Wintertime bearing capacity on different forest soils with respect to timber harvesting in the projected future climate of Finland was estimated by using a soil temperature model and a wide set of downscaled climate model simulations. The results indicate that, particularly, drained peatlands may virtually lack soil frost over large areas in most of winters during the late 21st century. There is thus a clear need to develop new sustainable and efficient logging practices for peatland forests.

An online survey was used to map the needs and preferences of the Finnish general public about extended-range forecasts and their presentation. Survey results guided the co-design process of novel extended-range forecasts in the project. The respondents considered that the tailored extended-range forecasts would be beneficial in planning activities, preparing for weather risks and scheduling everyday life. They also valued impact information higher than advice on how to prepare for the impacts.

The rapidly growing forest-based bioeconomy calls for increasing wood harvesting intensity, and an increase in thinning and a final felling area. This may increase wind damage risks at the upwind edges of new cleared felling areas and thinned stands. Efficient wind risk assessment is needed. We demonstrate a pragmatic and computationally feasible method for identifying at a high spatial resolution those locations having the highest forest wind damage risks.

Finnish Meteorological Institute and Helen Ltd examined the feasibility of long-range forecasts (longer than two weeks) of temperature for needs of the energy sector in Helsinki, Finland. In this study, we examined the quality of Heating degree day (HDD) forecasts. As the forecasts we used UK Met Office seasonal forecasts. The long-range forecasts of monthly HDD showed some skill in Helsinki in winter 2015–2016, up to two months, especially if the very cold January is excluded.

Freezing rain is a high-impact wintertime weather phenomenon. The direct damage it causes to critical infrastructure (transportation, communication and energy) and forestry can be substantial. In this work a method for estimating the occurrence of freezing rain was evaluated and used to derive the climatology. The method was able to accurately reproduce the observed, spatially aggregated annual variability. The highest frequencies of freezing rain were found in eastern and central Europe.

We studied the impact of projected climate change on the risk of snow-induced forest damage in Finland. Although winters are projected to become milder over the whole of Finland, our results suggest than in eastern and northern Finland the risk may increase while in southern and western parts of the country it is projected to decrease. This indicates that there is increasing need to consider the potential of snow damage in forest management in eastern and northern Finland.

The number of large forest fires in Finland will most likely increase during the twenty-first century in response to projected climate change. This would increase the risk that some of the fires could develop into real conflagrations which have become almost extinct in Finland due to effective fire suppression. However, our results show considerable inter-model variability, demonstrating the large uncertainty related to the rate of the projected change in forest-fire danger.

Emergency rescue data and weather reanalysis data were combined to study the spatial and decadal characteristics of potential forest damage days in Finland due to windstorms. The most prone area for damage days was the south-western part of Finland. Results also indicated a lull period during the 1990s compared to the 1980s and 2000s, albeit no trend was evident. The study highlighted the importance of not only focusing on wind speeds, but also soil conditions.

We assessed the quality of the seasonal precipitation forecasts issued by Regional Climate Outlook Forum for Malawi and Zambia. The forecasts, issued in August, are of rainy season rainfall accumulations for early and late season. The forecasts are rather well-calibrated, but cannot discriminate between different events. But these results can be too pessimistic, because forecasts have gone through much development lately, and forecasts using current methodology might have performed better.