Jach et al. (2026) Comparing Temporal Dynamics of Soil Moisture from Remote Sensing, Modeling, and Field Observations Across Europe

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: MDPI (MDPI AG)
• Year: 2026
• Authors: Lisa Jach, Anke Fluhrer, Hans‐Stefan Bauer, David Chaparro, Florian M. Hellwig, Gerard Portal, Thomas Jagdhuber
• DOI: 10.3390/rs18030445

Research Groups

• European Center for Medium-range Weather Forecasts (ECMWF)
• Research institutions involved in Soil Moisture Active Passive (SMAP) validation and hydrometeorological monitoring.

Short Summary

This study evaluates the accuracy and temporal variability of ECMWF and SMAP soil moisture products across Europe, finding that while both capture timing well, they consistently overestimate the magnitude of short-term fluctuations.

Objective

• To compare the representation of short-term and seasonal soil moisture variability in absolute and normalized terms between ECMWF operational analysis, SMAP satellite retrievals, and in situ measurements.

Study Configuration

• Spatial Scale: Continental Europe, with specific focus on in situ stations in Southern France and Eastern Europe.
• Temporal Scale: Two distinct hydrometeorological growing periods in 2021 and 2022.

Methodology and Data

• Models used: ECMWF operational analysis.
• Data sources: SMAP (Soil Moisture Active Passive) passive satellite product and in situ ground station measurements.
• Metrics: Pearson correlation coefficients, Interquartile Range (IQR) for variability magnitude, and Soil Wetness Index (SWI).

Main Results

• Both products show high temporal correlation with in situ data, with median Pearson coefficients ranging from 0.65 to 0.79.
• Absolute soil moisture variability is overestimated: In 2021 (2022), the median IQR was 0.085 (0.10) $m^3/m^3$ for ECMWF and 0.072 (0.079) $m^3/m^3$ for SMAP, compared to 0.063 (0.072) $m^3/m^3$ for in situ observations.
• Overestimation is primarily driven by short-term fluctuations, particularly at dry sites in Southern France and Eastern Europe.
• SMAP tends to underestimate the Soil Wetness Index.
• Performance is higher during drought conditions (e.g., 2022) because strong seasonal signals are easier to capture than the complex short-term fluctuations prevalent in 2021.

Contributions

• Identifies a specific bias in the magnitude of temporal variability in operational and satellite products, moving beyond simple correlation metrics.
• Demonstrates how hydrometeorological extremes (like the 2022 European drought) influence the relative accuracy of soil moisture algorithms.
• Highlights the impact of site-specific characteristics and data pre-processing on the reliability of soil moisture estimates.

Funding

• Not specified in the provided text.

Citation

@article{Jach2026Comparing,
  author = {Jach, Lisa and Fluhrer, Anke and Bauer, Hans‐Stefan and Chaparro, David and Hellwig, Florian M. and Portal, Gerard and Jagdhuber, Thomas},
  title = {Comparing Temporal Dynamics of Soil Moisture from Remote Sensing, Modeling, and Field Observations Across Europe},
  journal = {MDPI (MDPI AG)},
  year = {2026},
  doi = {10.3390/rs18030445},
  url = {https://doi.org/10.3390/rs18030445}
}

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