Remote Sensing of Droplet Number Concentration ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
URL permanente :
Titre :
Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives
Auteur(s) :
Grosvenor, Daniel P. [Auteur]
University of Leeds
Sourdeval, Odran [Auteur]
Leipziger Institut für Meteorologie [LIM]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Zuidema, Paquita [Auteur]
Rosenstiel School of Marine and Atmospheric Science [RSMAS]
Ackerman, Andrew [Auteur]
NASA Goddard Institute for Space Studies [GISS]
Alexandrov, Mikhail D. [Auteur]
Department of Applied Physics and Applied Mathematics [New York]
NASA Goddard Institute for Space Studies [GISS]
Bennartz, Ralf [Auteur]
Department of Earth and Environmental Sciences [Nashville]
Space Science and Engineering Center [Madison] [SSEC]
Boers, Reinout [Auteur]
Royal Netherlands Meteorological Institute [KNMI]
Cairns, Brian [Auteur]
NASA Goddard Institute for Space Studies [GISS]
Chiu, J. Christine [Auteur]
Colorado State University [Fort Collins] [CSU]
Christensen, Matthew [Auteur]
Department of Physics [Oxford]
CCLRC Rutherford Appleton Laboratory [RAL]
Deneke, Hartwig [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Diamond, Michael [Auteur]
University of Washington [Seattle]
Feingold, Graham [Auteur]
NOAA Earth System Research Laboratory [ESRL]
Fridlind, Ann [Auteur]
NOAA Earth System Research Laboratory [ESRL]
Hünerbein, Anja [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Knist, Christine [Auteur]
Deutscher Wetterdienst [Offenbach] [DWD]
Kollias, Pavlos [Auteur]
Stony Brook University [SUNY] [SBU]
Marshak, Alexander [Auteur]
NASA Goddard Space Flight Center [GSFC]
McCoy, Daniel [Auteur]
University of Leeds
Merk, Daniel [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Painemal, David [Auteur]
NASA Langley Research Center [Hampton] [LaRC]
Rausch, John [Auteur]
Department of Earth and Environmental Sciences [Nashville]
Rosenfeld, Daniel [Auteur]
The Hebrew University of Jerusalem [HUJ]
Russchenberg, Herman [Auteur]
Delft University of Technology [TU Delft]
Seifert, Patric [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Sinclair, Kenneth [Auteur]
Department of Earth and Environmental Engineering [New York]
NASA Goddard Institute for Space Studies [GISS]
Stier, Philip [Auteur]
Department of Physics [Oxford]
van Diedenhoven, Bastiaan [Auteur]
NASA Goddard Institute for Space Studies [GISS]
Center for Climate Systems Research [New York] [CCSR]
Wendisch, Manfred [Auteur]
Leipziger Institut für Meteorologie [LIM]
Werner, Frank [Auteur]
Joint Center for Earth Systems Technology [Baltimore] [JCET]
Wood, Robert [Auteur]
University of Washington [Seattle]
Zhang, Zhibo [Auteur]
Department of Physics [Baltimore]
Quaas, Johannes [Auteur]
Leipziger Institut für Meteorologie [LIM]
University of Leeds
Sourdeval, Odran [Auteur]
Leipziger Institut für Meteorologie [LIM]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Zuidema, Paquita [Auteur]
Rosenstiel School of Marine and Atmospheric Science [RSMAS]
Ackerman, Andrew [Auteur]
NASA Goddard Institute for Space Studies [GISS]
Alexandrov, Mikhail D. [Auteur]
Department of Applied Physics and Applied Mathematics [New York]
NASA Goddard Institute for Space Studies [GISS]
Bennartz, Ralf [Auteur]
Department of Earth and Environmental Sciences [Nashville]
Space Science and Engineering Center [Madison] [SSEC]
Boers, Reinout [Auteur]
Royal Netherlands Meteorological Institute [KNMI]
Cairns, Brian [Auteur]
NASA Goddard Institute for Space Studies [GISS]
Chiu, J. Christine [Auteur]
Colorado State University [Fort Collins] [CSU]
Christensen, Matthew [Auteur]
Department of Physics [Oxford]
CCLRC Rutherford Appleton Laboratory [RAL]
Deneke, Hartwig [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Diamond, Michael [Auteur]
University of Washington [Seattle]
Feingold, Graham [Auteur]
NOAA Earth System Research Laboratory [ESRL]
Fridlind, Ann [Auteur]
NOAA Earth System Research Laboratory [ESRL]
Hünerbein, Anja [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Knist, Christine [Auteur]
Deutscher Wetterdienst [Offenbach] [DWD]
Kollias, Pavlos [Auteur]
Stony Brook University [SUNY] [SBU]
Marshak, Alexander [Auteur]
NASA Goddard Space Flight Center [GSFC]
McCoy, Daniel [Auteur]
University of Leeds
Merk, Daniel [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Painemal, David [Auteur]
NASA Langley Research Center [Hampton] [LaRC]
Rausch, John [Auteur]
Department of Earth and Environmental Sciences [Nashville]
Rosenfeld, Daniel [Auteur]
The Hebrew University of Jerusalem [HUJ]
Russchenberg, Herman [Auteur]
Delft University of Technology [TU Delft]
Seifert, Patric [Auteur]
Leibniz Institute for Tropospheric Research [TROPOS]
Sinclair, Kenneth [Auteur]
Department of Earth and Environmental Engineering [New York]
NASA Goddard Institute for Space Studies [GISS]
Stier, Philip [Auteur]
Department of Physics [Oxford]
van Diedenhoven, Bastiaan [Auteur]
NASA Goddard Institute for Space Studies [GISS]
Center for Climate Systems Research [New York] [CCSR]
Wendisch, Manfred [Auteur]
Leipziger Institut für Meteorologie [LIM]
Werner, Frank [Auteur]
Joint Center for Earth Systems Technology [Baltimore] [JCET]
Wood, Robert [Auteur]
University of Washington [Seattle]
Zhang, Zhibo [Auteur]
Department of Physics [Baltimore]
Quaas, Johannes [Auteur]
Leipziger Institut für Meteorologie [LIM]
Titre de la revue :
Reviews of Geophysics
Numéro :
56
Pagination :
409-453
Éditeur :
American Geophysical Union (AGU)
Date de publication :
2018-06
ISSN :
8755-1209
Discipline(s) HAL :
Planète et Univers [physics]/Océan, Atmosphère
Résumé en anglais : [en]
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 ...
Lire la suite >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 summarizes 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 made 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.Lire moins >
Lire la suite >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 summarizes 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 made 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.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Projet Européen :
Établissement(s) :
Université de Lille
CNRS
CNRS
Collections :
Date de dépôt :
2023-01-06T12:50:01Z
2023-01-13T11:06:15Z
2023-01-13T11:06:15Z
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