RAPID: Evaluation of Climate Models in the Southeast Pacific Marine Stratocumulus Region

Texas A&M Research Foundation, College Station TX

Investigators

Abstract

This is one of 16 Rapid Response (RAPID) projects funded as the result of a Dear Colleague Letter (NSF 11-006) encouraging diagnostic analyses of climate model simulations prepared for the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). Research conducted in these projects is expected to lead to more detailed model intercomparisons, better understanding of robust model behaviors, and better understanding and quantification of uncertainty in future climate simulations. Marine stratocumulus (mSc) clouds occur in subtropical oceanic regions off the west sides of continents, and have a cooling effect on the earth's climate because of their strong reflection of incoming solar radiation. Regions dominated by mSc clouds have been shown to be an important driver of the large uncertainties in tropical cloud feedbacks in climate models, and are responsible for the large differences between model simulations and observations. Research conducted under this grant considers mSc properties in model simulations, and compares them with cloud properties found in recent observations from satellite instruments including the CloudSat Profiling Radar. The response of shortwave cloud radiative forcing to changes in sea surface temperature is examined, and model cloud diagnostic variables are compared to satellite observations to determine the underlying processes responsible for uncertainties in low-cloud feeback. The broader impact of the project lies in its support of the IPCC AR5, which is intended to provide information on climate change and its consequences to decision makers worldwide. Cloud feedbacks could play an important role in determining how much global warming comes from the expected increases in greenhouse gas concentrations, so research leading to better understanding of cloud feedbacks and better representation of clouds in climate models would be beneficial for understanding the likely severity of anthropogenic climate change.