An analytical framework reduces cloud feedback uncertainty by linking percentage cloud change to surface ocean warming patterns

Clouds significantly influence Earth’s radiative balance with complex changes in response to surface warming. The key drivers of the changes are the sea surface temperature (SST) pattern effect that reshapes cloud distributions, and the beta feedback that scales low-level fraction change to climatological amounts. Cloud radiative feedback remains the largest source of uncertainty in future climate projections, but current constraints are insufficient. Here, we demonstrate that the percentage change in tropical cloud fraction, driven by spatial patterns in SST increase, is linked to cloud height variations. We introduce a proportional warmer-get-higher paradigm and develop a pattern-based analytical framework, identifying three key factors governing cloud feedback: percentage cloud sensitivity to SST, climatological cloud cover, and SST warming patterns relative to the tropical mean. By leveraging recent observations to constrain these factors in two stages, we establish a process-oriented emergent constraint on projected cloud feedback in the 21st century. The first stage substitutes simulated cloud sensitivity and mean cloud cover to correct biases and reduce the spread by half. Then, the second stage attempts to further constrain the SST pattern effect, which explains 79% of the remaining spread in an attribution procedure. This percentage framework yields total, low, middle, and high cloud feedback of 0.49 ± 0.27, 0.33 ± 0.21, 0.09 ± 0.09, and 0.07 ± 0.06 W m-2 K-1 (90% confidence), respectively. It reduces intermodel uncertainty by 59% for cloud feedback and 33% for surface warming, resulting in a climate sensitivity of 4.08 ± 0.97 K.