Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations.

Area of Science:

• Climate Science
• Atmospheric Physics
• Numerical Modeling

Background:

• Radiative-convective equilibrium (RCE) is a simplified model of the tropical atmosphere used to study fundamental climate processes.
• Understanding cloud feedbacks and convective activity is crucial for accurate climate projections.

Purpose of the Study:

• To investigate the role of clouds and convection in determining cloud feedbacks, climate sensitivity, convective aggregation, and equilibrium climate using RCE.
• To intercompare a diverse range of numerical models, including GCMs, SCMs, CRMs, LES, and GCRMs.

Main Methods:

• Utilizing the Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) framework.
• Analyzing results from an ensemble of over 30 different climate models.
• Configuring models in radiative-convective equilibrium (RCE) to simulate idealized tropical atmospheric conditions.

Main Results:

• Significant inter-model differences exist in temperature, humidity, and cloudiness profiles.
• A majority of models show anvil clouds rising, warming, and decreasing in coverage with increased sea surface temperature (SST).
• Most models exhibit self-aggregation, leading to a drier, warmer troposphere, reduced high cloudiness, and increased cooling to space.

Conclusions:

• Self-aggregation's influence on climate sensitivity varies, with no clear trend related to warming.
• Models with parameterized convection generally show lower climate sensitivities compared to those with explicit convection.
• In parameterized convection models, aggregated simulations yield lower climate sensitivities than unaggregated ones.