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सीएसआईआर-राष्ट्रीय डेटा विज्ञान एवं कृत्रिम बुद्धिमत्ता संस्थान

(पूर्व में चैथा पैरारडाइम संस्थान तथा गणितीय प्रारूपण एवं कम्प्यूटर अनुकरण केन्द्र)

वैज्ञानिक तथा औद्योगिक अनुसंधान परिषद (सीएसआईआर) की एक घटक प्रयोगशाला की एक घटक प्रयोगशाला।.


विज्ञान एवं प्रौद्योगिकी मंत्रालय, भारत सरकार

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by K. C. Gouda, S. Joshi & Nagaraj Bhat 

Using an initial manifold approach, an ensemble forecast methodology is shown to simultaneously increase lead and realizable skill in long-range forecasting of monsoon over continental India. Initial manifold approach distinguishes the initial states that have coherence from a collection of unrelated states. In this work, an optimized and validated variable resolution general circulation model is being adopted for long-range forecasting of monsoon using the multi-lead ensemble methodology. In terms of realizable skill (as against potential) at resolution (~60km) and lead (2–5 months) considered here, the present method performs very well. The skill of the improved methodology is significant, capturing 9 of the 12 extreme years of monsoon during 1980–2003 in seasonal (June–August) scale. Eight-member ensemble-average hindcasts carried out for realizable skill with lead of 2 (for June) to 5 (for August) months and an optimum ensemble is presented.

 

Source: https://doi.org/10.1007/s00704-021-03589-x and https://link.springer.com/article/10.1007/s00704-021-03589-x