Rainfall forecasting skill of GFS model at T1534 and T574 resolution over India during the monsoon season

• Published in: Meteorology and atmospheric physics 2020-02, Vol.132 (1), p.35-52
• Main Authors: Sridevi, Ch, Singh, K. K., Suneetha, P., Durai, V. R., Kumar, Ashok
• Format: Article
• Language: English
• Subjects: Aquatic Pollution; Atmospheric Sciences; Climatology; Earth and Environmental Science; Earth Sciences; Forecasting; Forecasting skill; Heavy rainfall; Math. Appl. in Environmental Science; Mathematical models; Meteorology; Monsoon rainfall; Monsoons; Original Paper; Rain; Rainfall; Rainfall forecasting; Regions; Resolution; Seasonal distribution; Seasons; Spatial distribution; Summer monsoon; Terrestrial Pollution; Waste Water Technology; Water Management; Water Pollution Control; Weather forecasting; Wind
• ISSN: 0177-7971; 1436-5065
• DOI: 10.1007/s00703-019-00672-x

The rainfall forecast of global forecasting system (GFS) model running at the India Meteorological Department (IMD), i.e., GFS T574 (25 km) and GFS T1534 (12.5 km) is verified at its natural resolution. A verification study is conducted for the rainfall forecast over Indian window during the summer monsoon season (June–September) 2016. Regional verification of rainfall forecast was also carried out over five homogeneous regions of India, i.e., north India, west coast of India, northeast India, central India and peninsular India. The skill of the model forecast is also evaluated for yes/no, categorical and few heavy rainfall cases over India. Results show that both T1534 and T574 models are able to provide more realistic spatial distribution of seasonal mean rainfall over India. This study also shows that both the model forecasts are skillful in capturing the 24 h accumulated rainfall over climatologically heavy rainfall regions, but the magnitude and location fluctuated. The rainfall forecast for different rainfall categories in terms of different statistical skill scores, i.e., ratio score, HK, bias, hit rate and HKQ showed a relatively high skill for T1534 compared to T574 over most parts of the country from the day 1 to day 5 forecasts. It is also found from this study that the skill in predicting day 1 to day 3 forecasts of both the models was found to be good and usable for all parts of the country except for high terrain regions in India. The results documented here are expected to be useful to the operational forecasters in day-to-day weather forecasting over Indian monsoon regions.