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contributor authorXue, Yan
contributor authorLeetmaa, Ants
contributor authorJi, Ming
date accessioned2017-06-09T15:48:39Z
date available2017-06-09T15:48:39Z
date copyright2000/02/01
date issued2000
identifier issn0894-8755
identifier otherams-5407.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4194034
description abstractA series of seasonally varying linear Markov models are constructed in a reduced multivariate empirical orthogonal function (MEOF) space of observed sea surface temperature, surface wind stress, and sea level analysis. The Markov models are trained in the 1980?95 period and are verified in the 1964?79 period. It is found that the Markov models that include seasonality fit to the data better in the training period and have a substantially higher skill in the independent period than the models without seasonality. The authors conclude that seasonality is an important component of ENSO and should be included in Markov models. This conclusion is consistent with that of statistical models that take seasonality into account using different methods. The impact of each variable on the prediction skill of Markov models is investigated by varying the weightings among the three variables in the MEOF space. For the training period the Markov models that include sea level information fit the data better than the models without sea level information. For the independent 1964?79 period, the Markov models that include sea level information have a much higher skill than the Markov models without sea level information. The authors conclude that sea level contains the most essential information for ENSO since it contains the filtered response of the ocean to noisy wind forcing. The prediction skill of the Markov model with three MEOFs is competitive for both the training and independent periods. This Markov model successfully predicted the 1997/98 El Niño and the 1998/99 La Niña.
publisherAmerican Meteorological Society
titleENSO Prediction with Markov Models: The Impact of Sea Level
typeJournal Paper
journal volume13
journal issue4
journal titleJournal of Climate
identifier doi10.1175/1520-0442(2000)013<0849:EPWMMT>2.0.CO;2
journal fristpage849
journal lastpage871
treeJournal of Climate:;2000:;volume( 013 ):;issue: 004
contenttypeFulltext


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