1. Remote sensing of droplet number concentration in warm clouds: A review of the current state of knowledge and perspectives
- Author
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Hartwig Deneke, Graham Feingold, Kenneth Sinclair, Paquita Zuidema, Brian Cairns, J. Christine Chiu, Frank Werner, Manfred Wendisch, Andrew S. Ackerman, Daniel T. McCoy, Bastiaan van Diedenhoven, Ralf Bennartz, R. Boers, John Rausch, Ann M. Fridlind, Mikhail D. Alexandrov, Philip Stier, Herman Russchenberg, Robert Wood, Anja Hünerbein, Daniel Rosenfeld, Daniel P. Grosvenor, Pavlos Kollias, David Painemal, Alexander Marshak, Odran Sourdeval, Michael S. Diamond, Daniel Merk, Zhibo Zhang, Patric Seifert, Christine Knist, Matthew Christensen, Johannes Quaas, Université de Lille, CNRS, University of Leeds, Leipziger Institut für Meteorologie [LIM], Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518, Rosenstiel School of Marine and Atmospheric Science [RSMAS], NASA Goddard Institute for Space Studies [GISS], Department of Applied Physics and Applied Mathematics [New York], Department of Earth and Environmental Sciences [Nashville], Space Science and Engineering Center [Madison] [SSEC], Royal Netherlands Meteorological Institute [KNMI], Colorado State University [Fort Collins] [CSU], Department of Physics [Oxford], CCLRC Rutherford Appleton Laboratory [RAL], Leibniz Institute for Tropospheric Research [TROPOS], University of Washington [Seattle], NOAA Earth System Research Laboratory [ESRL], Deutscher Wetterdienst [Offenbach] [DWD], Stony Brook University [SUNY] [SBU], NASA Goddard Space Flight Center [GSFC], NASA Langley Research Center [Hampton] [LaRC], The Hebrew University of Jerusalem [HUJ], Delft University of Technology [TU Delft], Department of Earth and Environmental Engineering [New York], Center for Climate Systems Research [New York] [CCSR], Joint Center for Earth Systems Technology [Baltimore] [JCET], Department of Physics [Baltimore], Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Leipziger Institut für Meteorologie (LIM), Universität Leipzig, Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables], NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Columbia University [New York], Space Science and Engineering Center [Madison] (SSEC), University of Wisconsin-Madison, Vanderbilt University [Nashville], Royal Netherlands Meteorological Institute (KNMI), Colorado State University [Fort Collins] (CSU), CCLRC Rutherford Appleton Laboratory (RAL), University of Oxford, Leibniz Institute for Tropospheric Research (TROPOS), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Deutscher Wetterdienst [Offenbach] (DWD), Stony Brook University [SUNY] (SBU), State University of New York (SUNY), NASA Langley Research Center [Hampton] (LaRC), The Hebrew University of Jerusalem (HUJ), Delft University of Technology (TU Delft), Center for Climate Systems Research [New York] (CCSR), Joint Center for Earth Systems Technology [Baltimore] (JCET), NASA Goddard Space Flight Center (GSFC)-University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System, University of Maryland [Baltimore County] (UMBC), European Project: 306284,EC:FP7:ERC,ERC-2012-StG_20111012,QUAERERE(2012), European Project: 724602,Recap, and European Project: 641727,H2020,H2020-SC5-2014-two-stage,PRIMAVERA(2015)
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010504 meteorology & atmospheric sciences ,satellite ,Cloud computing ,Atmospheric Composition and Structure ,Review Article ,010502 geochemistry & geophysics ,01 natural sciences ,law.invention ,Remote Sensing ,Quality (physics) ,law ,Cloud/Radiation Interaction ,Instruments and Techniques ,Radar ,Review Articles ,lidar ,0105 earth and related environmental sciences ,Remote sensing ,[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,passive retrievals ,Effective radius ,business.industry ,Remote Sensing and Disasters ,Cloud physics ,Radiative forcing ,cloud droplet concentrations ,Geophysics ,Lidar ,13. Climate action ,Atmospheric Processes ,Cloud Physics and Chemistry ,Environmental science ,Satellite ,business ,Clouds and Aerosols ,Natural Hazards ,radar - 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 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. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and 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., Key Points Satellite cloud droplet concentration uncertainties of 78% for pixel‐level retrievals and 54% for 1 by 1 degree retrievals are estimatedThe effective radius retrieval is the most important aspect for improvement, and more in situ evaluation is neededPotential improvements using passive and active satellite, and ground‐based instruments are discussed
- Published
- 2018
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