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dc.contributor.authorJoseph, Susmitha
dc.contributor.authorSahai, A. K.
dc.contributor.authorPhani, R.
dc.contributor.authorMandal, R.
dc.contributor.authorDey, A.
dc.contributor.authorChattopadhyay, R.
dc.contributor.authorAbhilash, S.
dc.date.accessioned2019-09-22T09:02:51Z
dc.date.available2019-09-22T09:02:51Z
dc.date.copyright12/4/2018 12:00:00 AM
dc.date.issued2018
dc.identifier.otherWAF-D-18-0055.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4262480
dc.description.abstractUnder the National Monsoon Mission Project initiated by the government of India?s Ministry of Earth Sciences, an indigenous dynamical ensemble prediction system (EPS) has been developed at the Indian Institute of Tropical Meteorology based on the state-of-the-art Climate Forecast System Model version 2 (CFSv2) coupled model, for extended-range (~15?20 days in advance) prediction. The forecasts are generated for the entire year covering the southwest monsoon, the northeast monsoon, and the summer and winter seasons. As the forecast of rainfall is important during the southwest and northeast monsoon seasons, along with that of the temperature during the summer and winter seasons, the present study documents the deterministic as well as probabilistic skill of the EPS in predicting the results in the respective seasons, over various meteorological subdivisions throughout India, on a pentad-lead time scale. The EPS is found to be skillful in predicting rainfall during the southwest and northeast monsoon seasons, as well as temperature during the summer and winter seasons, across different subdivisions of India. In addition, the EPS is noted to be skillful in predicting selected extremes in rainfall and temperature. This affirms the reliability and usefulness of the present EPS from an operational perspective.
dc.publisherAmerican Meteorological Society
dc.titleSkill Evaluation of Extended-Range Forecasts of Rainfall and Temperature over the Meteorological Subdivisions of India
dc.typeJournal Paper
dc.journal.volume34
dc.journal.issue1
dc.journal.titleWeather and Forecasting
dc.identifier.doi10.1175/WAF-D-18-0055.1
dc.journal.fristpage81
dc.journal.lastpage101
dc.treeWeather and Forecasting:;2018:;volume 034:;issue 001
dc.contenttypeFulltext


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