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.

This article is a post-print and can be cited as follows:

Irving D & Simmonds I (2016). A new method for identifying the Pacific-South American pattern and its influence on regional climate variability. Journal of Climate, 29, 6109-6125. doi:10.1175/JCLI-D-15-0843.1


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 extending along an approximate great circle path from the central Pacific Ocean to the Amundsen and Weddell Seas. Some authors interpret these patterns as a single eastward propagating wave (Mo et al., 1998), while others argue that variability in the PSA sector is better described as a set of geographically fixed regimes (Robertson et al., 2003). On a decadal timescale, PSA-1 has been related to sea surface temperature (SST) anomalies over the central and eastern Pacific, while on an interannual timescale it appears as a response to ENSO (Mo et al., 2001). The association of PSA-2 with tropical variability is less clear, with some authors relating it to the quasi-biennial component of ENSO variability (Mo, 2000) and others to the Madden-Julian Oscillation (Renwick et al., 1999). While most of the features of the PSA pattern are consistent with theory and/or modelling of Rossby wave dispersion from anomalous tropical heat sources (e.g. Liu et al., 2007; Li et al., 2015), it is recognized that the pattern can also result from internal atmospheric fluctuations caused by instabilities of the basic state (and that both mechanisms likely act in concert; e.g. Grimm et al., 2009).

It has been shown that the PSA pattern plays a role in blocking events (Sinclair et al., 1997; Renwick et al., 1999), South American rainfall variability (Mo et al., 2001) and is also closely related to prominent regional features such as the Amundsen Sea Low (Turner et al., 2013), Antarctic Dipole (Yuan et al., 2001), Antarctic Circumpolar Wave (Christoph et al., 1998) and Southern Annular Mode (SAM; e.g. Ding et al., 2012; Fogt et al., 2012). While these are all important mid-to-high latitude impacts and relationships, in recent years the PSA pattern has been mentioned most frequently in the literature in relation to the rapid warming observed over West Antarctica and the Antarctic Peninsula (Nicolas et al., 2014). In particular, it has been suggested that seasonal trends in tropical Pacific SSTs may be responsible, via circulation trends resembling the PSA pattern, for winter (and to a lesser extent spring) surface warming in West Antarctica (Ding et al., 2011), spring surface warming over the western Antarctic Peninsula (Clem et al., 2015) and autumn surface warming across the entire Antarctic Peninsula (Ding et al., 2013). The pattern has also been associated with declines in sea ice in the Amundsen and Bellingshausen Seas (Schneider et al., 2012) and glacier retreat in the Amundsen Sea Embayment (Steig et al., 2012).

In identifying the PSA pattern as a possible contributor to these trends, the aforementioned studies looked through the lens of the variable/s of interest. For instance, Ding et al. (2011) performed a maximum covariance analysis to examine the relationship between central Pacific SSTs and the broader SH circulation (the 200 hPa geopotential height). The second mode of that analysis revealed a circulation resembling the PSA pattern (and that brings warm air over West Antarctica), and atmospheric model runs forced with the associated central Pacific SSTs produced a PSA-like wave train. While this is certainly a valid research methodology, the result would be more robust if a climatology of PSA pattern activity also displayed trends consistent with warming in West Antarctica. This concept of teleconnection reversibility was recently invoked to question the relationship between Indian Ocean SSTs and heat waves in south-western Australia (Boschat et al., 2016).

A climatology that addresses issues such as recent trends is currently lacking in the literature, so this study will present an update on our somewhat dated climatological understanding of the PSA pattern (Mo et al., 1998; Mo et al., 2001). Not only will it utilize a longer, higher quality reanalysis dataset than previous studies, it will also develop and apply a methodology that fully exploits the capabilities of Fourier analysis, as opposed to relying on a traditional EOF-based approach. This alternative methodology was adapted from a recent climatology of SH zonal wave activity (Irving et al., 2015) and seeks to avoid the issues associated with the stationary nature of spatial EOF modes, which can be problematic when trying to capture phase variations in a wave pattern of interest. This updated climatology will provide new insights into the variability, propagation and downstream impacts of the PSA pattern, including its role in recent high latitude trends.