OBSERVED CLIMATE VARIATIONS DURING THE LAST 100 YEARS IN LAPLAND, NORTHERN FINLAND

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1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 20: (2000) OBSERVED CLIMATE VARIATIONS DURING THE LAST 100 YEARS IN LAPLAND, NORTHERN FINLAND SUSAN E. LEE a, *, M.C. PRESS b and J.A. LEE b a Sheffield Centre for Arctic Ecology, Department of Animal and Plant Sciences, Tapton Experimental Gardens, Uni ersity of Sheffield, Sheffield S10 5BR, UK b Department of Animal and Plant Sciences, Alfred Denny Building, Uni ersity of Sheffield, Western Bank, Sheffield S10 2TN, UK Recei ed 25 February 1999 Re ised 15 June 1999 Accepted 20 June 1999 ABSTRACT Many general circulation models (GCMs) predict that high latitude environments will experience substantial warming over the next 100 years, which will be particularly pronounced during the winter months. Precipitation is also expected to increase but there is uncertainty as to the amount and spatial variation. The flora and fauna of the arctic and subarctic regions, together with indigenous people, such as the Saami, are particularly vunerable to rising temperatures and changing precipitation. Mean monthly temperature and precipitation data were examined for the last 100 years for northern Finland. These data were further analysed for the first and second half of the 20th century. There was no discernible warming trend between 1876 and 1993, but a significant annual warming (r=0.344, 0.05) occurred in the period , together with a significant summer warming (r=0.381, 0.05). Warming has occurred consistently in May and June over the last 100 years and there appears to be a current (i.e. post 1990) annual trend, mostly due to winter warming. The greatest temperature anomaly increase for the period was in the winter months (+0.72 C). The degree of temperature variation in the winter is greater than in the summer and has risen from 3.98 C for December in the period to 4.37 C in the period This is attributed to the recent high variability in the North Atlantic Oscillation (NAO) Index. Annual precipitation has increased significantly during the period The period was wetter than , with greater variability particularly in the summer months, which contribute most to the annual precipitation in Lapland. Copyright 2000 Royal Meteorological Society. KEY WORDS: temperature; precipitation; Lapland; northern Finland; North Atlantic Oscillation (NAO); Saami; region; technique(s); climate variable(s) 1. INTRODUCTION There is a general consensus among atmospheric scientists that global temperatures are rising and this is due, at least in part, to anthropogenic emissions of CO 2. Over the last 100 years, global mean temperatures have been gradually increasing, but since the early 1980s they have reached record levels (Intergovernmental Panel Climate Change (IPCC), 1996). Recently, the National Oceanic and Atmospheric Administration s (NOAA) National Climatic Data Center (NCDC) in Asheville, NC, USA reported that the warmest year on record was 1997 with the global mean temperature 0.42 C above the mean of 16.5 C for the period If this temperature is incorporated into the overall global warming trend since the start of this century, it is now just above 0.55 C per 100 years, with global land temperatures rising at a faster rate than the sea temperatures (Quayle et al., 1997). The increase in global mean temperature is predicted to be between 1 and 3.5 C by the end of the 21st century (IPCC, 1992). * Correspondence to: Sheffield Centre for Arctic Ecology, Department of Animal and Plant Sciences, Tapton Experimental Gardens, University of Sheffield, Sheffield S10 5BR, UK. Tel.: ; fax: Copyright 2000 Royal Meteorological Society

2 330 S.E. LEE ET AL. There have been a small number of studies undertaken on the regional effects of climate change in the high northern latitudes. These studies have shown that these areas are the most sensitive to an increase in temperature (Hansen et al., 1988; Mitchell et al., 1990) compared with the rest of the globe. By the year 2100, temperatures in such latitudes are forecast to have risen in summer by between 2 and 4 C, and in winter by between 1 and 5 C (Cattle and Crossley, 1995). Briffa et al. (1990) estimated from global and regional studies by Wigley (1989) and Santer and Wigley (1990) that mean Fennoscandian summer temperatures would increase by C by the year There tends to be few such predictions for specific boreal regions due to problems with forecasting the movement and behaviour of sea ice, which can lead to inaccuracies. Recently, Bengtsson (1997) presented results from a high resolution transient climate change experiment carried out at the Max Planck Institute for Meteorology, Hamburg. The results showed a small warming up to the present day in general agreement with observations. This warming pattern showed a strong peak in the Arctic associated with a noticeable reduction in Arctic sea ice. The overall warming for the period over the Scandinavian area was 1 2 C higher than the global average superimposed upon a similar high interannual variability as in the present climate. Overall global warming came to around 3.5 C for this period. At the time of greenhouse gas doubling ( ), the global warming amounted to 1.9 C. Recent GCM results for Finland presented by the Finnish Research Programme on Climate Change (SILMU) suggest a mean annual warming of 2.4 C by 2050 and 4.4 C by 2100 (central best-guess scenario). This is one and a half times greater than the average global warming expected over the same period. Warming is also expected to be greater in winter than summer. In addition to these increases in temperature, there is agreement that the amount and distribution of precipitation is changing with some areas receiving less than in the past and some more. The predictions from the IPCC (IS92a scenario) suggest a general global increase of 10% in precipitation by the middle of the next century. However, as with the temperature, there is likely to be considerable seasonal and regional variations in these predictions. If winter precipitation increases in the far North, as predicted by Warrick and Oelremans (1990) and Miller and Vernal (1992), this will lead to greater snowfall. This will, in turn, increase the likelihood of more flood water in the spring months when the snow melts. The SILMU central scenario for annual precipitation is an increase of 1% per decade (2% per decade in winter and 0.5% per decade in summer). There has been considerable debate as to whether climate warming is occurring in the northern high latitudes or whether the climate is just recovering after the last ice age (Kullman, 1994). For instance, it is well known that, in Scandinavia, there was a particularly warm period from the 1920s through to the 1940s and since the early 1960s there has been little change or a cooling (Jones and Briffa, 1992; Maxwell, 1997), although temperatures do now appear to be rising again. The major trend has been that of cooling after the warm spell experienced between the 1920s and 1940s. This has meant that there has been a difference between this region and the general northern hemispheric trend for the last 100 years. There are also climatic variations in the northern circumpolar region influenced by regional weather systems, local ocean currents and the degree of continentality. Chapman and Walsh (1993) showed that warming is strongest over northern land areas during the winter and spring. They also showed from an analysis of anomalies of sea ice coverage over the period , that there is considerable regional variability in long-term trends over 10-year time scales. Finland has a much warmer climate than other countries at a similar latitude due to the warming influence of the Atlantic Gulf Stream. Much work has been undertaken recently on the North Atlantic Oscillation (NAO) (Hurrell, 1995; Hurrell and van Loon, 1997; McCartney, 1997). This oscillation is a large-scale alternation of atmospheric airmass between the North Atlantic regions of subtropical high surface pressure (centred near the Azores) and subpolar low surface pressure (extending south and east of Greenland) (Lamb and Peppler, 1987). During high NAO winters, anomalously northerly flow occurs across western Greenland and enhanced moisture flux convergence occurs from Iceland through to Scandinavia, which gives warmer and wetter winters than normal (Hurrell, 1995). It is interesting to note that, over the last 30 years, there has been a reversal from the weak meridional pressure gradient of the 1960s to the strongly positive index values since 1980 (Hurrell, 1996).

3 CLIMATE VARIATIONS IN LAPLAND, NORTHERN FINLAND 331 Briffa et al. (1990) used tree ring records to reconstruct the summer temperature record for Fennoscandia over the last 1400 years and were unable to detect any significant recent warming in the region. They estimated that no significant greenhouse warming signal would be detected before 2020 at the earliest. More recent work by Timonen (1998) with timberline Scots Pine in northern Finland has shown that the period was the warmest of the millennium, although there has been a colder period between 1960 and 1990, which has been mostly unfavourable for the growth of pine. Some growth did, however, occur in the warm years of 1973, 1979, 1982, 1983 and This recent climate research has highlighted the need for more information on regional and local effects of climate change, especially in sensitive northern areas. Such areas are the habitat for plant species adapted to survive in the harsh cold environment often with severe water limitations and are at the northern limit of their range. Plant ecologists are particularly interested in studying how such plant species would respond to a change in climate in order to assess the impact of such climate changes on plant communities and their biodiversity both at the local level and regionally. Press et al. (1998) highlight a number of factors responsible for the existence of particular plants and their distribution within arctic ecosystems. These factors include low air and soil temperatures, persistent snow cover for at least half the year, low soil nutrient availability, permafrost either at or close to the surface, and low soil moisture. Any change in the climate may significantly affect the operation of these ecosystems and the distribution of species within them as well as the growth of the plants. Competitive relationships between species are also likely to be fundamentally altered. It is clear that there is a requirement for further studies to analyse the climate variability at different sites and to determine the level of variance in the sensitivity of the arctic and subarctic ecosystems to environmental change at these locations. In addition to the effects on the regional climate and ecosystems, a change in climate will also affect local people and their livelihood. In Lapland, the local indigenous people, the Saami, have strong links with the natural environment, both through their reindeer herding and through their dependence on berries and mushrooms to supplement their diet. Reindeer numbers in this region are controlled by Saami management practices, such as slaughtering and castration, but even so, it has been found that the number of live reindeer calves still retain a link with the local weather conditions. For example, the number of live calves tend to increase if the autumn prior to their birth is warm, but decrease if the previous winter is warm and wet. There is also particular concern about the effect of a changing climate on the distribution of lichens, the main food source for the reindeer. A combined ecological/social anthropological study was undertaken in Lapland during the period to determine the changes in climate that have occurred in this particular region over the last 100 years, both from a scientific viewpoint, using official meteorological measurements, and from the Saami viewpoint. This part of Lapland consists of fells intersected by rivers and lakes, the largest of which is Lake Inari. The topography ranges from 591 m for the highest peaks of the Muotkatunturi fell areas to m for the lower levels of the river valleys and lakes. Two large rivers, the Vaskojoki and the Lemmenjoki, run through Lake Paadar (Juutuankoki) and then east to Lake Inari and Inarijoki. The Kaarasjoki river flows through Karasjok to become the Teno river, which flows along part of the northwestern border of Finland and Norway and north into the Barents Sea. The vegetation consists mostly of birch and pine forests, with bogs in places, and tundra on the highest fells. There is also some spruce in the south of the area. The valleys tend to be colder than the fells in winter due to cold air drainage and the lakes tend to delay freeze-up in winter and the thaw in spring. This paper attempts to assess whether there is any evidence of a change in climate in this region over the last 100 years. It focuses on the meteorological data collected for Lapland both from local meteorological stations and from the NOAA for a 5 latitude by 5 longitude grid, which includes this area. There are three main aims: (i) to analyse the climate data for the last 100 years to assess the changes in temperature and precipitation that have occurred in Lapland, northern Finland.

4 332 S.E. LEE ET AL. (ii) to compare the temperature and precipitation from the NOAA grid square with the local temperature and precipitation recorded at the local meteorological stations. (iii) to analyse whether the more recent changes in the temperature and precipitation data are comparable with or greater than changes that occurred in the first half of the century. This would provide some indication as to whether there had been any change in climatic trends. 2. METHODS 2.1. Climate datasets Two climate datasets, the global station dataset and the global gridded dataset for mean monthly temperature and precipitation anomalies, were used in this study and extracted from the Global Historical Climate Network (GHCN) (Vose et al., 1992) produced by the Global Climate Laboratory of the National Climatic Data Center (NCDC/GCL) in Asheville, NC, USA, which are available on the world wide web. This climate dataset was created from 15 source datasets and has been quality controlled (Eischeid et al., 1995). Anomaly data from a common reference period ( ) were used to avoid problems arising from the use of absolute values of mean temperature or precipitation. The application of such data from meteorological stations can be misleading if the stations are at different altitudes or are close to each other and there may be slightly differing methods used to calculate the mean values of temperature or precipitation. Such problems are prevented by the use of anomaly data, but this means that mean temperatures and precipitation are only calculated in relative and not absolute terms. The meteorological station data are referenced by the World Meteorological Office (WMO) station number, country, latitude and longitude and contain mean monthly temperature anomalies and monthly precipitation anomalies for each year recorded. These anomalies are deviations from the mean temperature and mean precipitation calculated for each site. For the gridded data, the anomalies have been derived from the mean and are mapped on a 5 latitude by 5 longitude global grid. The gridded and station datasets cover the time period and are subdivided into seasonal and monthly data. The seasons fall into four categories of winter (December, January and February), spring (March, April and May), summer (June, July and August) and autumn (September, October and November). These seasonal data have been derived from the monthly data, so, for example, winter temperatures for 1987 would be derived from adding together the monthly temperature anomalies for December 1986, January 1987 and February 1987 and dividing by 3 to obtain a mean winter temperature anomaly for The monthly precipitation anomaly data are not averaged but are totalled for each season Climate data for Lapland, northern Finland The stations for which temperature and precipitation anomaly data were extracted are shown in Table I. Except for Sodankylä, all these stations fall within the region encompassed by the grid square coordinates. However, Sodankylä was included to extend the climate record. To ascertain whether the gridded temperature anomaly data were typical relative to the anomalies recorded at the meteorological stations in the area, a regression analysis was performed. This compared the station temperature data with the gridded data for the same period. In addition to this, the stations were compared with each other. The aim of this exercise was to derive a continuous temperature record for the whole of the period The meteorological stations closest to where the Saami people live (Ivalo, Kevo and Karasjok) do not have a complete temperature record from 1876 to 1993, so a regression with Sodankylä temperature data for each of the four seasons was performed to fill in the gaps in the record. This procedure was repeated with the precipitation data.

5 CLIMATE VARIATIONS IN LAPLAND, NORTHERN FINLAND 333 Table I. Meteorological stations used in the temperature and precipitation analysis for the study area of northern Finland Station name Latitude, longitude Elevation Years recorded (m) (temperature; precipitation) Ivalo, Finland N, E (both) Karasjok, Norway N, E , Kevo, Finland N, E (temperature only) Sodankylä, Finland N, E , Temperature and precipitation data for a 5 by 5 grid were then extracted from the global gridded data. The grid selected was as close as possible to the study area in Lapland, northern Finland (68 69 N and E). At the time of writing, data were only available for the period for this particular grid square. The selected 5 by 5 grid cell for Finland is centred on 70 N and 25 E, which means that the area covered by this cell ranges from 67.5 to 72.5 N and from 22.5 to 27.5 E. A regression analysis was performed between the site data and the gridded data. The anomaly data for each season and the annual anomaly data for each year from the Lapland site were correlated with the anomaly data from the Lapland grid to determine the strength of the relationship between the two sets of data for both temperature and the precipitation. In addition, both the temperature and precipitation anomalies were plotted for the Lapland grid for the period for each season and annually. The annual and seasonal data were analysed to determine whether there was any evidence of linear trends in temperature and precipitation during the period The 20th century was selected as the individual yearly estimates are more reliable in the this century compared with those from the 19th century (Jones and Briffa, 1992). In addition, trend lines were produced for these same data for two time periods, and , to determine whether there was any difference in the trends between the first half of the century and the latter half (up to 1990). Finally, a further statistical analysis was carried out for this period. Jones and Kelly (1983) noted that annually averaged data can mask changes in the magnitude and timing of variations that occur in different months. In order to determine whether there had been any change between the monthly temperatures and their relationship with the annual temperature, the data were again divided into the two time periods, and , and the correlations between the individual monthly series and the annual time series were examined. This was repeated with the precipitation data. 3. RESULTS 3.1. Local site temperature analysis In order to determine the relationship between the local meteorological stations in Lapland, a number of regression analyses were performed. First of all the three stations closest to the Saami people were compared for the years with available temperature data. It was found that Ivalo was warmer than both Karasjok and Kevo, with a mean annual temperature anomaly between Ivalo and Karasjok of +0.8 C and between Ivalo and Kevo of +0.6 C. Both Karasjok and Kevo are in steep-sided river valleys and hence tend to experience slightly lower winter temperatures than Ivalo due to cold air drainage off the fells. The Karasjok annual data and the data for each of the four seasons were then compared with those from a longer time period to establish whether the same trends were evident in the data. The station data from Sodankylä were used for this purpose for the period The temperature data from Karasjok cover the period from 1876 to 1970, and those from Sodankylä from 1908 to The results

6 334 S.E. LEE ET AL. of the regression analysis for the period showed that the spring temperature anomalies exhibited the highest regression values between the two sites (r=0.945), followed by the annual data (r=0.934). The equations from this regression were then used to predict the annual and seasonal temperature anomalies for Karasjok for the period , which had no data. The monthly data from Karasjok were divided into four seasons and the correlation between each season and the northern Finland gridded temperature data was calculated. The excellent correlation found for all seasons was a reflection of the fact that there are very few meteorological stations within the 5 by 5 grid for this region of Finland, so that Karasjok strongly influences the temperature data within this particular cell. The annual data showed the closest relationship (r=0.984) followed by the spring temperatures (r=0.978) Local site precipitation analysis The two stations closest to the Saami people were compared for the years with available precipitation data. It was found that Karasjok was wetter than Ivalo with an mean annual precipitation anomaly between Karasjok and Ivalo of 79 mm for the years The Karasjok data were then compared with those from Sodankylä as with the temperature data for the period The precipitation data from Karasjok cover the period from 1876 to 1970, and those from Sodankylä from 1907 to The equations derived from the results of the regression analysis were used to predict the annual and seasonal precipitation anomalies for Karasjok for the period , which had no data. The precipitation equations had lower values of the correlation coefficient, r, than those for temperature reflecting greater variability between the precipitation data at Karasjok and Sodankylä compared with the temperature data. However, the r value was still significant ( 0.1). The annual data had the highest correlation coefficient (r=0.617) followed by the summer data (r=0.533). The monthly precipitation data from Karasjok were divided into four seasons and the correlation between each season and the northern Finland gridded precipitation data was calculated. Again, the regression value was lower for all seasons compared with the temperature data but was still significant ( 0.1). The correlation coefficient between the summer precipitation data from Karasjok and the northern Finland gridded precipitation data was particularly strong (r=0.762). It would appear, therefore, that Karasjok also strongly influences the precipitation, particularly in summer, as well as the temperature data within this particular 5 by 5 cell Northern Finland temperature analysis Having examined the link between Karasjok and the northern Finland grid cell temperature and precipitation data, attention may now be focused on the time series of mean seasonal and annual temperature anomalies. These time series show how the temperature anomalies have varied over the period for northern Finland (Figures 1 and 2). It is evident from Figures 1 and 2 that there is no discernible warming trend between 1880 and 1993 for the annual series, although a warm period is very evident during the 1930s, with temperatures up to 3.2 C above the mean value. A number of colder periods can also be identified from Figure 1. For instance, the first decade of the 20th century, the late 1960s and 1970s and much of the 1980s. Since the late 1980s, there has been a gradual warming with the positive temperature anomalies increasing. It is interesting to note that this annual pattern in temperature is also consistent with that for all the arctic land areas over a similar time period as shown by Farmer (1989) (cited in Kullman, 1992). A similar pattern to the annual trend emerges with the winter temperature anomalies. Exceptionally warm winters occurred in the 1930s when anomalies were up to 6 C greater than the mean value. Comparable anomalies have also occurred in the 1990s. There was also a brief warm period between 1905 and In the case of the summer anomalies, some very warm summers occurred in the 1920s and 1930s, with anomalies up to almost 4 C but such anomalies have not occurred in the recent

7 CLIMATE VARIATIONS IN LAPLAND, NORTHERN FINLAND 335 Figure 1. Northern Finland surface air temperatures by season (winter and summer) and year, Data are expressed as C anomalies from 1951 to Winters are dated by the year in which January occurs. The smooth curves were obtained by using a 10-year Gaussian filter. Note the different scales summers of the 1990s, which have exhibited a slight cooling (around 0.5 C). Prior to 1915 there were a number of cool summers, with anomalies falling around 2 C below the mean value. The spring anomalies show that, prior to 1900, spring tended to be rather cold, with anomalies of up to 5 C below the mean value. There was also a cold spell between 1915 and 1918, but this was preceded by a warm spell between 1904 and 1908 and followed by a warm spell in the early 1920s. Since then there has continued to be a mixture of warm and cold springs with no evident trend. However, as with the annual anomalies, a slight warming trend can be identified for the 1990s. Prior to 1930, autumns tended to be rather cold, with anomalies of up to 4 C below the mean value. The 1930s to the late 1960s tended to be warm, but since the early 1970s autumns that have been cooler (1 or 2 C) than the mean value have occurred. In the 1990s there has been a noticeable autumnal cooling (around 2 C below the mean value). The results of a linear trend analysis for the annual and seasonal temperature data for the first half of the 20th century are shown in Table II. Although there was a slight positive trend during the period , for all seasons and annually, which suggests a warming, none of these trends was significant. However, during the period (see Table II) there was a significant annual warming trend (r=0.344, 0.05). There was also a

8 336 S.E. LEE ET AL. Figure 2. Northern Finland surface air temperatures by season (spring and autumn) and year, Data are expressed as C anomalies from 1951 to The smooth curves were obtained by using a 10-year Gaussian filter. Note the different scales significant summer warming (r=0.381, 0.05) and also a warming in autumn (r=0.287, 0.1). The linear trend for the winter and spring seasons was insignificant between 1901 and 1945 due to the warm spell in the period During the period , the annual temperature and all the seasons, except spring, exhibited a cooling trend. However, none of these trends were found to be significant. Table II. Results of a linear trend analysis of the Finland temperature data for the period [df=43 (n 2)] for the annual and seasonal data Season Regression equation r Significance Spring y=0.004x NS Summer y=0.0347x * Autumn y=0.0312x p 0.1 Winter y=0.0478x NS Annual y=0.0279x * n, number of years; NS, not significant. * p 0.05.

9 CLIMATE VARIATIONS IN LAPLAND, NORTHERN FINLAND 337 A further statistical analysis was carried out to determine whether there had been a change in the relationship between monthly temperatures and the annual temperature between the first half and the latter half on the 20th century. Figures 1 and 2 show that there was an overall warming from the start of the century until 1940 in all seasons except spring, which showed little overall variation in temperature over this period. Since then, until the late 1980s, there has been a general cooling. Analysing the net temperature change between these two periods provides an indication as to the nature of this change in terms of monthly temperature variations. In addition, the correlations between the annual and monthly data upon which these annual data are based were examined. The results are shown in Table III (see next page). Table III shows a net cooling between the two periods and , with a decrease in the annual difference of 0.26 C. It also shows the changes that occur between the mean temperature anomalies of the period and the period. The greatest overall cooling between these two periods ( T) occurred in the winter months, e.g. January ( 1.09 C). The standard deviation (S.D.) of the monthly values is also greatest for the winter months, as well as March and November. There was some warming in the months of April (0.16 C), May (0.21 C), June (0.16 C) and August (0.06 C), with the greatest warming occurring in October (0.27 C). The S.D. for these months of warming is lower than the value for the winter months, with the lowest value of 1.21 in August. Relative to the appropriate monthly deviation, the cooling in winter dominates, December ( 21 C), January ( 30 C) and February ( 25 C), although the month of July ( 25 C) is also high. If the two periods are considered separately it can be seen that warming has occurred in both periods for the months of May, June, July, August and November, although it has decreased in July and November for the second period ( ). September, October and April were all cooling in the first period ( ), but April and October appear to be getting warmer in the second period. All the winter months, and March, were warming in the first period but have been cooling in the second period. Comparing the variability in monthly temperatures, as represented by the S.D.s, it can be seen that there has been a greater annual variability in the latter time period ( =1.20) than the former period ( =1.06). The months of February (+1.23), March (+0.52) and December (+0.39) exhibit the greatest increase in variability but increases have also occurred in April ( +0.16), May ( +0.02), June ( +0.17), August ( +0.12) and September ( +0.02). This is consistent with the finding of Hurrell (1995), who noted that decadal variability in the NAO has become especially pronounced since about Decreases have occurred in January ( 0.15), July ( 0.25), October ( 0.09) and November ( 0.13). Table IV shows the correlations between the monthly anomalies and the annual anomaly for the period As was stated by Jones and Kelly (1983) significance testing is not appropriate for such coefficients in this type of analysis as all data are a subset of the same database. For the whole period between 1901 and 1990, the greatest correlation of 0.59 between the monthly and annual temperature data occurred in the month of March. During the period , the greatest correlation of 0.55 occurred in February and 0.53 in December. For the latter period, , the highest correlation of 0.68 occurred in the month of March. The winter months of December, January and February also had relatively high correlations compared with the other months (0.54, 0.50 and 0.60, respectively) together with April (0.50). Table IV. Correlation coefficients (r) between monthly (x) and annual temperature anomalies (y) for three different time periods ( ; and ) Period r Months Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

10 338 S.E. LEE ET AL. Table III. Temperature differences, mean value minus mean value Year Months Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec T ( C) ( ) T ( C)/ ( )% Mean T ( C) ( ) ( ) Mean T ( C)/ ( )% Mean T ( C) ( ) ( ) Mean T ( C)/ ( )%

11 CLIMATE VARIATIONS IN LAPLAND, NORTHERN FINLAND 339 It would appear from this analysis that the month of March together with the winter months consistently influence the annual temperature in Lapland. It is also interesting to note that the winter months, along with March, April and August have exhibited increasing correlation coefficients over the latter half of the century, while May, June, July and the autumn months have shown decreasing correlation coefficients. The greatest increase occurred in March ( +0.20) and the greatest decreases in July and September ( 0.21). Over the whole period, , warming has been occurring in the months of April, May, June, August and October (see Table III). These results show that although warming has occurred in some months, there has been a greater cooling for the period This cooling has occurred in months that have high correlation coefficients with the annual temperature, relative to the other months, hence there is an overall cooling effect in Lapland for the period Furthermore, due to the increasing correlation coefficients in March and April for the latter half of the century, there appears to be a shift from the previous influence of the winter months on the annual temperatures to the spring months. However, the winter months together continue to exhibit the greatest variability so they will continue to exert the most influence on the annual temperatures into the foreseeable future. This is perhaps not surprising as winter is the time when the temperature gradient between low and high latitudes is at its greatest, intensifying the hemispheric air circulation (Barry and Chorley, 1976). Also, the transport of heat by the Gulf Stream into high latitudes is most significant in winter when continental land temperatures are low Northern Finland precipitation analysis The time series of mean seasonal and annual precipitation anomalies are shown in Figures 3 and 4. It is clear from Figures 3 and 4 that the annual precipitation anomaly has become increasingly positive since the 1930s and that these positive anomalies reached 300 mm in the 1970s and 1980s. Figure 3 shows that the winter anomaly pattern is similar to the annual pattern. Again some large positive anomalies occurred in the 1970s and 1980s reaching a maximum of 130 mm. During the 1990s, the anomalies have been positive and similar to those of the 1970s. The summer anomalies display a slightly different pattern. During the 1980s, the anomalies decreased and became negative by the end of the decade. The anomalies were also negative (down to 70 mm) in the period The anomalies were, however, relatively high in the late 1800s (up to 70 mm) and the 1960s, with an extremely wet summer in 1975 (210 mm). The spring anomalies exhibit a general increase over the whole period, although the range of anomalies is relatively small ( 30 to +70 mm) compared with the others seasons. In the 1970s and 1990s the anomalies reached 70 mm. The autumn anomalies remained fairly static with a balance between wet and dry years until the 1960s. Since then, the anomalies were high in the 1970s and 1980s when they reached 115 mm. They have, however, decreased in the 1990s. The results of a linear trend analysis for the seasonal and annual precipitation data for the period are shown in Table V. This table shows that there is a positive linear trend for all seasons and on an annual basis, which suggests that precipitation has increased during the period This was significant for all seasons except summer, particularly spring and winter, as well as annually. The summer trend is not significant due to the particularly wet period towards the end of the 19th century, with similar Table V. Results of a linear trend analysis of the Finland precipitation data for the period [df=113 (n 2)] for the annual and seasonal data Season Regression equation r Significance Spring y=0.3671x *** Summer y=0.2256x NS Autumn y=0.3122x *** Winter y=0.3202x *** Annual y=1.2484x *** n, number of years; NS, means not significant. *** p

12 340 S.E. LEE ET AL. precipitation anomalies to those in the 1960s. There was also no significant linear trends for any of the seasons in either of the two time periods. In fact, the summer trend was negative (i.e. it was becoming drier) for both these periods, although this was not significant. There was also an insignificant drying trend for autumn in the first period. To determine whether there had been a change in the relationship between monthly precipitation and the annual precipitation between the first half and the latter half on the 20th century, a further statistical analysis was undertaken. The same technique was applied as with the temperature data. By analysing the net precipitation change between these two periods this would provide an indication as to the nature of this change in terms of monthly precipitation variations. In addition, the correlations between the annual and monthly data upon which these annual data were based were examined. The results are shown in Table VI. The table shows the net increase in precipitation between the two periods and , with an increase in the mean annual monthly difference of 3.37 mm. The greatest monthly increase of 6.03 mm occurred in September and the lowest in November (1.99 mm). The greatest variability occurred in the summer months ( =29.38 in July) and the least in March ( =9.23) and winter ( =9.32 in January). The greatest changes in the precipitation between the two periods relative to the S.D. occurred in March ( P/ =34%) and April ( P/ =37%). The second period Figure 3. Northern Finland precipitation by season (winter and summer) and year, Data are expressed as mm anomalies from 1951 to Winters are dated by the year in which January occurs. The smooth curves were obtained by using a 10-year Gaussian filter. Note the different scales

13 CLIMATE VARIATIONS IN LAPLAND, NORTHERN FINLAND 341 Table VI. Precipitation differences, mean value minus mean value Year Months Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec P (mm) ( ) P (mm)/ ( )% Mean P mm ( ) ( ) Mean P (mm)/ ( )% Mean P (mm) ( ) ( ) Mean P (mm)/ ( )%

14 342 S.E. LEE ET AL. Figure 4. Northern Finland precipitation by season (spring and autumn) and year, Data are expressed as mm anomalies from 1951 to The smooth curves were obtained by using a 10-year Gaussian filter. Note the different scales ( ) exhibits higher mean monthly precipitation anomalies with greater S.D.s than the earlier period ( ). The highest mean monthly anomalies in this period occurred in June (7.34 mm), July (7.67 mm) and September (7.71 mm), and the greatest S.D.s in July ( =31.41), August ( =29.96) and September ( =22.39). There are no monthly decreases in precipitation in this period. The greatest changes in precipitation relative to the S.D. in the second period occur in March ( P/ =42%), April ( P/ =55%) and December ( P/ =51%). In the period , February, March and September have the greatest mean anomalies relative to the S.D., but these are lower than those for the second period ( P/ =24% for March). The greatest S.D.s occur in July ( =26.63), August ( =22.66), and September ( =21.20). The greatest mean monthly increase of 4.36 mm is in September and the greatest decrease of 2.18 mm in July. Decreases also occur in October ( 0.66 mm) and December ( 0.18 mm). It appears that the period was wetter than the period with greater variability particularly in the summer months. The month of March exhibits high variability in mean precipitation relative to the S.D. for both periods (24 and 42%), but April has the greatest figure in the period (55%). The greatest overall mean increase in monthly precipitation over the whole period ( ) occurs in the summer months (11.04 mm) and the lowest increase in winter (7.95 mm).

15 CLIMATE VARIATIONS IN LAPLAND, NORTHERN FINLAND 343 Table VII. Correlation coefficients (r) between monthly and annual precipitation anomalies ( ) for three different time periods ( ; and ) Period r Months Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Spring and autumn show a similar increase (10.7 mm) over this period. The mean precipitation relative to the S.D. is greater for the spring months than for the other seasons, particularly in the first period, although the winter precipitation has increased in influence over the second period. Table VII shows the correlations between the monthly precipitation anomalies and the annual precipitation anomaly for the period From Figures 3 and 4, it can be seen that there has been a general increase in precipitation from the start of the century until 1980 in all seasons, although there has been a decrease during the 1980s and 1990s. The precipitation data were again analysed in the same manner as the temperature data to determine the net change in precipitation between the two periods and The results are shown in Table VII (see next page). For the whole period between 1901 and 1990, the highest correlation between the monthly and annual data occurred in July (0.63). There were also high correlations in the other summer months of June (0.45) and August (0.51) as well as the winter months (r=0.53 for January). During the period , the greatest correlations occurred in July (0.57) and in August (0.59). For the latter period, , the highest correlation again occurred in July (0.67). Apart from September in the second period, the spring and autumn months had relatively low correlations ( 0.41) for both periods. It would appear that the summer months of June, July and August regularly influence the annual precipitation in Lapland. These summer months have the highest rainfall during the year compared with the other seasons. The greatest increases have occurred in March ( +0.33) and September ( +0.33), the greatest decreases in October ( 0.22). Over the whole period, , all the months have been getting wetter (see Table V) although July, October and December exhibited some drying between 1901 and Summer has been shown to be the wettest season, with the greatest variability in precipitation during the period (note, though, that it was the driest season during the period ) and contributes most to the annual data. The correlation coefficient for July has increased between the two periods and now exceeds that for August. Although July is the most influential month on annual precipitation, the correlation coefficients for January ( +0.25), February ( +0.27) and September ( +0.33) have increased markedly between and This may be attributable to their increasing precipitation anomalies and monthly variability. This latter period has also been a time of high decadal variability in the NAO, with above average winter rainfall. 4. CONCLUSIONS The climate in Lapland, northern Finland, over the last 100 years has been analysed and changes in temperature and precipitation have been assessed. Recent changes in these data have been compared with those that occurred in the first half of the century. In addition, the climate data from the NOAA grid square covering the region have been compared with the temperature and precipitation recorded at the local meteorological stations closest to where the Saami people live. It has been demonstrated that the local climate experienced by the Saami people is also represented at a smaller scale (large grids) by the NOAA climate data.

16 344 S.E. LEE ET AL. The following conclusions may be drawn from the climate data for northern Finland: (i) There has been no significant warming or cooling during the entire period for the annual data and the seasonal temperature data. (ii) There has been no significant warming or cooling for the period for the annual data and the seasonal temperature data. (iii) However, a significant annual warming (r=0.344, 0.05) has occurred in the period , together with a significant summer warming (r=0.381, 0.05). The mean annual increase in temperature anomalies was 0.27 C with a 25% increase in mean temperature anomaly in relation to the monthly S.D. The mean summer increase in temperature anomaly over this period was 0.35 C, with July exhibiting the greatest percentage increase (29%) in mean temperature anomaly in relation to the monthly S.D. (iv) Exceptionally warm winters occurred in the 1930s when anomalies were up to 6 C greater than the mean value. Comparable anomalies have also occurred in the 1990s. (v) Monthly temperatures in March and the winter months of December, January and February are the main influences on the annual temperature in Lapland. These months have also shown increasing influence over the latter half of the century. The greatest mean annual monthly temperature anomaly increase for the period was in January ( C) with a mean anomaly increase for all the winter months of C. (vi) The degree of temperature variation in the winter month anomalies ( =4.18 C in December for the period ) is greater than the summer month anomalies ( =1.21 C in August) for the period ). (vii) The monthly temperature variation has risen from 3.98 C for December in the period to 4.37 C in the period , and from 3.33 C for February in the period to 4.56 C in the period (viii) There has been a significant increase in annual precipitation for the whole period from 1879 to (ix) With the exception of summer, there has also been a significant increase in precipitation for the winter, spring and autumn seasons from 1879 to (x) There are no significant increases or decreases in precipitation for the annual or seasonal data in the two periods, and (xi) The period was wetter than with greater variability particularly in the summer months. (xii) During the period , the summer months of June, July and August are the wettest months with the greatest variability in precipitation. They contribute most to the annual precipitation in Lapland. July is the most influential month on annual precipitation. It is clear that there have been changes in the Lapland climate over the last 100 years. Warming has occurred consistently in May and June over this period and there appears to be a current (i.e. post 1990) annual warming trend mostly due to winter warming. There was also significant summer warming between 1901 and This falls within a period of positive summer temperature anomalies from 1915 and is consistent with the findings of the Finnish Forest Research Institute (Metla). Timonen (1998) presented data from Metla that showed how the growth of Scots Pine in Finland was related to the summer temperatures for the last 1000 years. In general, the warmer the months of June and July then the greater the growth of the timberline pine. From the Metla data it was clear that the period could be considered as one of the warmest of the millennium. The previous period exhibiting comparable warmth was between (Timonen, 1998). Furthermore, it appears that there is greater variability in the winter temperature anomalies for the latter half of the century than the first 45 years, which may be attributable to an increase in the decadal variability of the NAO index (Hurrell, 1995). Precipitation has increased significantly over the period of study and continues to rise. Summer precipitation has had the greatest influence on the annual data over this period although the winter months have only a slightly lower correlation coefficient. The spring months show a large rise in