The article presents the climatological dataset from the Polish
Polar Station Hornsund located in the southwest part of Spitsbergen – the
biggest island of the Svalbard archipelago. Due to a general lack of
long-term in situ measurements and observations, the High Arctic remains one
of the largest climate-data-deficient regions on the Earth. Therefore, the
described time series of observations in this paper are of unique value. To
draw conclusions on the climatic changes in the Arctic, it is necessary to
analyse and compare the long-term series of continuous, in situ observations
from different locations, rather than relying on the climatic simulations
only. In recent decades, rapid environmental changes occurring in the
Atlantic sector of the Arctic are reflected in the data series collected by
the operational monitoring conducted at the Hornsund station. We demonstrate
the results of the 40-year-long series of observations. Climatological mean
values or totals are given, and we also examined the variability of
meteorological variables at monthly and annual scale using the modified
Mann–Kendall test for trend and Sen's method. The relevant daily, monthly,
and annual data are provided on the PANGAEA repository
(
For the analysis of the Arctic climate change, the long-term operational
monitoring of meteorological variables including reliable observations and
measurements is obligatory. Weather conditions are crucial drivers that have
feedback on many environmental components, and it is important to have a
relevant dataset of atmospheric observation data when analysing the
variability and fluctuations of climate at any given location. Climate
change in the Arctic reflects a global warming trend, but the warming here
is much faster than in lower latitudes (IPCC, 2019). The characteristics of
Earth's climate zones are primarily determined by astronomical factors, but
there are differences in the mechanisms that cause a regional warming trend
and determine their magnitude. The presence of solar radiation, modified by
the degree of cloudiness and type of clouds, is the main factor influencing
the transfer of energy. In polar regions during the polar night, the sole
source of energy is the dynamic advection of heat from the oceanic and
atmospheric circulations with regional differences throughout the area.
Mechanisms of Arctic amplification are still not fully understood but
include feedback of reduced summer albedo due to reduction of sea ice extent
and snow cover loss, higher sea surface temperatures, an increase of
atmospheric water vapour content, cloud conditions, and changes in
atmospheric circulation (IPCC, 2019). The growing number of positive annual
air temperature anomalies in the Arctic varies substantially within the
region, with the strongest changes observed in the Atlantic sector
(Przybylak, 2016). Here, the Greenland Sea to the west of Svalbard is
dominated by the West Spitsbergen Current, carrying warm (3–6
Polish Polar Station Hornsund on Spitsbergen in the Svalbard archipelago.
The Stanisław Siedlecki Polish Polar Station in Hornsund (
At Hornsund meteorological site (indexed by international numbering system
01003 (
Interseasonal weather fluctuations are determined by the changing Arctic climate system and atmospheric circulation. The changing global climate also modifies regional conditions. Weather conditions are crucial factors that have local feedback on many environmental components. Meteorological variables collected at the Hornsund station help to characterise the climate variability in this part of the Arctic and for a long time have been the background for multiple studies conducted in the SW Spitsbergen (Osuch and Wawrzyniak, 2017b; Wawrzyniak et al., 2017). Due to the diurnal variability of all meteorological variables, in this study, we use descriptive statistic methods to present the course and variation of multiple parameters. For most meteorological parameters, monthly mean values are calculated from daily mean values which are retrieved using the 3-hourly values (eight values a day, between 00:00 and 21:00 UTC), in the case of precipitation 6-hourly values (12:00, 18:00, and 00:00, 06:00 UTC of the following day), and daily sum of total solar radiation from Campbell–Stokes recorder obtained at the midnight.
Meteorological data measured at Hornsund including variables, current sensors, the period of operation, height, units, and their annual averages or sums.
Air temperature (TA) can be presumed to be one of the most sensitive
indicators of climatic changes. The time series of daily TA from the
Hornsund station covers the period 1979 to 2018. In the case of daily mean
TA, there are no gaps in data, while for maximum and minimum, daily TA data
for 1 September 1979, 29 February 1980, 15 June 2012, and 19 June 2017 are missing. Figure 2a presents the variability of the annual mean of minimum, mean, and maximum
TA in 1979–2018 at the Hornsund station. An upward trend is clearly visible
for the three analysed variables. The significance of the trend was
estimated by the modified Mann–Kendall test (Mann, 1945; Kendall, 1975;
Hamed and Rao, 1998) taking into account autocorrelation of time series. The
slope of the trend was estimated using Sen's method (Sen, 1968), where the
slope is calculated as a median of the slopes of all pairs of points. The
outcomes of the modified Mann–Kendall indicated that the trends are
statistically significant; the estimated
The estimated slope of trend equal to 1.34, 1.14, and 1.00
Figure 2b shows the box plots of monthly averages of minimum, mean, and
maximum daily TA from the period 1979–2018. The variability of TA depends on
the season, with the highest amplitudes during winter months. Summer TA is
rather constant, with monthly means reaching usually slightly below
5.0
The slope of the trend in monthly and annual data (air temperature – TA, relative humidity – RH, precipitation – Precip, atmospheric pressure at sea level – PA, wind speed – WS, sunshine duration – SD, cloudiness and visibility – VV) estimated by Sen's method in the period 1979–2018 for air temperature and sunshine duration and in 1983–2018 for other variables. The results of trend analysis by modified Mann–Kendall method to account for autocorrelation in the time series. Bold numbers denote a statistically significant trend at the 0.05 level.
The water vapour drives multiple atmospheric processes and has a significant influence on the global climate. It is the main greenhouse gas, affecting the surface by feedback cycle through changing energy balance through radiative fluxes and cloud formation. According to general concepts, the Arctic warming of recent decades is accompanied by the hydrological cycle intensification (Vihma et al., 2016; Osuch et al., 2019). To understand the variability of water vapour concentration and its causes is highly important, especially for climate studies as well as in water balance calculations. At the Hornsund station, the air humidity is currently measured by sensor HMP155, which replaced the previously used HMP45D sensor. The observations cover the period 1979–2018, but measurements were performed four times a day (00:00, 06:00, 12:00, 18:00 UTC) within the periods 1 July 1978–26 July 1981 and 16 August 1982–31 July 1986, two times a day (06:00 and 18:00 UTC) from 27 July 1981 to 30 June 1982, and eight times a day (00:00, 03:00, 06:00, 09:00, 12:00, 15:00, 18:00, 21:00 UTC) since 1 August 1986. Daily time series of the relative humidity (RH) was calculated as a mean of all available measurements within a particular day. There is a gap in the measurements from 1 July 1982 to 15 August 1982. Therefore the trend analyses were performed for the period 1983–2018.
The variability of the annual mean RH in the period 1983–2019 is presented in Fig. 3a. The average over the period 1983–2018 is 79.7 %. The range of variability is from 75.7 % (2003) to 82.7 % in 1994. The trend analyses indicated a statistically insignificant trend.
The course of the monthly mean RH in the period 1983–2018 is presented in Fig. 3b. Higher values of mean RH are observed in warmer months of the year and lower during winter. Such high values are attributed to continual dominance of marine air masses. The annual course of the RH is strongly connected with the air temperature and shows typical variability. It generally increases with warmer air temperatures. However, most of the trends are not statistically significant at the 0.05 level except March, June, and October.
The analyses at daily timescale indicated that drops of RH below 50 % are recorded rather sporadically, although these can occur throughout the year. Such situations are connected with advection of strongly cooled air masses, foehn effects, or katabatic winds from Hansbreen (Marsz and Styszyńska, 2013). The minimum observed quantity reached 24 % on 15 January 1981. The maximum of the observed RH is equal to 100 %. Such conditions occurred 27 times in the period 1979–2018.
In the case of precipitation, the daily sum at the Hornsund station is
calculated from four measurements obtained from an unfenced Hellmann rain gauge
at 12:00, 18:00, and 00:00, 06:00 of the following day, with the orifice 200 cm
The influence of the West Spitsbergen Current creates a relatively moist climate in SW Spitsbergen region, which is clearly reflected in the amount of precipitation. In comparison to the other meteorological stations in Spitsbergen (Osuch and Wawrzyniak, 2017a; Hanssen-Bauer et al., 2019), the annual amount reaching 477 mm is the highest. The variability of the annual sums of precipitation in the period 1983–2018 is shown in Fig. 4a. The amount of precipitation varies from 230 mm in 1987 to 805.5 mm in 2016. The trend analyses indicated large changes, an increase of 61.6 mm per decade for the annual sums of precipitation.
The annual course of monthly sums of precipitation from the period 1983–2018 is presented in Fig. 4b. The driest months are April and May with averages of 23 and 24 mm respectively. The highest precipitation is recorded in September reaching on average 75 mm. Trend analyses presented in Table 2 indicate statistically significant changes in January (3.51 mm per decade), September (19.67 mm/decade), and October (13.53 mm per decade).
The measurements of the atmospheric pressure (PA) at Hornsund started in
July 1978. In the beginning, PA was measured with a mercury barometer every
3 h. Since 2001 measurements have been conducted every 60 s with a
Vaisala PTB200A sensor, replaced by BARO-1QML_AV in 2018. The
lowest recorded PA reduced to sea level at Hornsund station was 982.2 hPa on
30 August 1994, while the absolute maximum was 1028.5 hPa on 7 August 1987. Mean annual
PA in long-term 1983–2018 is 1008.7 hPa, and its variability is presented in
Fig. 5a. An increasing trend (0.25 hPa per decade) is visible, but it is
statistically insignificant (
Figure 5b shows the variability of the mean monthly PA over the period 1983–2018. Well-pronounced seasonality is visible, with a mean monthly pressure higher than 1010 hPa from April to August. The month with the lowest mean PA is December with a mean of 1002.7 hPa, and the month with the largest PA is May with a mean of 1015.7 hPa. The variability of mean monthly PA within the observation period also is visible with the largest variability in January and February (larger than 30 hPa) and the smallest in July (13.7 hPa). The trend analyses of mean monthly PA resulted in a statistically insignificant trend for all months.
The wind is a result of atmospheric circulation and is highly correlated
with the intensity of cyclonic activity (Przybylak, 2016). The wind regime
results from the latitudinal shape of the Hornsund fjord, location near the
seashore and local topography. The measurements of wind speed (WS) and wind
direction (WD) were performed at Hornsund with different sensors: 1978–2000
with the Fuess 90z wind meter, 2001–2017 with Vaisala WAA151 for direction
and wind speed, since 2018 with Ultrasonic Wind Sensor WMT702. At Hornsund
station the height of the anemometer is 10 m above the ground, around 20 m
above sea level. WS is measured with an accuracy of 0.1 m s
The wind rose for the Hornsund station for the period 1983–2018.
The variability of the mean annual WS at Hornsund in the period 1983–2018 is
shown in Fig. 7a. The average over the period 1983–2018 is equal to 5.5 m s
The variability of mean monthly WS in the period 1983–2018 is presented in
Fig. 7b. WS regime is well visible with smaller average values during
summer months (minimum 4.0 m s
Sunshine duration (SD) is one of the important meteorological variables that provides data on the time period during which direct solar radiation reaches the Earth's surface and partly on the quantity of total solar energy. Daily SD is measured at Hornsund using a Campbell–Stokes sunshine recorder (CS). It uses a direct optical method with the heat energy of the Sun's direct radiation burning the card. Such a traditional sunshine recorder has been in service worldwide since the 19th century; although there are multiple automatic radiometers used simultaneously at the Hornsund station, the longest data are recorded by CS. The time series of sunshine duration cover the period 1983–2018. At the Hornsund station, the polar night lasts 104 d (31 October–11 February), while the polar day lasts 117 d (24 April–18 August).
Figure 8a shows the variability of the annual sums of SD at Hornsund in the period 1979–2018. The mean value is 1030.8 h, which is about 28 % of the potential SD calculated for the station (Wojkowski et al., 2015). The large span in the annual SD is visible. The minimum value (755.4 h) was observed in 1994 and the maximum (1325.6 h) in 1985. The slightly decreasing trend in SD is visible but statistically insignificant at the 0.05 level.
Monthly total SD is presented in Fig. 8b. Its variability results from the
different duration of the day at the location (latitude 77
Arctic clouds have a warming effect on the surface during most of the year because their effect of increasing the downward longwave radiation dominates their effect of reducing the net solar radiation over high-albedo snow and ice surfaces. In summer, however, clouds typically have a cooling effect on surface types with a lower albedo, such as the open sea, melting sea ice, and ground (Intrieri et al., 2002; Shupe and Intrieri, 2004). Observations of cloudiness at the Polish Polar Station in Hornsund are conducted by meteorologists and describe the predominant sky condition based upon octas (eighths) of the sky covered by opaque (not transparent) clouds. There are many factors that may hinder the heterogeneity and evaluation of cloudiness, due to the annual change in the meteorological observers and the fact that observers might be subjective, although they are provided with clear observable criteria.
Annual averages of cloudiness in the period 1983–2018 are presented in Fig. 9a. The mean over this period equals 5.85 octas. The minimum value of annual mean was observed in 1988 (5.16 octas) and the maximum in 1984 (6.39 octas). An increasing tendency of mean annual cloudiness is visible. The estimated trend (slope 0.13 octas per decade) is statistically significant at the 0.05 level.
The variability of the monthly cloudiness in the period 1983–2018 is presented in Fig. 9b. The annual cycle is characterised by lower mean cloudiness during the cold period from October till April (5.5–6.0 octas), and this period is also characterised by large interannual variability. The period from May till September is on average cloudier (6.0–6.7 octas), and interannual variability is lower.
The horizontal visibility is quantified using observations made by meteorologists in the surroundings of the Hornsund station with a marine scale that ranges from 1 to 9. The visual observations are performed using known distances to the surrounding mountains and other objects. Values 1 and 2 correspond to very bad visibility, 0–50 and 50–200 m, respectively. Bad visibility (200 m–1 km) is represented by a value of 3. Weak horizontal visibility represents conditions with 1–2 and 2–4 km that are quantified as 4 and 5 in the applied scale. Moderate horizontal visibility, described as 6 in the scale, represents conditions when an object or light can be clearly discerned from 4 to 10 km. Good horizontal visibility (7 in the scale) is 10–20 km, very good (8) 20–50 km, and extremely good (9) is for horizontal visibility larger than 50 km. Noted visibility might be reduced by multiple factors, including all products of the condensation of water vapour such as fog, precipitation, and darkness during cloudy conditions throughout the polar night, as there are no artificial lights in the area. There are no anthropogenic factors that would reduce visibility in the vicinity of the Hornsund station as it is located in the middle of the strictly protected South Spitsbergen National Park. Due to that, reduced visibility cannot be an indicator of poor air quality on the local scale.
Figure 10a shows the variability of mean annual visibility in the period
1983–2018. On average in this period, there is good horizontal visibility that
amounts to 7.40; minimum mean annual visibility was observed in 2016 (7.08),
while a maximum was observed in 1987 (7.70). A decreasing tendency is visible (slope of
trend
All presented datasets have undergone a thorough quality control process.
Such a process consisted of multiple steps as the measurements may not be
homogenous due to the varying number of observations during the day, changes
of sensors, and other factors (Estévez et al., 2011). In the first step,
the data were visualised as a time series that allowed verification if all
data had been collected and the record structure were correct, complete,
and without any gaps. In this way also the presence of outliers and step
change in the data was tested. To determine the degree of compatibility and
homogeneity of the measurements from different sensors, which changed over the
years, the old and new sensors were operated simultaneously for more than
1 year. The results allowed us to combine time series. In the following step,
different variables were compared to test the internal consistency between
variables. Such analyses include a comparison of minimum, mean, and maximum
daily TA that follow the rule TA
The dataset described in this article is available on the PANGAEA repository
(
This paper has presented details of a long-term (1979–2018) dataset from
the meteorological site at the Polish Polar Station Hornsund located in the
SW part of Spitsbergen. The data series includes daily, monthly, and annual
air temperature, PDD, NDD, the sum of precipitation, air humidity,
atmospheric pressure, wind speed and direction, sunshine duration,
cloudiness, and visibility. This rich dataset, now available online, is a
valuable source for documenting the state of the climate in SW Spitsbergen,
which represents the Atlantic sector of the Arctic. With the positive trend
of mean annual temperature of
TW and MO wrote the paper and carried out the data processing and analysis.
The authors declare that they have no conflict of interest.
The authors would like to kindly thank the meteorological staff from the
Polish Polar Station Hornsund (listed here:
This research has been supported by the Polish National Science Centre (grant no. 2017/27/B/ST10/01269) and the Ministry of Science and Higher Education of Poland (grant no. 3841/E-41/S/2020).
This paper was edited by Jens Klump and reviewed by two anonymous referees.