Regional variations in hourly and daily totals of global radiation recorded at automatic weather stations in Estonia/Eesti automaatsetes ilmajaamades moodetud summaarse kiirguse tunni- ja paevasummade regionaalne jaotus.
Rosin, Kai ; Keevallik, Sirje
1. INTRODUCTION
It is well known that diurnal variation of the surface solar
radiation fluxes causes diurnal variation in the sea surface temperature
and upper layer vertical stratification [1]. The related
deepening/shoaling of the upper mixed layer on the daily scale will also
affect the biological and material circulation processes. Marine Systems
Institute performs high resolution measurements of temperature, salinity
and chlorophyll a fluorescence in the Gulf of Finland. Two transects are
recorded per day between Tallinn and Helsinki by means of the Ferrybox
system [2]. An autonomous buoy profiler, deployed off the Tallinn Bay,
records vertical profiles every third hour [3]. To explain the observed
diurnal cycles in the surface layer temperature, vertical stratification
and chlorophyll a fluorescence distribution, estimation of surface solar
radiation fluxes (including diurnal cycle) should be available. It has
not been verified yet whether the estimates, based on model outputs,
could be applied for this purpose, especially in cloudy conditions.
Estimates of the surface solar radiation fluxes over the sea are
important for oceanographic applications in both long-term (from a month
to a season) and short-term (diurnal) scales. Modelling of the
development of vertical stratification in an estuary needs (among other
parameters) knowledge on heat fluxes at the sea surface [4]. The
long-term changes, e.g., in the sea surface temperature, are usually
correlated with the radiation or sun hours data from coastal stations
[5]. A similar approach was applied in a study of inter-annual variation
of the late-summer cyanobacteria blooms in the Gulf of Finland, where
the radiation data recorded at Tartu-Toravere meteorology station were
used to link the observed bloom intensities to the changes in
photosynthetically active radiation [6]. Toravere is situated
approximately 200 km from the Estonian coastline, but up to recent times
it was the best site in Estonia, where all components of the radiation
budget are recorded. The other site was Tiirikoja that is situated
somewhat closer to the Gulf of Finland, but Tartu-Toravere was preferred
as it is a BSRN station where the quality of data is guaranteed [7].
Since 2003, Estonia has step by step replaced traditional
measurement routine at the meteorological stations by automatic
equipment. Automatic weather stations offer new possibilities to
estimate solar radiation parameters by means of certain models that use
meteorological information (e.g. [8]). On the other hand, many stations
have been complemented with actinometric equipment that measure directly
solar radiation. In Estonia, pyranometers have been installed at several
coastal meteorological stations that should offer a possibility to get
better input to oceanographic models that need radiation data.
It is widely known that conditions for radiation measurements are
extremely strict. They need open horizon (especially in winter when the
sun is low), periodic calibration of pyranometers, regular control of
the condition of the receivers, etc.). Unfortunately these requirements
are in many cases not met at Estonian meteorological stations (except
Toravere).
The goal of the present paper is to investigate relationships
between global radiation at the coastal stations and Toravere. First,
this draws attention to the problems of radiation measurements at the
automatic weather stations and, second, this might lead to the
possibilities of reconstruction coastal global radiation from Toravere
data in case no measurements are carried out at the site of interest.
The stress is put on daily and hourly totals. Due to the short
observation period (2005-2010) and gaps in data series, it was not
possible to derive direct climatological estimates. On the other hand,
it was still possible to find common periods of 2-3 years when data were
available for all or several observation sites. This gave us a
possibility to give a rough estimate of the spatio-temporal distribution
of the solar radiation characteristics.
Approximate information on the mean distribution of annual totals
of global radiation over the territory of Estonia is presented in the
Handbook of Estonian Solar Radiation Climate [9], where the long-term
average distribution is calculated on the basis of mean cloudiness and
albedo values at 31 meteorological stations. Later we compare our
estimates with those described in [9].
2. MEASUREMENT SITES AND EQUIPMENT
In the network of Estonian Weather Service there are eight
meteorological stations, where global radiation is measured (Fig. 1,
Table 1). Radiation measurements at Pakri were terminated in 2009. At
Haapsalu and Roomassaare the automatic stations were installed somewhat
later than others, in 2007 and 2008, respectively. In the present study,
radiation data from six stations during 2005-2010 were used, stations
with shorter observation period were left out.
To measure the downward and upward fluxes of solar radiation, Kipp
& Zonen pyranometers CM11 and CM21 are used. All stations with the
exception of Tartu-Toravere provide hourly mean radiation flux densities
(W/[m.sup.2]). At Tartu-Toravere one minute mean values are gathered and
processed.
The measurements of the openness of the horizon were carried out at
all stations in 2001 [9]. Since then the forest around Tiirikoja has
grown and shades the instruments even more. The estimates for Parnu
meteorological station are not available, as the station was relocated
in 2003. It is situated at the airport and according to visual estimates
the horizon is not shaded considerably. From Table 1 it can be concluded
that winter data from Tiirikoja and Narva-Joesuu may be underestimated.
[FIGURE 1 OMITTED]
The radiation equipment is calibrated regularly at Toravere. At
Tiirikoja one calibration was carried out, on 28 May 2008. No changes in
sensibility were detected. The pyranometers at other stations are not
calibrated during the period under consideration.
The pyranometers are ventilated to prevent dew and frost at
Toravere, Harku and Parnu. Thermal offset corrections are applied in
measurements at Toravere. Special instructions are given to the
personnel of meteorological stations to check the condition of the
receivers [10]. This should avoid the situations when the pyranometer is
covered with snow or ice, etc.
The data of Toravere passes strict quality control before it is
transmitted to the archives of EMHI (Estonian Meteorological and
Hydrological Institute), BSRN and WRDC (World Radiation Data Centre).
Datasets from other stations are not checked so thoroughly--before
sending to the archives, only these values are removed that are
obviously erroneous.
3. DATA
The whole dataset (except data from Tartu-Toravere) contained a
number of missing values. Major causes of missing values at daytime were
changes in the sensor configuration and temporary interruptions of the
automatic stations work.
Nighttime values contained several types of anomalies--there were
missing, negative and small positive values. Negative and small positive
values are related to the zero offset of the sensor [11]. This is a
widely recognized problem of pyranometers that may lead to discrepancies
between modelled and measured solar radiation [12]. Thermal offset
corrections are applied at the Toravere BSRN station.
The initial data from Harku station contained the greatest number
of missing values. The reason here was elimination of negative values
during the data transmission from automatic station to the archive.
Mostly data were missing during nighttime when there is no solar
radiation, but often missing data were shown also for daytime hours,
especially for morning and evening.
At Vilsandi, the data from 30 July 2008 to 30 June 2010 were
obviously erroneous. Due to incorrect sensor installation at the
station, radiation values never exceeded 640 W/[m.sup.2] during the
period.
4. REGIONAL DISTRIBUTION OF DAILY TOTALS
To estimate differences between radiation regime at Toravere and
coastal stations, daily totals were calculated from "cleaned"
data sets. "Cleaning" was carried out separately for every
coastal station depending on the detected problems. At all stations the
days were left out when at least one hourly measurement was missing. At
Vilsandi the period from 30 July 2008 to 30 June 2010 (when sensor
problems were detected) was left out.
At Parnu, two periods when solar radiation was systematically shown
at night were left out (20 February to 2 November 2008 and 30 January to
14 September 2009). Additional analysis showed that nighttime recordings
formed only 0.2% of the long-term average daily total, but it could be
suspected that the sensor or recording regime was also biased. At Harku
the zero and missing data were distinguished by means of sunset and
sunrise times and records with missing data were left out.
At the coastal stations there exist several cases when in winter
the recorded daily total was 0. Keeping in mind that the absolute
minimum of the daily total during the period under consideration at
Toravere was 0.13 MJ/[m.sup.2], these cases were checked by means of
historical atmospheric phenomena records that showed fog, rain or
snowfall. Therefore, these results should be considered realistic and
not be attributed to some mistake in the measurement routine.
As seen from the above, different periods were left out at
different stations. This means that the comparison of the radiation
regime at different stations could be carried out for shorter periods
that are common to all (or at least to most of the) stations. For
different months these periods were different (Fig. 2). In October, the
common period for all stations was less than two months. Therefore only
four stations are considered where the common period was longer. In
January, Tiirikoja and Narva-Joesuu were left out due to the restricted
openness of the horizon that might introduce systematic errors.
The following (approximate) features of the spatio-temporal
distribution of solar radiation can be seen.
--In April there is more sunshine in West-Estonia than in
East-Estonia.
--In July the sunniest places are seaside resorts Parnu and
Narva-Joesuu as well as the westernmost island of Vilsandi. Harku
meteorological station is situated at least 5 km from the sea on a
cliff. Here complicated orography and the neighbourhood of a large city
Tallinn affect the meteorological regime.
--An interesting feature can be noted concerning two sites on the
northern coast: there is more sunshine at Harku in April and at
Narva-Joesuu in July.
--In October the radiation conditions in North-Estonia and
East-Estonia are similar, most probably due to extensive homogeneous
cloud cover.
[FIGURE 2 OMITTED]
To get an overview on the distribution of solar radiation over the
Estonian territory, a common period of 2005-2007 (with missing data from
October 2005 to March 2006, and August 2007) could be found for which
annual average daily totals were calculated. Figure 3 shows that the
amount of solar radiation at Parnu and Vilsandi exceeds distinctly that
on the northern coast and inland. This is partly due to astronomical
factors: in January the TOA (Top of the Atmosphere) radiation on the
northern coast forms approximately 86% of that above Toravere. In
October this percentage is around 94. The annual averages at Tiirikoja
and Narva-Joesuu might be underestimated, as winter data are included in
annual average calculations. On the other hand, in case only the period
from March to November is considered, Harku, Tiirikoja and Narva-Joesuu
show similar values (not shown in the present paper).
[FIGURE 3 OMITTED]
5. DIURNAL CYCLE OF HOURLY TOTALS
The same data from common time periods were used to calculate daily
cycles of global radiation. Figure 4 shows results for April and July
when a common three-year period could be found for all stations. Figure
4 also shows that differences between radiation conditions at different
stations are larger in spring than in summer.
At Toravere, the maximum of the solar radiation is measured around
local noon (10:00 GMT denotes the hour from 9:00 to 10:00 GMT or from
11:00 to 12:00 winter EET) whereas solar radiation maximum at Vilsandi
is about an hour later. The solar time difference between these stations
is approximately 19 min. Therefore, this time lag must be due to
meteorological conditions.
In July the differences between stations are the largest around
12:00 GMT, i.e., during the afternoon hours. Most probably these
differences stem from the cloudiness that is more extensive at the
inland sites.
[FIGURE 4 OMITTED]
6. CORRELATION BETWEEN GLOBAL RADIATION AT THE COASTAL STATIONS AND
TORAVERE
To estimate global radiation at the coastal stations from Toravere
data, respective regression equations can be calculated for each
station. For this purpose, additional data on cloud cover was used and
cases were chosen when the cloudiness conditions were similar at both
stations. Cloudiness is recorded with 3-h intervals. Therefore, we chose
for comparison the afternoon hour of 11:00-12:00 GMT (13:00-14:00 EET).
Unfortunately, since the 1st of May 2009, clouds are recorded at
Narva-Joesuu and Tiirikoja only at 06:00 and 18:00 GMT.
Table 2 shows that hourly totals at Tiirikoja and Parnu can be
restored from the Toravere data rather well. The square of the
correlation coefficient (coefficient of determination) is 0.68 for
Tiirikoja and 0.65 for Parnu. This means that 65%-68% of the variability
of the hourly totals of global radiation at these sites is determined by
the variability of the fluxes at Toravere. Correlation is low for
Vilsandi and Narva-Joesuu, showing that approximately 40% of the
variability can be ascribed to the variability at Toravere. Figure 5
presents two examples of such regression, demonstrating the best and the
worst correlation.
In case only clear conditions were chosen (actually coverage up to
1/10), correlation is perfect as expected. Figure 6 shows that even for
Vilsandi, where the coefficient of correlation in overcast conditions
was the lowest, global radiation can be well derived from Toravere data.
[FIGURE 5 OMITTED]
[FIGURE 6 OMITTED]
7. CONCLUSIONS
The results of the present paper can be divided into two groups.
First, comparison of the simultaneous radiation measurements at
coastal stations and Toravere enables one to estimate the approximate
solar radiation regime in different regions. Another approximate
description of the radiation climatology is shown in [9], where global
radiation is estimated on the basis of mean cloudiness and albedo values
using the formula of Averkiev [13]. The authors of [9] confirm that
annual totals, got by such indirect method, describe the radiation
climate roughly. Our estimates are based on direct measurements.
Although there are problems with the openness of the horizon and a lot
of data were labelled as not reliable, the general features of the
radiation regime are similar on the annual basis: there is more sunshine
on the West-Estonian islands and West-Estonian coast and less on the
North-Estonian coast. Although Toravere is an inland station, it seems
to be a favorable site for solar radiation [14]. Handbook [9] gives also
a possibility to compare calculated and measured radiation: at Kuusiku
direct measurements were carried out during 1954-1963 and at Tooma
1956-1963. It seems that calculated annual totals of global radiation
are underestimated by 1% at Kuusiku and 4% at Tooma.
In the present paper also seasonal differences of global radiation
are described. Here an interesting feature may be noticed concerning two
sites on the northern coast: in April the daily totals at Harku are
larger than at Narva-Joesuu, and in July vice versa. This phenomenon is
worth further analysis, as the comparison is carried out on a 3-month
basis only.
As a result, in case the measurement conditions at the coastal
stations are improved, direct measurements give the possibility to
describe the spatiotemporal distribution of solar radiation more
precisely.
Second, application of Toravere radiation data by marine
investigations is discussed. It can be said that direct transfer of
inland data to marine conditions is not recommended, as the radiation
regimes differ significantly. On the other hand, in case there are no
measurements carried out at the seaside, it should be possible to
reconstruct global radiation at coastal sites using linear regression.
This has been checked for afternoon for two states of cloudiness: clear
and overcast. Regression gives good results everywhere when both sites
are cloud-free--coefficient of correlation is practically 1.0. In
overcast conditions the correlation is over 0.8 for Tiirikoja and Parnu,
over 0.7 for Harku and less for the most distant sites Vilsandi and
Narva-Joesuu.
And last, but not least: the quality of global radiation data from
automatic weather stations should be carefully checked as there are many
factors that might contaminate the measurements. From the above it
follows that periodical checking of all sensors is necessary and
attention should be drawn to the maintenance of the equipment. If
possible, also the quality control of data should be introduced.
doi: 10.3176/eng.2012.1.06
ACKNOWLEDGEMENTS
The radiation data were drawn from the archives of the Estonian
Meteorological and Hydrological Institute and prepared for calculations
by Ms Epp Juust. The authors of the present paper are grateful to
Associate Professor Ain Kallis for valuable consultations. The research
was supported by the targeted financing by the Estonian Ministry of
Education and Science (grant SF0140017s08).
REFERENCES
[1.] Kawai, Y. and Wada, A. Diurnal sea surface temperature
variation and its impact on the atmosphere and ocean: a review. J.
Oceanogr., 2007, 63, 721-744.
[2.] Lips, U., Lips, I., Kikas, V. and Kuvaldina, N. Ferrybox
measurements: a tool to study mesoscale processes in the Gulf of Finland
(Baltic Sea). In US/EU-Baltic International Symposium, 2008 IEEE/OES:
1-8. DOI: 10.1109/BALTIC.2008.4625536
[3.] Lips, U., Lips, I., Liblik, T., Kikas, V., Altoja, K.,
Buhhalko, N. and Runk, N. Vertical dynamics of summer phytoplankton in a
stratified estuary (Gulf of Finland, Baltic Sea). Ocean Dynamics, 2011,
61, 903-915.
[4.] Burchard, H. and Hofmeister, R. A dynamic equation for the
potential energy anomaly for analysing mixing and stratification in
estuaries and coastal seas. Est. Coast. Shelf Sci., 2008, 77, 579-687.
[5.] Van Aken, H. M. Meteorological forcing of long-term
temperature variations of the Dutch coastal waters. J. Sea Res., 2010,
63, 143-151.
[6.] Lips, I. and Lips, U. Abiotic factors influencing
cyanobacterial bloom development in the Gulf of Finland (Baltic Sea).
Hydrobiologia, 2008, 614, 133-140.
[7.] Eerme, K., Kallis, A., Veismann, U. and Ansko, I. Long-term
variations of available solar radiation on seasonal timescales in
1955-2006 at Tartu-Toravere Meteorological Station, Estonia. Theor.
Appl. Climatology, 2010, 101, 371-379.
[8.] Belcher, B. N. and DeGaetano, A. T. A revised empirical model
to estimate solar radiation using automated surface weather
observations. Solar Energy, 2007, 81, 329-345.
[9.] Russak, V. and Kallis, A. (compilers). Handbook of Estonian
Solar Radiation Climate. EMHI, Tallinn, 2003.
[10.] McArthur, B. Baseline Surface Radiation Network. Operations
Manual. Version 2.1. WMO, Geneva, 2004.
[11.] Solar Instruments, CMP Series Pyranometers Manual, Kipp &
Zonen, www.kippzonen.com, 17.03.2011.
[12.] Philipona, R. Underestimation of solar global and diffuse
radiation measured at Earth's surface. J. Geophys. Res., 2002, 107,
D22, 4654.
[13.] Averkiev, M. S. An improved method for calculating total
radiation. Vestnik Mosk. Univ., Ser. Geogr., 1961, No. 1, 40-47 (in
Russian).
[14.] Keevallik, S. and Loitjarv, K. Solar radiation at the surface
around the Baltic Proper. Oceanologia, 2010, 52, 1-15.
Kai Rosin and Sirje Keevallik
Marine Systems Institute at Tallinn University of Technology,
Akadeemia tee 15a, 12618 Tallinn, Estonia; sirje.keevallik@phys.sea.ee
Received 27 October 2011, in revised form 25 January 2012
Table 1. Station positions and
openness of the horizon
Station Approximate elevation
of objects above the
horizon, degrees
N E S W
Vilsandi 0 1 1 6
Parnu
Harku 3 4 2 3
Narva-Joesuu 0 10 12 10
Tiirikoja 10 4 5 10
Toravere 3 5 2 2
Table 2. Correlation and regression coefficients for
reconstruction of afternoon (11:00-12:00 GMT) hourly
totals at coastal stations from Toravere data for
overcast conditions
Coefficient Intercept, Slope
of correlation MJ/[m.sup.2]
Vilsandi 0.61 0.094 0.73
Parnu 0.81 0.037 0.81
Harku 0.74 0.055 0.70
Narva-Joesuu 0.65 0.158 0.65
Tiirikoja 0.82 0.061 0.83