12 citations as recorded by crossref.

1. Extending our understanding on the retrievals of surface energy fluxes and surface soil moisture from the “triangle” technique G. Petropoulos https://doi.org/10.1016/j.envsoft.2024.106180
2. A First Verification of Sim2DSphere Model’s Ability to Predict the Spatiotemporal Variability of Parameters Characterizing Land Surface Interactions at Diverse European Ecosystems C. Lekka et al. https://doi.org/10.3390/s25051501
3. Recent Developments to the SimSphere Land Surface Modelling Tool for the Study of Land–Atmosphere Interactions G. Petropoulos & C. Lekka https://doi.org/10.3390/s24103024
4. Quantifying the prediction accuracy of a 1-D SVAT model at a range of ecosystems in the USA and Australia: evidence towards its use as a tool to study Earth's system interactions G. Petropoulos et al. https://doi.org/10.5194/gmd-8-3257-2015
5. Global Sensitivity Analysis of the Future Land Carbon Sink R. Deepak et al. https://doi.org/10.1080/07055900.2025.2540430
6. Extending the Global Sensitivity Analysis of the SimSphere model in the Context of its Future Exploitation by the Scientific Community G. Petropoulos et al. https://doi.org/10.3390/w7052101
7. Sim2DSphere: A novel modelling tool for the study of land surface interactions G. Petropoulos et al. https://doi.org/10.1016/j.envsoft.2024.106086
8. SimSphere model sensitivity analysis towards establishing its use for deriving key parameters characterising land surface interactions G. Petropoulos et al. https://doi.org/10.5194/gmd-7-1873-2014
9. Retrievals of key biophysical parameters at mesoscale from the Ts/VI scatterplot domain G. Petropoulos & D. Hristopulos https://doi.org/10.1080/10106049.2020.1821099
10. A Global Sensitivity Analysis of Parameter Uncertainty in the CLASSIC Model R. S. N. et al. https://doi.org/10.1080/07055900.2024.2396426
11. Exploring the potential of history matching for land surface model calibration N. Raoult et al. https://doi.org/10.5194/gmd-17-5779-2024
12. Emulation of high-resolution land surface models using sparse Gaussian processes with application to JULES E. Baker et al. https://doi.org/10.5194/gmd-15-1913-2022