Hahn et al. (2026) Next-generation Metop ASCAT surface soil moisture datasets from EUMETSAT H SAF

Identification

• Journal: Earth system science data
• Year: 2026
• Date: 2026-06-26
• Authors: Sebastian Hahn, Thomas Melzer, Wolfgang Wagner
• DOI: 10.5194/essd-18-4393-2026

Research Groups

• Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstraße 8-10, 1040 Vienna, Austria
• European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)
• International Soil Moisture Network (ISMN)

Short Summary

This article presents an updated version of the Advanced Scatterometer (ASCAT) surface soil moisture dataset provided by the Satellite Application Facility on Support to Operational Hydrology and Water Management (HÂ SAF). The new release brings the operational near real-time (NRT) product up to date with the historical offline data record, introducing a unified offline/NRT dataset.

Objective

• Investigate the performance of the updated ASCAT surface soil moisture datasets in various environmental conditions.
• Evaluate the impact of long-term land cover changes on the underlying backscatter observations and their effect on soil moisture retrievals.

Study Configuration

• Spatial Scale: Global, with a spatial resolution of 6.25 km and 12.5 km for the high-resolution and standard datasets, respectively.
• Temporal Scale: Daily, with data available from January 2007 to December 2024.

Methodology and Data

• Models used: Semi-empirical model parameters are estimated using a physically-based change detection approach.
• Data sources:
  • ASCAT Level 1B Sigma Zero Full-Resolution (SZF) dataset
  • ERA5 reanalysis data
  • Noah GLDAS-2.1 soil moisture data
  • ESA CCI Passive Soil Moisture v09.1 product
  • ESA CCI Land Cover dataset
  • Global Lakes and Wetlands Database (GLWD)
  • Copernicus DEM
  • In-situ observations from the International Soil Moisture Network (ISMN)

Main Results

• The updated ASCAT surface soil moisture datasets show improved performance in regions with strong seasonal variability.
• Long-term land cover changes have a noticeable effect on the underlying backscatter observations, requiring correction to avoid artificial trends in the soil moisture retrievals.
• A new moving-window calibration approach is introduced to dynamically correct the backscatter signal and prevent non-hydrological long-term trends.

Contributions

• The updated ASCAT surface soil moisture datasets provide a unified offline/NRT dataset, addressing the limitations of previous versions.
• The introduction of a high-resolution 6.25 km sampling dataset alongside the standard 12.5 km sampling version enhances spatial detail while retaining an acceptable noise level.

Funding

• This research was funded by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and the Austrian Science Fund (FWF).

Citation

@article{Hahn2026Nextgeneration,
  author = {Hahn, Sebastian and Melzer, Thomas and Wagner, Wolfgang},
  title = {Next-generation Metop ASCAT surface soil moisture datasets from EUMETSAT H SAF},
  journal = {Earth system science data},
  year = {2026},
  doi = {10.5194/essd-18-4393-2026},
  url = {https://doi.org/10.5194/essd-18-4393-2026}
}