Abstract

Satellite precipitation estimation provides crucial information for those places lacking rainfall observations from ground–based sensors, especially in terrestrial or marine areas with complex climatic or topographic conditions. This is the case over much of Western China, including Upper and Middle Lancang River Basin (UMLRB), an extremely important transnational river system in Asia (the Lancang–Mekong River Basin) with complex climate and topography that has limited long–term precipitation records and high–elevation data, and no operational weather radars. In this study, we evaluated three GPM IMERG satellite precipitation estimation (IMERG E, IMERG L and IMERG F) over UMLRB in terms of multi–year average precipitation distribution, amplitude consistency, occurrence consistency, and elevation–dependence in both dry and wet seasons. Results demonstrated that monsoon and solid precipitation mainly affected amplitude consistency of precipitation, aerosol affected occurrence consistency of precipitation, and topography and wind–induced errors affected elevation dependence. The amplitude and occurrence consistency of precipitation were best in wet seasons in the Climate Transition Zone and worst in dry seasons in the same zone. Regardless of the elevation–dependence of amplitude or occurrence in dry and wet seasons, the dry season in the Alpine Canyon Area was most positively dependent and most significant. More significant elevation–dependence was correlated with worse IMERG performance. The Local Weighted Regression (LOWERG) model showed a nonlinear relationship between precipitation and elevation in both seasons. The amplitude consistency and occurrence consistency of both seasons worsened with increasing precipitation intensity and was worst for extreme precipitation cases. IMERG F had great potential for application to hydroclimatic research and water resources assessment in the study area. Further research should assess how the dependence of IMERG’s spatial performance on climate and topography could guide improvements in global precipitation assessment algorithms and the study of mountain landslides, floods, and other natural disasters during the monsoon period.

Highlights

  • Precipitation is the result of the comprehensive influence of geographical location, atmospheric circulation, weather system conditions and other factors at multiple levels and scales [1,2,3,4,5,6]

  • IMERG accurately captured the distribution of precipitation in the dry and wet seasons in different horizontal spaces within Upper and Middle Lancang River Basin (UMLRB)

  • We divided the UMLRB into climatic and topographic zones by relevant features to assess the performance of Global Precipitation Measurement (GPM) in this region from three aspects; this is the first study to evaluate the spatial performance of IMERG under complex climatic and topographic conditions

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Summary

Introduction

Precipitation is the result of the comprehensive influence of geographical location, atmospheric circulation, weather system conditions and other factors at multiple levels and scales [1,2,3,4,5,6]. High–resolution, and continuous spatiotemporal coverage of precipitation data is very important for hydrological process simulation, remote sensing & climate research, water resources management and allocation, and disaster monitoring [7,8]. Finding suitable alternative sources of precipitation data and studying the spatial performance of data in regions with complex climatic and topographic conditions is a hotspot in hydrological remote sensing research as well as a challenge for water resources assessments and management under complex conditions in future. The Global Precipitation Measurement (GPM) mission was launched by NASA and JAXA on 28 February 2014 to obtain accurate global precipitation data from geostationary satellites (GEO) making full use of visible infrared (VIS–IR), passive microwave sensors (PMW) and low–orbit (LEO) satellite radar [12,13,14].

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