Advances on rainfall nowcasting techniques

Rainfall forecasting is of great significance in agriculture, water resource management, urban planning, and natural disaster early warning. Rainfall nowcasting can provide more effective information for real-time decision. This review summarized the main research methods of rainfall nowcasting: extrapolation from observations, numerical weather prediction models, statistical learning methods, and elaborated on the progress. Extrapolation from observations performs better for cases with short lead time and small scale. Numerical weather prediction models emphasize physical processes and can comprehensively analyze and simulate the evolution of atmospheric circulation and rainfall systems. The development of machine learning technique has promoted the application of algorithms based on statistical learning in short-term rainfall prediction, which has broad application prospects.