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Comprehensive global climate models are the only tools that account for the complex set of processes which will determine future climate change at both a global and regional level. Planners are typically faced with a wide range of predicted changes from different models of unknown relative quality, owing to large but unquantified uncertainties in the modelling process. Here we report a systematic attempt to determine the range of climate changes consistent with these uncertainties, based on a 53-member ensemble of model versions constructed by varying model parameters. We estimate a probability density function for the sensitivity of climate to a doubling of atmospheric carbon dioxide levels, and obtain a 5-95 per cent probability range of 2.4-5.4 degrees C. Our probability density function is constrained by objective estimates of the relative reliability of different model versions, the choice of model parameters that are varied and their uncertainty ranges, specified on the basis of expert advice. Our ensemble produces a range of regional changes much wider than indicated by traditional methods based on scaling the response patterns of an individual simulation.

Abstract. We describe a set of two "new generation" general circulation models of the Martian atmosphere derived from the models we originally developed in the early 1990s. The two new models share the same physical parameterizations but use two complementary numerical methods to solve the atmospheric dynamic equations. The vertical resolution near the surface has been refined, and the vertical domain has been extended to above 80 km.These changes are accompanied by the inclusion of state-of-the-art parameterizations to better simulate the dynamical and physical processes nero' the surface (boundary layer scheme, subgrid-scale topography parameterization, etc.) and at high altitude (gravity wave drag). In addition, radiative transfer calculations and the representation of polar processes have been significantly improved. We present some examples of zonal-mean fields from simulations using the model at several seasons. One relatively novel aspect, previously introduced by Wilson [1997], is that around northern winter solstice the strong pole to pole diabatic forcing creates a quasi-global, angular-momentum conserving Hadley cell which has no terrestrial equivalent. Within such a cell the Coriolis forces accelerate the winter meridional flow toward the pole and induce a strong warming of the middle polar atmosphere down to 25 km. This winter polar warming had been observed but not properly modeled until recently. In fact, thermal inversions are generally predicted above one, and often both, poles m'ound 60-70 km. However, the Mars middle atmosphere above 40 km is found to be very model-sensitive and thus difficult to simulate accurately in the absence of observations.

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The range of possibilities for future climate evolution needs to be taken into account when planning climate change mitigation and adaptation strategies. This requires ensembles of multi-decadal simulations to assess both chaotic climate variability and model response uncertainty. Statistical estimates of model response uncertainty, based on observations of recent climate change, admit climate sensitivities--defined as the equilibrium response of global mean temperature to doubling levels of atmospheric carbon dioxide--substantially greater than 5 K. But such strong responses are not used in ranges for future climate change because they have not been seen in general circulation models. Here we present results from the 'climateprediction.net' experiment, the first multi-thousand-member grand ensemble of simulations using a general circulation model and thereby explicitly resolving regional details. We find model versions as realistic as other state-of-the-art climate models but with climate sensitivities ranging from less than 2 K to more than 11 K. Models with such extreme sensitivities are critical for the study of the full range of possible responses of the climate system to rising greenhouse gas levels, and for assessing the risks associated with specific targets for stabilizing these levels.

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