14 citations as recorded by crossref.

1. Using an Explainable Machine Learning Approach to Characterize Earth System Model Errors: Application of SHAP Analysis to Modeling Lightning Flash Occurrence S. Silva et al.
2. Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0) P. Ghosh et al.
3. Conservation laws in a neural network architecture: enforcing the atom balance of a Julia-based photochemical model (v0.2.0) P. Sturm & A. Wexler
4. Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China Using Machine Learning Emulation L. Conibear et al.
5. Technical note: Parameterising cloud base updraft velocity of marine stratocumuli J. Ahola et al.
6. Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals A. Varble et al.
7. An ANN-Based Inversion Method for High-Precision Layer Thicknesses in Coal–Rock Recognition P. Zhu et al.
8. Bringing it all together: science priorities for improved understanding of Earth system change and to support international climate policy C. Jones et al.
9. Machine Learning in Weather Prediction and Climate Analyses—Applications and Perspectives B. Bochenek & Z. Ustrnul
10. A Nudge to the Truth: Atom Conservation as a Hard Constraint in Models of Atmospheric Composition Using a Species-Weighted Correction P. Sturm & S. Silva
11. Neural emulator based on physical fields for accelerating the simulation of surface chlorophyll in an Earth System Model B. Wu et al.
12. Forecasting estuarine salt intrusion in the Rhine–Meuse delta using an LSTM model B. Wullems et al.
13. Detection of Forced Change Within Combined Climate Fields Using Explainable Neural Networks J. Rader et al.
14. Deep learning representation of the aerosol size distribution D. Barahona et al.