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    Prediction of Extreme Events: Current Status and Future Pathways against the Backdrop of Climate Change

    Source: Bulletin of the American Meteorological Society:;2020:;volume( 101 ):;issue: 007::page E1137
    Author:
    Mukhopadhyay, Parthasarathi;Krishnan, R.;Nanjundiah, Ravi S.;Mohapatra, M.
    DOI: 10.1175/BAMS-D-20-0037.1
    Publisher: American Meteorological Society
    Abstract: Against the backdrop of increasingly frequent extreme precipitation events and the increasing severity of tropical cyclones, it is time to evaluate current forecast systems and develop pathways for improving the accuracy and reliability of predicting these high impact weather events in a changing climate. In India recurring recent extreme precipitation events in August 2018 and 2019 in the southern Indian state of Kerala severely disrupted lives and caused immense damage of more than $5 billion (U.S. dollars, 2018) to public properties. The Indian seas have experienced anomalously strong severe cyclones, such as Tropical Cyclone Ockhi (29 November–6 December 2017), at very low latitudes. There were other extreme rain events recently, such as flooding in the southern metropolis of Chennai during November and December 2015 as well as floods in the northern mountainous state of Uttarakhand in June 2013. For all of these events the existing forecast system provided useful guidance in the short-term (up to 10 days) and extended-range (up to 2–3 weeks) time scales. Though the short-range forecast succeeded in providing the guidance of ∼3 days, it could not provide the probability of extremes associated with those events, with longer lead time. Therefore, there remains a most urgent need to provide these probabilities with longer lead times (∼5–7 days).
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      Prediction of Extreme Events: Current Status and Future Pathways against the Backdrop of Climate Change

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    contributor authorMukhopadhyay, Parthasarathi;Krishnan, R.;Nanjundiah, Ravi S.;Mohapatra, M.
    date accessioned2022-01-30T17:47:33Z
    date available2022-01-30T17:47:33Z
    date copyright7/29/2020 12:00:00 AM
    date issued2020
    identifier issn0003-0007
    identifier otherbamsd200037.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263948
    description abstractAgainst the backdrop of increasingly frequent extreme precipitation events and the increasing severity of tropical cyclones, it is time to evaluate current forecast systems and develop pathways for improving the accuracy and reliability of predicting these high impact weather events in a changing climate. In India recurring recent extreme precipitation events in August 2018 and 2019 in the southern Indian state of Kerala severely disrupted lives and caused immense damage of more than $5 billion (U.S. dollars, 2018) to public properties. The Indian seas have experienced anomalously strong severe cyclones, such as Tropical Cyclone Ockhi (29 November–6 December 2017), at very low latitudes. There were other extreme rain events recently, such as flooding in the southern metropolis of Chennai during November and December 2015 as well as floods in the northern mountainous state of Uttarakhand in June 2013. For all of these events the existing forecast system provided useful guidance in the short-term (up to 10 days) and extended-range (up to 2–3 weeks) time scales. Though the short-range forecast succeeded in providing the guidance of ∼3 days, it could not provide the probability of extremes associated with those events, with longer lead time. Therefore, there remains a most urgent need to provide these probabilities with longer lead times (∼5–7 days).
    publisherAmerican Meteorological Society
    titlePrediction of Extreme Events: Current Status and Future Pathways against the Backdrop of Climate Change
    typeJournal Paper
    journal volume101
    journal issue7
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/BAMS-D-20-0037.1
    journal fristpageE1137
    journal lastpageE1141
    treeBulletin of the American Meteorological Society:;2020:;volume( 101 ):;issue: 007
    contenttypeFulltext
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