Performance of the Indian summer monsoon 2020 in NCEP-GFS

• Published in: Acta geophysica 2023-06, Vol.71 (3), p.1321-1334
• Main Authors: Raju, Pemmani Venkata Subba, Kulkarni, Akshay, Karadan, Muhammed Muhshif, Wang, Dongxiao
• Format: Article
• Language: English
• Subjects: Climatological means; Earth and Environmental Science; Earth Sciences; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Heavy rainfall; Mathematical models; Monsoon rainfall; Monsoons; Rain; Rainfall; Research Article - Atmospheric & Space Sciences; Seasons; Spatial analysis; Spatial distribution; Structural Geology; Summer; Summer monsoon; Tropical easterly jet; Wind
• ISSN: 1895-7455; 1895-6572; 1895-7455
• DOI: 10.1007/s11600-022-01014-z

The rainfall observed 957.6 mm during summer monsoon season (June–September) of 2020 over India, which is 9% more than the climatological mean summer monsoon rainfall. In this study, the Indian Summer Monsoon (ISM) features are evaluated with National Center for Environment Prediction-Global Forecast System (NCEP-GFS). The 1200 UTC operational analysis and forecast fields (up to 5 days) with 0.5° horizontal resolution and 64 vertical levels are archived for the period of 1st May up to 30th September 2020. The ISM characteristics such as the low-level westerly jet at 850 hPa throughout the monsoon season, reaching the maximum intensity (> 18 m sec −1 ) on the Somalian coast and upper-level tropical easterly jet at 150 hPa (> 30 m sec −1 ) are well reflected in the NCEP analysis during summer monsoon season. The NCEP model reveals that the ISM features are reasonably well predicted in day 1 forecast, whereas in day 3 and day 5 forecasts it exhibited certain biased tendencies with respect to NCEP analysis. The spatial distribution of observed rainfall was in good agreement with the day 1, day 3, and day 5 forecasts; however, the intensity was overestimated over central India when compared to India Meteorological Department (IMD) observations. The heavy rainfall events (> 64.5 mm as per the criteria of IMD) were realistically captured in the day 1 forecast in terms of spatial distribution and intensity, but the model has limitations to capture intensity and distribution on day 3 and day 5 forecasts.