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

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-02-15
• Authors: Thomas Jagdhuber, Lisa Jach, Anke Fluhrer, David Chaparro, Florian M. Hellwig, Gerard Portal, Hans‐Stefan Bauer, Harald Kunstmann
• DOI: 10.3390/rs18040608

Research Groups

The specific affiliations of the authors are not provided in the text. However, the study involves the analysis of data and models from: - European Centre for Medium-Range Weather Forecasts (ECMWF) for the IFS model. - NASA for the SMAP (Soil Moisture Active Passive) mission's passive microwave remote sensing product.

Short Summary

This study investigates the spatial similarity of soil moisture patterns between the SMAP passive microwave remote sensing product and the ECMWF IFS Earth system model across Europe. It finds that despite differences in their underlying drivers and methodologies, the two products exhibit significant spatial pattern similarities from local to continental scales.

Objective

• To investigate the similarity of spatial soil moisture patterns between passive microwave remote sensing products (SMAP Dual Channel Algorithm) and Earth system modeling (ECMWF IFS model).
• To identify the drivers behind the spatial soil moisture distributions at various scales and under different hydrological conditions (wet vs. dry years).

Study Configuration

• Spatial Scale: From single grid cells (minimum) to continental (maximum) scales, covering the whole of Europe.
• Temporal Scale: Growing periods of wet (2021) and dry (2022) years.

Methodology and Data

• Models used: Integrated Forecasting System (IFS) model from ECMWF.
• Data sources:
  • SMAP Dual Channel Algorithm (DCA) radiometer soil moisture product (passive microwave remote sensing).
  • Soil moisture output from IFS model runs of the ECMWF.
• Metrics: Two specifically configured spatial similarity metrics: total disagreement and mean category distance.

Main Results

• The configured spatial similarity metrics (total disagreement and mean category distance) effectively showcase the opportunities and challenges in assessing spatial similarity of soil moisture fields across different scales.
• Drivers of IFS soil moisture patterns:
  • In absolute terms (cubic metres per cubic metre, m³ m⁻³), soil texture is the most influential single driver.
  • In relative terms (soil wetness index, dimensionless), precipitation and soil temperature explain most of the variability.
• Drivers of SMAP retrievals: Predominantly brightness temperatures, which are mostly influenced by surface temperature, vegetation water content, and soil roughness.
• Despite inherent discrepancies due to differences in drivers and methodology, the assessment reveals underlying spatial similarity between the SMAP and IFS soil moisture patterns from the local to the continental scale.

Contributions

• Configured and applied novel spatial similarity metrics (total disagreement and mean category distance) for the intercomparison of soil moisture products from remote sensing and Earth system modeling.
• Provided a comprehensive spatial comparison of operational SMAP DCA soil moisture with ECMWF IFS model output across Europe.
• Identified and quantified the primary drivers of spatial soil moisture patterns for both the IFS model (distinguishing between absolute and relative terms) and SMAP retrievals.
• Demonstrated the underlying spatial similarity between SMAP and IFS soil moisture patterns across a wide range of scales, despite their methodological differences and distinct primary drivers.

Funding

No specific funding projects, programs, or reference codes are provided in the paper 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 = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18040608},
  url = {https://doi.org/10.3390/rs18040608}
}