La Niña-like sea surface temperature trend pattern reinforced by human activity

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Despite a steady rise in greenhouse gas concentrations in the atmosphere over the satellite era, a distinct decrease in sea surface temperature (SST) has been observed in the tropical central-to-eastern Pacific, whereas the Northwest and Southwest Pacific have exhibited a marked SST increase over the same period. Most of current and earlier climate model simulations, however, failed to reproduce this La Niña-like SST trend pattern, raising a question as to whether the observed tropical central-to-eastern Pacific cooling trend is either a forced response to greenhouse gas forcing or internally generated unforced variability. In a new study, published in the journal npj Climate and Atmospheric Science, an international team of scientists from South Korea and the United States of America shows that the observed La Niña-like SST trend pattern has been shaped, in large part, by a combination of internal climate variability and human-induced non-greenhouse gas forcing agents.

 It is well known that climate variability in the tropical Pacific exerts a large influence on weather and climate worldwide via atmospheric teleconnection. This implies that the response of tropical Pacific SST to increasing concentrations of greenhouse gases is a key factor determining the overall characteristics of human-induced future climate change. Hence, it is crucial to ensure that the physical processes governing the future evolution of mean state and variance changes for the tropical Pacific SST are sufficiently well depicted in climate models. One of the ways for testing the model performance is to check whether climate models are able to reproduce observed SST change and variability. Comparisons show that unlike observations that exhibit a La Niña-like SST trend pattern over the satellite era, model-simulated ensemble-mean SST trends rarely capture such a spatial pattern (Fig. 1). Considering that the characteristics of climate sensitivity and atmospheric teleconnections are closely linked to SST changes and variability in the tropical Pacific, the apparent observation-model discrepancy implies that the reliability of projected future climate changes might need to be carefully re-evaluated if greenhouse gas forcing is the main cause of the tropical Pacific cooling trends. Some previous studies, however, argued a potential role of internal climate variability and forcing agents other than greenhouse gas increases, which suggests that the observed La Niña-like SST trend pattern might have been driven, at least in part, by a reinforcing combination of low-frequency internal climate variability and non-greenhouse gas forcing agents.

Figure 1: Model-observation contrast in SST trends over the Pacific. (a-c) SST trends over the period 1979–2014 from (a) ERA5, (b) HadISST, and (c) COBE SST2. (d-f) Ensemble-mean SST trends over the same period for (d) ACCESS-ESM1-5, (e) CanESM5, and (f) MPI-ESM1-2-LR.
In order to elucidate the main process leading to the observed La Niña-like SST trend pattern and the causes responsible for related model-observation discrepancy, the research team led by Dr. Seong-Joong Kim, Vice President of Korea Polar Research Institute, South Korea, conducted a comprehensive analysis on a series of model simulations along with observations and reanalysis datasets over a post-war period. The research team found that in both observations and model simulations, low-frequency internal climate variability (more specifically, the Inter-decadal Pacific Oscillation or Pacific Decadal Oscillation) plays an important role in the occurrence of La Niña-like SST trend pattern. They also found that despite model biases and errors,  the ensemble-mean trends for some climate models do exhibit an enhanced zonal SST gradient along the equatorial Pacific, which suggest that the observed La Niña-like SST trend pattern is also linked to external forcing agents. To assess the validity of this hypothesis, they analyzed single-forcing large ensemble model simulations and found that human-induced stratospheric ozone depletion and/or aerosol changes have acted to strengthen the zonal SST gradient over the tropical Pacific via strengthening of Pacific trade winds, although the effect is model dependent (Fig. 2). These results imply that human-induced stratospheric ozone depletion and/or aerosol changes have reinforced the tropical Pacific cooling driven by low-frequency internal climate variability. This study therefore makes a crucial contribution to enhanced understanding of the cause of the La Niña-like SST trend pattern during the satellite era.
Figure 2: Ensemble-mean trends in the zonal SST gradient, defined as the SST difference between the western Pacific (10ºS-10ºN, 110ºE-180º) and the eastern Pacific (10ºS-10ºN, 180º-80ºW), under greenhouse gas-only (GHG, open circles), anthropogenic aerosol-only (AER, open squares), stratospheric ozone-only (filled stars in red), total ozone-only (filled stars in blue), and biomass burning emission-only (BMB, inverted open triangle in green) scenarios for IPSL-CM6A-LR, HadGEM3-GC31-LL, and the CESM2 Single Forcing Large Ensemble Project. Also shown are the ensemble-mean trends for the CESM2 Single Forcing Large Ensemble Project EE (filled stars in green) experiment and the multi-model, multi-ensemble mean trends for the historical minus hist-1950HC (filled stars in purple) and the historical minus hist-noLu (filled triangle in dark yellow) experiments. The x-axis denotes the end year of a given period starting from 1979.
This study demonstrating the linkage between stratospheric ozone depletion and/or aerosol changes and La Niña-like SST trend pattern implies that the current cooling trend might weaken in the future as both the ozone depletion and aerosol impacts will eventually weaken. The research team, however, acknowledges possible model biases and deficiencies as all-forcing climate model simulations rarely capture the observed cooling trends over the tropical central-to-eastern Pacific as well as over the Southern Ocean. Considering that the observational record can be regarded as one single realization, they emphasize that it is of particular importance to effectively devise a coordinated multi-model, multi-ensemble experimental design for fully resolving the model-observation discrepancy.

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