WP3 Task2: Compilation of multi-annual time series of EP flux divergence
using ERA40l
Objective
Stratospheric ozone concentration is mainly maintained by the balance between photochemical
production in the tropics, transport to higher latitudes, stratosphere- troposphere exchange (STE),
and photochemical loss. Among these, STE and transport of ozone are mainly controlled by the
wave driven Brewer-Dobson circulation. The strength of this circulation is mainly measured in
terms of the Eliassen Palm flux (EP flux). The strong correlation between EP flux and ozone is
very useful for empirical studies of climate and its variability. A measure of the upward
propagating momentum carried by planetary scale waves through a given horizontal surface is the
average vertical component of the Eliassen Palm (EP) vector on the surface and is a quantity that
can be calculated from meteorological fields. The vertical component of the EP flux vector is
proportional to the heat flux, a quantity used by many in place of the former for a measure of
upward propagating wave energy. The divergence of the EP vector field in a given volume of the
stratosphere gives the amount of momentum that is deposited in that volume by the dissipation of
planetary scale waves. Any change in tropospheric wave activity that may result from the rise in
greenhouse gases or from natural climate variability may influence the stratospheric circulation and
hence the trace gas and ozone distribution (Randel et al., 2002, Holton et al., 1995).
Tropospheric wave activity controls the strength of polar vortex and hence regulates ozone loss by
heterogeneous chemistry in the polar region (Rosenlof, 1995). Higher wave activity mechanism via
troposphere leads to higher polar stratospheric temperature, less PSC volume, and reduced
heterogeneous ozone loss (Newman et al., 2001, Fusco and Salby, 1999).
Methodology:
ERA40 is used to study winters with higher wave activity (warm polar winters) and with low wave
activity (cold polar winter). Seasonal heat flux (integrated heat flux for winter months) shows very
good correlation with ozone distribution on interannual scale. Higher wave activity leads to
increase in ozone transport, as well as higher temperature in polar region, and in turn decreases
ozone loss due to heterogeneous chemistry. Figure 1 shows the relationship between September to
March ozone ratio in SH (March to September in NH), with seasonal heat flux averaged over 40° to
70° latitude at 100 hPa. The seasonal heat flux was determined from integrating the monthly means
between the respective months (September to March in NH and March to September in SH). In socalled warm Arctic winters like 1998/99 and 2000/2001 higher spring to fall ozone ratios have been
observed. In those winter the chlorine activation (here shown as winter averages of the daily mean
OClO vertical column observed by GOME at 90° solar zenith angle). The Antarctic winter 2002
represents an intermediate case between the typical Antarctic winters and the cold Arctic winters.
This relationship can be applied for various latitude bands. Figure 2 shows the same relationship
applied to various latitude bands and the larger time period (1979-2003) using TOMS V7 data. It
can be seen that the relationship holds quite good for high and low latitude bands, with the
exception of the SH data in the eighties in high latitudes This may be due to differences in halogen
loading in 80s compared to 90s but it is more likely due to the reduced quality of meteorological
analyses during that period.
Figure 1. Left: High correlation between winter heat flux and spring/fall ozone ratio (50°-90°).
Right: Winter integrated daily OClO mean vertical columns as a function of winter heat flux
(updated from Weber et al., 2003).
Figure 2. Correlation between winter heat flux and spring/fall ozone ratio from TOMS/SBUV
(1979-2003) for high latitude band (left, 60°-70 °) and low latitude band (10°-20°, right) .
NCEP (1948-2004), ERA40 (1957-2002), ERA15 (1979-1993) and UKMO (UK Met. Office 19922004) datasets are used to compile long term EP flux time series. Although, it has been proven that
EP flux and its divergence are useful to study the dynamical influence on the ozone field, these
quantities are highly derived and vary in magnitude dependent on datasets used. Figure 3 below
shows EP flux and its divergence from different meteorological analysis scheme on 22 nd September
2002, on where a record high heat flux was observed in the southern hemisphere. ECWMF dataset
clears shows higher EP flux divergence than NCEP and UKMO analysis, and also the peak in the
EP flux from NCEP is at higher altitude than that from ECMWF and UKMO.
Figure 3 shows EP flux (vectors) and its divergence (contours) derived from NCEP, ECMWF and
UKMO analysis schemes on 22nd September 2002, when a record high wave activity was observed
in the southern hemisphere resulting in the first major stratospheric warming event ever observed
in the SH.
Figure 4. Heat flux series from different meteorological analysis for February in NH (left) and for
September in SH (right). The heat flux has been averaged between 40°-70° at 100hPa level (areaweighted) in each hemisphere.
On the monthly scale, it has been found that all the datasets agree reasonably well during the winter
season (high wave activity period) compared to the summer season (low wave activity period). As
quality of datasets during pre-satellite era is questionably, trends calculation is done only for
satellite era period (1980-2003). Results for the northern hemisphere have been summarised in
Table 1.
Maximum decadal trend (~2 sigma level) has been found in September in the SH using both
datasets ERA40 (2.6%/decade) and NCEP (3.0%/decade) whereas there is no statistically
significant trend in monthly heat flux in NH during the winter months (above the 90% confidence
level) except for November and NCEP. Positive trends are observed in November and December,
while January to March show negative trends. This was also noted by Randel et al. (2002),
however, this trend (within 2) is not statistically significant. Averaged over the winter (Sep-Mar)
no significant trend in heat flux is observed in either hemispheres for the period 1980-2002.
Figure 5: Winter heat fluxes calculated from NCEP, ERA40 and UKMO analysis at 100 hPa,
weighted average from 40° to 70° and integrated from September and March (in SH from march to
September.
Table 1: NH trends derived for the monthly 100hPa heat flux averaged from 40°N-70°N from
ERA40 and NCEP dataset for the 1980-2002 period.
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
ERA40
Trend 1
Confidence level
2
[Km/s /y]
[%]
-0.09
0.14
47
-0.18
0.2
61
-0.12
0.12
67
0.03
0.08
26
0.07
0.04
90
0.01
0.01
37
0.02
0.01
97
-0.02
0.01
82
0.03
0.02
87
-0.04
0.04
75
0.12
0.07
89
0.19
0.14
80
NCEP
Trend
1
Confidence level
2
[Km/s /y]
[%]
-0.1
0.14
50
-0.17
0.21
57
-0.1
0.13
53
0.02
0.07
28
0.07
0.04
92
0.01
0.01
46
0.02
0.009
99
-0.02
0.01
82
0.03
0.02
89
0.009
0.04
2
0.14
0.75
93
0.19
0.13
82
Sep-March
0.02
0.02
Month
0.03
36
0.03
52
Contribution to WP5:
Long-term ozone trends:
It is well known that both satellite and ground-based data show a long-term (several decades)
downward trend in ozone in middle and high latitudes (WMO, 1999 for the latest trend analyses).
The cause of the polar decline is well established, arising from reactions of chlorine and bromine
species following activation on polar stratospheric clouds. Both chemical and dynamical processes
play a role in the long-term ozone change in middle latitudes but the precise quantification of their
roles remains controversial. There is increasing evidence of an important dynamical component,
which could be associated with long-term variability or, possibly, climate change. Attribution of the
relative roles of chemical and dynamical processes in the observed ozone trend is essential to
understand the impact of the Montreal Protocol and to predict the development of the ozone
recovery during the coming years. In this study we will investigate the relative roles that changes
in dynamical and chemical processes have on the interannual variability
Methodology:
In a first attempt a multivariate regression analysis has been performed on total ozone from TOMS
and GOME. Figure 6 shows a regression on the Mar-September total ozone difference polewards of
50°N. Regression terms were stratospheric aerosols (averaged over the winter), winter heat flux,
and a linear term. The linear term (-8.1DU/decade) is not statistically significant and may be due to
instrumental differences between EP TOMS and GOME on one side and the early TOMS record
(before 1994). The winter heat flux and stratospheric aerosols explain to large extent the
interannual variability.
Figure 6. Multivariate regression to total ozone difference between March and September
polewards of 50°N . Regression terms included are stratospheric aerosol loading, winter heat flux,
and linear term. Left: Black and blue lines are observations from TOMS V7 and GOME V3,
respectively. Orange line represents the fit and the stratospheric aerosol term is indicated by the
dashed line. Right: Linear term with (solid) and without heat flux term (solid) added are shown as
orange lines, while the black curve shows observations with stratospheric aerosol term removed. In
this fit the late 90s data data from GOME were only used. Fit results with GOME data replaced by
TOMS also results in a statistically insignificant linear trend.
Deliverables
EP flux diagnostics (heat flux, momentum flux, EP flux vector, and EP flux divergence) on
nominal pressure levels from ERA40, NCEP, and UKMO are now available.
Outlook
1. The differences between NCEP and ERA40 datasets will be studied in detail and the
uncertainties in the EP flux calculation will be documented.
2. Continuation of multivariate regression on total ozone data using dynamical proxies
3. GOME vertical profile data (Müller et al. 2003) will be used to study the effect of EP flux
and its divergence on the vertical ozone distribution.
Publications
B.-M. Sinnhuber, M. Weber, A. Amankwah, and J.P. Burrows, Total ozone during the unusual
Antarctic winter of 2002, Geophys. Res. Lett. 30(11), 1580, doi:10.1029/2002GL016798,
2003
M.Weber, S. Dhomse, F. Wittrock, A. Richter, B.-M. Sinnhuber, and J.P. Burrows, Dynamical
Control of NH and SH Winter/Spring Total Ozone from GOME Observations in 1995-2002,
Geophys. Res. Lett., 30(11), 1583, doi:10.1029/2002GL016799, 2003
References
A.C. Fusco, and M.L. Salby, Interannual variations of total ozone and their relationship to
variations of wave activity , J. Clim. 12, 1619-1629, 1999.
J.R. Holton, P. H. Haynes, M. E. McIntyre, A. R. Douglass, R. B. Rood and L. Pfister, 1995:
Stratosphere-troposphere exchange. Reviews of Geophysics, 33, 403-439
M.D. Müller, A.K. Kaifel, M. Weber, S. Tellmann, J.P. Burrows, D. Loyola, Ozone profile
retrieval from GOME data using a neural network approach (NNORSY), J. Geophys. Res.,
108, 4497, doi:10.1029/2002JD002784, 2003.
P.A. Newmann, E.R. Nash and J. E. Rosenfield, What controls the temperature of Artic
stratosphere during spring, J. Geophys. Res. 106, 19,999-20,010, 2001
W. J. Randel, F. Wu, and R. Stolarski, Changes in column ozone correlated with the stratospheric
EP flux, J. Meteor.. Soc. Jpn, 80, 849-862, 2002.
K. H. Rosenlof, Seasonal cycle of residual mean meridional circulation in the stratosphere, J.
Geophys. Res. 100, 5173-5191, 1995