LAUSR

Ensemble prediction systems help in quantifying the inherent uncertainties in numerical weather prediction models. Verification of forecasts is essential, in order to monitor and improve forecast quality. Also, verification can be used to compare the capabilities of different numerical weather prediction models in predicting the weather. This study deals with a comparison of probabilistic rainfall forecasts obtained from the National Centre for Medium Range Weather Forecasting (NCMRWF) Global Ensemble Forecast System (NGEFS) and the UK Met Office Global and Regional Ensemble Prediction System (MOGREPS) for four monsoon seasons, June–September 2012–2015. Verification is done based on the Brier score, the Brier skill score, the reliability diagram, the relative operating characteristic (ROC) curve and the area under the ROC curve (AROC). The NMSG (India Meteorological Department NCMRWF merged satellite and gauge) observation dataset is used for verification. The Brier score values for verification of the MOGREPS are lower by approximately 6–14% across all rainfall thresholds and lead times, indicating that these forecasts match better with observations than the NGEFS. This is further reiterated by Brier skill score values of MOGREPS forecasts which are approximately 13–47% higher than the NGEFS. Furthermore, the reliability diagram shows that forecast probabilities are closer to observed frequencies for the MOGREPS than the NGEFS. The AROC for the MOGREPS is also higher than for the NGEFS, hence indicating a better skill of the MOGREPS. From this study, it can be concluded that the MOGREPS showed a better capability in predicting rainfall during the southwest monsoons of 2012–2015 over the Indian region compared to the NGEFS.