Title :

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

Author(s) :

Grosvenor, Daniel P. [Auteur]
University of Leeds
Sourdeval, Odran [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Leipziger Institut für Meteorologie [LIM]
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]
NASA Goddard Institute for Space Studies [GISS]
Department of Applied Physics and Applied Mathematics [New York]
Bennartz, Ralf [Auteur]
Space Science and Engineering Center [Madison] [SSEC]
Department of Earth and Environmental Sciences [Nashville]
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]
CCLRC Rutherford Appleton Laboratory [RAL]
Department of Physics [Oxford]
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]
NASA Goddard Institute for Space Studies [GISS]
Department of Earth and Environmental Engineering [New York]
Stier, Philip [Auteur]
Department of Physics [Oxford]
van Diedenhoven, Bastiaan [Auteur]
Center for Climate Systems Research [New York] [CCSR]
NASA Goddard Institute for Space Studies [GISS]
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]

Journal title :

Reviews of Geophysics

Volume number :

56

Pages :

409-453

Publisher :

American Geophysical Union (AGU)

Publication date :

2018-06

ISSN :

8755-1209

HAL domain(s) :

Planète et Univers [physics]/Océan, Atmosphère

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

European Project :

Quantifying aerosol-cloud-climate effects by regime
constRaining the EffeCts of Aerosols on Precipitation
PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment

Administrative institution(s) :

Université de Lille
CNRS

Collections :

• Autres travaux scientifiques

Submission date :

2023-01-06T12:50:01Z
2023-01-13T11:06:15Z