Comparing the performance of high-resolution global precipitation products across topographic and climatic gradients of Central Asia

International Journal of Climatology(2022)

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摘要
Accurate and reliable precipitation data with high spatial and temporal resolution are essential in studying climate variability, water resources management, and hydrological forecasting. A range of global precipitation data are available to this end, but how well these capture actual precipitation remains unknown, particularly for mountain regions where ground stations are sparse. We examined the performance of three global high-resolution precipitation products for capturing precipitation over Central Asia, a hotspot of climate change, where reliable precipitation data are particularly scarce. Specifically, we evaluated MSWEP, CHIRPS, and GSMAP against independent gauging stations for the period 1985-2015. Our results show that MSWEP and CHIRPS outperformed GSMAP for wetter periods (i.e., winter and spring) and wetter locations (150-600 mm center dot year(-1)), lowlands, and mid-altitudes (0-3,000 m), and regions dominated by winter and spring precipitation. MSWEP performed best in representing temporal precipitation dynamics and CHIRPS excelled in capturing the volume and distribution of precipitation. All precipitation products poorly estimated precipitation at higher elevations (>3,000 m), in drier areas (<150 mm), and in regions characterized by summer precipitation. All products accurately detected dry spells, but their performance decreased for wet spells with increasing precipitation intensity. In sum, we find that CHIRPS and MSWEP provide the most reliable high-resolution precipitation estimates for Central Asia. However, the high spatial and temporal heterogeneity of the performance call for a careful selection of a suitable product for local applications considering the prevailing precipitation dynamics, climatic, and topographic conditions.
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关键词
climate change, green water, Kazakhstan, Kyrgyzstan, satellite imagery, Tajikistan, Turkmenistan, Uzbekistan, validation, water resources
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