A New Approach to Skillful Seasonal Prediction of Southeast Asia Tropical Cyclone Occurrence

Predicting the peak-season (July–September) tropical cyclones (TCs) in Southeast Asia (SEA) several months ahead remains challenging, related to limited understanding and prediction of dynamics affecting variability SEA TC activity. Here, we introduce a new statistical approach sequentially identify mutually independent predictors for occurrence frequency TCs South China Sea (SCS) east Philippines (PHL). These predictors, which are identified from preseason (April-June) environmental fields, can capture interannual different clusters TCs, through cross-season effect on large-scale environment that governs genesis track. The physically oriented provides skillful seasonal 41-year period (1979–2019), with r = 0.73 0.54 SCS PHL frequency, respectively. lower performance is likely nonstationarity TC-environment relationship. We further develop hybrid method using derived dynamical forecasts. shows significant skill both lead times up four or 5 ahead, good models sea surface temperatures low-level winds tropics. predictions outperform predictions, showing potential operational use.