Evaluation of performance of WRF (ARW) and GFS for Quantitative Precipitation Forecast and its value addition over India river sub-basins during recent years
Keywords:Quantitative precipitation forecast (QPF), NWP, River Basin/sub-basin, FMO, WRF(ARW), GFS, Skill Scores
The Numerical Weather Prediction (NWP) models, Global Forecast System (GFS) and Weather Research & Forecast [WRF(ARW)] operationally run by India Meteorological Department (IMD) have been utilized to estimate sub-basin-wise rainfall forecast. The sub-basin-wise operational Quantitative Precipitation Forecast (QPF) have been issued by 14 Flood Meteorological Offices (FMOs) of IMD located at different flood prone areas of the country. The daily sub-basin-wise NWP model rainfall forecast for 146 sub-basins under these 14 FMOs for the flood season 2017 & 2018 and for 153 sub-basins for the flood season 2019 have been estimated on operational basis which are used by forecasters at FMOs as a guidance for the issue of operational sub-basin QPF for flood forecasting purposes. The performance of GFS and WRF (ARW) models in respect of rainfall at the sub-basin level have been studied in detail. It is found that the critical success index (CSI) and Probability of Detection (POD) decrease from lower to higher category of rainfall whereas False Alarm Rate (FAR) increases from lower to higher categories. The case base heavy rainfall analysis showed that model generally underestimated the rainfall. It is also found that performance of GFS is little better than WRF (ARW) when compared over all the flood prone river sub basins of India. It is also found that the performance of WRF (ARW) is little better in hilly areas in comparison to GFS.
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