30 citations as recorded by crossref.

1. Sensitivity analysis of Biome-BGCMuSo for gross and net primary productivity of typical forests in China H. Ren et al. 10.1016/j.fecs.2022.100011
2. Topographic Heterogeneity and Aspect Moderate Exposure to Climate Change Across an Alpine Tundra Hillslope K. Jay et al. 10.1029/2023JG007664
3. Developing an efficient climate forecasting model for the spatiotemporal climate dynamics estimation and the prediction that fits the variable topography feature of the upper Blue Nile basin, Ethiopia M. Wondie et al. 10.1016/j.heliyon.2023.e22870
4. A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0) L. Li et al. 10.5194/gmd-16-4017-2023
5. A Review of Machine Learning Applications in Land Surface Modeling S. Pal & P. Sharma 10.3390/earth2010011
6. Irrigation in the Earth system S. McDermid et al. 10.1038/s43017-023-00438-5
7. Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model E. Kyker‐Snowman et al. 10.1111/gcb.15894
8. Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5) H. Yan et al. 10.1029/2022MS003312
9. Inferring surface energy fluxes using drone data assimilation in large eddy simulations N. Pirk et al. 10.5194/amt-15-7293-2022
10. Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data R. Ma et al. 10.5194/gmd-15-6637-2022
11. Assessing the potential for simplification in global climate model cloud microphysics U. Proske et al. 10.5194/acp-22-4737-2022
12. Modeling China's terrestrial ecosystem gross primary productivity with BEPS model: Parameter sensitivity analysis and model calibration X. Xing et al. 10.1016/j.agrformet.2023.109789
13. Evaluating a reservoir parametrization in the vector-based global routing model mizuRoute (v2.0.1) for Earth system model coupling I. Vanderkelen et al. 10.5194/gmd-15-4163-2022
14. Exploring the potential of history matching for land surface model calibration N. Raoult et al. 10.5194/gmd-17-5779-2024
15. Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado P. Jiang et al. 10.5194/hess-27-2621-2023
16. AI-empowered next-generation multiscale climate modelling for mitigation and adaptation V. Eyring et al. 10.1038/s41561-024-01527-w
17. Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China Using Machine Learning Emulation L. Conibear et al. 10.1029/2021GH000570
18. Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States H. Yan et al. 10.1038/s41597-023-02049-7
19. Flexible Foliar Stoichiometry Reduces the Magnitude of the Global Land Carbon Sink E. Hauser et al. 10.1029/2023GL105493
20. Pushing the frontiers in climate modelling and analysis with machine learning V. Eyring et al. 10.1038/s41558-024-02095-y
21. Machine learning for numerical weather and climate modelling: a review C. de Burgh-Day & T. Leeuwenburg 10.5194/gmd-16-6433-2023
22. Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator D. Watson-Parris et al. 10.5194/gmd-14-7659-2021
23. Scalable deep learning for watershed model calibration M. Mudunuru et al. 10.3389/feart.2022.1026479
24. CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5) O. Dombrowski et al. 10.5194/gmd-15-5167-2022
25. Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1 D. Xu et al. 10.5194/gmd-15-5021-2022
26. Multi‐Objective Adaptive Surrogate Modeling‐Based Optimization for Distributed Environmental Models Based on Grid Sampling R. Sun et al. 10.1029/2020WR028740
27. The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere S. Westermann et al. 10.5194/gmd-16-2607-2023
28. Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition R. Braghiere et al. 10.1029/2022MS003204
29. An Outlook for Deep Learning in Ecosystem Science G. Perry et al. 10.1007/s10021-022-00789-y
30. Moving Land Models Toward More Actionable Science: A Novel Application of the Community Terrestrial Systems Model Across Alaska and the Yukon River Basin Y. Cheng et al. 10.1029/2022WR032204