Journal
ATMOSPHERIC RESEARCH
Volume 205, Issue -, Pages 134-146Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.atmosres.2018.02.010
Keywords
Precipitation; Global Precipitation Measurement Mission; Tropical Rainfall Measurement Mission; Northern Pakistan; Atmosphere
Categories
Funding
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDA19070501]
- National Natural Science Foundation of China [41730751, 41671066]
- National Science Fund for Distinguished Youth Scholars [41625001]
- Chinese Academy of Sciences and The World Academy of Sciences (CAS-TWAS)
- [KJF-STS-ZDTP-015]
- [SKLCS-ZZ-2017]
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Recently, the Global Precipitation Measurement (GPM) mission has released the Integrated Multi-satellite Retrievals for GPM (IMERG) at a fine spatial (0.1 degrees x 0.1 degrees) and temporal (half hourly) resolutions. A comprehensive evaluation of this newly launched precipitation product is very important for satellite-based precipitation data users as well as for algorithm developers. The objective of this study was to provide a preliminary and timely performance evaluation of the IMERG product over the northern high lands of Pakistan. For comparison reference, the real-time and post real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products were also evaluated parallel to the IMERG. All of the selected precipitation products were evaluated at annual, monthly, seasonal and daily time scales using reference gauges data from April 2014 to December 2016. The results showed that: (1) the precipitation estimates from IMERG, 3B42V7 and 3B42RT products correlated well with the reference gauges observations at monthly time scale (CC = 0.93, 0.91, 0.88, respectively), whereas moderately at the daily time scale (CC = 0.67, 0.61, and 0.58, respectively); (2) Compared to the 3B42V7 and 3B42RT, the precipitation estimates from IMERG were more reliable in all seasons particularly in the winter season with lowest relative bias (2.61%) and highest CC (0.87); (3) IMERG showed a clear superiority over 3B42V7 and 3B42RT products in order to capture spatial distribution of precipitation over the northern Pakistan; (4) Relative to the 3B42V7 and 3B42RT, daily precipitation estimates from IMEREG showed lowest relative bias (9.20% vs. 21.40% and 26.10%, respectively) and RMSE (2.05 mm/day vs. 2.49 mm/day and 2.88 mm/day, respectively); and (5) Light precipitation events (0-1 mm/day) were usually overestimated by all said satellite-based precipitation products. In contrast moderate (1-20 mm/day) to heavy ( > 20 mm/day) precipitation events were underestimated by both TMPA products while IMERG was found capable to detect moderate to heavy precipitation events more precisely. Overall, the performance of IMERG was better than that of TMPA products. This preliminary evaluation of new generation of satellite-based precipitation estimates might be a useful feedback for sensor and algorithm developers as well as data users.
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