Uncertainty in predictions of the climate response to rising levels of greenhouse gases.

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.

Origins and estimates of uncertainty in predictions of twenty-first century temperature rise.

Predictions of temperature rise over the twenty-first century are necessarily uncertain, both because the sensitivity of the climate system to changing atmospheric greenhouse-gas concentrations, as well as the rate of ocean heat uptake, is poorly quantified and because future influences on climate-of anthropogenic as well as natural origin-are difficult to predict. Past observations have been used to help constrain the range of uncertainties in future warming rates, but under the assumption of a particular scenario of future emissions. Here we investigate the relative importance of the uncertainty in climate response to a particular emissions scenario versus the uncertainty caused by the differences between future emissions scenarios for our estimates of future change. We present probabilistic forecasts of global-mean temperatures for four representative scenarios for future emissions, obtained with a comprehensive climate model. We find that, in the absence of policies to mitigate climate change, global-mean temperature rise is insensitive to the differences in the emissions scenarios over the next four decades. We also show that in the future, as the signal of climate change emerges further, the predictions will become better constrained.

The detection of large HNO3-containing particles in the winter Arctic stratosphere.

Large particles containing nitric acid (HNO3) were observed in the 1999/2000 Arctic winter stratosphere. These in situ observations were made over a large altitude range (16 to 21 kilometers) and horizontal extent (1800 kilometers) on several airborne sampling flights during a period of several weeks. With diameters of 10 to 20 micrometers, these sedimenting particles have significant potential to denitrify the lower stratosphere. A microphysical model of nitric acid trihydrate particles is able to simulate the growth and sedimentation of these large sizes in the lower stratosphere, but the nucleation process is not yet known. Accurate modeling of the formation of these large particles is essential for understanding Arctic denitrification and predicting future Arctic ozone abundances.