On the role of warm rain clouds in the tropics
Date
2008
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Abstract
A combined optimal estimation retrieval algorithm has been developed for warm rain clouds using Tropical Rainfall Measuring Mission (TRMM) satellite measurements. The algorithm uses TRMM Microwave Imager (TMI) brightness temperatures that have been deconvolved to the 19-GHz field-of-view (FOV) to retrieve cloud liquid water path (LWP), total precipitable water, and wind speed. Resampling the TMI measurements to a common FOV is found to decrease retrieved LWP by 30%. These deconvolved brightness temperatures are combined with cloud fraction from the Visible Infrared Scanner (VIRS) to overcome the beam-filling effects and with rainwater estimates from the TRMM Precipitation Radar (PR). This algorithm is novel in that it takes into account the water in the rain and retrieves the LWP due to only the cloud water in a raining cloud, thus allowing the investigation of the effects of precipitation on cloud properties. The uncertainties due to forward model parameters and assumptions are computed and range from 1.7 K at 10 GHz to about 6K at the 37 and 85 GHz TMI channels. Examination of the sensitivities in the LWP retrieval shows that the cloud fraction information increases the retrieved LWP with decreasing cloud fraction and that the PR rainwater reduces retrieved LWP. Retrieval algorithm results from December 2005 to January 2006 show that warm rain cloud LWP and the ratio of warm rain cloud LWP to rainwater both decrease by 50% over sea surface temperatures (SST) ranging from 292 to 302 K in the tropical western Pacific due to increased precipitation efficiency depleting more of the cloud water at higher SSTs. The LWP retrieval developed in this study is also applied to study the influence of warm rain clouds on atmospheric preconditioning for deep convection associated with tropical depression-type disturbances (TDs). Results show that positive warm rain cloud LWP anomalies occur with positive low-level moistening and heating anomalies prior to TD events, but that there is little variation in the properties of non-raining clouds. The moistening by these clouds is also shown to influence the generation of convective available potential energy (CAPE) prior to deep convection.
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Subject
cloud fraction
precipitation
rain clouds
tropics
atmospheric sciences
environmental science