Atmospheric Chemistry and Physics Discussions www.atmos-chem-phys-discuss.net 1680-7367 1680-7375 8 4 2008 10.5194/acpd-8-12737-2008 http://www.atmos-chem-phys-discuss.net/8/12737/2008/ http://www.atmos-chem-phys-discuss.net/8/12737/2008/acpd-8-12737-2008.html http://www.atmos-chem-phys-discuss.net/8/12737/2008/acpd-8-12737-2008.pdf 12737 12767 2008-07-04 Transport mechanisms for synoptic, seasonal and interannual SF₆ variations in troposphere P. K. Patra prabir@jamstec.go.jp M. Takigawa G. S. Dutton K. Uhse K. Ishijima B. R. Lintner K. Miyazaki J. W. Elkins Frontier Research Center for Global Change, JAMSTEC, Yokohama 236 001, Japan NOAA Earth System Research Laboratory, Boulder, CO 80305, USA Umweltbundesamt - Federal Environment Agency, 63225 Langen, Germany Department of Atmospheric and Oceanic Sciences and Institute of Geophysics and Planetary Physics, University of California Los Angeles, Los Angeles, CA 90095-1565, USA We use an atmospheric general circulation model (AGCM) driven Chemistry-Transport Model (ACTM) to simulate the evolution of sulfur hexafluoride (SF₆) in the atmosphere. The model results are compared with continuous measurements at 6 sites over 71° N–90° S. These comparisons demonstrate that the ACTM simulations lie within the measurement uncertainty over the analysis period (1999–2006) and capture salient features of synoptic, seasonal and interannual SF₆ variability. To understand transport timescales of SF₆ within the troposphere, transport times of air parcels from the surface to different regions of the troposphere ("age") are estimated from a simulation of an idealized tracer. Monthly-mean, 2-box model exchange times (τ_ex) are calculated from both the observed and simulated SF₆time series at the 6 observing sites and show favorable agreement, suggesting that the model adequately represents large-scale interhemispheric transport. The simulated SF₆ variability is further investigated through decomposition of the mixing ratio time-tendency into advective, convective, and vertical diffusive components. The transport component analysis illustrates the role of each process in SF₆synoptic variability at the site level and provides insight into the seasonality of τ_ex.