Spectral retrieval of latent heating profiles from TRMM PR Data: Comparisons of lookup tables from two- and three-dimensional simulations
Shoichi Shige, Department of Aerospace Engineering, Osaka Prefecture University, Japan
The Spectral Latent Heating (SLH) algorithm has been developed to estimate cooling/heating rate profiles for TRMM PR satellite data. The method uses precipitation top height (PTH), precipitation rates at the surface and melting level, and rain type to select profiles from lookup tables. Lookup tables for the three rain types-convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)-were derived from numerical simulations of tropical cloud systems from TOGA-COARE utilizing a cloud-resolving model (CRM). The SLH-retrieved are in good agreement with sounding-based ones from Johnson and Ciesielski (2002). Differences in profiles between the western Pacific and Atlantic estimated by the SLH algorithm are also consistent with those from previous budget studies. The availability of exponentially increasing computer capabilities has resulted in three-dimensional ("3D") CRM simulations for multiday periods with large horizontal domains. In this study, we compare performance of the SLH algorithm using look-up tables from two- and three-dimensional CRM simulations using the Goddard Cumulus Ensemble (GCE) model. Although real clouds and cloud systems are three-dimensional, a 3D CRM does not automatically give a more realistic simulation than a 2D one. This is because the results of the simulation depend very strongly on incomplete and uncertain parameterizations of ice-microphysical processes.
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