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      https://www.ias.ac.in/article/fulltext/jess/128/05/0130

    • Keywords

       

      MOS; neural network; T-1534; regular grid; monsoon season; Indian window.

    • Abstract

       

      In the present study, a model output statistics (MOS) guidance model was developed by using the neural network technique for a bias-corrected rainfall forecast. The model was developed over the Indian window (0–40$^{\circ}$N and 60–100$^{\circ}$E) by using the observed and global forecast system (GFS) T-1534 model output (up to 5 days) at a 0.125$^{\circ} \times$ 0.125$^{\circ}$ regular grid during the summer monsoon (June–September) 2016. The skill of the developed MOS model forecast against the observed 0.125$^{\circ} \times$ 0.125$^{\circ}$ grid rainfall data is obtained for the summer monsoon (June–September) 2017. The skill of the MOS model rainfall forecast is found to show good improvement over the T-1534 model’s direct forecast over the Indian window. In general, the T-1534 model’s direct forecast shows high skill but the forecast obtained by using the MOS model shows better skill than the direct model’s forecast, although a major improvement is seen for the Day 1 forecast at the national level. So the skill of the bias-corrected rainfall forecast by using the MOS guidance and the T-1534 model output is high and has the potential of being used as an operational forecast over the Indian region.

    • Author Affiliations

       

      Ashok Kumar1 Sridevi Ch1 Durai V R1 Singh K K1 Mukhopadhyay P2 Chattopadhyay N3

      1. India Meteorological Department, New Delhi 110 003, India.
      2. India Institute of Tropical Meteorology, Pune 411 017, India.
      3. India Meteorological Department, Pune 411 005, India.
    • Dates

       
  • Journal of Earth System Science | News

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