CMIP3 Subtropical Stratocumulus Cloud Feedback Interpreted Through a Mixed-Layer Model

TitleCMIP3 Subtropical Stratocumulus Cloud Feedback Interpreted Through a Mixed-Layer Model
Publication TypeJournal Article
Year of Publication2012
JournalJournal of Climate
Abstract / Summary

Large-scale conditions over subtropical marine stratocumulus areas are extracted from global climate models (GCMs) participating in Phase 3 of the Coupled Model Intercomparison Project (CMIP3) and used to drive an atmospheric mixed-layer model (MLM) for current and future climate scenarios. Cloud fraction is computed as the fraction of days where GCM forcings produce a cloudy equilibrium MLM state. This model is a good predictor of cloud fraction and its temporal variations on timescales longer than one week, but overpredicts liquid water path and entrainment.GCM cloud fraction compares poorly with observations of mean state, variability, and correlation with estimated inversion strength (EIS). MLM cloud fraction driven by these same GCMs, however, agrees well with observations, suggesting that poor GCM low cloud fraction is due to deficiencies in cloud parameterizations rather than large-scale conditions. Nevertheless, replacing the various GCM cloud parameterizations with a single physics package (the MLM) does not reduce inter-model spread in low-cloud feedback because the MLM is more sensitive than the GCMs to existent inter-model variations in large-scale forcing. This suggests that improving GCM low cloud physics will not by itself reduce inter-model spread in predicted stratocumulus cloud feedback.Differences in EIS and EIS change between GCMs are found to be a good predictor of current-climate MLM cloud amount and future cloud change. CMIP3 GCMs predict a robust increase of 0.5-1 K in EIS over the next century, resulting in a 2.3-4.5% increase in MLM cloudiness. If EIS increases are real, subtropical stratocumulus may damp global warming in a way not captured by the GCMs studied.

URLhttp://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-12-00188.1
DOI10.1175/JCLI-D-12-00188.1
Journal: Journal of Climate
Year of Publication: 2012

Large-scale conditions over subtropical marine stratocumulus areas are extracted from global climate models (GCMs) participating in Phase 3 of the Coupled Model Intercomparison Project (CMIP3) and used to drive an atmospheric mixed-layer model (MLM) for current and future climate scenarios. Cloud fraction is computed as the fraction of days where GCM forcings produce a cloudy equilibrium MLM state. This model is a good predictor of cloud fraction and its temporal variations on timescales longer than one week, but overpredicts liquid water path and entrainment.GCM cloud fraction compares poorly with observations of mean state, variability, and correlation with estimated inversion strength (EIS). MLM cloud fraction driven by these same GCMs, however, agrees well with observations, suggesting that poor GCM low cloud fraction is due to deficiencies in cloud parameterizations rather than large-scale conditions. Nevertheless, replacing the various GCM cloud parameterizations with a single physics package (the MLM) does not reduce inter-model spread in low-cloud feedback because the MLM is more sensitive than the GCMs to existent inter-model variations in large-scale forcing. This suggests that improving GCM low cloud physics will not by itself reduce inter-model spread in predicted stratocumulus cloud feedback.Differences in EIS and EIS change between GCMs are found to be a good predictor of current-climate MLM cloud amount and future cloud change. CMIP3 GCMs predict a robust increase of 0.5-1 K in EIS over the next century, resulting in a 2.3-4.5% increase in MLM cloudiness. If EIS increases are real, subtropical stratocumulus may damp global warming in a way not captured by the GCMs studied.

DOI: 10.1175/JCLI-D-12-00188.1
Citation:
Caldwell, PM, Y Zhang, and SA Klein.  2012.  "CMIP3 Subtropical Stratocumulus Cloud Feedback Interpreted Through a Mixed-Layer Model."  Journal of Climate.  https://doi.org/10.1175/JCLI-D-12-00188.1.