• Prashant Kumar

      Articles written in Journal of Earth System Science

    • Verification of cloud cover forecast with INSAT observation over western India

      Shivani Shah B M Rao Prashant Kumar P K Pal

      More Details Abstract Fulltext PDF

      Since the beginning of the summer monsoon 2009, experimental mesoscale weather forecasts in real time are being generated using WRF model by the Meteorology and Oceanography Group at the Space Applications Centre (ISRO)and are disseminated through MOSDAC (www.mosdac.gov.in) to various users. To begin with, the 12 h, 24 h and 48 h forecasts for the western India region are made available. A study is undertaken to comprehensively assess the cloudiness prediction performance of WRF model. The evaluations have been made over the three months period during monsoon 2009. INSAT cloud imagery data has been used as a reference for these evaluations. The verification strategy includes computation of various skill scores. It is seen that probability of detection (POD)of cloud is 84% and the false alarm rate (FAR) is around 18%. It is hoped that this assessment will provide information on the use of these forecasts in various applications.

    • Impact of additional surface observation network on short range weather forecast during summer monsoon 2008 over Indian subcontinent

      Prashant Kumar Randhir Singh P C Joshi P K Pal

      More Details Abstract Fulltext PDF

      The three dimensional variational data assimilation scheme (3D-Var) is employed in the recently developed Weather Research and Forecasting (WRF) model. Assimilation experiments have been conducted to assess the impact of Indian Space Research Organisation’s (ISRO) Automatic Weather Stations (AWS) surface observations (temperature and moisture) on the short range forecast over the Indian region. In this study, two experiments, CNT (without AWS observations) and EXP (with AWS observations) were made for 24-h forecast starting daily at 0000 UTC during July 2008. The impact of assimilation of AWS surface observations were assessed in comparison to the CNT experiment. The spatial distribution of the improvement parameter for temperature, relative humidity and wind speed from one month assimilation experiments demonstrated that for 24-h forecast, AWS observations provide valuable information. Assimilation of AWS observed temperature and relative humidity improved the analysis as well as 24-h forecast. The rainfall prediction has been improved due to the assimilation of AWS data, with the largest improvement seen over the Western Ghat and eastern India.

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