The presence of permanent snow cover for 200-220 days of the year has a determining role in the energy, hydrological and ecological processes at the climate-driven spruce (Picea abies) timberline in Lapland. Disturbances, such as forest fires or forest harvesting change the vegetation pattern and influence the spatial variation of snow cover. This variability in altered snow conditions (in subarctic Fennoscandia) is still poorly understood. We studied the influence of vegetation on the small-scale spatial variation of snow cover and wind climate in the Tuntsa area that was disturbed by a widespread forest fire in 1960. Radar was applied to measure snow thickness over two vegetation types, the spruce-dominant fire refuge and post-fire treeless tundra. Wind modelling was used to estimate the spatial variation of wind speed and direction. Due to the altered surface roughness and the increased wind velocity, snow drifting was more vigorous on the open tundra, resulting in a 30-cm thinner snow cover and almost half the water equivalent compared to the forest values. The changes in local climate after the fire, particularly in snow cover, may have played an important role in the poor recovery of vegetation: a substantial area is still unforested 40 years after the fire.

No abstract

Forest fires constitute the second largest form of disturbance to the Finnish boreal forest environment, playing a significant role in vegetation succession and landscape transformation. Warning systems aiming to minimize the risk of fires are based on fire danger estimation methods using weather information. In this study, the operational fire danger rating method used in Finland, the Finnish Forest Fire Index, is introduced and its performance evaluated by analysing the relationship between the predicted daily fire danger and observed fire activity. The Finnish Forest Fire Index is a physically-based soil surface moisture estimation method employing as input traditional surface observations, numerical weather forecast model fields and weather radar measurements. The fire danger index is found to predict high fire danger conditions well, with some decline in performance northward where the observations network is sparser than in the southern part of the country. The model indicated higher hit rates in the prediction of multiple fire (54%) and large fire days (54.3%), which are less dependent on a human-dominated fire environment than are single fire days. Highlighted future development priorities include the direct application of numerical analyses of meteorological data in the operational computation procedure. In addition, inclusion of the impact of land cover, such as vegetation type, on the fire danger index is under development.

At high latitudes in Lapland, near the climatological timberline, forestry and other environmental research require detailed information about the spatial variation of climate. In this study, the influence of local geographical factors on the climate in northern Finland (Lapland), as well as the applicability of the kriging interpolation method in the case of detailed spatial resolution, were examined. The spatial analysis of mean, maximum, minimum temperatures, length of the frost-free season, degree-days and daily range was made using a 1 km × 1 km resolution. The time period used was 1971-2000. We studied whether taking account of external forcing, such as lake coverage and altitude, would improve the accuracy of spatial interpolation of climatological parameters. The geographical factors of coordinates, elevation, lakes and sea influence on the regional features of the climate were examined. According to the results of this study, only geographical position and local relief have a significant influence on regional climate in Lapland. The effect of lakes and sea seems to be secondary.

Abstract. A method for estimating the occurrence of freezing rain (FZRA) in gridded atmospheric data sets was evaluated, calibrated against SYNOP weather station observations, and applied to the ERA-Interim reanalysis for climatological studies of the phenomenon. The algorithm, originally developed at the Finnish Meteorological Institute for detecting the precipitation type in numerical weather prediction, uses vertical profiles of relative humidity and temperature as input. Reanalysis data in 6 h time resolution were analysed over Europe for the period 1979-2014. Mean annual and monthly numbers of FZRA events, as well as probabilities of duration and spatial extent of events, were then derived. The algorithm was able to accurately reproduce the observed, spatially averaged interannual variability of FZRA (correlation 0.90) during the 36-year period, but at station level rather low validation and cross-validation statistics were achieved (mean correlation 0.38). Coarse-grid resolution of the reanalysis and misclassifications to other freezing phenomena in SYNOP observations, such as ice pellets and freezing drizzle, contribute to the low validation results at station level. Although the derived gridded climatology is preliminary, it may be useful, for example, in safety assessments of critical infrastructure.