Projections for near-surface soil moisture content in Europe for the 21st century were derived from simulations performed with 26 CMIP5 global climate models (GCMs). Two Representative Concentration Pathways, RCP4.5 and RCP8.5, were considered. Unlike in previous research in general, projections were calculated separately for all four calendar seasons. To make the moisture contents simulated by the various GCMs commensurate, the moisture data were normalized by the corresponding local maxima found in the output of each individual GCM. A majority of the GCMs proved to perform satisfactorily in simulating the geographical distribution of recent soil moisture in the warm season, the spatial correlation with an satellitederived estimate varying between 0.4-0.8. In southern Europe, long-term mean soil moisture is projected to decline substantially in all seasons. In summer and autumn, pronounced soil drying also afflicts western and central Europe. In northern Europe, drying mainly occurs in spring, in correspondence with an earlier melt of snow and soil frost. The spatial pattern of drying is qualitatively similar for both RCP scenarios, but weaker in magnitude under RCP4.5. In general, those GCMs that simulate the largest decreases in precipitation and increases in temperature and solar radiation tend to produce the most severe soil drying. Concurrently with the reduction of time-mean soil moisture, episodes with an anomalously low soil moisture, occurring once in 10 years in the recent past simulations, become far more common. In southern Europe by the late 21st century under RCP8.5, such events would be experienced about every second year.

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Abstract.Values of the scavenging coefficient determined from observations of ultrafine particles (with diameters in the range 10-510 nm) during rain events at a boreal forest site in Southern Finland between 1996 and 2001 were reported by Laakso et al. (2003a). The estimated range of the median values of the scavenging coefficient was [7×10 −6 −4×10 −5 ] s −1 , which is generally higher than model calculations based only on below-cloud processes (Brownian diffusion, interception, and typical phoretic and charge effects).In the present study, in order to interpret these observed data on scavenging coefficients from Laakso et al. (2003a), we use a model that includes below-cloud scavenging processes, mixing of ultrafine particles from the boundary layer (BL) into cloud, followed by cloud condensation nuclei activation and in-cloud removal by rainfall. The range of effective scavenging coefficient predicted by the new model, corresponding to wide ranges of values of its input parameters, are compared with observations. Results show that ultrafine particle removal by rain depends on aerosol size, rainfall intensity, mixing processes between BL and cloud elements, in-cloud scavenged fraction, in-cloud collection efficiency, and in-cloud coagulation with cloud droplets.The scavenging coefficients predicted by the new model are found to be significantly sensitive to the choice of representation of: (1) mixing processes; (2) raindrop size distribution; (3) phoretic effects in aerosol-raindrop collisions; and (4) cloud droplet activation. Implications for future studies of BL ultrafine particles scavenging are discussed.

ABSTRACT:The annual and seasonal mean temperature of Finland was calculated for 162 years based on spatially interpolated monthly mean temperature records. The spatial interpolation method, known as kriging, was used with the following forcing parameters: the geographical coordinates, elevation of the terrain, and percentage share of lakes and sea. Homogenised data was used, and thus the most important factor affecting the accuracy of the interpolated data was the uneven distribution of the available observation stations both in time and space. The uncertainty due to the homogenisation adjustments made earlier was notably smaller. In the mid-1800s, the uncertainty in the annual and seasonal mean temperatures was large, with a maximum in winter of over ±2.0°C, but the accuracy improved quickly with time as the number of the observation stations increased. At the beginning of the 20th century, the uncertainty related to the limited station network was less than ±0.2°C, in winter less than ±0.4°C. According to the data, the rise in Finland's annual mean temperature has been statistically significant during the last 100, 50 and 30 years. During the last 100 years the increase in the mean temperature was largest during spring, but during the last 50 years winters have warmed up the most. The temperature time series obtained are compatible with grid point values picked from the global temperature data grids starting from the 1880s, though the global data sets tend to smooth the extremes.

This study was aimed at assessing the potential impacts of climate change on the depth and duration of soil frost under snow cover in forests growing at different geographical locations in Finland. Frost simulations using a process-based forest ecosystem model (FinnFor) were made for Scots pine Pinus sylvestris L. stands (height 17 m, stand density 1100 stems ha -1 ) growing on a moraine sandy soil. The climate change forecast used in the computations was based on the global ocean-atmosphere general circulation model HadCM2 that was dynamically downscaled to the regional level. The simulated climate warming during the winter months was about 4 to 5°C by the end of the 21st century. Frost simulations showed that the length of the soil frost period would lessen all over the country. Though winters will be warmer, the associated decrease in snow cover in southern Finland will increase the probability of frozen ground there in the middle of winter compared with the current climate. In central and northern Finland there will be so much snow, even in the future, that the maximum annual soil frost depth will decrease there.KEY WORDS: Climate change · Soil frost · Soil freezing · Snow cover · Hydraulic frost model · Scots pine Resale or republication not permitted without written consent of the publisherClim Res 17: [63][64][65][66][67][68][69][70][71][72] 2001 The modelling of frost in the soil profile under snowfree surfaces can be done with the help of the frost sum and soil properties (e.g. Saarelainen 1992, McCormick 1993, Venäläinen et al. 2001. The frost sum is the sum of below-0°C daily mean temperatures calculated from the beginning of the frost period. In Scandinavia the frost period typically starts in October and ends in May, in northern Lapland in June. If there is snow on the ground, the modelling of soil temperature becomes more complex. Models must include many variables describing both meteorological conditions, such as air temperature, short and long wave radiation, amount and type of snow, and soil characteristics, such as thermal conductivity and soil heat capacity (e.g. Bonan 1991, Cox et al. 1999. The influence of snow cover on temperature is illustrated in Fig. 1. The daily variation of air temperature in the case of late winter conditions can be more than 20°C, whereas at a depth of 80 cm below the snow surface the daily cycle is practically negligible.Jansson (1991) introduced a comprehensive soil model known as SOIL that includes the processes relevant for the calculation of soil temperature. Kellomäki & Väi-sänen (1997) have integrated this SOIL model into a process-based forest ecosystem model (FinnFor), which links ecosystem dynamics with climate through selected physiological processes. Peltola et al. (1999) used this model when they studied the consequences of climate warming on soil frost and on the windthrow risk for trees in different geographical locations in Finland. Peltola et al. (1999) used 2 options for climate warming: the increase of temperature was estimated to be...

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The Finnish Wind Atlas was prepared applying the mesoscale model AROME with 2.5 km horizontal resolution and the diagnostic downscaling method Wind Atlas Analysis and Application Programme (WAsP) with 250 m resolution. The latter was applied for areas most favourable for wind power production: a 30 km wide coastal/offshore zone, highlands, large lakes and large fields. The methodology included several novel aspects: (i) a climatologically representative period of real 48 months during 1989-2007 was simulated with the mesoscale model; (ii) in addition, the windiest and calmest months were simulated; (iii) the results were calculated separately for each month and for sectors 30°wide; (iv) the WAsP calculations were based on the mesoscale model outputs; (v) in addition to point measurements, also radar wind data were applied for the validation of the mesoscale model results; (vi) the parameterization method for gust factor was extended to be applicable at higher altitudes; and (vii) the dissemination of the Wind Atlas was based on new technical solutions. The AROME results were calculated for the heights of 50, 75, 100, 125, 150, 200, 300 and 400 m, and the WAsP results for the heights of 50, 75, 100, 125 and 150 m. In addition to the wind speed, the results included the values of the Weibull distribution parameters, the gust factor, wind power content and the potential power production, which was calculated for three turbine sizes. The Wind Atlas data are available for each grid point and can be downloaded free of charge from dynamic maps at www.windatlas.fi. Production of the Finnish Wind Atlas B. Tammelin et al.Accordingly, a strong need arose for a more accurate wind atlas. In Finland, the size of the country, its complex terrain and large seasonal differences generate strong demands for a wind atlas. The complexity of the terrain is not so much related to orography but to the complex shape of the almost flat coastline and archipelago, which generates a need for very high spatial resolution. Further, the differences in wind conditions between seasons are particularly large because in winter, the sea and lakes are frozen and the ground is covered by snow, which changes the surface roughness and stabilizes the atmospheric boundary layer (ABL). Stable stratification favours the generation of low-level jets. 4 In winter, wind power plants are also subject to ice accretion. The production of a new Wind Atlas for Finland has also been motivated by the need to evaluate the possible effects of climate change on wind conditions. In 2008, the Ministry of Labour and Economics released an international tender for production of the new Finnish Wind Atlas. The tender was won by the Finnish Meteorological Institute (FMI), with Risø DTU and Vaisala Ltd as subcontractors. The project started 1 June 2008, and the wind atlas was released 25 November 2009 (www.windatlas.fi).Many national wind atlases have recently been produced applying numerical weather prediction (NWP) models. In an ideal approach, all possible weather condition...

Climate change induces multiple abiotic and biotic risks to forests and forestry. Risks in different spatial and temporal scales must be considered to ensure preconditions for sustainable multifunctional management of forests for different ecosystem services. For this purpose, the present review article summarizes the most recent findings on major abiotic and biotic risks to boreal forests in Finland under the current and changing climate, with the focus on windstorms, heavy snow loading, drought and forest fires and major insect pests and pathogens of trees. In general, the forest growth is projected to increase mainly in northern Finland. In the south, the growing conditions may become suboptimal, particularly for Norway spruce. Although the wind climate does not change remarkably, wind damage risk will increase especially in the south, because of the shortening of the soil frost period. The risk of snow damage is anticipated to increase in the north and decrease in the south. Increasing drought in summer will boost the risk of large‐scale forest fires. Also, the warmer climate increases the risk of bark beetle outbreaks and the wood decay by Heterobasidion root rot in coniferous forests. The probability of detrimental cascading events, such as those caused by a large‐scale wind damage followed by a widespread bark beetle outbreak, will increase remarkably in the future. Therefore, the simultaneous consideration of the biotic and abiotic risks is essential.