Spectral retrieval of latent heating profiles from TRMM PR data. Part IV: comparisons of lookup tables from two-and three-dimensional cloud-resolving model simulations

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Abstract

The spectral latent heating (SLH) algorithm was developed to estimate latent heating profiles for the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR). The method uses TRMM PR information (precipitation-top height, precipitation rates at the surface and melting level, and rain type) to select heating profiles from lookup tables (LUTs). LUTs 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 the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) using a cloud-resolving model (CRM). The two-dimensional (2D) CRM was used in previous studies. The availability of exponentially increasing computer capabilities has resulted in three-dimensional (3D) CRM simulations for multiday periods becoming increasingly prevalent. In this study, LUTs from the 2D and 3D simulations are compared. Using the LUTs from 3D simulations results in less agreement between the SLH-retrieved heating and sounding-based heating for the South China Sea Monsoon Experiment (SCSMEX). The level of SLH-estimated maximum heating is lower than that of the sounding-derived maximum heating. This is explained by the fact that using the 3D LUTs results in stronger convective heating and weaker stratiform heating above the melting level than is the case if using the 2D LUTs. More condensate is generated in and carried from the convective region in the 3D model than in the 2D model, and less condensate is produced by the stratiform region's own upward motion. © 2009 American Meteorological Society.

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Shige, S., Takayabu, Y. N., KIDA, S., Tao, W. K., Zeng, X., Yokoyama, C., & L’ecuyer, T. (2009). Spectral retrieval of latent heating profiles from TRMM PR data. Part IV: comparisons of lookup tables from two-and three-dimensional cloud-resolving model simulations. Journal of Climate, 22(20), 5577–5594. https://doi.org/10.1175/2009JCLI2919.1

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