A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

摘要

Highlights?We developed a new model (BGP) for teleconnection studies.?The BGP classifies monthly rainfall events.?The BGP can forecast rainfall classes based on global SST variations.?The BGP exhibits teleconnection signals with explicit mathematical expressions.AbstractThe effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The m