Exploring the predictability of within-season rainfall statistics of the Bangladesh monsoon using North American Multimodel Ensemble outputs

Improvement of rainfall forecasts on seasonal to within-season timescales is crucial for many vulnerable regions and nations, including Bangladesh. For South Asia, seasonal predictability of rainfall can be quite challenging, and Bangladesh has limited predictive skill with respect to total seasonal rainfall due to its weak relationship with ENSO variability. The relationship between total seasonal monsoon rainfall from June through September (JJAS), as simulated by the North American Multimodel Ensemble (NMME), and within-season observed rainfall statistics for Bangladesh were explored, employing 25-year cross-validations at lead times up to 3 months. The model hindcasts of total JJAS rainfall demonstrate only low-to-modest skill at predicting total observed seasonal rainfall, but a more robust predictive relationship is found for the number of observed dry and wet spells within the season, more so than with the number of extreme dry or wet days. A small ensemble of NMME models could be used to provide more valuable information to aid decision-makers than previously thought, with important implications for agricultural decision-making and climate services.