11 citations as recorded by crossref.

1. Enhancing simulations of snowpack properties in land surface models with the Soil, Vegetation and Snow scheme v2.0 (SVS2) V. Vionnet et al. https://doi.org/10.5194/gmd-18-9119-2025
2. Spatiotemporal estimation of actual forest evapotranspiration in semi-arid China using remote sensing and deep learning R. Su et al. https://doi.org/10.1080/17538947.2026.2660434
3. Evolving beyond collapse: an adaptive particle batch smoother for cryospheric data assimilation K. Aalstad et al. https://doi.org/10.5194/gmd-19-8565-2026
4. Simulating snow properties and Ku-band backscatter across the forest-tundra ecotone G. Woolley et al. https://doi.org/10.5194/tc-20-1315-2026
5. A high-resolution snow dataset for Switzerland (2016–2025) combining physics-based simulations and in situ observations M. Oberrauch et al. https://doi.org/10.5194/tc-20-3387-2026
6. Insights into the North Hemisphere daily snowpack at high resolution from the new Crocus–ERA5 product S. Ramos Buarque et al. https://doi.org/10.5194/essd-17-7227-2025
7. Ensemble-based data assimilation improves hyperresolution snowpack simulations in forests E. Alonso-González et al. https://doi.org/10.5194/tc-20-209-2026
8. Evaluating the utility of Sentinel-1 in a Data Assimilation System for estimating snow depth in a mountainous basin B. Mirza et al. https://doi.org/10.5194/tc-19-6691-2025
9. Assessment of snow model uncertainty in relation to the effect of a 1 °C warming using the snow modelling framework openAMUNDSEN E. Rottler et al. https://doi.org/10.5194/tc-20-2351-2026
10. Spatio-temporal snow data assimilation with the ICESat-2 laser altimeter M. Mazzolini et al. https://doi.org/10.5194/tc-19-3831-2025
11. Version 3.0.2 of the Crocus snowpack model M. Lafaysse et al. https://doi.org/10.5194/gmd-19-6273-2026