Random Forest–Predicted 1-km Monthly Surface Ozone over Sub-Saharan Africa, 2005–2025
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environment and energyCreator:
AmoAnaTsiDon
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Monthly 1-km surface ozone predictions from the Random Forest model developed in “Machine Learning-Based Prediction of Monthly Surface Ozone Over Sub-Saharan Africa Using Satellite-Derived Precursors, Meteorology, and Surface Measurements.”
The model was trained primarily on INDAAF observations from predominantly rural and semi-savannah environments, with a few sites near urban centers. Therefore, predicted ozone magnitudes in urban areas should be interpreted with caution. For details on the model, training data, and methodology, please refer to the accompanying paper.
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