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This paper describes the development of a statistical forecasting method for summer monsoon rainfall over Thailand. Predictors of Thailand summer (August–October) monsoon rainfall are identified from the large-scale ocean–atmospheric circulation variables (i.e. sea-surface temperature and sea-level pressure) in the Indo-Pacific region. The predictors identified are part of the broader El Niño southern oscillation (ENSO) phenomenon. The predictors exhibit a significant relationship with the summer rainfall only during the post-1980 period, when the Thailand summer rainfall also shows a relationship with ENSO. Two methods for generating ensemble forecasts are adapted. The first is the traditional linear regression, and the second is a local polynomial-based nonparametric method. The associated predictive standard errors are used for generating ensembles. Both the methods exhibit significant comparable skills in a cross-validated mode. However, the nonparametric method shows improved skill during extreme years (i.e. wet and dry years). Furthermore, the models provide useful skill at 1–3 month lead time that can have a strong impact on resources planning and management. Copyright © 2005 Royal Meteorological Society.
Singhrattna et al. (Sat,) studied this question.