10 citations as recorded by crossref.

1. Estimation of the Surface Fluxes for Heat and Momentum in Unstable Conditions with Machine Learning and Similarity Approaches for the LAFE Data Set V. Wulfmeyer et al. 10.1007/s10546-022-00761-2
2. Reconstruction of unstable atmospheric surface layer streamwise turbulence based on multi-layer perceptron neural network architecture C. Huang et al. 10.1016/j.euromechflu.2024.11.006
3. A Review of Machine Learning Applications in Land Surface Modeling S. Pal & P. Sharma 10.3390/earth2010011
4. How generalizable is a machine-learning approach for modeling hub-height turbulence intensity? N. Bodini et al. 10.1088/1742-6596/2265/2/022028
5. Machine learning for numerical weather and climate modelling: a review C. de Burgh-Day & T. Leeuwenburg 10.5194/gmd-16-6433-2023
6. Improved machine learning estimation of surface turbulent flux using interpretable model selection and adaptive ensemble algorithms over the Horqin Sandy Land area J. Zhao et al. 10.1016/j.atmosres.2025.107952
7. Can machine learning improve the model representation of turbulent kinetic energy dissipation rate in the boundary layer for complex terrain? N. Bodini et al. 10.5194/gmd-13-4271-2020
8. A deep learning method for predicting lower troposphere temperature using surface reanalysis H. Fan et al. 10.1016/j.atmosres.2022.106542
9. Surface Turbulent Fluxes From the MOSAiC Campaign Predicted by Machine Learning D. Cummins et al. 10.1029/2023GL105698
10. Reducing Parametrization Errors for Polar Surface Turbulent Fluxes Using Machine Learning D. Cummins et al. 10.1007/s10546-023-00852-8