Solar and wind energy resources of the Eger Region
17
Hungarian Geographical Bulletin 63 (1) (2014) 17–27.
DOI: 10.15201/hungeobull.63.1.2
Solar and wind energy resources of the Eger Region
János MIKA1, Edina Kitti CSABAI1, Ildikó DOBI2, Zsófia MOLNÁR3,
Zoltán NAGY2, András RÁZSI1,3, Zsuzsanna TÓTH-TARJÁNYI2 and
Ilona PAJTÓK-TARI1
Abstract
The spatial interpolation and mapping of renewable energy resources is an important task
of potential estimation of atmospheric renewable energy sources. First the global radiation
on horizontal surfaces and near-surface wind speed at 10 m height above the surface (not
at 60–120 m, which is the height of contemporary wind turbines) is measured. Based on
standard meteorological observations, the experts of the Hungarian Meteorological Service
elaborated a series of digital maps with 0.1°×0.1° resolution. The grid-point values are based
on homogenised data using MASH theory and soft ware. The study tackles solar and wind
energy from four aspects. Firstly, a trial for validation of the gridded data is provided by a
comparison between a single station, Eger and the very closely located grid-point values.
Secondly, the annual cycles of the areal-mean global radiation and wind speed are pre-
sented, based on the gridded data of a selected area of 50×50 km. Both the averages and
the standard deviations of the diurnal mean values are presented for the 1981–2010 refer-
ence period. Presenting the maps of the distribution within the area is the third issue with
average and standard deviation values. Finally, the point-wise trends are drawn for both
energy sources in the single grid-point used in the aspect one in 1981–2010 and also in the
nearby located stations for comparison. The trend of solar energy is positive, whereas the
trend for wind energy (speed cube) is negative in the given 30 year period. Since, mainly
warming characterised those three decades in the Northern Hemisphere, the trends might
also be interpreted as responses to the large-scale forcing, though the observed behaviour
does not necessarily mean causal relationship with the global tendencies.
Keywords: global radiation, wind energy, Eger Region, annual cycle, climate change
1 Eszterházy College, H-3300 Eger, Eszterházy tér 1. E-mails: mikaj@ektf.hu, ecsabai@gmail.
com, razsia@ektf.hu, pajtokil@ektf.hu
2 Hungarian Meteorological Service, H-1024 Budapest, Kitaibel Pál u. 1. E-mails: dobi@met.
hu, nagy.z@met.hu, tarjanyi.zs@met.hu
3 Hungarian Meteorological Service, Regional Centre, H-3530 Miskolc, Petőfi S. u. 18. E-mails:
razsi.a@met.hu, molnar.zs@met.hu
18
Introduction
The development of society and economy is oft en determined by climate, to-
pography and water availability. This relationship is in the focus of our present
research on renewable energy sources and energy effi ciency in the Eger Energy
Region, NE Hungary. Natural conditions for the utilisation of the resources
and the associated societal conditions will be discussed in the paper. The Eger
Energy Region consists of 23 sett lements including the county seat, Eger. The
area of the region is 718 km2; its population was 92,483 inhabitants in 2009.
The present study deals with solar and wind energy. Results of spatial
and temporal analyses of global radiation and wind speed data will be presented
below. Gridded data values will be compared with those of one single station
located very close to one of the grid-points. The annual cycle of the area-mean
values and the standard deviations of the diurnal means as well as distributions
will be presented. Finally, the point-wise linear trends of annual and seasonal solar
radiation and wind cube values will be given for the grid-points.
Data and methods
In the meteorological practice, solar energy is observed on a horizontal surface.
Wind energy is related to 10-metre height above the ground. None of them is
considered as maximum available energy since the optimally directed and tilted
solar cells as well as the higher-elevated wind turbines will provide more energy.
Nevertheless, the smooth spatial distribution of both energy sources provide a
fi rst insight into the availability of the energy, since direction and tilt modify the
energy independently of the spatial coordinates, except in the case of extreme
topographical conditions. The logarithmic dependence of wind speed from the
height does not explicitly vary with horizontal coordinates, either.
The presented results are mainly based on grid-point data in a ca.
50×50 km area containing the Eger Energy Region (Figure 1). More exactly,
the gridded data are characterised by their geographic limits of are 47.6° and
48.1° Northern latitudes and 20.0° and 20.7° Eastern longitudes. The gridded
data obtained by the experts of the Hungarian Meteorological Service are
also available on the Internet (www.carpatclim-eu.org). The interpolation was
performed for the whole country also involving some near-border stations of
the neighbouring countries. Hence it is diffi cult to assess how many stations
were involved in the interpolation. From the meta-data, one can establish that
allowing 0.6°–0.6° wider areas than the rectangle, the area contains 7 stations
for wind speed but only two stations for sunshine duration. The data series is
available for 1961–2010, but we use the data of the 1981–2010 period which co-
incides with a more or less even warming period in the Northern hemisphere
which is also confi rmed by the recent IPCC AR5 Report (IPCC, 2013).
19
Fig. 1. The Eger Energy Region in the 0.1°×0.1° geographical network with the single
station called Eger. The other lines represent the administrative areas of the 23 sett lements
of the region
The area of computations is characterised by variable topography,
though the majority of the highest hills of the investigated rectangle are not
included in the region. The average height of the rectangle is 205 m, the stand-
ard deviation of the elevation of the 48 grid-points is 150 m. The highest located
grid-point is at 866 m a.s.l., whereas the lowest point is at 86 m a.s.l.. There are
12 grid-points below 100 m a.s.l. and again 12 grid-points above 300 m a.s.l.. For
these features are considered by the interpolation methodology is applied.
The input data of the stations underwent on a homogenisation proc-
ess (“MASH” by Szentimrey, T. 1999) to avoid non-realistic fl uctuations and
to obtain a statistically optimal interpolation (“MISH” by Szentimrey, T. and
Bihari, Z. 2006). The latt er does not only use the spatial correlation of the
elements but also the temporal correlation which is not known in any other
spatial interpolation methodology. Both statistical processes are described by
the authors at htt p://www.carpatclim-eu.org/docs/mashmish/mashmish.pdf.
In the given database wind data are derived from direct measure-
ments, but solar radiation data are estimated from sunshine duration applying
the method of Angström, A. (1924) modifi ed by Prescott, J.A. (1940).
20
For comparison, the point-wise observed data measured by the stand-
ard meteorological station of Eger (47.90° N, 20.39° E, 225 m a.s.l.) are also used
for much shorter periods, namely the data of 2001–2010 for global radiation
and those of 1996–2010 for wind speed. The point-wise values are compared
with the grid-point data at the point of 47.90° N latitude and 20.40° E longi-
tude. One must note that the station Eger was not involved in the grid-point
value derivation due to the sparse data availability in 1961–2010.
The statistical calculations applied below are fairly simple: averaging
is based on the diurnal values. Standard deviations are also computed for the
diurnal values to represent diurnal variability of the available energy. The
trends are determined by the method of least squares. The signifi cance of the
trends is not estimated, the correlation coeffi cients are added for orientation.
The validations of the gridded data both for global radiation and wind
speed cube for Eger are presented in the next part of the paper. The validation
is crucial from the point of view of feasibility to apply the gridded data in the
evaluation of energy potential in the region.
The annual cycles of the gridded global radiation and wind speed data
based on the area mean values will also be presented. Not only the annual
cycle of the means but also the standard deviations are in the scope of the
evaluations to describe the stability of the available potential.
The estimated spatial diff erences for the climatic means and standard
deviations of January and July months will be detailed too. Geographical dis-
tribution around the mean values is also mapped exhibiting interesting spatial
patt erns despite the small size of the investigated rectangle.
Finally, we return to the point-wise values of Eger to explore the long-
term tendencies in the time variations of global radiation and wind cube at
10-m height.
Validation of the grid-point data
The fi rst important question concerning the grid-point data is whether they refl ect
the real values correctly, especially under the circumstances of complex topog-
raphy. We could make this comparison only between the meteorological station
of Eger and the nearby grid-point. The horizontal distance between them is less
than 1 km. Note that the station was always involved in the interpolation.
Global radiation
Table 1 represents a fair agreement between the global radiation of grid-point
(Rcc) and the observation by the station (Robs). The diff erence between the
21
means of the 30-year period and the means of the 10-year period is rather
signifi cant though in case of comparing the shorter station data series with
the identical gridded data, the diff erence is increasing. That statement also
refers to the medians. The standard deviation values taken from the identi-
cal ten-year periods, however, are closer to each other. The maxima and the
minima are fairly close to each other, as well. So, the grid-point values can
be considered as a fair approximation for global radiation with no consider-
able biases.
Wind speed
Unfortunately the grid-point values of wind speed cubes (Fcc), i.e. the fi rst
approaches of the available wind energy (Table 2) do not perform so well.
The 30-year climate estimate is 50% larger than values observed at the station
(Fobs) during a 15-year period. About half of the diff erence disappears if we
compare the identical time periods. The remaining diff erence is still 25%, i.e.
the gridded values overestimate the wind cubes by that value. The medians
are also a bit overestimated.
Table 1. Basic statistics for global radiation in Eger and in the nearest grid-point
MJ/m2/day Rcc Rcc Robs
Period 1981–2010 2001–2010
Mean
Median
Standard deviation
Minimum
12.00
10.67
7.59
2.09
12.27
11.00
8.36
0.39
12.06
10.61
8.44
0.00
Maximum
No of days
29.46
10,957
31.25
3,652
Table 2. Basic statistics for wind-cube in Eger and in the nearest grid-point
(m/s)3 Fcc Fcc Fobs
Period 1981–2010 1996–2010
Mean
Median
Standard deviation
Minimum
Maximum
30.07
10.65
69.29
0.02
1,702.21
25.07
10.22
52.18
0.06
1,401.17
19.94
9.26
34.38
0.00
614.13
No of days 10,957 5,479
22
The standard deviation of daily values diff ers even more signifi cantly.
The diff erence between the 30 years grid-point values and the 15 years station
values is above 100%, roughly the half of which remains when comparing the
identical periods but diff erent data. This strong overestimation peaks in case
of maxima with almost threefold diff erence between the 30-year gridded and
15 years local data. Due to the diff erence, the statistics of wind will be mapped
only for its fi rst power (instead of its cube).
We would like to emphasise again that the Eger station was not in-
volved in the grid-point value derivation, since the observations were per-
formed at diff erent sites during the basic 1961–2010 interpolation period. The
above validation is a good example for any point of the Eger region, because
the grid-point data are completely independent from the station-data.
Areal-mean daily statistics
Averages of global radiation and wind speed
Figure 2 illustrates the annual cycle of global radiation and wind speed by the
areal mean values based on the gridded data, also indicating the highest and
the smallest values of the 30 years average values of monthly total radiation and
monthly mean wind speed. The July maximum of global radiation is slightly
over the June value explained by the annual minimum of cloudiness in July.
Standard deviations of the diurnal values
The climatic mean values provide fi rst insights into the available energy re-
sources. The knowledge of diurnal variability around these values is also im-
portant. Figure 3 presents the standard deviations for the daily sums of global
radiation and the daily mean wind speed which, certainly, refl ect the strong
annual cycle of global radiation, but they behave diff erently from the annual
cycle of wind speed (Figure 2).
Fig. 2. Annual cycle of global radiation (MJ/m2) (left ) and the mean wind speed (m/s) (right) by
the areal mean values with the lowest and highest point-wise averages in 1981–2010
23
Mapping diurnal means and standard deviations
Global radiation
Figure 4 illustrates the spatial distribution of global radiation in January and
in July. The data represent the diurnal mean values. The maps were created by
the ArcGIS soft ware. The annual cycle of global radiation is mainly determined
by the astronomical diff erences at the given latitude, i.e. the early summer
maximum of the zenith angle, the length of daylight and by the annual cycle
of cloudiness which is the lowest in July.
The standard deviation maps of the diurnal data can be seen in Figure 5.
Here, again, the fair estimation of standard deviation by the single grid-point value
near Eger in the above validation allows for considering the above maps confi rm-
ing the estimates of the real standard deviations. Only the peak value of standard
deviation in the 47.9° N 20.0° E grid-point is infl uenced by the mountainous sta-
tion of Kékestető located almost there, nearly 1,000 m a.s.l.. Here, cloudiness may
cause strong time variations in radiation. That eff ect is present only in July, but
not in January when there are clouds at any elevation.
Fig. 3. Annual cycle of standard deviation for diurnal global radiation (M J/m2) and that of wind
speed by the areal average values with maxima and minima of the region (1981–2010)
Fig. 4. Average global radiation fi elds diurnal global radiation at a horizontal plain by the grid-
ded data. Units: MJ/m2
24
Fig. 5. Standard deviation of diurnal global radiation at a horizontal plain according to the
gridded data. Units: MJ/m2
Fig. 6. Average
fields of diur-
nal mean wind
speed according
to the gridded
data. Units: m/s
Wind speed
Figure 6 presents similar values of wind speed at the 10 meters observation
level. The maps indicate even larger relative diff erences within the area pos-
sibly as a consequence of over-interpretation of the topography. The maxima
around a few single grid-points are not convincing, either.
The standard deviation values of the diurnal mean values of wind
speed can be seen in Figure 7. Their structure also contains some surprising local
extremities which are hardly real consequences of the real topography. Hence,
even if the maps represent the linear wind speed estimates, the spatial patt erns
of both the averages and the standard deviation are rather uncertain.
Fig. 7. Standard
de viation of
diurnal mean
wind speed at
10 m above the
ground level ac-
cording to the
gridded data
25
Observations
Global radiation
The long-term trends are presented in a single grid-point located at the shortest
distance (ca. 1 km) from Eger. The CC series are based on the derived values
from sunshine duration (see above). It is fairly convincing that in the last
10 years with frequent observations, the inter-annual fl uctuation occurred
parallel in the two series (Figure 8).
The annual totals of global radiation exhibit unequivocal moderate
trend of 5.31 MJ/m2year. Comparing it with the average value of the 30-year
period, it can be establish that it is the only 1% per decade. It means that the
future development of solar energy industry will hardly depend on the direct
eff ect of climate change.
According to Figure 9
the two seasons with the high-
est absolute values, i.e. sum-
mer and spring exhibit in-
creasing trends, whereas the
two other seasons are charac-
terised by decreasing trends.
Both the absolute diff erence
and the diff erences of steep-
ness of the trends support the
positive trend of annual global
radiation presented in Figure 8.
Since the observed 1981–2010
period coincided with a global
warming period. The trends
can also be interpreted as a re-
sult of a monotonically warm-
ing period of 30 years.
Wind energy
The same analysis is per-
formed for wind cube data
and their annual means
shown in Figure 10. The dia-
gram indicates a considerably
decreasing trend in 1981–
Fig. 8. Trends of annual global radiation (MJ/m2) in
the near-Eger grid-point (CC: 1981–2010) and the local
observation in Eger (Obs2)
Fig. 9. Seasonal trend lines in the CC series of global ra-
diation with the linear trend and the explained variance
(square of correlation coeffi cient) by the given trends
26
2010. As stated previously, the diff er-
ences between the gridded and the
point-wise data are rather big. How-
ever, the strong biases may have been
constant during the 30-year period.
The wind speed trends of sea-
sonal means are presented in Figure 11.
They equally demonstrate the decreas-
ing tendency which makes the reality
of the trend in the annual mean even
more convincing.
Discussion
The gridded global radiation data may be considered as fairly good approach-
es but this is not the case for wind data. In both cases, data compared with the
data of Eger station were not involved in the interpolation. Hence, both experi-
ences can be considered to be based on the comparison of independent data.
The presented mapping is based on the probably best available sta-
tistical interpolation using input data from the whole country and for some
stations near the border. In principle, it promises a bett er estimation of real
Fig. 10. Trends of the annual mean value of
daily mean wind-cube (m3/s3) in the grid-
point nearest to Eger and in the point-wise
measurement in Eger
Fig. 11. Trends of the seasonal mean values of daily mean wind-cube (m3/s3) in the grid-
point nearest to Eger and in the point-wise measurement in Eger
27
values than any other interpolation using a smaller dataset. MISH does not
only use spatial but also temporal correlations, which may also improve the
interpolation. Furthermore, the statistical homogenisation of the data allows
avoiding the biggest errors of initial observations.
The spatial structure of the wind speed is derived without the fi nest
spatial structure of the region. Of course, at higher altitudes where the wind
turbines are generally operated, the wind fi eld is smoother. Nevertheless, the
real wind turbines would need site-specifi c dynamical modelling as generally
requested in the feasibility studies.
The observed trends are convincing both for the increasing global
radiation and for the decreasing wind speed. The positive experience of the
validation for global radiation supports the established trends, which cannot
be repeated for wind speed cubes. Moreover, the trends do not necessarily
mean that they continue in the future if the global warming continues.
Acknowledgements: The study was supported by the TÁMOP-4.2.2.A-11/1/KONV-2012-
0016 Project in Hungary. The gridded data are downloaded from Open Access data base
derived by the CarpatClim Project (htt p://www.carpatclim-eu.org/pages/home/).
REFERENCES
Angström, A. 1924. Solar and terrestrial radiation. Quarterly Journal of the Royal Meteorological
Society 50. 121–125.
IPCC 2013. Climate Change 2013. The Physical Science Basis. Final version. htt p://www.ipcc.
ch/report/ar5/wg1/) 2260 p.
Prescott, J.A. 1940. Evaporation from a water surface in relation to solar radiation.
Transactions of the Royal Society of South Australia 64. 114–118.
Szentimrey, T. 1999. Multiple Analysis of Series for Homogenization (MASH). Proceedings of
the Second Seminar for Homogenization of Surface Climatological Data. Budapest;
WMO, WCDMP-No. 41. 27–46.
Szentimrey, T. and Bihari, Z. 2006. MISH (Meteorological Interpolation based on Surface
Homogenized Data Basis). In The use of GIS in climatology and meteorology. Eds.
Tveito, O.E. et al. COST Action 719. Final Report,. The use of GIS in climatology and
meteorology. Eds. Tveito, O.E. et al. 54–56.
28
Changing Ethnic Patt erns of the Carpatho–Pannonian
Area from the Late 15th until the Early 21st Century
Edited by: Károly KOCSIS and Patrik TÁTRAI
Hungarian Academy of Sciences, Research Centre for Astronomy and Earth Sciences
Budapest, 2013.
This is a collection of maps that visually introduces
the changing ethnic patt erns of the ethnically, reli-
giously, culturally unique and diverse Carpathian
Basin and its neighbourhood, the Carpatho-
Pannonian area.
The Hungarian and English volume consist of
three structural units. On the main map, pie charts
depict the ethnic structure of the sett lements in pro-
portion to the population based on census data et the
millennium. In the supplementary maps, changes of
the ethnic structure can be seen at nine dates (in 1495,
1784, 1880, 1910, 1930, 1941, 1960, 1990 and 2001).
The third unit of the work is the accompanying text,
which outlines the ethnic trends of the past
fi ve hundred years in the studied area.
The antecedent of this publication is
the „series of ethnic maps” published by
the Geographical Research Institute of the
Hungarian Academy of Sciences from the
middle of the 1990’s, which displayed each
of the regions of the Carpathian Basin (in
order of publication: Transylvania, Slovakia,
Transcarpathia, Pannonian Croatia, Vojvodina,
Transmura Region, Burgenland, Hungary).
This work represents, on the one hand, the
updated and revised version of these areas,
and, on the other hand, regions beyond the
Carpathian Basin not included on previous
maps. Thus, the reader can browse ethnic
data of some thirty thousand sett lements in
diff erent maps.
-----------------------------------
Price: EUR 12.00
Order: Geographical Institute RCAES HAS
Library
H-1112 Budapest, Budaörsi út 45.
E-mail: magyar.arpad@csfk .mta.hu
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/HRV (Za stvaranje Adobe PDF dokumenata najpogodnijih za visokokvalitetni ispis prije tiskanja koristite ove postavke. Stvoreni PDF dokumenti mogu se otvoriti Acrobat i Adobe Reader 5.0 i kasnijim verzijama.)
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/NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken die zijn geoptimaliseerd voor prepress-afdrukken van hoge kwaliteit. De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 5.0 en hoger.)
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/SUO <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>
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/UKR <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>
/ENU (Use these settings to create Adobe PDF documents best suited for high-quality prepress printing. Created PDF documents can be opened with Acrobat and Adobe Reader 5.0 and later.)
/HUN <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>
>>
/Namespace [
(Adobe)
(Common)
(1.0)
]
/OtherNamespaces [
<<
/AsReaderSpreads false
/CropImagesToFrames true
/ErrorControl /WarnAndContinue
/FlattenerIgnoreSpreadOverrides false
/IncludeGuidesGrids false
/IncludeNonPrinting false
/IncludeSlug false
/Namespace [
(Adobe)
(InDesign)
(4.0)
]
/OmitPlacedBitmaps false
/OmitPlacedEPS false
/OmitPlacedPDF false
/SimulateOverprint /Legacy
>>
<<
/AddBleedMarks false
/AddColorBars false
/AddCropMarks false
/AddPageInfo false
/AddRegMarks false
/ConvertColors /ConvertToCMYK
/DestinationProfileName ()
/DestinationProfileSelector /DocumentCMYK
/Downsample16BitImages true
/FlattenerPreset <<
/PresetSelector /MediumResolution
>>
/FormElements false
/GenerateStructure false
/IncludeBookmarks false
/IncludeHyperlinks false
/IncludeInteractive false
/IncludeLayers false
/IncludeProfiles false
/MultimediaHandling /UseObjectSettings
/Namespace [
(Adobe)
(CreativeSuite)
(2.0)
]
/PDFXOutputIntentProfileSelector /DocumentCMYK
/PreserveEditing true
/UntaggedCMYKHandling /LeaveUntagged
/UntaggedRGBHandling /UseDocumentProfile
/UseDocumentBleed false
>>
]
>> setdistillerparams
<<
/HWResolution [2400 2400]
/PageSize [612.000 792.000]
>> setpagedevice