| Weather and Climate Extremes | |
| Performance evaluation of ERA-5, JRA-55, MERRA-2, and CFS-2 reanalysis datasets, over diverse climate regions of Pakistan | |
| Waheed Ullah1  Xieyao Ma2  Muhammad Arshad3  Irfan Ullah4  Jun Yin5  Mengyang Liu5  | |
| [1] Corresponding author.;Pakistan Meteorological Department, Sector H-8/2, Islamabad, 44000, Pakistan;School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China;School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing, 210044, China;School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing, 210044, China; | |
| 关键词: Evaluation; Reanalysis; Precipitation products; Extreme events; Pakistan; | |
| DOI : | |
| 来源: DOAJ | |
【 摘 要 】
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.
【 授权许可】
Unknown