T190 Satellite Remote Sensing Applications in Hydrology and Geology
Tuesday, 3 November 2015
8:00 AM - 12:00 PM
Room 341
AN ANALYSIS OF GPM IMERG AND TRMM TMPA PRECIPITATION ESTIMATES IN VARYING ENVIRONMENTS
Paper number: T190-8
Program: Technical Sessions
Time: 9:50 AM – 10:05 AM
Authors
-
Racha El KadiriMiddle Tennessee State University, Murfreesboro, TN
-
Wondwosen M. SeyoumUniversity of Georgia, Athens, GA
-
Michael C. DurhamUniversity of Georgia, Athens, GA
-
Veronica FayUniversity of Georgia, Athens, GA
-
Khalil LezzaikUniversity of Georgia, Athens, GA
-
Rachel R. RotzUniversity of Georgia, Athens, GA
-
Audrey FisherUniversity of Georgia, Athens, GA
-
Matthew CahalanUniversity of Georgia, Athens, GA
Abstract
We investigated the accuracy of multiple TMPA products in varying environments (e.g., rainfall, elevation) by performing a statistical analysis using over 200 rain gauges spanning a ten year period. In addition, we provide a first look at the skill of the GPM IMERG products within these environments compared to the field gauges and previous generation product (e.g., TMPA). We analyzed the overall correlation using standard statistical measures (e.g., Pearson Correlation Coefficient, Percent Bias, Mean Absolute Error) and precipitation specific indices (e.g., Probability of Detection, False Alarm Ratio, Heidke Skill Score).
Results demonstrate the accuracy of TMPA precipitation products and highlight the opportunities and challenges of their use in data scarce regions (e.g. Morocco; MENA). Specifically, the research products outperform the real-time products in all environments within the study areas, and the newest algorithm development (3B42 V7) outperforms the previous version (V6), particularly in the low rainfall and high elevation environments. Most notably, TMPA products continue to overestimate precipitation in arid environments and underestimate in high elevation areas. Moreover, a statistically significant temporal discrepancy was found in all of the analyzed products. The GPM IMERG product showed higher correlations though only one year of data was analyzed at this time. Overall, the results corroborated findings from previous studies, highlighted the difficulty of TMPA products in varying conditions, and presented preliminary research for future algorithm development for the GPM mission.