Chak-Hau Michael Tso, Eleanor Blyth, Maliko Tanguy, Peter E. Levy, Emma L. Robinson, Victoria Bell, Yuanyuan Zha, Matthew Fry
{"title":"Multi-product characterization of surface soil moisture drydowns in the UK","authors":"Chak-Hau Michael Tso, Eleanor Blyth, Maliko Tanguy, Peter E. Levy, Emma L. Robinson, Victoria Bell, Yuanyuan Zha, Matthew Fry","doi":"10.1175/jhm-d-23-0018.1","DOIUrl":null,"url":null,"abstract":"Abstract The persistence or memory of soil moisture (θ) after rainfall has substantial environmental implications. Much work has been done to study soil moisture drydown for in-situ and satellite data separately. In this work, we present a comparison of drydown characteristics across multiple UK soil moisture products, including satellite-merged (i.e. TCM), in-situ (i.e. COSMOS-UK), hydrological model (i.e. G2G), statistical model (i.e. SMUK) and land surface model (LSM) (i.e. CHESS) data. The drydown decay time scale (τ) for all gridded products are computed at an unprecedented resolution of 1-2 km, a scale relevant to weather and climate models. While their range of τ differ (except SMUK and CHESS are similar) due to differences such as sensing depths, their spatial patterns are correlated to land cover and soil types. We further analyse the occurrence of drydown events at COSMOS-UK sites. We show that soil moisture drydown regimes exhibit strong seasonal dependencies, whereby the soil dries out quicker in summer than winter. These seasonal dependencies are important to consider during model benchmarking and evaluation. We show that fitted τ based on COSMOS and LSM are well correlated, with a bias of lower τ for COSMOS. Our findings contribute to a growing body of literature to characterize τ, with the aim of developing a method to systematically validate model soil moisture products at a range of scales.","PeriodicalId":15962,"journal":{"name":"Journal of Hydrometeorology","volume":"63 1","pages":"0"},"PeriodicalIF":3.1000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrometeorology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/jhm-d-23-0018.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The persistence or memory of soil moisture (θ) after rainfall has substantial environmental implications. Much work has been done to study soil moisture drydown for in-situ and satellite data separately. In this work, we present a comparison of drydown characteristics across multiple UK soil moisture products, including satellite-merged (i.e. TCM), in-situ (i.e. COSMOS-UK), hydrological model (i.e. G2G), statistical model (i.e. SMUK) and land surface model (LSM) (i.e. CHESS) data. The drydown decay time scale (τ) for all gridded products are computed at an unprecedented resolution of 1-2 km, a scale relevant to weather and climate models. While their range of τ differ (except SMUK and CHESS are similar) due to differences such as sensing depths, their spatial patterns are correlated to land cover and soil types. We further analyse the occurrence of drydown events at COSMOS-UK sites. We show that soil moisture drydown regimes exhibit strong seasonal dependencies, whereby the soil dries out quicker in summer than winter. These seasonal dependencies are important to consider during model benchmarking and evaluation. We show that fitted τ based on COSMOS and LSM are well correlated, with a bias of lower τ for COSMOS. Our findings contribute to a growing body of literature to characterize τ, with the aim of developing a method to systematically validate model soil moisture products at a range of scales.
期刊介绍:
The Journal of Hydrometeorology (JHM) (ISSN: 1525-755X; eISSN: 1525-7541) publishes research on modeling, observing, and forecasting processes related to fluxes and storage of water and energy, including interactions with the boundary layer and lower atmosphere, and processes related to precipitation, radiation, and other meteorological inputs.