Rainstorms are one of the extreme rainfall events that cause serious disasters,such as urban flooding and mountain torrents.Traditional studies have used rain gauge observations to analyze rainstorm events,but relevan...Rainstorms are one of the extreme rainfall events that cause serious disasters,such as urban flooding and mountain torrents.Traditional studies have used rain gauge observations to analyze rainstorm events,but relevant information is usually missing in gauge-sparse areas.Satellite-derived precipitation datasets serve as excellent supplements or substitutes for the gauge observations.By developing a grid-based rainstorm-identification tool,we used the Tropical Rainfall Measurement Mission(TRMM)Multi-satellite Precipitation Analysis(TMPA)time series product to reveal the spatial and temporal variabilities of rainstorms over China during 1998–2017.Significant patterns of both increasing and decreasing rainstorm occurrences were detected,with no spatially uniform trend being observed across the whole country.There was an increase in the area being affected by rainstorms during the 20-year period,with rainstorm centers shifting along the southwest–northeast direction.Rainstorm occurrence was found to be correlated with local total precipitation.By comparing rainstorm occurrence with climate variables such as the El Ni?o-Southern Oscillation and Pacific Decadal Oscillation,we also found that climate change was likely to be the primary reason for rainstorm occurrence in China.This study complements previous studies that used gauge observations by providing a better understanding of the spatiotemporal dynamics of China’s rainstorms.展开更多
基金National Key Research and Development Program of China,No.2017YFC1502501,No.2017YFC0404302National Natural Science Foundation of China,No.41501460。
文摘Rainstorms are one of the extreme rainfall events that cause serious disasters,such as urban flooding and mountain torrents.Traditional studies have used rain gauge observations to analyze rainstorm events,but relevant information is usually missing in gauge-sparse areas.Satellite-derived precipitation datasets serve as excellent supplements or substitutes for the gauge observations.By developing a grid-based rainstorm-identification tool,we used the Tropical Rainfall Measurement Mission(TRMM)Multi-satellite Precipitation Analysis(TMPA)time series product to reveal the spatial and temporal variabilities of rainstorms over China during 1998–2017.Significant patterns of both increasing and decreasing rainstorm occurrences were detected,with no spatially uniform trend being observed across the whole country.There was an increase in the area being affected by rainstorms during the 20-year period,with rainstorm centers shifting along the southwest–northeast direction.Rainstorm occurrence was found to be correlated with local total precipitation.By comparing rainstorm occurrence with climate variables such as the El Ni?o-Southern Oscillation and Pacific Decadal Oscillation,we also found that climate change was likely to be the primary reason for rainstorm occurrence in China.This study complements previous studies that used gauge observations by providing a better understanding of the spatiotemporal dynamics of China’s rainstorms.
