Scientists have long recognized that the Arctic is warming at a much faster rate than the rest of the planet, a process known as Arctic amplification. However, many current climate models have struggled to accurately capture just how rapidly this warming is happening. One key reason is how these models represent Arctic clouds. Research shows that many models overestimate the amount of ice within these clouds, which causes them to underestimate how much heat the clouds trap. These so-called mixed-phase clouds, containing both ice and liquid water, are more effective at holding heat than previously thought, especially as they shift towards more liquid water with rising temperatures. This misrepresentation leads to models that don’t fully reflect the fast pace of Arctic warming observed in recent years.
To improve predictions, scientists are updating climate models with better data and new techniques. For example, the latest generation of models (CMIP6) includes improved simulations of Arctic precipitation and sea ice, but challenges like cold biases in winter temperatures still remain. Researchers are now using detailed observations from expeditions like MOSAiC and advanced methods such as machine learning to refine these models further. By enhancing how clouds and other unique Arctic processes are represented, scientists aim to produce more accurate forecasts of Arctic warming. These improvements are critical for informing global climate policies and preparing for the significant environmental and social impacts that accelerated Arctic change will bring. More