Journal
JOURNAL OF HYDROLOGY
Volume 513, Issue -, Pages 446-456Publisher
ELSEVIER
DOI: 10.1016/j.jhydrol.2014.03.040
Keywords
TRMM; Quantitative Precipitation Estimation; Verdigris River Basin; Upper Washita Basin; Global Precipitation Measurement; TMPA
Funding
- NOAA Multi-function Phased-Array Radar Project
- Responses to Climate Change program
- U.S. Army Corps of Engineers Institute for Water Resources
- South Central Climate Science Center
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This study assesses the latest version, Version 7 (V7) Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) rainfall estimates by comparison with the previous version, Version 6 (V6), for both near-real-time product (3B42RT) and post-real-time research products (3B42) over the climate-transitional zone in the southern Great Plains, USA. Two basins, the Verdigris River Basin (VRB) in the east and the Upper Washita Basin (UWB) in the west, with distinctive precipitation but similar vegetation and elevation, were selected to evaluate the TMPA products using rain gauge-blended products with WSR-88D NEXRAD Stage IV. This study sheds important insights into the detailed spatiotemporal precipitation errors, and also reveals algorithm performance during extreme events over the two low-relief basins within a high precipitation gradient zone. Based on nine years of measurements (2002-2010), this study shows that: (1) 3B42V7 corrects the widespread rainfall underestimation from research product 3B42V6, especially for the drier UWB with relative bias (RB) improvement from -23.24% to 2.24%. (2) 3B42RTV7 reduces the widespread, notable overestimation from the real-time product 3B42RTV6, with minor overestimation in the wet VRB and underestimation in the dry UWB. (3) For both versions of TMPA products, larger root mean square error (RMSE) but higher correlation coefficients (CCs) tend to appear for the wet VRB, while lower RMSE and CC mostly occur in the dry UWB. 3B42RTV7 shows a drawback that the CC declines significantly, especially in the dry region where it drops below 0.5. (4) Seasonally, autumn rainfall estimations in both versions and basins have the least bias. The 3B42RTV6 overestimation and 3B42V6 underestimation of spring and summer rainfall, which dominate the annual total bias, are significantly reduced for both basins in the V7 products. Winter precipitation estimation improvement is also noticeable with significant RB and RMSE reductions. However, considerable overestimation in summer rainfall still exists for the wet basin. (5) Although V7 has the overall best performance, it still shows deficiency in detecting extreme rainfall events in low-relief regions, tending to underestimate peak rainfall intensity and to misrepresent timing and locations. Results from this study can be used for reference in the algorithm development of the next generation of Integrated MultiSatellite Retrievals for Global Precipitation Measurement (GPM) scheduled to launch in 2014. (C) 2014 Elsevier B.V. All rights reserved.
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