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Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

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)

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.

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

2013-09-11T23:59:59.000Z

2

ARM - AMF Architecture  

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

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3

ARM - Visiting the NSA  

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 RUCProductstwrmr DocumentationProductsaodsasheniraodAlaskaVisiting the NSA NSA

4

ARM - AMF Contacts  

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 |November 2011AstudiesRing Under79FacilitiesAMF Architecture

5

ARM - AMF Data  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |November 2011AstudiesRing Under79FacilitiesAMF ArchitectureData

6

ARM - AMF 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 May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |November 2011AstudiesRing Under79FacilitiesAMF

7

ARM - AMF Operations  

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 |November 2011AstudiesRing Under79FacilitiesAMFOperations AMF

8

ARM - AMF2 Architecture  

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 |November 2011AstudiesRingFacilitiesAMF1 Baseline Instruments

9

ARM - AMF2 Operations  

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

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10

ARM - NSA Contacts  

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 : XDCResearchWarmingMethane Background Information OutreachContacts NSA

11

ARM - NSA Science  

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

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12

ARM - Visiting the SGP  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUCProductstwrmr DocumentationProductsaodsasheniraodAlaskaVisiting the NSA

13

ARM - SGP Extended Facility  

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

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14

SGP Shipment Notification Form  

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 JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SANDSDNTM7/31/13 Page3 SGP Cloud

15

ARM - AMF1 Baseline 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 May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |November 2011AstudiesRingFacilitiesAMF1 Baseline Instruments AMF

16

ARM - AMF3 Baseline Instruments  

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

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17

AMF Deployment, Steamboat Springs, Colorado  

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 |November 2011Astudies Colorado Steamboat Deployment AMF Home

18

ARM - AMF2 Baseline 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 May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |November 2011AstudiesRingFacilitiesAMF1 Baseline

19

Sandia National Laboratories: AMF3  

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 MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwardsSafeguardsEngineers Wind EnergyAMF3 Sierra Unmanned

20

Characterization of Surface Albedo Over the ARM SGP CART and the NSA  

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 Depth7-1D: Vegetation Proposed New Substation SitesStandingtheir Atmospheric Impacts. |Characterization of Surface

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

SGP-TR-32 STANFORD GEOTHERMAL PROGRAM  

E-Print Network [OSTI]

SGP- TR- 32 STANFORD GEOTHERMAL PROGRAM PROGRESS REPORT NO. 7 t o U. S. DEPARTMENT OF ENERGY Recent Radon Transient Experiments Energy Recovery from Fracture-Stimulated Geothermal Reservoirs 1 2 October 1, 1978 through December 31, 1978. Research is performed under t h e Department of Energy Contract

Stanford University

22

NSA AERI Hatch Correction Data Set  

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

From 2000-2008, the NSA AERI hatch was determined to be indicated as open too frequently. Analysis suggests that the hatch was actually opening and closing properly but that its status was not being correctly reported by the hatch controller to the datastream. An algorithm was written to determine the hatch status from the observed

Turner, David

23

NSA AERI Hatch Correction Data Set  

SciTech Connect (OSTI)

From 2000-2008, the NSA AERI hatch was determined to be indicated as open too frequently. Analysis suggests that the hatch was actually opening and closing properly but that its status was not being correctly reported by the hatch controller to the datastream. An algorithm was written to determine the hatch status from the observed

Turner, David

2012-03-23T23:59:59.000Z

24

ARM - AMF2 Management and Operations  

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

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25

ARM - AMF2 Organization and Contact Information  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |November 2011AstudiesRingFacilitiesAMF1

26

Soundings from SGP, June 2014 Sonde Comparison Study  

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

In early June 2014, a radiosonde intercomparison trial was undertaken at the SGP Central Facility site with the goal of quantifying the relative performance of the RS92-SGP/MW31 and RS41-SG/MW41 radiosondes/systems. The June time period at SGP represents a springtime mid-latitude convective environment where the extensive remote sensing observations at the SGP site were used to further quantify the environment during the intercomparison. Over the course of five days (3 - 8 June) a total of 20 balloon launches were completed with efforts to sample the entire diurnal cycle and a variety of cloud conditions

Jensen, Michael

27

SGP CART Site Affected by Ice Storm  

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 MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards ,# ,Schools WhenSection BA2,5,NY2 SGP

28

ARM - SGP Geographic Information By 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 May JunDatastreamsmmcrcalgovInstrumentsruc Documentation RUC :ProductsSCM Forcing Data DerivedInstrumentsPolarExtended Facility SGP

29

ARM - Field Campaign - NSA Scanning Radar IOP  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: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 ARMgovCampaignsNSA Scanning Radar IOP ARM

30

ARM - Field Campaign - NSA Snow 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 Depth (AOD) by Microtops ARMgovCampaignsNSA Scanning Radar IOP

31

Naval Support Activity (NSA) in Bethesda Employment Education Fair  

Broader source: Energy.gov [DOE]

Location: NSA Bethesda Fitness Center (Gymnasium, Bldg 17), 8901 Wisconsin Ave., Bethesda, MD 20889Attendees: Donna Friend (HC) and Rauland Sharp (HC)POC: Donna FriendWebsite: http://bit.ly/1yTjTNu

32

ARM Carbon Cycle Gases Flasks at SGP Site  

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

Data from flasks are sampled at the Atmospheric Radiation Measurement Program ARM, Southern Great Plains Site and analyzed by the National Oceanic and Atmospheric Administration NOAA, Earth System Research Laboratory ESRL. The SGP site is included in the NOAA Cooperative Global Air Sampling Network. The surface samples are collected from a 60 m tower at the ARM SGP Central Facility, usually once per week in the afternoon. The aircraft samples are collected approximately weekly from a chartered aircraft, and the collection flight path is centered over the tower where the surface samples are collected. The samples are collected by the ARM and LBNL Carbon Project.

Biraud, Sebastien

33

Microsoft Word - AMF2 Instruments for BAECC.docx  

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 JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challenge fundProject8 - Outline andPROPOSAL FACT SHEET PAC cycle: _AMF2

34

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

SciTech Connect (OSTI)

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

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

2007-06-01T23:59:59.000Z

35

SGP and TWP (Manus) Ice Cloud Vertical Velocities  

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

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

Kalesse, Heike

36

SGP and TWP (Manus) Ice Cloud Vertical Velocities  

SciTech Connect (OSTI)

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

Kalesse, Heike

2013-06-27T23:59:59.000Z

37

SGP Cloud and Land Surface Interaction Campaign (CLASIC)  

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 JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SANDSDNTM7/31/13 Page3 SGP Cloud and

38

ARM - Field Campaign - SGP Ice Nuclei Characterization 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)govCampaignsReplicator Sonde Campaign ARMgovCampaignsSGP

39

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)]

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

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

40

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe370mcfarlane  

SciTech Connect (OSTI)

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Riihimaki, Laura; Shippert, Timothy

2014-11-05T23:59:59.000Z

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe1mcfarlane  

SciTech Connect (OSTI)

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Riihimaki, Laura; Shippert, Timothy

2014-11-05T23:59:59.000Z

42

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe1mcfarlane  

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

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Riihimaki, Laura; Shippert, Timothy

43

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe370mcfarlane  

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

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Riihimaki, Laura; Shippert, Timothy

44

Atmospheric Radiation Measurement (ARM) Data from Oliktok Point, Alaska (an AMF3 Deployment)  

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

Located at the North Slope of Alaska on the coast of the Arctic Ocean, Oliktok Point is extremely isolated, accessible only by plane. From this remote spot researchers now have access to important data about Arctic climate processes at the intersection of land and sea ice. As of October 2013, Oliktok Point is the temporary home of ARM’s third and newest ARM Mobile Facility, or AMF3. The AMF3 is gathering data using about two dozen instruments that obtain continuous measurements of clouds, aerosols, precipitation, energy, and other meteorological variables. Site operators will also fly manned and unmanned aircraft over sea ice, drop instrument probes and send up tethered balloons. The combination of atmospheric observations with measurements from both the ground and over the Arctic Ocean will give researchers a better sense of why the Arctic sea ice has been fluctuating in fairly dramatic fashion over recent years. AMF3 will be stationed at Oliktok Point.

45

AEROSOL CHEMICAL COMPOSITION CHARACTERIZATION AT THE ARM SOUTHERN GREAT PLAINS (SGP) SITE USING AN AEROSOL CHEMICAL  

E-Print Network [OSTI]

AEROSOL CHEMICAL COMPOSITION CHARACTERIZATION AT THE ARM SOUTHERN GREAT PLAINS (SGP) SITE USING AN AEROSOL CHEMICAL SPECIATION MONITOR Yin-Nan Lee1 , Fan Mei1 , Stephanie DeJong1 , Anne Jefferson2 1 Atmospheric Sciences Division, Brookhaven National Lab, Upton, NY 2 CIRES, University of Colorado, Boulder, CO

46

Simultaneous Spectral Albedo Measurements Near the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) Central Facility  

SciTech Connect (OSTI)

In this study, a data analysis is performed to determine the area-averaged, spectral albedo at ARM's SGP central facility site. The spectral albedo is then fed into radiation transfer models to show that the diffuse discrepancy is diminished when the spectral albedo is used (as opposed to using the broadband albedo).

Michalsky, Joseph J.; Min, Qilong; Barnard, James C.; Marchand, Roger T.; Pilewskie, Peter

2003-04-30T23:59:59.000Z

47

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

E-Print Network [OSTI]

STUDY OF CLOUD LIFETIME EFFECTS USING THE SGP HETEROGENEOUS DISTRIBUTED RADAR NETWORK: PRELIMINARY-dimensional morphology and life cycle of clouds. Detailing key cloud processes as they transit from the formation stage to precipitation onset and cloud dissipation is critical towards establishing uncertainties in climate models

48

Investigation of the Downwelling LW Differences Between the Niamey AMF Main and Supplementary Sites  

SciTech Connect (OSTI)

The overall average downwelling longwave (LW) measured at the Niamey supplementary facility (S1) is 6-8 Wm-2 less than that measured by the two instruments located at the ARM Mobile Facility (AMF) main (N1) site. Examination of all other data available at both sites does not reveal any overarching differences that suggest this should be the case. However, examination of the pyrgeometer case and dome temperatures do suggest that the S1 values are also anomalously low, which in turn would explain the downwelling LW anomaly since the LW is calculated using these temperatures. Our recommendation then is to normalize the S1 data to the average N1 value by applying an adjustment factor to the S1 downwelling pyrgeometer case and dome temperatures (in Kelvin), then recalculating the downwelling LW values. The adjustment factor (0.00305) has been determined as that factor that brings the overall average S1 LWdn to agree with the overall average of the two N1 LWdn data series. We note that there is no reason to expect that the two site averages would actually be exactly equal to one another, and thus our recommendation is viewed as likely moving the S1 data in the right direction and by normalizing to the N1 average will help facilitate more meaningful temporal variability studies at least. It is also strongly recommended that for all future AMF deployments where supplementary sites will also be deployed, that the supplementary instrument systems (complete) be assembled as they will be operated in the field and run for at least a few days beside the corresponding AMF main site instruments, both at the beginning and end of the AMF field campaign. This is absolutely crucial so that all the measurements can be compared pre- and post-experiment to properly relate these measurements and systems, and to detect measurement anomalies such as those discussed in this report.

CN Long; P Gotseff; EG Dutton

2008-04-01T23:59:59.000Z

49

Surface Energy Balance System (SEBS) Handbook  

SciTech Connect (OSTI)

A Surface Energy Balance System (SEBS) has been installed collocated with each deployed ECOR system at the Southern Great Plains (SGP), North Slope of Alaska (NSA), Tropical Western Pacific (TWP), ARM Mobile Facility 1 (AMF1), and ARM Mobile Facility 2 (AMF2). The surface energy balance system consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil measurements. The SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

Cook, DR

2011-02-14T23:59:59.000Z

50

Atmospheric Radiation Measurement (ARM) Data from the Southern Great Plains (SGP) 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. Scientists are using the information obtained from the permanent SGP site to improve cloud and radiative models and parameterizations and, thereby, the performance of atmospheric general circulation models used for climate research. More than 30 instrument clusters have been placed around the SGP site. The locations for the instruments were chosen so that the measurements reflect conditions over the typical distribution of land uses within the site. The continuous observations at the SGP site are supplemented by intensive observation periods, when the frequency of measurements is increased and special measurements are added to address specific research questions. During such periods, 2 gigabytes or more of data (two billion bytes) are generated daily. SGP data sets from 1993 to the present reside in the ARM Archive at http://www.archive.arm.gov/ http. 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.

51

ARM Quick-looks Database for North Slope Alaska (NSA) sites  

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

From these pages one can monitor parts of the data acquisition process and access daily data visualizations from the different instruments. These data visualizations are produced in near real time automatically and are called Quick-Looks (QLs). The quick-looks contains unofficial data of unknown quality. Once data is released one can obtain the full data-set from any instrument available, and along with that, a statement about the data quality from the ARM archive. The database provides Quick-looks for the Barrow ACRF site (NSA C1), the Atqasuk ACRF site (NSA C2), or the SHEBA ice campaign of 1997 and 1998. As of 12-17-08, the database had more than 528,000 quick-looks available as data figures and data plots. No password is required for Quick-look access. (Specialized Interface)

Stamnes, Knut (NSA Site Scientist)

52

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.

53

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)]

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

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

54

ARM SGP and BN AERI Instrument Diagnostic Comparison and Preliminary Assessment  

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 SGP Program20 40 60ARM

55

Improved ARM-SGP TOA OLR Fluxes from GOES-8 IR Radiances Based on CERES Data  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsingFun withconfinementEtching.348 270 300 219 255 135 1982-2015 East CoastARM-SGP

56

Infrared Land Surface Emissivity in the Vicinity of the ARM SGP Central 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 Depth7-1D: Vegetation ProposedUsingFunInfrared Land Surface Emissivity in the Vicinity of the ARM SGP Central

57

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

E-Print Network [OSTI]

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

Dong, Xiquan

58

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

SciTech Connect (OSTI)

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.

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

2001-06-01T23:59:59.000Z

59

Multi-Summer Climatology of Cumuli at SGP site: Vertical Structure  

SciTech Connect (OSTI)

We perform a case study for estimating the impact of the vertical distribution of cloud fraction on the normalized cloud radiative forcing (CRF) using a decade-long (2000-2009) high resolution dataset of cloud macrophysical and radiative properties. This dataset is developed for fair-weather cumuli (FWC) observed at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The design of the case study reduces effects associated with non-cloud factors, such as the diurnal changes of aerosol loading and solar zenith angle. The results of the case study suggest that the impact of the vertical cloud structure can be substantial. Therefore, taking into account the vertical distribution of clouds would be beneficial for more comprehensive parameterizations aimed to portray the complex interactions between clouds and radiation more accurately

Kassianov, Evgueni I.; Berg, Larry K.

2011-10-01T23:59:59.000Z

60

Atmospheric Radiation Measurement (ARM) Data from Niamey, Niger for the Radiative Atmospheric Divergence using AMF, GERB and AMMA Stations (RADAGAST)  

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. The ARM Mobile Facility (AMF) operates at non-permanent sites selected by the ARM Program. Sometimes these sites can become permanent ARM sites, as was the case with Graciosa Island in the Azores. It is now known as the Eastern North Atlantic permanent site. In January 2006 the AMF deployed to Niamey, Niger, West Africa, at the Niger Meteorological Office at Niamey International Airport. This deployment was timed to coincide with the field phases and Special Observing Periods of the African Monsoon Multidisciplinary Analysis (AMMA). The ARM Program participated in this international effort as a field campaign called "Radiative Divergence using AMF, GERB and AMMA Stations (RADAGAST).The primary purpose of the Niger deployment was to combine an extended series of measurements from the AMF with those from the Geostationary Earth Radiation Budget (GERB) Instrument on the Meteosat operational geostationary satellite in order to provide the first well-sampled, direct estimates of the divergence of solar and thermal radiation across the atmosphere. A large collection of data plots based on data streams from specific instruments used at Niamey are available via a link from ARM's Niamey, Niger site information page. Other data can be found at the related websites mentioned above and in the ARM Archive. Users will be requested to create a password, but the plots and data files are free for viewing and downloading. The ARM Archive physically resides at the Oak Ridge National Laboratory.

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61

Raman lidar profiling of water vapor and aerosols over the ARM SGP Site  

SciTech Connect (OSTI)

The authors have developed and implemented automated algorithms to retrieve profiles of water vapor mixing ratio, aerosol backscattering, and aerosol extinction from Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) Raman Lidar data acquired during both daytime and nighttime operations. The Raman lidar sytem is unique in that it is turnkey, automated system designed for unattended, around-the-clock profiling of water vapor and aerosols. These Raman lidar profiles are important for determining the clear-sky radiative flux, as well as for validating the retrieval algorithms associated with satellite sensors. Accurate, high spatial and temporal resolution profiles of water vapor are also required for assimilation into mesoscale models to improve weather forecasts. The authors have also developed and implemented routines to simultaneously retrieve profiles of relative humidity. These routines utilize the water vapor mixing ratio profiles derived from the Raman lidar measurements together with temperature profiles derived from a physical retrieval algorithm that uses data from a collocated Atmospheric Emitted Radiance Interferometer (AERI) and the Geostationary Operational Environmental Satellite (GOES). These aerosol and water vapor profiles (Raman lidar) and temperature profiles (AERI+GOES) have been combined into a single product that takes advantage of both active and passive remote sensors to characterize the clear sky atmospheric state above the CART site.

Ferrare, R.A.

2000-01-09T23:59:59.000Z

62

RAMAN LIDAR PROFILING OF WATER VAPOR AND AEROSOLS OVER THE ARM SGP SITE.  

SciTech Connect (OSTI)

We have developed and implemented automated algorithms to retrieve profiles of water vapor mixing ratio, aerosol backscattering, and aerosol extinction from Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) Raman Lidar data acquired during both daytime and nighttime operations. This Raman lidar system is unique in that it is turnkey, automated system designed for unattended, around-the-clock profiling of water vapor and aerosols (Goldsmith et al., 1998). These Raman lidar profiles are important for determining the clear-sky radiative flux, as well as for validating the retrieval algorithms associated with satellite sensors. Accurate, high spatial and temporal resolution profiles of water vapor are also required for assimilation into mesoscale models to improve weather forecasts. We have also developed and implemented routines to simultaneously retrieve profiles of relative humidity. These routines utilize the water vapor mixing ratio profiles derived from the Raman lidar measurements together with temperature profiles derived from a physical retrieval algorithm that uses data from a collocated Atmospheric Emitted Radiance Interferometer (AERI) and the Geostationary Operational Environmental Satellite (GOES) (Feltz et al., 1998; Turner et al., 1999). These aerosol and water vapor profiles (Raman lidar) and temperature profiles (AERI+GOES) have been combined into a single product that takes advantage of both active and passive remote sensors to characterize the clear sky atmospheric state above the CART site.

FERRARE,R.A.

2000-01-09T23:59:59.000Z

63

Broadband Heating Rate Profile Project (BBHRP) - SGP 1bbhrpripbe1mcfarlane  

SciTech Connect (OSTI)

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Riihimaki, Laura; Shippert, Timothy

2014-11-05T23:59:59.000Z

64

Broadband Heating Rate Profile Project (BBHRP) - SGP 1bbhrpripbe1mcfarlane  

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

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

Riihimaki, Laura; Shippert, Timothy

65

QUANTIFYING HYDROMETEOR ADVECTION AND THE VERTICAL DISTRIBUTION OF CLOUD FRACTION OVER THE SGP CART SITE  

SciTech Connect (OSTI)

A single column model (SCM) is, in essence, an isolated grid column of a general circulation model (GCM). Hence, SCMs have rather demanding input data requirements, but do not suffer from problems associated with balance of a GCM. Among the initial conditions that must be used to describe the initial state of the SCM column are the vertical profile of the horizontal wind components and the vertical profiles of cloud water and ice. In addition, the large-scale divergence and advective tendencies of cloud water and ice must be supplied as external parameters. Finally, the liquid and ice cloud amount as a function of height within the SCM column are required for model evaluation. The scale of the SCM column over which the initial conditions, external parameters, and model evaluation fields must apply is relatively large ({approximately}300 km). To quantify atmospheric structure on this scale, the ARM SGP CART site is located within the NOAA wind profiler network and has boundary and extended measurement facilities in an area compatible with the scale requirements of SCMs. Over an area this size, however, there is often rich mesoscale structure. This mesoscale variability creates a sampling problem that can thwart even the most sophisticated attempts to quantify the initial conditions and external parameters, and to evaluate model performance. There are two approaches that can be used to quantify the time varying quantities required for SCMs: objective analysis and data assimilation. The latter relies on products produced for operational forecasting, while the former involves methods that can be used to combine measurements from various sources to produce synoptic descriptions of the large-scale dynamical and thermodynamic fields. Since data assimilation from operational models introduces the uncertainty of the parameterizations used in the models, most of the focus in the SCM effort has been on developing objective analysis techniques.

MILLER,M.; VERLINDE,J.

1998-03-23T23:59:59.000Z

66

Diurnal Cycle of Convection at the ARM SGP Site: Role of Large-Scale Forcing, Surface Fluxes, and Convective Inhibition  

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 Depth7-1D: Vegetation Proposed Newcatalyst phasesDataTranslocationDiurnal Cycle of Convection at the ARM SGP Site:

67

Scanning Microscopy, Vol. 5, No. 2, 1991 (Pages 317-328) Scanning Microscopy International, Chicago (AMF O'Hare), IL 60666 USA  

E-Print Network [OSTI]

(AMF O'Hare), IL 60666 USA 0891-7035/91$3.00+.00 RESTRICTED ENERGY TRANSFER IN LASER DESORPTION OF HIGH- guished importance in mass spectrometry. In our present study we survey different laser desorption methods of restricted energy transfer pathways as a pos- sible explanation to the volatilization of non-degraded large

Vertes, Akos

68

Scanning ARM Cloud Radar Handbook  

SciTech Connect (OSTI)

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.

Widener, K; Bharadwaj, N; Johnson, K

2012-06-18T23:59:59.000Z

69

Comparison of improved Aura Tropospheric Emission Spectrometer (TES) CO{sub 2} with HIPPO and SGP aircraft profile measurements  

SciTech Connect (OSTI)

Comparisons are made between mid-tropospheric Tropospheric Emission Spectrometer (TES) carbon dioxide (CO{sub 2}) satellite measurements and ocean profiles from three Hiaper Pole-to-Pole Observations (HIPPO) campaigns and land aircraft profiles from the United States Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site over a 4-yr period. These comparisons are used to characterize the bias in the TES CO{sub 2} estimates and to assess whether calculated and actual uncertainties and sensitivities are consistent. The HIPPO dataset is one of the few datasets spanning the altitude range where TES CO{sub 2} estimates are sensitive, which is especially important for characterization of biases. We find that TES CO{sub 2} estimates capture the seasonal and latitudinal gradients observed by HIPPO CO{sub 2} measurements; actual errors range from 0.8–1.2 ppm, depending on the campaign, and are approximately 1.4 times larger than the predicted errors. The bias of TES versus HIPPO is within 0.85 ppm for each of the 3 campaigns; however several of the sub-tropical TES CO{sub 2} estimates are lower than expected based on the calculated errors. Comparisons of aircraft flask profiles, which are measured from the surface to 5 km, to TES CO{sub 2} at the SGP ARM site show good agreement with an overall bias of 0.1 ppm and rms of 1.0 ppm. We also find that the predicted sensitivity of the TES CO{sub 2} estimates is too high, which results from using a multi-step retrieval for CO{sub 2} and temperature. We find that the averaging kernel in the TES product corrected by a pressure-dependent factor accurately reflects the sensitivity of the TES CO{sub 2} product.

Kulawik, S. S.; Worden, J. R.; Wofsy, S. C.; Biraud, S. C.; Nassar, R.; Jones, D. B.A.; Olsen, E. T.; Osterman, G. B.

2012-02-01T23:59:59.000Z

70

Cloud Property Retrieval Products for Graciosa Island, Azores  

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

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.

Dong, Xiquan

71

Cloud Property Retrieval Products for Graciosa Island, Azores  

SciTech Connect (OSTI)

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.

Dong, Xiquan

2014-05-05T23:59:59.000Z

72

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.

73

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

SciTech Connect (OSTI)

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

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

2004-11-01T23:59:59.000Z

74

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

SciTech Connect (OSTI)

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

Janet Intrieri; Mathhew Shupe

2005-01-01T23:59:59.000Z

75

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

SciTech Connect (OSTI)

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

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

2009-08-20T23:59:59.000Z

76

AMF Deployment, Hyytiala, Finland  

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77

AMF Deployment, Manacapuru, Brazil  

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78

AMF ARM Mobile FAcility  

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79

AMF Deployment, Oliktok, Alaska  

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80

AMF Deployment, Shouxian, China  

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Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

ARM - AMF Science  

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82

ARM - AMF Science Questions  

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83

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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84

NSA Atqasuk Facility  

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85

NSA Barrow Facility  

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86

ARM - NSA Barrow Facility  

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87

ARM - NSA Calendar  

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88

ARM - NSA Operations  

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89

SGP Overview Map  

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90

ARM - SGP Boundary Facility  

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91

ARM - SGP Central Facility  

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92

ARM - SGP Contacts  

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93

ARM - SGP Intermediate Facility  

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94

ARM - SGP Operations  

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95

ARM - SGP Science  

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96

SGP Central Facility  

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97

AMF Deployment, Black Forest, Germany  

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98

AMF Deployment, Ganges Valley, India  

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99

AMF Deployment, Graciosa Island, Azores  

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100

NSA Broadband Instrument Study: Update  

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Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

ARM - SGP Radiometric Calibration Facility  

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102

ARM - SGP Rural Driving Hazards  

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103

ARM - News : AMF Deployment, Shouxian, China  

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104

AMF Deployment, Niamey, Niger, West Africa  

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105

AMF Deployment, Point Reyes National Seashore, California  

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106

Tower Temperature and Humidity Sensors (TWR) Handbook  

SciTech Connect (OSTI)

Three tall towers are installed at the Atmospheric Radiation Measurement (ARM) Climate Research Facility: a 60-meter triangular tower at the Southern Great Plains (SGP) Central Facility (CF), a 21-meter walkup scaffolding tower at the SGP Okmulgee forest site (E21), and a 40-meter triangular tower at the North Slope of Alaska (NSA) Barrow site. The towers are used for meteorological, radiological, and other measurements.

Cook, DR

2010-02-01T23:59:59.000Z

107

ARM/NSA Vehicle Use Policy  

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108

ARM/NSA Vehicle Use Policy  

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

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109

ARM - NSA Atqasuk Facility-Inactive  

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110

Aerosol Retrievals from ARM SGP MFRSR Data  

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

The Multi-Filter Rotating Shadowband Radiometer (MFRSR) makes precise simultaneous measurements of the solar direct normal and diffuse horizontal irradiances at six wavelengths (nominally 415, 500, 615, 673, 870, and 940 nm) at short intervals (20 sec for ARM instruments) throughout the day. Time series of spectral optical depth are derived from these measurements. Besides water vapor at 940 nm, the other gaseous absorbers within the MFRSR channels are NO2 (at 415, 500, and 615 nm) and ozone (at 500, 615, and 670 nm). Aerosols and Rayleigh scattering contribute atmospheric extinction in all MFRSR channels. Our recently updated MFRSR data analysis algorithm allows us to partition the spectral aerosol optical depth into fine and coarse modes and to retrieve the fine mode effective radius. In this approach we rely on climatological amounts of NO2 from SCIAMACHY satellite retrievals and use daily ozone columns from TOMS.

Alexandrov, Mikhail

111

New Surface Meteorological Measurements at SGP,  

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112

ARM - Field Campaign - SGP '97 (Hydrology) IOP  

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113

ARM - Field Campaign - SGP99 IOP  

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114

Interpolation Uncertainties Across the ARM SGP Area  

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115

BNL-69418-AB Research by BNL investigators was performed under the auspices of the U.S. Department of Energy under Contract  

E-Print Network [OSTI]

For presentation at the American Geophysical Union 2002 Annual Meeting San Francisco, CA Dec. 6-10, 2002 ABSTRACT) program established the Southern Great Plains (SGP, north-central Oklahoma) and North Slope of Alaska (NSA solar irradiance (pyranometers). Spectral diffuse-horizontal irradiance relative to top of atmosphere

116

Microsoft Word - AMF2 Environmental Health and Safety Manual...  

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

to electrical hazards. 12.7.2 Selection Guidelines for Foot Protection Safety shoes and boots provide both impact and compression protection. Where necessary, safety shoes that...

117

ARM - AMF Deployment, Los Angeles, California, to Honolulu, Hawaii  

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118

ARM - Field Campaign - RAdiative Divergence using AMF, GERB and AMMA  

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119

AMF Deployment, Pearl Harbor, Hawaii, to San Francisco, California  

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120

ARM/NSA ES&H Policy Statement  

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Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
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121

ARM - PI Product - NSA AERI Hatch Correction Data Set  

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122

Radiative Closure Studies at the NSA ACRF Site  

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123

Microsoft PowerPoint - nsa_shippingforminstructions.ppt  

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124

A comparison of water vapor quantities from model short-range forecasts and ARM observations  

SciTech Connect (OSTI)

Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

Hnilo, J J

2006-03-17T23:59:59.000Z

125

Merged MMCR-WSR88D Reflectivities at SGP  

SciTech Connect (OSTI)

There are substantial attenuations of MMCR signals for very large LWP and during precipitation events. We have used the nearest precipitation radar (WSR-88D) to merge two measurements to better represent such selected cases. In the near future, we are going to provide all the cumulus cases from Jan. 1997 to present whenever the two datasets are available. The original 2 data sets:

Dong, Xiquan

2008-03-05T23:59:59.000Z

126

arm sgp site: Topics by E-print Network  

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

of detailed ... Waters, Richard C. 1979-10-01 25 ARM7100 Data Sheet ARM DDI 0035A Engineering Websites Summary: ARM7100 Data Sheet ARM DDI 0035A 5-1 11 1 Preliminary ARM...

127

Merged MMCR-WSR88D Reflectivities at SGP  

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

There are substantial attenuations of MMCR signals for very large LWP and during precipitation events. We have used the nearest precipitation radar (WSR-88D) to merge two measurements to better represent such selected cases. In the near future, we are going to provide all the cumulus cases from Jan. 1997 to present whenever the two datasets are available. The original 2 data sets:

Dong, Xiquan

128

Implementation of instruments and facilities at the SGP CART site  

SciTech Connect (OSTI)

This report discusses the installation of instruments and trailers at the southern Great Plains Clouds and Radiation Testbed site.

Sisterson, D.L.; Wesely, M.L.

1994-02-01T23:59:59.000Z

129

Direct Aerosol Forcing in the Infrared at the SGP Site?  

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130

sgp_stratus_poster_v1.0.ppt  

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131

New Atmospheric Profiling Instrument Added to SGP CART Suite  

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132

New Eddy Correlation System for ARM SGP Site  

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133

ARM - Publications: Science Team Meeting Documents: The SGP Aerosol  

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134

ARM - PI Product - Aerosol Retrievals from ARM SGP MFRSR Data  

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135

Deployment of a New Shortwave Spectroradiometer (SWS) at the SGP  

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136

* SGP Central Facility - surrounded by wheat felds, the  

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137

Investigation of Unusual Albedos in the SGP Domain  

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138

An Overview of the SGP Tandem Differential Mobility Analyzer  

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139

CIMEL Measurements of Zenith Radiances at the ARM SGP Site  

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140

Continental Liquid-phase Stratus Clouds at SGP: Meteorological Influences  

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Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Surface Albedo at ARM SGP from Helicopter Observations  

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142

Simultaneous Spectral Albedo Measurements Near the ARM SGP Central Facility  

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143

Eddy Correlation Flux Measurement System (ECOR) Handbook  

SciTech Connect (OSTI)

The eddy correlation (ECOR) flux measurement system provides in situ, half-hour measurements of the surface turbulent fluxes of momentum, sensible heat, latent heat, and carbon dioxide (CO2) (and methane at one Southern Great Plains extended facility (SGP EF) and the North Slope of Alaska Central Facility (NSA CF). The fluxes are obtained with the eddy covariance technique, which involves correlation of the vertical wind component with the horizontal wind component, the air temperature, the water vapor density, and the CO2 concentration.

Cook, DR

2011-01-31T23:59:59.000Z

144

Evaluating Global Aerosol Models and Aerosol and Water Vapor Properties Near Clouds  

SciTech Connect (OSTI)

Project goals: (1) Use the routine surface and airborne measurements at the ARM SGP site, and the routine surface measurements at the NSA site, to continue our evaluations of model aerosol simulations; (2) Determine the degree to which the Raman lidar measurements of water vapor and aerosol scattering and extinction can be used to remotely characterize the aerosol humidification factor; (3) Use the high temporal resolution CARL data to examine how aerosol properties vary near clouds; and (4) Use the high temporal resolution CARL and Atmospheric Emitted Radiance Interferometer (AERI) data to quantify entrainment in optically thin continental cumulus clouds.

Richard A. Ferrare; David D. Turner

2011-09-01T23:59:59.000Z

145

Coupling Between Oceanic Upwelling and Cloud-aerosol Properties at the AMF Point Reyes Site  

SciTech Connect (OSTI)

Cloud microphysical properties measured at the ARM Mobile Facility site located on the northern coast of California near Point Reyes, during the 2005 Marine Stratus Radiation, Aerosol and Drizzle experiment, were analyzed to determine their relationship to the coastal sea surface temperature (SST) which was characterized using measurements acquired from a National Oceanic and Atmospheric Administration offshore buoy. An increase in SST resulting from a relaxation of upwelling, occurring in the eastern Pacific Ocean off the coast of California in summer is observed to strongly correlate with nearby ground measured cloud microphysical properties and cloud condensation nuclei (CCN) concentrations. Correlations between these atmospheric and oceanic features provide insight into the interplay between the ocean and cloud radiative properties. We present evidence of this robust correlation and examine the factors controlling these features. The marine boundary layer is in direct contact with the sea surface and is strongly influenced by SST. Moisture and vertical motion are crucial ingredients for cloud development and so we examine the role of SST in providing these key components to the atmosphere. Although upwelling of cold subsurface waters is conventionally thought to increase aerosols in the region, thus increasing clouds, here we observed a relaxation of upwelling associated with changes in the structure of marine stratus clouds. As upwelling relaxes, the SST get warmer, thick clouds with high liquid water paths are observed and persist for a few days. This cycle is repeated throughout the summer upwelling season. A concomitant cyclic increase and decrease of CCN concentration is also observed. Forcing mechanisms and large-scale atmospheric features are discussed. Marine stratocumulus clouds are a critical component of the earth's radiation budget and this site provides an excellent opportunity to study the influence of SST on these clouds.

Dunn, M.; Jensen, M.; Miller, M.; Kollias, P.; Bartholomew, M. J.; Turner, D.; Andrews, E.; Jefferson, A.; Daum, P.

2008-03-10T23:59:59.000Z

146

ARM - Field Campaign - Application of the ARM Mobile Facility (AMF) to  

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147

Microsoft PowerPoint - 080306_stm_amf.ppt [KompatibilitĂ€tsmodus]  

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148

Microsoft Word - 20130423 AMF2_MAGIC_Safety_Appendix_for_Web.docx  

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149

Microsoft Word - AMF2 Environmental Health and Safety Manual April 2013.docx  

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150

Microsoft Word - AMF2_BAECC_Safety_Appendix_For_Web.doc  

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151

New ARM Data Stream: Surface Images at NSA/AAO Sites in Barrow and Atqasuk  

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152

Derivation of Seasonal Cloud Properties at ARM-NSA from Multispectral MODIS Data  

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153

ARM - Evaluation Product - NSA-Barrow AmeriFlux and Methane VAP  

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154

ARM - Field Campaign - AIRS Validation Soundings Phase IV and V-NSA  

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155

ARM - Field Campaign - ARM Radiosondes for NPOESS/NPP Validation - NSA  

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156

Analysis of Selected Radiosonde Data from the ARM/NSA Site  

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157

Short-Term Arctic Cloud Statistics at NSA from the Infrared Cloud Imager  

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158

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

SciTech Connect (OSTI)

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.

Richard C. J. Somerville

2009-02-27T23:59:59.000Z

159

SGP Cloud and Land Surface Interaction Campaign (CLASIC): Science and Implementation Plan  

SciTech Connect (OSTI)

The Cloud and Land Surface Interaction Campaign is a field experiment designed to collect a comprehensive data set that can be used to quantify the interactions that occur between the atmosphere, biosphere, land surface, and subsurface. A particular focus will be on how these interactions modulate the abundance and characteristics of small and medium size cumuliform clouds that are generated by local convection. These interactions are not well understood and are responsible for large uncertainties in global climate models, which are used to forecast future climate states. The campaign will be conducted from June 8 to June 30, 2007, at the U.S. Department of Energy’s Atmospheric Radiation Measurement Climate Research Facility Southern Great Plains site. Data will be collected using eight aircraft equipped with a variety of specialized sensors, four specially instrumented surface sites, and two prototype surface radar systems. The architecture of Cloud and Land Surface Interaction Campaign includes a high-altitude surveillance aircraft and enhanced vertical thermodynamic and wind profile measurements that will characterize the synoptic scale structure of the clouds and the land surface within the Atmospheric Radiation Measurement Climate Research Facility Southern Great Plains site. Mesoscale and microscale structures will be sampled with a variety of aircraft, surface, and radar observations.

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

2007-06-30T23:59:59.000Z

160

OFFLINE EVALUATION OF SIX SURFACE LAYER PARAMETERIZATION SCHEMES AGAINST OBSERVATIONS AT THE ARM SGP SITE  

E-Print Network [OSTI]

) and EBBR (Energy Balance Bowen Ratio) methods. To minimize potential feedback influences resulting from. The publisher by accepting the manuscript for publication acknowledges that the United States Government retains of this manuscript, or allow others to do so, for United States Government purposes. BNL-94806-2011-AB #12;

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

2.1 RAMAN LIDAR PROFILING OF WATER VAPOR AND AEROSOLS OVER THE ARM SGP SITE  

E-Print Network [OSTI]

with satellite sensors. Accurate, high spatial and temporal resolution profiles of water vapor are also required+GOES) have been combined into a single product that takes advantage of both active and passive remote sensors with the use of narrowband (~0.4 nm bandpass) filters, reduces the background skylight and, therefore

162

E-Print Network 3.0 - arm program sgp Sample Search Results  

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

of surface fluxes collected by the DOE (Department of Energy) ARM (Atmospheric Radiation Measurement) program... OFFLINE EVALUATION OF SIX SURFACE LAYER PARAMETERIZATION SCHEMES...

163

Evaluation of Precipitation Simulated by Seven SCMs against the ARM Observations at the SGP Site*  

E-Print Network [OSTI]

System Modeling, Center for Earth System Science, Tsinghua University, Beijing, China. Corresponding://dx.doi.org/10.1175/JCLI- D-00263.s1. 11 Current affiliation: Ministry of Education Key Laboratory for Earth

Ohta, Shigemi

164

Determination of Ice Water Path Over the ARM SGP Using Combined Surface and Satellite Datasets  

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165

Validation of Satellite-Derived Liquid Water Paths Using ARM SGP Microwave Radiometers  

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166

Validation of the ARchived CERES Surface and Atmosphere Radiation Budget at SGP  

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167

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

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168

Searching for Global Dimming Evidence at SGP and Update of ARM Submissions to BSRN  

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169

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

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

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170

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

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

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171

ARM - PI Product - Merged MMCR-WSR88D Reflectivities at SGP  

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

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172

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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173

ARM - PI Product - Soundings from SGP, June 2014 Sonde Comparison Study  

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 :ProductsSCM Forcing Data Derived from NWP Analyses ARM Data

174

Preliminary Analysis of ARM SGP Area Sky Cover and Downwelling SW Irradiance  

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

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175

Preliminary Analysis of Surface Radiation Measurement Data Quality at the SGP Extended Facilities  

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

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176

Observed and Simulated Cirrus Cloud Properties at the SGP CART Site  

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 MayAtmosphericNuclear Security Administration the ContributionsArmsSpeedingSpeedingUnder Well-ControlledObservationObserved Regimesand

177

Techniques and Methods Used to Determine the Best Estimate of Radiation Fluxes at SGP Central 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 MayAtmosphericNuclear Security AdministrationcontrollerNanocrystallineForeign ObjectOUR8,Materials Characterization Technique

178

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

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

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 MayAtmosphericNuclear SecurityTensile Strain Switched Ferromagnetism in Layered NbS2 and NbSe2Different Impacts of SO2 andOxide

179

ARM - Field Campaign - AIRS Validation Soundings Phase IV and V-SGP  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3, 2010September 30,JuneMayIII ARM Data Discovery

180

ARM - Field Campaign - ARM Radiosondes for NPOESS/NPP Validation - SGP  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNGExperience4AJ01)3, 2010September 30,JuneMayIII ARMgovCampaignsARMgovCampaignsARM

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
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181

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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182

Initial Evaluation of the Cumulus Potential Scheme at the ACRF SGP Site  

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

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183

Investigation of SGP Atmospheric Moisture Budget for CLASIC … Recycling Study  

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184

Measuring the Raindrop Size Distribution, ARM's Efforts at Darwin and SGP  

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

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185

An Improved Cloud Classification Algorithm Based on the SGP CART Site Observations  

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

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186

Senator Myers Tours SGP CART Site Technical Contact: James C. Liljegren  

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

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187

CONTINENTAL LIQUID-PHASE STRATUS CLOUDS AT SGP: METEOROLOGICAL INFLUENCES AND RELATIONSHIP TO ADIABACITY  

E-Print Network [OSTI]

of New York at Albany For Presentation at the ARM Science Team Meeting, Albuquerque, NM March 27-31, 2006, such as static stability and updraft velocity. These influences may contribute to the observed weak correlation with entrainment processes around cloud top. These processes would be expected to decrease the amount of column

188

ARM Multi-Filter Rotating Shadowband Radiometer (MFRSR): irradiances  

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

The multifilter rotating shadowband radiometer (MFRSR) takes spectral measurements of direct normal, diffuse horizontal and total horizontal solar irradiances. These measurements are at nominal wavelengths of 415, 500, 615, 673, 870, and 940 nm. The measurements are made at a user-specified time interval, usually about one minute or less. The sampling rate for the Atmospheric Radiation Measurement (ARM) Climate Research Facility MFRSRs is 20 seconds. From such measurements, one may infer the atmosphere's optical depth at the wavelengths mentioned above. In turn, these optical depths may be used to derive information about the column abundances of ozone and water vapor (Michalsky et al. 1995), as well as aerosol (Michalsky et al. 1994) and other atmospheric constituents. A silicon detector is also part of the MFRSR. This detector provides a measure of the broadband direct normal, diffuse horizontal and total horizontal solar irradiances. A MFRSR head that is mounted to look vertically downward can measure upwelling spectral irradiances. In the ARM system, this instrument is called a multifilter radiometer (MFR). At the Southern Great Plains (SGP) there are two MFRs; one mounted at the 10-m height and the other at 25 m. At the North Slope of Alaska (NSA) sites, the MFRs are mounted at 10 m. MFRSR heads are also used to measure normal incidence radiation by mounting on a solar tracking device. These are referred to as normal incidence multi-filter radiometers (NIMFRs) and are located at the SGP and NSA sites. Another specialized use for the MFRSR is the narrow field of view (NFOV) instrument located at SGP. The NFOV is a ground-based radiometer (MFRSR head) that looks straight up.

Hodges, Gary

189

Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected In-the-Wild  

E-Print Network [OSTI]

Computer classification of facial expressions requires large amounts of data and this data needs to reflect the diversity of conditions seen in real applications. Public datasets help accelerate the progress of research ...

McDuff, Daniel Jonathan

190

Atmosphere-Land-Surface Interaction over the Southern Great Plains: Diagnosis of Mechanisms from SGP ARM Data  

SciTech Connect (OSTI)

Work reported included analysis of pentad (5 day) averaged data, proposal of a hypothesis concerning the key role of the Atlantic Multi-decadal Oscillation in 20th century drought and wet periods over the Great Plains, analysis of recurrent super-synoptic evolution of the Great Plains low-level jet, and study of pentad evolution of the 1988 drought and 1993 flood over the Great Plains from a NARR perspective on the atmospheric and terrestrial water balance.

Sumant Nigam

2013-02-01T23:59:59.000Z

191

New Visible to Broadband Shortwave Conversions for Deriving Albedos from GOES-8 Over the ARM-SGP  

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

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192

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

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

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193

Techniques and Methods Used to Determine the Aerosol Best Estimate Value-Added Product at SGP Central Facility  

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

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194

Remotely Controlled, Continuous Observations of Infrared Radiance with the CSIRO/ARM Mark II Radiometer at the SGP CART Site  

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195

Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP. S...  

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196

ER2 Instrumentation and Measurements for CLASIC (Cloud Land Surface Interaction Campaign) June-2007 SGP {Author-Jimmy Voyles}  

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197

Effective Radius of Cloud Droplets Derived from Ground-based Remote Sensing at the ARM SGP site  

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 Depth7-1D: Vegetation Proposed NewcatalystNeutronEnvironmentZIRKLE FRUITYearEffect0/2002 Yun (Helen) He, GHC2002

198

Asymmetry in the Diurnal Cycle of Atmospheric Downwelling Radiation at the ARM SGP CF Site Over 1995-2001 Period  

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)ProductssondeadjustsondeadjustAbout theOFFICEAmesApplication2ArgonneAssemblyDemand ModuleMarket

199

Towards Development of a Synthesized Database of Spatial and Temporal Surface Spectral Reflectivity Over the ARM SGP CART Area  

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 MayAtmosphericNuclear SecurityTensile Strain Switched Ferromagnetism in Layered NbS2Topo II: An EnzymePersonal Computerso w a r d

200

Surface Di-directional Reflectance Properties Over the ARM SGP Area from Satellite Multi-Platform Observations  

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

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Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Surface Spectral Albedo Intensive Operational Period at the ARM SGP Site in august 2002: Results, Analysis, and Future Plans  

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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 MayAtmosphericNuclear Security AdministrationcontrollerNanocrystalline GalliumSuppression of conductivity inBatteriesonBeam

202

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

SciTech Connect (OSTI)

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.

Wang, Zhien

2010-06-29T23:59:59.000Z

203

Evaluating cloud retrieval algorithms with the ARM BBHRP framework  

SciTech Connect (OSTI)

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.

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

204

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

SciTech Connect (OSTI)

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.

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

2012-02-17T23:59:59.000Z

205

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)

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.

Xie, B; Dong, X; Xie, S

2012-05-18T23:59:59.000Z

206

Clouds, Aerosols and Precipitation in the Marine Boundary Layer (CAP-MBL) AMF Deployment Graciosa Island, Azores, NE Atlantic Ocean May 2009-December 2010  

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 Depth7-1D: Vegetation Proposed New SubstationClean Communities of WesternVailCloisteredPresence3 Cloudiness Inter-

207

Produced by the NC State Department of Computer Science www.csc.ncsu.edu NSA Science of Security "Lablet" Established at NC State  

E-Print Network [OSTI]

S) and a broad, self-sustaining community effort to advance it. A major goal is the creation of a unified body

Young, R. Michael

208

Millimeter-Wavelength Forward-Model Comparisons Based on Ground-Based Radiometric Data Taken During the 1999 NSA/AO Radiometric 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 Depth7-1D: VegetationEquipment SurfacesResource Program PreliminaryA3,

209

Measurement of Boundary-Layer Temperature Profiles by a Scanning 5-MM Radiometer During the 1999 Winter NSA/AAO Radiometer Exp  

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 Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale LandscapeImportsBG4, 2012 1:00core1

210

Comparison of Cloud Fraction and Liquid Water Path between ECMWF simulations and ARM long-term Observations at the NSA Site  

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 Depth7-1D: Vegetation Proposed New SubstationCleanCommunity Involvement and

211

Single-Column Modeling, GCM Parameterizations and Atmospheric Radiation Measurement Data  

SciTech Connect (OSTI)

Our overall goal is identical to that of the Atmospheric Radiation Measurement (ARM) Program: 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 and regional models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have first compared single-column model (SCM) output with ARM observations at the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Topical Western Pacific (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 3D 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. We are currently testing the performance of our ARM-based parameterizations in state-of-the--art global and regional models. One fruitful strategy for evaluating advances in parameterizations has turned out to be using short-range numerical weather prediction as a test-bed within which to implement and improve parameterizations for modeling and predicting climate variability. The global models we have used to date are the CAM atmospheric component of the National Center for Atmospheric Research (NCAR) CCSM climate model as well as the National Centers for Environmental Prediction (NCEP) numerical weather prediction model, thus allowing testing in both climate simulation and numerical weather prediction modes. We present detailed results of these tests, demonstrating the sensitivity of model performance to changes in parameterizations.

Somerville, R.C.J.; Iacobellis, S.F.

2005-03-18T23:59:59.000Z

212

LandUse/Land Cover Map of the CF of ARM in the SGP Site Using DOE's Multispectral Thermal Imager (MTI) Satellite Images  

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 Depth7-1D: VegetationEquipment Surfaces and Interfaces Sample6, 2011 CERN 73-11 Laboratory IPortal 2105ethanol

213

Measurement and Modeling of Vertically Resolved Aerosol Optical Properties and Radiative Fluxes Over the ARM SGP Site During the May 2003 Aerosol 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 Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale LandscapeImportsBG4, 2012 1:00core1 H(

214

E-Print Network 3.0 - alteros viewer irfan Sample Search Results  

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

Computer Technologies and Information Sciences 76 AMF File Viewer Utility for 3D Printing Applications Advisor: Prof. Hod Lipson hod.lipson@cornell.edu Summary: AMF File...

215

The Horizon Spirit is on its way to China for its previously scheduled maintenance and the AMF2, which is the suite of instruments used on MAGIC, is currently sitting in a warehouse in Los  

E-Print Network [OSTI]

, or SW, radiation (recall that the word "radiation" in this sense does NOT refer to radioactivity). Clouds scatter some of this radiation back to space, they absorb some of it (converting it to heat energy, or to the ocean #12;layers below the surface. The absorbed energy is converted to heat energy, and from

216

Spanish and Portuguese Alvin F. Sherman, Jr., Chair  

E-Print Network [OSTI]

in government service (translation, U.S. State Department, CIA, FBI, Border Patrol, Peace Corps, NSA, USIA

Hart, Gus

217

Influence of clouds and diffuse radiation on ecosystem-atmosphere CO 2 and CO 18 O exchanges  

E-Print Network [OSTI]

support provided by the Oklahoma and Kansas Mesonet program.Plains (SGP) region of Oklahoma and Kansas [Ackerman andwere taken from the Oklahoma and Kansas Mesonet program. The

2009-01-01T23:59:59.000Z

218

E-Print Network 3.0 - altus cumulus electrification Sample Search...  

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

in depleting low... -level water vapor as it is advected to the SGP from the Gulf of Mexico? How do cumulus clouds and ... Source: Brookhaven National Laboratory, Environmental...

219

High Spectral Resolution Infrared and Raman Lidar Observations for the ARM Program: Clear and Cloudy Sky Applications  

SciTech Connect (OSTI)

This grant began with the development of the Atmospheric Emitted Radiance Interferometer (AERI) for ARM. The AERI has provided highly accurate and reliable observations of downwelling spectral radiance (Knuteson et al. 2004a, 2004b) for application to radiative transfer, remote sensing of boundary layer temperature and water vapor, and cloud characterization. One of the major contributions of the ARM program has been its success in improving radiation calculation capabilities for models and remote sensing that evolved from the multi-year, clear-sky spectral radiance comparisons between AERI radiances and line-by-line calculations (Turner et al. 2004). This effort also spurred us to play a central role in improving the accuracy of water vapor measurements, again helping ARM lead the way in the community (Turner et al. 2003a, Revercomb et al. 2003). In order to add high-altitude downlooking AERI-like observations over the ARM sites, we began the development of an airborne AERI instrument that has become known as the Scanning High-resolution Interferometer Sounder (Scanning-HIS). This instrument has become an integral part of the ARM Unmanned Aerospace Vehicle (ARM-UAV) program. It provides both a cross-track mapping view of the earth and an uplooking view from the 12-15 km altitude of the Scaled Composites Proteus aircraft when flown over the ARM sites for IOPs. It has successfully participated in the first two legs of the “grand tour” of the ARM sites (SGP and NSA), resulting in a very good comparison with AIRS observations in 2002 and in an especially interesting data set from the arctic during the Mixed-Phase Cloud Experiment (M-PACE) in 2004. More specifically, our major achievements for ARM include 1. Development of the Atmospheric Emitted Radiance Interferometer (AERI) to function like a satellite on the ground for ARM, providing a steady stream of accurately calibrated spectral radiances for Science Team clear sky and cloud applications (Knuteson et al. 2004a), 2. Detailed radiometric calibration and characterization of AERI radiances, with uncertainty estimates established from complete error analyses and proven by inter-comparison tests (Knuteson et al. 2004b), 3. AERI data quality assessment and maintenance over the extended time frames needed to support ARM (Dedecker et al., 2005) 4. Key role in the radiative transfer model improvements from the AERI/LBLRTM QME (Turner et al. 2004) and AERI-ER especially from the SHEBA experiment (Tobin et al. 1999), 5. Contributed scientific and programmatic leadership leading to significant water vapor accuracy improvements and uncertainty assessments for the low to mid troposphere (Turner et al. 2003a, Revercomb et al. 2003), 6. Leadership of the ARM assessment of the accuracy of water vapor observations from radiosondes, Raman Lidar and in situ aircraft observations in the upper troposphere and lower stratosphere (Tobin et al. 2002, Ferrare et al. 2004), 7. New techniques for characterizing clouds from AERI (DeSlover et al. 1999, Turner 2003b, Turner et al. 2003b), 8. Initial design and development of the Scanning-HIS aircraft instrument and application to ARM UAV Program missions (Revercomb et al. 2005), and 9. Coordinated efforts leading to the use of ARM observations as a key validation tool for the high resolution Atmospheric IR Sounder on the NASA Aqua platform (Tobin et al. 2005a) 10. Performed ARM site and global clear sky radiative closure studies that shows closure of top-of-atmosphere flux at the level of ~1 W/m2 (Moy et al 2008 and Section 3 of this appendix) 11. Performed studies to characterize SGP site cirrus cloud property retrievals and assess impacts on computed fluxes and heating rate profiles (Borg et al. 2008 and Section 2 of this appendix).

Henry Revercomb, David Tobin, Robert Knuteson, Lori Borg, Leslie Moy

2009-06-17T23:59:59.000Z

220

Erfolg ist eine Frage der Technik. Und des richtigen Timings.  

E-Print Network [OSTI]

2014 in Karlsruhe. The Siemens Graduate Program siemens.com/careers/sgp Das Siemens Graduate Program Tag für Technikbegeisterte. Tauchen Sie ein in das Siemens Graduate Program (SGP) ­ das internationale von Siemens. Die Highlights: Sie stehen kurz vor dem Abschluss Ihres technischen oder naturwissen

Ulm, Universität

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221

NERSC/DOE FES Requirements Workshop Worksheet - Zhihong Lin  

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

Center and GPS-TTBP Center Principal Investigator Zhihong Lin Participating Organizations University of California, Irvine Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2....

222

NERSC/DOE BES Requirements Workshop Worksheet - Tony Ladd  

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

Principal Investigator Tony Ladd Participating Organizations University of Florida University of Warsaw Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project...

223

NERSC/DOE FES Requirements Workshop Worksheet - Kai Germaschewski  

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

and Turbulence Principal Investigator Amitava Bhattacharjee Participating Organizations University of New Hampshire Dartmouth College Funding Agencies DOE SC DOE NSA NSF NOAA NIH...

224

NERSC/DOE FES Requirements Workshop Worksheet - John Ludlow  

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

National Laboratory Los Alamos National Laboratory University of Strathclyde Queen's University of Belfast Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: EAEC, IAEA 2....

225

NERSC/DOE BES Requirements Workshop Worksheet - Burkhard Militzer  

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

Pressure Materials Principal Investigator Burkhard Militzer Participating Organizations University of California, Berkeley Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2....

226

NERSC/DOE BES Requirements Workshop Worksheet - Randy Cygan  

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

Sandia National Laboratories Michigan State University Northwestern University Purdue University Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary &...

227

NERSC/DOE FES Requirements Workshop Worksheet - Alex Friedman  

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

Fusion Energy) Principal Investigator Alex Friedman Participating Organizations LBNL, LLNL, PPPL, Univ. of Maryland Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2....

228

NERSC/DOE BES Requirements Workshop Worksheet - Hai-Ping Cheng  

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

Organizations University of Florida Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

229

NERSC/DOE BES Requirements Workshop Worksheet - Habib Najm  

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

Organizations Sandia National Laboratories Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

230

NERSC/DOE FES Requirements Workshop Worksheet - William Tang  

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

William Tang Participating Organizations Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

231

NERSC/DOE FES Requirements Workshop Worksheet - Stephane Ethier  

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

Weixing Wang Participating Organizations PPPL Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

232

NERSC/DOE FES Requirements Workshop Worksheet - Linda Sugiyama  

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

Sugiyama Participating Organizations test data Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

233

NERSC/DOE BES Requirements Workshop Worksheet - Thomas Miller  

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

California Institute of Technology Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

234

NERSC/DOE FES Requirements Workshop Worksheet - Stephen Jardin  

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

Participating Organizations PPPL, MIT, NYU Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

235

NERSC/DOE FES Requirements Workshop Worksheet - Scott Kruger  

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

Scott Kruger Participating Organizations Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

236

Careers in Government for Mathematicians  

E-Print Network [OSTI]

Sep 22, 2011 ... Secure Entrance to Main Building ... concerning the domestic activities of United States persons. NSA has declared that it relies on the FBI to ...

Edray Herber Goins

2011-09-20T23:59:59.000Z

237

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...

238

Faculty and Staff (cont.): UNL Parents Association Certificates of Recognition for  

E-Print Network [OSTI]

Richard Rebarber and Gordon Woodward, NSF-REU Site Funding Mark Walker, NSA grant Roger Wiegand, NSA grant). Susan Hermiller and John Meakin, Proceedings of the International Conference on Groups and Semigroups, 2000, International Journal of Algebra and Computa- tion (with M. Sapir). Jim Lewis, (et al

Logan, David

239

Proceedings of Meetings on Acoustics Volume 19, 2013 http://acousticalsociety.org/  

E-Print Network [OSTI]

Montreal Montreal, Canada 2 - 7 June 2013 Noise Session 3aNSa: Wind Turbine Noise I 3aNSa7. Development Recently, much attention is being paid to the noise produced by wind turbines. Interest has risen and annoyance related to wind turbine noise (Pedersen and Waye, 2004). More recent epidemiological studies

Grace, Sheryl M.

240

Proceedings of Meetings on Acoustics Volume 19, 2013 http://acousticalsociety.org/  

E-Print Network [OSTI]

Montreal Montreal, Canada 2 - 7 June 2013 Noise Session 3aNSa: Wind Turbine Noise I 3aNSa6. Amplitude modulation of audible sounds by non-audible sounds: Understanding the effects of wind turbine noise Jeffery-frequency noise could bother individuals living near wind turbines: causing endolymphatic hydrops, exciting

Salt, Alec N.

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

COMMUNICATIONS OF THE ACM December 2007/Vol. 50, No. 12 00 Building surveillance technologies into commu-  

E-Print Network [OSTI]

continents often transit the U.S. This role has been a real boon to the National Security Agency (NSA), the U security prob- lems--difficulty providing auditing, relying on passwords rather than token.S. signals intelligence organization. In recent years, however, cable has broadly replaced satellites. NSA

Singh, Jaswinder Pal

242

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)

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.

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

2013-05-31T23:59:59.000Z

243

Technical Report Documentation Page 1. Report No.  

E-Print Network [OSTI]

. Researchers developed accident modification factors (AMFs) related to frontage road conversion segments Frontage Road, Frontage Road Conversion, Crash Reduction Factor, CRF, Accident Modification Factor, AMF site in Texas that remained two-way for comparison to four of the treatment (conversion) sites

244

ARM: Short Wave Flux Analysis: 15-min resolution on SIRS data, Long algorithm  

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

Short Wave Flux Analysis: 15-min resolution on SIRS data, Long algorithm. Measurements began in January, 1994, and have continued to the present time. Data collected are from the Southern Great Plains (SGP) location.

Stoffel, Tom; Kay, Bev; Habte, Aron; Anderberg, Mary; Kutchenreiter, Mark

245

Geothermal Reservoir Evaluation Considering Fluid Adsorption  

E-Print Network [OSTI]

SGP-"R- 68 Geothermal Reservoir Evaluation Considering Fluid Adsorption and Composition Michael J. Economides September, 1983 Financial support was provided through the Stanford Geothermal Program Contract No Geothermal Program Interdisciplinary Research in Engineering and Earth Sciences STANFORD UNIVERSITY Stanford

Stanford University

246

CCRS Landcover Maps From Satellite Data  

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

The Canadian Centre for Remote Sensing (CCRS) presents several landcover maps over the SGP CART site area (32-40N, 92-102W) derived from satellite data including AVHRR, MODIS, SPOT vegetation data, and Landsat satellite TM imagery.

Trishchenko, Alexander

247

Parameterizing Size Distribution in Ice Clouds  

SciTech Connect (OSTI)

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

DeSlover, Daniel; Mitchell, David L.

2009-09-25T23:59:59.000Z

248

Peter Galison Interviewed by B. R. Cohen  

E-Print Network [OSTI]

, the Central Intelligence Agency (CIA), the National Security Agency (NSA), the Federal Bureau of Investigation the military and nuclear weapons labs, from the CIA, from the critics of secrecy from the Federation

Galison, Peter L.

249

Cornell University, Office of Sponsored Programs Awards Received in April 2009  

E-Print Network [OSTI]

AWARENESS $16,000 THF 57168 BOOTH, JAMES STAT SCI NSA 24TH INTERNATIONAL WORKSHOP ON STATISTICAL MODELING J CCMR-GENERAL NSF REU SITE: INTERDISCIPLINARY MATERIALS $168,000 MBF 49833 CHRISTOPHERSON, SUSAN M

Danforth, Bryan Nicholas

250

Descriptive and Predictive Analysis of Climate Data Advisor: Nitesh V. Chawla  

E-Print Network [OSTI]

Descriptive and Predictive Analysis of Climate Data Advisor: Nitesh V. Chawla DepartmentNSA) University of Notre Dame Co-Advisor: Auroop R. Ganguly Geographic Information Science and Technology Group

251

NERSC/DOE FES Requirements Workshop Worksheet - Doug McCune  

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

Doug McCune Participating Organizations Funding Agencies DOE SC DOE NSA NSF NOAA NIH Other: 2. Project Summary & Scientific Objectives for the Next 5 Years Please give a...

252

Joint Computer Science Department and Electrical and Computer Engineering Department Special Seminar Sponsored by ISTeC  

E-Print Network [OSTI]

Joint Computer Science Department and Electrical and Computer Engineering Security Professor of Computer Science (College of Science) Tue., Sept. 16 IEEE, ACM, NSA and NIST such as the IEEE Computer Society's Technical

253

Warrantless Wiretapping, FISA Reform, and the Lessons of Public Liberty: A Comment on Holmes' Jorde Lecture  

E-Print Network [OSTI]

it can be used to authorize the FBI to engage in electronichad revealed abuses by the NSA, FBI, and other governmentthe United States, while the FBI maintained watch lists of

Schwartz, Paul M.

2009-01-01T23:59:59.000Z

254

An Introduction Common Criteria  

E-Print Network [OSTI]

(Germany), NLNCSA (Netherlands), CESG (UK), NIST (USA) and NSA (USA). Contents 2 This document provides... Page 3 Page 4 Page 6 Page 8 Page 10 Page 12 Page 14 Page 16 Page 17 Page 18 #12;Common Criteria

Sandhu, Ravi

255

Quantum Algorithms for Element Distinctness Harry Buhrman  

E-Print Network [OSTI]

Quantum Algorithms for Element Distinctness Harry Buhrman Christoph Dšurr Mark Heiligman§ Peter, France. Email: durr@lri.fr. §NSA, Suite 6111, Fort George G. Meade, MD 20755, USA. Email: mheilig

Magniez, Frédéric

256

Quantum Algorithms for Element Distinctness Harry Buhrman  

E-Print Network [OSTI]

Quantum Algorithms for Element Distinctness Harry Buhrman£ Christoph Dšurr� Mark Heiligman� Peter, France. Email: durr@lri.fr. �NSA, Suite 6111, Fort George G. Meade, MD 20755, USA. Email: mheilig

de Wolf, Ronald

257

Magnetically multiplexed heating of single domain nanoparticles  

E-Print Network [OSTI]

Selective hysteretic heating of multiple collocated types of single domain magnetic nanoparticles (SDMNPs) by alternating magnetic fields (AMFs) may offer a useful tool for biomedical applications. The possibility of ...

Romero, G.

258

ARM-LBNL-NOAA Flask Sampler for Carbon Cycle Gases  

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

Data from ccg-flasks are sampled at the ARM SGP site and analyzed by the NOAA Earth System Research Laboratory (ESRL) as part of the NOAA Cooperative Global Air Sampling Network. Surface samples are collected from a 60m tower at the SGP Central Facility, usually once per week on one afternoon. The aircraft samples are collected approximately weekly from a chartered aircraft, and the collection flight path is centered over the tower where the surface samples are collected. Samples are collected by the ARM/LBNL Carbon Project. CO2 flask data contains measurements of CO2 concentration and CO2 stable isotope ratios (13CO2 and C18OO) from flasks collected at the SGP site. The flask samples are collected at 2m, 4m, 25m, and 60m along the 60m tower.

Torn, Margaret

259

The Aerosol Lidar Validation Experiment … ALIVE 1Schmid, B., 2Ferrare, R., 3Turner,D., 4Flynn, C., 5Cairns, B., 6Dominguez, R., 6Gore, W., 7Groff, D., 8Herman, B., 9Hovelman, B., 10Jefferson, A., 6Johnson, R., 5Knobelspiesse, K., 4Mendoza, A., 10Ogren, J., 4Petty, D., ?Russell, E., 6Russell, P., 4Roeder, L., 6Truong, N. 1BAER Institute, 2NASA Langley Res. Center, 3Univ. Of Wisconsin-Madison, 4Pacific Northwest Natl. Lab., 5Columbia Univ., 6NASA Ames Res. Center, 7ARM SGP, 8City Univ. of New York, 9Sky Research, Inc., 10NOAA CMDL  

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 MayAtmosphericNuclear SecurityTensile Strain Switched Ferromagnetism in Layered NbS2 and NbSe2 .2004 North Slope

260

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009  

E-Print Network [OSTI]

, are as follows: (a) reduce the operations and maintenance cost; (b) reduce the power plant cost; (c) choose, Stanford, California, February 9-11, 2009 SGP-TR-187 OPTIMIZATION OF THE ECONOMICS OF ELECTRIC POWER FROM) developed to date, numerical simulation of idealized EGS reservoirs, economic sensitivity analysis

Stanford University

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

PROCEEDINGS, Thirty-Fifth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 1-3, 2010  

E-Print Network [OSTI]

for the simulation of steam flow in a geothermal power plant network". The fluid movement is governed. In the pipeline network of geothermal power plant the steam flows from high to low pressure and heat flows from, Stanford, California, February 1-3, 2010 SGP-TR-188 GeoSteamNet: 2. STEAM FLOW SIMULATION IN A PIPELINE

Stanford University

262

PROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 -February 2, 2011  

E-Print Network [OSTI]

significantly increase the costs of geothermal power plants, rendering less the feasibility of utilizationPROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 - February 2, 2011 SGP-TR-191 - A METHODOLOGY FOR OPTIMAL GEOTHERMAL

Stanford University

263

PROCEEDINGS, Thirty-Fifth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 1-3, 2010  

E-Print Network [OSTI]

, Stanford, California, February 1-3, 2010 SGP-TR-188 2010 PRESENT STATUS OF GEOTHERMAL ENERGY IN TURKEY capacity in Turkey is about 100 MWe, while that of direct use installations is around 795 MWt. Direct use, solar, etc. Geological studies indicate that the most important geothermal systems of Turkey are located

Stanford University

264

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009  

E-Print Network [OSTI]

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009 SGP-TR-187 ASSESSMENT OF GEOTHERMAL POTENTIAL AT UNGARAN VOLCANO.Prof.Soedarto, Semarang, Indonesia. 2 Department of Earth Resources Engineering, Faculty of Engineering, Kyushu University

Stanford University

265

PROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 -February 2, 2011  

E-Print Network [OSTI]

, Stanford, California, January 31 - February 2, 2011 SGP-TR-191 DIRECTIONAL WELLS AT THE PAILAS GEOTHERMAL Costa Rica. Since 2009, the Costa Rican Electricity Company (ICE) has drilled 7 deep directional boreholes (in addition to the 9 existing vertical boreholes). The purpose of directional drilling has been

Stanford University

266

PROCEEDINGS, Thirty-Fifth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 1-3, 2010  

E-Print Network [OSTI]

, Stanford, California, February 1-3, 2010 SGP-TR-188 HYDRAULIC FRACTURING OF NATURALLY FRACTURED RESERVOIRS hydraulic fractures formed in naturally fractured crystalline rock masses. The propped fractures were formed on injection of thin or low viscosity fluids (e.g. water) at pressures that are below the fracture opening

Stanford University

267

PROCEEDINGS, Thirty-Fifth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 1-3, 2010  

E-Print Network [OSTI]

reservoirs where there exist coupled interactions among fluid and heat flow, and mechanical response, Stanford, California, February 1-3, 2010 SGP-TR-188 SIMULATION OF FLUID FLOW IN FRACTURED PORO and fracture pressure variation. This is accomplished by considering fluid flow and heat transport in a 2D

Stanford University

268

PROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 -February 2, 2011  

E-Print Network [OSTI]

, Stanford, California, January 31 - February 2, 2011 SGP-TR-191 DESIGNING THERMAL-PHYSICAL, POWER out at expeditious development rates and there are about a million power plants of this type-energy power plant, that supplies consumers with heat within constrained by them parameters, standard

Stanford University

269

PRESSURE TRANSIENT ANALYSIS FOR COMPOSITE SYSTEMS  

E-Print Network [OSTI]

SGP-TR-117 PRESSURE TRANSIENT ANALYSIS FOR COMPOSITE SYSTEMS Ani1 Kumar Ambastha October 1988 my graduate studies. #12;f #12;ABSTRACT A composite reservoir model is used to analyze well. A composite reservoir is made up of two or more regions. Each region has its own rock and fluid properties

Stanford University

270

PROCEEDINGS, Thirty-Fifth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 1-3, 2010  

E-Print Network [OSTI]

in waste Hot reservoir: earth Cold reservoir: atmosphere Electricity Energy in raw materials Maintenance Energy Restoration Energy Heat Engine Energy in waste Figure 1: Geothermal heat engine converting raw, Stanford, California, February 1-3, 2010 SGP-TR-188 ENERGY RETURN ON ENERGY INVESTMENT, AN IMPORTANT FIGURE

Stanford University

271

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 911, 2009  

E-Print Network [OSTI]

, Stanford, California, February 9­11, 2009 SGP-TR-187 HOT DRY ROCK GEOTHERMAL ENERGY: IMPORTANT LESSONS FROM FENTON HILL Donald W. Brown Los Alamos National Laboratory P.O. Box 1663, MS-D443 Los Alamos, New Mexico 87545 USA e-mail: dwb@lanl.gov ABSTRACT The concept of Hot Dry Rock (HDR) geothermal energy originated

Stanford University

272

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009  

E-Print Network [OSTI]

, Stanford, California, February 9-11, 2009 SGP-TR-187 FIELD EXPERIMENTS FOR STUDYING ON CO2 SEQUESTRATION to study CO2 sequestration in solid minerals by injecting CO2 dissolved water into a high temperature as carbonate minerals. INTRODUCTION For the global warming problems, it is considered to reduce CO2 emission

Stanford University

273

Experimental Study of Water Vapor Adsorption on Geothermal  

E-Print Network [OSTI]

Geothermal Program under Department of Energy Grant No. DE-FG07-90IDI2934,and by the Department of PetroleumSGP-TR-148 Experimental Study of Water Vapor Adsorption on Geothermal Reservoir Rocks Shubo Shang Engineering, Stanford University Stanford Geothermal Program Interdisciplinary Research in Engineering

Stanford University

274

PROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 -February 2, 2011  

E-Print Network [OSTI]

, Stanford, California, January 31 - February 2, 2011 SGP-TR-191 ARE GEOTHERMAL ENERGY RETURNS ON INVESTMENT as the investment energy for the next generation system. In the case of geothermal energy that means using on geothermal EROI of closing the loop is examined. The benefit of using geothermal energy, as compared

Stanford University

275

. Stanford Geothermal Program Interdisciplinary Research in  

E-Print Network [OSTI]

. Stanford Geothermal Program Interdisciplinary Research in Engineering and Earth Sciences STANFORD UNIVERSITY Stanford, California SGP-TR- 80 DEPLETION MODELING OF LIQUID DOMINATED GEOTHERMAL RESERVOIRS BY Gudmund 01sen June 1984 Financial support was provided through the Stanford Geothermal Program under

Stanford University

276

STANFORD GEOTHERMAL PROGRAM STANFORD UNIVERSITY  

E-Print Network [OSTI]

STANFORD GEOTHERMAL PROGRAM STANFORD UNIVERSITY STANFORD, CALIFORNIA 34105 Stanford Geothermal, California SGP-TR-72 A RESERVOIR ENGINEERING ANALYSIS OF A VAPOR-DOMINATED GEOTHERMAL FIELD BY John Forrest Dee June 1983 Financial support was provided through the Stanford Geothermal Program under Department

Stanford University

277

Stanford Geothermal Program Interdisciplinary Research in  

E-Print Network [OSTI]

was provided through the Stanford Geothermal Program under Department of Energy Contract No. DE-AT03-80SF11459Stanford Geothermal Program Interdisciplinary Research in Engineering and Earth Sciences STANFORTI UNIVERSITY Stanford, California SGP-TR-85 ANALYSIS OF THE STANFORD GEOTHERMAL RESERVOIR MODEL EXPERIMENTS

Stanford University

278

GEOTHERMAL ENERGY DEVELOPMENT Paul Kruger  

E-Print Network [OSTI]

SGP-TR 9 * GEOTHERMAL ENERGY DEVELOPMENT Paul Kruger C i v i l Engineering Department Stanford on an aggressive program t o develop its indigenous resources of geothermal energy. For more than a decade, geothermal energy has been heralded as one of the more promising forms of energy a l t e r n a t e t o o i l

Stanford University

279

STANFORD GEOTHERMAL PR0GRAh.I STANFORD UNIVERSITY  

E-Print Network [OSTI]

Department of Energy since 1975. research i n geothermal r e s e r v o i r engineering techniques t h a t w iSTANFORD GEOTHERMAL PR0GRAh.I STANFORD UNIVERSITY STANFORD,CALIFORNIA 94305 SGP-TR-5 1 GEOTHERMAL Implications of Adsorption and Formation Fluid Composition on Geothermal Reservoir Evaluation . . 40 TASK 5

Stanford University

280

Stanford Geothermal Program Interdisciplinary Research in  

E-Print Network [OSTI]

Geothermal Program under Department of Energy Contract No. DE-AT03-80SF11459 and by the DepartmentStanford Geothermal Program Interdisciplinary Research in Engineering and Earth Sciences STANFORD UNIVERSITY Stanford, California SGP-TR-81 TRACER TEST ANALYSIS OF THE KLAMATH FALLS GEOTHERMAL RESOURCE

Stanford University

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

STANFORD GEOTHERMAL PROGRAM STANFORD UNIVERSITY  

E-Print Network [OSTI]

of Proceedings that stand as one of the prominent literature sources in the field of geothermal energySTANFORD GEOTHERMAL PROGRAM STANFORD UNIVERSITY STANFORD, CALIFORNIA 94105 SGP-TR- 61 GEOTHERMAL APPENDIX A: PARTICIPANTS IN THE STANFORD GEOTHERMAL PROGRAM '81/'82 . 60 APPENDIX B: PAPERS PRESENTED

Stanford University

282

PROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 -February 2, 2011  

E-Print Network [OSTI]

attention in the last five decades. Geothermal heating and cooling are possible in zones having a normalPROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 - February 2, 2011 SGP-TR-191 SUSTAINABILITY OF GEOTHERMAL DOUBLETS

Stanford University

283

Southern Great Plains Newsletter  

SciTech Connect (OSTI)

This months issue contains the following articles: (1) Scientists convene at SGP site for complex convective cloud experiment; (2) VORTEX2 spins down; (3) Sunphotometer supports SPARTICUS (a Sun and Aureole Measurement imaging sunphotometer) campaign and satellite validation studies; and (4) Ceilometer represents first deployment of new ground-based instruments from Recovery Act.

J. Prell

2010-09-01T23:59:59.000Z

284

Emissions of air pollutants and greenhouse gases over1 Asian regions during 20002008: Regional Emission2  

E-Print Network [OSTI]

-3-9 Toranomon, Minato-ku, Tokyo, 105-0001, Japan}12 [5]{Ocean Policy Research Foundation, 3-4-10 Toranomon Singapore SGP Thailand THA Vietnam VNM Bangladesh OSA BGD Bhutan BTN India/Andhra Pradesh IND ANPR India/Bihar, Jharkhand BIHA India/Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura EHIM India/Gujarat GUJA

Meskhidze, Nicholas

285

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009  

E-Print Network [OSTI]

and its heat source. INTRODUCTION The Kizildere geothermal field, which is situated within the MTPROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009 SGP-TR-187 ELECTRICAL RESISTIVITY IMAGE OF THE KIZILDERE

Stanford University

286

PROCEEDINGS, Thirty-Fifth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 1-3, 2010  

E-Print Network [OSTI]

, Stanford, California, February 1-3, 2010 SGP-TR-188 FUTURE OF GEOTHERMAL ENERGY Subir K. Sanyal Geotherm This paper first describes the salient features of the various types of geothermal energy resources) geopressured systems, and (6) magma energy. Of these six types, only hydrothermal systems have been

Stanford University

287

PROCEEDINGS, Thirty-Sixth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, January 31 -February 2, 2011  

E-Print Network [OSTI]

, Stanford, California, January 31 - February 2, 2011 SGP-TR-191 A CONCEPTUAL MODEL FOR GEOTHERMAL ENERGY of the Caribbean islands have great potential for Geothermal Energy. These islands have been formed partially for geothermal energy. The only operating geothermal plant in the Caribbean is at Bouillante in Guadeloupe

Stanford University

288

Optimization of Injection Scheduling in  

E-Print Network [OSTI]

SGP-TR-I12 Optimization of Injection Scheduling in Geothermal Fields James Lovekin May 1987&injection optimization problem is broke$ into two subpmbkm:(1) choosing a configuration of injectorsfrom an existing set is defined as the fieldwide break- through lindex, B. Injection is optimized by choosing injection wells

Stanford University

289

Proof of concept of a zinc-silver battery for the extraction of energy from a concentration difference.  

E-Print Network [OSTI]

solution. The cyclic operation allows us to extract a surplus of energy, at the expense of the free energyProof of concept of a zinc-silver battery for the extraction of energy from a concentration power (SGP) is the production of renewable and clean power from naturally available water reservoirs

Carati, Andrea

290

Optical depth measurements by shadow-band radiometers and their uncertainties  

E-Print Network [OSTI]

and Atmospheric Administration Surface Radiation (SURFRAD) Network, and NASA Solar Irradiance Research Network important product of Sun-photometric measurements. [According to the American Meteoro- logical Society (AMS Measurement (ARM) Program [7]. This network con- sists of 21 instruments located at the SGP Central (CF

291

PROCEEDINGS, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 9-11, 2009  

E-Print Network [OSTI]

Geothermal wells producing acidic fluid have been abandoned because of high corrosion potential on casing. In the Miravalles geothermal field, Costa Rica, there are geothermal wells producing acidic fluid. For these wells, Stanford, California, February 9-11, 2009 SGP-TR-187 ANALYSIS OF NEUTRALIZATION REACTION IN A GEOTHERMAL

Stanford University

292

Collection and Evaluation of Flowing Pressure and Temperature  

E-Print Network [OSTI]

SGP-TR-100 Collection and Evaluation of Flowing Pressure and Temperature Data fkom Geothermal Wells profiles from ten geothermal wells around the world. It also provides calculated pressure and temperature and flow pattern transitions for the ten geothermal wells in our study is also presented. The analysis

Stanford University

293

Stanford Geothermal Program Stanford University  

E-Print Network [OSTI]

s Stanford Geothermal Program Stanford University Stanford, California RADON MEASUEMENTS I N GEOTHERMAL SYSTEMS ? d by * ** Alan K. Stoker and Paul Kruger SGP-TR-4 January 1975 :: raw at Lcs Alams S c i and water, o i l and n a t u r a l gas wells. with radon i n geothermal reservoirs. Its presence i n

Stanford University

294

DOWNHOLE ENTHALPY MEASUREMENT IN GEOTHERMAL  

E-Print Network [OSTI]

SGP-TR-186 DOWNHOLE ENTHALPY MEASUREMENT IN GEOTHERMAL WELLS WITH FIBER OPTICS Nilufer Atalay June 2008 Financial support was provided through the Stanford Geothermal Program under Idaho National University Stanford Geothermal Program Interdisciplinary Research in Engineering and Earth Sciences STANFORD

Stanford University

295

STANFORD GEOTHERMAL PROGRAM STANFORD UNIVERSITY  

E-Print Network [OSTI]

STANFORD GEOTHERMAL PROGRAM STANFORD UNIVERSITY STANFORD, CALIFORNIA 94305 SGP-TR-35 SECOND ANNUAL #12;INTRODUCTION The research e f f o r t of t h e Stanford Geothermal Program is focused on geothermal reservoir engineering. The major o b j e c t i v e of t h e protiram is t o develop techniques f o

Stanford University

296

PROCEEDINGS, Thirty-Eighth Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 11-13, 2013  

E-Print Network [OSTI]

-elastic deformation with damage evolution, and groundwater flow are solved using the Explicit Finite Difference Lagrangian Method for solid deformation and the Finite Element Method for fluid mass conservation. Rock, Stanford, California, February 11-13, 2013 SGP-TR-198 MODELING RESERVOIR STIMULATION INDUCED BY WELLBORE

Lyakhovsky, Vladimir

297

Constant-Pressure Measurement of Steam-  

E-Print Network [OSTI]

SGP-TR-169 Constant-Pressure Measurement of Steam- Water Relative Permeability Peter A. O by measuring in-situ steam saturation more directly. Mobile steam mass fraction was established by separate steam and water inlets or by correlating with previous results. The measured steam-water relative

Stanford University

298

FIA-12-0034- In the Matter of National Security Archive  

Broader source: Energy.gov [DOE]

The Office of Hearings and Appeals (OHA) issued a decision granting in part an appeal from a Freedom of Information Act (FOIA) determination issued by the Office of Information Resources (OIR). The National Security Archive (NSA) filed a FOIA request for documents relating to the Bonn Climate Change talks in August 2010. OIR conducted a search and located one responsive document. NSA challenged the adequacy of the search and the OIR agreed to search the retired records at the Washington National Records Center. Consequently, we remanded this matter to OIR so that a search of those records could be performed.

299

Atmospheric Radiation Measurement (ARM) Data from Point Reyes, California for the Marine Stratus, Radiation, Aerosol, and Drizzle (MASRAD) Project  

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

Point Reyes National Seashore, on the California coast north of San Francisco, was the location of the first deployment of the DOE's Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The ARM Program collaborated with the U.S. Office of Naval Research and DOE's Aerosol Science Program in the Marine Stratus, Radiation, Aerosol, and Drizzle (MASRAD) project. Their objectives were to collect data from cloud/aerosol interactions and to improve understanding of cloud organization that is often associated with patches of drizzle. Between March and September 2005, the AMF and at least two research aircraft were used to collect data.

300

Joining of parts via magnetic heating of metal aluminum powders  

DOE Patents [OSTI]

A method of joining at least two parts includes steps of dispersing a joining material comprising a multi-phase magnetic metal-aluminum powder at an interface between the at least two parts to be joined and applying an alternating magnetic field (AMF). The AMF has a magnetic field strength and frequency suitable for inducing magnetic hysteresis losses in the metal-aluminum powder and is applied for a period that raises temperature of the metal-aluminum powder to an exothermic transformation temperature. At the exothermic transformation temperature, the metal-aluminum powder melts and resolidifies as a metal aluminide solid having a non-magnetic configuration.

Baker, Ian

2013-05-21T23:59:59.000Z

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

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.

302

ARM - AOS Aerosol Properties 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 May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |November 2011AstudiesRingFacilitiesAMF1FacilitiesAMF3

303

ARM - ARM Data Integrator  

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 |November 2011AstudiesRingFacilitiesAMF1FacilitiesAMF3FormsARM

304

THE ODD MOMENTS OF RANKS AND CRANKS GEORGE E. ANDREWS, SONG HENG CHAN, AND BYUNGCHAN KIM  

E-Print Network [OSTI]

THE ODD MOMENTS OF RANKS AND CRANKS GEORGE E. ANDREWS, SONG HENG CHAN, AND BYUNGCHAN KIM Abstract by National Security Agency, NSA grant award 101015. Song Heng Chan was partially supported by Nanyang of Education, Science and Technology (NRF2011-0009199). 1 #12;2 GEORGE E. ANDREWS, SONG HENG CHAN

305

FOREIGN POLICY MAGAZINE JANUARY FEBRUARY 2002 Smarter Intelligence  

E-Print Network [OSTI]

.S. counterterrorism intelligence? Not more spies nor the power to assassinate terrorist leaders, say two former CIA Intelligence Agency (CIA), envisioned the enemy to be states such as the Soviet Union and also recognized for the former, and the intelligence community--comprising the CIA, the National Security Agency (NSA

Deutch, John

306

NPS Program Highlights Dr. Leonard A. Ferrari  

E-Print Network [OSTI]

Ed · Masters' Degrees ­ Science & Technology (S&T) focused · Electrical Engineering (EE) ­ Energy Conversation, a 3-year long cross- Agency series on energy in Washington DC 6 #12;Energy Program Update ­ NSA provides space and resources ­ Enormous potential for research collaboration · Relationship

307

Testimony before the Senate Committee on Commerce, Science, and Transportation  

E-Print Network [OSTI]

as an advisor to Federal law enforcement and defense agencies, in- cluding the FBI, the Air Force and the NSA. I at Purdue University. I also have courtesy ap- pointments in the departments of Electrical and Computer compromised at banks, utilities, hospitals, law en- forcement agencies, every branch of the armed forces

Ginzel, Matthew

308

Appl. Comput. Harmon. Anal. 20 (2006) 345356 www.elsevier.com/locate/acha  

E-Print Network [OSTI]

without phase Radu Balan a , Pete Casazza b, , Dan Edidin b a Siemens Corporate Research, 755 College was supported by NSA MDA 904-03-1-0040. * Corresponding author. E-mail addresses: radu.balan@siemens.com (R precisely, the linear transformation from the initial Hilbert space to the space of coefficients obtained

Maryland at College Park, University of

309

Exogenous application of gibberellins to hasten yaupon seed germination for surface mine reclamation  

E-Print Network [OSTI]

) (T-1) (S-1)(T-1) a e + ntca s a e + nsco t s e + nco st GA concentration/ GA type (C) CXS Error T (C-1) T(C-1) (S-1) (N-1)STC a e + nsa c(t) 0 e + ns sc(t) o e TOTAL NSTC-1 ') The following abbreviations were used: Number of Sample...

Whatley, Christopher Marc

1988-01-01T23:59:59.000Z

310

MAJOR TO CAREER GUIDE B.A. Mathematics  

E-Print Network [OSTI]

prices, or as fine detail of an abstract geometric figure. With today's powerful computers, mathematics oil reservoirs under the surface of the earth, to make and break secret codes Value of B://www.nsf.gov/ National Security Agency http://www.nsa.gov/ Mathworld, http://mathworld.wolfram.com/ SIAM- History

Walker, Lawrence R.

311

MAJOR TO CAREER GUIDE B.S. Mathematics  

E-Print Network [OSTI]

prices, or as fine detail of an abstract geometric figure. With today's powerful computers, mathematics oil reservoirs under the surface of the earth, to make and break secret codes Value of B://www.nsf.gov/ National Security Agency http://www.nsa.gov/ Mathworld, http://mathworld.wolfram.com/ SIAM- History

Walker, Lawrence R.

312

PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY  

E-Print Network [OSTI]

)0000-0 EXPECTED DISCREPANCY FOR ZEROS OF RANDOM ALGEBRAIC POLYNOMIALS IGOR E. PRITSKER AND ALAN A. SOLA support from NSA under grant H98230-12-1-0227; Sola acknowl- edges support from the EPSRC under grant EP/103372X/1. c XXXX American Mathematical Society 1 #12;2 PRITSKER AND SOLA coefficients of Pn

Grimmett, Geoffrey

313

PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY  

E-Print Network [OSTI]

)0000-0 EXPECTED DISCREPANCY FOR ZEROS OF RANDOM ALGEBRAIC POLYNOMIALS IGOR E. PRITSKER AND ALAN A. SOLA support from NSA under grant H98230-12-1-0227; Sola acknowl- edges support from the EPSRC under grant EP/103372X/1. cXXXX American Mathematical Society 1 #12;2 PRITSKER AND SOLA coefficients of Pn

Pritsker, Igor

314

Proposal to Establish the Center for Extreme Data Management Analysis and Visualization  

E-Print Network [OSTI]

new power and cooling systems, such as the ones being built for the new National Security Agency (NSA acquired with high- resolution sensors from aircrafts, robots, satellites, increasingly high, and image processing. Once extreme data is securely housed and efficiently managed, the real work begins

Capecchi, Mario R.

315

www.newphytologist.org 413 Blackwell Publishing, Ltd.  

E-Print Network [OSTI]

endophyte Epichloë glyceriae has a positive effect on clonal growth of its host (Pan & Clay, 2002; 2003 in hosts infected by E. glyceriae may function as one mechanism by which endophytic fungi could increase, AMF and leaf- inhabiting fungal endophytes are widely distributed in some ecologically important

Alvarez, Nadir

316

A New Approximate Matrix Factorization for Implicit Time Integration in Air Pollution  

E-Print Network [OSTI]

A New Approximate Matrix Factorization for Implicit Time Integration in Air Pollution Modeling + M on the one hand and its e#ciency on the other hand. For example, in air pollution modeling, AMF has been factorization, large sparse linear systems, sti# ODEs, method of lines, Rosenbrock methods, air pollution

Botchev, Mike

317

Ecology, 93(7), 2012, pp. 15501559 2012 by the Ecological Society of America  

E-Print Network [OSTI]

alter metal sequestration and AMF effects on plant growth in soils polluted with heavy metals SYDNEY I-dependency; Deschampsia flexuosa; heavy metal pollution; microbial wash; non-mycorrhizal soil microbes; Palmerton a gradient of heavy metal contamination originating at the site of zinc smelters that operated for a century

Silver, Whendee

318

Global Policy Research Institute External Advisory Council  

E-Print Network [OSTI]

, and global health. Additionally, Dr. Blumenthal serves as Senior Policy and Medical Advisor to amf. She is the former U.S. Assistant Surgeon General, Senior Global Health Advisor, and Founding Deputy for Agricultural Trade and Food Assistance, focusing primarily on Farm Bill issues. Mr. Conner received a Bachelor

Ginzel, Matthew

319

CLIMATOLOGY OF VERTICAL AIR MOTION DURING RAINFALL IN NIAMEY, NIGER AND BLACK FOREST, GERMANY USING AN  

E-Print Network [OSTI]

CLIMATOLOGY OF VERTICAL AIR MOTION DURING RAINFALL IN NIAMEY, NIGER AND BLACK FOREST, GERMANY USING in Niamey, Niger and eight months in Germany's Black Forest. The AMF includes a vertically pointing 95 GHz of the orographically influenced precipitation in Germany's mountains. __________ NOTICE: This manuscript has been

320

Revised for: Correspondence to: Plant and Soil Gregory K. Eaton  

E-Print Network [OSTI]

While agricultural research has traditionally focused on average environmental conditions, environmental and decrease tissue concentrations of N and P. Successful application of AMF to sustainable agriculture are usually classified as mutualistic symbioses; the fungus aids the plant in absorbing nutrients (especially

Ayres, Matthew.P.

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

AFFILIATIONS: MILLER--Brookhaven National Laboratory, Up-ton, New York; SLINGO--Environmental Systems Science Centre,  

E-Print Network [OSTI]

con- tinuously for periods of 6­12 months and includes a core suite of active remote sensors of radiation, latent heat, sensible heat, and carbon dioxide at the surface. The centerpieces of the AMF are a collection of active and passive remote sensors (Table 1) including a vertically pointing 95-GHz Doppler

322

Ecology 2006 94, 905914  

E-Print Network [OSTI]

Ecological Society Blackwell Publishing Ltd Arbuscular mycorrhizal fungi and water table affect wetland plant in experimental wetland plant communities, where the dominant plant species are non-mycorrhizal and subordinate table (un-saturated) treatment, above-ground plant biomass increased in the presence of AMF relative

Pringle, Anne

323

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

SciTech Connect (OSTI)

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.

Xie, Shaocheng; McCoy, Renata; Zhang, Yunyan

2012-10-25T23:59:59.000Z

324

The 2dF Galaxy Redshift Survey: Final Data Release  

E-Print Network [OSTI]

The 2dF Galaxy Redshift Survey (2dFGRS) has obtained spectra for 245591 sources, mainly galaxies, brighter than a nominal extinction-corrected magnitude limit of b_J=19.45. Reliable redshifts were measured for 221414 galaxies. The galaxies are selected from the extended APM Galaxy Survey and cover an area of approximately 1500 square degrees in three regions: an NGP strip, an SGP strip and random fields scattered around the SGP strip. This paper describes the 2dFGRS final data release of 30 June 2003 and complements Colless et al. (2001), which described the survey and the initial 100k data release. The 2dFGRS database and full documentation are available on the WWW at http://www.mso.anu.edu.au/2dFGRS/

Matthew Colless; Bruce A. Peterson; Carole Jackson; John A. Peacock; Shaun Cole; Peder Norberg; Ivan K. Baldry; Carlton M. Baugh; Joss Bland-Hawthorn; Terry Bridges; Russell Cannon; Chris Collins; Warrick Couch; Nicholas Cross; Gavin Dalton; Roberto De Propris; Simon P. Driver; George Efstathiou; Richard S. Ellis; Carlos S. Frenk; Karl Glazebrook; Ofer Lahav; Ian Lewis; Stuart Lumsden; Steve Maddox; Darren Madgwick; Will Sutherland; Keith Taylor

2003-06-27T23:59:59.000Z

325

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

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

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.

Xie, Shaocheng; McCoy, Renata; Zhang, Yunyan

326

Atmospheric State, Cloud Microphysics and Radiative Flux  

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

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.

Mace, Gerald

327

Effects of implantation of Synovex (progesterone-estradiol) and castration in Holstein and Brown Swiss bull calves for beef production  

E-Print Network [OSTI]

"ra@-HE'LL 5~?. Cn?. X. . ~n?? @no Tech? yy 2~- 69? QS, TelK~ H+ K?~mezg, B, snQ G~, Q H LNA, ENeee yR ~ el eaaeeaeLm cad oC eeseosCevms p:ey~ oa migs getLe ~ CQKCSSS QQQSUECIIKXCI QS SCCQX8o ASSCo Do ETC ~ AQSZ4 Eeslhi, 4sGP~ Ki ~ +Lese's, J, lLM7+ Xke...

Vergara, Francisco de Patino

1967-01-01T23:59:59.000Z

328

Solar and Infrared Radiation Station (SIRS) Handbook  

SciTech Connect (OSTI)

The Solar Infrared Radiation Station (SIRS) provides continuous measurements of broadband shortwave (solar) and longwave (atmospheric or infrared) irradiances for downwelling and upwelling components. The following six irradiance measurements are collected from a network of stations to help determine the total radiative flux exchange within the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Climate Research Facility: • Direct normal shortwave (solar beam) • Diffuse horizontal shortwave (sky) • Global horizontal shortwave (total hemispheric) • Upwelling shortwave (reflected) • Downwelling longwave (atmospheric infrared) • Upwelling longwave (surface infrared)

Stoffel, T

2005-07-01T23:59:59.000Z

329

STORMVEX: The Storm Peak Lab Cloud Property Validation Experiment Science and Operations Plan  

SciTech Connect (OSTI)

During the Storm Peak Lab Cloud Property Validation Experiment (STORMVEX), a substantial correlative data set of remote sensing observations and direct in situ measurements from fixed and airborne platforms will be created in a winter season, mountainous environment. This will be accomplished by combining mountaintop observations at Storm Peak Laboratory and the airborne National Science Foundation-supported Colorado Airborne Multi-Phase Cloud Study campaign with collocated measurements from the second ARM Mobile Facility (AMF2). We describe in this document the operational plans and motivating science for this experiment, which includes deployment of AMF2 to Steamboat Springs, Colorado. The intensive STORMVEX field phase will begin nominally on 1 November 2010 and extend to approximately early April 2011.

Mace, J; Matrosov, S; Shupe, M; Lawson, P; Hallar, G; McCubbin, I; Marchand, R; Orr, B; Coulter, R; Sedlacek, A; Avallone, L; Long, C

2010-09-29T23:59:59.000Z

330

Atmospheric Radiation Measurement (ARM) Data from Shouxian, China for the Study of Aerosol Indirect Effects in China  

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

In a complex ARM Mobile Facility (AMF) deployment, monitoring data was collected at four locations in China during 2008. The various sites are located in regions with different climate regimes and with high aerosol loadings of different optical, physical, and chemical properties. Measurements obtained at all the AMF sites during the 8-month deployment in China will help scientists to validate satellite-based findings, understand the mechanisms of the aerosol indirect effects in the region, and examine the roles of aerosols in affecting regional climate and atmospheric circulation, with a special focus on the impact of the East Asian monsoon system. As with other collections from the ARM Mobile Facility, the datasets are available from the ARM Archive. The ARM Archive physically resides at the Oak Ridge National Laboratory.

331

MAGIC: Marine ARM GPCI Investigation of Clouds  

SciTech Connect (OSTI)

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.

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

332

A new simulation approach and its integration with perturbation analysis in tandem queueing systems  

E-Print Network [OSTI]

. (August 1992) Ki- Young Jeong, B. E. (Industrial Engr. ), Korea University, Korea Chair of Advisory Committee: Dr. Don T, Phillips This research presents a new simulation approach (NSA) to a single-server tandem queueing system (TQS) and empirically... resource, a single name can be assigned to several different resource types with each resource having its own capacity. 2. 1. 2. Components and structures of an EDSA The following components and structures of an EDSA are well explained by Law P. aw...

Jeong, Ki-Young

1992-01-01T23:59:59.000Z

333

Faculty Office Hours Fall 2014 Aberle, James  

E-Print Network [OSTI]

Faculty Office Hours Fall 2014 Aberle, James GWC 326 01:30 PM 02:45 PMM T W F to Tuesday is through:30 AMR to Coleman, James BYENG 450 08:45 AM 09:45 AMT R to By Appointment Cotter, Jeff GWC 424 03:15 PM:00 AM 09:30 AMF to Or at a time arranged via e-mail to reisslein@asu.edu Rodriguez, Armando GWC 352 10

Zhang, Yanchao

334

Near infrared optical lymphography for cancer diagnostics  

E-Print Network [OSTI]

amplitude of intensity-modulated light [a.u.] IDC mean intensity of modulated light [a.u.] k non-radiative relaxation rate [s-1] MS mixed signal n refractive index x English symbols continued: N number of samples in Fourier transform PS... quantum yield ? photon fluence rate [W/cm2] ? radiative relaxation rate [sec-1] ? wavelength of light [nm] ? a absorption coefficient [cm-1] ? amf absorption coefficient due to fluorophores at fluorescent emission wavelength [cm-1] ? axf...

Houston, Jessica Perea

2007-04-25T23:59:59.000Z

335

The production and characterization of protective monoclonal antibodies against Fasciola hepatica and Schistosoma mansoni  

E-Print Network [OSTI]

fulfillment of the requirements for the degree MASTER OF SCIENCE August 1988 Major Subject: Veterinary Microbiology THE PRODUCTION AND CHARACTERIZATION OF PROTECTIVE MONOCLONAL ANTIBODIES AGAINST FASCIOLA HEPATICA AND SCHISTOSOMA MANSONI A Thesis... 1 A t t d Ag t P . ' 1 AMf t d Schistosoma mansoni (August 1988) Carolyn Sue Hicks, B. A. Anderson College Chair of Advisory Committee: Dr. Barbara Doughty Monoclonal antibodies that showed specificity for the tg tl f f dltf. ~A* t' p d df...

Hicks, Carolyn Sue

2012-06-07T23:59:59.000Z

336

The design of an intrusion security system using digital processing for alarm indication  

E-Print Network [OSTI]

has been noise spikes in the diode. These spikes can easily cause a false alarm which is difficult to trace since it results from a sporadic, elec- tronic malfunction. General Electric, Amperex, and other concerned companies have made a great... is the requirement of multiple triggering of this one threshold. AMF Inc. , Alexandria, Virginia, has recently introduced an intricate signal processor with diode transistor logic and transistor transistor logic integrated circuits to handle intru- sion signals...

Holyoak, Joel Nelson

2012-06-07T23:59:59.000Z

337

Objective assessment of image quality (OAIQ) in fluorescence-enhanced optical imaging  

E-Print Network [OSTI]

.7 SNR Hot computed from simulated measurements of light intensity (filled circles) and phase (open circles) in hundred percent lumpy backgrounds of endogenous ( axi ? , ami ? , sx ? , and sm ? ) as well as exogenous ( axf ? , and amf ? ) optical..., fluorophores do not have an intrinsic half-life as do radiopharmaceuticals. This greatly enhances the duration of time for imaging, which is limited in the case of nuclear imaging, and results in higher target- to-background ratios (TBR). Despite...

Sahu, Amit K.

2009-05-15T23:59:59.000Z

338

Microwave and Millimeter-Wave Radiometric Studies of Temperature, Water Vapor and Clouds  

SciTech Connect (OSTI)

The importance of accurate measurements of column amounts of water vapor and cloud liquid has been well documented by scientists within the Atmospheric Radiation Measurement (ARM) Program. At the North Slope of Alaska (NSA), both microwave radiometers (MWR) and the MWRProfiler (MWRP), been used operationally by ARM for passive retrievals of the quantities: Precipitable Water Vapor (PWV) and Liquid Water Path (LWP). However, it has been convincingly shown that these instruments are inadequate to measure low amounts of PWV and LWP. In the case of water vapor, this is especially important during the Arctic winter, when PWV is frequently less than 2 mm. For low amounts of LWP (< 50 g/m{sup 2}), the MWR and MWRP retrievals have an accuracy that is also not acceptable. To address some of these needs, in March-April 2004, NOAA and ARM conducted the NSA Arctic Winter Radiometric Experiment - Water Vapor Intensive Operational Period at the ARM NSA/Adjacent Arctic Ocean (NSA/AAO) site. After this experiment, the radiometer group at NOAA moved to the Center for Environmental Technology (CET) of the Department of Electrical and Computer Engineering of the University of Colorado at Boulder. During this 2004 experiment, a total of 220 radiosondes were launched, and radiometric data from 22.235 to 380 GHz were obtained. Primary instruments included the ARM MWR and MWRP, a Global Positioning System (GPS), as well as the CET Ground-based Scanning Radiometer (GSR). We have analyzed data from these instruments to answer several questions of importance to ARM, including: (a) techniques for improved water vapor measurements; (b) improved calibration techniques during cloudy conditions; (c) the spectral response of radiometers to a variety of conditions: clear, liquid, ice, and mixed phase clouds; and (d) forward modeling of microwave and millimeter wave brightness temperatures from 22 to 380 GHz. Many of these results have been published in the open literature. During the third year of this contract, we participated in another ARM-sponsored experiment at the NSA during February-March 2007. This experiment is called the Radiative Heating in Underexplored Bands Campaign (RHUBC) and the GSR was operated successfully for the duration of the campaign. One of the principal goals of the experiment was to provide retrievals of water vapor during PWV amounts less than 2 mm and to compare GSR data with ARM radiometers and radiosondes. A secondary goal was to compare the radiometric response of the microwave and millimeter wavelength radiometers to water and ice clouds. In this final report, we will include the separate progress reports for each of the three years of the project and follow with a section on major accomplishments of the project.

Westwater, Edgeworth

2011-05-06T23:59:59.000Z

339

ARM CLASIC ER2 CRS/EDOP  

SciTech Connect (OSTI)

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.

Gerald Heymsfield

2010-12-20T23:59:59.000Z

340

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

SciTech Connect (OSTI)

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

Widener, K; Bharadwaj, N

2012-10-29T23:59:59.000Z

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Diurnal Rhythms Result in Significant Changes in the Cellular Protein  

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 Depth7-1D: Vegetation Proposed Newcatalyst phasesDataTranslocationDiurnal Cycle of Convection at the ARM SGP

342

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 LandSystemCentral FacilityInstruments SGP

343

ARM Participation  

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 SGP Program recently

344

ARM People Search  

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 SGP Program

345

ARM Poster 2007.ai  

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 SGP Program20 40 60 80

346

ARM Program Data Quality Inspection and Assessment Activities: A Streamlined Approach  

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 SGP Program20 40 60

347

ARM STM Plenary: CS Report  

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 SGP Program20 40 60ARM8

348

ARM Scanning Radar  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: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 SGP Program20 40

349

ARM Science Meeting  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: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 SGP Program20 40Science

350

ARM Science Team Meeting Scheduled The 11th Annual ARM Science  

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 SGP Program20

351

ARM Site Atmospheric State Best Estimates for AIRS Validation  

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 SGP Program20Site

352

ARM TR-006  

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 SGP Program20Site7 The

353

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 SGP Program20Site7 The3

354

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 SGP Program20Site7

355

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 SGP Program20Site75

356

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 SGP Program20Site756

357

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 SGP Program20Site7567

358

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 SGP Program20Site75677

359

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 SGP Program20Site756778

360

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 SGP

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

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 SGP10 Atmospheric

362

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 SGP10 Atmospheric1 ACRF

363

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 SGP10 Atmospheric1

364

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 SGP10 Atmospheric13

365

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 SGP10 Atmospheric134

366

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 SGP10

367

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 SGP10 Atmospheric

368

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 SGP10 Atmospheric4 ACRF

369

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 SGP10 Atmospheric4

370

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 SGP10 Atmospheric46

371

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 SGP10 Atmospheric461

372

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 SGP10 Atmospheric46107

373

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 SGP10 Atmospheric461079

374

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 SGP10

375

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 Atmospheric

376

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

377

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

378

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

379

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

380

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

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

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

382

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

383

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

384

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

385

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

386

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

387

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

388

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

389

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

390

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

391

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

392

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

393

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

394

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

395

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

396

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

397

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

398

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

399

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

400

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

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

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

402

ARM TR-008  

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

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403

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 SGP101449SC-ARM/TR-0331

404

SHE 2015  

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

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405

Research Highlight  

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 MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared at 278,ValidatingPollution + StormObservations Guide Low-CloudSGP

406

1  

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

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407

1  

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

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408

Infrared Mapping Helps Optimize Catalytic Reactions  

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 Depth7-1D: Vegetation ProposedUsingFunInfrared Land Surface Emissivity in the Vicinity of the ARM SGP

409

CLASIC Measurement Platforms  

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 DocumentationP-Series to someone6Energy, science, andAnalysis1 SolelyCHANGE INDOE -CID4 SGP

410

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

SciTech Connect (OSTI)

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.

Albrecht, Bruce,

2013-07-12T23:59:59.000Z

411

Characterization of Vertical Velocity and Drop Size Distribution Parameters in Widespread Precipitation at ARM Facilities  

SciTech Connect (OSTI)

Extended, high-resolution measurements of vertical air motion and median volume drop diameter D0 in widespread precipitation from three diverse Atmospheric Radiation Measurement Program (ARM) locations [Lamont, Oklahoma, Southern Great Plains site (SGP); Niamey, Niger; and Black Forest, Germany] are presented. The analysis indicates a weak (0-10 cm{sup -1}) downward air motion beneath the melting layer for all three regions, a magnitude that is to within the typical uncertainty of the retrieval methods. On average, the hourly estimated standard deviation of the vertical air motion is 0.25 m s{sup -1} with no pronounced vertical structure. Profiles of D0 vary according to region and rainfall rate. The standard deviation of 1-min-averaged D0 profiles for isolated rainfall rate intervals is 0.3-0.4 mm. Additional insights into the form of the raindrop size distribution are provided using available dual-frequency Doppler velocity observations at SGP. The analysis suggests that gamma functions better explain paired velocity observations and radar retrievals for the Oklahoma dataset. This study will be useful in assessing uncertainties introduced in the measurement of precipitation parameters from ground-based and spaceborne remote sensors that are due to small-scale variability.

Giangrande S. E.; Luke, E. P.; Kollias, P.

2012-02-01T23:59:59.000Z

412

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

SciTech Connect (OSTI)

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.

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

2011-07-21T23:59:59.000Z

413

Utilizing CLASIC observations and multiscale models to study the impact of improved Land surface representation on modeling cloud- convection  

SciTech Connect (OSTI)

The CLASIC experiment was conducted over the US southern great plains (SGP) in June 2007 with an objective to lead an enhanced understanding of the cumulus convection particularly as it relates to land surface conditions. This project was design to help assist with understanding the overall improvement of land atmosphere convection initiation representation of which is important for global and regional models. The study helped address one of the critical documented deficiency in the models central to the ARM objectives for cumulus convection initiation and particularly under summer time conditions. This project was guided by the scientific question building on the CLASIC theme questions: What is the effect of improved land surface representation on the ability of coupled models to simulate cumulus and convection initiation? The focus was on the US Southern Great Plains region. Since the CLASIC period was anomalously wet the strategy has been to use other periods and domains to develop the comparative assessment for the CLASIC data period, and to understand the mechanisms of the anomalous wet conditions on the tropical systems and convection over land. The data periods include the IHOP 2002 field experiment that was over roughly same domain as the CLASIC in the SGP, and some of the DOE funded Ameriflux datasets.

Niyogi, Devdutta S. [Purdue

2013-06-07T23:59:59.000Z

414

Final Report for High Latitude Climate Modeling: ARM Takes Us Beyond Case Studies  

SciTech Connect (OSTI)

The main thrust of this project was to devise a method by which the majority of North Slope of Alaska (NSA) meteorological and radiometric data, collected on a daily basis, could be used to evaluate and improve global climate model (GCM) simulations and their parameterizations, particularly for cloud microphysics. Although the standard ARM Program sensors for a less complete suite of instruments for cloud and aerosol studies than the instruments on an intensive field program such as the 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC), the advantage they offer lies in the long time base and large volume of data that covers a wide range of meteorological and climatological conditions. The challenge has been devising a method to interpret the NSA data in a practical way, so that a wide variety of meteorological conditions in all seasons can be examined with climate models. If successful, climate modelers would have a robust alternative to the usual “case study” approach (i.e., from intensive field programs only) for testing and evaluating their parameterizations’ performance. Understanding climate change on regional scales requires a broad scientific consideration of anthropogenic influences that goes beyond greenhouse gas emissions to also include aerosol-induced changes in cloud properties. For instance, it is now clear that on small scales, human-induced aerosol plumes can exert microclimatic radiative and hydrologic forcing that rivals that of greenhouse gas–forced warming. This project has made significant scientific progress by investigating what causes successive versions of climate models continue to exhibit errors in cloud amount, cloud microphysical and radiative properties, precipitation, and radiation balance, as compared with observations and, in particular, in Arctic regions. To find out what is going wrong, we have tested the models' cloud representation over the full range of meteorological conditions found in the Arctic using the ARM North Slope of Alaska (NSA) data.

Russell, Lynn M [Scripps/UCSD; Lubin, Dan [Scripps/UCSD

2013-06-18T23:59:59.000Z

415

Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals  

SciTech Connect (OSTI)

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

Shupe, Matthew

2013-05-22T23:59:59.000Z

416

Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals  

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

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

Shupe, Matthew

417

Fluorescence method for enzyme analysis which couples aromatic amines with aromatic aldehydes  

DOE Patents [OSTI]

Analysis of proteinases is accomplished using conventional amino acid containing aromatic amine substrates. Aromatic amines such as 4-methoxy-2-naphthylamine (4M2NA), 2-naphthylamine, aminoisophthalic acid dimethyl ester, p-nitroaniline, 4-methoxy-1-aminofluorene and coumarin derivatives resulting from enzymatic hydrolysis of the substrate couples with aromatic aldehydes such as 5-nitrosalicylaldehyde (5-NSA), benzaldehyde and p-nitrobenzaldehyde to produce Schiff-base complexes which are water insoluble. Certain Schiff-base complexes produce a shift from blue to orange-red (visible) fluorescence. Such complexes are useful in the assay of enzymes. No Drawings

Smith, R.E.; Dolbeare, F.A.

1980-10-21T23:59:59.000Z

418

Fluorescence method for enzyme analysis which couples aromatic amines with aromatic aldehydes  

DOE Patents [OSTI]

Analysis of proteinases is accomplished using conventional amino acid containing aromatic amine substrates. Aromatic amines such as 4-methoxy-2-naphthylamine (4M2NA), 2-naphthylamine, aminoisophthalic acid dimethyl ester, p-nitroaniline, 4-methoxy-1-aminofluorene and coumarin derivatives resulting from enzymatic hydrolysis of the substrate couples with aromatic aldehydes such as 5-nitrosalicylaldehyde (5-NSA), benzaldehyde and p-nitrobenzaldehyde to produce Schiff-base complexes which are water insoluble. Certain Schiff-base complexes produce a shift from blue to orange-red (visible) fluorescence. Such complexes are useful in the assay of enzymes.

Smith, Robert E. [557 Escondido Cir., Livermore, CA 94550; Dolbeare, Frank A. [5178 Diane La., Livermore, CA 94550

1980-10-21T23:59:59.000Z

419

Use of Aeronet Aerosol Retrievals to Calculate Clear-Sky Irradiance at the Surface  

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 MayAtmosphericNuclear SecurityTensile Strain Switched Ferromagnetism inS-4500II Field Emission SEM withSecurityUranium(VI)ARM/NSA Data

420

Use of Arginase and/or Threonine Deaminase in Plant Protection against  

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 MayAtmosphericNuclear SecurityTensile Strain Switched Ferromagnetism inS-4500II Field Emission SEM withSecurityUranium(VI)ARM/NSA

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

ARM - Site Instruments  

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

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422

PowerPoint Presentation  

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

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423

ARM - Field Campaign - NSF-Sponsored Aerosonde Project  

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

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: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 ARMgovCampaignsNSA Scanning Radar

424

ARM - Field Campaign - Nauru99 Campaign  

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 ARMgovCampaignsNSA Scanning

425

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon  

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

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426

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon  

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 ARMgovCampaignsNSA Scanning- Hi-Vol

427

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon:  

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 ARMgovCampaignsNSA Scanning- Hi-VolAerosol

428

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon:  

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 ARMgovCampaignsNSA Scanning-

429

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon:  

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 ARMgovCampaignsNSA Scanning-CCN Activity

430

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon:  

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 ARMgovCampaignsNSA Scanning-CCN

431

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon:  

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 ARMgovCampaignsNSA Scanning-CCNHarvard

432

ARM - Field Campaign - Observations and Modeling of the Green Ocean Amazon:  

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 ARMgovCampaignsNSA

433

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

SciTech Connect (OSTI)

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

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

2011-04-11T23:59:59.000Z

434

ARM - GVAX News  

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435

AMG Benchmark  

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 |November 2011Astudies Colorado Steamboat Deployment AMF HomeAMG

436

AMIE (ARM MJO Investigation Experiment):  

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

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437

ANI-testbed-ESCC-Feb2011.pptx  

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438

Microsoft PowerPoint - Lamb_et_al_Norfolk_Poster  

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439

Sandia National Laboratories: AMI  

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440

Sandia National Laboratories: AMII  

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Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Sandia National Laboratories: AML  

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442

Sandia National Laboratories: AMPED  

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443

Sandia National Laboratories: ANL  

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444

Sandia National Laboratories: AQWA  

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445

Sandia National Laboratories: ARDEC  

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446

Sandia National Laboratories: AREVA  

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447

Sandia National Laboratories: ARL  

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448

Sandia National Laboratories: ARM  

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449

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

SciTech Connect (OSTI)

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

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

2006-07-10T23:59:59.000Z

450

Oxidation and Volatilization from Tungsten Brush High Heat Flux Armor During High Temperature Steam Exposure  

SciTech Connect (OSTI)

Tungsten brush accommodates thermal stresses and high heat flux in fusion reactor components such as plasma facing surfaces or armor. However, inherently higher surface areas are introduced with the brush design. We have tested a specific design of tungsten brush in steam between 500 and 1100°C. Hydrogen generation and tungsten volatilization rates were determined to address fusion safety issues. The brush prepared from 3.2-mm diameter welding rods had a packing density of 85 percent. We found that both hydrogen generation and tungsten volatilization from brush, fixtured to represent a unit within a larger component, were less than projections based upon the total integrated surface area (TSA). Steam access and the escape of hydrogen and volatile oxide from void spaces within the brush are restricted compared to specimens with more direct diffusion pathways to the test environment. Hydrogen generation rates from restrained specimens based on normal surface area (NSA) remain about five times higher than rates based on total surface areas from specimens with direct steam access. Volatilization rates from restrained specimens based upon normal surface area (NSA) were only 50 percent higher than our historic cumulative maximum flux plot (CMFP) for tungsten. This study has shown that hydrogen generation and tungsten volatilization from brush do not scale according to predictions with previously determined rates, but in fact, with higher packing density could approach those from flat surfaces.

Smolik, Galen Richard; Pawelko, Robert James; Anderl, Robert Andrew; Petti, David Andrew

2000-05-01T23:59:59.000Z

451

Atmospheric Radiation Measurement (ARM) Data from Black Forest Germany for the Convective and Orographically Induced Precipitation Study (COPS)  

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

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 maintains four major, permanent sites for data collection and deploys the ARM Mobile Facility (AMF) to other sites as determined. In 2007 the AMF operated in the Black Forest region of Germany as part of the Convective and Orographically Induced Precipitation Study (COPS). Scientists studied rainfall resulting from atmospheric uplift (convection) in mountainous terrain, otherwise known as orographic precipitation. This was part of a six -year duration of the German Quantitative Precipitation Forecasting (QPF) Program. COPS was endorsed as a Research and Development Project by the World Weather Research Program. This program was established by the World Meteorological Organization to develop improved and cost-effective forecasting techniques, with an emphasis on high-impact weather. A large collection of data plots based on data streams from specific instruments used at Black Forest are available via a link from ARM's Black Forest site information page. Users will be requested to create a password, but the plots and the data files in the ARM Archive are free for viewing and downloading.

452

Geothermal reservoir engineering research at Stanford University. First annual report, October 1, 1980-September 30, 1981  

SciTech Connect (OSTI)

The work on energy extraction experiments concerns the efficiency with which the in-place heat and fluids can be produced. The work on noncondensable gas reservoir engineering covers both the completed and continuing work in these two interrelated research areas: radon emanation from the rock matrix of geothermal reservoirs, and radon and ammonia variations with time and space over geothermal reservoirs. Cooperative research programs with Italy and Mexico are described. The bench-scale experiments and well test analysis section covers both experimental and theoretical studies. The small core model continues to be used for the study of temperature effects on absolute permeability. The unconsolidated sand study was completed at the beginning of this contract period. The Appendices describe some of the Stanford Geothermal program activities that results in interactions with the geothermal community. These occur in the form of SGP Technical Reports, presentations at technical meetings and publications in the open literature.

Brigham, W.E.; Horne, R.N.; Kruger, P.; Miller, F.G.; Ramey, H.J. Jr.

1981-09-01T23:59:59.000Z

453

Satellite Measurement of Upper Tropospheric Water Vapor: Development and Applications and Applications for the ARM Program  

SciTech Connect (OSTI)

Upper tropospheric humidity (UTH) measurements from the 6.7 micron channel on GOES (8, 9, 12) and GMS-5 satellites were employed to develop a near real-time UTH product that is now available from the ARM External Data Center (XDC). The UTH product is available in either gridded format (2.0 x 2.0 lat-lon resolution), full-disk pixel resolution, or individual pixel resolution for both the SGP and TWP sites. This product provides the basis for the instrument intercomparison and validation activities (Section 0.2), diurnal analysis and model evaluation (0.3), and cloud lifecycle studies (0.5); and is also an important component of the research proposed here. Full details regarding the retrieval algorithm for the ARM sites can be found in Soden et al. (2004a) and references therein.

Brian J. Soden

2005-01-11T23:59:59.000Z

454

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

SciTech Connect (OSTI)

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.

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

2003-03-06T23:59:59.000Z

455

Raman lidar/AERI PBL Height Product  

SciTech Connect (OSTI)

Planetary Boundary Layer (PBL) heights have been computed using potential temperature profiles derived from Raman lidar and AERI measurements. Raman lidar measurements of the rotational Raman scattering from nitrogen and oxygen are used to derive vertical profiles of potential temperature. AERI measurements of downwelling radiance are used in a physical retrieval approach (Smith et al. 1999, Feltz et al. 1998) to derive profiles of temperature and water vapor. The Raman lidar and AERI potential temperature profiles are merged to create a single potential temperature profile for computing PBL heights. PBL heights were derived from these merged potential temperature profiles using a modified Heffter (1980) technique that was tailored to the SGP site (Della Monache et al., 2004). PBL heights were computed on an hourly basis for the period January 1, 2009 through December 31, 2011. These heights are provided as meters above ground level.

Ferrare, Richard

2012-12-14T23:59:59.000Z

456

Radiosondes Corrected for Inaccuracy in RH Measurements  

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

Corrections for inaccuracy in Vaisala radiosonde RH measurements have been applied to ARM SGP radiosonde soundings. The magnitude of the corrections can vary considerably between soundings. The radiosonde measurement accuracy, and therefore the correction magnitude, is a function of atmospheric conditions, mainly T, RH, and dRH/dt (humidity gradient). The corrections are also very sensitive to the RH sensor type, and there are 3 Vaisala sensor types represented in this dataset (RS80-H, RS90, and RS92). Depending on the sensor type and the radiosonde production date, one or more of the following three corrections were applied to the RH data: Temperature-Dependence correction (TD), Contamination-Dry Bias correction (C), Time Lag correction (TL). The estimated absolute accuracy of NIGHTTIME corrected and uncorrected Vaisala RH measurements, as determined by comparison to simultaneous reference-quality measurements from Holger Voemel's (CU/CIRES) cryogenic frostpoint hygrometer (CFH), is given by Miloshevich et al. (2006).

Miloshevich, Larry

457

Thermal drawdown analysis of the Hijiori HDR 90-day circulation test  

SciTech Connect (OSTI)

The Hijiori 90-day circulation test is unique in the development of HDR technology in that it was the first (and thus far the only) multiproduction well test run for a sufficient production period to obtain observed cooldown curves at multiple production horizons in the stimulated reservoir volume. The experimental data have been analyzed by the SGP 1-D linear heat sweep model to examine the extent of thermal cooldown in this relatively small, multi-well, multi-zone reservoir. Although changes in production flow were carried out in specific wells at specific times during the 90 days of circulation, matching of the observed cooldown curves in conjunction with the structural and temperature logging data allows estimation of the reservoir volume and the mean fracture spacing between rock blocks for heat extraction during the 90-day test.

Kruger, Paul; Yamaguchi, Tsutomu

1993-01-28T23:59:59.000Z

458

Comparison of thermal cooldown estimates in the Russkie Komarovtsy petrogeothermal reservoir  

SciTech Connect (OSTI)

A comparison of several models to estimate the rate of thermal cooldown in artificial circulation geothermal reservoirs was made for the Russkie Komarovtsy fracture-stimulated reservoir, which will be located near the town of Uzhgorod in the Zakarpate region of the Ukraine SSR. The economic viability of this moderate-temperature resource depends on sustained flow above the minimum abandonment temperature for a period sufficient to recover investment and operating costs. The rate of heat extraction for the required flowrate depends on the fracture distribution in the reservoir. Results of the SGP 1-D Heat Sweep model are compared to approximate analytical and numerical models developed at the Leningrad Mining Institute, based on a common set of initial conditions for the Russkie Komarovtsy reservoir. The comparison shows that all of the models yielded reasonably similar thermal decline estimates with a satisfactory lifetime of about 25 years to abandonment temperature.

Kruger, Paul; Dyadkin, Yuri; Gendler, Semon; Artemieva, Elena; Smirnova, Nina

1991-01-01T23:59:59.000Z

459

Raman lidar/AERI PBL Height Product  

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

Planetary Boundary Layer (PBL) heights have been computed using potential temperature profiles derived from Raman lidar and AERI measurements. Raman lidar measurements of the rotational Raman scattering from nitrogen and oxygen are used to derive vertical profiles of potential temperature. AERI measurements of downwelling radiance are used in a physical retrieval approach (Smith et al. 1999, Feltz et al. 1998) to derive profiles of temperature and water vapor. The Raman lidar and AERI potential temperature profiles are merged to create a single potential temperature profile for computing PBL heights. PBL heights were derived from these merged potential temperature profiles using a modified Heffter (1980) technique that was tailored to the SGP site (Della Monache et al., 2004). PBL heights were computed on an hourly basis for the period January 1, 2009 through December 31, 2011. These heights are provided as meters above ground level.

Ferrare, Richard

460

Evaluation of the Multi-scale Modeling Framework Using Data from the Atmospheric Radiation Measurement Program  

SciTech Connect (OSTI)

One of the goals of the Atmospheric Radiation Measurement (ARM) program is to provide long-term observations for evaluating and improving cloud and radiation treatment in global climate models. Unfortunately, the traditional parametric approach of diagnosing cloud and radiation properties for gridcells that are tens to hundreds kilometers across from large-scale model fields is not well suited for comparison with time series of ground based observations at selected locations. A recently emerging approach called a multi-scale modeling framework (MMF) has shown promise to bridge the scale gap. The MMF consists of a two-dimensional or small three-dimensional cloud resolving model (CRM) embedded into each grid column of the Community Atmospheric Model (CAM), thereby computing cloud properties at a scale that is more consistent with observations. We present a comparison of data from two ARM sites, one at the Southern Great Plains (SGP) in Oklahoma and one at Nauru Island in the Tropical Western Pacific (TWP) region, with output from both the CAM and MMF. 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 the MMF as well as the CAM run with traditional or standard cloud and radiation treatment. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are statistically analyzed. For the TWP site, nearly all parameters of frequency distributions of these variables from the MMF run are shown to be more consistent with observation than those from the CAM run. This change is attributed to the improved representation of convective clouds in the MMF compared to the conventional climate model. For the SGP, the MMF shows little to no improvement in predicting the same quantities. Possible causes of this lack of improvement are discussed.

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

2006-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "amf nsa sgp" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Evaluation of the Multi-Scale Modeling Framework using Data from the Atmospheric Radiation Measurement Program  

SciTech Connect (OSTI)

One of the goals of the Atmospheric Radiation Measurement (ARM) program was to provide long-term observations for evaluation of cloud and radiation treatment in global climate models. Unfortunately, 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 the multi-scale modeling framework (MMF) has shown promise to bridge the gap. MMF consists of a two-dimensional cloud system resolving model (CSRM) embedded into each CAM grid column of the Community Atmospheric Model (CAM), 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. In this presentation, we will present a comparison of data from two ARM sites, one at the Southern Great Plains (SGP) in Oklahoma and one at Nauru island in the Tropical Western Pacific (TWP) region, with output from both CAM and MMF. 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 MMF as well as CAM run with traditional or standard cloud and radiation treatment. Time series of cloud fraction, precipitation intensity, and downwelling solar radiation flux at the surface are statistically analyzed. For the TWP site, nearly all parameters of frequency distributions of these variables from MMF run are shown to be more consistent with observation than those from CAM run. For the SGP, the improvements are marginal.

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

2004-07-01T23:59:59.000Z

462

Statistics of Voids in the 2dF Galaxy Redshift Survey  

E-Print Network [OSTI]

We present a statistical analysis of voids in the 2dF galaxy redshift survey (2dFGRS). In order to detect the voids, we have developed two robust algorithms. We define voids as non-overlapping maximal spheres empty of halos or galaxies with mass or luminosity above a given one. We search for voids in cosmological $N$-Body simulations to test the performance of our void finders. We obtain and analyze the void statistics for several volume-limited samples for the North Galactic Strip (NGP) and the South Galactic Strip (SGP) constructed from the 2dFGRS full data release. We find that the results obtained from the NGP and the SGP are statistically compatible. From the results of several statistical tests we conclude that voids are essentially uncorrelated, with at most a mild anticorrelation and that there is a dependence of the void number density on redshift at least at the 99.5% confidence level. We develop a technique to correct the distortion caused by the fact that we use the redshift as the radial coordinate. We calibrate this technique with mock catalogues and find that the correction might be of some relevance to carry out accurate inferences from void statistics. We study the statistics of the galaxies inside nine nearby voids. We find that galaxies in voids are not randomly distributed: they form structures like filaments. We also obtain the galaxy number density profile in voids. This profile follow a similar but steeper trend to that follow by halos in voids.

Santiago G. Patiri; Juan Betancort-Rijo; Francisco Prada; Anatoly Klypin; Stefan Gottlöber

2006-10-27T23:59:59.000Z

463

Nuclear Reactors and Technology; (USA)  

SciTech Connect (OSTI)

Nuclear Reactors and Technology (NRT) announces on a monthly basis the current worldwide information available from the open literature on nuclear reactors and technology, including all aspects of power reactors, components and accessories, fuel elements, control systems, and materials. This publication contains the abstracts of DOE reports, journal articles, conference papers, patents, theses, and monographs added to the Energy Science and Technology Database (EDB) during the past month. Also included are US information obtained through acquisition programs or interagency agreements and international information obtained through the International Energy Agency's Energy Technology Data Exchange or government-to-government agreements. The digests in NRT and other citations to information on nuclear reactors back to 1948 are available for online searching and retrieval on EDB and Nuclear Science Abstracts (NSA) database. Current information, added daily to EDB, is available to DOE and its contractors through the DOE integrated Technical Information System. Customized profiles can be developed to provide current information to meet each user's needs.

Cason, D.L.; Hicks, S.C. (eds.)

1991-01-01T23:59:59.000Z

464

Bonneville - Hood River Vegetation Management Environmental Assessment  

SciTech Connect (OSTI)

To maintain the reliability of its electrical system, BPA, in cooperation with the U.S. Forest Service, needs to expand the range of vegetation management options used to clear unwanted vegetation on about 20 miles of BPA transmission line right-of-way between Bonneville Dam and Hood River; Oregon, within the Columbia Gorge National Scenic Area (NSA). We propose to continue controlling undesirable vegetation using a program of Integrated Vegetation Management (IVM) which includes manual, biological and chemical treatment methods. BPA has prepared an Environmental Assessment (EA) (DOE/EA-1257) evaluating the proposed project. Based on the analysis in the EA, BPA has determined that the proposed action is not a major Federal action significantly affecting the quality of the human environment, within the meaning of the National Environmental Policy Act (NEPA) of 1969. Therefore, the preparation of an Environmental Impact Statement (EIS) is not required and BPA is issuing this FONSI.

N /A

1998-08-01T23:59:59.000Z

465

Light-Water Breeder Reactor  

DOE Patents [OSTI]

Described is a light-water-moderated and -cooled nuclear breeder reactor of the seed-blanket type characterized by core modules comprising loosely packed blanket zones enriched with fissile fuel and axial zoning in the seed and blanket regions within each core module. Reactivity control over lifetime is achieved by axial displacement of movable seed zones without the use of poison rods in the embodiment illustrated. The seed is further characterized by a hydrogen-to-uranium-233 atom ratio in the range 10 to 200 and a uranium-233-to-thorium-232 atom ratio ranging from 0.012 to 0.200. The seed occupies from 10 to 35 percent of the core volume in the form of one or more individual islands or annuli. (NSA 26: 55130)

Beaudoin, B. R.; Cohen, J. D.; Jones, D. H.; Marier, Jr, L. J.; Raab, H. F.

1972-06-20T23:59:59.000Z

466

The multi-filter rotating shadowband radiometer (MFRSR) - precision infrared radiometer (PIR) platform in Fairbanks: Scientific objectives  

SciTech Connect (OSTI)

The multi-filter rotating shadowband radiometer (MFRSR) and precision infrared radiometer (PIR) have been employed at the Geophysical Institute in Fairbanks to check their performance under arctic conditions. Drawing on the experience of the previous measurements in the Arctic, the PIR was equipped with a ventilator to prevent frost and moisture build-up. We adopted the Solar Infrared Observing Sytem (SIROS) concept from the Southern Great Plains Cloud and Radiation Testbed (CART) to allow implementation of the same data processing software for a set of radiation and meteorological instruments. To validate the level of performance of the whole SIROS prior to its incorporation into the North Slope of Alaska (NSA) Cloud and Radiation Testbed Site instrumental suite for flux radiatin measurements, the comparison between measurements and model predictions will be undertaken to assess the MFRSR-PIR Arctic data quality.

Stamnes, K.; Leontieva, E. [Univ. of Alaska, Fairbanks (United States)

1996-04-01T23:59:59.000Z

467

Atmospheric Radiation Measurment (ARM) Data from the Ganges Valley, India for the Ganges Valley Aerosol Experiment (GVAX)  

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

In 2011 and 2012, the Ganges Valley Aerosol Experiment (GVAX) began in the Ganges Valley region of India. The objective was to obtain measurements of clouds, precipitation, and complex aerosols to study their impact on cloud formation and monsoon activity in the region. During the Indian Ocean Experiment (INDOEX) field studies, aerosols from the Ganges Valley region were shown to affect cloud formation and monsoon activity over the Indian Ocean. The complex field study used the ARM Mobile Facility (AMF) to measure radiative, cloud, convection, and aerosol characteristics over the mainland. The resulting data set captured pre-monsoon to post-monsoon conditions to establish a comprehensive baseline for advancements in the study of the effects of atmospheric conditions of the Ganges Valley.

468

ULTRA SECURE HIGH RELIABILITY WIRELESS RADIATION MONITOR  

SciTech Connect (OSTI)

Radiation monitoring in nuclear facilities is essential to safe operation of the equipment as well as protecting personnel. In specific, typical air monitoring of radioactive gases or particulate involves complex systems of valves, pumps, piping and electronics. The challenge is to measure a representative sample in areas that are radioactively contaminated. Running cables and piping to these locations is very expensive due to the containment requirements. Penetration into and out of an airborne or containment area is complex and costly. The process rooms are built with thick rebar-enforced concrete walls with glove box containment chambers inside. Figure 1 shows high temperature radiation resistance cabling entering the top of a typical glove box. In some case, the entire processing area must be contained in a 'hot cell' where the only access into the chamber is via manipulators. An example is shown in Figure 2. A short range wireless network provides an ideal communication link for transmitting the data from the radiation sensor to a 'clean area', or area absent of any radiation fields or radioactive contamination. Radiation monitoring systems that protect personnel and equipment must meet stringent codes and standards due to the consequences of failure. At first glance a wired system would seem more desirable. Concerns with wireless communication include latency, jamming, spoofing, man in the middle attacks, and hacking. The Department of Energy's Savannah River National Laboratory (SRNL) has developed a prototype wireless radiation air monitoring system that address many of the concerns with wireless and allows quick deployment in radiation and contamination areas. It is stand alone and only requires a standard 120 VAC, 60 Hz power source. It is designed to be mounted or portable. The wireless link uses a National Security Agency (NSA) Suite B compliant wireless network from Fortress Technologies that is considered robust enough to be used for classified data transmission in place of NSA Type 1 devices.

Cordaro, J.; Shull, D.; Farrar, M.; Reeves, G.

2011-08-03T23:59:59.000Z

469

Atmospheric Radiation Measurement (ARM) Data from Manacapuru, Brazil for the Green Ocean Amazon (GOAMAZON) Field Campaign  

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

The Amazon rain forest in Brazil is the largest broadleaf forest in the world, covering 7 million square kilometers of the Amazon Basin in South America. It represents over half of the planet’s remaining rain forests, and comprises the most biodiverse tract of tropical rain forest on the planet. Due to the sheer size of the Amazon rain forest, the area has a strong impact on the climate in the Southern Hemisphere. To understand the intricacies of the natural state of the Amazon rain forest, the Green Ocean Amazon, or GOAMAZON, field campaign is a two-year scientific collaboration among U.S. and Brazilian research organizations. They are conducting a variety of different experiments with dozens of measurement tools, using both ground and aerial instrumentation, including the ARM Aerial Facility's G-1 aircraft. For more information on the holistic view of the campaign, see the Department of Energy’s GOAMAZON website. As a critical component of GOAMAZON, the ARM Mobile Facility (AMF) will obtain measurements near Manacapuru, south of Manaus, Brazil, from January to December 2014. The city of Manaus, with a population of 3 million, uses high-sulfur oil as their primary source of electricity. The AMF site is situated to measure the atmospheric extremes of a pristine atmosphere and the nearby cities’ pollution plume, as it regularly intersects with the site. Along with other instrument systems located at the Manacapuru site, this deployment will enable scientists to study how aerosol and cloud life cycles are influenced by pollutant outflow from a tropical megacity.

470

Final Report - From Measurements to Models: Cross-Comparison of Measured and Simulated Behavioral States of the Atmosphere  

SciTech Connect (OSTI)

The ARM sites and the ARM Mobile Facility (AMF) were constructed to make measurements of the atmosphere and radiation system in order to quantify deficiencies in the simulation of clouds within models and to make improvements in those models. While the measurement infrastructure of ARM is well-developed and a model parameterization testbed capability has been established, additional effort is needed to develop statistical techniques which permit the comparison of simulation output from atmospheric models with actual measurements. Our project establishes a new methodology for objectively comparing ARM measurements to the outputs of leading global climate models and reanalysis data. The quantitative basis for this comparison is provided by a statistical procedure which establishes an exhaustive set of mutually-exclusive, recurring states of the atmosphere from sets of multivariate atmospheric and cloud conditions, and then classifies multivariate measurements or simulation outputs into those states. Whether measurements and models classify the atmosphere into the same states at specific locations through time provides an unequivocal comparison result. Times and locations in both geographic and state space of model-measurement agreement and disagreement will suggest directions for the collection of additional measurements at existing sites, provide insight into the global representativeness of the current ARM sites (suggesting locations and times for use of the AMF), and provide a basis for improvement of models. Two different analyses were conducted: One, using the Parallel Climate Model, focused on an IPCC climate change scenario and clusters that characterize long-term changes in the hydrologic cycle. The other, using the GISS Model E GCM and the ARM Active Remotely Sensed Cloud Layers product, explored current climate cloud regimes in the Tropical West Pacific.

Del Genio, Anthony D; Hoffman, Forrest M; Hargrove, Jr, William W

2007-10-22T23:59:59.000Z

471

Temporal Variability of Aerosol Properties during TCAP: Impact on Radiative Forcing  

SciTech Connect (OSTI)

Ground-based remote sensing and in situ observations of aerosol microphysical and optical properties have been collected during summertime (June-August, 2012) as part of the Two-Column Aerosol Project (TCAP; http://campaign.arm.gov/tcap/), which was supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program (http://www.arm.gov/). The overall goal of the TCAP field campaign is to study the evolution of optical and microphysical properties of atmospheric aerosol transported from North America to the Atlantic and their impact on the radiation energy budget. During TCAP, the ground-based ARM Mobile Facility (AMF) was deployed on Cape Cod, an arm-shaped peninsula situated on the easternmost portion of Massachusetts (along the east coast of the United States) and that is generally downwind of large metropolitan areas. The AMF site was equipped with numerous instruments for sampling aerosol, cloud and radiative properties, including a Multi-Filter Rotating Shadowband Radiometer (MFRSR), a Scanning Mobility Particle Sizer (SMPS), an Aerodynamic Particle Sizer (APS), and a three-wavelength nephelometer. In this study we present an analysis of diurnal and day-to-day variability of the column and near-surface aerosol properties obtained from remote sensing (MFRSR data) and ground-based in situ measurements (SMPS, APS, and nephelometer data). In particular, we show that the observed diurnal variability of the MFRSR aerosol optical depth is strong and comparable with that obtained previously from the AERONET climatology in Mexico City, which has a larger aerosol loading. Moreover, we illustrate how the variability of aerosol properties impacts the direct aerosol radiative forcing at different time scales.

Kassianov, Evgueni I.; Barnard, James C.; Pekour, Mikhail S.; Berg, Larry K.; Fast, Jerome D.; Michalsky, Joseph J.; Lantz, K.; Hodges, G. B.

2013-11-01T23:59:59.000Z

472

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

SciTech Connect (OSTI)

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 GCMsù�� 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.

Liu, Guosheng

2013-03-15T23:59:59.000Z

473

Regional CO2 and latent heat surface fluxes in the Southern Great Plains: Measurements, modeling, and scaling  

SciTech Connect (OSTI)

Characterizing net ecosystem exchanges (NEE) of CO{sub 2} and sensible and latent heat fluxes in heterogeneous landscapes is difficult, yet critical given expected changes in climate and land use. We report here a measurement and modeling study designed to improve our understanding of surface to atmosphere gas exchanges under very heterogeneous land cover in the mostly agricultural U.S. Southern Great Plains (SGP). We combined three years of site-level, eddy covariance measurements in several of the dominant land cover types with regional-scale climate data from the distributed Mesonet stations and Next Generation Weather Radar precipitation measurements to calibrate a land surface model of trace gas and energy exchanges (isotope-enabled land surface model (ISOLSM)). Yearly variations in vegetation cover distributions were estimated from Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index and compared to regional and subregional vegetation cover type estimates from the U.S. Department of Agriculture census. We first applied ISOLSM at a 250 m spatial scale to account for vegetation cover type and leaf area variations that occur on hundred meter scales. Because of computational constraints, we developed a subsampling scheme within 10 km 'macrocells' to perform these high-resolution simulations. We estimate that the Atmospheric Radiation Measurement Climate Research Facility SGP region net CO{sub 2} exchange with the local atmosphere was -240, -340, and -270 gC m{sup -2} yr{sup -1} (positive toward the atmosphere) in 2003, 2004, and 2005, respectively, with large seasonal variations. We also performed simulations using two scaling approaches at resolutions of 10, 30, 60, and 90 km. The scaling approach applied in current land surface models led to regional NEE biases of up to 50 and 20% in weekly and annual estimates, respectively. An important factor in causing these biases was the complex leaf area index (LAI) distribution within cover types. Biases in predicted weekly average regional latent heat fluxes were smaller than for NEE, but larger than for either ecosystem respiration or assimilation alone. However, spatial and diurnal variations of hundreds of W m{sup -2} in latent heat fluxes were common. We conclude that, in this heterogeneous system, characterizing vegetation cover type and LAI at the scale of spatial variation are necessary for accurate estimates of bottom-up, regional NEE and surface energy fluxes.

Riley, W. J.; Biraud, S.C.; Torn, M.S.; Fischer, M.L.; Billesbach, D.P.; Berry, J.A.

2009-08-15T23:59:59.000Z

474

Climate Science for a Sustainable Energy Future Atmospheric Radiation Measurement Best Estimate (CSSEFARMBE)  

SciTech Connect (OSTI)

The Climate Science for a Sustainable Energy Future (CSSEF) project is working to improve the representation of the hydrological cycle in global climate models, critical information necessary for decision-makers to respond appropriately to predictions of future climate. In order to accomplish this objective, CSSEF is building testbeds to implement uncertainty quantification (UQ) techniques to objectively calibrate and diagnose climate model parameterizations and predictions with respect to local, process-scale observations. In order to quantify the agreement between models and observations accurately, uncertainty estimates on these observations are needed. The DOE Atmospheric Radiation Measurement (ARM) program takes atmospheric and climate related measurements at three permanent locations worldwide. The ARM VAP called the ARM Best Estimate (ARMBE) [Xie et al., 2010] collects a subset of ARM observations, performs quality control checks, averages them to one hour temporal resolution, and puts them in a standard format for ease of use by climate modelers. ARMBE has been widely used by the climate modeling community as a summary product of many of the ARM observations. However, the ARMBE product does not include uncertainty estimates on the data values. Thus, to meet the objectives of the CSSEF project and enable better use of this data with UQ techniques, we created the CSSEFARMBE data set. Only a subset of the variables contained in ARMBE is included in CSSEFARMBE. Currently only surface meteorological observations are included, though this may be expanded to include other variables in the future. The CSSEFARMBE VAP is produced for all extended facilities at the ARM Southern Great Plains (SGP) site that contain surface meteorological equipment. This extension of the ARMBE data set to multiple facilities at SGP allows for better comparison between model grid boxes and the ARM point observations. In the future, CSSEFARMBE may also be created for other ARM sites. As each site has slightly different instrumentation, this will require additional development to understand the uncertainty characterization associated with instrumentation at those sites. The uncertainty assignment process is implemented into the ARM program’s new Integrated Software Development Environment (ISDE) so that many of the key steps can be used in the future to screen data based on ARM Data Quality Reports (DQRs), propagate uncertainties when transforming data from one time scale into another, and convert names and units into NetCDF Climate and Forecast (CF) standards. These processes are described in more detail in the following sections.

Riihimaki, Laura D.; Gaustad, Krista L.; McFarlane, Sally A.

2012-09-28T23:59:59.000Z

475

Site Scientific Mission Plan for the Southern Great Plains CART site: January--June 1994  

SciTech Connect (OSTI)

The Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site is designed to help satisfy the data needs of the Atmospheric Radiation Measurement (ARM) Program Science Team. This document defines the scientific priorities for site activities during the six months beginning on January 1, 1994, and also looks forward in lesser detail to subsequent six-month periods. The primary purpose of this Site Scientific Mission Plan is to provide guidance for the development of plans for site operations. It also provides information on current plans to the ARM Functional Teams (Management Team, Experiment Support Team, Operations Team, Data Management Team, Instrument Team, and Campaign Team), and it serves to disseminate the plans more generally within the ARM Program and among the Science Team. This document includes a description of the site`s operational status and the primary envisaged site activities, together with information concerning approved and proposed Intensive Observation Periods. Amendments will be prepared and distributed whenever the content changes by more than 30% within a six-month period. The primary users of this document are the site operator, the site scientist, the Science Team through the ARM Program Science Director, the ARM Program Experiment Center, and the aforementioned ARM Program Functional Teams. This plan is a living document that will be updated and reissued every six months as the observational facilities are developed, tested, and augmented and as priorities are adjusted in response to developments in scientific planning and understanding.

Schneider, J.M.; Lamb, P.J. [Univ. of Oklahoma, Norman, OK (United States). Cooperative Inst. for Mesoscale Meteorological Studies; Sisterson, D.L. [Argonne National Lab., IL (United States). Environmental Research Div.

1993-12-01T23:59:59.000Z

476

Site scientific mission plan for the southern Great Plains CART site, January--June 1998  

SciTech Connect (OSTI)

The Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site is designed to help satisfy the data needs of the Atmospheric Radiation Measurement (ARM) Program Science Team. The primary purpose of this site scientific mission plan is to provide guidance for the development of plans for site operations. It also provides information on current plans to the ARM functional teams (Management Team, Data and Science Integration Team, Operations Team, and Instrument Team) and serves to disseminate the plans more generally within the ARM Program and among the members of the Science Team. This document includes a description of the operational status of the site and the primary site activities envisioned, together with information concerning approved and proposed intensive observation periods (IOPs). The primary users of this document are the Site operator, the Site Scientist Team (SST), the Science Team through the ARM Program science director, the ARM Program Experiment Center, and the aforementioned ARM Program functional teams. This plan is a living document that is updated and reissued every six months as the observational facilities are developed, tested, and augmented and as priorities are adjusted in response to developments in scientific planning and understanding.

Peppler, R.A.; Lamb, P.J. [Univ. of Oklahoma, Norman, OK (United States). Cooperative Inst. for Mesoscale Meteorological Studies; Sisterson, D.L. [Argonne National Lab., IL (United States). Environmental Research Div.

1998-01-01T23:59:59.000Z

477

Atmospheric Radiation Measurement Program facilities newsletter, January 2000  

SciTech Connect (OSTI)

The subject of this newsletter is the ARM unmanned aerospace vehicle program. The ARM Program's focus is on climate research, specifically research related to solar radiation and its interaction with clouds. The SGP CART site contains highly sophisticated surface instrumentation, but even these instruments cannot gather some crucial climate data from high in the atmosphere. The Department of Energy and the Department of Defense joined together to use a high-tech, high-altitude, long-endurance class of unmanned aircraft known as the unmanned aerospace vehicle (UAV). A UAV is a small, lightweight airplane that is controlled remotely from the ground. A pilot sits in a ground-based cockpit and flies the aircraft as if he were actually on board. The UAV can also fly completely on its own through the use of preprogrammed computer flight routines. The ARM UAV is fitted with payload instruments developed to make highly accurate measurements of atmospheric flux, radiance, and clouds. Using a UAV is beneficial to climate research in many ways. The UAV puts the instrumentation within the environment being studied and gives scientists direct measurements, in contrast to indirect measurements from satellites orbiting high above Earth. The data collected by UAVs can be used to verify and calibrate measurements and calculated values from satellites, therefore making satellite data more useful and valuable to researchers.

Sisterson, D.L.

2000-02-16T23:59:59.000Z

478

Site scientific mission plan for the southern Great Plain CART site July-December 1997.  

SciTech Connect (OSTI)

The Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site is designed to help satisfy the data needs of the Atmospheric Radiation Measurement (ARM) Program Science Team. This document defines the scientific priorities for site activities during the six months beginning on July 1, 1997, and looks forward in lesser detail to subsequent six-month periods. The primary purpose of this Site Scientific Mission Plan is to provide guidance for the development of plans for site operations. It also provides information on current plans to the ARM functional teams (Management Team, Data and Science Integration Team [DSIT], Operations Team, Instrument Team [IT], and Campaign Team) and serves to disseminate the plans more generally within the ARM Program and among the members of the Science Team. This document includes a description of the operational status of the site and the primary site activities envisioned, together with information concerning approved and proposed intensive observation periods (IOPs). The primary users of this document are the site operator, the Site Scientist Team (SST), the Science Team through the ARM Program science director, the ARM Program Experiment Center, and the aforementioned ARM Program functional teams. This plan is a living document that is updated and reissued every six months as the observational facilities are developed, tested, and augmented and as priorities are adjusted in response to developments in scientific planning and understanding.

Lamb, P.J.; Peppler, R.A.; Sisterson, D.L.

1997-08-28T23:59:59.000Z

479

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

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

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.

Williams, Christopher; Jensen, Mike

480

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)]

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.

Williams, Christopher; Jensen, Mike

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481

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

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

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.

Williams, Christopher; Jensen, Mike

482

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)]

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.

Williams, Christopher; Jensen, Mike

483

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)]

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.

Williams, Christopher

484

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)

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.

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

2007-09-30T23:59:59.000Z

485

Final Report for ARM Project Measuring 4-D Water Vapor Fields with GPS  

SciTech Connect (OSTI)

Water vapor is a primary element in the Earth’s climate system. Atmospheric water vapor is central to cloud processes, radiation transfer, and the hydrological cycle. Using funding from Department of Energy (DOE) grant DE-FG03-02ER63327, the University Corporation for Atmospheric Research (UCAR) developed new observational techniques to measure atmospheric water vapor and applied these techniques to measure four dimensional water vapor fields throughout the United States Southern Great Plains region. This report summarizes the development of a new observation from ground based Global Positioning System (GPS) stations called Slant Water Vapor (SW) and it’s utilization in retrieving four dimensional water vapor fields. The SW observation represents the integrated amount of water vapor between a GPS station and a transmitting satellite. SW observations provide improved temporal and spatial sampling of the atmosphere when compared to column-integrated quantities such as preciptitable water vapor (PW). Under funding from the DOE Atmospheric Radiation Measurement (ARM) program, GPS networks in the Southern Great Plains (SGP) region were deployed to retrieve SW to improve the characterization of water vapor throughout the region. These observations were used to estimate four dimensional water vapor fields using tomographic approaches and through assimilation into the MM5 numerical weather model.

Braun, John

2006-02-06T23:59:59.000Z

486

Merged and corrected 915 MHz Radar Wind Profiler moments  

SciTech Connect (OSTI)

The radar wind profiler (RWP) present at the SGP central facility operates at 915 MHz and was reconfigured in early 2011, to collect key sets of measurements for precipitation and boundary layer studies. The RWP is configured to run in two main operating modes: a precipitation (PR) mode with frequent vertical observations and a boundary layer (BL) mode that is similar to what has been traditionally applied to RWPs. To address issues regarding saturation of the radar signal, range resolution and maximum range, the RWP PR mode is set to operate with two different pulse lengths, termed as short pulse (SP) and long pulse (LP). Please refer to the RWP handbook (Coulter, 2012) for further information. Data from the RWP PR-SP and PR-LP modes have been extensively used to study deep precipitating clouds, especially their dynamical structure as the RWP data does not suffer from signal attenuation during these conditions (Giangrande et al., 2013). Tridon et al. (2013) used the data collected during the Mid-latitude Continental Convective Cloud Experiment (MC3E) to improve the estimation of noise floor of the RWP recorded Doppler spectra.

Jonathan Helmus,Virendra Ghate, Frederic Tridon

2014-06-25T23:59:59.000Z

487

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)

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.

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

2003-09-11T23:59:59.000Z

488

The Status of the ACRF Millimeter Wave Cloud Radars (MMCRs), the Path Forward for Future MMCR Upgrades, the Concept of 3D Volume Imaging Radar and the UAV Radar  

SciTech Connect (OSTI)

The United States (U.S.) Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) operates millimeter wavelength cloud radars (MMCRs) in several climatological regimes. The MMCRs, are the primary observing tool for quantifying the properties of nearly all radiatively important clouds over the ACRF sites. The first MMCR was installed at the ACRF Southern Great Plains (SGP) site nine years ago and its original design can be traced to the early 90s. Since then, several MMCRs have been deployed at the ACRF sites, while no significant hardware upgrades have been performed. Recently, a two-stage upgrade (first C-40 Digital Signal Processors [DSP]-based, and later the PC-Integrated Radar AcQuisition System [PIRAQ-III] digital receiver) of the MMCR signal-processing units was completed. Our future MMCR related goals are: 1) to have a cloud radar system that continues to have high reliability and uptime and 2) to suggest potential improvements that will address increased sensitivity needs, superior sampling and low cost maintenance of the MMCRs. The Traveling Wave Tube (TWT) technology, the frequency (35-GHz), the radio frequency (RF) layout, antenna, the calibration and radar control procedure and the environmental enclosure of the MMCR remain assets for our ability to detect the profile of hydrometeors at all heights in the troposphere at the ACRF sites.

P Kollias; MA Miller; KB Widener; RT Marchand; TP Ackerman

2005-12-30T23:59:59.000Z

489

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

SciTech Connect (OSTI)

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.

Williams, Christopher

2012-11-06T23:59:59.000Z

490

ARM - Midlatitude Continental Convective Clouds (jensen-sonde)  

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

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.

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

491

ARM - Midlatitude Continental Convective Clouds (jensen-sonde)  

SciTech Connect (OSTI)

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.

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

2012-01-19T23:59:59.000Z

492

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

SciTech Connect (OSTI)

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.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

493

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

SciTech Connect (OSTI)

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.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

494

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

SciTech Connect (OSTI)

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.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

495

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

SciTech Connect (OSTI)

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.

Williams, Christopher; Jensen, Mike

2012-11-06T23:59:59.000Z

496

Planetary Boundary Layer from AERI and MPL  

SciTech Connect (OSTI)

The distribution and transport of aerosol emitted to the lower troposphere is governed by the height of the planetary boundary layer (PBL), which limits the dilution of pollutants and influences boundary-layer convection. Because radiative heating and cooling of the surface strongly affect the PBL top height, it follows diurnal and seasonal cycles and may vary by hundreds of meters over a 24-hour period. The cap the PBL imposes on low-level aerosol transport makes aerosol concentration an effective proxy for PBL height: the top of the PBL is marked by a rapid transition from polluted, well-mixed boundary-layer air to the cleaner, more stratified free troposphere. Micropulse lidar (MPL) can provide much higher temporal resolution than radiosonde and better vertical resolution than infrared spectrometer (AERI), but PBL heights from all three instruments at the ARM SGP site are compared to one another for validation. If there is agreement among them, the higher-resolution remote sensing-derived PBL heights can accurately fill in the gaps left by the low frequency of radiosonde launches, and thus improve model parameterizations and our understanding of boundary-layer processes.

Sawyer, Virginia

2014-02-13T23:59:59.000Z

497

Merged and corrected 915 MHz Radar Wind Profiler moments  

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

The radar wind profiler (RWP) present at the SGP central facility operates at 915 MHz and was reconfigured in early 2011, to collect key sets of measurements for precipitation and boundary layer studies. The RWP is configured to run in two main operating modes: a precipitation (PR) mode with frequent vertical observations and a boundary layer (BL) mode that is similar to what has been traditionally applied to RWPs. To address issues regarding saturation of the radar signal, range resolution and maximum range, the RWP PR mode is set to operate with two different pulse lengths, termed as short pulse (SP) and long pulse (LP). Please refer to the RWP handbook (Coulter, 2012) for further information. Data from the RWP PR-SP and PR-LP modes have been extensively used to study deep precipitating clouds, especially their dynamical structure as the RWP data does not suffer from signal attenuation during these conditions (Giangrande et al., 2013). Tridon et al. (2013) used the data collected during the Mid-latitude Continental Convective Cloud Experiment (MC3E) to improve the estimation of noise floor of the RWP recorded Doppler spectra.

Jonathan Helmus,Virendra Ghate, Frederic Tridon

498

Final Technical Report  

SciTech Connect (OSTI)

During the 1-year duration of this project a new Shortwave Spectrometer (SWS) was designed and developed for deployment at the Southern Great Plains Central Facility to measure zenith solar spectral radiance. The SWS is comprised of two Zeiss miniature monolithic spectrometers (MMS-1 and MMS-NIR) for visible and near-infrared detection in the wavelength range between 350 and 2250 nm. Spectral resolution is 8 nm for the MMS-1 and 12 nm for the MMS-NIR. The light collector is a narrow field of view (±1.5 ș) collimator at the front end of a high-grade custom-made fiber optic bundle. The data acquisition and control system is a 933 MHz Pentium based PC in a PC104 format with a USB interface between the computer and the spectrometers. Spectral sampling rate is approximately 1 Hz. A prototype SWS was deployed at SGP in November and December 2004 and it collected zenith-sky solar spectra at 1 Hz continuously over a 29 day period. Prior to deployment it was calibrated and characterized at the NASA Ames Airborne Sensor Facility (ASF) using a 30 inch Integrating Sphere. The SWS was also calibrated using a portable 12 inch integrating sphere at the Central Facility. The testing and calibration procedures were developed during this implementation. The planning and scheduling for permanent installation of the new SWS as well as data processing, calibration, archiving, and distribution was conducted.

Pilewskie, Peter

2009-05-27T23:59:59.000Z

499

Watershed response and land energy feedbacks under climate change depend upon groundwater.  

SciTech Connect (OSTI)

Human induced climate change will have a significant impact on the hydrologic cycle, creating changes in fresh water resources, land cover, and feedbacks that are difficult to characterize, which makes it an issue of global importance. Previous studies have not included subsurface storage in climate change simulations and feedbacks. A variably-saturated groundwater flow model with integrated overland flow and land surface model processes is used to examine the interplay between coupled water and energy processes under climate change conditions. A case study from the Southern Great Plains (SGP) USA, an important agricultural region that is susceptible to drought, is used as the basis for three scenarios simulations using a modified atmospheric forcing dataset to reflect predicted effects due to human-induced climate change. These scenarios include an increase in the atmospheric temperature and variations in rainfall amount and are compared to the present-day climate case. Changes in shallow soil saturation and groundwater levels are quantified as well as the corresponding energy fluxes at the land surface. Here we show that groundwater and subsurface lateral flow processes are critical in understanding hydrologic response and energy feedbacks to climate change and that certain regions are more susceptible to changes in temperature, while others to changes in precipitation. This groundwater control is critical for understanding recharge and drought processes, possible under future climate conditions.

Maxwell, R M; Kollet, S J

2008-06-10T23:59:59.000Z

500

Planetary Boundary Layer from AERI and MPL  

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

The distribution and transport of aerosol emitted to the lower troposphere is governed by the height of the planetary boundary layer (PBL), which limits the dilution of pollutants and influences boundary-layer convection. Because radiative heating and cooling of the surface strongly affect the PBL top height, it follows diurnal and seasonal cycles and may vary by hundreds of meters over a 24-hour period. The cap the PBL imposes on low-level aerosol transport makes aerosol concentration an effective proxy for PBL height: the top of the PBL is marked by a rapid transition from polluted, well-mixed boundary-layer air to the cleaner, more stratified free troposphere. Micropulse lidar (MPL) can provide much higher temporal resolution than radiosonde and better vertical resolution than infrared spectrometer (AERI), but PBL heights from all three instruments at the ARM SGP site are compared to one another for validation. If there is agreement among them, the higher-resolution remote sensing-derived PBL heights can accurately fill in the gaps left by the low frequency of radiosonde launches, and thus improve model parameterizations and our understanding of boundary-layer processes.

Sawyer, Virginia