1. . Sensitivity Studies of Ozone Depletion with a 3D CTM Wuhu Feng 1, M.P. Chipperfield 1, S. Dhomse 1, L. Gunn 1, S. Davies 1, B. Monge-Sanz 1, V.L. Harvey 2, C.E. Randall 2, M.L. Santee 3 1.1. School of Earth and Environment, University of Leeds, U.K. 2. LASP, University of Colorado, Boulder, U.S.A. 3. JPL, California Institute of Technology, Pasadena, California, U.S.A. earfw@env.leeds.ac.uk Chipperfield, M.P., JGR, 104, 1781-1805, 1999. Feng W., et al., ACP, 7, 2357-2369, 2007. Feng W, et al, GRL, doi:10.1029/2006GL029098,2007. 3.1 Modelled Ozone Loss Under Different Meteorological Conditions 2. SLIMCAT 3D CTM 3D off-line chemical transport model forced by meteorlogical analyses.  -  vertical coordinate. Detailed chemical scheme. Chemical data assimilation scheme Different treatment of PSCs: (i) equilibrium denitrification scheme or (ii) detailed DLAPSE microphysical scheme. 1. Introduction 3D CTMs and CCMs have been widely used to study the dynamical and chemical processes which control polar ozone losses and mid-latitude ozone trends. However, there are still some uncertainties in both the models and our understanding. In this poster, a number of model experiments are used to discuss some of these uncertainties. We show the modelled Arctic ozone loss under different meteorological conditions (Fig.1) and discuss the denitrification effect on the Arctic ozone loss (Fig.2) and the impact of different absorption cross section of Cl 2 O 2 (Fig. 3). Model transport issues are discussed by running the CTM with options of assimilation of long- lived traces (HALOE CH 4, O 3, HCl and H 2 O from 1991-2002) (Fig. 4, 5) and by using the new ERA-Interim 4D-var reanalyses (1989-1998) (Fig 6). Fig 1. Time series of vortex-averaged model chemical ozone loss for 456 K (%) for simulations of 14 Arctic winters. Also shown is the accumulated daily relative sunlit area north of 66 o N geographic latitude integrated since December 1 (sza  93 o ) in units of relative area  days (circles, right axis). 3.2 Denitrification Effect on Arctic Ozone Loss 3.5 Effect of Meteorological Analyses Fig 2. Comparisons of HNO 3 and ClO from AURA MLS measurements and simulations using different PSC schemes (equilibrium, DLAPSE and no sedimentation) and without chlorine activation and N 2 O5+H 2 O reaction on liquid aerosols at 456 K and their impact on Arctic ozone loss. Fig 6. Comparisons of ozonesonde observations at Resolute (75N) with SLIMCAT results using ERA-40 and ERA-Interim meteorological analyses. 3.4 Effect of Chemical Data Assimilation Fig 3. Impact of different laboratory measurements (Burkholder et al. (1990), JPL (2006), Huder and Demore (1995) and Pope et al. (2007)) of Cl 2 O 2 absorption cross section on the polar ozone loss rate at 475 K for Arctic winter 2002/03. Fig 4. CH 4 zonal mean for July 1992 from SLIMCAT runs with/without assimilation of HALOE data.  Arctic ozone loss is initially limited by the availability of sunlight in early winter and curtailed by the breakdown on the vortex in late winter/spring.  Year-to-year variations of polar Arctic O 3 loss due to different meteorological conditions. 3.3 Cl 2 O 2 Photolysis  Modelled O 3 loss is sensitive to the absorption cross sections of Cl 2 O 2  Applying the new cross section from Pope et al. (2007) in the model leads to large discrepancy and very poor agreement with observations.  SLIMCAT with detailed DLAPSE scheme is less denitrified than using equilibrium scheme and better reproduces observed HNO 3.  Basic (equilibrium) model overestimates chlorine activation (MLS ClO). Reducing the denitrification and chlorine activation on aerosols can improve the comparisons somewhat. Fig 5. Ground-based column NO 2 at Lauder comparison with SLIMCAT runs with/without assimilation of HALOE CH 4, H 2 O, HCl and O 3.  SLIMCAT with data assimilation shows an increased CH 4 gradient in the subtropics.  SLIMCAT run with assimilation produces much better long-term NO 2 variations than the basic model run.  Long-lived tracer assimilation ‘corrects’ transport errors.  SLIMCAT forced by ERA-40 and Interim analyses captures observed O 3 seasonal cycle quite well.  The smaller O 3 values from ERA- Interim run are in better agreement with the observations. This work was supported by the EU SCOUT- O3 project. The ECMWF analyses were obtained via the British Atmospheric Data Centre.