2.3 Using transport diagnostics to understand chemistry climate model ozone simulations

Tuesday, 25 January 2011: 2:15 PM
3B (Washington State Convention Center)
Susan E. Strahan, Univ. of Maryland, Greenbelt, MD; and A. R. Douglass and R. S. Stolarski

While stratospheric ozone distributions depends on transport, chemistry, and temperature (dynamics), a significant portion of the O3 column resides in the lower stratosphere where O3 is largely controlled by transport. Thus, a critical aspect of producing a realistic ozone simulation is credible LS transport. We demonstrate the use of N2O and mean age observations to identify realistic transport between 150-30 hPa. The results are applied to 15 CCMS participating in the 2010 WMO assessment to diagnose circulation strength and tropical isolation. Comparison of the observed and simulated N2O/mean age relationship identifies models with fast or slow circulations as well as those with problems with the recirculation of older air into the tropics.

We link the diagnosed model transport behavior with a model's ability to produce realistic tropical and midlatitude O3 profiles in the lower stratosphere. Models with the most realistic LS transport agree more closely with observations and each other than the models with the greatest tropical transport problems. We incorporate results from the chemistry evaluations in the SPARC CCMVal Report (2010) in order to explain the range of CCM predictions for the return to 1980 dates for global (60S-60N) and Antarctic column ozone. While Antarctic return dates are in general strongly correlated to vortex Cly levels in the LS, the correlation between vortex Cly and transport can be altered due to problems with a model's Cl chemistry or conservation. In both regions, the range of predictions made by the models with good LS transport and chemistry is smaller than the range predicted by 1) all participating CCMs , and 2) the set of CCMs that shows close agreement with observed column O3 from 1980-2006 (10 models). This study suggests that the current range of predicted return dates is unnecessarily large due to identifiable model transport deficiencies.

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