Sensitivity Studies of Ozone Depletion with a 3D CTM
Wuhu Feng1, M.P. Chipperfield1, S. Dhomse1, L. Gunn1, S. Davies1,
B. Monge-Sanz1, V.L. Harvey2, C.E. Randall2, M.L. Santee3
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.
[email protected]
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 Cl2O2 (Fig.
3) . Model transport issues are discussed by running the CTM with options of assimilation of longlived traces (HALOE CH4, O3, HCl and H2O from 1991-2002) (Fig. 4, 5) and by using the new
ERA-Interim 4D-var reanalyses (1989-1998) (Fig 6).
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.
3.3 Cl2O2 Photolysis
 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 O3 loss due to different
meteorological conditions.
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 66oN geographic
latitude integrated since December 1 (sza 93o) in units of relative area  days (circles, right axis).
.
3.2 Denitrification Effect on Arctic Ozone Loss
Fig 3. Impact of different laboratory measurements
(Burkholder et al. (1990), JPL (2006), Huder and Demore
(1995) and Pope et al. (2007)) of Cl2O2 absorption cross
section on the polar ozone loss rate at 475 K for Arctic
winter 2002/03.
 Modelled O3 loss is sensitive to the
Fig 2. Comparisons of HNO3 and ClO from AURA MLS measurements and simulations using
different PSC schemes (equilibrium, DLAPSE and no sedimentation) and without chlorine activation
and N2O5+H2O reaction on liquid aerosols at 456 K and their impact on Arctic ozone loss.
 SLIMCAT with detailed DLAPSE scheme is less denitrified than
using equilibrium scheme and better reproduces observed HNO3.
 Basic (equilibrium) model overestimates chlorine activation
(MLS ClO). Reducing the denitrification and chlorine activation on
aerosols can improve the comparisons somewhat.
absorption cross sections of Cl2O2
 Applying the new cross section from
Pope et al. (2007) in the model leads to
large discrepancy and very poor
agreement with observations.
3.5 Effect of Meteorological Analyses
3.4 Effect of Chemical Data Assimilation
Fig 4. CH4 zonal
mean for July
1992 from
SLIMCAT runs
with/without
assimilation of
HALOE data.
 SLIMCAT with data assimilation
shows an increased CH4 gradient in
the subtropics.
 SLIMCAT run with assimilation
produces much better long-term NO2
variations than the basic model run.
 Long-lived tracer assimilation
‘corrects’ transport errors.
Fig 5. Ground-based column NO2 at Lauder comparison with SLIMCAT runs with/without assimilation
of HALOE CH4, H2O, HCl and O3.
Fig 6. Comparisons of ozonesonde observations at
Resolute (75N) with SLIMCAT results using ERA-40 and
ERA-Interim meteorological analyses .
 SLIMCAT forced by ERA-40 and
Interim analyses captures observed
O3 seasonal cycle quite well.
The smaller O3 values from ERAInterim run are in better agreement
with the observations.
This work was supported by the EU SCOUTO3 project. The ECMWF analyses were
obtained via the British Atmospheric Data
Centre.
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