Abstract
Abstract 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 remains above 0.6 for 50 days for both the MJO and BSISO when 23 yr of training data are used and 37 days for the MJO when 9 yr of data are used.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
