Response of soil moisture to extreme climate events based on various data-sets
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.Ad-ditionally,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 dis-tribution 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 ac-curately capture the responses of soil moisture to droughts and extreme precipitation events in the middle and low-er 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 dis-tribution of soil moisture,but SMOS had lower values than the other products,and its spatial variations differed somewhat from the others.SMAP,SMCI,and ERA5 reasonably captured the responses of soil moisture to extreme precipitation,while SMOS did not accurately reflect these responses.The responses of SMOS and ESA CCI soil moisture to extreme drought events differed from the other products,whereas ERA5 and SMCI demonstrated more accurate spatial responses to drought conditions.Overall,while all five products provided reasonable spatial distributions of soil moisture over the study area,their performances in capturing response to climate extremes varied substantially.Therefore,the accuracy of these datasets needs to be evaluated under different conditions,especially during droughts and extreme precipitation e-vents.This study enhances our understanding of soil moisture variations in the middle and lower reaches of the Yangtze River and guides the use of various soil moisture datasets for examining responses to climatic extremes.
万方数据
维普
