Professor Myles Allen CBE FRS

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.

Abstract:

When a damaging extreme meteorological event occurs, the question often arises as to whether that event was caused by anthropogenic greenhouse gas emissions. The question is more than academic, since people affected by the event will be interested in recurring damages if they find that someone is at fault. However, since this extreme event could have occurred by chance in an unperturbed climate, we are currently unable to properly respond to this question. A solution lies in recognising the similarity with the cause-effect issue in the epidemiological field. The approach there is to consider the changes in the risk of the event occurring as attributable, as against the occurrence of the event itself. Inherent in this approach is a recognition that knowledge of the change in risk as well as the amplitude of the forcing itself are uncertain. Consequently, the fraction of the risk attributable to the external forcing is a probabilistic quantity. Here we develop and demonstrate this methodology in the context of the climate change problem. © Springer 2005.