Kernel analog forecasting of tropical intraseasonal oscillations

This paper presents the results of forecasting the Madden-Julian oscillation (MJO) and boreal summer intraseasonal oscillation (BSISO) through the use of satellite-obtained global brightness temperature data with a recently developed nonparametric empirical method. This new method, referred to as kernel analog forecasting, adopts specific indices extracted using the technique of nonlinear Laplacian spectral analysis as baseline definitions of the intraseasonal oscillations of interest, which are then extended into forecasts through an iterated weighted averaging scheme that exploits the predictability inherent to those indices. The pattern correlation of the forecasts produced in this manner remain above 0.6 for 50 days for both the MJO and BSISO when 23 years of training data is used, and 37 days for the MJO when nine years of data is used. 7