Articles | Volume 15, issue 12
Atmos. Meas. Tech., 15, 3875–3892, 2022
https://doi.org/10.5194/amt-15-3875-2022
Atmos. Meas. Tech., 15, 3875–3892, 2022
https://doi.org/10.5194/amt-15-3875-2022
Research article
01 Jul 2022
Research article | 01 Jul 2022

The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data

Edward Gryspeerdt et al.

Data sets

Airborne Science Data for Atmospheric Composition NASA https://www-air.larc.nasa.gov/missions.htm

All Field Projects and Deployments EOL https://www.eol.ucar.edu/all-field-projects-and-deployments

MICROphysicS of COnvective PrEcipitation (MICROSCOPE) project: In-situ airborne atmospheric and ground-based radar measurements CEDA Archive http://catalogue.ceda.ac.uk/uuid/8440933238f72f27762005c33d2aa278

Cloud droplet number concentration, calculated from the MODIS (Moderate resolution imaging spectroradiometer) cloud optical properties retrieval and gridded using different sampling strategies E. Gryspeerdt, D. McCoy, E. Crosbie, R. H. Moore, G. J. Nott, . Painemal, J. Small-Griswold, A. Sorooshian, and L. Ziemba https://doi.org/10.5285/864a46cc65054008857ee5bb772a2a2b

Model code and software

A Multi-Year Data Set on Aerosol-Cloud-Precipitation-Meteorology Interactions for Marine Stratocumulus Clouds Armin Sorooshian, Alexander B. MacDonald, Hossein Dadashazar, Kelvin H. Bates, Matthew M. Coggon, Jill S. Craven, Ewan Crosbie, Eva-Lou Edwards, Scott P. Hersey, Natasha Hodas, Jack J. Lin, Ali Hossein Mardi, Arnaldo N. Marty, Lindsay C. Maudlin, Andrew R. Metcalf, Shane M. Murphy, Luz T. Padro, Gouri Prabhakar, Tracey A. Rissman, Joseph Schlosser, Taylor Shingler, Varuntida Varutbangkul, Zhen Wang, Roy K. Woods, Patrick Y. Chuang, Athanasios Nenes, Haflidi H. Jonsson, Richard C. Flagan, John H. Seinfeld, and Connor Stahl https://figshare.com/articles/dataset/A_Multi-Year_Data_Set_on_Aerosol-Cloud-Precipitation-Meteorology_Interactions_for_Marine_Stratocumulus_Clouds/5099983

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Short summary
Droplet number concentration is a key property of clouds, influencing a variety of cloud processes. It is also used for estimating the cloud response to aerosols. The satellite retrieval depends on a number of assumptions – different sampling strategies are used to select cases where these assumptions are most likely to hold. Here we investigate the impact of these strategies on the agreement with in situ data, the droplet number climatology and estimates of the indirect radiative forcing.