Network-Based Approach and Climate Change Benefits for Forecasting the Amount of Indian Monsoon Rainfall

Abstract Despite the development of sophisticated statistical and dynamical climate models, a relative long-term reliable prediction Indian summer monsoon rainfall (ISMR) has remained challenging problem. Toward achieving this goal, here we construct series physical networks based on global near-surface air temperature field. We show that some characteristics directed weighted can serve as efficient predictors for ISMR forecasting. The developed method produces forecasting skill 0.54 (Pearson correlation) with 5-month lead time by using previous calendar year’s data. our forecast is better than operational forecasts which have, however, quite short time. discuss underlying mechanism predictor associate it network–ENSO ENSO–monsoon connections. Moreover, approach allows predicting all-India rainfall, well different homogeneous regions, crucial agriculture in India. reveal warming affects network enhancing cross-equatorial teleconnections between southwest Atlantic, western part Ocean, North Asia–Pacific region, significant impacts precipitation A stronger connection through chain main atmospheric circulations patterns benefits amount rainfall. uncover hotspot area midlatitude South basis predictor, Atlantic subtropical index (SWAS index). Remarkably, trend yields an improvement skill.