FY 2024

Unique temperature trend pattern associated with internally driven global cooling and Arctic warming during 1980-2022

Sweeney, A.J., Q. Fu, S. Po-Chedley, H. Wang, and M. Wang

Geophys. Res. Lett., 51(11), e2024GL108798, doi: 10.1029/2024GL108798, View open access article at AGU/Wiley (external link) (2024)

Diagnosing the role of internal variability over recent decades is critically important for both model validation and projections of future warming. Recent research suggests that for 1980–2022 internal variability manifested as Global Cooling and Arctic Warming (i-GCAW), leading to enhanced Arctic Amplification (AA), and suppressed global warming over this period. Here we show that such an i-GCAW is rare in CMIP6 large ensembles, but simulations that do produce similar i-GCAW exhibit a unique and robust internally driven global surface air temperature (SAT) trend pattern. This unique SAT trend pattern features enhanced warming in the Barents and Kara Sea and cooling in the Tropical Eastern Pacific and Southern Ocean. Given that these features are imprinted in the observed record over recent decades, this work suggests that internal variability makes a crucial contribution to the discrepancy between observations and model-simulated forced SAT trend patterns.

Plain Language Summary. When comparing model simulations of Earth's recent warming to real-world observations, differences may arise from several factors. Two important factors are the model errors in the simulated response to increased greenhouse gases, and natural fluctuations within the climate system that produced discrepancies between observations and models. Thus, quantifying the role of these natural fluctuations is important for the assessment of model-observation differences. Previous studies have shown that natural climate variability has depressed global warming and enhanced Arctic warming. By compositing the multi-decadal trend patterns from CMIP6 simulations in which natural variability warms the Arctic but has a global cooling effect, we find that the majority of these model simulations also produce enhanced warming in the Barents and Kara Seas and cooling in the Tropical Eastern Pacific and Southern Ocean due to natural variability. Since these are the exact features imprinted on observed surface temperature changes over 1980–2022, our work suggests that natural variability is an important component of several noteworthy differences between models and observations.