.png){kind=icon}
.png){kind=icon}
Return
Observational Constraints on the Cloud Feedback Pattern Effect
.png){kind=icon}
OA
AI
DOI：10.1175/JCLI-D-22-0862.1.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Model evidence for the pattern effect assumes that global climate models (GCMs) faithfully simulate how clouds respond to varying sea surface temperature (SST) patterns and associated meteorological perturbations. We exploit time-invariant satellite-based estimates of the sensitivity of marine low clouds to meteorological perturbations to estimate how these clouds responded to time-varying SST patterns and meteorology between 1870 and 2014. GCMs and reanalyses provide estimates of the historical meteorological changes. Observations suggest that increasing estimated inversion strength (EIS) between 1980 and 2014 produced a negative low cloud feedback, opposite to the positive feedback expected from increasing CO2. This indicates that the processes responsible for marine cloud changes from 1980 to the near present are distinct from those associated with an increase in CO2. We also observationally constrain the difference between the historical near-global marine low cloud feedback, lhist cloud, and that arising from increasing CO2, l4xCO(2) cloud. We find that this cloud feedback pattern effect depends strongly on time period and reanalysis dataset, and that varying changes in EIS and SST with warming explain much of its variability. Between 1980 and 2014, we estimate that l4xCO(2) cloud 2lhist cloud 5 0:78 6 0:21Wm22K21 (90% confidence) assuming meteorological changes from the Multiple Reanalysis Ensemble, implying a total pattern effect (that arising from all climate feedbacks) of 1.86 6 0.45 Wm22K21. This observational evidence corroborates previous quantitative estimates of the pattern effect, which heretofore relied largely upon GCMbased cloud changes. However, disparate historical meteorological changes across individual reanalyses contribute to considerable uncertainty in its magnitude.
Keywords:
Climate
Clouds
Feedback
Satellite observations
Climate models
Journal
IF:
4
Papers:
1.4W
Citations:
5.9W
