Trend analyses, assuming a linear trend which started at 1970, were performed from total ozone measurements from Arosa (Switzerland, 1926-1991). Decreases in monthly mean values were statistically significant for October through April showing decreases of about 2.0-4 percent per decade. For the period 1947-91, total ozone trends were further investigated using a multiple regression model. Temperature of a mountain peak in Switzerland (Mt. Santis), the F10.7 solar flux series, the QBO series (quasi biennial oscillation), and the southern oscillation index (SOI) were included as explanatory variables. Trends in the monthly mean values were statistically significant for December through April. The same multiple regression model was applied to investigate the ozone trends at various altitudes using the ozone balloon soundings from Payerne (1967-1989) and the Umkehr measurements from Arosa (1947-1989). The results show four different vertical trend regimes: On a relative scale changes were largest in the troposphere (increase of about 10 percent per decade). On an absolute scale the largest trends were obtained in the lower stratosphere (decrease of approximately 6 per decade at an altitude of about 18 to 22 km). No significant trends were observed at approximately 30 km, whereas stratospheric ozone decreased in the upper stratosphere

Bader, Juerg

Gelpke, Verena

Staehelin, Johannes

English

NASA Technical Reports Server

N95-10634
35$3
TREND
ANALYSIS OF THE LONG-TERM SWISS OZONE MEASUREMENTS
Johannes Staehelin and Juerg Bader
Atmospheric Physics, ETH-Hoenggerberg
CH-8093 ZUrich, Switzerland
Verena Gelpke
Statistics, ETH-Ziirich,
CH-8092 Ziirich, Switzerland
ABSTRACT
Trend analyses, assuming a linear trend which started
at 1970, were performed from total ozone measurements from
Arosa (Switzerland, 1926-1991). Decreases in monthly mean
values were statistically significant for October through April
showing decreases of about 2.0-4% per decade. For the
period 1947-91, total ozone trends were further investigated
using a multiple regression model. Temperature of a mountain
peak in Switzerland (Mt. S_intis), the F10.7 solar flux series,
the QBO series (Quasi Biennial Oscillation) and the southern
oscillation index (SO1) were included as explanatory variables.
Trends in the monthly mean values were statistically
significant for December through April.
The same multiple regression model was applied to
investigate the ozone trends at various altitudes using the
ozone balloon soundings from Payerne (1967-1989) and the
Umkehr measurements from Arosa (1947-1989). The results
show four different vertical trend regimes: On a relative scale
changes were largest in the troposphere (increase of about
10% per decade). On an absolute scale the largest trends were
obtained in the lower stratosphere (decrease of approximately
6% per decade at an altitude of about 18 to 22 kin). No
significant trends were observed at approximately 30 km,
whereas stratospheric ozone decreased in the upper
stratosphere.
1. INTRODUCYION
A multiple regression model, similar to a previously
used model by Bojkov et al., 1990 and the OTP, 1989, was
applied to calculate ozone trends from the long term Swiss
ozone measurements. They include the world's longest total
ozone series (Arosa), ozone balloon soundings (Payerne) and
one of the most extensive data sets of Umkehr measurements
(Arosa).
2. MEASUREMENTS
The total ozone series from Arosa (monthly mean
values) adjusted to the Dobson world standard instrument
(Hoegger et al., 1992) was used.
The Umkehr measurements (wavelength pair C) have
been processed using the program of Mateer (Mateer, 1965)
and the aerosol correction of J. DeLuisi (pers. commun.).
The ozone balloon sondes (Brewer mast sondes) were
launched from Thalwil (near Ziirich) during the first 2 years
(1967-1969) and thereafter from Payerne, which is about 200
km to the west of Arosa. Three ascents per week were planned
from the beginning, the number of the successful ascents and
their data quality is described in Staehelin and Schmid, 1991.
3. TREND ANALYSES OF TOTAL OZONE
We first present the results of a trend model which
only includes total ozone (monthly means) using a linear trend
which started at 1970.
i=12 i=12
Yt = 12 + Z 12ilit + Z [3ilitRt + Nt (1)
i=l i=l
Yt : Ozone monthly mean at the month t
It: overall mean of ozone
12i: deviation of ozone of the i-th month of the year
from the overall mean; Zi12i = 0
lit: 1 if month t corresponds to i-th month of the year,
otherwise 0
13i: trend for the i-th month of the year
Rt: linear ramp function: Rt =(t-to)/12 if t>to (to: Dec.
1969) and 0 = if t< to
Summation goes over i=l to 12.
The month to month correlation in ozone, which is present
after the elimination of seasonal and other effects, was
modelled by an autoregressive series of second order (AR(2)):
Nt = ¢lNt-I + ¢2Nt-2 + ct (2)
We first included in eq.(2) the values back m the sixth
month, but the results showed that an AR(2)-model is
appropriate to treat the data. We used maximum likelihood
fitting of model (1) assuming Gaussian errors tt. The
variances for each month were estimated, then model (1) was
calculated again using weighted least squares. This procedure
did not yield new results and was therefore not applied in the
further calculations.
Fig. la shows the seasonal variation of total ozone at
Arosa. The total ozone decrease is much stronger during
winter time (see Fig. lb). The results are consistent with
results from more sophisticated models in which shorter time
periods have been used (OTP, 1990, Bojkov et al., 1990,
Stolarski et al., 1992).
186
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Figure 1:
4. INFLUENCE OF EXPLANATORY VARIABLES
The following multiple regression model is an
extension of the model described in Bojkov et al., 1990. We
added the SO1 (Southern Oscillation Index, used e.g. by
Zerefos et al., 1992) and the temperature from a mountain
peak in Switzerland representing the temperature in the free
troposphere as potential explanatory variables. Because some
variables were not available before 1957 the model was
applied for the later measurements.
i=12 i=12
Yt = ¢t + X_ilit + X[_iIitRt+ X'yklog(F10.7)t-k
i= 1 i= 1 ieK 1
+ _kTt-k + XrlkQBOt-k + _kSOIt-k + Nt (3)
ieK 2 icK 3 icK 4
Where:
Summation: i: 1...12 and k: kekn
Total ozone series of Arosa. Labels of the abscissa: number of the calendar month. (a): Deviation of the monthly mean
values (in D.U.) from the long-term annual mean value (332 D.U). The dashed lines include the 95% confidence
intervals of the monthly deviations. (b)-(d): Trends in the monthly mean values (in % per decade). The dashed lines
include the 95% confidence intervals for the calculated trends which were assumed to start in Jan. 1970. (b): Model of
eq. (1), ozone series 1926-91• (c): Model of eq. (1), ozone series 1947-91. (d): Model of eq. (3), ozone series 1947-
91, including temperature of Mt. S_ntis and the F10.7 solar flux as explanatory variables.
QBOt-k : QBO time series with time lag k and
associated coefficient "qk
t_: Intercept
F10.Tt-k: solar 10.7-cm flux series with time lag k and
associated coefficient 7k
Tt_ k : deseasonalized temperature at Mt. S_intis with
time lag k and associated coefficient 8k
SOIt-k: Southern Oscillation Index series with time lag
k and associated coefficients _k
Nt: noise series, AR(2)
Ki (i = 1.... 4): Sets of time lags at which the different
variables influence total ozone at Arosa
We tried to evaluate the appropriate time lags using the lagged
regression model of Shumway (Shumway, 1988).
Temperature influences ozone strongly with a time lag of zero.
The calculations of the other variables did not indicate any
clearly evident pattern of time lags. Some sensitivity runs,
including different time lags of the explanatory variables,
indicated that the QBO- and ENSO series did not significantly
influence the results of.the trend calculations. However, the
F10.7 significandy influences total ozone at Arosa (time lag of
0 month). We therefore included in the calculations of total
ozone trends temperature of Mt. Siintis and F10.7. The
calculated trends of the period 1947-91 are stronger in May
and June using model of eq (3) than model of eq (1),
otherwise the results of the two models are very similar (see
Fig. lc and ld).
187
Dtitschand Staehelin,1989, have shown that the
negative correlation between total ozone at Arosa and the
temperature record of Mt. S_intis can be interpreted by the
transport of ozone rich air masses from the polar region to
midlatitudes by polar cyclones, i.e. regional weather
influences. Diitsch et al., 1992, have used a similar model
inluding the total ozone from 1926 to 1989, the temperature of
Mt. Slintis, and the solar cycle which was described by the
sunspot number. In this study, the influence of the solar cycle
on total ozone was statistically significant (at 5%) only if the
temperature of Mt. Santis was included in the analysis (1.26%
or 4.4D from minimum to maximum of the solar cycle, in
good agreement with previous studies of the worldwide
Dobson network (WMO, 1989)).
5. RESULTS OF THE TREND ANALYSES
CONSIDERING THE VERTICAL DISTRIBUTION OF
OZONE
A similar type of multiple regression model (eq. (3))
was used to elucidate the vertical distribution of the trends. In
a pre run the autocorrelations were calculated. Based on the
results of the calculations of total ozone (see 4) we included
the time lags of zero in this model. A strong dependency
between the temperature at Mt. S/intis and ozone was found
for most altitudes (see Fig. 2). The strongest signal of QBO
was found for an altitude of approximately 22.5 km, which is
about the altitude of the ozone maximum layer, where ozone
concentration is most strongly influenced by the transport
from the tropics. The influence of SOl on ozone concentration
is generally weak, but noticeable at the altitude of about 19km.
Similarly, the influence of the solar cycle is weak for most
altitudes and only weakly statistically significant at an altitude
of about 30km, which already has been described in Diitsch et
al., 1992.
Four different regimes of trends can be distinguished
in the vertical (see Fig. 3a-3d):
- On a relative scale, changes are strongest in the troposphere
showing strongly increasing ozone concentrations especially
during the eighties (Staehelin and Schmid, 1991). This is most
probably attributable to the tropospheric air pollution by
nitrogen oxides, hydrocarbons and carbon monoxide.
- On an absolute scale trends are strongest in the lower
stratosphere. In this region, ozone decrease was faster in
winter (about 10% per decade), than in summer and in autumn
(approximately 5% per decade). The altitude where the ozone
decrease was strongest was at approximatel)_ 16 km in winter
and at approximately 20 km during summer and autumn.
- No trends were observed at an altitude region of 30 kin.
- The Umkehr measurements indicate decreasing trends of
ozone in the upper stratosphere.
The trends in the upper stratosphere can be explained
by the gas phase ozone destruction. However, at the altitude
of the strongest stratospheric trends heterogeneous processes
destroying stratospheric ozone are probably important.
ACKNOWLEDGEMENTS
The authors acknowledge the advise of H. Kiinsch
(Sem. Statist., ETH-Z) and are grateful to W. Stahel and R.
Dixon for reviewing the manuscript (Sem. Statist., ETH-Z).
The authors further acknowledge the careful performance of
the ozone measurements by the coworkers of the Swiss
Meteorological Institute (SMI). We are grateful to C. Zerefos
and L. Bishop for providing us the data of ENSO, QBO and
F10.7.
10_ 7
...............................
............................. i
..........> i
100
o _i
_uo _:.- ...........
/_,O ".FI0,7 .................. Temp
IOO0 Lq'B° __ ..... 3 ........ 4....
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30
25
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I0
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Figure 2: Significance, given as error probabilities (p-
values), of the dependence of the ozone
concentration on the used explanatory variables
as function of the altitude. The p-value in this
case is the probability that the standardized
regression coefficient is smaller than the
estimated value.
REFERENCES
Bojkov, R., Bishop, L., Hill, W.J., Reinsel, G.C., and Tiao,
G.C. (1990): A statistical trend analysis of revised
Dobson total ozone data over the Northern Hemisphere,
J. Geophys. Res., 95, 9785-9807.
Diitsch, H.U. and Staehelin, J. (1989): Discussion of the 60
year total ozone record at Arosa based on measurements
of the vertical distribution and a meteorological
parameter, Planet. Space Sci., 37, 1587-1599.
Dtitsch, H.U., Bader J. and Staehelin, J. (1992): Separation
of solar effects on ozone from anthropogenically
produced trends, J. Geomagn. Geoelectr., in press.
Hoegger, B., Viatte, Levrat, G., Bader, J., Ribordy, P.,
Schill, H. and Staehelin, J. (1992): Quality control
concept and recent developments of the Light Climatic
Observatory at Arosa - Ozone measuring station of the
Swiss Meteorological Institute (LKO), this conference.
Mateer, C. (1965): On the information content of Umkehr
observations, J. Atmos. Sci., 22, 370-381.
OTP (1990): Report of the International Ozone Trends Pannel:
1988, World Meteorological Organization, Global
Research and Monitoring Project Report, No. 18, World
Meteorological Organization, Geneva, Switzerland.
Shumway, R.H. (1988): Applied statistical time series
analysis, Prentice-Hall International Editions, p.203-
213.
Staehelin, J. and Schmid, W. (1991): Trend analysis of
tropospheric ozone concentrations utilizing the 20-year
data set of ozone balloon soundings over Payerne
(Switzerland), Atrn. Env., 25A, 1739-1749.
Stolarski, R., Bojjkov, R., Bishop, L., Zerefos, C.,
Staehelin, J., and Zawdony, J. (1992): Measuered
trends in stratospheric ozone, Science, 256, 342-349.
WMO (1989): Scientific assessment of stratospheric ozone,
VoI.I, 165, 194-234.
Zerefos, C.S., Bais, A.F. and Ziomas, I.C. and Bojkov,
R.D (1992)t On the relative importance of QBO and
ENSO in the revised Dobson total ozone records. J.
geophys. Res., in press.
188
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Figure 3: Trends for different altitudes deduced from the ozone balloon soundings from
Payerne (1967-89) and the Umkehr-measurements from Arosa (1956-89),
calculated using model of eq. (3). Trends are assumed to start on Jan., 1970. The
dashed lines describe o_+_2s(s is the standard deviation of the trends). Thus points
outside the dashed line indicate trends, which are statistically significant according
the t-test for regression coefficients approximately at the 5% level, a: Year around
trends; b: Trends for winter (Dec. to March); c: Trends for summer (May to Aug.);
d: Trends for fall (Sept. to Nov.).
189


Trend analysis of the long-term Swiss ozone measurements

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