Global surface warming is recognized for its spatial asymmetry. However, mainstream climate assessments solely rely on average surface temperature change (∆T_mean) as a primary indicator, which is statistically insufficient to characterize such asymmetric patterns. In this presentation, we will move beyond the conventional mean-based framework. We will quantify the long-term change in global warming asymmetry and discuss its mathematical and practical implications for climate impact assessment and mitigation.
Our findings reveal a significant increase in warming asymmetry since 1900. Among 58 IPCC reference regions, the Arctic Ocean, Northwest North America, and Russian Regions contribute only ~50% of this trend, with other Northern Hemisphere mid-high latitudes accounting for an additional ~30%. Climate models project an emission-dependent nonlinear acceleration of warming asymmetry, with trends under SSP 5-8.5 being approximately 3–8 times greater than those under SSP2-4.5 and SSP1-2.6. Consequently, the global surface temperature change deviates from its original Gaussian distribution toward a highly skewed bimodal distribution. This increasing asymmetry implies a widening "divergence" within the climate system that is dependent on emission levels, including the gap between the ∆T_mean and those observed across the majority of regions. Without rigorous emission reductions, this gap could foster cognitive biases in public awareness toward climate change, undermining public acceptance of climate mitigation policies.