The change in the mean temperature in Finland is investigated with a dynamic linear model in order to define the sign and the magnitude of the trend in the temperature time series within the last 166 years. The data consists of gridded monthly mean temperatures. The grid has a 10 km spatial resolution, and it was created by interpolating a homogenized temperature series measured at Finnish weather stations. Seasonal variation in the temperature and the autocorrelation structure of the time series were taken account in the model. Finnish temperature time series exhibits a statistically significant trend, which is consistent with human-induced global warming. The mean temperature has risen very likely over 2°C in the years 1847-2013, which amounts to 0.14°C/decade. The warming after the late 1960s has been more rapid than ever before. The increase in the temperature has been highest in November, December and January. Also spring months (March, April, May) have warmed more than the annual average, but the change in summer months has been less evident. The detected warming exceeds the global trend clearly, which matches the postulation that the warming is stronger at higher latitudes.

Using reports of forest losses caused directly by large scale windstorms (or primary damage, PD) from the European forest institute database (comprising 276 PD reports from 1951–2010), total growing stock (TGS) statistics of European forests and the daily North Atlantic Oscillation (NAO) index, we identify a statistically significant change in storm intensity in Western, Central and Northern Europe (17 countries). Using the validated set of storms, we found that the year 1990 represents a change-point at which the average intensity of the most destructive storms indicated by PD/TGS > 0.08% increased by more than a factor of three. A likelihood ratio test provides strong evidence that the change-point represents a real shift in the statistical behaviour of the time series. All but one of the seven catastrophic storms (PD/TGS > 0.2%) occurred since 1990. Additionally, we detected a related decrease in September–November PD/TGS and an increase in December–February PD/TGS. Our analyses point to the possibility that the impact of climate change on the North Atlantic storms hitting Europe has started during the last two and half decades.

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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...

A B S T R A C TWe project changes in the annual maximum ice extent and the maximum coastal fast ice thickness in the Baltic Sea during the ongoing century. The influence of future warming on the ice conditions was assessed using the NovemberÁMarch Baltic coastal mean temperature as a predictor for the annual maximum ice extent (MIB), and the local freezing degree-day sum as a predictor for the fast ice thickness. Future winter temperatures were derived by adjusting observational baseline-period temperatures in accordance with temperature projections based on 28 global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5. Under the Representative Concentration Pathway (RCP) 4.5 scenario, the ensemble-mean trend of MIB is (6400 km 2 /10 yr, and from the 2060s onwards in a typical winter MIB remains below 80 )10 3 km 2 . If the RCP8.5 scenario is realised, the corresponding estimates are (10 900 km 2 /10 yr for the trend and 60)10 3 km 2 for a typical MIB. For cold rather than typical winters, the projected rate of decrease in MIB is even faster. During the late century under RCP8.5, in 9 out of 10 yr the ice would only cover 5Á20% of the total sea area. The projected trends in the mean annual maximum ice thickness are (7.6 . . . (3.3 cm/10 yr, depending on location and applied scenario. In the 2040s under both scenarios, and in the 2080s under RCP4.5, the ice thickness may still exceed 60 cm in the northernmost Bay of Bothnia, while elsewhere in the Gulf of Bothnia and in the Gulf of Finland, it will vary between about 10 and 40 cm. In the 2080s under RCP8.5, virtually no ice occurs outside the Bay of Bothnia. For both the ice extent and thickness, the spread among the responses based on the temperature projections of individual GCMs is considerable. Nonetheless, a robust finding is that the Baltic Sea is unlikely to become totally ice-free during this century.