Evaluation of GPM IMERG and TRMM TMPA Precipitation Estimates in the Continental United States and Kuwait
Abstract
Satellite-based estimates of precipitation recently migrated towards using merged satellite products which utilize multiple satellite intercalibrations were developed to improve the accuracy as well as the temporal and spatial resolution. These include the TRMM Multi-Satellite Precipitation Analysis (TMPA) product and more recently, the GPM Integrated Multi-Satellite Retrievals for GPM (IMERG) which offers a higher temporal and spatial resolution along with a presumed increase in precipitation estimates. Unfortunately, due to both scientific and sensor constraints, precipitation estimates in arid environments is still problematic.
We investigated the accuracy of multiple TMPA products in varying environments (e.g., climate, elevation) by performing a statistical analysis using PRISM data from 1999-2017 in conjunction with GPM IMERG and TRMM TMPA data within these environments both in the USA and Kuwait. 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 and IMERG precipitation products and highlight the opportunities and challenges of their use in data scarce regions (e.g. Kuwait). The GPM IMERG product showed higher correlations as compared to the TMPA product, particularly in arid environments. PCC results indicate a high-degree of correlation between IMERG and PRISM (0.97), however low rainfall environments exhibit the lowest correlation (PCC: 0.83 CONUS; 0.77 Kuwait). Overall, the results corroborated findings from previous studies, highlighted the difficulty of satellite-based estimates in varying conditions, and presents preliminary research for future algorithm development for the GPM mission.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H43F2475M
- Keywords:
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- 3354 Precipitation;
- ATMOSPHERIC PROCESSESDE: 3360 Remote sensing;
- ATMOSPHERIC PROCESSESDE: 1817 Extreme events;
- HYDROLOGYDE: 1847 Modeling;
- HYDROLOGY