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  • Author or Editor: Ying Dai x
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Zhiguo Yue
Daniel Rosenfeld
Guihua Liu
Jin Dai
Xing Yu
Yannian Zhu
Eyal Hashimshoni
Xiaohong Xu
Ying Hui
, and
Oliver Lauer


The advent of the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi NPP (SNPP) satellite made it possible to retrieve a new class of convective cloud properties and the aerosols that they ingest. An automated mapping system of retrieval of some properties of convective cloud fields over large areas at the scale of satellite coverage was developed and is presented here. The system is named Automated Mapping of Convective Clouds (AMCC). The input is level-1 VIIRS data and meteorological gridded data. AMCC identifies the cloudy pixels of convective elements; retrieves for each pixel its temperature T and cloud drop effective radius r e ; calculates cloud-base temperature T b based on the warmest cloudy pixels; calculates cloud-base height H b and pressure P b based on T b and meteorological data; calculates cloud-base updraft W b based on H b ; calculates cloud-base adiabatic cloud drop concentrations N d,a based on the T–r e relationship, T b , and P b ; calculates cloud-base maximum vapor supersaturation S based on N d,a and W b ; and defines N d,a /1.3 as the cloud condensation nuclei (CCN) concentration N CCN at that S. The results are gridded 36 km × 36 km data points at nadir, which are sufficiently large to capture the properties of a field of convective clouds and also sufficiently small to capture aerosol and dynamic perturbations at this scale, such as urban and land-use features. The results of AMCC are instrumental in observing spatial covariability in clouds and CCN properties and for obtaining insights from such observations for natural and man-made causes. AMCC-generated maps are also useful for applications from numerical weather forecasting to climate models.

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