The evolution of climate is dependent upon the energy balance of the earth-atmosphere-ocean system, which is in turn dependent on the composition of the atmosphere, in particular on the concentration of gases and aerosols, which may absorb or reflect long-wave and short-wave radiation. The atmospheric concentration of these constituents is dependent on their emission into the atmosphere from both natural and man-made sources. The increase in the man-made component of these emissions since the beginning of the Industrial Revolution and the effect this is having, and will have, on climate are cause for concern. Global climate models (GCMs) have been developed to determine the climate response to changing atmospheric composition, and have been used in the simulation of both past and future climates. GCMs are complex three-dimensional mathematical models of the earth-atmosphere-ocean system, able to reproduce successfully the spatial patterns of global climate. At more regional scales, however, there are differences, or biases, between model-simulated and actual current climate conditions, which affect how this information is used. In order to overcome these biases, changes in the simulated climate between some future time period, e.g., the 2050s, and the GCM’s baseline climate period, currently 1961–90, are used rather than the model output directly from the climate change experiments. There are many GCMs available for use; each one gives slightly different results because of differences in the way in which they are formulated.
To simulate future climate, GCMs require information about future atmospheric composition, which is dependent on a scenario of future emissions of radiatively active gases into the atmosphere. Since future emissions are dependent on such things as future population and economic growth, energy use, technological development and land use change, the uncertainty associated with estimates of future emissions increases over time. There are, therefore, any number of future emissions scenarios which are plausible and could be used as the basis for GCM climate change experiments. However, the cost of running GCMs precludes their use for simulating climate for many emissions scenarios: instead, a small number of plausible emissions futures have been selected by the Intergovernmental Panel on Climate Change (IPCC) and have been used by the international global climate modelling community.
All experiments indicate warmer future conditions for Saskatchewan, with the largest increases in mean temperature occurring in winter and spring as a result of snow and ice cover change. There is also a general tendency for increases in precipitation, particularly in winter and spring, although about half of the experimental results indicate decreases in precipitation in the summer. Business-as-usual emissions scenarios indicate that climate may change in the future if little is done to reduce greenhouse gas emissions. Most GCMs project increases in winter average temperature of between about 2° and 4°C by the 2050s, although some GCMs indicate changes less than or in excess of this range. Changes in summer precipitation are much more variable, being less coherent spatially and also differing much more from GCM to GCM; this is partly due to the difficulty in modelling the precipitation process, which occurs at spatial scales smaller than a global climate model can resolve directly. However, there is a general trend for decreases in summer precipitation in southern Saskatchewan, which will lead to decreases in soil moisture content. Soil moisture deficits are likely to increase even where precipitation increases are projected, since the warmer conditions will lead to increased evapotranspiration.
Elaine Barrow