Impacts of the Unforced Pattern Effect on the Cloud Feedback in CERES Observations and Climate Models. Issue 2 (20th January 2022)

• Record Type: Journal Article
• Authors: Chao, Li‐Wei; Muller, Jacob C.; Dessler, Andrew E.
• Is Part Of: Geophysical research letters. Volume 49:Issue 2(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-01-20
• Subjects: cloud feedback -- pattern effect -- climate models; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2021GL096299
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: The equilibrium climate sensitivity estimated from different sources is inconsistent due to its dependence on the surface warming pattern. Cloud feedbacks have been identified as the major contributor to this so‐called pattern effect. We find a large unforced pattern effect in CERES data, with cloud feedback estimated from two consecutive 125‐month periods (March 2000–July 2010 and August 2010–December 2020) changing from −0.45 ± 0.85 to +1.2 ± 0.78 W/m 2 /K. When comparing to models, 27% of consecutive 10‐year segments in CMIP6 control runs have differences similar to the observations. We also compare the spatial patterns in the CERES data to those in climate models and find they are similar, with the East Pacific playing a key role. This suggests that the impact of the unforced pattern effect can be significant and that models are capable of reproducing its global‐average magnitude. Plain Language Summary: Climate sensitivity, the amount of surface warming in response to increasing carbon dioxide, is often used as a metric to quantify the severity of climate change. The estimates of climate sensitivity from different sources, however, are not consistent. The main reason is that the response of clouds to surface temperature changes, called cloud feedback, depends on the spatial pattern of surface warming. We investigate the impact of this so‐called pattern effect on cloud feedback in observations and climate models. Here we find that the observed cloud feedbacks calculated from two consecutive decades have significant differences in both global mean value and spatial pattern, and the climate models produce similar results. This highlights the fact that differences of surface warming patterns can have large influences on cloud feedbacks, and climate models have the ability to reproduce what happened in the real world. Key Points: The difference in cloud feedback between two ∼10‐year periods inferred from CERES is 1.6 ± 1.1 W/m 2 /K The distinct difference in cloud feedback verifies the existence of a large unforced pattern effect CMIP6 models produce unforced pattern effects of similar magnitude and spatial structure to those seen in the observations