Evaluation of Multiple Precipitation Products in the Hainan Island

Abstract

Global precipitation observations have been realized through the development of satellite remote-sensing technology. However, there is a lack of evaluation of remote-sensing precipitation products in complex tropical island terrains. This study used hourly rain gauge data to conduct a multi-scale systematic evaluation of common precipitation products, such as CMORPH, CHIRPS, GsMAP, GPM, MSWEP, ERA5-Land, and PERSIANN, over Hainan Island, providing an in-depth analysis of the precipitation detection capabilities of various products in this region. The main conclusions are: (1) In a multi-temporal scale evaluation, GPM and GsMAP outperformed the other products across all time scales. On a 3-hour scale, GPM and GsMAP showed the highest correlation coefficients (0.53 and 0.52, respectively). On a daily scale, except for PERSIANN, all products showed correlation coefficients above 0.56, with GPM and GsMAP showing the best performance (R = 0.73 and 0.74, respectively). (2) In comparing annual precipitation, Hainan Island's average-annual precipitation over the past 20 years showed a fluctuating trend, with a mean of 1,776.4 mm/a. The CMORPH annual average of 1,765.1 mm/a was the closest to the CHM-PRE dataset, with minimal error. ERA5-Land and MSWEP significantly overestimated (2,504.3 mm/a) and underestimated (1,662.2 mm/a) the average-annual precipitation, respectively. (3) Spatial distribution pattern analysis revealed that the observed multi-year annual precipitation in Hainan Island ranges from 996.9 to 2,368.9 mm, exhibiting an annular-distribution pattern with higher precipitation in the east than in the west and the southwestern mountainous areas than in the northeastern plains. The precipitation range of 1,337.9‒2,287.0 mm observed in GsMAP was the closest to the rain gauge data and particularly matched that of the high-value center in the southeast of the island. (4) In a precipitation trend analysis, CMORPH, ERA5-Land, GPM, MSWEP, CHIRPS, and PERSIANN showed an increasing trend in local areas of Hainan Island, while GsMAP showed a stronger increasing trend. (5) In an analysis of extreme precipitation events, GsMAP, CMORPH, and GPM reproduced the spatiotemporal evolution of extreme precipitation events on a daily scale in Hainan relatively well. GPM better reproduced the spatial and temporal evolution characteristics of typhoon precipitation events in Hainan Island. However, the accuracy of the precipitation estimation still requires improvement. The results of this study not only contribute to our understanding of precipitation products applicable to Hainan but also provide insights for improving satellite-based precipitation products in tropical island environments. These findings underscore the importance of regional validation and the potential of multi-product fusion approaches for enhancing precipitation estimates in complex terrains.

Keywords

• spatial-temporal patterns
• extreme precipitation events
• climate change
• multi-scale
• hainan island