Prediction Skill of Global Numerical Weather Prediction Model Deterministic Forecast over India during North East Monsoon

Abstract

This study provides a concise documentation of the current level of skill of the deterministic NWP model during North East monsoon 2010; making detailed inter-comparison with daily rainfall analysis from the use of rain gauge observations and satellite (TRMM) derived quantitative precipitation estimates (QPE) obtained from NASA web site. Model performance is evaluated for day-1 to day-5 forecasts of 24-h accumulated precipitation in terms of several accuracy and skill measures. Forecast quality and potential value are found to depend strongly on the verification dataset, geographic region, and precipitation threshold. Precipitation forecasts of the model, when accumulated over the whole season (October to December), reproduce the observed pattern. However, the model predicted rainfall is comparatively higher than the observed rainfall over most parts of the NE Monsoon regions during the season. The model showed considerable skill in predicting the daily and seasonal mean rainfall over southern peninsular India and also over five broad regions (Tamilnadu, Kerala, South Interior Karnataka, Royalseema and Coastal Andra Pradesh) of Indian North East monsoon areas. Various skill score and categorical statistics for the deterministic global model of IMD GFS rainfall forecast for NE Monsoon 2010 are prepared. The model bias for rainfall prediction changes from overestimation to underestimation at the threshold of 20 mm/day except for day-5 forecast. Model skill falls dramatically for occurrence rainfall thresholds greater than 15 mm/day. This implies that the model is much better at predicting the occurrence of rainfall than they are at predicting the magnitude and location of the peak values.