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Title: Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives

Abstract

The cloud droplet number concentration (N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol-cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) and cloud top temperature. This review compiles issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel-level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in re, and therefore, improvements in re retrievals would greatly improve the quality of the N d retrievals. Recommendations are revealed for how this might be achieved. Some existing N d data sets are compared and discussed, andmore » best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high-quality ground-based observations are examined.« less

Authors:
ORCiD logo [1];  [2]; ORCiD logo [3]; ORCiD logo [4];  [5];  [6]; ORCiD logo [7];  [4]; ORCiD logo [8];  [9];  [10]; ORCiD logo [11]; ORCiD logo [12]; ORCiD logo [4];  [10];  [13]; ORCiD logo [14]; ORCiD logo [15];  [1];  [10] more »; ORCiD logo [16];  [17]; ORCiD logo [18];  [19]; ORCiD logo [10];  [5]; ORCiD logo [20]; ORCiD logo [5]; ORCiD logo [2]; ORCiD logo [21]; ORCiD logo [11]; ORCiD logo [22]; ORCiD logo [2] « less
  1. Univ. of Leeds (United Kingdom)
  2. Universität Leipzig (Germany)
  3. Rosenstiel School of Marine and Atmospheric Science, Miami, FL (United States)
  4. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)
  5. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Columbia Univ., New York, NY (United States)
  6. Vanderbilt Univ., Nashville, TN (United States); Univ. of Wisconsin-Madison, Madison, WI (United States)
  7. Royal Netherlands Meteorological Inst., De Bilt (Netherlands)
  8. Colorado State Univ., Fort Collins, CO (United States)
  9. Univ.of Oxford (United Kingdom)
  10. Leibniz Inst. for Tropospheric Research (Germany)
  11. Univ. of Washington, Seattle, WA (United States)
  12. National Center for Atmospheric Research, Boulder, CO (United States)
  13. Deutscher Wetterdienst, Lindenberg (Germany)
  14. Stony Brook Univ., NY (United States)
  15. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  16. NASA Langley Research Center, Hampton, VA (United States)
  17. Vanderbilt Univ., Nashville, TN (United States)
  18. Hebrew Univ. of Jerusalem (Israel)
  19. Delft Univ. of Technology (Netherlands)
  20. Univ. of Oxford (United Kingdom)
  21. Joint Center for Earth Systems Technology, Baltimore MD (United States)
  22. Univ. of Maryland Baltimore County (UMBC), Baltimore, MD (United States)
Publication Date:
Research Org.:
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); Federal Ministry for Education and Research in Germany (BMBF); European Research Council (ERC)
OSTI Identifier:
1457505
Alternate Identifier(s):
OSTI ID: 1457507; OSTI ID: 1547362
Grant/Contract Number:  
SC0016237
Resource Type:
Published Article
Journal Name:
Reviews of Geophysics (1985)
Additional Journal Information:
Journal Name: Reviews of Geophysics (1985); Journal Volume: 56; Journal Issue: 2; Journal ID: ISSN 8755-1209
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; cloud droplet concentrations; satellite; radar; lidar; remote sensing; passive retrievals

Citation Formats

Grosvenor, Daniel P., Sourdeval, Odran, Zuidema, Paquita, Ackerman, Andrew, Alexandrov, Mikhail D., Bennartz, Ralf, Boers, Reinout, Cairns, Brian, Chiu, J. Christine, Christensen, Matthew, Deneke, Hartwig, Diamond, Michael, Feingold, Graham, Fridlind, Ann, Hünerbein, Anja, Knist, Christine, Kollias, Pavlos, Marshak, Alexander, McCoy, Daniel, Merk, Daniel, Painemal, David, Rausch, John, Rosenfeld, Daniel, Russchenberg, Herman, Seifert, Patric, Sinclair, Kenneth, Stier, Philip, van Diedenhoven, Bastiaan, Wendisch, Manfred, Werner, Frank, Wood, Robert, Zhang, Zhibo, and Quaas, Johannes. Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives. United States: N. p., 2018. Web. doi:10.1029/2017rg000593.
Grosvenor, Daniel P., Sourdeval, Odran, Zuidema, Paquita, Ackerman, Andrew, Alexandrov, Mikhail D., Bennartz, Ralf, Boers, Reinout, Cairns, Brian, Chiu, J. Christine, Christensen, Matthew, Deneke, Hartwig, Diamond, Michael, Feingold, Graham, Fridlind, Ann, Hünerbein, Anja, Knist, Christine, Kollias, Pavlos, Marshak, Alexander, McCoy, Daniel, Merk, Daniel, Painemal, David, Rausch, John, Rosenfeld, Daniel, Russchenberg, Herman, Seifert, Patric, Sinclair, Kenneth, Stier, Philip, van Diedenhoven, Bastiaan, Wendisch, Manfred, Werner, Frank, Wood, Robert, Zhang, Zhibo, & Quaas, Johannes. Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives. United States. doi:10.1029/2017rg000593.
Grosvenor, Daniel P., Sourdeval, Odran, Zuidema, Paquita, Ackerman, Andrew, Alexandrov, Mikhail D., Bennartz, Ralf, Boers, Reinout, Cairns, Brian, Chiu, J. Christine, Christensen, Matthew, Deneke, Hartwig, Diamond, Michael, Feingold, Graham, Fridlind, Ann, Hünerbein, Anja, Knist, Christine, Kollias, Pavlos, Marshak, Alexander, McCoy, Daniel, Merk, Daniel, Painemal, David, Rausch, John, Rosenfeld, Daniel, Russchenberg, Herman, Seifert, Patric, Sinclair, Kenneth, Stier, Philip, van Diedenhoven, Bastiaan, Wendisch, Manfred, Werner, Frank, Wood, Robert, Zhang, Zhibo, and Quaas, Johannes. Tue . "Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives". United States. doi:10.1029/2017rg000593.
@article{osti_1457505,
title = {Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives},
author = {Grosvenor, Daniel P. and Sourdeval, Odran and Zuidema, Paquita and Ackerman, Andrew and Alexandrov, Mikhail D. and Bennartz, Ralf and Boers, Reinout and Cairns, Brian and Chiu, J. Christine and Christensen, Matthew and Deneke, Hartwig and Diamond, Michael and Feingold, Graham and Fridlind, Ann and Hünerbein, Anja and Knist, Christine and Kollias, Pavlos and Marshak, Alexander and McCoy, Daniel and Merk, Daniel and Painemal, David and Rausch, John and Rosenfeld, Daniel and Russchenberg, Herman and Seifert, Patric and Sinclair, Kenneth and Stier, Philip and van Diedenhoven, Bastiaan and Wendisch, Manfred and Werner, Frank and Wood, Robert and Zhang, Zhibo and Quaas, Johannes},
abstractNote = {The cloud droplet number concentration (Nd) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol-cloud interactions. Current standard satellite retrievals do not operationally provide Nd, but it can be inferred from retrievals of cloud optical depth (τc) cloud droplet effective radius (re) and cloud top temperature. This review compiles issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel-level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. Nd uncertainty is dominated by errors in re, and therefore, improvements in re retrievals would greatly improve the quality of the Nd retrievals. Recommendations are revealed for how this might be achieved. Some existing Nd data sets are compared and discussed, and best practices for the use of Nd data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative Nd estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high-quality ground-based observations are examined.},
doi = {10.1029/2017rg000593},
journal = {Reviews of Geophysics (1985)},
number = 2,
volume = 56,
place = {United States},
year = {2018},
month = {4}
}

Journal Article:
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DOI: 10.1029/2017rg000593

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Composite study of aerosol export events from East Asia and North America
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Strong aerosol–cloud interaction in altocumulus during updraft periods: lidar observations over central Europe
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A study of warm rain detection using A-Train satellite data: A STUDY OF WARM RAIN DETECTION
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Retrieving co-occurring cloud and precipitation properties of warm marine boundary layer clouds with A-Train data: Cloud and Precipitation Properties
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Droplet Growth in Warm Water Clouds Observed by the A-Train. Part I: Sensitivity Analysis of the MODIS-Derived Cloud Droplet Sizes
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Observed Southern Ocean Cloud Properties and Shortwave Reflection. Part I: Calculation of SW Flux from Observed Cloud Properties
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Constraining the instantaneous aerosol influence on cloud albedo
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The Retrieval of Stratus Cloud Droplet Effective Radius with Cloud Radars
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Evaluation of Hydrometeor Phase and Ice Properties in Cloud-Resolving Model Simulations of Tropical Deep Convection Using Radiance and Polarization Measurements
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First extended validation of satellite microwave liquid water path with ship-based observations of marine low clouds: SATELLITE MW MARINE CLOUD VALIDATION
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Unveiling aerosol–cloud interactions – Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate
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Pollution from China increases cloud droplet number, suppresses rain over the East China Sea: POLLUTION OVER EAST CHINA SEA
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An overview of MODIS radiometric calibration and characterization
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    Works referencing / citing this record:

    Is positive correlation between cloud droplet effective radius and aerosol optical depth over land due to retrieval artifacts or real physical processes?
    journal, January 2019

    • Jia, Hailing; Ma, Xiaoyan; Quaas, Johannes
    • Atmospheric Chemistry and Physics, Vol. 19, Issue 13
    • DOI: 10.5194/acp-19-8879-2019

    The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing, and climate sensitivity
    journal, January 2019

    • Neubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe
    • Geoscientific Model Development, Vol. 12, Issue 8
    • DOI: 10.5194/gmd-12-3609-2019