Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part III: Estimating Apparent Moisture Sink Profiles over Tropical Oceans

• Published in: Journal of applied meteorology (1988) 2008-02, Vol.47 (2), p.620-640
• Main Authors: Shige, Shoichi, Takayabu, Yukari N., Tao, Wei-Kuo
• Format: Article
• Language: English
• Subjects: Algorithms; Anvils; Atmosphere; Budgeting; Drying; Earth, ocean, space; Estimates; Exact sciences and technology; External geophysics; Geophysics. Techniques, methods, instrumentation and models; Heating; Marine; Mathematical models; Melting; Meteorology; Meteors; Moisture; Oceans; Precipitation; Radar; Rain; Retrieval; Scale models; Togas; Tropical regions; Water in the atmosphere (humidity, clouds, evaporation, precipitation); Water vapor
• ISSN: 1558-8424; 0894-8763; 1558-8432; 1520-0450
• DOI: 10.1175/2007jamc1738.1

The spectral latent heating (SLH) algorithm was developed to estimate apparent heat source (Q₁) profiles for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in Parts I and II of this study. In this paper, the SLH algorithm is used to estimate apparent moisture sink (Q₂) profiles. The procedure ofQ₂ retrieval is the same as that of heating retrieval except for using theQ₂ profile lookup tables derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere (TOGA) Coupled Ocean–Atmosphere Response Experiment (COARE) utilizing a cloud-resolving model (CRM). TheQ₂ profiles were reconstructed from CRM-simulated parameters with the COARE table and then compared with CRM-simulated “true”Q₂ profiles, which were computed directly from the water vapor equation in the model. The consistency check indicates that discrepancies between the SLH-reconstructed and CRM-simulated profiles forQ₂, especially at low levels, are larger than those forQ₁ and are attributable to moistening for the nonprecipitating region that SLH cannot reconstruct. Nevertheless, the SLH-reconstructed totalQ₂ profiles are in good agreement with the CRM-simulated ones. The SLH algorithm was applied to PR data, and the results were compared withQ₂ profiles derived from the budget study. Although discrepancies between the SLH-retrieved and sounding-based profiles forQ₂ for the South China Sea Monsoon Experiment (SCSMEX) are larger than those for heating, key features of the vertical profiles agree well. The SLH algorithm can also estimate differences ofQ₂ between the western Pacific Ocean and the Atlantic Ocean, consistent with the results from the budget study.