多源遥感降水产品在西北干旱区的气象干旱性能评估OA北大核心CSTPCD

Multisource remote-sensing precipitation products play an important role in drought monitoring in re-gions with few or uneven meteorological stations,such as arid areas in northwest China.In this study,five sets of typical remote-sensing precipitation products(PERSIANN,CHIRPS,CMORPH,TMPA,and MSWEP)were se-lected.The meteorological drought performance of the precipitation products at three timescales was evaluated based on the standardized precipitation evapotranspiration index(SPEI).The capability of remote-sensing precipi-tation products to capture drought events was explained by identifying drought events using the run-course theo-ry.The results showed the following:(1)In arid northwest China,the five sets of remote-sensing precipitation products could capture the spatial distribution pattern of annual mean precipitation well,but it was difficult to ac-curately capture the change trend of precipitation.(2)MSWEP had the best performance in capturing SPEI,fol-lowed by TMPA,PERSIANN,and CHIRPS,and CMORPH had the worst performance.SPEI1 was the best tim-escale for remote-sensing precipitation products to identify meteorological droughts.(3)CHIRPS had the best rec-ognition capability for several drought events,whereas PERSIANN had the worst.MSWEP and TMPA were the best indicators of drought severity,whereas CHIRPS was the worst.Except for CMORPH,the other four sets of products captured the intensity and extreme values of the drought events well.In summary,although the five sets of remote-sensing precipitation products could capture the drought characteristics of the northwest arid region on the whole,finding a precipitation product with the best performance in all aspects of capturing drought character-istics was difficult because of the impact of the inversion algorithm of falling aquatic products,terrain complexi-ty,and density of ground verification stations.The results of this study can provide a reference for the selection of the best precipitation products for regional meteorological drought monitoring and for the improvement of re-mote-sensing precipitation products in the inversion algorithm of extreme drought environments.