An assessment of possible snow changes in a changing climate for Finland is presented. The snowpack structure model SNOWPACK (developed at the Swiss Federal Institute for Snow and Avalanche Research) was used for calculating snow conditions at six different locations in Finland for the decades 1980-89 and 2080-89. Regional climate model (RCAO) data from the Rossby Centre, Sweden, were used as input to the SNOWPACK model. Ten years from the RCAO control run and scenario run Were chosen, and the snow conditions for different snow zones were calculated for these winters. The snow-cover depth and duration decreased at all locations in the scenario run cases, and the snow-cover quality also changed between the control and scenario runs: grains were bigger, snow was warmer and denser, and the fraction of faceted snow decreased while the fraction of icy or melting snow increased, even in mid-winter. Finally, the variability between different global climate predictions was analyzed. Significant differences were found between different climate-model outputs. The inter-model variable is comparable to the interannual variability of a single model. The qualitative Conclusions from the scenario run do not critically depend oil the climate-model variability.

A basic analysis is presented for a series of regional climate change simulations that were conducted by the Swedish Rossby Centre and contribute to the PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects) project. For each of the two driving global models HadAM3H and ECHAM4/OPYC3, a 30-year control run and two 30-year scenario runs (based on the SRES A2 and B2 emission scenarios) were made with the regional model. In this way, four realizations of climate change from 1961-1990 to 2071-2100 were obtained. The simulated changes are larger for the A2 than the B2 scenario (although with few qualitative differences) and in most cases in the ECHAM4/OPYC3-driven (RE) than in the HadAM3H-driven (RH) regional simulations. In all the scenario runs, the warming in northern Europe is largest in winter or late autumn. In central and southern Europe, the warming peaks in summer when it locally reaches 10 degreesC in the RE-A2 simulation and 6-7 degreesC in the RH-A2 and RE-B2 simulations. The four simulations agree on a general increase in precipitation in northern Europe especially in winter and on a general decrease in precipitation in southern and central Europe in summer, but the magnitude and the geographical patterns of the change differ markedly between RH and RE. This reflects very different changes in the atmospheric circulation during the winter half-year, which also lead to quite different simulated changes in windiness. All four simulations show a large increase in the lowest minimum temperatures in northern, central and eastern Europe, most likely due to reduced snow cover. Extreme daily precipitation increases even in most of those areas where the mean annual precipitation decreases.

The decade 1991-2000 was warm and wet in Sweden, with 10-station mean temperature 0.8 degreesC above and 20-station mean precipitation 6% above the mean for 1961-1990. Here we study the question if such changes should be seen as a symptom of anthropogenic climate change or if they might be of purely natural origin. Using the control simulations of 19 atmosphere-ocean general circulation models and taking into account difference's between the simulated and observed interannual variability, we estimate that the recent increase in temperature and that in precipitation had both about a 6-7% chance to occur solely as a result of natural variability. Using the corresponding simulations with increasing CO2, we further estimate that the anthropogenic forcing raised the probability of the observed changes to occur to 23% for the increase in temperature and to 14% for the increase in precipitation. About half of the warming and about 30% of the increase in precipitation appear to be explained by anthropogenic forcing. The seasonal aspects of observed and simulated climate change are also discussed, with special emphasis on winter, when the observed warming has been much larger than expected from the model simulations. Finally, a probabilistic forecast for the Swedish climate in the first decade of the 21st century suggests a 95% (87%) possibility of warmer (wetter) annual mean conditions than in 1961-1990 on the average. One of the caveats in our analysis is that the model simulations exclude variations in solar and volcanic activity, the effects of which might not be fully covered by our resealing of interannual variability.

The response of atmospheric angular momentum to a gradual doubling of CO2 is studied using 16 model experiments participating in the second phase of the Coupled Model Intercomparison Project (CMIP2). The relative angular momentum associated with atmospheric zonal winds increases in all but one of the models, although the magnitude of the change varies widely. About 90% of the 16-model mean increase comes from increasing westerly winds in the stratosphere and the uppermost low-latitude troposphere above 200 hPa. This increase in westerly winds reflects a steepening of the meridional temperature gradient near the tropopause and in the upper troposphere. The simulated temperature gradient at this height increases partly as an indirect consequence of the poleward decrease in the tropopause height, and partly because convection induces a maximum in warming in the tropical upper troposphere. The change in the omega angular momentum associated with the surface pressure distribution is in most models smaller than the change in the relative angular momentum, although its exact value is sensitive to the method of calculation.

According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.

CO2-induced changes in the interannual variability of monthly surface air temperature and precipitation are studied using 19 model experiments participating in the second phase of the Coupled Model Intercomparison Project (CMIP2). The magnitude of variability in the control runs appears generally reasonable, but it varies a great deal between different models, almost all of which overestimate temperature variability on low-latitude land areas. In most models the gradual doubling of CO2 leads to a decrease in temperature variability in the winter half-year in the extratropical Northern Hemisphere and over the high-latitude Southern Ocean. Over land in low latitudes and in northern midlatitudes in summer, a slight tendency toward increased temperature variability occurs. The standard deviation of monthly precipitation increases, on average, where the mean precipitation increases but also does so in some areas where the mean precipitation decreases slightly. The coefficient of variation of precipitation (i.e., the ratio between the standard deviation and the mean) also tends to increase in most areas, especially where the mean precipitation decreases. However, the changes in variability are less similar between the 19 experiments than the changes in mean temperature and precipitation, at least partly because they have a much lower signal-to-noise ratio. In addition, the changes in the standard deviation of monthly temperature are generally much smaller than the time-mean warming, which suggests that future changes in the extremes of interannual temperature variability will be largely determined by the latter.

By using a process-oriented ocean model forced with data from a gridded synoptic database, net precipitation values (precipitation minus evaporation) over the Baltic Sea are obtained. For a range of realistic meteorological forcing the average annual value obtained from an 18 yr (1981-1998) simulation ranges between 1100 and 2500 m(3) s(-1). The monthly variations are significant with the highest values occurring in early summer and even negative values in late autumn. Ice is an important factor, and the net precipitation is close to zero in the southern basins with no ice. Calculated net precipitation for a 98 yr period (1901-1998) using river runoff and maximum ice extent indicates that the investigated 18 yr period was wetter than the almost 100 yr climate mean. A realistic climate estimate of net precipitation during the 20th century is estimated to be 1500 +/-1000 m(3) s(-1). The evaluation of 2 present day regional climate simulations indicated high precipitation, low evaporation, and thus excessive net precipitation compared to the climate estimate from this investigation. When simulating the effect of increased greenhouse gases, the change in net precipitation was positive but small due to the compensating effects of increased precipitation and increased evaporation associated with increased temperature and reduced ice.

Increasing concentrations of atmospheric carbon dioxide will almost certainly lead to changes in global mean climate(1). But because-by definition-extreme events are rare, it is significantly more difficult to quantify the risk of extremes. Ensemble-based probabilistic predictions(2), as used in short- and medium-term forecasts of weather and climate, are more useful than deterministic forecasts using a 'best guess' scenario to address this sort of problem(3,4). Here we present a probabilistic analysis of 19 global climate model simulations with a generic binary decision model. We estimate that the probability of total boreal winter precipitation exceeding two standard deviations above normal will increase by a factor of five over parts of the UK over the next 100 years. We find similar increases in probability for the Asian monsoon region in boreal summer, with implications for flooding in Bangladesh. Further practical applications of our techniques would be helped by the use of larger ensembles (for a more complete sampling of model uncertainty) and a wider range of scenarios at a resolution adequate to analyse average-size river basins.