Seminar

Abstract

The atmospheric response to increasing greenhouse gas concentrations is often described in terms of the climate sensitivity, or the global-mean surface temperature response. The climate sensitivity of global climate models remains poorly constrained, in large part due to uncertainty in cloud feedbacks. However, the atmospheric response to increasing greenhouse gases in global climate models is not limited to an increase in the global-mean surface temperature: for example, the midlatitude jet streams shift poleward, the Hadley circulation expands, and consequently the hydrological cycle is altered. The linkages among these changes in the atmospheric circulation, cloud feedbacks, and climate sensitivity remain poorly understood.

Atmospheric circulation changes and cloud feedbacks might be expected to closely follow the time evolution of global-mean surface temperature warming. In this talk, I will show evidence from CMIP5 global climate models that key features of the large-scale atmospheric circulation of the Southern Hemisphere actually respond to increased CO2 on a faster time scale than the global-mean surface temperature. Consequently, any cloud feedbacks driven primarily by changes in the circulation will also occur on a faster timescale than the global-mean surface temperature. For example, as the Southern Hemisphere midlatitude storm tracks and their associated cloud features shift poleward, they move from a latitude of greater incoming solar radiation to one of less incoming solar radiation. Such poleward movement in the clouds leads to a warming feedback in many climate models, as the clouds will be reflecting less solar radiation when they move to higher latitudes. However, there is little evidence from NASA CERES satellite observations to suggest that a poleward movement of the storm tracks alone could contribute to a large warming feedback. The positive circulation-driven cloud feedback that occurs in climate models appears to arise from an improper sensitivity of the models' low-level clouds to changes in the boundary layer inversion strength. Implications of these model biases for future climate projections will be discussed.

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Kevin Grise has been an assistant professor in the Department of Environmental Sciences at the University of Virginia since 2014. His research focuses on large-scale atmospheric dynamics and their role in climate variability and change. Prior to arriving at University of Virginia, he spent one year as a postdoc at McGill University in Montreal and two years as a postdoc at Lamont-Doherty Earth Observatory (Columbia University) in New York. He has a B.S. in meteorology from Penn State University and a M.S. and Ph.D. in atmospheric science from Colorado State University.