Meteorological drivers of the low-cloud radiative feedback pattern effect and its uncertainty

Abstract. The radiative feedback pattern effect remains a large source of uncertainty for both projections of future trends and interpretations of past trends in global temperature. The pattern effect is defined as the difference in feedbacks between transient and long-term simulations, and past work shows that is primarily attributed to changes in the marine low-cloud radiative feedback. Here we use low cloud meteorological kernels to map out both the primary cloud controlling factors through which changing surface temperature patterns drive changes in low-cloud feedback, as well as the sources of model spread. We find that the pattern effect is almost entirely driven by changes in EIS in the Southern Hemisphere, particularly in the South East Pacific and Southern Ocean. In both past and future simulations, inter-model spread is primarily caused by model differences in the sensitivity of low clouds to the environmental conditions, rather than differences in the simulated evolution of environmental conditions.

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Publication Details

Journal
Atmospheric chemistry and physics
Published
2026-03-27
DOI
https://doi.org/10.5194/acp-26-4289-2026
Primary Topic
Climate variability and models
Type
article
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Meteorological drivers of the low-cloud radiative feedback pattern effect and its uncertainty

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Meteorological drivers of the low-cloud radiative feedback pattern effect and its uncertainty

Cristian Proistosescu, Yuan‐Jen Lin, Rachel Yuen Sum Tam, Timothy A. Myers, Kate Marvel, Mark D. Zelinka
article en

Abstract

Abstract. The radiative feedback pattern effect remains a large source of uncertainty for both projections of future trends and interpretations of past trends in global temperature. The pattern effect is defined as the difference in feedbacks between transient and long-term simulations, and past work shows that is primarily attributed to changes in the marine low-cloud radiative feedback. Here we use low cloud meteorological kernels to map out both the primary cloud controlling factors through which changing surface temperature patterns drive changes in low-cloud feedback, as well as the sources of model spread. We find that the pattern effect is almost entirely driven by changes in EIS in the Southern Hemisphere, particularly in the South East Pacific and Southern Ocean. In both past and future simulations, inter-model spread is primarily caused by model differences in the sensitivity of low clouds to the environmental conditions, rather than differences in the simulated evolution of environmental conditions.

Atmospheric chemistry and physicsVol. 26(6)
Life below water
Openalex Percentile: Top 4%
Climate variability and models
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