. 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.

  9. ARM - Field Campaign - IR Cloud Camera Feasibility Study

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

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  10. 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.

  11. 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.

  12. W-Band Sheet Beam Klystron Design

    SciTech Connect (OSTI)

    Scheitrum, G.; Caryotakis, G.; Burke, A.; Jensen, A.; Jongewaard, E.a Krasnykh, A.; Neubauer, M.; Phillips, R.; Rauenbuehler, K.; /SLAC

    2011-11-11T23:59:59.000Z

    Sheet beam devices provide important advantages for very high power, narrow bandwidth RF sources like accelerator klystrons [1]. Reduced current density and increased surface area result in increased power capabi1ity, reduced magnetic fields for focusing and reduced cathode loading. These advantages are offset by increased complexity, beam formation and transport issues and potential for mode competition in the ovennoded cavities and drift tube. This paper will describe the design issues encountered in developing a 100 kW peak and 2 kW average power sheet beam k1ystron at W-band including beam formation, beam transport, circuit design, circuit fabrication and mode competition.

  13. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band ARM Cloud RadarPearl

  14. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band ARM Cloud

  15. 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

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

    SciTech Connect (OSTI)

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

    2011-09-14T23:59:59.000Z

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

  17. 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)

  18. 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)

  19. 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.

  20. 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.

  1. 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.

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

    E-Print Network [OSTI]

    ARRA-funded Cloud Radar Development for the Department of Energy's ARM Climate Research Facility assembler jobs were saved because of this large order. ProSensing is also planning to engage a local defense for similar cloud radar contracts for customers in India, China and Korea. By developing these complex radar

  3. ARM - SPARTICUS Planning - Data Plots

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band ARM Cloud Radar

  4. 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.

  5. Toward Understanding of Differences in Current Cloud Retrievals of ARM Ground-based Measurements

    SciTech Connect (OSTI)

    Zhao, Chuanfeng; Xie, Shaocheng; Klein, Stephen A.; Protat, Alain; Shupe, Matthew D.; McFarlane, Sally A.; Comstock, Jennifer M.; Delanoe, Julien; Deng, Min; Dunn, Maureen; Hogan, Robin; Huang, Dong; Jensen, Michael; Mace, Gerald G.; McCoy, Renata; O'Conner, Ewan J.; Turner, Dave; Wang, Zhien

    2012-05-30T23:59:59.000Z

    Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasize on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice effective radius. It is shown that most of these large differences have their roots in the retrieval algorithms used by these cloud products, including the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

  6. Comparison of POLDER Apparent and Corrected Oxygen Pressure to ARM/MMCR Cloud Boundary Pressures

    SciTech Connect (OSTI)

    Vanbauce, Claudine; Cadet, Bertrand; Marchand, Roger T.

    2003-03-06T23:59:59.000Z

    POLDER (POLarization and Directionality of the Earth’s Reflectances) cloud oxygen pressures are compared to cloud boundary pressures obtained from the combination of Lidar and Millimeter Wave Cloud Radar ground measurements located at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. Without ground reflection correction, the apparent pressures are found to be closer to the mean cloud pressure than to the cloud top pressure. Nevertheless, for almost a quarter of our comparison cases the apparent pressure level is found to be below the cloud base level. This problem practically disappears applying a simple correction for the surface reflection effect. The corrected oxygen pressures are then found to be very close (12 hPa on average) to the mean cloud pressure.

  7. Toward understanding of differences in current cloud retrievals of ARM ground-based measurements

    SciTech Connect (OSTI)

    Zhao C.; Dunn M.; Xie, S.; Klein, S. A.; Protat, A.; Shupe, M. D.; McFarlane, S. A.; Comstock, J. M.; Delanoë, J.; Deng, M.; Hogan, R. J.; Huang, D.; Jensen, M. P.; Mace, G. G.; McCoy, R.; O’Connor, E. J.; Turner, D. D.; Wang, Z.

    2012-05-30T23:59:59.000Z

    Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

  8. 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...

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

    SciTech Connect (OSTI)

    Alexander Marshak; Warren Wiscombe; Yuri Knyazikhin; Christine Chiu

    2011-05-24T23:59:59.000Z

    We proposed a variety of tasks centered on the following question: what can we learn about 3D cloud-radiation processes and aerosol-cloud interaction from rapid-sampling ARM measurements of spectral zenith radiance? These ARM measurements offer spectacular new and largely unexploited capabilities in both the temporal and spectral domains. Unlike most other ARM instruments, which average over many seconds or take samples many seconds apart, the new spectral zenith radiance measurements are fast enough to resolve natural time scales of cloud change and cloud boundaries as well as the transition zone between cloudy and clear areas. In the case of the shortwave spectrometer, the measurements offer high time resolution and high spectral resolution, allowing new discovery-oriented science which we intend to pursue vigorously. Research objectives are, for convenience, grouped under three themes: â?˘ Understand radiative signature of the transition zone between cloud-free and cloudy areas using data from ARM shortwave radiometers, which has major climatic consequences in both aerosol direct and indirect effect studies. â?˘ Provide cloud property retrievals from the ARM sites and the ARM Mobile Facility for studies of aerosol-cloud interactions. â?˘ Assess impact of 3D cloud structures on aerosol properties using passive and active remote sensing techniques from both ARM and satellite measurements.

  10. 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.

  11. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAn AssessmentARM EngineeringOn theTheARM

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

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

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  13. Climatology and Formation of Tropical Midlevel Clouds at the Darwin ARM Site

    SciTech Connect (OSTI)

    Riihimaki, Laura D.; McFarlane, Sally A.; Comstock, Jennifer M.

    2012-10-01T23:59:59.000Z

    A 4-yr climatology of midlevel clouds is presented from vertically pointing cloud lidar and radar measurements at the Atmospheric Radiation Measurement Program (ARM) site at Darwin, Australia. Few studies exist of tropical midlevel clouds using a dataset of this length. Seventy percent of clouds with top heights between 4 and 8 km are less than 2 km thick. These thin layer clouds have a peak in cloud-top temperature around the melting level (0°C) and also a second peak around -12.5°C. The diurnal frequency of thin clouds is highest during the night and reaches a minimum around noon, consistent with variation caused by solar heating. Using a 1.5-yr subset of the observations, the authors found that thin clouds have a high probability of containing supercooled liquid water at low temperatures: ~20% of clouds at -30°C, ~50% of clouds at -20°C, and ~65% of clouds at -10°C contain supercooled liquid water. The authors hypothesize that thin midlevel clouds formed at the melting level are formed differently during active and break monsoon periods and test this over three monsoon seasons. A greater frequency of thin midlevel clouds are likely formed by increased condensation following the latent cooling of melting during active monsoon periods when stratiform precipitation is most frequent. This is supported by the high percentage (65%) of midlevel clouds with preceding stratiform precipitation and the high frequency of stable layers slightly warmer than 0°C. In the break monsoon, a distinct peak in the frequency of stable layers at 0°C matches the peak in thin midlevel cloudiness, consistent with detrainment from convection.

  14. 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.

  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. 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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  17. 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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  18. ARM - Field Campaign - Complex Layered Cloud Experiment (CLEX)

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

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  19. 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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  20. A Climatology of Surface Cloud Radiative Effects at the ARM Tropical Western Pacific Sites

    SciTech Connect (OSTI)

    McFarlane, Sally A.; Long, Charles N.; Flaherty, Julia E.

    2013-04-01T23:59:59.000Z

    Cloud radiative effects on surface downwelling fluxes are investigated using long-term datasets from the three Atmospheric Radiation Measurement (ARM) sites in the Tropical Western Pacific (TWP) region. The Nauru and Darwin sites show significant variability in sky cover, downwelling radiative fluxes, and surface cloud radiative effect (CRE) due to El Nińo and the Australian monsoon, respectively, while the Manus site shows little intra-seasonal or interannual variability. Cloud radar measurement of cloud base and top heights are used to define cloud types so that the effect of cloud type on the surface CRE can be examined. Clouds with low bases contribute 71-75% of the surface shortwave (SW) CRE and 66-74% of the surface longwave (LW) CRE at the three TWP sites, while clouds with mid-level bases contribute 8-9% of the SW CRE and 12-14% of the LW CRE, and clouds with high bases contribute 16-19% of the SW CRE and 15-21% of the LW CRE.

  1. ARM - PI Product - Cloud Property Retrieval Products for Graciosa Island,

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

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

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

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  3. 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.

  4. 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.

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

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

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  6. ARM - Field Campaign - Midlatitude Continental Convective Clouds Experiment

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

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  7. ARM - Field Campaign - Midlatitude Continental Convective Clouds 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical Depth (AOD) by Microtops ARM Data(MC3E) Experiment

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

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

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  9. Comparison of POLDER Cloud Phase Retrievals to Active Remote Sensors Measurements at the ARM SGP Site

    SciTech Connect (OSTI)

    Riedi, J.; Goloub, P.; Marchand, Roger T.

    2001-06-01T23:59:59.000Z

    In our present study, cloud boundaries derived from a combination of active remote sensors at the ARM SGP site are compared to POLDER cloud top phase index which is derived from polarimetric measurements using an innovative method. This approach shows the viability of the POLDER phase retrieval algorithm, and also leads to interesting results. In particular, the analysis demonstrates the sensitivity of polarization measurements to ice crystal shape and indicates that occurrence of polycrystalline ice clouds has to be taken into account in order to improve the POLDER phase retrieval algorithm accuracy. Secondly, the results show that a temperature threshold of 240 K could serve for cloud top particle phase classification. Considering the limitations of the analysis, the temperature threshold could be biased high, but not by more than about 5 degrees.

  10. ARM - Evaluation Product - Active Remote Sensing of Clouds from Ka-band ARM

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

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  11. 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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  12. ARM - Evaluation Product - Cloud Optical Properties from MFRSR Using Min

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

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  13. ARM - Field Campaign - Cirrus Clouds and Aerosol Properties Campaign

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

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  14. ARM - Field Campaign - Deep Convective Clouds and Chemistry

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

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  15. 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.

  16. DOE/SC-ARM-TR-099 ARM Cloud Retrieval Ensemble Data Set

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

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  17. DOE/SC-ARM-14-030 ARM Cloud Aerosol Precipitation Experiment

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

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

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

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  19. 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.

  20. Atmospheric Radiation Measurement (ARM) Data from Steamboat Springs, Colorado, for the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX)

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

    In October 2010, the initial deployment of the second ARM Mobile Facility (AMF2) took place at Steamboat Springs, Colorado, for the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX). The objective of this field campaign was to obtain data about liquid and mixed-phase clouds using AMF2 instruments in conjunction with Storm Peak Laboratory (located at an elevation of 3220 meters on Mt. Werner), a cloud and aerosol research facility operated by the Desert Research Institute. STORMVEX datasets are freely available for viewing and download. Users are asked to register with the ARM Archive; the user's email address is used from that time forward as the login name.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Testing AGCM-Predicted Cloud and Radiation Properties with ARM Data: The Super-Parameterization Approach

    SciTech Connect (OSTI)

    Ovchinnikov, Mikhail; Ackerman, Thomas P.; Marchand, Roger T.; Khairoutdinov, Marat

    2004-01-31T23:59:59.000Z

    The goal of our study is to directly evaluate treatment of clouds and radiation in an atmospheric global climate model (AGCM) using long-term observations from the Atmospheric Radiation Measurement (ARM) program. In this presentation, we will present a comparison of observations from two ARM sites, one in north central Oklahoma and one at Nauru island in the Tropical Western Pacific region, with the model output from corresponding grid points. Traditional parametric approach of diagnosing cloud and radiation properties from large-scale model fields is not well suited for comparison with observed time series at selected locations. A recently emerging approach called super parameterization has shown promise to bridge the gap. Super parameterization consists of a two-dimensional cloud system resolving model (CSRM) embedded into each grid of the NCAR Community Climate System Model thereby computing cloud properties at a scale that is more consistent with observations. Because the approach is computationally expensive only limited simulations have been carried out. Two sets of one year long simulations are considered: one using climatological sea surface temperatures (SST) and another using 1999 SST. Each set includes a run with super-parameterization (SP) as well as an AGCM run with traditional or standard (STD) cloud and radiation treatment. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are statistically analyzed. Nearly all parameters of frequency distributions of these variables from SP run are shown to be more consistent with observation than those from STD model run. Different temporal and spatial averaging in the simulations and observations imposes limitations on the comparisons and these scale effects will be discussed. Output from the STD run represents statistics for the AGCM grid, which, in our case, is roughly 300 km x 300 km. In contrast, the CSRM domain is 4 km x 256 km and consists of a row of 64 columns, 4 km x 4 km each. One of the benefits of the SP approach is that statistics can be collected for domain-averaged as well as column cloud and radiation properties. The column statistics are representative of scales that are closer to the scales of observations and therefore allow for more direct comparisons.

  8. 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

  9. 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.

  10. 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.

  11. 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).

  12. Comparison of the CALIPSO satellite and ground-based observations of cirrus clouds at the ARM TWP sites

    SciTech Connect (OSTI)

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

    2011-11-10T23:59:59.000Z

    Statistics of ice cloud macrophysical and optical properties from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite are compared with those from ground-based lidar observations over a 31 month period. Ground-based lidar observations are taken from the micropulse lidars (MPL) at the three Department of Energy Atmospheric Radiation Measurement (ARM) tropical western pacific (TWP) sites: Manus, Nauru and Darwin. CALIPSO observations show a larger cloud fraction at high altitudes while the ground-based MPLs show a larger cloud fraction at low altitudes. The difference in mean ice cloud top and base heights at the Manus and Nauru sites are all within 0.51 km, although differences are statistically significant. Mean ice cloud geometrical thickness agree to within 0.05 km at the Manus and Nauru sites. Larger differences exist at Darwin due to excessive degradation of the MPL output power during our sampling period. Both sets of observations show thicker clouds during the nighttime which may be real but could also be partially an artifact of the decreased signal-to-noise ratio during the daytime. The number of ice cloud layers per profile are also shown to be consistent after accounting for the difference in spatial resolution. For cloud optical depths, four different retrieval methods are compared, two for each set of observations. All products show that the majority of ice cloud optical depths ({approx}60%) fall below an optical depth of 0.2. For most comparisons all four retrievals agree to within the uncertainty intervals. We find that both CALIPSO retrievals agree best to ground-based optical depths when the lidar ratio in the latter is retrieved instead of set to a fixed value. Also thoroughly compared is the cloud properties for the subset of ice clouds which reside in the tropical tropopause layer (TTL).

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations

    SciTech Connect (OSTI)

    Qian, Yun; Long, Charles N.; Wang, Hailong; Comstock, Jennifer M.; McFarlane, Sally A.; Xie, Shaocheng

    2012-02-17T23:59:59.000Z

    Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulations in the IPCC AR4 GCMs against ARM ground measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity, for both inter-model deviation and model-measurement discrepancy. Our intercomparisons of three CF or sky-cover related dataset reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The results also show that the model-observation and the inter-model deviations have a similar magnitude for the total CF (TCF) and the normalized cloud effect, and they are twice as large as the surface downward solar radiation and cloud transmissivity. This implies that the other cloud properties, such as cloud optical depth and height, have a similar magnitude of disparity to TCF among the GCMs, and suggests that a better agreement among the GCMs in solar radiative fluxes could be the result of compensating errors in either cloud vertical structure, cloud optical depth or cloud fraction. Similar deviation pattern between inter-model and model-measurement suggests that the climate models tend to generate larger bias against observations for those variables with larger inter-model deviation. The simulated TCF from IPCC AR4 GCMs are very scattered through all seasons over three ARM sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). The GCMs perform better at SGP than at Manus and NSA in simulating the seasonal variation and probability distribution of TCF; however, the TCF in these models is remarkably underpredicted and cloud transmissivity is less susceptible to the change of TCF than the observed at SGP. Much larger inter-model deviation and model bias are found over NSA than the other sites in estimating the TCF, cloud transmissivity and cloud-radiation interaction, suggesting that the Arctic region continues to challenge cloud simulations in climate models. Most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels in the tropics. The high altitude CF is much larger in the GCMs than the observation and the inter-model variability of CF also reaches maximum at high levels in the tropics. Most of the GCMs tend to underpredict CF by 50-150% relative to the measurement average at low and middle levels over SGP. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near surface over the Arctic. The internal variability of CF simulated in ensemble runs with the same model is very minimal.

  1. 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.

  2. 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.

  3. Validation of Surface Retrieved Cloud Optical Properties with in situ Measurements at the Atmospheric Radiation Measurement Program (ARM) South Great Plains Site

    SciTech Connect (OSTI)

    Min, Qilong; Duan, M.; Marchand, Roger T.

    2003-09-11T23:59:59.000Z

    The surface inferred cloud optical properties from a multifilter rotating shadowband radiometer have been validated against the in situ measurements during the second ARM Enhanced Shortwave Experiment (ARESE II) field campaign at the ARM South Great Plains (SGP) site. On the basis of eight effective radius profiles measured by the in situ Forward Spectra Scattering Probe (FSSP), our retrieved cloud effective radii for single-layer warm water clouds agree well with in situ measurements, within 5.5%. The sensitivity study also illustrates that for this case a 13% uncertainty in observed liquid water path (LWP, 20 g/m2) results in 1.5% difference in retrieved cloud optical depth and 12.7% difference in referred cloud effective radius, on average. The uncertainty of the LWP measured by the microwave radiometer (MWR) is the major contributor to the uncertainty of retrieved cloud effective radius. Further, we conclude that the uncertainty of our inferred cloud optical properties is better than 5% for warm water clouds based on a surface closure study, in which cloud optical properties inferred from narrowband irradiances are applied to a shortwave model and the modeled broadband fluxes are compared to a surface pyranometer.

  4. Cloud Computing as a Tool to Secure and Manage Information Flow in Swedish Armed Forces Networks.

    E-Print Network [OSTI]

    Ali, Muhammad

    2012-01-01T23:59:59.000Z

    ??In the last few years cloud computing has created much hype in the IT world. It has provided new strategies to cut down costs and… (more)

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

    E-Print Network [OSTI]

    of radar, lidar, and ceilometer data collected at the Atmospheric Radiation Measurements Southern Great [1995] and Chernykh and Eskridge [1996]. The lidar and ceilometer data yield lowest-level cloud base. These quantities are used to assess the accuracy of coincident cloud base heights obtained from radar and the two

  6. 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.

  7. Final Report - Satellite Calibration and Verification of Remotely Sensed Cloud and Radiation Properties Using ARM UAV Data (February 28, 1995 - February 28, 1998)

    SciTech Connect (OSTI)

    Minnis, Patrick

    1998-02-28T23:59:59.000Z

    The work proposed under this agreement was designed to validate and improve remote sensing of cloud and radiation properties in the atmosphere for climate studies with special emphasis on the use of satellites for monitoring these parameters to further the goals of the Atmospheric Radiation Measurement (ARM) Program.

  8. 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

    radiation calculations performed with an ice-free ocean orradiation calculations performed with an ice-free ocean orradiation. STREAMER calculations with the observed cloud, either over an ocean

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

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearchWarmingMethaneProductsCSSEF ARMBE ARM Data Discovery Browse

  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

    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...

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

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

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  12. ARM - PI Product - SGP and TWP (Manus) Ice Cloud Vertical Velocities

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

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  13. Marine ARM GPCI Investigation of Clouds (MAGIC) Science Objectives and Significance

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

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  14. Low-order-mode harmonic multiplying gyrotron traveling-wave amplifier in W band

    SciTech Connect (OSTI)

    Yeh, Y. S.; Chen, C. H.; Yang, S. J.; Lai, C. H.; Lin, T. Y.; Lo, Y. C.; Hong, J. W. [Department of Electro-Optical Engineering, Southern Taiwan University, Tainan, Taiwan (China); Hung, C. L. [Department of Communication Engineering, National Penghu University of Science and Technology, Penghu, Taiwan (China); Chang, T. H. [Department of Physics, National Tsing Hua University, Hsinchu, Taiwan (China)

    2012-09-15T23:59:59.000Z

    Harmonic multiplying gyrotron traveling-wave amplifiers (gyro-TWAs) allow for magnetic field reduction and frequency multiplication. To avoid absolute instabilities, this work proposes a W-band harmonic multiplying gyro-TWA operating at low-order modes. By amplifying a fundamental harmonic TE{sub 11} drive wave, the second harmonic component of the beam current initiates a TE{sub 21} wave to be amplified. Absolute instabilities in the gyro-TWA are suppressed by shortening the interaction circuit and increasing wall losses. Simulation results reveal that compared with Ka-band gyro-TWTs, the lower wall losses effectively suppress absolute instabilities in the W-band gyro-TWA. However, a global reflective oscillation occurs as the wall losses decrease. Increasing the length or resistivity of the lossy section can reduce the feedback of the oscillation to stabilize the amplifier. The W-band harmonic multiplying gyro-TWA is predicted to yield a peak output power of 111 kW at 98 GHz with an efficiency of 25%, a saturated gain of 26 dB, and a bandwidth of 1.6 GHz for a 60 kV, 7.5 A electron beam with an axial velocity spread of 8%.

  15. 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)

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  16. 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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  17. ARM - Field Campaign - Ground-based Cloud Tomography Experiment at SGP

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

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  18. ARM - Field Campaign - MASRAD: Pt. Reyes Stratus Cloud and Drizzle Study

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

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  19. 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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  20. 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.

  1. 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.

  2. 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.

  3. 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.

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

    SciTech Connect (OSTI)

    Williams, Christopher; Jensen, Mike

    2012-11-06T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Williams, Christopher; Jensen, Mike

    2012-11-06T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Williams, Christopher; Jensen, Mike

    2012-11-06T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Williams, Christopher; Jensen, Mike

    2012-11-06T23:59:59.000Z

    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.

  8. ARM - Site Instruments

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

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  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. WACR Calibration Report

    SciTech Connect (OSTI)

    Mead, D

    2010-03-23T23:59:59.000Z

    Calibration report for the W-Band (95 GHz) ARM Cloud Radar performed for the ARM Climate Research Facility by ProSensing Inc.

  15. ARM - Cloud Memory

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

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  16. ARM - Cloud Twist

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

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  17. ARM - Cloud Word Seek

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformationbudapest Comments? We would love to heartotdngovInstrumentswrf-chemHistory OutreachTwistWord

  18. X-AND W-BAND EPR SPECTROSCOPY COMBINED WITH MOLECULAR DYNAMICS SIMULATIONS UNRAVEL THE STRUCTURE AND STRUCTURAL

    E-Print Network [OSTI]

    Steinhoff, Heinz-JĂĽrgen

    X- AND W-BAND EPR SPECTROSCOPY COMBINED WITH MOLECULAR DYNAMICS SIMULATIONS UNRAVEL THE STRUCTURE (EPR) spectroscopy is combined with molecular dynamics (MD) simulations to study the structure and thus the EPR spectral line shape contain direct information about the secondary and tertiary structure

  19. Failure and Redemption of Multifilter Rotating Shadowband Radiometer (MFRSR)/Normal Incidence Multifilter Radiometer (NIMFR) Cloud Screening: Contrasting Algorithm Performance at Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) and Southern Great Plains (SGP) Sites

    SciTech Connect (OSTI)

    Kassianov, Evgueni I.; Flynn, Connor J.; Koontz, Annette S.; Sivaraman, Chitra; Barnard, James C.

    2013-09-11T23:59:59.000Z

    Well-known cloud-screening algorithms, which are designed to remove cloud-contaminated aerosol optical depths (AOD) from AOD measurements, have shown great performance at many middle-to-low latitude sites around the world. However, they may occasionally fail under challenging observational conditions, such as when the sun is low (near the horizon) or when optically thin clouds with small spatial inhomogeneity occur. Such conditions have been observed quite frequently at the high-latitude Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) sites. A slightly modified cloud-screening version of the standard algorithm is proposed here with a focus on the ARM-supported Multifilter Rotating Shadowband Radiometer (MFRSR) and Normal Incidence Multifilter Radiometer (NIMFR) data. The modified version uses approximately the same techniques as the standard algorithm, but it additionally examines the magnitude of the slant-path line of sight transmittance and eliminates points when the observed magnitude is below a specified threshold. Substantial improvement of the multi-year (1999-2012) aerosol product (AOD and its Angstrom exponent) is shown for the NSA sites when the modified version is applied. Moreover, this version reproduces the AOD product at the ARM Southern Great Plains (SGP) site, which was originally generated by the standard cloud-screening algorithms. The proposed minor modification is easy to implement and its application to existing and future cloud-screening algorithms can be particularly beneficial for challenging observational conditions.

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

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

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  1. 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.

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

    SciTech Connect (OSTI)

    Williams, Christopher

    2012-11-06T23:59:59.000Z

    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.

  3. Merging Cloud and Precipitation Radar Data Provides a Better

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

    Merging Cloud and Precipitation Radar Data Provides a Better View of Tropical Rain Clouds For original submission and image(s), see ARM Research Highlights http:www.arm.gov...

  4. 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

  5. ARM - About ARM

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  6. ARM - Measurement - Cloud base height

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  7. ARM - Measurement - Cloud condensation nuclei

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  8. ARM - Measurement - Images of Clouds

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  9. ARM TR-047

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  10. 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

  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. ARM - ARM Logos

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  13. ARM - About ARM

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  14. ARM - ARM Data Integrator

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  15. ARM - ARM Safety Policy

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  16. ARM - ARM Science Board

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  17. 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.

  18. 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.

  19. Relationship between cloud radiative forcing, cloud fraction and cloud albedo, and new surface-based approach for determining cloud albedo

    SciTech Connect (OSTI)

    Liu, Y.; Wu, W.; Jensen, M. P.; Toto, T.

    2011-07-21T23:59:59.000Z

    This paper focuses on three interconnected topics: (1) quantitative relationship between surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo; (2) surface-based approach for measuring cloud albedo; (3) multiscale (diurnal, annual and inter-annual) variations and covariations of surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo. An analytical expression is first derived to quantify the relationship between cloud radiative forcing, cloud fraction, and cloud albedo. The analytical expression is then used to deduce a new approach for inferring cloud albedo from concurrent surface-based measurements of downwelling surface shortwave radiation and cloud fraction. High-resolution decade-long data on cloud albedos are obtained by use of this surface-based approach over the US Department of Energy's Atmospheric Radiaton Measurement (ARM) Program at the Great Southern Plains (SGP) site. The surface-based cloud albedos are further compared against those derived from the coincident GOES satellite measurements. The three long-term (1997-2009) sets of hourly data on shortwave cloud radiative forcing, cloud fraction and cloud albedo collected over the SGP site are analyzed to explore the multiscale (diurnal, annual and inter-annual) variations and covariations. The analytical formulation is useful for diagnosing deficiencies of cloud-radiation parameterizations in climate models.

  20. 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.

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

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  2. ARM - Events Article

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  3. 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).

  4. ARM Instrumentation

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  5. 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.

  6. 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.

  7. ARM Participation

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  8. Science Goals for the ARM Recovery Act Radars

    SciTech Connect (OSTI)

    JH Mather

    2012-05-29T23:59:59.000Z

    Science Goals for the ARM Recovery Act Radars. In October 2008, an ARM workshop brought together approximately 30 climate research scientists to discuss the Atmospheric Radiation Measurement (ARM) Climate Research Facility's role in solving outstanding climate science issues. Through this discussion it was noted that one of ARM's primary contributions is to provide detailed information about cloud profiles and their impact on radiative fluxes. This work supports cloud parameterization development and improved understanding of cloud processes necessary for that development. A critical part of this work is measuring microphysical properties (cloud ice and liquid water content, cloud particle sizes, shapes, and distribution). ARM measurements and research have long included an emphasis on obtaining the best possible microphysical parameters with the available instrumentation. At the time of the workshop, this research was reaching the point where additional reduction in uncertainties in these critical parameters required new instrumentation for applications such as specifying radiative heating profiles, measuring vertical velocities, and studying the convective triggering and evolution of three-dimensional (3D) cloud fields. ARM was already operating a subset of the necessary instrumentation to make some progress on these problems; each of the ARM sites included (and still includes) a cloud radar (operating at 35 or 94 GHz), a cloud lidar, and balloon-borne temperature and humidity sensors. However, these measurements were inadequate for determining detailed microphysical properties in most cases. Additional instrumentation needed to improve retrievals of microphysical processes includes radars at two additional frequencies for a total of three at a single site (35 GHz, 94 GHz, and a precipitation radar) and a Doppler lidar. Evolving to a multi-frequency scanning radar is a medium-term goal to bridge our understanding of two-dimensional (2D) retrievals to the 3D cloud field. These additional microphysical measurements would allow detailed cloud properties to be derived even in the presence of light precipitation. It is important to couple these detailed measurements of cloud microphysics to vertical motion on the cloud scale to couple microphysics with meteorological processes. Vertically pointing Doppler radars provide the vertical motion of cloud particles but, to separate particle motion from air motion, a wind profiler is required. The American Recovery and Reinvestment Act provided the means to address these needs and implement a multi-frequency suite of radars, including scanning radars, at each of the ARM sites. In addition, Doppler lidars have been deployed at several sites. With these new measurement capabilities, ARM has the measurement capabilities to tackle the problems of improving microphysical profile descriptions and evaluating the relationship between our current narrow-field-of view, zenith perspective on clouds to a description of the full 3D cloud field and its temporal evolution.

  9. ARM - ARM at AGU 2011

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  10. 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.

  11. ARM Climate Research Facility Annual Report 2005

    SciTech Connect (OSTI)

    J. Voyles

    2005-12-31T23:59:59.000Z

    Through the ARM Program, the DOE funded the development of several highly instrumented ground stations for studying cloud formation processes and their influence on radiative transfer, and for measuring other parameters that determine the radiative properties of the atmosphere. This scientific infrastructure, and resultant data archive, is a valuable national and international asset for advancing scientific knowledge of Earth systems. In fiscal year (FY) 2003, the DOE designated ARM sites as a national scientific user facility: the ARM Climate Research (ACRF). The ACRF has enormous potential to contribute to a wide range interdisciplinary science in areas such as meteorology, atmospheric aerosols, hydrology, biogeochemical cycling, and satellite validation, to name only a few.

  12. ARM - Acronyms

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  13. ARM - Article

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

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

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

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

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

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

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

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

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  2. ARM - Collaborations

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  3. ARM - Instrument -

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  4. ARM - Article

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  5. ARM - Article

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  6. ARM - Article

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  7. ARM - Article

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  8. ARM - Article

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

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  9. ARM - Archive

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  10. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM Engineering6, 2010 [Facility News,

  11. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM Engineering6, 2010 [Facility News,August

  12. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM Engineering6, 2010 [Facility

  13. ARM - Blog

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM Engineering6,GermanyBlack Forest

  14. ARM - Brochures

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

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  15. ARM - ARM Operations Quarterly Reports

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM Engineering and Related Links

  16. Ka-Band ARM Zenith Radar (KAZR) Instrument Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N; Johnson, K

    2012-03-06T23:59:59.000Z

    The Ka-band ARM zenith radar (KAZR) is a zenith-pointing Doppler cloud radar operating at approximately 35 GHz. The KAZR is an evolutionary follow-on radar to ARM's widely successful millimeter-wavelength cloud radar (MMCR). The main purpose of the KAZR is to provide vertical profiles of clouds by measuring the first three Doppler moments: reflectivity, radial Doppler velocity, and spectra width. At the sites where the dual-polarization measurements are made, the Doppler moments for the cross-polarization channel are also available. In addition to the moments, velocity spectra are also continuously recorded for each range gate.

  17. ARM - Collaborations

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformationbudapest Comments? We would love to heartotdngovInstrumentswrf-chemHistoryListCloud and

  18. ARM - Collaborations

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformationbudapest Comments? We would love to heartotdngovInstrumentswrf-chemHistoryListCloud

  19. ARM - Collaborations

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformationbudapest Comments? We would love to heartotdngovInstrumentswrf-chemHistoryListCloudArctic

  20. ARM - Blog Article

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

    , 2014 ARM Mobile Facility 2, BAECC, Blog, Field Notes AMF2 Arrives in Finland Bookmark and Share Editor's note: Mike Ritsche, technical operations manager for the ARM Mobile...

  1. ARM - Field Campaign - ISDAC - NASA ARCTAS Coordination with ARM

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

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  2. ARM - Field Campaign - Spring Cloud 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops Atmospheric Optical DepthgovCampaignsSpring 1994 Single Column ModelgovCampaignsSpring

  3. Micropulse Lidar Cloud Mask Value-Added Product Technical Report

    SciTech Connect (OSTI)

    Sivaraman, C; Comstock, J

    2011-07-25T23:59:59.000Z

    Lidar backscattered signal is a useful tool for identifying vertical cloud structure in the atmosphere in optically thin clouds. Cloud boundaries derived from lidar signals are a necessary input for popular ARM data products, such as the Active Remote Sensing of Clouds (ARSCL) product. An operational cloud boundary algorithm (Wang and Sassen 2001) has been implemented for use with the ARM Micropulse Lidar (MPL) systems. In addition to retrieving cloud boundaries above 500 m, the value-added product (VAP) named Micropulse Lidar Cloud Mask (MPLCMASK) applies lidar-specific corrections (i.e., range-square, background, deadtime, and overlap) as described in Campbell et al. (2002) to the measured backscattered lidar. Depolarization ratio is computed using the methodology developed by Flynn et al. (2007) for polarization-capable MPL systems. The cloud boundaries output from MPLCMASK will be the primary lidar cloud mask for input to the ARSCL product and will be applied to all MPL systems, including historical data sets.

  4. 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.

  5. Cloud Property Retrieval Products for Graciosa Island, Azores

    SciTech Connect (OSTI)

    Dong, Xiquan

    2014-05-05T23:59:59.000Z

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

  6. 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.

  7. The ARM unpiloted aerospace vehicle (UAV) program

    SciTech Connect (OSTI)

    Sowle, D. [Mission Research Corporation, Santa Barbara, CA (United States)

    1995-09-01T23:59:59.000Z

    Unmanned aerospace vehicles (UAVs) are an important complement to the DOE`s Atmospheric Radiation Measurement (ARM) Program. ARM is primarily a ground-based program designed to extensively quantify the radiometric and meteorological properties of an atmospheric column. There is a need for airborne measurements of radiative profiles, especially flux at the tropopause, cloud properties, and upper troposphere water vapor. There is also a need for multi-day measurements at the tropopause; for example, in the tropics, at 20 km for over 24 hours. UAVs offer the greatest potential for long endurance at high altitudes and may be less expensive than piloted flights. 2 figs.

  8. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band ARMShouxian,

  9. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band ARMShouxian,Niamey,

  10. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-Band

  11. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-BandGanges Valley,

  12. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-BandGanges

  13. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-BandGangesPoint Reyes

  14. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-BandGangesPoint

  15. ARM - Site Instruments

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAnthe Infrared LandSystem W-BandGangesPointgovSitesNorth

  16. ARM CLASIC ER2 CRS/EDOP

    SciTech Connect (OSTI)

    Gerald Heymsfield

    2010-12-20T23:59:59.000Z

    Data was taken with the NASA ER-2 aircraft with the Cloud Radar System and other instruments in conjunction with the DOE ARM CLASIC field campaign. The flights were near the SGP site in north Central Oklahoma and targeted small developing convection. The CRS is a 94 GHz nadir pointing Doppler radar. Also on board the ER-2 was the Cloud Physics Lidar (CPL). Seven science flights were conducted but the weather conditions did not cooperate in that there was neither developing convection, or there was heavy rain.

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAn Assessment ofCloud StructureCloud Radiativean ImprovedARM

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAn Assessment ofCloud StructureCloudModeling Aerosols andARM

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD) by Microtops AtmosphericApplication andAn Assessment ofCloudInteractions Between Clouds andUsing ARM

  20. 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.

  1. 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

  2. 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.

  3. TROPICAL CLOUD LIFE CYCLE AND OVERLAP STRUCTURE A. M. Vogelmann, M. P. Jensen, P. Kollias, and E. Luke

    E-Print Network [OSTI]

    TROPICAL CLOUD LIFE CYCLE AND OVERLAP STRUCTURE A. M. Vogelmann, M. P. Jensen, P. Kollias, and E.bnl.gov ABSTRACT The profile of cloud microphysical properties and how the clouds are overlapped within a vertical simulations. We will present how cloud microphysical properties and overlap structure retrieved at the ARM

  4. 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.

  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. Planning Single-arm Manipulations with N-Arm Robots

    E-Print Network [OSTI]

    Guestrin, Carlos

    Planning Single-arm Manipulations with N-Arm Robots Benjamin Cohen bcohen@seas.upenn.edu University@cs.cmu.edu Carnegie Mellon University Abstract--Many robotic systems are comprised of two or more arms. Such systems robotic arms. While the use of multiple arms increases the pro- ductivity of the system and extends

  7. 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.

  8. 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.

  9. ARM - Evaluation Product - ARM Navigation Best Estimate 10 Hz (NAVBE) and

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

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  10. 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.

  11. Armed With A Heart.

    E-Print Network [OSTI]

    Horton, Willie Charles, Jr.

    2009-01-01T23:59:59.000Z

    ?? This paper thoroughly examines the production of the thesis short film, Armed With A Heart, from conception to completion. Each area of the film's… (more)

  12. 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.

  13. 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.

  14. ARM - ARM Mobile Facility 1 Article

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  15. ARM - ARM Recovery Act Project FAQs

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  16. 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.

  17. 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

  18. Cloud Computing.

    E-Print Network [OSTI]

    Siddiqui, Muhammad Anas

    2013-01-01T23:59:59.000Z

    ?? Cloud computing has been given a great deal of attention during recent years. Almost all the technology market leaders and leading hosting service providers… (more)

  19. ARM - Publications: Science Team Meeting Documents

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  20. ARM - Publications: Science Team Meeting Documents

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  1. ARM - Field Campaign - Fall 1997 Shortwave IOP

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  2. ARM - Field Campaign - Fall 1997 UAV IOP

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  3. ARM - Field Campaign - Fall 2002 SCM IOP

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  4. ARM - Field Campaign - ISDAC - Hemispheric Flux Spectroradiometer

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  5. ARM Climate Research Facility

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  6. ARM Climate Research Facility

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

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  7. ARM Climate Research Facility

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  8. ARM TR-008

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  9. ARM TR-008

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  10. ARM Water Vapor IOP

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  11. ARM XDC Datastreams

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  12. ARM XDC Datastreams

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  13. ARM XDC Datastreams

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  14. 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.

  15. Science Plan for the Atmospheric Radiation Measurement Program (ARM)

    SciTech Connect (OSTI)

    NONE

    1996-02-01T23:59:59.000Z

    The purpose of this Atmospheric Radiation Measurement (ARM) Science Plan is to articulate the scientific issues driving the ARM Program, and to relate them to DOE`s programmatic objectives for ARM, based on the experience and scientific progress gained over the past five years. ARM programmatic objectives are to: (1) Relate observed radiative fluxes and radiances in the atmosphere, spectrally resolved and as a function of position and time, to the temperature and composition of the atmosphere, specifically including water vapor and clouds, and to surface properties, and sample sufficient variety of situations so as to span a wide range of climatologically relevant possibilities; (2) develop and test parameterizations that can be used to accurately predict the radiative properties and to model the radiative interactions involving water vapor and clouds within the atmosphere, with the objective of incorporating these parameterizations into general circulation models. The primary observational methods remote sending and other observations at the surface, particularly remote sensing of clouds, water vapor and aerosols.

  16. Testbed model and data assimilation for ARM

    SciTech Connect (OSTI)

    Louis, J.F.

    1992-09-22T23:59:59.000Z

    The objectives of this contract are to further develop and test the ALFA (AER Local Forecast and Assimilation) model originally designed at AER for local weather prediction and apply it to three distinct but related purposes in connection with the Atmospheric Radiation Measurement (ARM) program: (a) to provide a testbed that simulates a global climate model in order to facilitate the development and testing of new cloud parametrizations and radiation models; (b) to assimilate the ARM data continuously at the scale of a climate model, using the adjoint method, thus providing the initial conditions and verification data for testing parameumtions; (c) to study the sensitivity of a radiation scheme to cloud parameters, again using the adjoint method, thus demonstrating the usefulness of the testbed model. The data assimilation will use a variational technique that minimizes the difference between the model results and the observation during the analysis period. The adjoint model is used to compute the gradient of a measure of the model errors with respect to nudging terms that are added to the equations to force the model output closer to the data. The radiation scheme that will be included in the basic ALFA model makes use of a gen two-stream approximation, and is designed for vertically inhonogeneous, multiple-scattering atmospheres. The sensitivity of this model to the definition of cloud parameters will be studied. The adjoint technique will also be used to compute the sensitivities. This project is designed to provide the Science Team members with the appropriate tools and modeling environment for proper testing and tuning of new radiation models and cloud parametrization schemes.

  17. ROBOTICS -INTRODUCTION t Manipulator Arms

    E-Print Network [OSTI]

    Petriu, Emil M.

    ROBOTICS - INTRODUCTION t Manipulator Arms The common industrial manipulator is often referred to as a robot arm, with links and joints described in similar terms. Manipulators which emulate. The motion of articulated robot arms differs from the motion of the human arm. While robot joints have fewer

  18. 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.

  19. 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.

  20. ARM Climate Research Facility

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  1. ARM Climate Research Facility

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

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  2. ARM Climate Research Facility

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  3. ARM Climate Research Facility

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  4. ARM TR-008

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  5. ARM - Instrument - sodar

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  6. ARM - Instrument - sp2

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  7. ARM - Instrument - spn

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  8. ARM - Instrument - stable

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  9. ARM - Measurement - Nitrogen

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  10. ARM - Measurement - Surface albedo

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  11. ARM - Measurement - Surface condition

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  12. ARM - Measurement - Total carbon

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  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. 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.

  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. ARM - ARM Summer Training and Science Applications

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  17. ARM - Field Campaign - ARM LBNL Carbon Project

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  18. ARM - 1998 ARM Science Team Meeting

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  19. ARM - 1999 ARM Science Team Meeting

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  20. ARM - 2000 ARM Science Team Meeting

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  1. ARM - 2001 ARM Science Team Meeting

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  2. ARM - 2002 ARM Science Team Meeting

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  3. ARM - ARM Engineering and Operations Contacts

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  4. ARM - ARM Facility at EGU 2012

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  5. ARM - ARM Facility at EGU 2014

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  6. ARM - ARM MJO Investigation Experiment (AMIE)

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  7. CIMEL SUN PHOTOMETERS: UPDATES ON NEW DEPLOYMENTS AND CLOUD MODE ZENITH RADIANCE DATA

    E-Print Network [OSTI]

    CIMEL SUN PHOTOMETERS: UPDATES ON NEW DEPLOYMENTS AND CLOUD MODE ZENITH RADIANCE DATA Richard of Science ABSTRACT Since March 1998, ARM has deployed Cimel Sun PHOTometers (CSPHOT) at several but not all

  8. The Tropical Warm Pool International Cloud Experiment

    SciTech Connect (OSTI)

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

    2008-05-01T23:59:59.000Z

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

  9. Dynamic Cloud Infrastructure.

    E-Print Network [OSTI]

    Gundersen, Espen

    2012-01-01T23:59:59.000Z

    ??This thesis will explore and investigate the possibility of implementing nested clouds to increase flexibility. A nested cloud is a private cloud running inside another… (more)

  10. Securing Cloud Storage Service.

    E-Print Network [OSTI]

    Zapolskas, Vytautas

    2012-01-01T23:59:59.000Z

    ?? Cloud computing brought flexibility, scalability, and capital cost savings to the IT industry. As more companies turn to cloud solutions, securing cloud based services… (more)

  11. ARM Climate Research Facility

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  12. ARM Climate Research Facility

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  13. ARM People Search

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  14. ARM Poster 2007.ai

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  15. ARM Scanning Radar

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  16. ARM Science Meeting

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  17. ARM TR-006

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  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

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  3. ARM TR-008

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  4. ARM TR-008

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  5. ARM TR-008

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  6. ARM TR-008

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  7. ARM TR-008

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  8. ARM TR-008

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  9. ARM TR-008

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  10. ARM TR-008

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  11. ARM TR-008

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  12. ARM TR-008

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  13. ARM TR-008

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  14. ARM TR-008

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  15. ARM TR-008

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  16. ARM TR-008

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  17. ARM TR-008

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  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

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric5

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric59

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric599

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101 Atmospheric5990

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar Wind

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar Wind54

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar Wind546

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar0 Belfort

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar0

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar032

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar0328

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar03287

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar032875

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar0328755

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar03287555

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar03287555

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144 Radar032875558

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP10144

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision Gas

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision Gas

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision51

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449 Precision5125

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM SGP101449

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave7 Total Sky

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave7 Total

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave7

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave73 Whole-Sky

  12. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62 Shortwave73

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62ARMStreamsC-Band

  14. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The ARM62ARMStreamsC-BandModel

  15. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3, 2010September 30,June 24,ARM Science LiaisonBestNovemberARM

  16. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3, 2010September 30,June 24,ARM ScienceAlaskanRadarARM Archive

  17. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3, 2010September 30,June 24,ARM ScienceAlaskanRadarARM

  18. ARM - About RSS Feeds

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM Engineering and RelatedCenterARM

  19. EMSL - W-band pulsed EPR spectrometer

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

    http:www.emsl.pnl.govemslweb Effects of Oxygen-Containing Functional Groups on Supercapacitor Performance. http:www.emsl.pnl.govemslwebpublicationseffects-oxygen-containin...

  20. W-band pulsed EPR spectrometer | EMSL

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

    The Role of FeS in Initial Activation and Performance Degradation of Na-NiCl2 Batteries. Abstract: The role of iron sulfide (FeS) in initial cell activation and degradation in the...

  1. 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).

  2. 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.

  3. 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

  4. Experiment to Characterize Tropical Cloud Systems

    SciTech Connect (OSTI)

    May, Peter T.; Mather, Jim H.; Jakob, Christian

    2005-08-02T23:59:59.000Z

    A major experiment to study tropical convective cloud systems and their impacts will take place around Darwin, Northern Australia in early 2006. The Tropical Warm Pool International Cloud Experiment (TWP-ICE) is a collaboration including the DOE ARM (Atmospheric Radiation Measurement) and ARM-UAV programs, NASA centers, the Australian Bureau of Meteorology, CSIRO, and universities in the USA, Australia, Japan, the UK, and Canada. TWP-ICE will be preceded in November/December 2004 by a collaborating European aircraft campaign involving the EU SCOUT-O3 and UK NERC ACTIVE projects. Detailed atmospheric measurements will be made in the Darwin area through the whole Austral summer, giving unprecedented coverage through the pre-monsoon and monsoon periods.

  5. 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.

  6. 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.

  7. 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.

  8. Microelectromechanical safe arm device

    DOE Patents [OSTI]

    Roesler, Alexander W. (Tijeras, NM)

    2012-06-05T23:59:59.000Z

    Microelectromechanical (MEM) apparatus and methods for operating, for preventing unintentional detonation of energetic components comprising pyrotechnic and explosive materials, such as air bag deployment systems, munitions and pyrotechnics. The MEM apparatus comprises an interrupting member that can be moved to block (interrupt) or complete (uninterrupt) an explosive train that is part of an energetic component. One or more latching members are provided that engage and prevent the movement of the interrupting member, until the one or more latching members are disengaged from the interrupting member. The MEM apparatus can be utilized as a safe and arm device (SAD) and electronic safe and arm device (ESAD) in preventing unintentional detonations. Methods for operating the MEM apparatus include independently applying drive signals to the actuators coupled to the latching members, and an actuator coupled to the interrupting member.

  9. 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.

  10. 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.

  11. Small arms ammunition

    DOE Patents [OSTI]

    Huerta, Joseph (399 Clover St., Aberdeen, MD 21001)

    1992-01-01T23:59:59.000Z

    An elongate projectile for small arms use has a single unitary mass with a hollow nose cavity defined by a sharp rigid cutting edge adapted to make initial contact with the target surface and cut therethrough. The projectile then enters the target mass in an unstable flight mode. The projectile base is substantially solid such that the nose cavity, while relatively deep, does not extend entirely through the base and the projectile center of gravity is aft of its geometric center.

  12. ARM Climate Research Facility

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

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  13. ARM Climate Research Facility

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

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  14. ARM Climate Research Facility

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  15. ARM Climate Research Facility

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

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  16. ARM Climate Research Facility

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

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  17. ARM Climate Research Facility

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

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  18. ARM Climate Research Facility

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

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  19. ARM Climate Research Facility

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust Documentation DataProductswsicloudwsicloudsummarygifAOS3 ARM

  20. ARM Observations Projected

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

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  1. ARM Orientation Workshop

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

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  2. ARM Orientation Workshop

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

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  3. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet The

  4. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNet

  5. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in SuomiNetStreamsUpper

  6. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation in

  7. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation ingovExternal Data

  8. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation ingovExternal

  9. ARM XDC Datastreams

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

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  10. ARM XDC Datastreams

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

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  11. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM Participation

  12. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM ParticipationStreamsNOAA Surface Meteorology Data,

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM ParticipationStreamsNOAA Surface Meteorology

  14. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM ParticipationStreamsNOAA Surface

  15. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM ParticipationStreamsNOAA

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM ParticipationStreamsNOAAStreamsSuomiNet Global

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM ParticipationStreamsNOAAStreamsSuomiNet

  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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth (AOD)Productssondeadjustsondeadjust DocumentationARM

  19. ARM - Instrument - cmh

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

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  20. ARM - Instrument - gvrp

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

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  1. ARM - Instrument - hsrl

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

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  2. ARM - Instrument - htdma

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

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  3. ARM - Instrument - iap

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

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  4. ARM - Instrument - irsi

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

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  5. ARM - Instrument - irt

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

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  6. ARM - Instrument - issrwp

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcal Documentation(AVIRIS)govInstrumentsgrams Documentation ARM Data Discovery

  7. ARM - Instrument - isssonde

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcal Documentation(AVIRIS)govInstrumentsgrams Documentation ARM Data DiscoverygovInstrumentsisssonde Documentation

  8. ARM - Instrument - kasacr

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

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  9. ARM - Instrument - kazr

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

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  10. ARM - Instrument - ksumeso

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

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  11. ARM - Instrument - landsat

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

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  12. ARM - Instrument - ldis

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

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  13. ARM - Instrument - maps

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcal Documentation(AVIRIS)govInstrumentsgrams Documentation ARM DatagovInstrumentsksumeso

  14. ARM - Instrument - masc

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

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  15. ARM - Instrument - maws

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

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  16. ARM - Instrument - met

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

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  17. ARM - Instrument - mwacr

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

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  18. ARM - Instrument - mwr

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

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  19. ARM - Instrument - ngm

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

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  20. ARM - Instrument - nimfr

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

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  1. ARM - Instrument - ozone

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  2. ARM - Instrument - prp

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  3. ARM - Instrument - psap

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

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  4. ARM - Instrument - rwp

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

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  5. ARM - Instrument - sashe

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

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  6. ARM - Instrument - sasze

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  7. ARM - Instrument - sebs

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

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  8. ARM - Instrument - sirs

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

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  9. ARM - Instrument - skyrad

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  10. ARM - Instrument - smet

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

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  11. ARM - Instrument - smos

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  12. ARM - Instrument - smps

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  13. ARM - Instrument - smps-2

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

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  14. ARM - Instrument - soil

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  15. ARM - Instrument - sonde

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  16. ARM - Instrument - sonicwind

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDC documentation ARM Data

  17. ARM - Instrument - suomigps

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

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  18. ARM - Instrument - surflog

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

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  19. ARM - Instrument - surthref

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

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  20. ARM - Instrument - swacr

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

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  1. ARM - Instrument - tlcv

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

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  2. ARM - Instrument - tsi

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

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  3. ARM - Instrument - twr

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDC documentationgovInstrumentstsi Documentation TSI : Handbook ARM

  4. ARM - Measurement - Aerosol absorption

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

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  5. ARM - Measurement - Aerosol scattering

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAcid RainTheimage ARM Dataparticle

  6. ARM - Measurement - Atmospheric 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAcid RainTheimage ARM Dataparticlemoisture

  7. ARM - Measurement - Atmospheric pressure

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAcid RainTheimage ARM

  8. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAcid RainTheimage ARMtemperature ARM Data

  9. ARM - Measurement - Atmospheric turbulence

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

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  10. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAciddroplet size ARM

  11. ARM - Measurement - Hydrometeor Geometry

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAciddroplet sizeGeometry ARM Data Discovery

  12. ARM - Measurement - Hydrometeor image

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAciddroplet sizeGeometry ARM Datafallimage

  13. ARM - Measurement - Hydrometeor phase

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAciddroplet sizeGeometry ARMphase ARM Data

  14. ARM - Measurement - Hydrometeor size

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAciddroplet sizeGeometry ARMphase ARM

  15. ARM - Measurement - Ice nuclei

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Related InformationAciddroplet sizeGeometry ARMphasenuclei ARM

  16. ARM - Measurement - Isotope ratio

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

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  17. ARM - Measurement - Methane flux

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Relatedcontent ARM Data Discovery

  18. ARM - Measurement - Ozone

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Relatedcontent ARM DatagovMeasurementsNitrogen

  19. ARM - Measurement - Ozone Concentration

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

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  20. ARM - Measurement - Radar Doppler

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

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  1. ARM - Measurement - Radar polarization

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

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  2. ARM - Measurement - Radar reflectivity

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

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  3. ARM - Measurement - Soil characteristics

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Relatedcontentcharacteristics ARM Data Discovery Browse Data

  4. 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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC : XDCResearch Relatedcontentcharacteristics ARM Data Discovery Browse

  5. ARM - Measurement - Vertical velocity

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

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  6. ARM - Measurement - Virtual temperature

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

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  7. ARM - Measurement - Visibility

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

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  8. ARM - Datastreams - ncepgfszprof

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

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  9. ARM - CARES Measurements

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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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |NovemberARMContactsARM

  10. 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.

  11. 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

  12. 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

  13. 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

  14. Cloud Computing: Rain-Clouds System

    E-Print Network [OSTI]

    Harinder Kaur

    Abstract — Cloud Computing is the on demand service can be provided to the users at any time. It delivers the software, data access, computing as a service rather than the product. The Cloud application simplifies the computing technology by providing pay-per-use customer relationship. It is the theory that familiar to cheaper devices with low processing power, lower storage capacities, great flexibility and many more things. The security of cloud computing is a major factor as users store sensitive and confidential information with cloud storage providers. The range of these providers may be un trusted and harmful. The purpose of adopting cloud computing in an organization is to decide between a „public cloud ? and „private cloud ? by means of privacy. Public clouds often known as provider clouds are administrated by third parties and services are offered on pay-per-use basis. Private clouds or internal clouds are owned by the single firm but it has some metrics such as lacking of availability of services (such as memory, server) and network resources which leads it to down. Due to this, technology moves toward the concept of “Multi clouds ” or “Rain Clouds”. This paper displays the use of multi-clouds or rain clouds due to its ability to handle the huge amount of data traffic that affect the cloud computing user.

  15. 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.

  16. Cloud Security by Max Garvey

    E-Print Network [OSTI]

    Tolmach, Andrew

    Cloud Security Survey by Max Garvey #12;Cloudy Cloud is Cloudy What is the cloud? On Demand Service Network access Resource pooling Elasticity of Resources Measured Service #12;Cloud Types/Variants Iaa Cloud Public Cloud Hybrid Cloud combination. Private cloud with overflow going to public cloud. #12

  17. 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.

  18. 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.

  19. Categorical Exclusion for Cross Arm

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

    but not limited to ... changing insulators, circuit breakers, conductors, transformers, and cross arms." C. Regulatorv Requirements in 10 CFR 1021.410 (b): a. The...

  20. Improving Convection Parameterization Using ARM Observations and NCAR Community Atmosphere Model

    SciTech Connect (OSTI)

    Zhang, Guang J [Scripps Institution of Oceanography

    2013-07-29T23:59:59.000Z

    Highlight of Accomplishments: We made significant contribution to the ASR program in this funding cycle by better representing convective processes in GCMs based on knowledge gained from analysis of ARM/ASR observations. In addition, our work led to a much improved understanding of the interaction among aerosol, convection, clouds and climate in GCMs.