Professor Myles Allen CBE FRS

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.

Abstract:

Any attempt to estimate climate sensitivity using observations requires a set of models or model-versions that simultaneously predict both climate sensitivity and some observable quantity(-ies) given a range of values of unknown climate system properties, represented by choices of parameters, subsystems or even entire models. The choices researchers make with respect to these unknown properties play a crucial role in conditioning their climate forecasts. We show that any probabilistic estimate of climate sensitivity, and hence of the risk that a given greenhouse gas stabilisation level might result in a "dangerous" equilibrium warming, is critically dependent on subjective prior assumptions of the investigators, not simply on constraints provided by actual climate observations. This apparent arbitrariness can be resolved by focussing on the intended purpose of the forecast: while uncertainty in long-term equilibrium warming remains high, an objectively determined 10-90% (5-95%) range of uncertainty in climate sensitivity that is relevant to forecasts of 21st century transient warming under nearly all current emission scenarios is 1.4-4.1°C with a median of 2.4°C, in good agreement with the "traditional" range. Copyright 2005 by the American Geophysical Union.