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Documenting hydrometeor layer occurrence within International Satellite Cloud Climatology Project-defined cloud classifications using CLOUDSAT and CALIPSO

Posted on:2013-05-13Degree:M.SType:Thesis
University:The University of UtahCandidate:Wrenn, ForrestFull Text:PDF
GTID:2458390008983182Subject:Atmospheric Sciences
Abstract/Summary:
The multi-decadal and global International Satellite Cloud Climatology Project (hereafter ISCCP) dataset has proven invaluable to the modeling community. ISCCP provides information only on the effective radiative top of cloud layers in a vertical column and the column-integrated optical depth. The effective radiative cloud top has been used to characterize cloudy pixels in terms of certain morphological types even though this is known to be inaccurate. In the presence of multiple clouds layers, such as cirrus over boundary layer clouds, the effective radiative cloud top may have little to do with the geometric distribution of hydrometeor layers. This ambiguity in the presence of multiple cloud layers leads to possible misinterpretations of ISCCP statistics when cast into the traditional cloud top pressure-optical depth classifications. CloudSat and CALIPSO provide detailed information regarding the vertical structure of clouds layers but on a much coarser temporal and spatial grid. Therefore, we use the detailed information from CloudSat and CALIPSO to document the actual distribution of cloud layers within the ISCCP cloud classifications. Cloud properties provided from CloudSat and CALIPSO combined with atmospheric state data from ECMWF and column optical depth from MODIS are input into an ISCCP simulator code to provide ISCCP-like cloud top pressures and the active remote sensing data are used to explore the vertical structure of cloud and precipitation layers within the standard nine ISCCP cloud top pressure--optical depth classifications. We will show that ISCCP-defined "types" defy a simple interpretation and are often ambiguous within a region and entirely nonunique between regions calling into question recent results that attempt to use ISCCP global statistics to evaluate model results.
Keywords/Search Tags:Cloud, ISCCP, Classifications
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