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Aerosol effect on the warm rain formation process: Satellite observations and modeling
Author(s) -
Suzuki Kentaroh,
Stephens Graeme L.,
Lebsock Matthew D.
Publication year - 2013
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/jgrd.50043
Subject(s) - aerosol , environmental science , satellite , meteorology , atmospheric sciences , remote sensing , geology , geography , aerospace engineering , engineering
This study demonstrates how aerosols influence the liquid precipitation formation process. This demonstration is provided by the combined use of satellite observations and global high‐resolution model simulations. Methodologies developed to examine the warm cloud microphysical processes are applied to both multi‐sensor satellite observations and aerosol‐coupled global cloud‐resolving model (GCRM) results to illustrate how the warm rain formation process is modulated under different aerosol conditions. The observational analysis exhibits process‐scale signatures of rain suppression due to increased aerosols, providing observational evidence of the aerosol influence on precipitation. By contrast, the corresponding statistics obtained from the model show a much faster rain formation even for polluted aerosol conditions and much weaker reduction of precipitation in response to aerosol increase. It is then shown that this reduced sensitivity points to a fundamental model bias in the warm rain formation process that in turn biases the influence of aerosol on precipitation. A method of improving the model bias is introduced in the context of a simplified single‐column model (SCM) that represents the cloud‐to‐rain water conversion process in a manner similar to the original GCRM. Sensitivity experiments performed by modifying the model assumptions in the SCM and their comparisons to satellite statistics both suggest that the auto‐conversion scheme has a critical role in determining the precipitation response to aerosol perturbations and also provide a novel way of constraining key parameters in the auto‐conversion schemes of global models.