Meteorol. Appl. 12, 101–110 (2005)
doi:10.1017/S1350482705001659
Comparison of offshore wind park sites using SAR wind measurement techniques Tobias Schneiderhan1 , Susanne Lehner1 , Johannes Schulz-Stellenfleth1 & Jochen Horstmann2 1 German Aerospace Centre, Oberpfaffenhofen, 82234 Wessling, Germany 2 GKSS Research Centre, Max-Planck-Str., 21502 Geesthacht, Germany Email:
[email protected]
Wind farming has grown rapidly in Europe over the last decade. All European countries with shallow coastal waters and strong mean coastal wind speeds are planning or already constructing offshore wind farms. Large parts of the North Sea and Baltic Sea are being investigated to see whether they are suitable for offshore wind parks. In this study we show how satellite images taken by space-borne radar sensors can be used to determine mesoscale wind fields and thus help in the task of planning offshore wind farms. High-resolution synthetic aperture radar (SAR) images acquired by the European remote sensing satellite ERS-2 showing single wind turbines are investigated. The methods for retrieving high-resolution wind fields from SAR images are explained and statistical comparisons of wind speed and wind direction at the two offshore wind park sites in the North Sea, Horns Rev and Butendiek, are given.
1. Introduction Active microwave radar satellites transmit and receive radar signals with wavelengths in the range of centimetres to one metre, thus measuring the roughness of the sea surface and enabling the retrieval of wind and ocean wave fields. Synthetic aperture radars (SARs) are capable of imaging synoptic wind fields with a coverage of up to 500 km × 500 km and a resolution as low as 100 m. Because the radar signals penetrate clouds these sensors have all-weather capability (Katsaros et al. 2002) and can also collect data at night. Therefore, they are especially suited for sea surface observations in coastal regions and in severe weather conditions (Lehner et al. 2001). Since 1991, the European remote sensing satellites ERS-1 and ERS-2, the Canadian satellite RADARSAT1 and the European environmental satellite ENVISAT have been providing SAR images over the oceans on a continuous basis. Their high resolution and large spatial coverage make them a valuable tool for measuring wind fields especially in coastal areas and for comparing wind parameters for different sites located on the same SAR scene. Great efforts have been made to develop algorithms for the derivation of wind vectors from SAR images (Vachon & Dobson 1996; Wackermann et al. 1996; Fetterer et al. 1998; Lehner et al. 1998, Korsbakken et al. 1998; Horstmann et al. 2000, Du et al. 2002; Furevik et al. 2002) and also in wind resource estimation (Fichaux & Ranchin 2002; Hasager et al. 2004).
The wind direction can be deduced from the direction of wind-induced streaks visible in most SAR images, which are approximately in line with the mean wind direction. The direction of these streaks can either be retrieved using spectral methods (Lehner et al. 1998; Horstmann et al. 2000), or in the spatial domain by a method based on local gradients (Horstmann et al. 2002; Koch 2003). The wind speed is derived from the normalised radar cross section (NRCS) measured by the SAR using semiempirical C-band models that were originally derived for scatterometers at an accuracy of about 20 degrees and 1 ms−1 (Lehner et al. 1998; Horstmann et al. 2000, 2003). These high-resolution wind fields allow the extraction of wind speed and wind directions for any offshore site located in the scene. Therefore estimates of the energy output at the respective offshore location and comparisons of wind situations at different sites are possible. Using this and additional information about the wind distribution in time and space (also derived from the SAR scenes) offshore wind-farm projects can be supported in selecting the most suitable sites in areas where no or only few data can be collected, and can further help to reduce risks and costs during the building phase. The results also lead to new knowledge about the effects of the wind parks on the local wind field, such as turbulent wakes or wind shadowing, which can be used for future planning and construction of the sites. In this paper 35 ERS SAR scenes from March 2002 to April 2003 covering the area of Horns Rev and Butendiek are analysed, resulting in 28 single comparisons
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Tobias Schneiderhan, Susanne Lehner, Johannes Schulz-Stellenfleth & Jochen Horstmann SAR scenes 2003
SAR scenes 2002 1
1
0
0
1
31
61
91
121
151
181
211
240
270
300
330
360
1
31
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Days of the year
Days of the year
Figure 1. Overview of the utilised SAR scenes 2002 and 2003.
(Figure 1 and Appendix). In seven cases the observed offshore wind parks are located on consecutive scenes. The dataset represents one complete year of nearly equally distributed acquisitions taken over the region of interest, 21 scenes are from descending orbits (about 1030 UTC) and seven from ascending (2130 UTC) orbits. The aim of this study is to investigate the effects of the different locations and to estimate the possible power output at the Butendiek offshore site, making use of the in situ data measured at Horns Rev and the synoptic SAR data showing both sites in different wind field situations.
Figure 2. The Horns Rev wind park.
2. Offshore wind farming in Europe In Europe offshore wind farming is developing rapidly. During the past ten years several wind parks have been constructed, and within the last few years the production of wind energy in Europe has grown to more than 23000 MW (installed by the end of the year 2002) and nearly 32000 MW worldwide. Wind energy is about to replace hydropower as the most important commercial source of clean, renewable energy. In the North Sea and the Baltic about 280 MW of offshore power is generated. Many new wind farms, each with over 150 single wind turbines and an output of more than 5000 MW, covering areas of more than 200 km2 , are planned or are already under construction. For example, the first planned and approved German offshore wind park at Borkum West will have more than 200 wind turbines with a total power yield of up to 1000 MW and will cover an area of nearly 200 km2 . The largest wind park that is already in operation is Horns Rev (Figure 2), which is situated in the North Sea off the west coast of Denmark. Figure 3 shows a SAR image of the Horns Rev wind park while it was still
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Figure 3. Sub-image of 30 km × 50 km ERS-2 SAR scene from the Danish offshore wind park Horns Rev, obtained on 30 July 2002.
under construction. Today, 80 wind energy converters are running at this offshore site. Investigations into ecological short- and long-term effects of these parks on the environment are currently being undertaken. One important parameter that can be observed with space-borne SAR is the high-resolution wind field in the vicinity of the wind farms. SAR enables the investigation of changes in the wind field due to the wind turbines, e.g. turbulent wakes and blockage effects in front of the wind farm.
SAR wind measurement of offshore wind park sites Such wake effects were found in some images, leading in one scene to a reduction in wind speed from 6 ms−1 in front of the wind park to 5 ms−1 behind the turbines. These results show that SAR data have the potential to estimate influences on onshore wind parks or maritime shipping and to optimise wind park design.
3. Investigated SAR data Since the launch of the European remote sensing satellites ERS-1 and ERS-2 in 1991 and 1995, SAR images have been obtained over the oceans on a continuous basis. The ERS SAR operates at C-band with vertical (VV) polarisation in transmit and receive. The resolution is about 30 m in range (across flight direction) and 10 m in azimuth (along flight direction). The ERS-satellites are positioned in a near-circular, polar and sun-synchronous orbit at an altitude of ∼ 790 km. ERS provides in the image mode calibrated high-resolution images of the Earth’s surface in a range of incidence angles between 20◦ and 26◦ perpendicular to the flight direction, corresponding to a coverage of 100 km × 100 km. The coverage of the image mode scenes is essential for this comparison. Therefore wind park sites were chosen that are less than 100 km apart, thereby making it possible to compare the sites by analysing single scenes. Nevertheless, both wind parks are at significantly different distances to the coast and it cannot therefore be assumed a priori that the wind conditions are the same. The revisit time of the ERS satellites is about 11 days because of the scene coverage. The availability depends on existing acquisition requests. The basis for this comparison are 35 ERS SAR scenes of the North Sea showing the area of both wind farms. In seven cases the wind park sites are on consecutive scenes. Therefore the dataset shows only 28 single dates of observation. The SAR scenes analysed in this comparison (an example is given in Figure 15) represent one year of data in this area, which are available at the European Space Agency. This way one receives a good first guess of wind parameters for offshore sites where only few or no measured data exist. In future, comparisons using ENVISAT data can be added to increase the revisit time.
4. SAR Wind measurements SAR wind field retrieval is a two-step process. In the first step, wind directions are retrieved, which are a necessary input into the second step to retrieve wind speeds from the intensity values. Wind directions are retrieved from wind-induced phenomena aligned according to the wind direction, which are visible in most SAR images. Their imaging by SAR is caused by phenomena
such as boundary layer rolls, Langmuir cells and wind shadowing. The orientation of these streak-like features (see Figure 5) is approximately in the direction of the mean surface wind. The method used hereafter defines the wind direction as normal to the local gradients derived from smoothed amplitude images. Therefore the SAR images are smoothed and reduced to an appropriate pixel size, e.g. 100 m, 200 m and 400 m. From these pixels the local direction is computed, leaving a 180o ambiguity (Koch 2003). From the resulting directions the most frequent and most probable local direction is selected using additional assumptions about the wind flux pattern. The 180o ambiguity can be removed if wind shadowing is present, which is often visible in the lee of coastlines and large objects such as offshore structures. For retrieving wind speeds from SAR data a model function relating the NRCS of the ocean surface σ 0 to the local near-surface wind speed u, wind direction versus antenna look direction and incidence angle θ , pol
σ0
= a(θ )uγ (0) [1 + b(θ ) cos + c(θ )2 cos ]
(1)
is applied. Here a, b, c and γ are coefficients that in general depend on radar frequency and polarisation pol. These coefficients were determined empirically in the case of the model functions CMOD4 by evaluation of scatterometer data of the European satellite ERS-1 and wind fields from the ECMWF (Stoffelen & Andersen 1997). CMOD4 has been applied successfully in wind speed retrieval from C-band VV polarised ERS SAR images (Lehner et al. 1998; Horstmann et al. 2002, 2003) in which the accuracy of the algorithm was shown to be about 1 ms−1 in wind speed and about 22◦ in wind direction. Hail, raindrops or ocean currents and salinity change the roughness of the surface and thus the image intensity, which influences the wind velocity derivation. Furthermore, the directions can change within a front as can be observed in Figure 4. In particular, areas with ocean current shear can show a pattern in the scale of wind streaks that can be misinterpreted as the wind direction. An example of a tidal current feature at Horns Rev is shown in Figure 7. To avoid the influence of features not due to the local wind, e.g. atmospheric fronts or current shear that occur in some of the SAR scenes of this study, the boxes to determine the wind speed estimation were manually set to areas with no or only weak feature effects.
5. The Horns Rev and Butendiek offshore wind parks The two offshore wind farms that are investigated here are located in the German Bight of the North Sea about 60 km apart. An overview is given in Figure 5 where the locations are indicated on an ENVISAT ASAR wide swath mode scene.
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Tobias Schneiderhan, Susanne Lehner, Johannes Schulz-Stellenfleth & Jochen Horstmann The second wind farm investigated, Butendiek, is approved and in planning stage. This wind farm will be located 35 km off the German island of Sylt. It consists of 80 single wind turbines of the 3 MW class. The hub height will be 80 metres and the rotor diameter 90 metres. In the following, SAR data are used to investigate the difference in wind climate between the two sites, which are about 60 km apart. Their varying distances to the coast and their different exposures in the North Sea were expected to affect the wind direction and the wind speed and thus the energy yield of the two farms. A measurement mast at the wind park site at Horns Rev has been recording data since 1999.
Figure 4. Atmospheric front on a 100 × 100 km ERS scene (22 September 2002).
Local wind speed is the key parameter for estimating the power generated by a wind farm. The power output is in a first approximation proportional to the cube of wind speed. For an idealised wind turbine with blade diameter D, the power yield is given by power =
π ρ · D 2 · U3 8
(2)
where U is the wind speed at hub height and ρ is the air density (≈ 1 kg m–3 ). In practice wind converters are limited to a certain range of wind speeds. Typically, wind turbines are operating at wind speeds between 4 and 25 ms–1 (see also Figure 6). The maximum energy output is reached with wind speeds of more than 13 ms–1 . When the wind speed reaches 25 ms–1 or more, the wind converters have to be switched off because of the likelihood of damage. Special interest is therefore given to the ascending slope of the power curve between 4 and 13 ms–1 . Even small uncertainties in wind speed result in big differences in the estimated energy output.
Figure 5. ENVISAT ASAR wide swath mode scene of 400 km × 400 km obtained on 14 April 2003 at 2128 UTC with imprinted locations of the two offshore wind farms.
The Danish wind farm Horns Rev is situated 15 km off the Danish west coast near Blavands Huk. The wind farm was built in 2002 and the turbines have been in operation since December 2002. It is the first wind farm of this size in the world. There are 80 single 2 MW wind turbines installed, with a hub height of 70 m and rotor diameters of over 80 m, resulting in an overall height of 110 m. The turbines are arranged as a rectangle with 8 × 10 piles. The separation distance is 560 m between the rows and therefore the site covers a region of about 20 km2 .
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Figure 6. Energy output of a 2 MW wind turbine for wind speeds from 0 to 30 ms−1 (courtesy of ELSAM).
SAR wind measurement of offshore wind park sites Horns Rev vs. Butendiek 16
Butendiek wind (m/s)
14 12 10 8 6 4 2 0 0
5
10
Horns Rev wind (m/s)
bias: rms: Figure 7. Derived local wind field of an offshore wind situation (25 June 2002, 1026 UTC) of a 100 km × 100 km SAR scene.
6. Comparison of the Horns Rev and the Butendiek offshore sites
0,2 1,1
15 2
R = 0,909
Figure 8. Wind speed U10 at Horns Rev versus wind speed at Butendiek.
wind farm was taken to be the mean of five measurement areas around the respective offshore site. The choice of the locations of the boxes took into account taken possible wind shadowing effects in wind direction.
The first step was to determine the local wind field for the SAR images, deriving the wind direction and the wind speed for the whole scene with a resolution of 10 km. The areas of the wind farms were then extracted from the resulting data. Five areas, each of about 5 × 5 km around the wind farms, were taken to reduce the effects of non-wind induced features. This is the reason for the varying positioning of the white boxes in Figure 7. At Horns Rev the wind turbines themselves affect the derivation by their bright return and therefore the measurement areas are put around the site. The second cause affecting this formation is the effect of the tidal current flowing over the shallow area at Blavands Huk, causing strong variations in currents (Figure 7).
The results are plotted in Figure 8. One can see that the wind speed measurements at the two sites are the same to measurement accuracy for the 28 wind field situations imaged by the SAR. At medium wind speeds, from 4.5 to 8 ms−1 , the wind speed at Butendiek is slightly higher than the corresponding values at Horns Rev; outside this range the trend is reversed.
The wind farm Butendiek is still in planning stage and therefore no piles exist that can affect the backscatter. Additionally the site shows no current features relating to tidal currents that influence the derivation of wind fields.
To investigate the data further, wind directions were split into four mean wind directions classes (N, E, S and W) and the mean wind speed for each class was calculated from the derived wind speed values of the comparison. The results are listed in Table 1.
Possible shadow effects of the wind park itself are taken into account in the measurements. But the aim of the work was to compare Horns Rev (with all the conditions, including distance to the shore) to the Butendiek site. So shadow effects of the land are not excluded.
6.1. Wind speed analysis
As can be seen, the mean wind speed at Butendiek shows higher values in three out of four cases than at Horns Rev and a total increase in the mean wind speed of 2% between Horns Rev and Butendiek. This is in contrast to the former assumption that Butendiek will have lower wind speeds because of its location further south in the German Bight. The distance to the coastline has more influence on the wind speed than the difference of the site locations inside the German Bight.
The mean wind speed at the two locations was derived and compared for all 28 scenes. The wind speed for each
Therefore, in terms of SAR measurement accuracy, and assuming that the dataset investigated is representative,
At Horns Rev the mean wind speed for the scenes investigated is 5.5 ms−1 and at Butendiek it is 5.6 ms−1 , a difference of 2%.
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Tobias Schneiderhan, Susanne Lehner, Johannes Schulz-Stellenfleth & Jochen Horstmann Table 1. Wind direction class, the number of scenes of each class and the mean values of the classes. Mean wind speed (ms−1 ) Direction North East South West
No. of scenes
Horns Rev
Butendiek
Horns Rev
Butendiek
5 10 9 4
6.7 4.2 6.8 4.2
6.9 4.5 6.9 4.1
1.14 0.82 1.59 1.48
1.26 0.94 1.58 1.33
Figure 9. Wind speed distribution derived from three years of in situ measurements at 62 m height at Horns Rev (courtesy of ELSAM).
the wind speed distributions at the two sites show no significant difference. Figure 9 shows the wind speed distribution measured at a height of 62 m at the Danish offshore site of Horns Rev (courtesy of ELSAM). The data are based on a 3-year measurement campaign starting in 1999. It can be seen that the wind climate at Horns Rev is dominated by westerly winds of about 10 ms−1 . The wind speeds measured at hub height can be converted to the 10 m wind speeds measured by SAR, and vice versa, using the well known logarithmic model for the vertical wind profile. U10 is chosen because the surface roughness measured with SAR techniques represents the wind speed at 10 m height (see equation (1) and description) and afterwards the values can be extrapolated to the desired hub height which depends on the turbine type. Under stable atmospheric conditions the vertical wind profile is usually assumed to be of the following form z u∗ log 1 + U(z) = κ z0
(3)
with Karman constant κ= 0.41, friction velocity u∗ , and roughness length z0 . For the water surface the following empirical relationship between the roughness length and the friction velocity can be used: z0 = α ·
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Std deviation (ms−1 )
(u∗ )2 g
(4)
Figure 10. Vertical wind speed profiles for stable atmospheric conditions according to the model given by eq. 3.
with Charnock constant α = 0.0144 and acceleration of gravity g. Figure 10 shows respective wind profiles together with a horizontal line at U10 , the height to which the SAR measurements are calibrated. Profiles are given for U10 = 5, 10 and 15 ms−1 .
6.2. Wind direction analysis Both wind farms are situated in the North Sea where winds from the west and southwest normally predominate. In the SAR dataset winds from the south and east are more prevalent than from the north and west. This difference in the distribution of the wind directions may be due to the fact that 18 scenes were acquired during the winter half year and only 14 scenes during the summer half year. In the winter, easterly winds are more frequent than in the summer. To get a more realistic distribution a longer time series may have to be analysed. The wind directions of the two sites are compared in Figure 11. The circle shows the number of images analysed in each quadrant. In contrast to in situ data from Horns Rev, the SAR dataset winds are coming more frequently from southern and eastern directions. At Horns Rev the most frequent wind directions are from southwest to northwest. As expected, the comparison of the wind directions shows no significant difference between the two sites. A small adaptation of northerly and easterly winds to the coastline around Horns Rev can be observed. This effect is not present at Butendiek because of the long distance to the shore.
SAR wind measurement of offshore wind park sites
5 4
9
10
wind directions (coming from)
Butendiek (degree)
300
200
100
0 0
bias: rms:
100
4,3 15,4
200
Horns Rev (degree)
300 R2 = 0,9721
Figure 11. Mean wind directions occurring in the 28 analysed SAR scenes. These are classified in the 4 wind direction classes (upper left).
Figure 12. Local wind field from SAR with the location of the two offshore wind farms 8 October 2002, at 1026 UTC (SAR scene: 100 km × 100 km).
7. Discussion of single wind situations In the following some wind field cases of special interest from 8 October 2002 (Figures 12, 13 and 14) and 25 June 2002 (Figures 15 and 16) are discussed.
7.1. Case 1: Wind rolls The first example shows a northerly wind situation with changing wind variability from the shore. The size of the atmospheric structures on the ocean surface grows with increasing distance to the coast. The wind speed ranges from about 5 to 7 ms−1 over the whole scene. Only behind the islands at the coast does it drops down to 3.5 ms−1 . The structures show small clusters that increase in size with distance to the coast. They show an alignment along the mean wind direction and are most likely to be associated with marine boundary layer (MABL) rolls. The diameter of the turning rolls is related to the height of the boundary layer (Stull 1988). The measurement of the rolls in the SAR scene shows a significant increase of the variability from the coast to offshore and from north to south. Just behind the islands in the upper part of the image the rolls have a size of ∼ 800 m, growing in the southwest to 3600 m (Figure 12). In the lee of the islands there is an additional effect of slight dark stripes lying above the clustered structure. These lines have an average distance of less than 500 metres and are the result of wind shadowing and varying currents.
Figure 13. Profile 1 of wind speed U10 between Horns Rev and Butendiek (from north to south).
In Figures 13 and 14 a wind profile of the Horns Rev and the Butendiek site and an across-component profile (as imprinted on Figure 12) are plotted. A reduction in wind velocity from north to south and from west to east can be identified and spatial variation of the wind field can be observed to be of the order of 1 ms−1 . On this day a high pressure system is present over the eastern North Sea, with winds from the north-east having a mean wind velocity of 5 ms−1 (mean of several meteorological stations in the region), which is in good agreement with the SAR measurements of 5.7 ms−1 . It should be noted that the wind speed given in the weather map represents a 10-minute mean and the SAR measurement a snapshot of the wind situation averaged
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Figure 14. Profile 2 of wind speed U10 across the wind direction (from west to east).
In the case of onshore situations like this, the wind field is homogeneous in the absence of fronts. As expected the difference in wind speed between the two sites is very small (0.1 ms−1 ).
Horns
profile 3
Butendiek
5,3 m/s 5,2 m/s
Figure 15. Wind field derived from an ERS SAR scene of 100 km × 100 km with indicated areas used for wind measurements (white boxes) and the location of the wind park sites (red boxes).
over space. At Sylt airport a wind speed of 6.4 ms−1 was measured at 12:00 UTC.
7.2. Case 2: Onshore winds The SAR scene taken on 25 June 2002 (Figure 15) represents a typical onshore wind situation, with wind coming from westerly directions. The SAR derived wind speed is about 5.3 ms−1 . The weather situation on this day (winds from the west) and the SAR derived wind field agree well. The estimated wind speeds at the wind farms are 5.3 and 5.2 ms−1 , while in situ data from weather stations taken out from a weather map show wind speeds of 5 to 7.5 ms−1 .
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Figure 16. Wind profile 3 from Butendiek wind park into the wind (left side: west, right side: east).
In Figure 16 the wind profile is shown imprinted on Figure 15. The idea is to derive a short-term forecast for the wind output. At the moment of acquisition, a wind speed of 5.2 ms−1 is detected. The distance of about 50 km corresponds to a forecast of 160 minutes from acquisition time, if we make use of Taylor’s hypothesis. This technique provides new opportunities for offshore operators to estimate near term energy outputs or the reduction of fatigue loading using single situations for their estimation.
8. Conclusion and outlook Using SAR-derived wind fields the spatial variability of wind fields of two offshore wind farm locations in the German Bight of the North Sea was investigated. The comparison of 28 SAR scenes representing different wind field situations from the year 2002 shows slightly higher wind speeds at the Butendiek wind farm than at Horns Rev. The difference of the mean wind speed between the two sites amounts to 0.1 ms−1 or 2% higher wind speeds at Butendiek. The rms error of 1.1 ms−1 is about the measurement accuracy. Bias in wind direction is 4.3 degrees and an rms error of 15.4 degrees. The assumption that the wind speed will be lower at Butendiek because of its closer location in the German Bight has to be dismissed. To verify these results a larger dataset will be analysed together with results of an atmospheric numerical model. ERS image mode data are taken since 1991 on a continuous basis, which makes it possible to carry out a long-term statistical analysis.
SAR wind measurement of offshore wind park sites The comparison of the local wind field and the weather situation showed good agreement, and additional features like spatial wind variability can be observed in the SAR images. For future applications, ENVISAT data are available in the same format. An additional wide swath mode with up to 400 km swath width and 150 m spatial resolution extends the applicability of this tool to an area covering almost the entire North Sea in one scene and reduces the revisit time. This gives new opportunities for comparing more offshore wind farm sites and validating the results with in situ measurements located in the images yielding a synoptic overview of nearly the whole North Sea. Furthermore, due to the larger area covered, the repetition rate of the acquisitions means that measurements are taken nearly daily at these latitudes.
Acknowledgements A special thanks to ELSAM for permission to use their figures and photographs. The SAR data were kindly provided by ESA in the frame of an ERS AO.
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Appendix
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Scene no.
Orbit
Frame
Date
Time
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
35762 36263 36535 36764 36828 37329 37537 37766 37830 38038 38102 38267 38539 38603 38768 38811 39040 39312 39770 39813 40271 40314 40815 40836 41044 41108 41545 41774
2493 2493 2493 2493 1107 1107 2493 2493 1107 2493 1107 2493 2493 1107 2493 2493 2493 2493 2493 2493 2493 2493 2493 1107 2493 1107 2493 2493
21.02.2002 28.03.2002 16.04.2002 02.05.2002 06.05.2002 10.06.2002 25.06.2002 11.07.2002 15.07.2002 30.07.2002 03.08.2002 15.08.2002 03.09.2002 07.09.2002 19.09.2002 22.09.2002 08.10.2002 27.10.2002 28.11.2002 01.12.2002 02.01.2003 05.01.2003 09.02.2003 10.02.2003 25.02.2003 01.03.2003 01.04.2003 17.04.2003
10:23 10:23 10:26 10:23 21:22 21:22 10:26 10:23 21:22 10:26 21:25 10:24 10:23 21:25 10:23 10:29 10:26 10:29 10:23 10:29 10:23 10:29 10:29 21:22 10:26 21:25 10:26 10:23
