Representation of the quasi‐biennial oscillation in the tropical stratospheric wind by nonlinear principal component analysis

The zonal winds at several levels between 70 and 10 hPa (roughly 20–30 km) measured at near‐equatorial stations during 1956–2000 were analyzed to produce a one‐dimensional approximation. The neural network‐based technique applied was the circular nonlinear principal component analysis (NLPCA.cir) designed to characterize quasiperiodic phenomena. The reconstructed height‐time series of wind based on the one‐dimensional NLPCA.cir captures many of the characteristic features of the observed quasi‐biennial oscillation (QBO). The nonlinear results were evaluated relative to comparable linear principal component analysis and found to produce a superior one‐dimensional representation of the data. The NLPCA.cir analysis produces a single time series of QBO phase based on data at all levels. This phase was then applied to demonstrate a strong correlation of the state of the tropical QBO and boreal winter high‐latitude stratospheric temperatures.