The response of the climate system to prescribed changes in the concentrations of greenhouse gases and aerosols depends on the characteristics of the system such as the climate sensitivity, rate of heat uptake by the ocean and strength of aerosol forcing. All these characteristics are highly uncertain, leading to the uncertainty in future climate. Different approaches have been used for producing probability distributions for the changes in surface air temperature (SAT) and other climate variables, including the multi-model ensemble approach. Distributions obtained using the latter approach may be biased for a number of reasons. The ranges of possible SAT changes given in IPCC AR4 were adjusted to account for the fact that values of climate sensitivity and rate of oceanic heat uptake for AOGCMs used in AR4 simulations do not cover the full uncertainty ranges. These SAT ranges are, however, based on the multi-model ensemble means. The rates of the oceanic heat uptake for most of AR4 AOGCMs lie in the upper part of the range suggested by observations. As a result the means of the multi-model ensemble are likely to be biased toward low warming, especially in the simulations with large increase in radiative forcing (SRES A2). Here we evaluate the uncertainty in climate response to prescribed changes in greenhouse gas concentrations using the MIT Integrated Global System Model (IGSM2.2).We carried out three 250 member ensembles for SRES scenarios B1, A1B and A2. Probability distributions for the climate sensitivity, strength of aerosol forcing and the rate of ocean heat uptake were obtained by comparing 20th century climate as simulated by the IGSM with available observations. Our simulations suggest that by the end of the 21st century (2090-2099) surface air temperature is likely to increase above the present level (1980-1999) by 1.6C to 2.3C for B1, 2.5C to 3.6C for A1B and 3.4C to 4.6C for A2. Corresponding ranges for a sea level rise due to thermal expansion are: 9 cm to 18 cm for B1, 13 cm to 25 cm for A1B and 16 cm to 29 cm for A2. The mean values of surface warming obtained in our simulations for these three scenarios, 2.1C, 3.2C and 4.0C respectively, are noticeably higher than the AR4 multi-model ensemble means, 1.8C, 2.4C and 3.4C. The upper bounds of the possible SAT increases obtained in simulations with the MIT IGSM2.2 significantly exceed the warming simulated by AR4 AOGCMs. Thus for the high emissions scenario (A2) the results of all AOGCMs lie in the low half of the range (below the mean) suggested by the MIT IGSM and below the 67% percentile for the other two scenarios. The situation is the opposite for the sea level rise due to thermal expansion. The results presented illustrate the importance of properly sampling the full range of uncertainties in the input parameters when predicting future climate change by means of numerical simulations.