publication . Article . 2015

Improving Multi-model Ensemble Probabilistic Prediction of Yangtze River Valley Summer Rainfall

Fang Li; Zhongda Lin;
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  • Published: 10 Feb 2015 Journal: Advances in Atmospheric Sciences, volume 32, pages 497-504 (issn: 0256-1530, eissn: 1861-9533, Copyright policy)
  • Publisher: Springer Science and Business Media LLC
Abstract
Seasonal prediction of summer rainfall over the Yangtze River valley (YRV) is valuable for agricultural and industrial production and freshwater resource management in China, but remains a major challenge. Earlier multi-model ensemble (MME) prediction schemes for summer rainfall over China focus on single-value prediction, which cannot provide the necessary uncertainty information, while commonly-used ensemble schemes for probability density function (PDF) prediction are not adapted to YRV summer rainfall prediction. In the present study, an MME PDF prediction scheme is proposed based on the ENSEMBLES hindcasts. It is similar to the earlier Bayesian ensemble pre...
Subjects
free text keywords: Atmospheric Science
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