| Summary: | The ACCESS-AM2 (Australian Community Climate and Earth-System Simulator - Atmospheric Model Version 2) and SHAP analysis code and data used for the study described in Fiddes et al. (2024) ' A machine learning approach for evaluating Southern Ocean cloud-radiative biases over the Southern Ocean in a global atmosphere model ' accepted in Geoscientific Model Development Included files: - code.zip, inc: - pre-process_modis.ipynb: process the modis data, described in Fiddes et al. 2022 (https://doi.org/10.5194/acp-22-14603-2022) - pre-process.ipynb: organises model and modis data for analysis. Produces the files: COSP_vars_MODIS_2015-2019.nc, COSP_vars_cg207_2015-2019.nc and COSP_vars_bx400_2015-2019.nc - run_XGBoost+SHAP_control.ipynb: run the XGBoost model and SHAP analysis for the control run (bx400). Produces the files: SHAP_values_SWCRE_2015-2019_bx4002.nc, XGBoost_predicted_SWCRE_2015-2019_bx4002.nc, SHAP_interactions_bx400.nc - run_XGBoost+SHAP_ice.ipynb: run the XGBoost model and SHAP analysis for the ice experiment run (cg207).Produces the files:SHAP_values_SWCRE_2015-2019_cg2072.nc,XGBoost_predicted_SWCRE_2015-2019_cg2072.nc - analysis+plots_ML.ipynb: plots and stats presented in paper - COSP_vars_MODIS_2015-2019.nc - COSP_vars_cg207_2015-2019.nc - COSP_vars_bx400_2015-2019.nc - SHAP_values_SWCRE_2015-2019_bx4002.nc - SHAP_values_SWCRE_2015-2019_cg2072.nc - XGBoost_predicted_SWCRE_2015-2019_cg2072.nc - XGBoost_predicted_SWCRE_2015-2019_bx4002.nc - SHAP_interaction_bx400.nc The cloud typesused in this work can be found athttps://doi.org/10.5281/zenodo.6004061 This project was funded by the Australian Government as part of the Antarctic Science Collaboration Initiative program, under the Australian Antarctic Program Partnership, ASCI000002.
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