{"title":"Variational Assimilation of the SMAP Surface Soil Moisture Retrievals into an Integrated Urban Land Model","authors":"Ch. Meng, H. Li, J. Cui","doi":"10.3103/s1068373924060037","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Soil moisture is a key parameter in land surface modeling. In this study, a variational data assimilation algorithm was applied to an integrated urban land model (IUM) to assimilate the NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture product. The 10 cm soil moisture data observed in situ at eight sites was used for validation. A very simple analytical algorithm was developed to characterize the error weighting matrix in the cost function. The results indicated that with assimilation, the simulation results of the surface volumetric soil moisture improved in almost the whole research region as compared with the SMAP data. In most of the time periods, accuracy of simulated surface volumetric soil moisture increased. With assimilation, as compared with the observations at eight sites, the 10 cm volumetric soil moisture improved over the whole research time period.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":"24 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Meteorology and Hydrology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.3103/s1068373924060037","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Soil moisture is a key parameter in land surface modeling. In this study, a variational data assimilation algorithm was applied to an integrated urban land model (IUM) to assimilate the NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture product. The 10 cm soil moisture data observed in situ at eight sites was used for validation. A very simple analytical algorithm was developed to characterize the error weighting matrix in the cost function. The results indicated that with assimilation, the simulation results of the surface volumetric soil moisture improved in almost the whole research region as compared with the SMAP data. In most of the time periods, accuracy of simulated surface volumetric soil moisture increased. With assimilation, as compared with the observations at eight sites, the 10 cm volumetric soil moisture improved over the whole research time period.
期刊介绍:
Russian Meteorology and Hydrology is a peer reviewed journal that covers topical issues of hydrometeorological science and practice: methods of forecasting weather and hydrological phenomena, climate monitoring issues, environmental pollution, space hydrometeorology, agrometeorology.