Machine learning-based 1-year-lead summer rainfall prediction over the DPRK using regionally optimized spatial-contrast indices

Key Points

• The aim is to predict summer rainfall one year ahead in the northern part of the Korean Peninsula using machine learning techniques.
• Utilized machine learning algorithms to analyze climatic data.
• Employed regionally optimized spatial-contrast indices for prediction accuracy.
• Focused on summer monsoon precipitation patterns in the region.
• Achieved reliable predictions for summer rainfall one year in advance.
• Improved disaster risk management strategies through enhanced forecasting accuracy.