Download presentation
Presentation is loading. Please wait.
Published byAlan Atkinson Modified over 9 years ago
1
Dynamical Control on Decadal Ozone Change S. Dhomse 1, M. Weber 1, I. Wohltmann 2, M. Rex 2, V. Eyring 3, M. Dameris 3, and J.P. Burrows 1 (1)Institute of Environmental Physics, University Bremen, Bremen (2)Alfred-Wegner Institute for Polar and Marine Research, Potsdam (3)Institute of Atmospheric Physics, DLR Oberpfaffenhofen sandip@iup.physik.uni-bremen.de
2
Overview Data sources: TOZ :- GOME V3, TOMS V7, TOMS-SBUV merged dataset Met Analyses:- ERA40, UKMO, NCEP GCC:- ECHAM/DLR E39/C Topics: Planetary wave driving and ozone (introduction) Heat flux and spring/fall ozone ratio – Interhemispheric linkage ERA40 – Problems in SH(!) and NH(?) Multivariate regression analysis (preliminary results) Summary and Conclusion
3
Annual cycle in total ozone
4
Interannual variability Winter/spring ozone Photochem. summer decay
5
Annual cycle of GOME total ozone in NH and SH NH SH Winter gain through transport in ozone outweighs chemical ozone loss in NH In SH, chemical ozone loss is larger than winter transport, except 2002.
6
Heat flux starts increasing in fall NH heat flux is generally higher than in SH Annual cycle of heat flux in NH and SH 3 day mean time series
7
Tropospheric forcing and spring/fall ozone ratio GOME ozone ratio 50°-90° Sep over Mar (SH) Mar over Sep (NH) Winter heat flux 43°-70° 100 mbar Sep-Mar (Mar-Sep) integrated and averaged SH anomaly 2002 Cold Arctic winter/spring seasons Update from Weber et al. 2003 For SH :-
8
Update from weber et al Tropospheric forcing and chlorine activation OClO BrO+ClO –> OClO + O Measured in twilight inside the polar vortex Maximum vertical column at 90° solar zenith angle integrated over the winter Below 92°SZA OClO is a measure of chlorine activation UKMO High chlorine activation persisted during SH anomaly 2002
9
Correlation coefficients for selected latitude bands 70-6050-4030-20 Jan/Aug0.97--0.91 Feb/Aug0.980.22-0.87 Mar/Aug0.990.41-0.83 Apr/Aug0.980.09-0.7 May/Aug0.960.33-0.66 Jan/Sep0.98-0.18-0.93 Feb/Sep0.980.08-0.91 Mar/Sep0.990.25-0.89 Apr/Sep0.98-0.15-0.83 Oct/Sep0.960.1-0.79 Jan/Oct0.96-0.1-0.94 Feb/Oct0.970.19-0.92 Mar/Oct0.980.47-0.9 Apr/Oct0.97--0.81 May/Oct0.950.31-0.77 Sig. Level > 99% Sig. Level < 95% Sig. Level > 95% Nearly identical results using TOMS,TOMS/SBUV merged dataset
10
Ozone winter gain and summer transition ERA40 vs UKMO Interannual variability of winter heat flux correlates well with winter ozone gain Winter heat flux higher in ERA40 (too much transport) E39/C vs GOME lower interannual variability in winter (NH) weaker wave driving in SH (cold bias?) Photochemical decay about 3m (>50°N) and 2.5 m (>62°N) Good agreement between GOME and E39/C
11
ERA40 in Early 80s vs. late 90s Correlation with ERA40 in early 80s and SH very poor What is changing ? Dynamics or chemistry? ERA40
12
1957 / 09 – 1957 / 11 1957 / 12 – 1972 / 04 1972 / 05 – 1972 / 12 1973 / 01 – 1974 / 04 1974 / 05 – 1974 / 06 1974 / 07 – 1985 / 03 1985 / 04 – 1986 / 03 1986 / 04 – 1988 / 10 1988 / 11 – 1988 / 12 1989 / 01 – 1994 / 12 1995 / 01 – 1995 / 04 1995 / 05 – 2002 / 08 ERA40 in various streams
13
Long term trend 1979-2003 Difference March-September 50°N-90°N Linear regression terms: const, linear, aerosol & heat flux
14
Long term trend 1979-2003 Difference March-September 50°N-90°N Linear regression terms: const, linear, aerosol & heat flux Linear: r=0.88, EESC: r=0.89, no linear term: r=0.83 “Linear“ term not statistically significant (3 ): instrumental drift/bias /met analysis quality 80s vs 90s
15
Summary & Conclusion Compact relationship between winter ozone gain and seasonal heat flux for both hemispheres (late nineties/early 2000) Winter chlorine activation shows good correlation with wave driving Summer ozone levels are tied to wave activity of the previous winter (see also Fioletov and Shepard 2003) Met. Analyses good measure of interannual variability differences in strength of high latitude ozone transport varies (ERA40 higher than NCEP/UKMO) Correlations between wave driving & ozone particularly well in 90s ERA40 seems inconsistant in SH in presatellite era E39/C (and possibly other CCMs) less interannual variability in winter No summer minimum in SH
16
Multivariate regression of spring-fall difference at high latitudes Linear term is not significent Largest contribution from aerosol and heat flux Summary & Conclusion
17
Candidoz: 3 rd Year WP 3: Residual circulation and Tropospheric Coupling: Systematic investigation of interhemispheric linkage (latitude bands and diffrent periods) Cumulative effect over winter is not necessarily linear Multivariate regression using different latitude bands with CANDIDOZ proxies Use of GOME neural net O3 profile data (1995-2001) TEM transport diagnostics (in collabaoration with AWI) EP flux correlation with the zonal mean vertical field EOF analysis of latitude-altitude field
18
Proxies for statistical trend analysis/O3 changes (1) Longer term variability Residual circulation EP flux from preceding winter (most important) Pol ozone loss V_psc X EESC (take into account H2O vapour trend, abt. 10%/decade, and bromine, latter is already included) Dilution proxy (RDF advection of O3 depletion profile, see Knudsen, somewhat dificult to obtain) Mid-stratosphere homogeneous ozone loss EESC Aerosol Stratospheric extinction (multiplying with EESC) QBO 2 QBO indices differing by a phase shift of pi/2 Solar cycle F10.7 cm flux, after 1978 MgII index, sun spot number for older data
19
Proxies for statistical trend analysis/O3 changes (2) Short term variability (days) Vertical lifting (TH change)/thickness of O3 layer between TH and photochemical equilibrium (10hPa) Tropopause pressure (NCEP)/200 hPa Geopotential Short-term advection (TH change) Equivalent latitude (bad in summer)/ PV at various altitude (PV trend problem?)
21
UB Action Item Inform CANDIDOZ when WFDOAS data are ready Discuss with Greg Bodeker about using WFDOAS in NIWA dataset Make MgII index available to Candidoz
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.