National Library of Energy BETA

Sample records for minnis cloud products

  1. ARM - VAP Product - goes7minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES7MINNIS GOES-7: 0.5 degree cloud products

  2. ARM - VAP Product - goes8minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES8MINNIS GOES-8: 0.5 degree cloud products

  3. ARM - VAP Product - goes12minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES12MINNIS GOES-12: 0.5 degree cloud products Active Dates 2003.04.01 - 2003.08.31 Originating VAP Process Minnis Cloud Products Using LBTM Algorithm : LBTM-MINNIS Measurements The measurements below provided by this product are those considered

  4. ARM - VAP Product - lbtm3minnis

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

    minnis Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNIS Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5 Active Dates 1998.01.03 - 2003.05.21 Originating VAP Process Minnis Cloud Products Using LBTM Algorithm : LBTM-MINNIS Measurements The measurements below provided by this

  5. ARM - VAP Product - visstgridg13minnis

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

    minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG13MINNIS SatCORPS-Satellite Cloud Observations and Radiative Property retrieval System-derived gridded products from satellite GOES13 Active Dates 2014.02.11 - 2015.12.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST

  6. ARM - VAP Product - goes7minnis-acf

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

    minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES7MINNIS-ACF GOES-7: 0.3 degree cloud products, ARM Central Facility

  7. ARM - VAP Product - goes8minnis-acf

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

    minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES8MINNIS-ACF GOES-8: 0.3 degree cloud products, ARM Central Facility

  8. ARM - VAP Product - visstgridfy2minnis

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

    Productsvisstvisstgridfy2minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDFY2MINNIS VISST-derived gridded products from satellite Feng-Yun2E Active Dates 2011.10.15 - 2011.12.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this

  9. ARM - VAP Product - visstpxfy2minnis

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

    Productsvisstvisstpxfy2minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPXFY2MINNIS VISST-derived pixel-level products from satellite Feng-Yun2E Active Dates 2011.10.15 - 2011.12.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this

  10. ARM - VAP Product - visstpxg13minnis

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

    Productsvisstvisstpxg13minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPXG13MINNIS VISST-derived pixel-level products from satellite GOES13 Active Dates 2014.02.11 - 2015.12.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this

  11. ARM - VAP Product - visstpxm09minnis

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

    Productsvisstvisstpxm09minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPXM09MINNIS VISST-derived pixel-level products from satellite Meteosat-9 Active Dates 2007.05.01 - 2010.12.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this

  12. ARM - VAP Product - goes12minnis-acf

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

    minnisgoes12minnis-acf Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES12MINNIS-ACF GOES-12: 0.3 degree cloud products, ARM Central Facility Active Dates 2003.04.01 - 2003.08.31

  13. ARM - VAP Product - visstgridg10v4minnis

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

    v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG10V4MINNIS VISST-derived gridded products from satellite GOES10, version 4 Active Dates 2005.03.15 - 2005.09.16 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this product are

  14. ARM - VAP Product - visstgridm1rv1minnis

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

    rv1minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDM1RV1MINNIS VISST-derived gridded products from satellite MTSAT, version 1 Active Dates 2006.01.01 - 2006.02.28 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this product are

  15. ARM - VAP Product - visstpx04g09v3minnis

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

    9v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G09V3MINNIS VISST-derived pixel-level products from satellite GOES9, version 3 Active Dates 2003.05.01 - 2005.10.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this product

  16. ARM - VAP Product - visstpx04g10v4minnis

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

    v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G10V4MINNIS VISST-derived pixel-level products from satellite GOES10, version 4 Active Dates 2005.03.15 - 2005.09.16 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this product

  17. ARM - VAP Product - visstpx04g13v4minnis

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

    3v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G13V4MINNIS VISST-derived pixel-level products from satellite GOES13, version 4 Active Dates 2011.12.01 - 2016.06.30 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this product

  18. ARM - VAP Product - visstpx04m1rv1minnis

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

    rv1minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04M1RV1MINNIS VISST-derived pixel-level products from satellite MTSAT, version 1 Active Dates 2006.01.01 - 2006.02.28 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this product

  19. ARM - VAP Product - visstpx04g15v4minnis

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

    g15v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G15V4MINNIS VISST-derived pixel-level products from satellite GOES15, version 4 Active Dates 2012.09.24 - 2012.12.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this

  20. ARM - VAP Product - visstpx08m1rv4minnis

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

    8m1rv4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX08M1RV4MINNIS VISST-derived pixel-level products from satellite MTSAT, version 4 Active Dates 2008.05.01 - 2008.12.31 Originating VAP Process Minnis Cloud Products Using Visst Algorithm : VISST Measurements The measurements below provided by this

  1. ARM - VAP Product - goes7minnis-scm

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

    scm Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : GOES7MINNIS-SCM GOES-7: 0.5 degree cloud products, Single Column Model Active Dates 1994.07.01 - 1994.07.31

  2. ARM - VAP Product - visstgridg08v2minnis

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

    v2minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG08V2MINNIS VISST-derived gridded products from satellite GOES8, version 2 Active Dates 1998.05.01 - 1999.12

  3. ARM - VAP Product - visstgridg08v3minnis

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

    v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG08V3MINNIS VISST-derived gridded products from satellite GOES8, version 3 Active Dates 2000.01.02 - 2003.03

  4. ARM - VAP Product - visstgridg10v2minnis

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

    v2minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG10V2MINNIS VISST-derived gridded products from satellite goes10, version 2 Active Dates 2004.01.01 - 2006.06.2

  5. ARM - VAP Product - visstgridg10v3minnis

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

    v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG10V3MINNIS VISST-derived gridded products from satellite GOES10, version 3 Active Dates 2003.04.01 - 2005.08.3

  6. ARM - VAP Product - visstgridg11v3minnis

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

    v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG11V3MINNIS VISST-derived gridded products from satellite GOES11, version 3 Active Dates 2006.06.21 - 2011.06

  7. ARM - VAP Product - visstgridg11v4minnis

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

    v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG11V4MINNIS VISST-derived gridded products from satellite GOES11, version 4 Active Dates 2011.07.01 - 2011.11

  8. ARM - VAP Product - visstgridg13v4minnis

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

    3v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG13V4MINNIS VISST-derived gridded products from satellite GOES13, version 4 Active Dates 2011.12.01 - 2016.07.31

  9. ARM - VAP Product - visstgridg15v4minnis

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

    5v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDG15V4MINNIS VISST-derived gridded products from satellite GOES15, version 4 Active Dates 2012.09.24 - 2013.06.10

  10. ARM - VAP Product - visstgridm1rv3minnis

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

    rv3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDM1RV3MINNIS VISST-derived gridded products from satellite MTSAT, version 3 Active Dates 2007.10.01 - 2007.12.31

  11. ARM - VAP Product - visstgridm1rv4minnis

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

    rv4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDM1RV4MINNIS VISST-derived gridded products from satellite MTSAT, version 4 Active Dates 2008.01.01 - 2008.04.30

  12. ARM - VAP Product - visstgridm2rv4minnis

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

    Productsvisstvisstgridm2rv4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTGRIDM2RV4MINNIS VISST-derived gridded products from satellite MTSAT-2, version 4 Active Dates 2011.12.26 - 2012

  13. ARM - VAP Product - visstpx04g08v2minnis

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

    v2minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G08V2MINNIS VISST-derived pixel-level products from satellite GOES8, version 2 Active Dates 1998.05.01 - 1999.12

  14. ARM - VAP Product - visstpx04g08v3minnis

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

    v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G08V3MINNIS VISST-derived pixel-level products from satellite GOES8, version 3 Active Dates 2000.01.02 - 2003.03

  15. ARM - VAP Product - visstpx04g10v2minnis

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

    v2minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G10V2MINNIS VISST-derived pixel-level products from satellite GOES10, version 2 Active Dates 2004.01.01 - 2006.06.2

  16. ARM - VAP Product - visstpx04g10v3minnis

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

    v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G10V3MINNIS VISST-derived pixel-level products from satellite GOES10, version 3 Active Dates 2003.04.01 - 2005.08.3

  17. ARM - VAP Product - visstpx04g11v3minnis

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

    v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G11V3MINNIS VISST-derived pixel-level products from satellite GOES11, version 3 Active Dates 2006.06.21 - 2011.06

  18. ARM - VAP Product - visstpx04g11v4minnis

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

    v4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04G11V4MINNIS VISST-derived pixel-level products from satellite GOES11, version 4 Active Dates 2011.07.01 - 2011.11

  19. ARM - VAP Product - visstpx04m1rv3minnis

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

    rv3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04M1RV3MINNIS VISST-derived pixel-level products from satellite MTSAT, version 3 Active Dates 2007.10.01 - 2007.12.31

  20. ARM - VAP Product - visstpx04m1rv4minnis

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

    rv4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04M1RV4MINNIS VISST-derived pixel-level products from satellite MTSAT, version 4 Active Dates 2008.01.01 - 2008.04.30

  1. ARM - VAP Product - visstpx04m2rv4minnis

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

    m2rv4minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : VISSTPX04M2RV4MINNIS VISST-derived pixel-level products from satellite MTSAT-2, version 4 Active Dates 2011.01.01 - 2014.10.31

  2. ARM - VAP Product - visstpxm10minnis

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

    Productsvisstvisstpxm10minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Error occurred. No VAP found.

  3. ARM - Measurement - Cloud optical depth

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

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

  4. Minnis-P

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

    Over the ARM SGP Domain P. Minnis, W. L. Smith, Jr., and D. F. Young National Aeronautics ... together with the technique of Minnis and Smith (1998) to derive cloud fraction, height, ...

  5. ARM - Campaign Instrument - lbtm-minnis

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

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

  6. Minnis.ARM07.ppt

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

    Multilayered Cloud Detection Methods Patrick Minnis Patrick Minnis 1 1 , Fu-Lung Chang , Fu-Lung Chang 2 2 , , Mandana Mandana Khaiyer Khaiyer 3 3 , J. Kirk Ayers , J. Kirk...

  7. ARM - VAP Product - visstgridg09v3minnis

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

    9v3minnis Documentation visst : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you Send us a...

  8. minnis-98.pdf

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

    9 Surface Emissivity Derived from Multispectral Satellite Data P. Minnis and D. F. Young Atmospheric Sciences Division NASA-Langley Research Center Hampton, Virginia W. L. Smith, Jr. Analytical Services and Materials, Inc. Hampton, Virginia Introduction Surface emissivity is critical for remote sensing of surface skin temperature and infrared cloud properties when the observed radiance is influenced by the surface radiation. It is also necessary to correctly compute the longwave flux from a

  9. ARM - VAP Process - lbtm-minnis

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

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

  10. ARM - VAP Product - lbtm3minnisman

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

    minnisman Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNISMAN Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Manus

  11. ARM - VAP Product - lbtm3minnisnau

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

    minnisnau Documentation lbtm-minnis : XDC documentation Data Management Facility Plots (Quick Looks) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : LBTM3MINNISNAU Layered Bispectral Threshold Method (LBTM) cloud products derived from GMS-5,Nauru

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

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

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

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

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

    Azores ProductsCloud Property Retrieval Products for Graciosa Island, Azores ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Cloud Property Retrieval Products for Graciosa Island, Azores [ research data - ASR funded ] The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets

  14. Microsoft PowerPoint - Minnis.TWPICE.short.11.06.ppt

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

    Workshop NASA Langley Research Center / Climate Sciences ARM November 13-15, 2006 Overview of NASA-LaRC TWP-ICE Satellite Products P. Minnis, L. Nguyen, and W. L. Smith National Aeronautics and Space Administration Langley Research Center Climate Science Branch R. Palikonda, M.M. Khaiyer, J. K. Ayers, D. R. Doelling, M. L. Nordeen, D. A. Spangenberg, P. K. Chan, and Y. Yi Analytical Services and Materials, Inc. Y. Chan, Q. Z. Trepte, & S. Sun-Mack Science Application International

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

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

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

  16. Cloud Property Retrieval Products for Graciosa Island, Azores

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

    Dong, Xiquan

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

  17. Cloud Property Retrieval Products for Graciosa Island, Azores

    SciTech Connect (OSTI)

    Dong, Xiquan

    2014-05-05

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

  18. ARM - PI Product - Atmospheric State, Cloud Microphysics & Radiative Flux

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

    ProductsAtmospheric State, Cloud Microphysics & Radiative Flux ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Atmospheric State, Cloud Microphysics & Radiative Flux [ ARM Principal Investigator (PI) Data Product ] Atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates for the ARM Southern Great Plains (SGP) site. The data represent a characterization of the

  19. ARM - Evaluation Product - Cloud Classification VAP

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

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

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

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

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

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

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

    MC3E Garber X-band site (I5) Garber X-band site (I5) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : AERIoe Thermodynamic Profile and Cloud Retrieval for MC3E Garber X-band site (I5) [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared

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

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

    MC3E Lamont X-band site (I6) Lamont X-band site (I6) ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : AERIoe Thermodynamic Profile and Cloud Retrieval for MC3E Lamont X-band site (I6) [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared

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

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

    ProductsCloud Microbase-kazr Profiles (ka) VAP ARM Data Discovery Browse Data Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Evaluation Product : Cloud Microbase-kazr Profiles (ka) VAP The KAZR radars have recently replaced the MMCR at ARM sites, and so the new KAZR-based radar products will now serve as input to Microbase. All of the historic Microbase

  4. Scanning Cloud Radar Observations at Azores: Preliminary 3D Cloud Products

    SciTech Connect (OSTI)

    Kollias, P.; Johnson, K.; Jo, I.; Tatarevic, A.; Giangrande, S.; Widener, K.; Bharadwaj, N.; Mead, J.

    2010-03-15

    The deployment of the Scanning W-Band ARM Cloud Radar (SWACR) during the AMF campaign at Azores signals the first deployment of an ARM Facility-owned scanning cloud radar and offers a prelude for the type of 3D cloud observations that ARM will have the capability to provide at all the ARM Climate Research Facility sites by the end of 2010. The primary objective of the deployment of Scanning ARM Cloud Radars (SACRs) at the ARM Facility sites is to map continuously (operationally) the 3D structure of clouds and shallow precipitation and to provide 3D microphysical and dynamical retrievals for cloud life cycle and cloud-scale process studies. This is a challenging task, never attempted before, and requires significant research and development efforts in order to understand the radar's capabilities and limitations. At the same time, we need to look beyond the radar meteorology aspects of the challenge and ensure that the hardware and software capabilities of the new systems are utilized for the development of 3D data products that address the scientific needs of the new Atmospheric System Research (ASR) program. The SWACR observations at Azores provide a first look at such observations and the challenges associated with their analysis and interpretation. The set of scan strategies applied during the SWACR deployment and their merit is discussed. The scan strategies were adjusted for the detection of marine stratocumulus and shallow cumulus that were frequently observed at the Azores deployment. Quality control procedures for the radar reflectivity and Doppler products are presented. Finally, preliminary 3D-Active Remote Sensing of Cloud Locations (3D-ARSCL) products on a regular grid will be presented, and the challenges associated with their development discussed. In addition to data from the Azores deployment, limited data from the follow-up deployment of the SWACR at the ARM SGP site will be presented. This effort provides a blueprint for the effort required for the

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

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

    ProductsISCCP Cloud Data Around the ARM Sites ARM Data Discovery Browse Data Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Evaluation Product : ISCCP Cloud Data Around the ARM Sites ISCCP data (Rossow and Schiffer, 1999 and Rossow, et.al. 2005) are widely used in the climate modeling community. Within our LLNL CCPP-ARM Parameterization Testbed (CAPT)

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

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

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

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

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

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

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

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

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

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

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

    Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP Site Stage 1: Cloud Amounts, Optical Depths, and Cloud Heights Reconciliation I. Genkova and C. N. Long Pacific Northwest National Laboratory Richland, Washington P. W. Heck Analytical Services & Materials, Inc. Hampton, Virginia P. Minnis National Aeronautics and Space Administration Langley Research Center Hampton, Virginia Introduction One of the primary Atmospheric

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

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

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

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

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

    ProductsCloud Properties and Radiative Heating Rates for TWP ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Cloud Properties and Radiative Heating Rates for TWP A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites

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

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

    Rate Retrievals ProductsCloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files

  13. ARSCL Cloud Statistics - A Value-Added Product

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

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

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

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

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

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

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

    Cloud Properties Derived from GOES-9 Over the ARM TWP Region M. M. Khaiyer, M. L. Nordeen, D. R. Doelling, and V. Chakrapani Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis and W. L. Smith, Jr. Atmospheric Sciences National Aeronautic and Space Administration Langley Research Center Hampton, Virginia Introduction Satellite data are essential for monitoring clouds and radiative fluxes where ground-based instruments are unavailable. On April 24, 2003, the ninth geostationary

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

    Office of Scientific and Technical Information (OSTI)

    We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ...

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

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

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

  18. A 3-Year Climatology of Cloud and Radiative Properties Derived...

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

    Hampton, Virginia P. Minnis, W. L. Smith, Jr., and L. Nguyen Atmospheric Sciences Division ... to broadband correlations (Minnis and Smith 1998) between GOES-6 and data from the ...

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

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

    CF during LABLE-2012 2 ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : AERIoe Thermodynamic Profile and Cloud Retrieval for SGP CF during LABLE-2012 [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The method is a

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

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

    CF during LABLE-2013 3 ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : AERIoe Thermodynamic Profile and Cloud Retrieval for SGP CF during LABLE-2013 [ ARM research ] The AERIoe algorithm retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The method is a

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

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

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

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

    SciTech Connect (OSTI)

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

    1995-12-31

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

  3. ARM08_khaiyer_final.ppt

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

    VA D. R. Doelling, P. Minnis NASA Langley Research Center, Hampton, VA 1.Introduction * As part of a cloud and radiation product dataset, the NASA Langley Cloud Group provides ...

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

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

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

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

    SciTech Connect (OSTI)

    Turner, D. D.; McFarlane, S. A.; Riihimaki, L.; Shi, Y.; Lo, C.; Min, Q.

    2014-02-01

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

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

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

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

    2010-01-01

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

  7. ARM - Campaign Instrument - visst

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

    govInstrumentsvisst Comments? We would love to hear from you Send us a note below or call us at 1-888-ARM-DATA. Send Campaign Instrument : Minnis Cloud Products Using Visst...

  8. Evaluation of a 5-Year Cloud and Radiative Property Dataset Derived...

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

    Hampton, Virginia P. Minnis, W. L. Smith, Jr., and L. Nguyen National Aeronautics and ... based only ERBE broadband and GOES-6 SW albedos from October 1986 (Minnis and Smith 1998). ...

  9. ARM - Measurement - Cloud fraction

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

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

  10. Clouds Environmental Ltd | Open Energy Information

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

    Logie, B.D.

    1995-09-10

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

  12. Precipitating clouds

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

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

  13. ARM - Measurement - Cloud size

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

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

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

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

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

  15. ARM - Measurement - Cloud type

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

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

  16. 1

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

    for Partially Cloud-Filled Pixels L. Nguyen, P. Minnis, D. V. Young, and W. L. Smith Jr. ... Meteorol., 39, 645-665. Dong, X., P. Minnis, G. G. Mace, W. L. Smith Jr, M. Poellot, and ...

  17. 1

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

    Warm Pool - International Cloud Experiment P. Minnis, L. Nguyen, and W.L. Smith, Jr. ... Journal of Atmospheric and Oceanic Technology 19:1250-1266. Minnis, P, WL Smith, Jr., DF ...

  18. Dispelling Clouds of Uncertainty

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

    Lewis, Ernie; Teixeira, João

    2015-06-15

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

  19. Dispelling Clouds of Uncertainty

    SciTech Connect (OSTI)

    Lewis, Ernie; Teixeira, João

    2015-06-15

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

  20. ARM - Measurement - Cloud location

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

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

  1. Science Cloud 2011

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

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

  2. ARM - VAP Process - visst

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

    see the External Data Center web page. Output Products visstgridg08v2minnis : VISST-derived gridded products from satellite GOES8, version 2 visstgridg08v3minnis : VISST-derived...

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

    SciTech Connect (OSTI)

    Wang, Zhien

    2010-06-29

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

  4. Cloud Properties Working Group Low Clouds Update

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

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

  5. 1

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

    Validation of Satellite Retrieved Cloud Amounts Over the Continental United States with Automatic Sciences Research Center Ceilometer Data D.R. Doelling, D.N. Phan, and D.A. Spangenberg Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis National Aeronautics and Space Administration - Langley Research Center Hampton, Virginia Introduction The National Aeronautics and Space Administration (NASA) Langley cloud and radiation retrieval products are produced near real time over the

  6. 1

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

    Developing a Three-Dimensional Cloud Product over the ARM Sites Using Geostationary Meteorological Satellite Data P. Minnis National Aeronautics and Space Administration Langley - Research Center Hampton, Virginia M. Khaiyer, Y. Yi, J. Huang, D. Spangenberg, and J. Huang Analytical Services & Materials, Inc. Hampton, Virginia S. Sun-Mack Science Applications International Corporation Hampton, Virginia Introduction Determining the three-dimensional (3D) structure of clouds over large areas

  7. ARM - Measurement - Cloud extinction

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

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

  8. Scientific Cloud Computing Misconceptions

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

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

  9. ARM - Measurement - Atmospheric pressure

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

    ... Measurements associated with the Aerosol Observing System UAV-MET-OTTER : Meteorology from UAV-Twin Otter MWRP : Microwave Radiometer Profiler VISST : Minnis Cloud ...

  10. Using ARM data to correct plane-parallel satellite retrievals...

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

    Using ARM data to correct plane-parallel satellite retrievals of cloud properties Dong, Xiquan University of North Dakota Minnis, Patrick NASA Langley Research Center Xi, Baike...

  11. ARM07Chang_poster.ppt

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

    Retrievals and Comparisons of Various MODIS-Spectrum Inferred Water Cloud Droplet Effective Radii Fu-Lung Chang @ , Patrick Minnis , Bing Lin , Sunny Sun-Mack & , Mandana ...

  12. ARM - Publications: Science Team Meeting Documents

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

    Minnis, P., and Young, D.F., NASA Langley Research Center Eighth Atmospheric Radiation Measurement (ARM) Science Team Meeting Current retrievals of cloud properties at night...

  13. ARM - Publications: Science Team Meeting Documents: Improved...

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

    Improved Techniques for Deriving Thin Cirrus Cloud Heights from Daytime GOES Data Heck, Patrick University of Wisconsin Minnis, Patrick NASA Langley Research Center Khaiyer,...

  14. ARM - VAP Product - arsclwacr1kollias

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

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

  15. ARM - VAP Product - arsclbnd1cloth

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

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

  16. ARM - VAP Product - arsclcbh1cloth

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

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

  17. Finance Idol Word Cloud

    Broader source: Energy.gov [DOE]

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

  18. ARM - Measurement - Cloud phase

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

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

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

    SciTech Connect (OSTI)

    Wang, Zhien

    2006-01-04

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

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

    Office of Scientific and Technical Information (OSTI)

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

  1. Boundary Layer Cloud Turbulence Characteristics

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

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

  2. Minnis.poster.ARM.08.ppt

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

    2008) are being incorporated into the real time retrievals for GOES-12 and Meteosat-89. ... AMF domains (e.g., MASRAD, COPS, China) are being processedreprocessed. Near-real time, ...

  3. Cloud computing security.

    SciTech Connect (OSTI)

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

    2010-10-01

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

  4. Temperature, Water Vapor, and Clouds"

    Office of Scientific and Technical Information (OSTI)

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

  5. TC_CLOUD_REGIME.cdr

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

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

  6. ARM - Measurement - Cloud effective radius

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

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

  7. Tropical Cloud Properties and Radiative Heating Profiles

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

    Mather, James

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

  8. Tropical Cloud Properties and Radiative Heating Profiles

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

    Mather, James

    2008-01-15

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

  9. Microsoft Word - ayers_jk.doc

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

    Overview of National Aeronautics and Space Agency Langley Atmospheric Radiation Measurement Project Cloud Products and Validation J.K. Ayers, R. Palikonda, M. Khaiyer, D.R. Doelling, D.A. Spangenberg, M.L. Nordeen, D.N. Phan, and H. Yi Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis and L. Nguyen National Aeronautics and Space Agency Langley Research Center Climate Science Branch Hampton, Virginia Q.Z. Trepte Science Applications International Corporation Hampton, Virginia

  10. Magellan: A Cloud Computing Testbed

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

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

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

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

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

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

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  15. Cloud Properties and Radiative Heating Rates for TWP

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

    Comstock, Jennifer

    A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

  16. Cloud Properties and Radiative Heating Rates for TWP

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

    Comstock, Jennifer

    2013-11-07

    A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

  17. Science on the Hill: Methane cloud hunting

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

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

  18. The diverse use of clouds by CMS

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

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

    2015-01-01

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

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

    Office of Scientific and Technical Information (OSTI)

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

  20. Opaque cloud detection

    DOE Patents [OSTI]

    Roskovensky, John K.

    2009-01-20

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

  1. Bringing Clouds into Focus

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

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

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

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

    Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu

    2016-05-12

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

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

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

    Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu

    2016-05-12

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

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

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

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

    2015-10-21

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

  5. Cloud Based Applications and Platforms (Presentation)

    SciTech Connect (OSTI)

    Brodt-Giles, D.

    2014-05-15

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

  6. TWP Island Cloud Trail Studies

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

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

  7. ARM - Measurement - Images of Clouds

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

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

  8. ARM - Measurement - Total cloud water

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

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

  9. ARM - AGU Presentations Featuring ARM Data

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

    ... Cloud Properties with DOE ARM AMF Measurements at Shouxian, China Y. Qiu; X. Dong; B. Xi; P. Minnis 1:40 pm, M-South Poster A13A-0184. Effect of Land Surface Interactions on Cloud ...

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

    SciTech Connect (OSTI)

    Shupe, Matthew D

    2007-10-01

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

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

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

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

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

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

    SciTech Connect (OSTI)

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

    2004-05-31

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

  13. ARM - Field Campaign - Macquarie Island Cloud and Radiation Experiment

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

    (MICRE) govCampaignsMacquarie Island Cloud and Radiation Experiment (MICRE) Campaign Links Science Plan Backgrounder Baseline Instruments and Data Plots Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Macquarie Island Cloud and Radiation Experiment (MICRE) 2016.03.01 - 2018.03.31 Lead Scientist : Roger Marchand Abstract Clouds over the Southern Ocean are poorly represented in present day reanalysis products and global climate model

  14. Research Highlight

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

    New Method for Retrieving Cloud Heights from Satellite Data Download a printable PDF Submitter: Chang, F., Science Systems and Applications, Inc. Minnis, P., NASA - Langley Research Center Area of Research: Cloud Distributions/Characterizations Working Group(s): Cloud Properties Journal Reference: Chang F, P Minnis, B Lin, MM Khaiyer, R Palikonda, and DA Spangenberg. 2010. "A modified method for inferring cloud top height using GOES-12 imager 10.7- and 13.3-µm data." Journal of

  15. Research Highlight

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

    ARM Measurements Validate New Satellite Multilayer Cloud Remote Sensing Method Submitter: Minnis, P., NASA - Langley Research Center Area of Research: Cloud Distributions/Characterizations Working Group(s): Cloud Properties Journal Reference: Huang, J., P. Minnis, B. Lin, Y. Yi, T.-F. Fan, S. Sun-Mack, and J. K. Ayers, 2006: Determination of ice water path in ice-over-water cloud systems using combined MODIS and AMSR-E measurements. Geophys. Res. Lett., 33, L21801, 10.1029/2006GL027038. Minnis,

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

    Office of Scientific and Technical Information (OSTI)

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

  17. Cloud Condensation Nuclei Counter (CCN) Instrument Handbook

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

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

  18. Cloud Properties Working Group Break Out Session

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

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

  19. The Magellan Final Report on Cloud Computing

    SciTech Connect (OSTI)

    ,; Coghlan, Susan; Yelick, Katherine

    2011-12-21

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  2. TURBULENCE DECAY AND CLOUD CORE RELAXATION IN MOLECULAR CLOUDS

    SciTech Connect (OSTI)

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

    2015-02-01

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

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

    SciTech Connect (OSTI)

    Marchand, RT; Protat, A; Alexander, SP

    2015-12-01

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

  4. Holistic Interactions of Shallow Clouds,

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

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

  5. Cumulus Clouds and Reflected Sunlight

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

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

  6. ARM - Measurement - Cloud ice particle

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

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

  7. ARM - Measurement - Cloud droplet size

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

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

  8. ARM - Measurement - Cloud condensation nuclei

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

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

  9. ARM - Measurement - Cloud top height

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

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

  10. DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING...

    Office of Scientific and Technical Information (OSTI)

    These products and raw satellite images can be accessed at http:cloudsgate2.larc.nasa.gov... Authors: Minnis, Patrick 1 + Show Author Affiliations NASA Langley Research ...

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

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

    Meskhidze, Nicholas; Nenes, Athanasios

    2010-01-01

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

  12. Widget:LogoCloud | Open Energy Information

    Open Energy Info (EERE)

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

  13. Zenith Radiance Retrieval of Cloud Properties

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

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

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

    SciTech Connect (OSTI)

    2013-10-18

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

  15. Production

    Broader source: Energy.gov [DOE]

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

  16. [Multifractal cloud properties data assessment

    SciTech Connect (OSTI)

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

    1992-05-06

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

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

    Office of Scientific and Technical Information (OSTI)

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

  18. Radiative Effects of Cloud Inhomogeneity and

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    SciTech Connect (OSTI)

    Koch, G.E.

    1985-04-01

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

  1. Evaluating cloud retrieval algorithms with the ARM BBHRP framework

    SciTech Connect (OSTI)

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

    2008-03-10

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

  2. cloud | OpenEI Community

    Open Energy Info (EERE)

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

  3. Millimeter Wave Cloud Radar (MMCR) Handbook

    SciTech Connect (OSTI)

    KB Widener; K Johnson

    2005-01-30

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

  4. ARM - VAP Product - rhbarscl1cloth

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

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

  5. ARM - VAP Product - arscl1cloth

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

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

  6. ARM - Publications: Science Team Meeting Documents

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

    Correlaton Between Satellite-Derived Water Cloud Microphysical Properties and ARM Aerosol Data at the SGP Smith, W.L., Jr.(a), Minnis, P.(a), Ferrare, R.A.(a), and Khaiyer,...

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

    Office of Scientific and Technical Information (OSTI)

    Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations Citation Details In-Document Search Title: Evaluation of high-level clouds in ...

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

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

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

    2015-04-21

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

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

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

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

    2015-09-25

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

  15. ARM KAZR-ARSCL Value Added Product

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

    Jensen, Michael

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

  16. ARM KAZR-ARSCL Value Added Product

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

    Jensen, Michael

    2012-09-28

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

  17. Researching Impact of Clouds on Solar Plants

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  18. ARM Cloud Properties Working Group: Meeting Logistics

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

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

  19. ARM - Field Campaign - Fall 1997 Cloud IOP

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

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

  20. Evaluating the MMF Using CloudSat

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

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

  1. ARM - Measurement - Cloud particle size distribution

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

    from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle size distribution The number of cloud particles present in any given volume of air...

  2. ARM - Measurement - Cloud particle number concentration

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

    from you Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Cloud particle number concentration The total number of cloud particles present in any given volume...

  3. What Makes Clouds Form, Grow and Die?

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

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

  4. ARM - VAP Product - wsicloud

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

    Productswsicloudwsicloud Documentation Data Management Facility Plots (Quick Looks) Citation DOI: 10.5439/1027762 [ What is this? ] Generate Citation ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send VAP Output : WSICLOUD WSI: derived, cloud numbers, area, perimeter, & more Active Dates 1995.09.20 - 2004.01.12 Originating VAP Process Whole Sky Imager Cloud Products : WSICLOUD Measurements The measurements below

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

    SciTech Connect (OSTI)

    PT May; C Jakob; JH Mather

    2004-05-30

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

  6. ARM Data for Cloud Parameterization

    SciTech Connect (OSTI)

    Xu, Kuan-Man

    2006-10-02

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

  7. Unlocking the Secrets of Clouds

    Broader source: Energy.gov [DOE]

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

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

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

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

    2003-03-20

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

  9. Cloud Microphysical and Radiative Properties Derived from MODIS, VIRS, AVHRR, and GMS Data Over the Tropical Western Pacific

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

    Microphysical and Radiative Properties Derived from MODIS, VIRS, AVHRR, and GMS Data Over the Tropical Western Pacific G. D. Nowicki, M. L. Nordeen, P. W. Heck, D. R. Doelling, and M. M. Khaiyer Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis National Aeronautics and Space Administration Atmospheric Sciences Division Langley Research Center Hampton, Virginia S. Sun-Mack Science Applications International Corporation Hampton, Virginia Introduction Utilization of the

  10. 1

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

    Overview of Atmospheric Radiation Measurement Satellite Cloud and Radiation Products from Langley Research Center R. Palikonda, M.M. Khaiyer, D.R. Doelling, J.K. Ayers, D.A. Spangenberg, M.L. Nordeen, and D.N. Phan Analytical Services and Materials, Inc. Hampton, Virginia P. Minnis and L. Nguyen National Aeronautics and Space Administration Langley Research Center Climate Science Branch Hampton, Virginia P.W. Heck CIMSS/University of Wisconsin-Madison Madison, Wisconsin R. Arduini, Q.Z. Trepte,

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

    SciTech Connect (OSTI)

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

    2010-02-01

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

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

    SciTech Connect (OSTI)

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

    2015-01-01

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

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

    SciTech Connect (OSTI)

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

    2015-06-01

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

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

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

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

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

    SciTech Connect (OSTI)

    Wu, Xiaoqing

    2014-02-25

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

  16. Clouds, Aerosols and Precipitation in

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  18. ARM - VAP Product - mmcrmode3ge200408121cloth

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

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

  19. ARM - VAP Product - mmcrmode3ge200404141cloth

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

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

  20. ARM - VAP Product - mmcrmode2ci200712011cloth

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

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

  1. ARM - VAP Product - mmcrmode3ge200511041cloth

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

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

  2. ARM - VAP Product - mmcrmode4pr200511041cloth

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

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

  3. ARM - VAP Product - mmcrmode3ge200608161cloth

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

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

  4. ARM - VAP Product - mmcrmode4pr200608161cloth

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

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

  5. ARM - VAP Product - mmcrmode1bl200606161cloth

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

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

  6. ARM - VAP Product - mmcrmode4pr200606161cloth

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

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

  7. ARM - VAP Product - mmcrmode1st200404151cloth

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

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

  8. ARM - VAP Product - mmcrmode2ci200309091cloth

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

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

  9. ARM - VAP Product - mmcrmode2ci200608161cloth

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

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

  10. ARM - VAP Product - mmcrmode3ge200712011cloth

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

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

  11. ARM - VAP Product - mmcrmode1bl200608121cloth

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

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

  12. ARM - VAP Product - mmcrmode2ci200404141cloth

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

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

  13. ARM - VAP Product - mmcrmode3ge200606161cloth

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

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

  14. ARM - VAP Product - mmcrmode2ci200606161cloth

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

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

  15. ARM - VAP Product - mmcrmode2ci200511041cloth

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

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

  16. ARM - VAP Product - mmcrmode2ci200408121cloth

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

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

  17. ARM - VAP Product - mmcrmode1bl200712011cloth

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

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

  18. ARM - VAP Product - mmcrmode1bl200511041cloth

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  1. ARM - Value-Added Products - Status

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

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

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

    SciTech Connect (OSTI)

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

    2002-01-01

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

  3. Testing a New Cirrus Cloud Parameterizaton

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

    Testing a New Cirrus Cloud Parameterization in NCAR CCM3 D. Zurovac-Jevtic, G. J. Zhang, and V. Ramanathan Center for Atmospheric Sciences Scripps Institute of Oceanography La Jolla, California Introduction Cirrus cloud cover and ice water content (IWC) are the two most important properties of cirrus clouds. However, in general circulation models (GCMs), their treatment is very crude. For example, in the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3), IWC is

  4. Midlatitude Continental Convective Clouds Experiment Science Objective

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

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

  5. Storm Peak Lab Cloud Property Validation

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

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

  6. Tropical Cloud Life Cycle and Overlap Structure

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  8. Characterizing Arctic Mixed-phase Cloud Structure

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

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

  9. ARM - Field Campaign - Spring Cloud IOP

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

    govCampaignsSpring Cloud IOP ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Spring Cloud IOP 2000.03.01 - 2000.03.26 Lead Scientist : Gerald Mace For data sets, see below. Summary The Atmospheric Radiation Measurement (ARM) Program conducted a Cloud Intensive Operational Period (IOP) in March 2000 that was the first-ever effort to document the 3-dimensional cloud field from observational data. Prior

  10. ARM - Field Campaign - Cloud Radar IOP

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

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

  11. CHARACTERIZATION OF CLOUDS IN TITAN'S TROPICAL ATMOSPHERE

    SciTech Connect (OSTI)

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

    2009-09-10

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

  12. DOE Research and Development Accomplishments Tag Cloud

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

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

  13. The LANL Cloud-Aerosol Model

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

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

  14. Fragmentation in rotating isothermal protostellar clouds

    SciTech Connect (OSTI)

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

    1980-01-01

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

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

    Office of Scientific and Technical Information (OSTI)

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

  16. What Makes Clouds Form, Grow and Die?

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

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

  17. Ground-based Microwave Cloud Tomography

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

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

  18. Mountain-induced Dynamics Influence Cloud Phase

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

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

  19. Electron Cloud Effects in Accelerators

    SciTech Connect (OSTI)

    Furman, M.A.

    2012-11-30

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    SciTech Connect (OSTI)

    Minnis, Patrick

    2013-06-28

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

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

    SciTech Connect (OSTI)

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

    1996-04-01

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

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

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

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

  5. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

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

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

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

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

    Open Energy Info (EERE)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  2. Towards a Characterization of Arctic Mixed-Phase Clouds

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  7. Radiative properties of ice clouds

    SciTech Connect (OSTI)

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

    1996-04-01

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

  8. Scanning ARM Cloud Radar Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N; Johnson, K

    2012-06-18

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

  9. Modeling Incoherent Electron Cloud Effects

    SciTech Connect (OSTI)

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

    2007-06-18

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

  10. ARM - Midlatitude Continental Convective Clouds

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

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

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

  11. ARM - Midlatitude Continental Convective Clouds

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

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

    2012-01-19

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

  12. HOT HYDROGEN IN DIFFUSE CLOUDS

    SciTech Connect (OSTI)

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

    2012-08-20

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

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

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

    Prather, M. J.

    2015-05-27

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

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

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

    Prather, M. J.

    2015-08-14

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

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

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

    Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas

    2015-11-05

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

  16. Absorption of solar radiation in broken clouds

    SciTech Connect (OSTI)

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

    1996-04-01

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

  17. Albedo and transmittance of inhomogeneous stratus clouds

    SciTech Connect (OSTI)

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

    1996-04-01

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

  18. ARM - Field Campaign - Arctic Cloud Infrared Imaging

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

    govCampaignsArctic Cloud Infrared Imaging Campaign Links Field Campaign Report ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Arctic Cloud Infrared Imaging 2012.07.16 - 2014.07.31 Lead Scientist : Joseph Shaw For data sets, see below. Abstract The 3rd-generation Infrared Cloud Imager (ICI) instrument was deployed close to the Great White facility at the North Slope of Alaska site and operated as

  19. Parameterizing Size Distribution in Ice Clouds

    SciTech Connect (OSTI)

    DeSlover, Daniel; Mitchell, David L.

    2009-09-25

    PARAMETERIZING SIZE DISTRIBUTIONS IN ICE CLOUDS David L. Mitchell and Daniel H. DeSlover ABSTRACT An outstanding problem that contributes considerable uncertainty to Global Climate Model (GCM) predictions of future climate is the characterization of ice particle sizes in cirrus clouds. Recent parameterizations of ice cloud effective diameter differ by a factor of three, which, for overcast conditions, often translate to changes in outgoing longwave radiation (OLR) of 55 W m-2 or more. Much of this uncertainty in cirrus particle sizes is related to the problem of ice particle shattering during in situ sampling of the ice particle size distribution (PSD). Ice particles often shatter into many smaller ice fragments upon collision with the rim of the probe inlet tube. These small ice artifacts are counted as real ice crystals, resulting in anomalously high concentrations of small ice crystals (D < 100 m) and underestimates of the mean and effective size of the PSD. Half of the cirrus cloud optical depth calculated from these in situ measurements can be due to this shattering phenomenon. Another challenge is the determination of ice and liquid water amounts in mixed phase clouds. Mixed phase clouds in the Arctic contain mostly liquid water, and the presence of ice is important for determining their lifecycle. Colder high clouds between -20 and -36 oC may also be mixed phase but in this case their condensate is mostly ice with low levels of liquid water. Rather than affecting their lifecycle, the presence of liquid dramatically affects the cloud optical properties, which affects cloud-climate feedback processes in GCMs. This project has made advancements in solving both of these problems. Regarding the first problem, PSD in ice clouds are uncertain due to the inability to reliably measure the concentrations of the smallest crystals (D < 100 m), known as the small mode. Rather than using in situ probe measurements aboard aircraft, we employed a treatment of ice cloud

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

    SciTech Connect (OSTI)

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

    2011-07-02

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

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

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

    of Energy Cloud-Based Transportation Management System Delivers Savings Cloud-Based Transportation Management System Delivers Savings October 21, 2014 - 1:53pm Addthis DOE's cloud based transportation management system (ATLAS) offers dramatically enhanced capabilities and modernization. ATLAS provides a powerful user-friendly system built to allow access to information to meet transportation needs. Its processes promote regulatory compliance, while providing access to qualified carriers and

  2. ARM - VAP Product - lbtm3minnisdar

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

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

  3. X.509 Authentication/Authorization in FermiCloud

    SciTech Connect (OSTI)

    Kim, Hyunwoo; Timm, Steven

    2014-11-11

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

  4. Developing and Evaluating Ice Cloud Parameterizations by

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

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

  5. QER- Comment of Cloud Peak Energy Inc

    Office of Energy Efficiency and Renewable Energy (EERE)

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

  6. Building a private cloud with Open Nebula

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

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

  7. HPC CLOUD APPLIED TO LATTICE OPTIMIZATION

    SciTech Connect (OSTI)

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

    2011-03-18

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

  8. Posters Sensitivity of Cirrus Cloud Radiative

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

  10. Drizzle production in stratocumulus

    SciTech Connect (OSTI)

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

    1996-04-01

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

  11. Science on the Hill: Methane cloud hunting

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

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

  12. Ignition of Aluminum Particles and Clouds

    SciTech Connect (OSTI)

    Kuhl, A L; Boiko, V M

    2010-04-07

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

  13. Electron-Cloud Build-Up: Summary

    SciTech Connect (OSTI)

    Furman, M.A.

    2007-06-18

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

  14. Atmospheric State, Cloud Microphysics and Radiative Flux

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

    Mace, Gerald

    2008-01-15

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

  15. Atmospheric State, Cloud Microphysics and Radiative Flux

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

    Mace, Gerald

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

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

    SciTech Connect (OSTI)

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

    2014-07-27

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

  17. Longwave scattering effects on fluxes in broken cloud fields

    SciTech Connect (OSTI)

    Takara, E.E.; Ellingson, R.G.

    1996-04-01

    The optical properties of clouds in the radiative energy balance are important. Most works on the effects of scattering have been in the shortwave; but longwave effects can be significant. In this work, the fluxes above and below a single cloud layer are presented, along with the errors in assuming flat black plate clouds or black clouds. The predicted fluxes are the averaged results of analysis of several fields with the same cloud amount.

  18. Magellan Explores Cloud Computing for DOE's Scientific Mission

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

    Explores Cloud Computing for DOE's Scientific Mission Magellan Explores Cloud Computing for DOE's Scientific Mission March 30, 2011 Cloud Control -This is a picture of the Magellan management and network control racks at NERSC. To test cloud computing for scientific capability, NERSC and the Argonne Leadership Computing Facility (ALCF) installed purpose-built testbeds for running scientific applications on the IBM iDataPlex cluster. (Photo Credit: Roy Kaltschmidt) Cloud computing is gaining

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

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

    Climate Campaign Links Final Campaign Summary BAECC Website ARM Data Discovery Browse Data Related Campaigns Biogenic Aerosols - Effects on Clouds and Climate: Cloud OD Sensor TWST 2014.06.15, Scott, AMF Biogenic Aerosols - Effects on Clouds and Climate: Extended Radiosonde IOP 2014.05.01, Nicoll, AMF Biogenic Aerosols - Effects on Clouds and Climate: FIGAERO-ToF-CIMS Instrument in Hyytiala with AMF-2 2014.04.01, Thornton, AMF Biogenic Aerosols - Effects on Clouds and Climate: Snowfall

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

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

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

  1. ARM - PI Product - Vaisala CL51 ceilometer

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

    ProductsVaisala CL51 ceilometer Citation DOI: 10.5439/1177195 [ What is this? ] ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Vaisala CL51 ceilometer [ research data - External funding ] Vaisala CL51 ceilometer providing attenuated backscatter coefficients and cloud base heights. Purpose Understand vertical profiles of aerosol and cloud. Data Details Developed by Ewan OConnor | Reijo Roinonen Contact

  2. Star formation relations in nearby molecular clouds

    SciTech Connect (OSTI)

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

    2014-02-20

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

  3. Strategies to reduce end-product inhibition in family 48 glycoside...

    Office of Scientific and Technical Information (OSTI)

    Subject: 09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES glycoside hydrolases; product inhibition; biofuels; cellulose; molecular dynamics Word Cloud More Like This Free Publicly ...

  4. Role of Fluid Pressure in the Production Behavior of EnhancedGeotherma...

    Office of Scientific and Technical Information (OSTI)

    Country of Publication: United States Language: English Subject: 54; GEOTHERMAL SYSTEMS; HEAT EXTRACTION; HEAT TRANSFER; PRODUCTION; SIMULATION; WATER; WORKING FLUIDS Word Cloud ...

  5. ARM - Evaluation Product - Scanning ARM Cloud Radar Corrections...

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

    added moment variables (reflectivitycorrected, meandopplervelocitycorrected, and meandopplervelocitycorrected2) provide radar moments filtered to remove measurement...

  6. ARM - Evaluation Product - KAZR Active Remotely-Sensed Cloud...

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

    measurements to provide a more comprehensive dataset. Data Details Developed by Karen Johnson | Michael Jensen Contact Tami Toto ttoto@bnl.gov (631) 344-5952 Upton, NY...

  7. ARM - Evaluation Product - MicroPulse LIDAR Cloud Optical Depth...

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

    from the MPLNOR (Micro Pulse Lidar Normalized Backscatter) and radiosonde thermodynamic profiles. The optical depth retrieval is derived following Comstock et al. (2001),...

  8. Cloud Condensation Nuclei Profile Value-Added Product (Technical...

    Office of Scientific and Technical Information (OSTI)

    Authors: McFarlane, S ; Sivaraman, C ; Ghan, S Publication Date: 2012-10-08 OSTI Identifier: 1052588 Report Number(s): DOESC-ARMTR-103 PNNL-21877 DOE Contract Number: ...

  9. ARM - Evaluation Product - Cloud Optical Properties from MFRSR...

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

    operational VAP run at other sites, MFRSRCLDOD is based on the algorithm by Min and Harrison (1996). Users are referred to that documentation for more details: http:...

  10. Understanding the AIRS, ARM, and MODIS cloud products by cross...

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

    of passive IR-derived CTH from other measurement platforms despite the nominal footprint size of 45 km at nadir view. Independent comparisons of CTH to the millimeter-wave...

  11. Active probing of cloud multiple scattering, optical depth, vertical thickness, and liquid water content using wide-angle imaging LIDAR.

    SciTech Connect (OSTI)

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

    2002-01-01

    At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60-degree full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer, and, from there, estimate the volume-averaged liquid water content. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Here we present recent WAIL data oti various clouds and discuss the extension of WAIL to full diurnal monitoring by means of an ultra-narrow magneto-optic atomic line filter for daytime measurements.

  12. A study of Monte Carlo radiative transfer through fractal clouds

    SciTech Connect (OSTI)

    Gautier, C.; Lavallec, D.; O`Hirok, W.; Ricchiazzi, P.

    1996-04-01

    An understanding of radiation transport (RT) through clouds is fundamental to studies of the earth`s radiation budget and climate dynamics. The transmission through horizontally homogeneous clouds has been studied thoroughly using accurate, discreet ordinates radiative transfer models. However, the applicability of these results to general problems of global radiation budget is limited by the plane parallel assumption and the fact that real clouds fields show variability, both vertically and horizontally, on all size scales. To understand how radiation interacts with realistic clouds, we have used a Monte Carlo radiative transfer model to compute the details of the photon-cloud interaction on synthetic cloud fields. Synthetic cloud fields, generated by a cascade model, reproduce the scaling behavior, as well as the cloud variability observed and estimated from cloud satellite data.

  13. A comparison of cloud properties at a coastal and inland site...

    Office of Scientific and Technical Information (OSTI)

    have examined differences in cloud liquid water paths (LWPs) at a coastal (Barrow) and an ... KEYWORDS: arctic clouds, cloud liquid water, microwave radiometer, ECMWF model, ...

  14. Cloud classification using whole-sky imager data

    SciTech Connect (OSTI)

    Buch, K.A. Jr.; Sun, C.H.; Thorne, L.R.

    1996-04-01

    Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes based on measured data from real cloud scenes. These renderings will provide the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here uses binary decision trees to distinguish the different cloud types based on cloud features vectors.

  15. Inferring spatial clouds statistics from limited field-of-view, zenith observations

    SciTech Connect (OSTI)

    Sun, C.H.; Thorne, L.R.

    1996-04-01

    Many of the Cloud and Radiation Testbed (CART) measurements produce a time series of zenith observations, but spatial averages are often the desired data product. One possible approach to deriving spatial averages from temporal averages is to invoke Taylor`s hypothesis where and when it is valid. Taylor`s hypothesis states that when the turbulence is small compared with the mean flow, the covariance in time is related to the covariance in space by the speed of the mean flow. For clouds fields, Taylor`s hypothesis would apply when the {open_quotes}local{close_quotes} turbulence is small compared with advective flow (mean wind). The objective of this study is to determine under what conditions Taylor`s hypothesis holds or does not hold true for broken cloud fields.

  16. ARM - PI Product - Cloudnet Project

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

    ProductsCloudnet Project ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : Cloudnet Project Cloudnet is a research project supported by the European Commission. This project aims to use data obtained quasi-continuously for the development and implementation of cloud remote sensing synergy algorithms. The use of active instruments (lidar and radar) results in detailed vertical profiles of important cloud

  17. ARM - PI Product - ISDAC Microphysics

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

    ProductsISDAC Microphysics ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send PI Product : ISDAC Microphysics Best estimate of cloud microphysical parameters derived using data collected by the cloud microphysical probes installed on the National Research Council (NRC) of Canada Convair-580 during ISDAC. These files contain phase, liquid and ice crystal size distributions (Nw(D) and Ni(D) respectively), liquid water

  18. Research Highlight

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

    A Climatology of Midlatitude Continental Cloud Properties and Their Impact on the Surface Radiation Budget Submitter: Dong, X., University of Arizona Area of Research: Cloud Distributions/Characterizations Working Group(s): Cloud Properties Journal Reference: Dong, X., P. Minnis, and B. Xi, 2005: A climatology of midlatitude continental clouds from ARM SGP site. Part I: Low-level Cloud Macrophysical, microphysical and radiative properties. J. Climate. 18, 1391-1410. Dong, X., B. Xi, and P.

  19. Research Highlight

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

    Tropical Rain Clouds Still a Challenge to Cloud-Resolving Models Download a printable PDF Submitter: Fridlind, A. M., NASA - Goddard Institute for Space Studies Ackerman, A., NASA - Goddard Institute for Space Studies Area of Research: Cloud Distributions/Characterizations Working Group(s): Cloud Life Cycle, Cloud-Aerosol-Precipitation Interactions Journal Reference: Fridlind AM, AS Ackerman, J Chaboureau, J Fan, WW Grabowski, AA Hill, TR Jones, MM Khaiyer, G Liu, P Minnis, H Morrison, L Nguyen,

  20. Magellan: experiences from a Science Cloud

    SciTech Connect (OSTI)

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

    2011-02-02

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

  1. ARM - Field Campaign - Boundary Layer Cloud IOP

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

    govCampaignsBoundary Layer Cloud IOP Campaign Links Campaign Images ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Boundary Layer Cloud IOP 2005.07.11 - 2005.08.07 Lead Scientist : William Shaw For data sets, see below. Abstract Investigators from Pacific Northwest National Laboratory, in collaboration with scientists from a number of other institutions, carried out a month of intensive measurements at

  2. Cloud-based Architecture Capabilities Summary Report

    SciTech Connect (OSTI)

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

    2014-09-01

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

  3. Layered Atlantic Smoke Interactions with Clouds (LASIC) Science...

    Office of Scientific and Technical Information (OSTI)

    Many uncertainties contribute to the highly variable model radiation fields: the aging of ... layer, and how the low clouds adjust to smoke-radiation and smoke-cloud interactions. ...

  4. Analysis of In situ Observations of Cloud Microphysics from M...

    Office of Scientific and Technical Information (OSTI)

    Cloud Microphysics from M-PACE Final Report, DOE Grant Agreement No. DE-FG02-06ER64168 Citation Details In-Document Search Title: Analysis of In situ Observations of Cloud ...

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

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

    W-Band ARM Cloud Radar - Specifications and Design K. B. Widener Pacific Northwest ... to develop and deploy the W-band ARM Cloud Radar (WACR) at the SGP central facility. ...

  6. Testing Cloud Microphysics Parameterizations in NCAR CAM5 with...

    Office of Scientific and Technical Information (OSTI)

    Title: Testing Cloud Microphysics Parameterizations in NCAR CAM5 with ISDAC and M-PACE Observations Arctic clouds simulated by the NCAR Community Atmospheric Model version 5 (CAM5) ...

  7. Joint retrievals of cloud and drizzle in marine boundary layer...

    Office of Scientific and Technical Information (OSTI)

    Specifically, the vertical structure of droplet size and water content of both cloud and ... cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g ...

  8. E-Cloud Build-up in Grooved Chambers

    SciTech Connect (OSTI)

    Venturini, Marco

    2007-05-01

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

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

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

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

  10. Biogenic Aerosols„Effects on Clouds and Climate (BAECC)

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

    Biogenic Aerosols-Effects on Clouds and Climate (BAECC) Final Campaign Summary T Petj ... DOESC-ARM-15-051 Biogenic Aerosols-Effects on Clouds and Climate (BAECC) Final Campaign ...

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

    Office of Scientific and Technical Information (OSTI)

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

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

    SciTech Connect (OSTI)

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

    2015-12-11

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

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

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

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

  14. Nighttime Cloud Detection Over the Arctic Using AVHRR Data

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

    ... Table 3. SHEBA domain cloud statistics from the polar cloud mask for January-March 1998. ... Earth Radiation Budget Experiment (ERBE) and NOAA-9 AVHRR data from 1986 were matched to ...

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

    Office of Scientific and Technical Information (OSTI)

    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 ...

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

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

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

  17. Treatment of cloud radiative effects in general circulation models

    SciTech Connect (OSTI)

    Wang, W.C.; Dudek, M.P.; Liang, X.Z.; Ding, M.

    1996-04-01

    We participate in the Atmospheric Radiation Measurement (ARM) program with two objectives: (1) to improve the general circulation model (GCM) cloud/radiation treatment with a focus on cloud verticle overlapping and layer cloud optical properties, and (2) to study the effects of cloud/radiation-climate interaction on GCM climate simulations. This report summarizes the project progress since the Fourth ARM Science Team meeting February 28-March 4, 1994, in Charleston, South Carolina.

  18. Prediction of cloud droplet number in a general circulation model

    SciTech Connect (OSTI)

    Ghan, S.J.; Leung, L.R.

    1996-04-01

    We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.

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

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

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

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

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

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

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

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

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

  2. Direct Numerical Simulations and Robust Predictions of Cloud Cavitation

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

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

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

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

    govCampaignsMarine ARM GPCI Investigation of Clouds (MAGIC) Campaign Links MAGIC Website ARM Data Discovery Browse Data Related Campaigns Marine ARM GPCI Investigations of Clouds (MAGIC): Measuring the Composition of Aerosol Particles 2013.07.01, Lewis, AMF Marine ARM GPCI Investigation of Clouds (MAGIC): Shortwave Hyperspectral Observations 2013.07.01, McBride, AMF Marine ARM GPCI Investigation of Clouds (MAGIC): Marine Ice Nuclei Collections 2013.06.01, DeMott, AMF Marine ARM GPCI

  4. Model of E-Cloud Instability in the Fermilab Recycler

    SciTech Connect (OSTI)

    Balbekov, V.

    2015-06-24

    Simple model of electron cloud is developed in the paper to explain e-cloud instability of bunched proton beam in the Fermilab Recycler. The cloud is presented as an immobile snake in strong vertical magnetic field. The instability is treated as an amplification of the bunch injection errors from the batch head to its tail. Nonlinearity of the e-cloud field is taken into account. Results of calculations are compared with experimental data demonstrating good correlation.

  5. Surface based remote sensing of aerosol-cloud interactions

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

    Surface based remote sensing of aerosol-cloud interactions Feingold, Graham NOAA/Environmental Technology Laboratory Frisch, Shelby NOAA/Environmental Technology Laboratory Min, Qilong State University of New York at Albany Category: Cloud Properties We will present an analysis of the effect of aerosol on clouds at the Southern Great Plains ARM site. New methods for retrieving cloud droplet effective radius with radar (MMCR), multifilter rotating shadowband radiometer (MFRSR), and microwave

  6. Determining Best Estimates and Uncertainties in Cloud Microphysical

    Office of Scientific and Technical Information (OSTI)

    Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions (Technical Report) | SciTech Connect Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions Citation Details In-Document Search Title: Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for

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

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

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

  8. Doppler Lidar Vertical Velocity Statistics Value-Added Product

    SciTech Connect (OSTI)

    Newsom, R. K.; Sivaraman, C.; Shippert, T. R.; Riihimaki, L. D.

    2015-07-01

    Accurate height-resolved measurements of higher-order statistical moments of vertical velocity fluctuations are crucial for improved understanding of turbulent mixing and diffusion, convective initiation, and cloud life cycles. The Atmospheric Radiation Measurement (ARM) Climate Research Facility operates coherent Doppler lidar systems at several sites around the globe. These instruments provide measurements of clear-air vertical velocity profiles in the lower troposphere with a nominal temporal resolution of 1 sec and height resolution of 30 m. The purpose of the Doppler lidar vertical velocity statistics (DLWSTATS) value-added product (VAP) is to produce height- and time-resolved estimates of vertical velocity variance, skewness, and kurtosis from these raw measurements. The VAP also produces estimates of cloud properties, including cloud-base height (CBH), cloud frequency, cloud-base vertical velocity, and cloud-base updraft fraction.

  9. Retrievals of Cloud Fraction and Cloud Albedo from Surface-based...

    Office of Scientific and Technical Information (OSTI)

    Ground-based radiation measurements have been widely conducted to gain information on ... Compared to Min2008 and Liu2011, the XL2013 retrieval of cloud albedo tends to be greater ...

  10. The Tropical Warm Pool International Cloud Experiment

    SciTech Connect (OSTI)

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

    2008-05-01

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

  11. Diffusion and scattering in multifractal clouds

    SciTech Connect (OSTI)

    Lovejoy, S.; Schertzer, D.; Waston, B.

    1996-04-01

    This paper describes investigations of radiative properties of multifractal clouds using two different approaches. In the first, diffusion is considered by examining the scaling properties of one dimensional random walks on media with multifractal diffusivities. The second approach considers the scattering statistics associated with radiative transport.

  12. Argonne's Magellan Cloud Computing Research Project

    ScienceCinema (OSTI)

    Beckman, Pete

    2013-04-19

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

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

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

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

  14. Water clouds in Y dwarfs and exoplanets

    SciTech Connect (OSTI)

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

    2014-05-20

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

  15. CloudSat as a Global Radar Calibrator

    SciTech Connect (OSTI)

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

    2011-03-01

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

  16. Analyzing signatures of aerosol-cloud interactions from satelliteretrievals and the GISS GCM to constrain the aerosol indirecteffect

    SciTech Connect (OSTI)

    Menon, S.; Del Genio, A.D.; Kaufman, Y.; Bennartz, R.; Koch, D.; Loeb, N.; Orlikowski, D.

    2007-10-01

    Evidence of aerosol-cloud interactions are evaluated using satellite data from MODIS, CERES, AMSR-E, reanalysis data from NCEP and data from the NASA Goddard Institute for Space Studies climate model. We evaluate a series of model simulations: (1) Exp N- aerosol direct radiative effects; (2) Exp C- Like Exp N but with aerosol effects on liquid-phase cumulus and stratus clouds; (3) Exp CN- Like Exp C but with model wind fields nudged to reanalysis data. Comparison between satellite-retrieved data and model simulations for June to August 2002, over the Atlantic Ocean indicate the following: a negative correlation between aerosol optical thickness (AOT) and cloud droplet effective radius (R{sub eff}) for all cases and satellite data, except for Exp N; a weak but negative correlation between liquid water path (LWP) and AOT for MODIS and CERES; and a robust increase in cloud cover with AOT for both MODIS and CERES. In all simulations, there is a positive correlation between AOT and both cloud cover and LWP (except in the case of LWP-AOT for Exp CN). The largest slopes are obtained for Exp N, implying that meteorological variability may be an important factor. The main fields associated with AOT variability in NCEP/MODIS data are warmer temperatures and increased subsidence for less clean cases, not well captured by the model. Simulated cloud fields compared with an enhanced data product from MODIS and AMSR-E indicate that model cloud thickness is over-predicted and cloud droplet number is within retrieval uncertainties. Since LWP fields are comparable this implies an under-prediction of R{sub eff} and thus an over-prediction of the indirect effect.

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

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

    Cloud OD Sensor TWST Cloud OD Sensor TWST Campaign Links Field Campaign Report ARM Data Discovery Browse Data Related Campaigns Biogenic Aerosols - Effects on Clouds and Climate 2014.02.01, Petäjä, AMF Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Biogenic Aerosols - Effects on Clouds and Climate: Cloud OD Sensor TWST 2014.06.15 - 2014.08.31 Lead Scientist : Herman Scott For data sets, see below. Abstract This deployment

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

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

    Cloud Properties from Zenith Radiance Data Cloud Properties from Zenith Radiance Data Campaign Links Final Campaign Summary ARM Data Discovery Browse Data Related Campaigns Marine ARM GPCI Investigation of Clouds (MAGIC) 2012.10.01, Lewis, AMF Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Marine ARM GPCI Investigations of Clouds (MAGIC): Cloud Properties from Zenith Radiance Data 2012.10.01 - 2013.09.30 Lead Scientist : J.-Y.

  19. Icy Cirrus Clouds to Be Studied This Spring

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

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

  20. pCloud: A Cloud-based Power Market Simulation Environment

    SciTech Connect (OSTI)

    Rudkevich, Aleksandr; Goldis, Evgeniy

    2012-12-02

    This research conducted by the Newton Energy Group, LLC (NEG) is dedicated to the development of pCloud: a Cloud-based Power Market Simulation Environment. pCloud is offering power industry stakeholders the capability to model electricity markets and is organized around the Software as a Service (SaaS) concept -- a software application delivery model in which software is centrally hosted and provided to many users via the internet. During the Phase I of this project NEG developed a prototype design for pCloud as a SaaS-based commercial service offering, system architecture supporting that design, ensured feasibility of key architecture's elements, formed technological partnerships and negotiated commercial agreements with partners, conducted market research and other related activities and secured funding for continue development of pCloud between the end of Phase I and beginning of Phase II, if awarded. Based on the results of Phase I activities, NEG has established that the development of a cloud-based power market simulation environment within the Windows Azure platform is technologically feasible, can be accomplished within the budget and timeframe available through the Phase II SBIR award with additional external funding. NEG believes that pCloud has the potential to become a game-changing technology for the modeling and analysis of electricity markets. This potential is due to the following critical advantages of pCloud over its competition: - Standardized access to advanced and proven power market simulators offered by third parties. - Automated parallelization of simulations and dynamic provisioning of computing resources on the cloud. This combination of automation and scalability dramatically reduces turn-around time while offering the capability to increase the number of analyzed scenarios by a factor of 10, 100 or even 1000. - Access to ready-to-use data and to cloud-based resources leading to a reduction in software, hardware, and IT costs

  1. Clouds and snowmelt on the north slope of Alaska

    SciTech Connect (OSTI)

    Zhang, T.; Stamnes, K.; Bowling, S.A.

    1996-04-01

    Clouds have a large effect on the radiation field. Consequently, possible changes in cloud properties may have a very substantial impact on climate. Of all natural surfaces, seasonal snow cover has the highest surface albedo, which is one of the most important components of the climatic system. Interactions between clouds and seasonal snow cover are expected to have a significant effect on climate and its change at high latitudes. The purpose of this paper is to investigate the sensitivity of the surface cloud-radiative forcing during the period of snowmelt at high latitudes. The primary variables investigated are cloud liquid path (LWP) and droplet equivalent radius (r{sub e}). We will also examine the sensitivity of the surface radiative fluxes to cloud base height and cloud base temperature.

  2. Operation Greenhouse. Scientific Director's report of atomic-weapon tests at Eniwetok, 1951. Annex 4. 1. Cloud studies. Part 1. Cloud physics. Part 2. Development of the atomic cloud. Part 3. Cloud-tracking photography

    SciTech Connect (OSTI)

    Anderson, C.E.; Gustafson, P.E.; Kellogg, W.W.; McKown, R.E.; McPherson, D.E.

    1985-09-01

    The cloud-physics project was primarily intended to fulfill a requirements for detailed information on the meteorological microstructure of atomic clouds. By means of a tracking and photographic network extending halfway around Eniwetok Atoll, the behavior of the first three clouds of Operation Greenhouse were observed and recorded. The rise of the fourth cloud was observed visually from only one site. The analysis of these observations, combined with information about the local weather conditions, gives a fairly complete picture of the development of each of the clouds. Particular emphasis was placed on the earlier phases of development, and the heights and sizes of the cloud parts have been determined as functions of time. A summary of important features of some previous atomic clouds are included for comparison.

  3. Research Highlight

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

    Observational Evidence of Changes in Water Vapor, Clouds, and Radiation Submitter: Dong, X., University of Arizona Area of Research: Cloud Distributions/Characterizations Working Group(s): Cloud Properties Journal Reference: Dong, X., B. Xi, and P. Minnis, 2006: Observational Evidence of Changes in Water vapor, Clouds, and Radiation at the ARM SGP site. Geophys. Res. Lett., 33, L19818,doi:10.1029/2006GL027132. Figure 1. This plot shows that atmospheric precipitable water vapor and downwelling

  4. Research Highlight

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

    TOA Radiation Budget of Convective Core/Stratiform Rain/Anvil Clouds from Deep Convection Download a printable PDF Submitter: Feng, Z., Pacific Northwest National Laboratory Dong, X., University of Arizona Area of Research: Cloud Distributions/Characterizations Working Group(s): Cloud Life Cycle Journal Reference: Feng Z, XQ Dong, BK Xi, C Schumacher, P Minnis, and M Khaiyer. 2011. "Top-of-atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective

  5. Research Highlight

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

    On Thin Ice: Retrieval Algorithms for Ice Clouds Examined for Improvements Submitter: Comstock, J. M., Pacific Northwest National Laboratory Area of Research: Cloud Distributions/Characterizations Working Group(s): Cloud Properties Journal Reference: An Intercomparison of Microphysical Retrieval Algorithms for Upper Tropospheric Ice Clouds. Jennifer M. Comstock, Robert d'Entremont, Daniel DeSlover, Gerald G. Mace, Sergey Y. Matrosov, Sally A. McFarlane, Patrick Minnis, David Mitchell,Kenneth

  6. Cirrus clouds in a global climate model with a statistical cirrus cloud scheme

    SciTech Connect (OSTI)

    Wang, Minghuai; Penner, Joyce E.

    2010-06-21

    A statistical cirrus cloud scheme that accounts for mesoscale temperature perturbations is implemented in a coupled aerosol and atmospheric circulation model to better represent both subgrid-scale supersaturation and cloud formation. This new scheme treats the effects of aerosol on cloud formation and ice freezing in an improved manner, and both homogeneous freezing and heterogeneous freezing are included. The scheme is able to better simulate the observed probability distribution of relative humidity compared to the scheme that was implemented in an older version of the model. Heterogeneous ice nuclei (IN) are shown to decrease the frequency of occurrence of supersaturation, and improve the comparison with observations at 192 hPa. Homogeneous freezing alone can not reproduce observed ice crystal number concentrations at low temperatures (<205 K), but the addition of heterogeneous IN improves the comparison somewhat. Increases in heterogeneous IN affect both high level cirrus clouds and low level liquid clouds. Increases in cirrus clouds lead to a more cloudy and moist lower troposphere with less precipitation, effects which we associate with the decreased convective activity. The change in the net cloud forcing is not very sensitive to the change in ice crystal concentrations, but the change in the net radiative flux at the top of the atmosphere is still large because of changes in water vapor. Changes in the magnitude of the assumed mesoscale temperature perturbations by 25% alter the ice crystal number concentrations and the net radiative fluxes by an amount that is comparable to that from a factor of 10 change in the heterogeneous IN number concentrations. Further improvements on the representation of mesoscale temperature perturbations, heterogeneous IN and the competition between homogeneous freezing and heterogeneous freezing are needed.

  7. Experiment to Characterize Tropical Cloud Systems

    SciTech Connect (OSTI)

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

    2005-08-02

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

  8. MAGIC: Marine ARM GPCI Investigation of Clouds

    SciTech Connect (OSTI)

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

    2012-10-03

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

  9. Size distributions of boundary-layer clouds

    SciTech Connect (OSTI)

    Stull, R.; Berg, L.; Modzelewski, H.

    1996-04-01

    Scattered fair-weather clouds are triggered by thermals rising from the surface layer. Not all surface layer air is buoyant enough to rise. Also, each thermal has different humidities and temperatures, resulting in interthermal variability of their lifting condensation levels (LCL). For each air parcel in the surface layer, it`s virtual potential temperature and it`s LCL height can be computed.

  10. Filaments in simulations of molecular cloud formation

    SciTech Connect (OSTI)

    Gmez, Gilberto C.; Vzquez-Semadeni, Enrique

    2014-08-20

    We report on the filaments that develop self-consistently in a new numerical simulation of cloud formation by colliding flows. As in previous studies, the forming cloud begins to undergo gravitational collapse because it rapidly acquires a mass much larger than the average Jeans mass. Thus, the collapse soon becomes nearly pressureless, proceeding along its shortest dimension first. This naturally produces filaments in the cloud and clumps within the filaments. The filaments are not in equilibrium at any time, but instead are long-lived flow features through which the gas flows from the cloud to the clumps. The filaments are long-lived because they accrete from their environment while simultaneously accreting onto the clumps within them; they are essentially the locus where the flow changes from accreting in two dimensions to accreting in one dimension. Moreover, the clumps also exhibit a hierarchical nature: the gas in a filament flows onto a main, central clump but other, smaller-scale clumps form along the infalling gas. Correspondingly, the velocity along the filament exhibits a hierarchy of jumps at the locations of the clumps. Two prominent filaments in the simulation have lengths ?15 pc and masses ?600 M {sub ?} above density n ? 10{sup 3} cm{sup 3} (?2 10{sup 3} M {sub ?} at n > 50 cm{sup 3}). The density profile exhibits a central flattened core of size ?0.3 pc and an envelope that decays as r {sup 2.5} in reasonable agreement with observations. Accretion onto the filament reaches a maximum linear density rate of ?30 M {sub ?} Myr{sup 1} pc{sup 1}.

  11. An Analysis of Cloud Absorption During

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

    Analysis of Cloud Absorption During ARESE II (Spring 2000) D. M. Powell, R. T. Marchand, and T. P. Ackerman Pacific Northwest National Laboratory Richland, Washington Introduction In early spring 2000, Atmospheric Radiation Measurement (ARM) Program researchers held an intensive operational period (IOP) at the ARM Southern Great Plains (SGP) site. This IOP had several objectives, one of which was to was to re-evaluate (with redundant measurements wherever possible) absorption by low-level

  12. Cloud services for the Fermilab scientific stakeholders

    SciTech Connect (OSTI)

    Timm, S.; Garzoglio, G.; Mhashilkar, P.; Boyd, J.; Bernabeu, G.; Sharma, N.; Peregonow, N.; Kim, H.; Noh, S.; Palur, S.; Raicu, I.

    2015-01-01

    As part of the Fermilab/KISTI cooperative research project, Fermilab has successfully run an experimental simulation workflow at scale on a federation of Amazon Web Services (AWS), FermiCloud, and local FermiGrid resources. We used the CernVM-FS (CVMFS) file system to deliver the application software. We established Squid caching servers in AWS as well, using the Shoal system to let each individual virtual machine find the closest squid server. We also developed an automatic virtual machine conversion system so that we could transition virtual machines made on FermiCloud to Amazon Web Services. We used this system to successfully run a cosmic ray simulation of the NOvA detector at Fermilab, making use of both AWS spot pricing and network bandwidth discounts to minimize the cost. On FermiCloud we also were able to run the workflow at the scale of 1000 virtual machines, using a private network routable inside of Fermilab. As a result, we present in detail the technological improvements that were used to make this work a reality.

  13. Cloud services for the Fermilab scientific stakeholders

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

    Timm, S.; Garzoglio, G.; Mhashilkar, P.; Boyd, J.; Bernabeu, G.; Sharma, N.; Peregonow, N.; Kim, H.; Noh, S.; Palur, S.; et al

    2015-01-01

    As part of the Fermilab/KISTI cooperative research project, Fermilab has successfully run an experimental simulation workflow at scale on a federation of Amazon Web Services (AWS), FermiCloud, and local FermiGrid resources. We used the CernVM-FS (CVMFS) file system to deliver the application software. We established Squid caching servers in AWS as well, using the Shoal system to let each individual virtual machine find the closest squid server. We also developed an automatic virtual machine conversion system so that we could transition virtual machines made on FermiCloud to Amazon Web Services. We used this system to successfully run a cosmic raymore » simulation of the NOvA detector at Fermilab, making use of both AWS spot pricing and network bandwidth discounts to minimize the cost. On FermiCloud we also were able to run the workflow at the scale of 1000 virtual machines, using a private network routable inside of Fermilab. As a result, we present in detail the technological improvements that were used to make this work a reality.« less

  14. Embracing the Cloud for Better Cyber Security

    SciTech Connect (OSTI)

    Shue, Craig A; Lagesse, Brent J

    2011-01-01

    The future of cyber security is inextricably tied to the future of computing. Organizational needs and economic factors will drive computing outcomes. Cyber security researchers and practitioners must recognize the path of computing evolution and position themselves to influence the process to incorporate security as an inherent property. The best way to predict future computing trends is to look at recent developments and their motivations. Organizations are moving towards outsourcing their data storage, computation, and even user desktop environments. This trend toward cloud computing has a direct impact on cyber security: rather than securing user machines, preventing malware access, and managing removable media, a cloud-based security scheme must focus on enabling secure communication with remote systems. This change in approach will have profound implications for cyber security research efforts. In this work, we highlight existing and emerging technologies and the limitations of cloud computing systems. We then discuss the cyber security efforts that would support these applications. Finally, we discuss the implications of these computing architecture changes, in particular with respect to malware and social engineering.

  15. CHEMISTRY IN DIFFUSE CLOUDS WITH TRANSIENT MICROSTRUCTURE

    SciTech Connect (OSTI)

    Cecchi-Pestellini, C.; Casu, S.; Williams, D. A.; Viti, S.

    2009-12-01

    Microstructure is observed on many lines of sight in the diffuse interstellar medium, mainly through variations in atomic line absorptions on timescales of a decade or less. This timescale implies that microstructure exists on a size scale comparable with that of the solar system; it is overpressured and transient. Both observations and theory confirm that a specific chemistry occurs in microstructure. We therefore explore a model of diffuse interstellar gas in which the chemistry in diffuse clouds is supplemented by chemistry in many transient and tiny perturbations. These perturbations are here assumed to be of unidentified origin, but it is assumed that ambipolar diffusion occurs within them. For plausible physical parameters, we find that this model can account for the range of molecular column densities observed in diffuse clouds, including species not usually accounted for by conventional models. Some molecular ions, predicted to be generated in the microstructure (including HS{sup +}, CH{sup +} {sub 2}, CH{sup +} {sub 3}, H{sub 2}O{sup +}, and H{sub 3}O{sup +}) but not yet observed in diffuse clouds, should be present at levels that may allow their detection.

  16. Intercomparison of the Cloud Water Phase among Global Climate Models

    SciTech Connect (OSTI)

    Komurcu, Muge; Storelvmo, Trude; Tan, Ivy; Lohmann, U.; Yun, Yuxing; Penner, Joyce E.; Wang, Yong; Liu, Xiaohong; Takemura, T.

    2014-03-27

    Mixed-phase clouds (clouds that consist of both cloud droplets and ice crystals) are frequently present in the Earths atmosphere and influence the Earths energy budget through their radiative properties, which are highly dependent on the cloud water phase. In this study, the phase partitioning of cloud water is compared among six global climate models (GCMs) and with Cloud and Aerosol Lidar with Orthogonal Polarization retrievals. It is found that the GCMs predict vastly different distributions of cloud phase for a given temperature, and none of them are capable of reproducing the spatial distribution or magnitude of the observed phase partitioning. While some GCMs produced liquid water paths comparable to satellite observations, they all failed to preserve sufficient liquid water at mixed-phase cloud temperatures. Our results suggest that validating GCMs using only the vertically integrated water contents could lead to amplified differences in cloud radiative feedback. The sensitivity of the simulated cloud phase in GCMs to the choice of heterogeneous ice nucleation parameterization is also investigated. The response to a change in ice nucleation is quite different for each GCM, and the implementation of the same ice nucleation parameterization in all models does not reduce the spread in simulated phase among GCMs. The results suggest that processes subsequent to ice nucleation are at least as important in determining phase and should be the focus of future studies aimed at understanding and reducing differences among the models.

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

    SciTech Connect (OSTI)

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

    2011-07-02

    In part I, the influence of cloud microphysics and dynamics on the shape of cloud radar Doppler spectra in warm stratiform clouds was discussed. The traditional analysis of radar Doppler moments was extended to include skewness and kurtosis as additional descriptors of the Doppler spectrum. Here, a short climatology of observed Doppler spectra moments as a function of the radar reflectivity at continental and maritime ARM sites is presented. The evolution of the Doppler spectra moments is consistent with the onset and growth of drizzle particles and can be used to assist modeling studies of drizzle onset and growth. Time-height radar observations are used to exhibit the coherency of the Doppler spectra shape parameters and demonstrate their potential to improve the interpretation and use of radar observations. In addition, a simplified microphysical approach to modeling the vertical evolution of the drizzle particle size distribution in warm stratiform clouds is described and used to analyze the observations. The formation rate of embryonic drizzle droplets due to the autoconversion process is not calculated explicitly; however, accretion and evaporation processes are explicitly modeled. The microphysical model is used as input to a radar Doppler spectrum forward model, and synthetic radar Doppler spectra moments are generated. Three areas of interest are studied in detail: early drizzle growth near the cloud top, growth by accretion of the well-developed drizzle, and drizzle depletion below the cloud base due to evaporation. The modeling results are in good agreement with the continental and maritime observations. This demonstrates that steady state one-dimensional explicit microphysical models coupled with a forward model and comprehensive radar Doppler spectra observations offer a powerful method to explore the vertical evolution of the drizzle particle size distribution.

  18. Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings

    SciTech Connect (OSTI)

    Rosenfeld, Daniel

    2015-12-23

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Developing and validating this methodology was possible thanks to the ASR/ARM measurements of CCN and vertical updraft profiles. Validation against ground-based CCN instruments at the ARM sites in Oklahoma, Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25º restricts the satellite coverage to ~25% of the world area in a single day. This methodology will likely allow overcoming the challenge of quantifying the aerosol indirect effect and facilitate a substantial reduction of the uncertainty in anthropogenic climate forcing.

  19. Evaluation of tropical cloud and precipitation statistics of CAM3 using CloudSat and CALIPSO data

    SciTech Connect (OSTI)

    Zhang, Y; Klein, S; Boyle, J; Mace, G G

    2008-11-20

    The combined CloudSat and CALIPSO satellite observations provide the first simultaneous measurements of cloud and precipitation vertical structure, and are used to examine the representation of tropical clouds and precipitation in the Community Atmosphere Model Version 3 (CAM3). A simulator package utilizing a model-to-satellite approach facilitates comparison of model simulations to observations, and a revised clustering method is used to sort the subgrid-scale patterns of clouds and precipitation into principal cloud regimes. Results from weather forecasts performed with CAM3 suggest that the model underestimates the horizontal extent of low and mid-level clouds in subsidence regions, but overestimates that of high clouds in ascending regions. CAM3 strongly overestimates the frequency of occurrence of the deep convection with heavy precipitation regime, but underestimates the horizontal extent of clouds and precipitation at low and middle levels when this regime occurs. This suggests that the model overestimates convective precipitation and underestimates stratiform precipitation consistent with a previous study that used only precipitation observations. Tropical cloud regimes are also evaluated in a different version of the model, CAM3.5, which uses a highly entraining plume in the parameterization of deep convection. While the frequency of occurrence of the deep convection with heavy precipitation regime from CAM3.5 forecasts decreases, the incidence of the low clouds with precipitation and congestus regimes increases. As a result, the parameterization change does not reduce the frequency of precipitating convection that is far too high relative to observations. For both versions of CAM, clouds and precipitation are overly reflective at the frequency of the CloudSat radar and thin clouds that could be detected by the lidar only are underestimated.

  20. Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

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

    Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; Somerville, Richard C.; Zhang, Kai; Liu, Xiaohong; Li, J-L F.

    2014-11-06

    In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice numbermore » is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.« less

  1. Impacts of aerosol-cloud interactions on past and future changes in tropospheric composition

    SciTech Connect (OSTI)

    Unger, N.; Menon, S.; Shindell, D. T.; Koch, D. M.

    2009-02-02

    The development of effective emissions control policies that are beneficial to both climate and air quality requires a detailed understanding of all the feedbacks in the atmospheric composition and climate system. We perform sensitivity studies with a global atmospheric composition-climate model to assess the impact of aerosols on tropospheric chemistry through their modification on clouds, aerosol-cloud interactions (ACI). The model includes coupling between both tropospheric gas-phase and aerosol chemistry and aerosols and liquid-phase clouds. We investigate past impacts from preindustrial (PI) to present day (PD) and future impacts from PD to 2050 (for the moderate IPCC A1B scenario) that embrace a wide spectrum of precursor emission changes and consequential ACI. The aerosol indirect effect (AIE) is estimated to be -2.0 Wm{sup -2} for PD-PI and -0.6 Wm{sup -2} for 2050-PD, at the high end of current estimates. Inclusion of ACI substantially impacts changes in global mean methane lifetime across both time periods, enhancing the past and future increases by 10% and 30%, respectively. In regions where pollution emissions increase, inclusion of ACI leads to 20% enhancements in in-cloud sulfate production and {approx}10% enhancements in sulfate wet deposition that is displaced away from the immediate source regions. The enhanced in-cloud sulfate formation leads to larger increases in surface sulfate across polluted regions ({approx}10-30%). Nitric acid wet deposition is dampened by 15-20% across the industrialized regions due to ACI allowing additional re-release of reactive nitrogen that contributes to 1-2 ppbv increases in surface ozone in outflow regions. Our model findings indicate that ACI must be considered in studies of methane trends and projections of future changes to particulate matter air quality.

  2. Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

    SciTech Connect (OSTI)

    Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; Somerville, Richard C.; Zhang, Kai; Liu, Xiaohong; Li, J-L F.

    2014-12-01

    In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice number is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 ?m for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.

  3. Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

    SciTech Connect (OSTI)

    Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; Somerville, Richard C.; Zhang, Kai; Liu, Xiaohong; Li, J-L F.

    2014-11-06

    In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice number is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 ?m for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.

  4. MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary

    SciTech Connect (OSTI)

    Chiu, J. -Y.C.; Gregory, L.; Wagener, R.

    2016-01-01

    Cloud droplet size and optical depth are the most fundamental properties for understanding cloud formation, dissipation and interactions with aerosol and drizzle. They are also a crucial determinant of Earth’s radiative and water-energy balances. However, these properties are poorly predicted in climate models. As a result, the response of clouds to climate change is one of the major sources of uncertainty in climate prediction.

  5. Vertical Velocities in Continental Boundary Layer Stratocumulus Clouds

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

    Velocities in Continental Boundary Layer Stratocumulus Clouds Virendra Ghate Bruce Albrecht and Pavlos Kollias Why BL Stratocumulus?? * Extensive Coverage - Cover ~24% of earth's surface - Persist of long time-scales * Impact on radiation budget - High SW albedo compared to land or ocean Klein and Hartmann 1993 But Why Continental Clouds? * They do exist - Monthly cloud fraction can vary from 10% to 23% * Impact on pollution & Diurnal Cycle - Affect pollutant venting out of BL & Aerosol

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

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

    Campaign Links Field Campaign Report ACAPEX Website ARM Data Discovery Browse Data Related Campaigns ARM Cloud Aerosol Precipitation Experiment (ACAPEX): Aerosols and Ocean Science Expedition (AEROSE) 2015.01.14, Morris, AMF ARM Cloud Aerosol Precipitation Experiment (ACAPEX): Ship-Based Ice Nuclei Collections 2015.01.14, DeMott, AMF ARM Cloud Aerosol Precipitation Experiment (ACAPEX): Aerial Observations 2015.01.14, Leung, AAF Comments? We would love to hear from you! Send us a note below or

  7. ARM - Field Campaign - Cloud, Aerosol, and Complex Terrain Interactions

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

    (CACTI) govCampaignsCloud, Aerosol, and Complex Terrain Interactions (CACTI) Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Cloud, Aerosol, and Complex Terrain Interactions (CACTI) 2018.08.15 - 2019.04.30 Lead Scientist : Adam Varble Abstract General circulation models and downscaled regional models exhibit persistent biases in deep convective initiation location and timing, cloud top height, stratiform area and precipitation

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

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

    (MC3E) Experiment (MC3E) Campaign Links Science Plan MC3E Website Field Campaign Report ARM Data Discovery Browse Data Related Campaigns Midlatitude Continental Convective Clouds Experiment (MC3E): Inner Domain Thermodynamic Profiling during MC3E 2011.04.22, Turner, SGP Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers 2011.04.22, Williams, SGP Midlatitude Continental Convective Clouds Experiment: 2DVD Support 2011.04.22, Schwaller, SGP Midlatitude

  9. Enhanced Cloud-based Control System for Small Commercial Buildings |

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

    Department of Energy Enhanced Cloud-based Control System for Small Commercial Buildings Enhanced Cloud-based Control System for Small Commercial Buildings Lead Performer: Pacific Northwest National Laboratory - Richland, WA Partner: NorthWrite Inc. - Portland, OR DOE Total Funding: $300,000 Project Term: June 1, 2016 - November 30, 2017 Funding Type: Small Business Vouchers Pilot PROJECT OBJECTIVE NorthWrite Inc. delivers services to owners of small commercial buildings, using a cloud-based

  10. Macquarie Island Cloud and Radiation Experiment Science Objective

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

    Macquarie Island Cloud and Radiation Experiment Science Objective The overarching objective of this field campaign is to make observations of the surface broadband radiative fluxes in combination with other measurements useful in characterizing cloud and aerosol properties. In addition to having large uncertainties, satellite data sets for the Southern Ocean are incomplete because they are not continuous, rarely sample the diurnal cycle, and view primarily the tops of cloud systems. This is

  11. Assessing the Radiative Impact of Clouds of Low Optical Depth

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

    the Radiative Impact of Clouds of Low Optical Depth W. O'Hirok and P. Ricchiazzi Institute for Computational Earth System Science University of California Santa Barbara, California C. Gautier Department of Geography and Institute for Computational Earth System Science University of California Santa Barbara, California Introduction Analysis from the International Satellite Cloud Climatology Project (ISCCP) reveals that the global mean cloud optical depth is surprisingly low (i.e., τ = 3.8).

  12. Radiative Importance of ThinŽ Liquid Water Clouds

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

    Program Accomplishments of the Cloud Properties Working Group (CPWG) August 2006 Cloud Radiative Forcing at the ARM Climate Research Facility: Using ARM Data to Establish Testable Metrics for GCM Predictions of Cloud Feedback Gerald Mace University of Utah, Salt Lake City, Utah The scientific underpinning of the Atmospheric Radiation Measurement (ARM) Program is largely based on the premise that long term ground-based measurements of certain quantities provide information sufficient to test the

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

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

    Measurements by the UAF Polarization Diversity Lidar during M-PACE Cirrus Cloud Measurements by the UAF Polarization Diversity Lidar during M-PACE Sassen, Kenneth University of Alaska Fairbanks Zhu, Jiang UAF During the final week of the September-October 2004 Mixed-Phase Cloud Experiment (M-PACE) conducted in and around the North Slope of Alaska (NSA) Atmospheric Radiation Measurement (ARM) site in Barrow, Alaska, cirrus clouds were unexpectedly prevalent. Overcoming earlier adversity, the

  14. Cloud properties derived from the High Spectral Resolution Lidar during

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

    MPACE Cloud properties derived from the High Spectral Resolution Lidar during MPACE Eloranta, Edwin University of Wisconsin Category: Field Campaigns Cloud properties were derived from data acquired with University of Wisconsin High Spectral Resolution Lidar during its 6-week MPACE deployment. This poster presents statistics on: 1) the altitude and temperature distribution of optical depth and cloud phase. 2) the dependence of lidar depolarization and backscatter phase function on

  15. Continental Liquid-phase Stratus Clouds at SGP: Meteorological Influences

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

    and Relationship to Adiabacity Continental Liquid-phase Stratus Clouds at SGP: Meteorological Influences and Relationship to Adiabacity Kim, Byung-Gon Kangnung National University Schwartz, Stephen Brookhaven National Laboratory Miller, Mark Brookhaven National Laboratory Min, Qilong State University of New York at Albany Category: Cloud Properties The microphysical properties of continental stratus clouds observed over SGP appear to be substantially influenced by micrometeorological

  16. Posters Radar/Radiometer Retrievals of Cloud Liquid Water and

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

    for retrieving cloud liquid water content and drizzle characteristics using a K -band Doppler radar (Kropfli et al. 1990) and microwave radiometer (Hogg et al. 1983). The...

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

    Office of Scientific and Technical Information (OSTI)

    2015, a multi-agency field campaign that aims to improve understanding of atmospheric rivers and aerosol sources and transport that influence cloud and precipitation processes. ...

  18. Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems...

    Office of Scientific and Technical Information (OSTI)

    Cumulus convection is an important component in the atmospheric radiation budget and ... when intense turbulence induced by surface radiation couples the land surface to clouds. ...

  19. Posters Mean Fluxes of Visible Solar Radiation in Broken Clouds

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

    7 Posters Mean Fluxes of Visible Solar Radiation in Broken Clouds V. E. Zuev, G. A. Titov, ... Introduction Generally, radiation codes for general circulation models (GCMs) include, ...

  20. Cloud Lake, Florida: Energy Resources | Open Energy Information

    Open Energy Info (EERE)

    Cloud Lake, Florida: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 26.6761772, -80.0739308 Show Map Loading map... "minzoom":false,"mappingse...

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

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

    Shupe, Matthew

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

  2. The Tropical Warm Pool International Cloud Experiment: Overview

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

    The Tropical Warm Pool International Cloud Experiment: Overview May, Peter Bureau or Meteorology Research Centre Mather, James Pacific Northwest National Laboratory Jakob,...

  3. Cloud Optical Properties from the Multi-Filter Shadowband Radiometer...

    Office of Scientific and Technical Information (OSTI)

    public from the National Technical Information Service, Springfield, VA at www.ntis.gov. ... depths larger than approximately 7. The retrieval assumes a single cloud layer consisting ...

  4. Overview of the COPS Aerosol and Cloud Microphysics (ACM) Subgroup...

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

    COPS Aerosol and Cloud Microphysics (ACM) Subgroup Activities Dave Turner Space Science ... (ACM) - Chairs: Susanne Crewell, Dave Turner, Stephen Mobbs ACM Scientific Questions * ...

  5. Separating Cloud and Drizzle Radar Moments during Precipitation...

    Office of Scientific and Technical Information (OSTI)

    Onset using Doppler Spectra Citation Details In-Document Search Title: Separating Cloud and Drizzle Radar Moments during Precipitation Onset using Doppler Spectra Authors: ...

  6. Testing Statistical Cloud Scheme Ideas in the GFDL Climate Model

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

    Testing Statistical Cloud Scheme Ideas in the GFDL Climate Model Klein, Stephen Lawrence Livermore National Laboratory Pincus, Robert NOAA-CIRES Climate Diagnostics Center...

  7. Fundamental to the Cloud Land Surface Interaction Campaign (CLASIC...

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

    in agriculture ranging from more accurate weather forecasting to improved water management decisions and crop yield estimation. CLASIC CLASIC - - LAND LAND Cloud and Land...

  8. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E...

    Office of Scientific and Technical Information (OSTI)

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

  9. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E...

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

    Sponsoring Org: USDOE SC OFFICE OF SCIENCE (SC) Country of Publication: United States Language: English Subject: 54 ENVIRONMENTAL SCIENCES Word Cloud More Like This Full Text ...

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

    Office of Scientific and Technical Information (OSTI)

    Sponsoring Org: USDOE SC OFFICE OF SCIENCE (SC) Country of Publication: United States Language: English Subject: 54 ENVIRONMENTAL SCIENCES Word Cloud More Like This Full Text ...

  12. Scanning ARM Cloud Radar Handbook (Technical Report) | SciTech...

    Office of Scientific and Technical Information (OSTI)

    Because RF attenuation increases with atmospheric water vapor content, ARM's Tropical ... Subject: 54 ENVIRONMENTAL SCIENCES; ATTENUATION; CLOUDS; MANUALS; RADAR; WATER VAPOR Word ...

  13. RACORO continental boundary layer cloud investigations. 2. Large...

    Office of Scientific and Technical Information (OSTI)

    Facility AAF Clouds with Low Optical Water Depths CLOWD Optical Radiative ... droplet number concentration with liquid water content (LWC), corresponding to the ...

  14. The Radiative Properties of Small Clouds: Multi-Scale Observations...

    Office of Scientific and Technical Information (OSTI)

    characterize shallow clouds and the role of aerosol in modifying their radiative effects. ... Sponsoring Org: USDOE Country of Publication: United States Language: English Subject: 54 ...

  15. BAECC Biogenic Aerosols - Effects on Clouds and Climate (Technical...

    Office of Scientific and Technical Information (OSTI)

    The main research goal was to understand the role of biogenic aerosols in cloud formation. ... Country of Publication: United States Language: English Subject: 54 ENVIRONMENTAL SCIENCES ...

  16. Biogenic Aerosols-Effects on Clouds and Climate (BAECC) Final...

    Office of Scientific and Technical Information (OSTI)

    Title: Biogenic Aerosols-Effects on Clouds and Climate (BAECC) Final Campaign Summary Atmospheric aerosol particles impact human health in urban environments, while on regional and ...

  17. Detecting Cirrus-Overlapping-Water Clouds and Retrieving their...

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

    Clouds and Retrieving their Optical Properties Using MODIS Data F.-L. Chang and Z. Li Earth System Science Interdisciplinary Center University of Maryland College...

  18. Understanding the Effect of Aerosol Properties on Cloud Droplet...

    Office of Scientific and Technical Information (OSTI)

    5-055 ENERGY Science Understanding the Effect of Aerosol Properties on Cloud Droplet Formation during TCAP Field Campaign Report D Cziczo May 2016 ARM CLIMATE RESEARCH FACILITY ...

  19. Intersecting Cold Pools: Convective Cloud Organization by Cold...

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

    Intersecting Cold Pools: Convective Cloud Organization by Cold Pools over Tropical Ocean For original submission and image(s), see ARM Research Highlights http:www.arm.gov...

  20. Simulations of Midlatitude Frontal Clouds by Single-Column and...

    Office of Scientific and Technical Information (OSTI)

    condensates due to differences in parameterizations, however, the differences among inter-compared models are smaller in the CRMs than the SCMs. While the CRM-produced clouds...

  1. Atmospheric Rivers Coming to a Cloud Near You

    ScienceCinema (OSTI)

    Leung, Ruby

    2014-06-12

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

  2. 915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds ...

  3. ARM - Publications: Science Team Meeting Documents: Clouds in...

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

    Clouds in the Darwin area and their relation to large-scale conditions Jakob, Christian BMRC Hoeglund, Sofia Lulea University of Technology This poster shows a climatological...

  4. Evolution in Cloud Population Statistics of the MJO. From AMIE...

    Office of Scientific and Technical Information (OSTI)

    Sponsoring Org: USDOE Country of Publication: United States Language: English Subject: 08 HYDROGEN convection in MJO Word Cloud More Like This Full Text preview image File size N...

  5. Studies of Emissions and Atmospheric Composition, Clouds, and...

    Office of Scientific and Technical Information (OSTI)

    and aerosols in deep convective outflow, and the influences and feedbacks of aerosol particles from anthropogenic pollution and biomass burning on meteorology, clouds, and climate. ...

  6. Testing a Cloud Condensation Nuclei Remote Sensing Method

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

    a Cloud Condensation Nuclei Remote Sensing Method S. J. Ghan Climate Physics Pacific Northwest National Laboratory Richland, Washington D. R. Collin Department of Atmospheric...

  7. ARM - Field Campaign - Aerosol and Cloud Experiments in the Eastern...

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

    horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol,...

  8. arm_stm_2007_revercomb_poster_cloud.ppt

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

    AERI Derived Cloud Properties David Tobin, Lori Borg, David Turner, Robert Holz, Daniel DeSlover, Hank Revercomb, Bob Knuteson, Leslie Moy, Ed Eloranta, Jun Li Space Science...

  9. ARM - Field Campaign - Tropical Warm Pool - International Cloud...

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

    was a data set suitable to provide the forcing and testing required by cloud resolving models and parameterizations in Global Climate Models (GCMs). This data set provided ...

  10. Atmospheric Rivers Coming to a Cloud Near You

    SciTech Connect (OSTI)

    Leung, Ruby

    2014-03-29

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

  11. "Lidar Investigations of Aerosol, Cloud, and Boundary Layer Properties...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: "Lidar Investigations of Aerosol, Cloud, and Boundary Layer Properties Over the ARM ACRF Sites" Citation Details In-Document Search Title: "Lidar Investigations ...

  12. Polluting of Winter Convective Clouds upon Transition from Ocean...

    Office of Scientific and Technical Information (OSTI)

    These findings provide the motivation for deeper investigations into the nature of the aerosols seeding clouds. less Authors: Rosenfeld, Daniel ; Chemke, Rei ; Prather, Kimberly ...

  13. Cloud Condensation Nuclei Activity of Aerosols during GoAmazon...

    Office of Scientific and Technical Information (OSTI)

    microphysical properties of the aerosol." The Observations and Modeling of the Green Ocean Amazon (GoAmazon 201415) study seeks to understand how aerosol and cloud life cycles ...

  14. University of California, San Diego (UCSD) Sky Imager Cloud Position...

    Office of Scientific and Technical Information (OSTI)

    University of California, San Diego (UCSD) Sky Imager Cloud Position Study Field Campaign Report Citation Details In-Document Search Title: University of California, San Diego ...

  15. ARM - Field Campaign - Holistic Interactions of Shallow Clouds...

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

    Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE); National Geospatial-Intelligence Agency Calibration Target Placements 2016.04.24, Kalukin, SGP ...

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

    Office of Scientific and Technical Information (OSTI)

    The techniques used for the nine cloud retrievals are briefly described in this document. This document also outlines the ACRED data availability, variables, and the nine retrieval ...

  17. ARM: AOS: Dual Column Cloud Condensation Nuclei Counter (Dataset...

    Office of Scientific and Technical Information (OSTI)

    AOS: Dual Column Cloud Condensation Nuclei Counter Authors: Derek Hageman ; Bill Behrens ; Scott Smith ; Janek Uin ; Janek Uin ; Cynthia Salwen ; Cynthia Salwen ; Annette Koontz ; ...

  18. A Comparison of Cirrus Cloud Visible Optical Depth Derived from...

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

    Comparison of Cirrus Cloud Visible Optical Depth Derived from Lidar Lo, Chaomei Pacific Northwest National Laboratory Comstock, Jennifer Pacific Northwest National Laboratory...

  19. Biogenic Aerosol - Effect on Clouds and Climate (BAECC-ERI)....

    Office of Scientific and Technical Information (OSTI)

    Modified meteorological radiosondes have been extensively developed at the University of Reading for measuring cloud properties, to allow measurements beyond the traditional ...

  20. Characterization of 3D Cirrus Cloud and Radiation Fields Using...

    Office of Scientific and Technical Information (OSTI)

    aerosol number concentration, ice cloud water path, and ice particle number ... effective ice crystal size (De) and ice water content (IWC) by dividing the atmosphere ...

  1. Determining Best Estimates and Uncertainties in Cloud Microphysical...

    Office of Scientific and Technical Information (OSTI)

    Particles in Cirrus (SPARTICUS) Experiment and the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign, over the North ...

  2. Drizzle formation in stratocumulus clouds: Effects of turbulent mixing

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

    Magaritz-Ronen, L.; Pinsky, M.; Khain, A.

    2016-02-17

    The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian–Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ~ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic andmore » characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. Lastly, it was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.« less

  3. MBL Drizzle Properties and Their Impact on Cloud Property Retrieval

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

    layer drizzle properties and their impact on cloud property retrieval." Atmospheric Measurement Techniques, 8, doi:10.5194amt-8-3555-2015. Contributors Xiquan Dong,...

  4. Cloud-Based Air Traffic Management Announcement | GE Global Research

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

    Aeronautics and Space Administration (NASA) to help bring NextGen air traffic ... GE's program with NASA will identify opportunities within ATM that can benefit from cloud ...

  5. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E...

    Office of Scientific and Technical Information (OSTI)

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

  6. Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems...

    Office of Scientific and Technical Information (OSTI)

    and over many regions of the world, particularly during the summertime growing season when intense turbulence induced by surface radiation couples the land surface to clouds. ...

  7. A Lidar View of Clouds in Southeastern China

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

    Lidar View of Clouds in Southeastern China For original submission and image(s), see ARM Research Highlights http:www.arm.govsciencehighlights Research Highlight From May 2008...

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

    SciTech Connect (OSTI)

    Shupe, Matthew

    2013-05-22

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

  9. Chameleon: A Computer Science Testbed as Application of Cloud...

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

    Chameleon: A Computer Science Testbed as Application of Cloud Computing Event Sponsor: Mathematics and Computing Science Brownbag Lunch Start Date: Dec 15 2015 - 12:00pm Building...

  10. Posters Diagnostic Analysis of Cloud Radiative Properties R.C...

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

    are extremely sensitive to parameterizations of certain poorly understood physical processes, most notably cloud-radiation interactions. As a result, models with different...

  11. Stereo Photogrammetry Reveals Substantial Drag on Cloud Thermals

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

    sciencehighlights Research Highlight Fast updrafts within clouds can generate hail, lightning, and tornadoes at the surface, as well as clear-air turbulence that pose...

  12. MG-RAST in "the cloud" | Argonne Leadership Computing Facility

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

    MG-RAST in "the cloud" Event Sponsor: Mathematics and Computer Science Division Seminar ... data uploaded and analyzed in the past few years posing numerous computational challenges. ...

  13. CLOUD BASE SIGNATURE IN TRANSMISSION SPECTRA OF EXOPLANET ATMOSPHERES

    SciTech Connect (OSTI)

    Vahidinia, Sanaz; Cuzzi, Jeffrey N.; Marley, Mark; Fortney, Jonathan

    2014-07-01

    We present an analytical model for the transmission spectrum of a transiting exoplanet, showing that a cloud base can produce an observable inflection point in the spectrum. The wavelength and magnitude of the inflection can be used to break the degeneracy between the atmospheric pressure and the abundance of the main cloud material, however, the abundance still depends on cloud particle size. An observed inflection also provides a specific point on the atmospheric P-T profile, giving us a ''thermometer'' to directly validate or rule out postulated cloud species. We apply the model to the transit spectrum of HD 189733b.

  14. In the OSTI Collections: Clouds, Sunlight, and Radiant Heat ...

    Office of Scientific and Technical Information (OSTI)

    ... Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to ... Antarctic Division, Department of the Environment (Australia) 2015-12-01 Holistic ...

  15. Validation of MODIS-Retrieved Cloud Fractions Using Whole Sky...

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

    (ARM) locales for the year 2002. Statistics concerning the frequency of cloud ... especially apparent in the arctic environment, will be shown and a preliminary ...

  16. ARM - Routine AAF Clouds with Low Optical Water Depths (CLOWD...

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

    News Discovery Channel Earth Live Blog News & Press RACORO Backgrounder (PDF, 528K) ... will obtain representative statistics of cloud microphysical, aerosol, and ...

  17. Evolution in Cloud Population Statistics of the MJO: From AMIE...

    Office of Scientific and Technical Information (OSTI)

    to Global-Cloud Permitting Models Final Report Version 1 Methods of convectivestratiform precipitation classification and surface rain rate estimation based on the ...

  18. Evolution in Cloud Population Statistics of the MJO. From AMIE...

    Office of Scientific and Technical Information (OSTI)

    to Global-Cloud Permitting Models final report Version 1 Methods of convectivestratiform precipitation classification and surface rain rate estimation based on the ...

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

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

    Clouds and radiation in the Arctic coastal system - effects of local heterogeneity Key, Erica University of Miami, RSMAS Minnett, Peter University of Miami Improving our...

  20. Liquid Water the Key to Arctic Cloud Radiative Closure

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

    Water the Key to Arctic Cloud Radiative Closure For original submission and image(s), see ARM Research Highlights http:www.arm.govsciencehighlights Research Highlight...

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

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

    Cloud Property Retrievals using AIRS data during MPACE Huang, Allen University of Wisconsin Li, Jun University of Wisconsin-Madison Baggett, Kevin University of Wisconsin-Madison...

  2. Evaluate the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius

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

    the Effect of Upper-Level Cirrus Clouds on Satellite Retrievals of Low-Level Cloud Droplet Effective Radius F.-L. Chang and Z. Li Earth System Science Interdisciplinary Center University of Maryland College Park, Maryland Z. Li Department of Meteorology University of Maryland College Park, Maryland Introduction The earth's radiation budget is sensitive to changes in the microphysical properties of low-level stratiform clouds. Their extensive coverage can significantly reduce the solar energy

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

    SciTech Connect (OSTI)

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

    2013-01-20

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

  4. Cloud feedback studies with a physics grid

    SciTech Connect (OSTI)

    Dipankar, Anurag; Stevens, Bjorn

    2013-02-07

    During this project the investigators implemented a fully parallel version of dual-grid approach in main frame code ICON, implemented a fully conservative first-order interpolation scheme for horizontal remapping, integrated UCLA-LES micro-scale model into ICON to run parallely in selected columns, and did cloud feedback studies on aqua-planet setup to evaluate the classical parameterization on a small domain. The micro-scale model may be run in parallel with the classical parameterization, or it may be run on a "physics grid" independent of the dynamics grid.

  5. SUPERNOVA REMNANT KES 17: AN EFFICIENT COSMIC RAY ACCELERATOR INSIDE A MOLECULAR CLOUD

    SciTech Connect (OSTI)

    Gelfand, Joseph D.; Castro, Daniel; Slane, Patrick O.; Temim, Tea; Hughes, John P.; Rakowski, Cara E-mail: cara.rakowski@gmail.com

    2013-11-10

    The supernova remnant Kes 17 (SNR G304.6+0.1) is one of a few but growing number of remnants detected across the electromagnetic spectrum. In this paper, we analyze recent radio, X-ray, and γ-ray observations of this object, determining that efficient cosmic ray acceleration is required to explain its broadband non-thermal spectrum. These observations also suggest that Kes 17 is expanding inside a molecular cloud, though our determination of its age depends on whether thermal conduction or clump evaporation is primarily responsible for its center-filled thermal X-ray morphology. Evidence for efficient cosmic ray acceleration in Kes 17 supports recent theoretical work concluding that the strong magnetic field, turbulence, and clumpy nature of molecular clouds enhance cosmic ray production in supernova remnants. While additional observations are needed to confirm this interpretation, further study of Kes 17 is important for understanding how cosmic rays are accelerated in supernova remnants.

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

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

    Yum, Seong Soo; Wang, Jian; Liu, Yangang; Senum, Gunnar; Springston, Stephen; McGraw, Robert; Yeom, Jae Min

    2015-05-27

    Cloud microphysical data obtained from G-1 aircraft flights over the southeastern pacific during the VOCALS-Rex field campaign were analyzed for evidence of entrainment mixing of dry air from above cloud top. Mixing diagram analysis was made for the horizontal flight data recorded at 1 Hz and 40 Hz. The dominant observed feature, a positive relationship between cloud droplet mean volume (V) and liquid water content (L), suggested occurrence of homogeneous mixing. On the other hand, estimation of the relevant scale parameters (i.e., transition length scale and transition scale number) consistently indicated inhomogeneous mixing. Importantly, the flight altitudes of the measurementsmore » were significantly below cloud top. We speculate that mixing of the entrained air near the cloud top may have indeed been inhomogeneous; but due to vertical circulation mixing, the correlation between V and L became positive at the measurement altitudes in mid-level of clouds, because during their descent, cloud droplets evaporate, faster in more diluted cloud parcels, leading to a positive correlation between V and L regardless of the mixing mechanism near the cloud top.« less

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

    SciTech Connect (OSTI)

    Yum, Seong Soo; Wang, Jian; Liu, Yangang; Senum, Gunnar; Springston, Stephen; McGraw, Robert; Yeom, Jae Min

    2015-05-27

    Cloud microphysical data obtained from G-1 aircraft flights over the southeastern pacific during the VOCALS-Rex field campaign were analyzed for evidence of entrainment mixing of dry air from above cloud top. Mixing diagram analysis was made for the horizontal flight data recorded at 1 Hz and 40 Hz. The dominant observed feature, a positive relationship between cloud droplet mean volume (V) and liquid water content (L), suggested occurrence of homogeneous mixing. On the other hand, estimation of the relevant scale parameters (i.e., transition length scale and transition scale number) consistently indicated inhomogeneous mixing. Importantly, the flight altitudes of the measurements were significantly below cloud top. We speculate that mixing of the entrained air near the cloud top may have indeed been inhomogeneous; but due to vertical circulation mixing, the correlation between V and L became positive at the measurement altitudes in mid-level of clouds, because during their descent, cloud droplets evaporate, faster in more diluted cloud parcels, leading to a positive correlation between V and L regardless of the mixing mechanism near the cloud top.

  8. Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

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

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-02-16

    Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m−2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m−2.« less

  9. Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

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

    Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; Feingold, G.; Eloranta, E.; O'Connor, E. J.; Cadeddu, M. P.

    2015-07-02

    Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m-2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m-2.« less

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

    SciTech Connect (OSTI)

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

    2014-03-01

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

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

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

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

  12. Evidence for climate change in the satellite cloud record

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

    Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

    2016-07-11

    Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts4, 5. Here we show that several independent, empirically corrected satellitemore » records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

  13. Evaluation of a stratiform cloud parameterization for general circulation models

    SciTech Connect (OSTI)

    Ghan, S.J.; Leung, L.R.; McCaa, J.

    1996-04-01

    To evaluate the relative importance of horizontal advection of cloud versus cloud formation within the grid cell of a single column model (SCM), we have performed a series of simulations with our SCM driven by a fixed vertical velocity and various rates of horizontal advection.

  14. INFERENCE OF INHOMOGENEOUS CLOUDS IN AN EXOPLANET ATMOSPHERE

    SciTech Connect (OSTI)

    Demory, Brice-Olivier; De Wit, Julien; Lewis, Nikole; Zsom, Andras; Seager, Sara; Fortney, Jonathan; Knutson, Heather; Desert, Jean-Michel; Heng, Kevin; Madhusudhan, Nikku; Gillon, Michael; Barclay, Thomas; Cowan, Nicolas B.

    2013-10-20

    We present new visible and infrared observations of the hot Jupiter Kepler-7b to determine its atmospheric properties. Our analysis allows us to (1) refine Kepler-7b's relatively large geometric albedo of Ag = 0.35 0.02, (2) place upper limits on Kepler-7b thermal emission that remains undetected in both Spitzer bandpasses and (3) report a westward shift in the Kepler optical phase curve. We argue that Kepler-7b's visible flux cannot be due to thermal emission or Rayleigh scattering from H{sub 2} molecules. We therefore conclude that high altitude, optically reflective clouds located west from the substellar point are present in its atmosphere. We find that a silicate-based cloud composition is a possible candidate. Kepler-7b exhibits several properties that may make it particularly amenable to cloud formation in its upper atmosphere. These include a hot deep atmosphere that avoids a cloud cold trap, very low surface gravity to suppress cloud sedimentation, and a planetary equilibrium temperature in a range that allows for silicate clouds to potentially form in the visible atmosphere probed by Kepler. Our analysis does not only present evidence of optically thick clouds on Kepler-7b but also yields the first map of clouds in an exoplanet atmosphere.

  15. Research Highlight

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

    The Role of Microphysics Parameterization in Simulating Tropical Mesoscale Convective Systems Download a printable PDF Submitter: Van Weverberg, K., Brookhaven National Laboratory Vogelmann, A. M., Brookhaven National Laboratory Area of Research: Cloud Processes Working Group(s): Cloud Life Cycle Journal Reference: Van Weverberg K, AM Vogelmann, W Lin, EP Luke, AT Cialella, P Minnis, MM Khaiyer, ER Boer, and MP Jensen. 2013. "The role of cloud microphysics parameterization in the simulation

  16. ARM - Publications: Science Team Meeting Documents

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

    Comparison of Stratus Cloud Optical Depths Retrieved from Surface and GOES Measurements over the SGP ARM Central Facility Dong, X., and Smith, W.L. Jr., Analytical Services and Materials, Inc.; Minnis, P., NASA Langley Research Center Eighth Atmospheric Radiation Measurement (ARM) Science Team Meeting For reliable application of satellite datasets in cloud process and single column models, it is important to have a reasonable estimate of the errors in the observed cloud properties. When properly

  17. ARM - Publications: Science Team Meeting Documents

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

    Comparison of Boundary Layer Cloud Properties using Surface and GOES Measurements at the ARM SGP Site Dong, X. (a), Minnis, P. (b), Smith, W.L., Jr. (b), and Mace, G.G. (a), University of Utah (a), NASA Langley Research Center (b) Eleventh Atmospheric Radiation Measurement (ARM) Science Team Meeting Boundary layer cloud microphysical and radiative properties derived from GOES data during March 2000 cloud IOP at ARM SGP site are compared with simultaneous surface-based observations. The

  18. Kawamoto-K

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

    Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site K. Kawamoto Virginia Polytechnic Institute and State University Blacksburg, Virginia P. Minnis and W. L. Smith, Jr. National Aeronautics and Space Administration Langley Research Center Hampton, Virginia Introduction One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one-layer cloud system in a given retrieval of

  19. ARM - Publications: Science Team Meeting Documents

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

    Comparison of Cloud-Radiative Properties from Regional Very-High-Resolution Modeling and Satellite Retrievals Wang, D.-H. (a,b) and Minnis, P.(b), Hampton University (a), NASA Langley Research Center (b) Fourteenth Atmospheric Radiation Measurement (ARM) Science Team Meeting Data from a regional very-high-resolution modeling/assimilation and the GOES satellite-derived cloud-radiative properties including cloud fraction, temperature, height, thickness, phase, optical depth, effective particle

  20. Comparison of the Vertical Velocity Used to Calculate the Cloud Droplet Number Concentration in a Cloud Resolving and a Global Climate Model

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

    Comparison of the Vertical Velocity used to Calculate the Cloud Droplet Number Concentration in a Cloud-Resolving and a Global Climate Model H. Guo, J. E. Penner, M. Herzog, and X. Liu Department of Atmospheric, Oceanic and Space Sciences University of Michigan Ann Arbor, Michigan Introduction Anthropogenic aerosols are effective cloud condensation nuclei (CCN). The availability of CCN affects the initial cloud droplet number concentration (CDNC) and droplet size; therefore, cloud optical