CR 29:139-156 (2005)  -  doi:10.3354/cr029139

ABSTRACT: Monthly series from 7 Global Climate Models (GCMs) were used to estimate forthcoming changes in global solar radiation, precipitation amount, daily average temperature, and daily temperature range in the Czech region. scenarios were constructed using the pattern scaling technique: the standardised scenario, which relates the climate variable responses to a 1°C rise in global mean temperature (T_G), was multiplied by the predicted change (ΔT_G). The standardised scenarios were determined from the GCM runs, ΔT_G values were calculated by the simple climate model MAGICC. Two groups of uncertainties were analysed: (1) uncertainties in the standardised scenario, with (1a) inter-GCM variability, (1b) internal GCM variability, (1c) uncertainty due to the choice of the site (within the Czech territory), (1d) uncertainty involved in the regression technique; (2) uncertainties in ΔT_G, with (2a) choice of the emission scenario, (2b) value of the climate sensitivity factor. In the case of group 1, (1a) dominated, (1b) was in some cases similar to (1a), and (1c) was nearly negligible; regression uncertainty (1d) indicated that the climate variable changes are often statistically insignificant. In the case of group 2, uncertainty due to climate sensitivity (2b) dominated for the nearest future, but uncertainty in emission scenarios (2a) attained greater importance later in the 21st century. The mean magnitude of the effect of aerosols on changes in temperature and precipitation was mostly lower than its inter-GCM variability, which was lower than (in the case of the temperature changes) or similar to (in the case of precipitation) the inter-GCM uncertainty in greenhouse gas (GHG) simulations. A stochastic model was developed to assess the combined effect of inter-GCM uncertainty, regression uncertainty, and uncertainty in ΔT_G. While the overall uncertainty in the temperature scenarios was dominated by inter-GCM uncertainty and ΔT_G uncertainty, the aggregated uncertainty in the precipitation scenarios was dominated by inter-GCM uncertainty only.

KEY WORDS: Climate change scenarios · Uncertainty analysis · Global climate models · Pattern scaling