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| Pacific–South American pattern | |
|---|---|
| Name | Pacific–South American pattern |
| Abbreviation | PSA |
| Region | Pacific Ocean, South America, Southern Hemisphere |
| First described | 1990s |
| Related | El Niño–Southern Oscillation, Southern Annular Mode, Pacific Decadal Oscillation |
Pacific–South American pattern The Pacific–South American pattern is a prominent mode of atmospheric variability linking the Pacific Ocean basin with South America and the Southern Hemisphere extratropics. It modulates circulation across the tropical Pacific, South Pacific Convergence Zone, and high-latitude sectors, interacting with phenomena such as El Niño–Southern Oscillation, the Southern Annular Mode, and the Pacific Decadal Oscillation. The pattern influences seasonal weather over Chile, Peru, Argentina, Australia, and New Zealand, and affects marine conditions near the Galápagos Islands and Falkland Islands.
The PSA emerges from analyses of atmospheric reanalyses and observational networks including ERA-Interim, NCEP/NCAR reanalysis, and JRA-55, and is often identified through empirical orthogonal function methods applied to sea level pressure, 500 hPa geopotential height, and sea surface temperature fields. Studies by groups at NOAA, CSIRO, Columbia University, University of California, Santa Cruz, and University of Washington have characterized spatial patterns resembling Pacific-centered wave trains extending toward Antarctica and along the South American Andes. Research published in journals such as Journal of Climate, Nature Geoscience, Geophysical Research Letters, and Climate Dynamics has advanced understanding of its structure.
The PSA comprises multiple modes, commonly labeled PSA-1 and PSA-2, identified via EOF analysis and rotated EOF techniques applied to sea level pressure or 500 hPa geopotential height anomalies. PSA-1 typically projects from the central tropical Pacific Ocean toward the southern cone of South America and the Amundsen Sea, while PSA-2 exhibits distinct meridional phase propagation toward the Antarctic Peninsula and Ross Sea. These modes are analyzed alongside canonical correlation analysis, singular value decomposition, and wavelet spectra used by researchers at MIT, Princeton University, and University of Oxford.
Mechanistic explanations invoke tropical-extratropical interaction via atmospheric waveguide processes, baroclinic instability, and Rossby wave propagation associated with convective forcing in regions like the Warm Pool, Maritime Continent, and the eastern tropical Pacific Ocean near Ecuador and the Galápagos Islands. Links with upper-tropospheric jets, the subtropical jet stream, and Southern Hemisphere storm tracks implicate interactions with blocking over Patagonia and the South Atlantic Convergence Zone. Modeling studies from NCAR, Met Office Hadley Centre, and IPSL attribute PSA variability to anomalous tropical convection, ocean–atmosphere coupling modulated by ENSO, and stratosphere–troposphere coupling influenced by the Antarctic Oscillation.
PSA teleconnections affect precipitation and temperature anomalies across Peru, Ecuador, Bolivia, Paraguay, Uruguay, and southern Brazil as well as remote impacts in Tasmania and the South Island (New Zealand). It modifies sea surface temperature patterns affecting fisheries off Peru and Chile, alters wind-driven upwelling near the Humboldt Current, and modulates sea ice extent around the Bellingshausen Sea and Weddell Sea. Interactions with El Niño, La Niña, and the Indian Ocean Dipole can amplify droughts in Central Chile or enhance rainfall over the Bolivian Altiplano, with socioeconomic consequences for sectors represented by institutions like World Bank, FAO, and regional agencies in CONAGUA-type organizations.
Long-term records from HadISST, GPCP, and paleoclimate proxies including tree rings studied by teams at University of Arizona and Lamont–Doherty Earth Observatory show interannual to decadal PSA variability modulated by PDO and multidecadal oscillations. Trend analyses in the context of anthropogenic climate change use coupled models participating in the CMIP5 and CMIP6 intercomparison projects coordinated by PCMDI and IPCC authors. Observed shifts in PSA patterns have been linked to changes in the Southern Westerlies, snowpack variability in the Andes, and shifts in marine ecosystems documented by researchers at Scripps Institution of Oceanography and Universidad de Chile.
Seasonal forecasting systems at NOAA Climate Prediction Center, Bureau of Meteorology (Australia), Met Office, and regional centers incorporate PSA indices into statistical and dynamical schemes, including NCEP CFSv2 and multimodel ensembles from Iscam-style networks. Predictability studies assess skill using hindcasts from ECMWF and regional climate models such as RegCM and WRF downscaling used by labs at CSIR and INPE. Challenges include representing tropical convection, ocean mixed-layer processes, and stratospheric teleconnections; data assimilation efforts leverage ARGO floats, TAO/TRITON arrays, and satellite missions like Aqua and TRMM.
PSA-driven variability influences crop yields of soybean and maize in Argentina and Brazil, affects hydropower reservoirs managed by utilities in Chile and Peru, and alters fisheries for anchoveta and squid critical to ports such as Callao and Valparaíso. Impacts extend to urban water supply in Lima, wildfire regimes near Patagonia, and biodiversity hotspots managed by institutions like CONABIO and SERNATUR. Adaptation and mitigation planning by agencies including UNEP, World Meteorological Organization, and national meteorological services integrates PSA-informed projections into disaster risk reduction and resource management.
Category:Climate patterns