Statistical Prediction of 500 mb Height Field Using Eigenvectors

Abstract

Empirical orthogonal functions for the 500 mb height and 850 mb temperature fields over a limited domain are obtained. These functions are then used as predictors in a regression model to forecast the height field 24 h in the future. Several regression models are formulated using predictors from the current 850 mb temperature field, 6 and 12 h barotropic forecast fields, as well as the current 500 mb height field. The nonlinear predictors derived from the barotropic forecast fields predominate as selected predictors in those models where they were available for selection and contribute considerable skill to the forecasts. The predictors of the 12 h forecast field are also selected more frequently than those of the 6 h forecast field. The regression models were developed from seven winters of data and then tested against an independent three-winter sample. The error fields of these regression forecasts are compared to those of climatology, persistence and the NMC primitive equation model. The NMC model is found to be considerably better in baroclinic and data-dense regions than any of the regression models. In data-spare regions the distribution of error is similar.