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This page contains a single entry from the blog posted on October 7, 2009 3:30 AM.

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Seminar: Wednesday, October 7, 2009 at 3:30 p.m.

How do we know whether to believe model predictions?
Dr. Susan Strahan
Goddard Space Flight Center

Chemistry climate models (CCMs) embody the state of our knowledge of atmospheric chemistry and physics. They are used to predict future changes in atmospheric composition and climate based on estimates of future emissions of CO2, CH4, N2O, chlorofluorocarbons (CFCs), and other trace species. Every four years, chemistry climate modeling groups participate in an international effort sponsored by the World Meteorological Organization (WMO) to predict the future state of the stratospheric ozone. 13 CCMs participated in the most recent WMO assessment and they produced a wide range of predictions for benchmarks such as the date of the disappearance of the Antarctic ozone hole and the return of northern midlatitude ozone to 1980 levels. How do we know which, if any, of the model predictions to believe?
The answer lies in the use of observations to assess the ability of CCMs to represent key aspects of stratospheric circulation and chemistry. The analyses of several decades of aircraft, balloon, and satellite trace gas observations such as O3, H2O, CH4, and N2O have identified many important transport processes in the stratosphere. We use observational analyses to derive diagnostics for stratospheric transport processes, and because of them we now understand many aspects of stratospheric circulation, e.g, the rate at which air ascends in the tropical stratosphere and the existence of transport barriers in the subtropics and polar regions. Diagnostics are applied to model simulations to assess whether models realistically represent known processes. In recent years an international group of scientist has been systematically applying a growing set of stratospheric chemistry and transport diagnostic to CCMs in order to better understand their behavior and determine model credibility. This effort is providing a rational basis for distinguishing between model predictions of the future of stratospheric ozone.


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