Evaluation of forecast skill of GFS T1534 for heavy rainfall events of Monsoon 2017 at district level across India
Keywords:GFS, NWP, Global model, Heavy rainfall analysis, District-level forecast, Indian summer monsoon, Rainfall prediction skill
The extreme rainfall events are natural hazards; affect the country's economy, especially an agricultural country like India. In the current study, the uncertainty of Global Forecasting System (GFS) T1534 model in predicting heavy rainfall (>64.5mm) at district level under particular meteorological sub-divisions of India has been evaluated for the summer monsoon 2017. With the help of IMD rain gauge observations, few heavy rainfall cases are selected based on the highest amount of rainfall observed over a district in a particular meteorological sub-division. For the qualitative spatial verification, the observed gridded rainfall data have been used to locate the heavy rainfall area over a particular district in a sub-division. Further, various statistical skill scores derived through the quantitative verification of the GFS model forecast against gauge observations, in predicting different rainfall categories at the district level are also discussed. Based on the present study, it is found that the model rainfall forecast is much better at predicting the occurrence of light to moderate rain at meteorological sub-division and district level. For the heavy and extreme rainfall cases of monsoon 2017, the model could capture reasonably at meteorological sub-division level and district level in few cases; but due to the spatial shift of rainfall pattern model could not capture at district level in many cases. It is suggested that, for the location specific heavy rainfall forecast there is a need to use the ensemble forecast with probabilistic guidance.
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