Goddard Latent Heating Retrieval Algorithm for TRMM and GPM

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Abstract

The Goddard Convective-Stratiform Heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission. The CSH algorithm requires the use of a cloud-resolving model (CRM) to simulate LH profiles to build look-up tables. This paper describes the current V6 CSH and its differences/similarities versus the previous V5 CSH. Long-term CRM simulations were conducted to identify the impact of the CRM resolution and convective-stratiform separation method on LH structure/profiles. The TRMM and GPM Combined radar-radiometer algorithm-derived surface rain rates and their associated precipitation properties were the input to the CSH algorithm. CSH V6-retrieved regional LH profiles in the tropics and subtropics display the classic signatures of heating in the convective region and heating over cooling in the stratiform region. Because there is no direct measurement of LH structure, the performance of the CSH V6 algorithm is examined by comparing its vertically integrated heating (or equivalent surface rain rate) against the surface rain rate derived from the TRMM/GPM Combined algorithm. The CSH three-month and zonal mean equivalent surface rain rates are in good agreement with the Combined rain rates over the Inter Tropical Convergence Zone region; the agreement is best over the ocean. CSH three-month and zonal mean equivalent surface rain rates are larger than the Combined rain rates over land in both the tropics and subtropics. CSH three-month mean equivalent surface rain rates also have local differences with the Combined rain rates that can be smoothed by area averaging to larger horizontal resolutions (from the CSH standard grid of 0.25° × 0.25° to 0.5° × 0.5° or 1.0° × 1.0°). CSH equivalent surface rain rates have more light rain rates but less larger rates compared to the GPM Combined surface rain rates.

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APA

Tao, W. K., Lang, S., Iguchi, T., & Song, Y. (2022). Goddard Latent Heating Retrieval Algorithm for TRMM and GPM. Journal of the Meteorological Society of Japan, 100(2), 293–320. https://doi.org/10.2151/jmsj.2022-015

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