期刊
GEOPHYSICAL RESEARCH LETTERS
卷 31, 期 9, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2003GL019209
关键词
-
In this study, a statistical prediction model has been developed to forecast monthly Sea Surface Temperature (SST) in the Indian Ocean. It is a linear regression model based on a lagged relationship between the Indian Ocean SST and the NINO3 SST. A new approach to the statistical modeling has been tried out, in which the model predictors are obtained from not only observed NINO3 SST but also predicted results produced by a dynamical El Nino model. The forecast skill of the present model is better than that of persistence prediction. In particular, the present model has a significantly improved predictive skill during the spring and summer seasons when the boreal summer Indian monsoon is affected by the Indian Ocean SST.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据