A Method to Estimate Rain Rate over Tropical Oceans with the TRMM Microwave Imager Radiometer

Abstract

In this preliminary study, we have developed a method to retrieve rain rate on a scale of 20 km from the brightness temperatures measured by the TRMM microwave imaging radiometer (TMI) over the tropical oceans, using the estimates of rain rate R_PR made by the TRMM Precipitation Radar (PR) as a benchmark. The purpose of this study is to demonstrate with a limited amount of PR and TMI data the feasibility of improving the TRMM operational rain retrieval method V6 over the tropical oceans. This study utilizes the TMI-measured brightness temperatures T_19H, T_37H, and T_85H of horizontally polarized microwave radiances at 19, 37 and 85 GHz, respectively, to deduce a salient non-linear parameter ξ that is highly correlated with R_PR over the oceans. Two additional parameters generated from TMI data, ω and γ, add significant amounts of rain information to our retrieval method. The parameter &omega is based on T_19V and T_21V, the brightness temperatures measured by TMI for vertically polarized microwave radiances at 19 and 21 GHz respectively. This parameter takes advantage of the independent information contained in T_21V. The parameter Γ depends on the average horizontal gradient of the TMI-measured T_85V (vertically-polarized 85 GHz radiance) in a 20 km footprint. Initially our TMI rain retrieval algorithm is tuned with the help of R_PR for seven cases of 2° × 3° area over tropical oceans. Then it is applied to 13 other independent tropical ocean cases. For these independent cases, the rain rate R* estimated from our method correlates better with R_PR than the rain rate R_V6 retrieved from the present TMI V6 operational retrieval method. On a 20 km scale, the correlation between R_PR and R* is better by about 6% compared to that between R_PR and R_V6. The slope of the regression line between the rain rates R_PR and R_V6 is about 0.5. With respect to R_PR, the rain rate R_V6 retrieved from operational V6 method tends to underestimate high rain rates and overestimate low rain rates. The slope of the regression line between R_PR and the rain rate R* retrieved with our method is about 0.8, another indication of the improvement of R* over R_V6. In addition, the area average rain rate on a scale of 2° × 3° deduced from our method agrees better with that of PR by about 7%.