4.6 Article

Performance evaluation of ERA-5, JRA-55, MERRA-2, and CFS-2 reanalysis datasets, over diverse climate regions of Pakistan

期刊

WEATHER AND CLIMATE EXTREMES
卷 33, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.wace.2021.100373

关键词

Evaluation; Reanalysis; Precipitation products; Extreme events; Pakistan

资金

  1. National Natural Science Foundation of China [41877158]
  2. Jiangsu distinguished faculty program, China
  3. Pakistan Meteorological Department (PMD), Pakistan
  4. World Meteorological Organization (WMO), Switzerland

向作者/读者索取更多资源

Reanalysis precipitation products (RPPs) from different sources were evaluated for their performance in capturing precipitation intensity and extreme events over Pakistan. ERA-5 showed the best performance at both daily and monthly scales, while MERRA-2 had limitations in detecting extreme precipitation events. These findings can assist researchers in selecting reliable datasets for hydrological studies and applications in flood and drought prediction.
Reanalysis precipitation products (RPPs) are frequently used for studying the water cycle changes from short to long-term scale globally. In the current study, ERA-5 produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), the Japanese 55-year Reanalysis (JRA-55), the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), and the Climate Forecast System version 2 (CFS-2) precipitation products were evaluated with the rain-gauge data as a reference during 1981-2019 over Pakistan. The performance was assessed using statistical error metrics on daily, monthly, and annual timescales. The reanalysis precipitation products (RPPs) captured the precipitation intensities and the extreme precipitation events (75th to 99th percentile) across climatic classes. On a daily scale, the ERA-5 follows rain-gauges very closely (RC: 0.67, R: 0.81, RMSE: 1.69 mm), consistently capturing the precipitation intensities (light to violent) and extreme precipitation events (95th percentile), followed by CFS-2. The MERRA-2 captured precipitation intensity but did not detect extreme precipitation events in some regions. The JRA-55 produced good results in the central area while overestimated the precipitation in the northern and southern parts of the study area. On a monthly time scale, ERA-5 performed well as compared to the rest of RPPs, with regression coefficient values of 0.91, correlation coefficient (0.96), and a lower value of RMSE (11.09 mm), followed by JRA-55, MERRA-2, and CFS-2. All the RPPs performed better in winter, pre-monsoon, and post-monsoon seasons with slight deviations/differences, but in monsoon season, the ERA-5 and JRA-55 (MERRA-2, CFS-2) overestimated (underestimated) precipitation mean. The findings can help the researchers select reliable datasets for bias correction of the projections and real-time application in flood, drought estimation, and prediction.

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