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Parametrizing the horizontal inhomogeneity of ice water content using CloudSat data products
Author(s) -
Hill Peter G.,
Hogan Robin J.,
Manners James,
Petch Jon C.
Publication year - 2012
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.1893
Subject(s) - parametrization (atmospheric modeling) , cloud fraction , standard deviation , water content , cloud computing , environmental science , scale (ratio) , cloud physics , overcast , radiative transfer , mathematics , meteorology , computer science , statistics , geology , physics , cloud cover , geotechnical engineering , quantum mechanics , sky , operating system
In order to calculate unbiased microphysical and radiative quantities in the presence of a cloud, it is necessary to know not only the mean water content but also the distribution of this water content. This article describes a study of the in‐cloud horizontal inhomogeneity of ice water content, based on CloudSat data. In particular, by focusing on the relations with variables that are already available in general circulation models (GCMs), a parametrization of inhomogeneity that is suitable for inclusion in GCM simulations is developed. Inhomogeneity is defined in terms of the fractional standard deviation (FSD), which is given by the standard deviation divided by the mean. The FSD of ice water content is found to increase with the horizontal scale over which it is calculated and also with the thickness of the layer. The connection to cloud fraction is more complicated; for small cloud fractions FSD increases as cloud fraction increases while FSD decreases sharply for overcast scenes. The relations to horizontal scale, layer thickness and cloud fraction are parametrized in a relatively simple equation. The performance of this parametrization is tested on an independent set of CloudSat data. The parametrization is shown to be a significant improvement on the assumption of a single‐valued global FSD. Copyright © 2012 Royal Meteorological Society and British Crown Copyright, the Met Office