Professor Myles Allen CBE FRS

Abstract:

This paper investigates the impact of aerosol forcing uncertainty on the robustness of estimates of the twentieth-century warming attributable to anthropogenic greenhouse gas emissions. Attribution analyses on three coupled climate models with very different sensitivities and aerosol forcing are carried out. The Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3), Parallel Climate Model (PCM), and GFDL R30 models all provide good simulations of twentieth-century global mean temperature changes when they include both anthropogenic and natural forcings. Such good agreement could result from a fortuitous cancellation of errors, for example, by balancing too much (or too little) greenhouse warming by too much (or too little) aerosol cooling. Despite a very large uncertainty for estimates of the possible range of sulfate aerosol forcing obtained from measurement campaigns, results show that the spatial and temporal nature of observed twentieth-century temperature change constrains the component of past warming attributable to anthropogenic greenhouse gases to be significantly greater (at the 5% level) than the observed warming over the twentieth century. The cooling effects of aerosols are detected in all three models. Both spatial and temporal aspects of observed temperature change are responsible for constraining the relative roles of greenhouse warming and sulfate cooling over the twentieth century. This is because there are distinctive temporal structures in differential warming rates between the hemispheres, between land and ocean, and between mid- and low latitudes. As a result, consistent estimates of warming attributable to greenhouse gas emissions are obtained from all three models, and predictions are relatively robust to the use of more or less sensitive models. The transient climate response following a 1% yr-1 increase in CO2 is estimated to lie between 2.2 and 4 K century-1 (5-95 percentiles). © 2006 American Meteorological Society.

Abstract:

Optimal detection analyses have been used to determine the causes of past global warming, leading to the conclusion by the Third Assessment Report of the IPCC that "most of the observed warming over the last 50 years is likely to have been due to the increase in greenhouse gas concentrations". To date however, these analyses have not taken full account of uncertainty in the modelled patterns of climate response due to differences in basic model formulation. To address this current "perfect model" assumption, we extend the optimal detection method to include, simultaneously, output from more than one GCM by introducing inter-model variance as an extra uncertainty. Applying the new analysis to three climate models we find that the effects of both anthropogenic and natural factors are detected. We find that greenhouse gas forcing would very likely have resulted in greater warming than observed during the past half century if there had not been an offsetting cooling from aerosols and other forcings. Copyright 2006 by the American Geophysical Union.

Abstract:

Anthropogenic climate change has been detected on continental-scale regions on all inhabited continents of the World. From knowledge of the relative contributions of greenhouse gases and other forcings to observed temperature change it is possible to infer the likely rates of future warming, consistent with past observed temperature changes. Probabilistic forecasts of future warming rates in six continental-scale regions have been calculated by assuming that there is a linear relationship between past and future fractional error in temperature change on these spatial scales. All regions are expected to warm over the next century with the largest uncertainty in future warming rates being in North America and Europe. More tightly constrained predictions are obtained if it is assumed that fractional errors in global mean temperature change scale the regional projections. Copyright 2006 by the American Geophysical Union.

Abstract:

The first multi thousand member "perturbed physics" ensemble simulation of present and future climate, completed by the distributed computing project climateprediction.net, is used to search for constraints on the response to increasing greenhouse gas levels among present day observable climate variables. The search is conducted with a systematic statistical methodology to identify correlations between observables and the quantities we wish to predict, namely the climate sensitivity and the climate feedback parameter. A sensitivity analysis is conducted to ensure that results are minimally dependent on the parameters of the methodology. Our best estimate of climate sensitivity is 3.3 K. When an internally consistent representation of the origins of model-data discrepancy is used to calculate the probability density function of climate sensitivity, the 5th and 95th percentiles are 2.2 K and 6.8 K respectively. These results are sensitive, particularly the upper bound, to the representation of the origins of model-data discrepancy. Copyright 2005 by the American Geophysical Union.