Understanding differences in upper stratospheric ozone response to changes in...

Douglass, A., R. Stolarski, S. Strahan, and L. D. Oman (2012), Understanding differences in upper stratospheric ozone response to changes in chlorine and temperature as computed using CCMVal-2 models, J. Geophys. Res., 117, D16306, doi:10.1029/2012JD017483.
Abstract: 

Projections of future ozone levels are made using models that couple a general circulation model with a representation of atmospheric photochemical processes, allowing interactions among photochemical processes, radiation, and dynamics. Such models are known as coupled chemistry-climate models (CCMs). Although developed from common principles and subject to the same boundary conditions, simulated ozone time series vary among models for scenarios for ozone depleting substances (ODSs) and greenhouse gases. Photochemical processes control the upper stratospheric ozone level, and there is broad agreement among CCMs in that ozone increases as ODSs decrease and temperature decreases due to greenhouse gas increase. There are quantitative differences in the ozone sensitivity to chlorine and temperature. We obtain insight into differences in sensitivity by examining the relationship between the upper stratospheric seasonal cycles of ozone and temperature as produced by fourteen CCMs. All simulations conform to expectation in that ozone is less sensitive to temperature when chlorine levels are highest because chlorine catalyzed loss is nearly independent of temperature. Analysis reveals differences in simulated temperature, ozone and reactive nitrogen that lead to differences in the relative importance of ozone loss processes and are most obvious when chlorine levels are close to background. Differences in the relative importance of loss processes underlie differences in simulated sensitivity of ozone to composition change. This suggests 1) that the multimodel mean is not a best estimate of the sensitivity of upper stratospheric ozone to changes in ODSs and temperature; and 2) that the spread of values is not an appropriate measure of uncertainty.

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Research Program: 
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Modeling Analysis and Prediction Program (MAP)