Professor Myles Allen CBE FRS

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.

Abstract:

Detection and attribution studies of observed surface temperature changes have served to consolidate our understanding of the climate system and its past and future behaviour. Most recent studies analysing up-to-date observations have relied on general circulation models (GCMs) to provide estimates of the responses to various external forcings. Here we revisit a methodology which instead estimates the responses using a simple model tuned directly to the observed record, paralleling a technique currently used with GCM output. The effects of greenhouse gases, tropospheric sulphate aerosols, and volcanic aerosols are all detected in the observed record, while the effects of solar irradiance are unclear. These results provide further observational constraints on past and future warming estimates consistent with those from recent studies with GCMs, supporting the notion that current estimates are robust against the modelling system used. Copyright 2005 by the American Geophysical Union.