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 ζ 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 ω 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

Comparison of TRMM Rain-Rate Retrievals in Tropical Cyclones

“…These grid points make it relatively easy for all products to converge on the same answer. While developing a new TMI-based rain rate retrieval algorithm, Prabhakara et al (2008) compared TMI 2A12 and PR 2A25 for twenty tropical oceanic cases, after averaging to a 20 km x 20 km grid. Linear correlation coefficients ranged from 0.51 to 0.83 for the individual cases, generally consistent with the correlations in this study.…”

Estimation of Crop-coefficients and Evapotranspiration of Field Pea (Pisum sativum L.) Using Lysimeter and Empirical Models under Temperate Climate

“…Peas can tolerate temperatures ranging from 7 to 30°C in higher tropical altitudes [10]. Being a winter crop, peas can withstand relatively low temperatures, especially during the early stages of growth, but may not survive severe and prolonged frost [11]. To estimate evapotranspiration accurately, it is essential to develop crop coefficients (Kc) for different models.…”