A new method for identifying the Pacific-South American pattern and its influence on regional climate variability


The Pacific-South American (PSA) pattern is an important mode of climate variability in the mid-to-high southern latitudes. It is widely recognized as the primary mechanism by which the El Niño-Southern Oscillation (ENSO) influences the south-east Pacific and south-west Atlantic, and in recent years has also been suggested as a mechanism by which longer-term tropical sea surface temperature trends can influence the Antarctic climate. This study presents a novel methodology for objectively identifying the PSA pattern. By rotating the global coordinate system such that the equator (a great circle) traces the approximate path of the pattern, the identification algorithm utilizes Fourier analysis as opposed to a traditional Empirical Orthogonal Function approach. The climatology arising from the application of this method to ERA-Interim reanalysis data reveals that the PSA pattern has a strong influence on temperature and precipitation variability over West Antarctica and the Antarctic Peninsula, and on sea ice variability in the adjacent Amundsen, Bellingshausen and Weddell Seas. Identified seasonal trends towards the negative phase of the PSA pattern are consistent with warming observed over the Antarctic Peninsula during autumn, but are inconsistent with observed winter warming over West Antarctica. Only a weak relationship is identified between the PSA pattern and ENSO, which suggests that the pattern might be better conceptualized as preferred regional atmospheric response to various external (and internal) forcings.


The Pacific South-American (PSA) pattern has long been recognized as an important mode of regional climate variability. First named by Mo et al. (1987), the pattern was identified in a number of studies of the large-scale Southern Hemisphere (SH) circulation during the late 1980s and early 1990s (e.g. Kidson, 1988; Ghil et al., 1991; Lau et al., 1994). A link between the pattern and Rossby wave dispersion associated with the El Niño-Southern Oscillation (ENSO) was soon found (e.g. Karoly, 1989), and this work was followed by a number of detailed analyses of the characteristics of the pattern and its downstream impacts (e.g. Mo et al., 1998; Mo, 2000; Mo et al., 2001). In the period since these initial climatological accounts, substantial advances have been made in the methods and datasets used to identify quasi-stationary Rossby wave patterns. Given that the PSA pattern has been implicated in recent Antarctic temperature and sea ice trends, these advances could be employed to better understand the role of the pattern in high latitude climate variability and its climatological characteristics more generally (e.g. spatial pattern, propagation, seasonal and interannual variability).

The PSA pattern is most commonly analyzed in terms of a pair of Empirical Orthogonal Function (EOF) modes (e.g. Figure \ref{fig:eof}). Known as PSA-1 and PSA-2, these modes are in quadrature and depict a wave train