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Assessing the Spatial Similarity of Soil Moisture Patterns and Their Environmental and Observational Drivers from Remote Sensing and Earth System Modeling Across Europe

Jagdhuber, Thomas ; Jach, Lisa; Fluhrer, Anke; Chaparro, David; Hellwig, Florian M.; Portal, Gerard; Bauer, Hans-Stefan; Kunstmann, Harald 1,2
1 Institut für Meteorologie und Klimaforschung Atmosphärische Umweltforschung (IMKIFU), Karlsruher Institut für Technologie (KIT)
2 Zukunftscampus (CAMPUS), Karlsruher Institut für Technologie (KIT)

Abstract:

Soil moisture is an essential climate variable exhibiting strong spatio-temporal dynamics, especially in the topsoil. Therefore, it is assessed multiple times by sensors within in situ networks, satellites, and by modeling of the Earth system. The resulting soil moisture fields from all methods are individual and non-congruent due to the imperfection of the methods and retrievals. But their spatial patterns have valuable similarities that call for investigation to foster intercomparison or even fusion of soil moisture products. In this research study, the similarity of spatial soil moisture patterns between passive microwave remote sensing products and Earth system modeling is investigated. We configure and apply spatial similarity metrics to enable a spatial comparison of the operational SMAP Dual Channe Algorithm (DCA) radiometer soil moisture product with the soil moisture output from IFS model runs of the ECMWF. The pattern assessment spans over the whole of Europe and aims to find the drivers behind the spatial soil moisture distributions at scales ranging from single grid cells (minimum) to continental (maximum) spatial scales, and between growing periods of wet (2021) and dry (2022) years. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000191280
Veröffentlicht am 10.03.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Atmosphärische Umweltforschung (IMKIFU)
Zukunftscampus (CAMPUS)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 2072-4292
KITopen-ID: 1000191280
Erschienen in Remote Sensing
Verlag MDPI
Band 18
Heft 4
Seiten Art.-Nr.: 608
Vorab online veröffentlicht am 15.02.2026
Nachgewiesen in Scopus
Web of Science
OpenAlex
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