Global Modes of Climate Variability

The atmosphere, hydrosphere, and cryosphere form a fully coupled climate system. This system exhibits a number of large-scale phenomena, such as the El Niño–Southern Oscillation, the Asian Monsoon, the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), and the Madden-Julian Oscillation. These modes of variability are oscillatory in character, and their state is monitored using so-called climate indices. Each of these scalar indices is a combination of several climate variables. Here we use a comprehensive set of 25 climate indices for time intervals that range between 1948 and 2011 and estimate an optimal set of lags between these indices to maximize their correlation. We show that most of the index pairs drawn from this set present a significant correlation on interannual time scales, and we optimize the lags between the 25 indices on these time scales. About two thirds of the total variability in each index can be described by using only the four leading principal components (PCs) of the entire set of lagged indices. Our index set's leading orthogonal modes exhibit several interannual frequencies: the first and largest component is associated with North Atlantic variability, while the second is linked with North Pacific variability. Lagged cross-covariances between the sea surface temperature field and these PCs yield geographical patterns that resemble the well-known NAO and PDO modes of variability. The few indices that are not described by the first four PCs are somewhat isolated and local in nature, such as the Sahel Rainfall. Further work is being carried out to compare these optimized-lag results with those provided by empirical model reduction (EMR) and multi-channel singular-spectrum analysis (M-SSA). Citation de Viron, O., J. O. Dickey, and M. Ghil (2013), Global modes of climate variability, Geophys. Res. Lett., 40, doi:10.1002/grl.50386.