The impact of interannual variability on multidecadal total ozone simulations

The core information for this publication's citation.: 
Fleming, E. L., C. H. Jackman, D. Weisenstein, and M. K. W. Ko (2007), The impact of interannual variability on multidecadal total ozone simulations, J. Geophys. Res., 112, D10310, doi:10.1029/2006JD007953.
Abstract: 

We have used a two-dimensional chemistry and transport model to study the effects of interannual dynamical variability on global total ozone for 1979–2004. Long-term meteorological data from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis-2 project and the European Center for Medium Range Weather Forecasts (ECMWF) updated reanalysis (ERA-40) are used to construct yearly dynamical fields for use in the model. The simulations qualitatively resolve much of the seasonal and interannual variability observed in long-term global total ozone data, including fluctuations related to the quasi-biennial oscillation (QBO). We performed a series of model experiments to examine the relative roles of the interannual variability, changes in halogen and volcanic aerosol loading, and the 11-year solar cycle in controlling the multidecadal ozone changes. Statistical regression is used to isolate these signals in the observed and simulated time series. At Northern midlatitudes, the simulated interannual dynamical variability acts to reinforce the chemical ozone depletion caused by the enhanced aerosol loading following the eruption of Mt. Pinatubo in 1991. However, at Southern midlatitudes, the interannual variability masks the aerosol-induced chemical effect. The simulated solar cycle response in total ozone is generally consistent with observations and is primarily due to the direct photochemical effect. The halogen-induced total ozone trend for 1979–1996 derived from the model is in good agreement with that derived from observations in the tropics and the Northern Hemisphere (NH). However, at Southern midlatitudes, the trend derived from the model is more sensitive to halogen loading than that derived from observations.

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