Jagdhuber et al. (2026) Assessing the Spatial Similarity of Soil Moisture Patterns and Their Environmental and Observational Drivers from Remote Sensing and Earth System Modeling Across Europe

Identification

• Journal: KITopen
• Year: 2026
• Date: 2026-01-01
• Authors: Thomas Jagdhuber, Lisa Jach, Anke Fluhrer, David Chaparro, Florian M. Hellwig, Gerard Portal, Hans‐Stefan Bauer, Harald Kunstmann
• DOI: 10.5445/ir/1000191280

Research Groups

• Institut für Meteorologie und Klimaforschung Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT)
• Zukunftscampus (CAMPUS), Karlsruher Institut für Technologie (KIT)

Short Summary

This study investigates the spatial similarity of soil moisture patterns between passive microwave remote sensing (SMAP) and Earth system modeling (ECMWF IFS) across Europe, identifying the environmental and observational drivers behind these patterns. It reveals underlying spatial similarities despite inherent discrepancies between the products and highlights soil texture, precipitation, and temperature as key drivers for model outputs, while SMAP retrievals are driven by brightness temperatures influenced by surface properties.

Objective

• To investigate the similarity of spatial soil moisture patterns between passive microwave remote sensing products (SMAP) and Earth system modeling (ECMWF IFS) across Europe.
• To identify the environmental and observational drivers behind the spatial soil moisture distributions at various scales.

Study Configuration

• Spatial Scale: Continental (whole of Europe), ranging from single grid cells to continental scales.
• Temporal Scale: Growing periods of wet (2021) and dry (2022) years.

Methodology and Data

• Models used: Integrated Forecasting System (IFS) model runs from the European Centre for Medium-Range Weather Forecasts (ECMWF).
• Data sources:
  • Passive microwave remote sensing: SMAP Dual Channel Algorithm (DCA) radiometer soil moisture product.
  • Earth system modeling: Soil moisture output from ECMWF IFS model runs.
  • Environmental drivers: Soil texture, precipitation, soil temperature, surface temperature, vegetation water content, soil roughness.
• Metrics: Two specifically configured spatial similarity metrics: total disagreement and mean category distance.

Main Results

• Two configured metrics, total disagreement and mean category distance, effectively assessed spatial similarity in soil moisture fields across different scales.
• Soil texture is the most influential single driver of spatial patterns in the IFS soil moisture runs when analyzed in absolute terms (cubic meters per cubic meter, m$^3$ m$^{-3}$).
• In relative terms of soil moisture (soil wetness index, dimensionless), precipitation and soil temperature explain most of the variability of the IFS soil moisture for Europe.
• SMAP retrievals are predominantly driven by brightness temperatures, which are mostly influenced by surface temperature, vegetation water content, and soil roughness.
• Despite differences in drivers and methodology leading to inherent discrepancies between the two soil moisture products, the assessment of their spatial patterns reveals underlying similarity from local to continental scales.

Contributions

• Developed and applied novel spatial similarity metrics to enable a robust comparison of soil moisture patterns from remote sensing and Earth system models.
• Systematically investigated and identified the key environmental and observational drivers influencing spatial soil moisture patterns for both SMAP and ECMWF IFS products across Europe.
• Demonstrated the underlying spatial similarity between disparate soil moisture products across various scales, fostering intercomparison and potential fusion efforts.

Funding

• Not specified in the provided text.

Citation

@article{Jagdhuber2026Assessing,
  author = {Jagdhuber, Thomas and Jach, Lisa and Fluhrer, Anke and Chaparro, David and Hellwig, Florian M. and Portal, Gerard and Bauer, Hans‐Stefan and Kunstmann, Harald},
  title = {Assessing the Spatial Similarity of Soil Moisture Patterns and Their Environmental and Observational Drivers from Remote Sensing and Earth System Modeling Across Europe},
  journal = {KITopen},
  year = {2026},
  doi = {10.5445/ir/1000191280},
  url = {https://doi.org/10.5445/ir/1000191280}
}