possibilities to detect trends in spectral uv irradiance

Theor. Appl. Climatol. 81, 33–44 (2005)DOI 10.1007/s00704-004-0109-9

1 Institute of Meteorology and Climatology, University of Hannover, Germany2 Finnish Meteorological Institute, Kuopio, Finland3 Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Greece

Possibilities to detect trends in spectral UV irradiance

M. Glandorf1, A. Arola2, A. Bais3, and G. Seckmeyer1

With 8 Figures

Received February 11, 2004; accepted October 6, 2004Published online December 22, 2004 # Springer-Verlag 2004

Summary

It is investigated how long-term UV trends can be assessedby analysing the longest time series of measured spectralUV irradiance in Europe, which have been started in theearly 1990s in Thessaloniki, Greece and Sodankyl€aa,Finland. It can be concluded that both time series do notyet show an unambiguous yearly trend in UV irradiance.The regression lines show no uniform behaviour and varyirregularly in strength and from one solar zenith angle to thenext if all sky conditions are analysed. It is emphasised thatthese findings do not disagree with previous studies, thatsignificant changes in UV irradiance have been observedover Europe especially in spring.

Our study introduces a new method to estimate therequired time series length for trend detection using themeasured time series in combination with model calcula-tions. At Sodankyl€aa, a reduction of the total ozone columnof �5.7% per decade has been observed from 1979 to 1998.A positive UV trend due to such conditions may be detectedafter 12 years at the earliest. For Thessalonki, a decrease intotal ozone of �4.5% per decade has been observed. Acorresponding increase of UV irradiance should be detect-able after 15 years. It should be noted that a constant ozonetrend over the whole period had to be assumed for thisanalysis.

Since 1990 there has been a considerable variability oftotal ozone, but no steady decrease could be observed. Con-sequently, no general UV increase could be expected due toozone changes. Even if there was a constant ozone trend overthat period it is shown that even the longest European timeseries of UV irradiance are still too short to show distincttrends. However, this does not imply that no changes haveoccurred, it only shows that the large natural variability of

UV irradiance has so far hindered the identification of unam-biguous trends. The only way to find significant and consis-tent UV trends is the continuation of high-quality long-termmeasurements of spectral UV irradiance.

1. Introduction

The main objectives for taking long-term system-atic measurements of surface ultraviolet (UV) ra-diation are to establish a global climatology of UV,both average and extreme values, and to quantifyany long-term changes that may have occurred as aresult of changes in stratospheric ozone or othervariables (Kerr and Seckmeyer et al., 2003). SolarUV radiation is known to have adverse effects onthe biosphere including terrestrial and aquatic eco-systems as well as public health. Especially forhuman beings, exposure to UV radiation from theSun is associated with skin cancer, acceleratedageing of the skin, cataract, or other eye diseases(Seckmeyer et al., 2001). During the past decades adepletion of stratospheric ozone has been detectedwhich brought up concern about increased surfaceUV radiation levels. Increases in UV radiationassociated with ozone decline have been observedby spectral measurements at a number of siteslocated in Europe (e.g. Zerefos, 2002). In recentyears the possible recovery of the stratospheric

ozone layer has been discussed as well (Reinselet al., 2002). If these scenarios, that are complicatedby complex interactions with climate change, arecorrect, a significant decrease in UV irradiance canbe expected.

A number of publications focus on the searchfor the evidence of long-term changes in UV ir-radiance. Analyses of changes in UV doses havebeen performed, for example, by Herman et al.(1996), Seckmeyer et al. (1997), Weatherheadet al. (1997), Udelhofen et al. (1999), Lindforset al. (2003), Trepte and Winkler (2004), andEngelsen et al. (2004). Spectrally resolved rou-tine measurements of solar UV irradiance inEurope only started in the 1990s. Recent studieson possible long-term changes in spectral UVirradiance hence are hampered by the limitednumber of years of available data. Zerefos (2002),Zerefos (1997), Arola et al. (2003), and Lakkalaet al. (2003) for example analysed time seriesof spectral UV irradiance measurements. Zerefos(2002) detected a UV increase of 2% per year at305 nm for cloudless skies, but he concludes thatfew years of the time series are not enough forreliable conclusions on long-term changes. Thesame conclusion is drawn by Arola et al. (2003)who analysed the time series of Thessaloniki andSodankyl€aa focusing on the factors influencingshort- and long-term changes in spectral UV irra-diance. Lakkala et al. (2003) evaluated changesin Sodankyl€aa spectral UV data: significant changesin summer monthly mean irradiances could notbe detected. Previous studies using spectral datahave been limited to particular wavelengths andsolar zenith angles (SZAs). In this study we pres-ent an analysis of a wide range of SZAs andwavelengths.

In addition to the trend analysis of the mea-sured UV time series we investigate the requiredlength of a time series of UV irradiance. Prior tothis study the possibilities of the detection oftrends have been investigated by Weatherheadet al. (1998) who provide a general statisticalstudy on the detection of trends. The resultingtables give an estimation of the number of yearsto detect a trend (of any geophysical parameter)in dependency on the autocorrelation of the noiseof the time series and the standard deviation ofthe noise. Lubin and Jensen (1995) calculated theelapsed time after the onset of ozone depletionbefore the dose rate for skin cancer has increased

by a certain factor. This deduced time period de-pends on the standard deviation of the cloud-induced interannual variability, and the resultsare provided as global maps. Our study intro-duces a new method for an estimation on therequired time series length for trend detectionusing the measured time series in combinationwith model calculations.

2. Data and methods

Spectral UVirradiance from Thessaloniki, Greece,(40.5� N, 22.9� E) and Sodankyl€aa, Finland,(67.4� N, 26.6� E) has been analysed with theaim to search for trends in UV irradiance. Thesestations were chosen because they comprise thelongest time series of spectral irradiance withinEurope, about 12–14 years each, and they repre-sent different climate zones within Europe. Bothtime series were recorded by Brewer single mono-chromator spectroradiometers (Bais et al., 1996;Lakkala, 2001).

2.1 Instrumentation

For the global UV measurements both instru-ments contain a Teflon diffusor with a diameterof about 35 mm, protected by a quartz dome. TheUV scans are recorded in a wavelength range of290–330 nm in Thessaloniki and 290–325 nm inSodankyl€aa, both in steps of 0.5 nm.

Single monochromators have the disadvantageof stray light (Seckmeyer et al., 2001) especially atthe short wavelength end where the UV changesdue to ozone changes are most pronounced. How-ever, for this study priority was given to the lengthof the time series. Stray light becomes importantin the wavelength region below 300 nm (Bais et al.,1996), thus it was decided to focus on the wave-length range between 300 and 315 nm. The upperlimit was chosen according to the decreasing in-fluence of ozone on the UV radiation towards theUVA range.

At both stations the instrument is calibratedmonthly while the stability of the instrument’sspectral responsitivity is controlled once per week(Arola et al., 2003). Moreover, for the purpose ofquality assurance both Brewer instruments havetaken part in several intercomparisons for UVspectroradiometers (Kjeldstad, 1997; Bais et al.,1996).

34 M. Glandorf et al.

2.2 Data extraction

The spectral data have been submitted to theEuropean UV Database (EUVDB; FMI, 2003;Seckmeyer, 2000). This relational database al-lowed us to extract all data with SZAs between30� and 65� (Thessaloniki) and between 44� and65� (Sodankyl€aa) and to separate it into subsetswith constant SZA as a function of the wave-length. A limited band of only 1� width wasselected. A SZA of e.g. ’ ¼ 62� is defined tocomprise all SZAs with 61.5� � ’ < 62:5�. Inaddition to the data set that comprises all sky con-ditions a cloudless sky data set has been ex-tracted from the EUVDB. For such cases theEUVDB provides the option to search for spectrawith specified atmospheric conditions. The selec-tion of cloudless sky data relies on comparisonsof measured UV spectra with modelled UV spec-tra for the various atmospheric scenarios.

The dependence of the SZA on UV irradianceis very strong. Therefore the influence of the SZAmust be removed for the analysis of the data. Evenwith a relatively small variation of the SZA, erro-

neous results may be obtained (Arola et al., 2003).In order to remove this effect all measurementsare normalised to specified SZA values by meansof model calculation. Each irradiance is multi-plied by a factor that represents the difference inUV irradiance caused by the difference betweenthe SZA during the measurement and the speci-fied SZA value. Additionally all measurements arealso normalised for a constant Sun-Earth-distance.

When studying irradiances at single wave-lengths wavelength stability is crucial (Arolaet al., 2003). Thus, all spectra were correctedfor possible wavelength shifts using the SHIC-rivm program developed by Slaper (2002).The remaining uncertainty due to wavelengthalignment of up to 0.02 nm is negligible.

2.3 Data analysis

Regression lines were fitted to all time series ofspectral UV irradiance; an example for 306 nm isgiven in Fig. 1. With an analysis of the residualsthe assumption of a linear trend was justified.

Fig. 1. Spectral irradiances at different SZAs at 306 nm from Thessaloniki. Each data point represents one measurement atthe given combination of wavelength and SZA. The solid line represents the regression line. Strength and sign of the changevary. Please note that the range of the y-axis varies due to the large dependence of UV irradiance on SZA

Possibilities to detect trends in spectral UV irradiance 35

For the interpretation of detected gradients it isessential to have information about its statisticalsignificance. The test after Mann (1945) is anappropriate method to estimate the significancewithout requiring the data being normally distrib-uted. It assesses a relative increase or decrease inthe time series but gives no detailed informationabout the temporal behaviour of this change. Ithas to be noted that the resulting significancelevel (¼ error probability) refers to the existenceof a positive or negative gradient and does notconfirm the magnitude of the calculated increaseor decrease rate.

For the estimation of the required number ofyears we utilise the original, 12–14 year long timeseries and their variability. It can be suspectedthat this time series adequately reflects the natu-ral variability of UV irradiance. The initial timeseries is detrended and extended. Afterwards an

artificial trend is superimposed on the data whichrepresents a UV increase due to a given ozonetrend scenario. The extended time series is thenanalysed by a linear regression. We considereda time series to be long enough if the calculatedUV upward gradient caused by the given ozonedecrease is significant at the 1% level.

The following list gives an overview of thesingle steps of this method:

1. A possible linear trend from the original timeseries is removed.

2. An artificial trend, which corresponds to anincrease in UV irradiance due to a realisticdecline in total ozone column, is superim-posed on the data.

3. A linear regression analysis is carried out.4. The significance of the calculated gradient is

determined.

Fig. 2. The process of extending the time series.Top: the original detrended time series (Thessaloniki,304 nm, 63� SZA). Middle: extension of the timeseries from 13 years to 52 years by appending theinitial data. Bottom: the extended data set after themultiplication with factors representing an increasein UV irradiance due to a �4.5% decrease in totalozone


5. Criterion: A time series is considered longenough if the calculated upward gradient ofthe regression line has a significance level of�1%:

a) Significance level �1% ! time series islong enough.

b) Significance level >1% ! time series hasto be extended: the original sequence isattached and the process continues withstep 2 again.

The superposition of the artificial trend is doneby multiplication of the spectral irradiances withfactors that represent the increase of UV irradi-ance due to a certain ozone decrease for clearskies. These factors have been determinedthrough simulations with the radiative transfermodel UVspec (Kylling and Mayer, 2002).

The Thessaloniki ozone trend rate is an averagedecrease for the years 1990–1998 (Zerefos, 2002).Information on the ozone trend for Sodankyl€aa(Arctic region, 65� N) was taken from Bojkovet al. (1998). The corresponding period is fromJanuary 1979 to December 1997. To gain moreinformation about the performance, additionalmodel runs with an imaginary ozone decrease of�1.0% per decade were carried out. The completeyear analyses use the complete data set whilethe seasonal analyses comprise only data of therelevant months. A possible winter scenario for

Sodankyl€aa is not considered as the UV irradiancemeasurements in winter are too sparse.

Figure 2 shows the process of time seriesextension from the original (uppermost paneldiagram) to the extended time series with theintroduced ozone trend (diagram at the bottom).

3. Results and discussion

Figure 1 provides an overview of spectral irra-diances measured at Thessaloniki for the arbi-trarily chosen wavelength 306 nm. It can be seenthat magnitude and sign of the regression linevary for different SZAs. While there is a slightdecrease in UV irradiance at SZAs of 30�, 35�,40�, and 45�, slight increases at 50�, 55�, 63�,and 65� and a strong increase at 60� SZA canbe observed. With regard to the variation of theregression lines this selection is representativefor other combinations.

Figure 3 shows calculated changes of irradianceper decade for Thessaloniki. Each single datapoint in this diagram represents the calculatedin- or decrease of UV irradiance of a particularcombination of SZA and wavelength. These cal-culated UV changes per decade range from �20%per decade up to almost 80% per decade. For themaximum data point the data set is added in anextra display. Lines indicating SZAs between 30�

and 43� are coloured light grey, SZAs between

Fig. 3. Change of irradiance perdecade in percent as a function ofwavelength for Thessaloniki. Dif-ferent symbols and linestyles indi-cate different SZAs (see legend).The top symbol represents SZA 54�


44� and 54� are marked grey, and between 55�

and 65� black lines are used. Looking only atFig. 1 it could have been concluded that low SZAsare associated with UV decreases while increasesoccur at higher zenith angles. As Fig. 3 shows,this guess cannot be approved: The grey and lightgrey changes which denote middle and low SZAsare both negative and positive. Moreover, some ofthe black graphs which represent high SZAs alsocan be found below zero. The distribution of thedata points representing the SZAs at one wave-length is not found to be systematic. If therewas a trend it would have been expected to beindependent of SZA and not showing a variationfrom one SZA to the next.

For Sodankyl€aa the calculated changes of UVirradiance are shown in Fig. 4. The legend fromFig. 3 applies to this figure, too, and again asystematic dependence on SZA is missing.

In both Figs. 3 and 4 the majority of datapoints has a positive sign. The variability of spec-tral irradiance at both stations increases towardslower wavelengths (e.g. Fig. 3) which is due tothe effect of ozone: Different SZAs are linkedwith different paths of radiation through theatmosphere and hence different ozone absorp-tion. Additionally it can be seen that the averageof all data points at any wavelength has a positivesign at both stations.

The same analyses have been repeated withcloudless sky data from both stations. As ex-pected the variability of the changes is reduced

compared to all sky data: the Thessaloniki irra-diance changes range from �20% to more than50% at 300 nm and from about 0% to 15% at315 nm. At Sodankyl€aa the UV changes rangefrom about �10% to 35% at 300 nm and from�5% to 5% at 315 nm. An average of all datapoints at one wavelength is around zero at300 nm, it increases continuously and exceeds5% at 315 nm for Thessaloniki. The Sodankyl€aadata show a different distribution: The average isnearly zero for the complete wavelength range.

All calculated gradients were tested for signif-icance, the results are displayed in Fig. 5. Themethod for determining the significance onlydelivers information about a relative increase ordecrease in the time series. For each detectedchange in Figs. 3 and 4 with an associated lowerror probability the corresponding bar in the his-togram is enhanced by one in positive direction ifthere is an increase or in negative direction ifthere is a decrease in the regression line. Onlythose changes with allocated low significancelevels are considered.

For Thessaloniki (Fig. 5a) only increases anddecreases in UV irradiance that are significant atthe 1% level are shown. The majority of the datapoints are located in the positive region, andabove 305 nm only increases are found to besignificant. There are only minor differences be-tween all sky and cloudless sky results. Bothshow an increase of positive gradients towardshigher wavelengths.

Fig. 4. Sodankyl€aa: Change of irradi-ance per decade in percent dependenton the wavelength. Different symbolsand linestyles indicate different SZAs


A different behaviour can be seen at theSodankyl€aa data: The criterion applied to theThessaloniki data set rejects most of the datapoints shown in Fig. 4. Therefore it was decidedto enhance the limit to 5%. The result in Fig. 5billustrates that only few gradients are significant.With increasing wavelength the number of sig-nificant changes decreases slightly, mainly in thecloudless sky data.

The high number of gradients with a positivesign indicates an increase in UV irradiance forThessaloniki. However, no simple explanationcan be given for the distribution of data pointsat one particular wavelength. For example at306 nm a datapoint of about 20% represents aSZA of 53� whereas another one close to zero

corresponds to a SZA of 51� (Thessaloniki). Thereasons for these contrasting gradients betweentwo close-by SZAs are unknown. Although onlysignificant gradients have been considered, resultslike this are not expected due to any atmosphericeffect. This reflects the fact that no significancetest is sufficient for a final conclusion on the valid-ity of a trend analysis. In addition, the trend anal-ysis must be consistent with respect to physicalexplanations as well.

Another aspect of our analysis is the inhomo-geneous distribution of data points over the timeperiod. Interruptions of routine measurements forexample due to calibration procedures or theparticipation in campaigns or, as mentionedbefore, changing measurement schedules hinder

Fig. 5. The number of increases and de-creases with a calculated significancelevel of 1% for Thessaloniki (a) or 5% forSodankyl€aa (b). Dark grey bars refer to allsky condition data, light grey bars representcloudless sky data


the determination of the irradiance for a givencombination of wavelength and SZA. Especiallyfor Sodankyl€aa seasonal variations play an impor-tant role. Measurements of solar irradiance atSZA¼ 65� or lower are possible only from endof March until mid of September. In Thessalonikimeasurements at lower solar zenith angles canonly be recorded during late spring and in sum-mer. One of the consequences is shown in Fig. 3.The strong increase in the time series at 304 nmand 54� SZA is probably caused by a higher tem-poral density of the UV irradiance measurementstowards the end of the time series. With a longertime series this uncertainty could be reduced.

Ozone is one of the dominant factors in longterm changes of solar UV irradiance (Zerefos,

2002). Figure 6 illustrates total ozone time seriesfrom Thessaloniki and Sodankyl€aa. It is evidentthat the series lack a clear decrease or increasein the analysed time period between 1990 and2001 and therefore it would be puzzling if therewas an ozone induced UV increase for this timeperiod. However, if the spectral measurementswould have been started much earlier (e.g. im-mediately after the first hypothesis about thedestruction of ozone by CFCs in the 1970s) itis expected that the situation would be different,as is shown below.

Figure 7 shows the results of the analyses ofthe extended time series. The number of years atone wavelength is an average for the completeSZA range we studied. Different scenarios for

Fig. 6. Yearly means of total ozone atThessaloniki and Sodankyl€aa. No sys-tematic upward or downward trendcan be recognised for this time periodin which spectral UV measurementshave been performed

Fig. 7. The number of years requiredfor detecting an increase in UV irradi-ance for the stations Thessaloniki andSodankyl€aa. The number of years isgiven for an average of all SZAs.Different symbols and linestyles indi-cate different scenarios with variousrates of ozone trends (see legend)


the two stations have been studied, for each sta-tion one scenario with a realistic ozone trend andone with a fictional ozone trend of �1.0% perdecade. The graphs indicate the number of yearsrequired for the detection of a positive gradient inUV irradiance in dependence on wavelength.

An assumed ozone trend of �4.5% per decadein Thessaloniki can be detected in all sky irradi-ance after 15 years for the wavelength rangebetween 311 and 313 nm if the influence of theother UV affecting parameters remains constant.Trend detection at Sodankyl€aa with an assumedozone trend of �5.7% per decade would bepossible at the earliest after about 12 years at300 nm. A lower rate of ozone decrease leadsto a higher number of years required for trenddetection. With an assumed trend of �1.0% perdecade a UV trend would be detected after 22years at 311 nm for Thessaloniki and after 23years at 300 nm in Sodankyl€aa at the earliest.

If cloudless sky time series are analysedinstead of all sky data the required number ofyears diminishes. The cloudless sky graph ofthe Thessaloniki �1.0% scenario is about 3 to5 years lower than the all sky line. Only theSodankyl€aa results between 300 and 307 nm showan unexpected behaviour with the cloudless skylines being above the all sky ones. It was firstassumed that there might be differences in thevariability, but the ratio of the standard devia-tions �(all sky)=�(cloudless sky) cannot explainthe performance since it does not show differ-ences between Thessaloniki and Sodankyl€aa data.

Instead we think that the number of data forcloudless sky situations are too sparse to reflectrepresentative cases for Sodankyl€aa.

For Sodankyl€aa we also calculated the numberof required years for different seasons (Fig. 8).For spring and summer about 20 years arerequired to find significant trends, although theozone trends are quite different (Mar.–May,�7.7% per decade; Jun.–Aug., �2.5% per de-cade). For autumn it is found that at least 30 yearsof measurements are needed to detect a UVdecline caused by an ozone trend of �3.6% perdecade (Sep.–Nov.). Generally with cloudlesssky time series less years are required for trenddetection. An interesting exception are the sum-mer data, which show that the analysis of cloud-less sky cases is not shortening the number ofyears required.

All seasonal analyses result in higher numbersof required years compared to the all-the-yearresult, even for the spring scenario with the high-est ozone loss rate of �7.7% per decade. It canbe concluded that not only the magnitude ofozone trends determines the required length ofthe time series needed for trend detection, butalso the density of the analysed data set. In ourstudy a year-round ozone decline of �5.7% canbe detected earlier in a UV measurement timeseries than an ozone reduction of �7.7% inspring UV data. This finding may be explainedby the higher natural ozone variability in spring,which requires a longer time series of UVmeasurements.

Fig. 8. Similar to Fig. 7 with seasonalscenarios for Sodankyl€aa


A similar behaviour as for the year-rounddata can be seen within the seasonal scenarios.Although the ozone trend in the autumn period(September–November) is higher than the one inthe summer period (June–August), more yearsare needed to detect a UV increase. The higherUV data density in combination with a lowerozone variability in summer compared to theautumn data could be an explanation for this per-formance. From the Sodankyl€aa result it can alsobe concluded that if there was an ozone trend of�5.7% per decade, it should have been recog-nised in the UV time series, provided the calibra-tion of the instrument to be constant over thistime period.

It is pointed out that these findings are unex-pected after the trend analysis results. Since theSodankyl€aa trend results are less significant thanthe Thessaloniki ones (Fig. 5), it was expectedthat a possible trend should be detectable earlierat Thessaloniki and later at Sodankyl€aa, but ourresult is vice versa.

It should be emphasised that we assume theozone trend to be constant for the complete anal-ysed period. Moreover, it is assumed that theinterannual variability due to the influence ofother UV affecting factors such as aerosols,albedo and clouds remains constant as well. Bothassumptions do not reflect the complex behav-iour of atmospheric parameters. It is extremelyunlikely that the ozone trends proceed in a linearway and thus a linear regression model might notbe able to comprehend possible future changesin UV irradiance. Moreover it is questionablewhether the variability of the original time seriesis representative for future conditions. All thesefactors would require even more years to detectsignificant trends.

For the superimposition of the artificial upwardtrend model calculation have been carried out.While the input parameters wavelength and SZAare adjusted to the characteristics of the data sub-sets, the variables albedo, day of year (and henceEarth-Sun-distance) and cloud coverage remainconstant in all model simulations. As this con-stancy cannot represent realistic conditions, thisapproximation is subject to uncertainties, too.

A trend detection can only be successful in awavelength range where the uncertainty of themeasurement is lower than the change in UVirradiance due to a change in total ozone. Assum-

ing the nowadays lowest possible uncertainty inspectral measurements, Bernhard and Seckmeyer(1999) found that this term applies mostly in thewavelength region of 295–300 nm, but also up to305 nm there is a chance to perceive a change inUV irradiance due to a 3% change in total ozone.It has to be emphasised that this result is basedon strict requirements regarding the measure-ment uncertainty.

In our analyses the wavelength, at which thelowest number of years for UV trend detection isneeded, can thus be considered to be the optimalone for trend detection. Our results show thatshort wavelengths are not as appropriate forThessaloniki as for Sodankyl€aa. If ozone is thedominant factor, it would be expected that lowerwavelengths are more appropriate for trend de-tection than higher ones (as it is the case for sta-tion Sodankyl€aa), because the ozone influence onUV irradiance becomes most important below305 nm.

Figure 7 indicates a remarkable difference be-tween the two stations. The Thessaloniki resultsare nearly independent of wavelength with a slightdecrease towards 315 nm. The Sodankyl€aa scenar-ios show an opposite behaviour: the number ofyears required to detect a trend increases towardshigher wavelengths. Thus for Sodankyl€aa wave-lengths near 300 nm seem to be more appropriatefor trend detection than higher wavelengths,which is not the case for Thessaloniki.

A difference in the variability at the differentstations cannot explain this behaviour. Our re-sults are in accordance with the findings of Arolaet al. (2003) who found out that the amplitude ofthe long-term variability caused by ozone ismuch stronger in Sodankyl€aa than in Thessaloniki.As the standard deviation in our analyses, thatcan be regarded as a measure for the variability,is higher for Sodankyl€aa than for Thessalonikidata, especially in the lower, ozone-affectedwavelength region, our analysis leads to the sameresult.

4. Conclusion

Spectral UV irradiance time series from Thessa-loniki and Sodankyl€aa have been analysed forpossible trends. Although positive gradients havebeen detected, mainly for Thessaloniki, an unam-biguous upward trend cannot be constituted.


A new method determining the required num-ber of years for trend detection and hence anoptimal wavelength range has been presented.In this study it was applied to two time seriesof UV irradiance, but it can be applied to otherstations and shorter time series as well.

It can be concluded that longer time series ofhigh quality spectral data would improve thepossibilities of trend detection and enhance thereliability of trend detection results. Especiallytime series of spectral global UV irradiance re-corded by instruments with low uncertainties inthe wavelength range between 295 and 305 nmwould be most interesting as this is the regionmostly affected by ozone changes. Such investiga-tions can only be performed by instruments witha low stray light, which is presently only possiblewith double monochromator instruments. As aconsequence the only way to find significant andconsistent UV trends, caused by further ozone de-pletion or ozone recovery, is the continuation ofhigh-quality long-term measurements of spectralUV irradiance.

Acknowledgements

We would like to thank Richard McKenzie (NIWA, NewZealand), Kaisa Lakkala, and Esko Kyr€oo (FMI, Finland)for their helpful suggestions. Kaisa Lakkala and EskoKyr€oo also kindly provided the Sodankyl€aa data used in thisstudy.

This study was supported by EU-funded project EDUCE(EVK2-CT-1999-00028).

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Authors’ addresses: Merle Glandorf (e-mail: [email protected]) and Gunther Seckmeyer (e-mail:[email protected]), Institute of Meteorologyand Climatology, University of Hannover, Herrenh€aauserStrasse 2, 30419 Hannover, Germany; Antti Arola, FinnishMeteorological Institute, Melania D245, Savilahdentie 9,P.O. Box 1627, 70211 Kuopio, Finland; Alkiviadis Bais,Aristotle University of Thessaloniki, Laboratory of Atmo-spheric Physics, 541 24 Thessaloniki, Greece.

44 M. Glandorf et al.: Possibilities to detect trends in spectral UV irradiance

possibilities to detect trends in spectral uv irradiance

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