Abstract
The interannual variability and trends of sea surface temperature (SST) around southern South America are studied from 1982 to 2017 using monthly values of the Optimally Interpolation SST version 2 gridded database. Mid-latitude (30°–50°S) regions in the eastern South Pacific and western South Atlantic present moderate to intense warming (~0.4°C decade−1), while south of 50°S the region around southern South America presents moderate cooling (~ −0.3°C decade−1). Two areas of statistically significant trends of SST anomalies (SSTa) with opposite sign are found on the Patagonian Shelf over the southwest South Atlantic: a warming area delimited between 42 and 45°S (Northern Patagonian Shelf; NPS), and a cooling area between 49 and 52°S (Southern Patagonian Shelf; SPS). Between 1982 and 2017 the warming rate has been 0.15 ± 0.01°C decade−1 representing an increase of 0.52°C at NPS, and the cooling rate has been –0.12 ± 0.01°C decade−1 representing a decrease of 0.42°C at SPS. On both regions, the largest trends are observed during 2008–2017 (0.35 ± 0.02°C decade−1 at NPS and –0.27 ± 0.03°C decade−1 at SPS), while the trends in 1982–2007 are non-significant, indicating the record-length SSTa trends are mostly associated with the variability observed during the past 10 years of the record. The spectra of the records present significant variance at interannual time scales, centered at about 80 months (~6 years). The observed variability of SSTa is studied in connection with atmospheric forcing (zonal and meridional wind components, wind speed, wind stress curl and surface heat fluxes). During 1982–2007, the local meridional wind explains 25–30% of the total variance at NPS and SPS on interannual time scales. During 2008–2017, the SSTa at NPS is significantly anticorrelated with the local zonal wind (r = –0.85), while at SPS it is significantly anticorrelated with the meridional wind (r = –0.61). Our results show that a substantial fraction of the interannual variability of SSTa around southern South America can be described by the first three empirical orthogonal function (EOF) modes which explain 28, 16, and 12% of the variance, respectively. The variability of the three EOF principal components time series is associated with the combined variability of El Niño–Southern Oscillation, the Interdecadal Pacific Oscillation and the Southern Annular Mode.
Highlights
The variability of Sea Surface Temperature (SST), which is highly influenced by feedbacks with the atmosphere, is a sensitive indicator of climate change
Comparisons of climatological wind stress and wind stress curl in the southeast Southeastearn Pacific Ocean (SEP) and SWA estimated from NCEPR1, CFSR, Era-Interim, and CCMPv2 data during the overlapping period (1987–2017) reveal substantial differences in spatial distribution (Figure 2)
Intense positive SST anomalies (SSTa) linear trends are observed along the Brazil Current and the BrazilMalvinas Confluence (> 0.4◦C decade−1), while negative trends (< –0.2◦C decade−1) are observed in the northernmost extension of the Malvinas Current
Summary
The variability of Sea Surface Temperature (SST), which is highly influenced by feedbacks with the atmosphere, is a sensitive indicator of climate change. Recent observation-based estimates indicate a fast increase of global SST in the past decades as part of a long-term warming of the ocean surface since the mid-nineteenth century (Rhein et al, 2013; Abram et al, 2019). Ocean warming is considered a major driver of variability, inducing changes in circulation, mixing, oxygen content and bioavailability (Oschlies et al, 2018) which may promote the expansion of oxygen minimum zones (OMZ) and a reduction of available habitat for some species, temperature and chemistry-sensitive organisms (Stramma et al, 2012; Abram et al, 2019; Bindoff et al, 2019)
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