Assessment and intercomparison of 23 global satellite and model-based soil moisture products using cosmic ray neutron sensing observations over Europe
Comprehensive evaluation of satellite and model-based soil moisture (SM) products is essential for their further development and application. With the advent of Cosmic Ray Neutron Sensing (CRNS), which has an observation radius of 130–240 m, the spatial representativeness mismatch between these grid-based SM products and ground single-point observations during the evaluation process can be feasibly relieved. In this study, we systematically evaluated 23 gridded SM products, including single-sensor satellite, multi-sensor merged, and model-based products, using 68 CRNS measurement sites across the Europe. Our evaluation revealed that the SMAP-INRAE-BORDEAUX (SMAP-IB) SM retrievals showed the superior consistency with CRNS measurements among all analyzed products, demonstrating both high correlation ( R = 0.80) and low unbiased root mean square error (ubRMSE = 0.050 m 3 /m 3 ). The CCI/C3S combined active-passive SM products ranked second in performance ( R > 0.75, ubRMSE <0.060 m 3 /m 3 ). In the bias analysis, 17 products had negative bias (−0.003 m 3 /m 3 to −0.190 m 3 /m 3 ) against CRNS measurements, while AMSR2-LPRM at C1 and C2 bands and CCI/C3S at active and passive products had positive bias (0.011 m 3 /m 3 to 0.161 m 3 /m 3 ). It was also found that the capabilities of all SM products retrievals degraded in terms of R and ubRMSE with increasing vegetation density, topographic complexity and soil wetness. Most products showed the lowest ubRMSE and highest R values in cropland compared to other land cover types. Our study emphasizes the substantial potential of cosmic field-scale SM observations for the validation of satellite- and model-based SM products, and our findings have the potential to advance algorithm refinement, product improvement, and hydrometeorological applications. • Performance of 23 satellites/models-based soil moisture products was assessed over Europe. • Evaluation was based on Cosmic Ray Neutron Sensing (CRNS) measurement data. • SMAP-IB and CCI-combined followed the temporal dynamics of CRNS soil moisture best. • Lower performance with dense vegetation, higher soil wetness and topographic complexity. • Most soil moisture products underestimate CRNS measurements.
Authors
- J. Zeng
- Jian Peng (ORCID: https://orcid.org/0000-0003-0332-0248)
- Pariha Helili (ORCID: https://orcid.org/0000-0002-0041-4292)
- Jean‐Pierre Wigneron (ORCID: https://orcid.org/0000-0001-5345-3618)
- Yao Xiao (ORCID: https://orcid.org/0000-0002-5317-8799)
- Preethi Konkathi (ORCID: https://orcid.org/0000-0002-2720-0964)
- Patricia de Rosnay (ORCID: https://orcid.org/0000-0002-7374-3820)
- Frédéric Frappart (ORCID: https://orcid.org/0000-0002-4661-8274)
- Gabrielle Jacinthe Maria de Lannoy
- Xiaojun Li
- Zanpin Xing
- Andreas Colliander
- L. Karthikeyan
- Ke Zhang
- Ardeshir Ebtehaj
- Lei Fan
Institutions
- Finnish Meteorological Institute (FI)
- University of Minnesota (US)
- Helmholtz Centre for Environmental Research (DE)
- Southwest University (CN)
- Université de Bordeaux (FR)
- European Centre for Medium-Range Weather Forecasts (GB)
- Indian Institute of Technology Bombay (IN)
- Chinese Academy of Sciences (CN)
- Saint Anthony College of Nursing (US)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Unité mixte de recherche Œnologie (FR)
- Aerospace Information Research Institute (CN)
- Southwest Jiaotong University (CN)
- Lanzhou University (CN)
- Leipzig University (DE)
- KU Leuven (BE)
Publication Details
- Journal
- Remote Sensing of Environment
- Published
- 2025-12-30
- DOI
- https://doi.org/10.1016/j.rse.2025.115207
- Citations
- 1
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.80