Fingerprinting the Pattern of Natural Variability in Recent Global Warming
Climate model simulations that have internally generated global cooling and Arctic warming are rare but produce a robust and unique natural variability trend pattern that is imprinted in the observational record.
Image by David Stanfield | Pexels
The extent to which model-observation differences of recent climate change is linked to systemic model biases or natural variability is crucially important. If the former is to blame, then model simulations of future warming may be less reliable. Otherwise, future warming may be better predicted by the models. This work highlights that a large component of this model-observation discrepancy is due to natural variability, bolstering faith in current climate models. The authors note that while this natural variability is a key contribution to the model-observation difference, natural variability alone cannot explain all the differences, leaving the door open to potential model biases or observation uncertainties.
When comparing model simulations of Earth's recent warming to real-world observations, differences may arise from several factors. Two important factors are 1) model errors in the simulated response to increased greenhouse gases, and 2) natural fluctuations within the climate system. Thus, quantifying the role of these natural fluctuations is important for the assessment of model-observation differences. A previous study by the same team has shown that natural climate variability has depressed global warming and enhanced Arctic warming. By compositing the trend patterns from model simulations in which natural variability warms the Arctic but has a global cooling effect, the current study reveals that most 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, this work suggests that natural variability is an important component of several noteworthy differences between models and observations.