Multiproduct characterization of surface soil moisture drydowns in the United Kingdom

Tso, Chak-Hau Michael ORCID: https://orcid.org/0000-0002-2415-0826; Blyth, Eleanor ORCID: https://orcid.org/0000-0002-5052-238X; Tanguy, Maliko ORCID: https://orcid.org/0000-0002-1516-6834; Levy, Peter E. ORCID: https://orcid.org/0000-0002-8505-1901; Robinson, Emma L. ORCID: https://orcid.org/0000-0002-3746-4517; Bell, Victoria ORCID: https://orcid.org/0000-0002-0792-5650; Zha, Yuanyuan; Fry, Matthew ORCID: https://orcid.org/0000-0003-1142-4039. 2023 Multiproduct characterization of surface soil moisture drydowns in the United Kingdom. Journal of Hydrometeorology, 24 (12). 2299-2319. 10.1175/JHM-D-23-0018.1

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Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1175/JHM-D-23-0018.1
UKCEH and CEH Sections/Science Areas:	Atmospheric Chemistry and Effects (Science Area 2017-) Hydro-climate Risks (Science Area 2017-) Pollution (Science Area 2017-) Water Resources (Science Area 2017-)
ISSN:	1525-755X
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	soil moisture, model evaluation/performance, water resources, data science, land surface model
NORA Subject Terms:	Agriculture and Soil Science Data and Information
Related URLs:	Dataset Dataset
Date made live:	09 Nov 2023 16:20 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/536127

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