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作 者:丁思聪 邱博[1] 李倩[2] DING Sicong;QIU Bo;LI Qian(School of Atmospheric Sciences,Nanjing University,Nanjing 210023,China;Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China)
机构地区:[1]南京大学大气科学学院,江苏南京210023 [2]中国科学院大气物理研究所,北京100029
出 处:《大气科学学报》2024年第5期701-712,共12页Transactions of Atmospheric Sciences
基 金:国家自然科学基金项目(42175136);中央高校基本科研业务费专项资金(14380172,14380191);关键地球物质循环前沿科学中心“科技人才团队”项目。
摘 要:评估了5种常用的土壤湿度产品(SMOS、SMAP、ESA CCI、ERA5、SMCI)在长江中下游地区的适用性,并结合气象数据分析了各产品在极端降水、干旱事件期间的时空变化特征。结果表明:5种产品都能较好地反映长江中下游地区土壤湿度空间分布特征,SMOS与其他产品相比存在普遍低估,时空变化特征与其他几种产品有一定差异。在反映土壤湿度对极端降水响应方面,SMAP、SMCI和ERA5都能反映出与异常降水变化相匹配的土壤湿度空间变化特征,而SMOS在空间上没能准确反映对降水的响应过程。在反映土壤湿度对极端干旱响应方面,SMOS和ESA CCI对极端干旱事件的响应与其他几种产品差异较大,ERA5和SMCI土壤湿度对干旱在空间上的响应较为准确。Soil moisture plays a significant role in global terrestrial water cycles and interactions between land and atmosphere,serving as a crucial factor in hydrologic and climate applications.Due to its long-term memory on time scales ranging from several weeks to months,soil moisture is valuable for weather and climate forecasts.Additionally,it profoundly influences plant photosynthesis,especially during extreme precipitation events and droughts.Accurate and continuous high-resolution soil moisture datasets are essential for analyzing the response of soil moisture to extreme events.However,in situ observations of soil moisture are inadequate due to the sparse distribution of stations,necessitating reliable datasets with fine coverage and accuracy.Three primary types of high-resolution soil moisture datasets exist:remote sensing data,reanalysis data,and machine learning-enhanced data based on ground-based observations.However,the ability of these datasets to accurately capture the responses of soil moisture to droughts and extreme precipitation events in the middle and lower reaches of the Yangtze River remains uncertain.This study assessed five soil moisture products—Soil Moisture Active Passive(SMAP),Soil Moisture and Ocean Salinity(SMOS),European Space Agency Climate Change Initiative(ESA CCI),European Reanalysis 5(ERA5),and Soil Moisture of China by in situ data(SMCI)—to investigate their accuracy in capturing the responses of soil moisture to precipitation anomalies in this region.Precipitation datasets were used to identify years with extremely dry and wet Meiyu seasons based on the standard deviations of total precipitation in June and July.Extremely dry(2013 and 2018)and wet(2016 and 2020)years were identified.The responses of the soil moisture datasets to extreme precipitation and drought events in the study area were then compared.The results showed that all five products could reflect the spatial distribution of soil moisture,but SMOS had lower values than the other products,and its spatial variations di
分 类 号:P407[天文地球—大气科学及气象学]
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