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Kug, Jong-Seong; Kang, In-Sik; Lee, June-Yi; Jhun, Jong-Ghap
Geophysical research letters, 16 May 2004, Volume: 31, Issue: 9Journal Article
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 Niño 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.
