Publications by Myles Allen


Warming caused by cumulative carbon emissions towards the trillionth tonne.

Nature 458 (2009) 1163-1166

MR Allen, DJ Frame, C Huntingford, CD Jones, JA Lowe, M Meinshausen, N Meinshausen

Global efforts to mitigate climate change are guided by projections of future temperatures. But the eventual equilibrium global mean temperature associated with a given stabilization level of atmospheric greenhouse gas concentrations remains uncertain, complicating the setting of stabilization targets to avoid potentially dangerous levels of global warming. Similar problems apply to the carbon cycle: observations currently provide only a weak constraint on the response to future emissions. Here we use ensemble simulations of simple climate-carbon-cycle models constrained by observations and projections from more comprehensive models to simulate the temperature response to a broad range of carbon dioxide emission pathways. We find that the peak warming caused by a given cumulative carbon dioxide emission is better constrained than the warming response to a stabilization scenario. Furthermore, the relationship between cumulative emissions and peak warming is remarkably insensitive to the emission pathway (timing of emissions or peak emission rate). Hence policy targets based on limiting cumulative emissions of carbon dioxide are likely to be more robust to scientific uncertainty than emission-rate or concentration targets. Total anthropogenic emissions of one trillion tonnes of carbon (3.67 trillion tonnes of CO(2)), about half of which has already been emitted since industrialization began, results in a most likely peak carbon-dioxide-induced warming of 2 degrees C above pre-industrial temperatures, with a 5-95% confidence interval of 1.3-3.9 degrees C.


A review of uncertainties in global temperature projections over the twenty-first century

Journal of Climate 21 (2008) 2651-2663

R Knutti, R Knutti, MR Allen, P Friedlingstein, JM Gregory, JM Gregory, GC Hegerl, GA Meehl, M Meinshausen, JM Murphy, GK Plattner, GK Plattner, SCB Raper, TF Stocker, PA Stott, H Teng, TML Wigley

Quantification of the uncertainties in future climate projections is crucial for the implementation of climate policies. Here a review of projections of global temperature change over the twenty-first century is provided for the six illustrative emission scenarios from the Special Report on Emissions Scenarios (SRES) that assume no policy intervention, based on the latest generation of coupled general circulation models, climate models of intermediate complexity, and simple models, and uncertainty ranges and probabilistic projections from various published methods and models are assessed. Despite substantial improvements in climate models, projections for given scenarios on average have not changed much in recent years. Recent progress has, however, increased the confidence in uncertainty estimates and now allows a better separation of the uncertainties introduced by scenarios, physical feedbacks, carbon cycle, and structural uncertainty. Projection uncertainties are now constrained by observations and therefore consistent with past observed trends and patterns. Future trends in global temperature resulting from anthropogenic forcing over the next few decades are found to be comparably well constrained. Uncertainties for projections on the century time scale, when accounting for structural and feedback uncertainties, are larger than captured in single models or methods. This is due to differences in the models, the sources of uncertainty taken into account, the type of observational constraints used, and the statistical assumptions made. It is shown that as an approximation, the relative uncertainty range for projected warming in 2100 is the same for all scenarios. Inclusion of uncertainties in carbon cycle-climate feedbacks extends the upper bound of the uncertainty range by more than the lower bound. © 2008 American Meteorological Society.


Constraints on model response to greenhouse gas forcing and the role of subgrid-scale processes

Journal of Climate 21 (2008) 2384-2400

BM Sanderson, R Knutti, T Aina, C Christensen, N Faull, DJ Frame, WJ Ingram, C Piani, DA Stainforth, DA Stone, MR Allen

A climate model emulator is developed using neural network techniques and trained with the data from the multithousand-member climateprediction.net perturbed physics GCM ensemble. The method recreates nonlinear interactions between model parameters, allowing a simulation of a much larger ensemble that explores model parameter space more fully. The emulated ensemble is used to search for models closest to observations over a wide range of equilibrium response to greenhouse gas forcing. The relative discrepancies of these models from observations could be used to provide a constraint on climate sensitivity. The use of annual mean or seasonal differences on top-of-atmosphere radiative fluxes as an observational error metric results in the most clearly defined minimum in error as a function of sensitivity, with consistent but less well-defined results when using the seasonal cycles of surface temperature or total precipitation. The model parameter changes necessary to achieve different values of climate sensitivity while minimizing discrepancy from observation are also considered and compared with previous studies. This information is used to propose more efficient parameter sampling strategies for future ensembles. © 2008 American Meteorological Society.


Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations

Climate Dynamics 30 (2008) 175-190

BM Sanderson, C Piani, WJ Ingram, DA Stone, MR Allen

A linear analysis is applied to a multi-thousand member "perturbed physics" GCM ensemble to identify the dominant physical processes responsible for variation in climate sensitivity across the ensemble. Model simulations are provided by the distributed computing project, climate prediction.net. A principal component analysis of model radiative response reveals two dominant independent feedback processes, each largely controlled by a single parameter change. The leading EOF was well correlated with the value of the entrainment coefficient - a parameter in the model's atmospheric convection scheme. Reducing this parameter increases high vertical level moisture causing an enhanced clear sky greenhouse effect both in the control simulation and in the response to greenhouse gas forcing. This effect is compensated by an increase in reflected solar radiation from low level cloud upon warming. A set of 'secondary' cloud formation parameters partly modulate the degree of shortwave compensation from low cloud formation. The second EOF was correlated with the scaling of ice fall speed in clouds which affects the extent of cloud cover in the control simulation. The most prominent feature in the EOF was an increase in longwave cloud forcing. The two leading EOFs account for 70% of the ensemble variance in λ - the global feedback parameter. Linear predictors of feedback strength from model climatology are applied to observational datasets to estimate real world values of the overall climate feedback parameter. The predictors are found using correlations across the ensemble. Differences between predictions are largely due to the differences in observational estimates for top of atmosphere shortwave fluxes. Our validation does not rule out all the strong tropical convective feedbacks leading to a large climate sensitivity. © Springer-Verlag 2007.


A multimodel update on the detection and attribution of global surface warming

Journal of Climate 20 (2007) 517-530

DA Stone, MR Allen, PA Stott

This paper presents an update on the detection and attribution of global annual mean surface air temperature changes, using recently developed climate models. In particular, it applies a new methodology that permits the inclusion of many more general circulation models (GCMs) into the analysis, and it also includes more recent observations. This methodology involves fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. Despite considerable spread in estimated EBM parameters, characteristics of model performance, such as the transient climate response, appear to be more constrained for each of the forcings. The resulting estimated response patterns are provided as input to the standard fingerprinting method used in previous studies. The estimated GCM responses to changes in greenhouse gases are detected in the observed record for all of the GCMs, and are generally found to be consistent with the observed changes; the same is generally true for the responses to changes in stratospheric aerosols from volcanic eruptions. GCM responses to changes in tropospheric sulfate aerosols and solar irradiance also appear consistent with the observed record, although the uncertainty is larger. Greenhouse gas and solar irradiance changes are found to have contributed to a best guess of ∼0.8 and ∼0.3 K warming over the 1901-2005 period, respectively, while sulfate aerosols have contributed a ∼0.4 K cooling. This analysis provides an observationally constrained estimate of future warming, which is found to be fairly robust across GCMs. By 2100, a warming of between about 1.5 and 4.5 K can be expected according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B emissions scenario. These results indicate an emerging constraint for global mean surface temperature responses to external forcings across GCMs, which is corroborated in the observed record. This implies that observationally constrained estimates of past warming and predictions of future warming are indeed becoming robust. © 2007 American Meteorological Society.


Testing the Clausius-Clapeyron constraint on changes in extreme precipitation under CO2 warming

Climate Dynamics 28 (2007) 351-363

P Pall, MR Allen, DA Stone

Increases in extreme precipitation greater than in the mean under increased greenhouse gases have been reported in many climate models both on global and regional scales. It has been proposed in a previous study that whereas global-mean precipitation change is primarily constrained by the global energy budget, the heaviest events can be expected when effectively all the moisture in a volume of air is precipitated out, suggesting the intensity of these events increases with availability of moisture, and significantly faster than the global mean. Thus under conditions of constant relative humidity one might expect the Clausius-Clapeyron relation to give a constraint on changes in the uppermost quantiles of precipitation distributions. This study examines if the phenomenon manifests on regional and seasonal scales also. Zonal analysis of daily precipitation in the HadCM3 model under a transient CO2 forcing scenario shows increased extreme precipitation in the tropics accompanied by increased drying at lower percentiles. At mid- to high-latitudes there is increased precipitation over all percentiles. The greatest agreement with Clausius-Clapeyron predicted change occurs at mid-latitudes. This pattern is consistent with other climate model projections, and suggests that regions in which the nature of the ambient flows change little give the greatest agreement with Clausius-Clapeyron prediction. This is borne out by repeating the analyses at gridbox level and over season. Furthermore, it is found that Clausius-Clapeyron predicted change in extreme precipitation is a better predictor than directly using the change in mean precipitation, particularly between 60°N and 60°S. This could explain why extreme precipitation changes may be more detectable then mean changes. © Springer-Verlag 2006.


Regional probabilistic climate forecasts from a multithousand, multimodel ensemble of simulations

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 112 (2007) ARTN D24108

C Piani, B Sanderson, F Giorgi, DJ Frame, C Christensen, MR Allen


Estimates of uncertainty in predictions of global mean surface temperature

Journal of Climate 20 (2007) 843-855

JA Kettleborough, JA Kettleborough, BBB Booth, PA Stott, MR Allen

A method for estimating uncertainty in future climate change is discussed in detail and applied to pridictions of global mean temperature change. The method uses optimal fingerprinting to make estimates of uncertainty in model simulations of twentieth-century warming. These estimates are then projected forward in time using a linear, compact relationship between twentieth-century warming and twenty-first-century warming. This relationship is established from a large ensemble of energy balance models. By varying the energy balance model parameters an estimate is made of the error associated with using the linear relationship in forecasts of twentieth-century global mean temperature. Including this error has very little impact on the forecasts. There is a 50% chance that the global mean temperature change between 1995 and 2035 will be greater than 1.5 K for the Special Report on Emissions Scenarios (SRES) A1FI scenario. Under SRES B2 the same threshold is not exceeded until 2055. These results should be relatively robust to model developments for a given radiative forcing history. © 2007 American Meteorological Society.


The detection and attribution of climate change using an ensemble of opportunity

Journal of Climate 20 (2007) 504-516

DA Stone, MR Allen, F Selten, M Kliphuis, PA Stott

The detection and attribution of climate change in the observed record play a central role in synthesizing knowledge of the climate system. Unfortunately, the traditional method for detecting and attributing changes due to multiple forcings requires large numbers of general circulation model (GCM) simulations incorporating different initial conditions and forcing scenarios, and these have only been performed with a small number of GCMs. This paper presents an extension to the fingerprinting technique that permits the inclusion of GCMs in the multisignal analysis of surface temperature even when the required families of ensembles have not been generated. This is achieved by fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. This methodology is applied to the very large Challenge ensemble of 62 simulations of historical climate conducted with the NCAR Community Climate System Model version 1.4 (CCSM1.4) GCM, as well as some simulations from other GCMs. Considerable uncertainty exists in the estimates of the parameters in fitted EBMs. Nevertheless, temporal response patterns from these EBMs are more reliable and the combined EBM time series closely mimics the GCM in the context of transient forcing. In particular, detection and attribution results from this technique appear self-consistent and consistent with results from other methods provided that all major forcings are included in the analysis. Using this technique on the Challenge ensemble, the estimated responses to changes in greenhouse gases, tropospheric sulfate aerosols, and stratospheric volcanic aerosols are all detected in the observed record, and the responses to the greenhouse gases and tropospheric sulfate aerosols are both consistent with the observed record without a scaling of the amplitude being required. The result is that the temperature difference of the 1996-2005 decade relative to the 1940-49 decade can be attributed to greenhouse gas emissions, with a partially offsetting cooling from sulfate emissions and little contribution from natural sources. The results support the viability of the new methodology as an extension to current analysis tools for the detection and attribution of climate change, which will allow the inclusion of many more GCMs. Shortcomings remain, however, and so it should not be considered a replacement to traditional techniques. © 2007 American Meteorological Society.


Millennial temperature reconstruction intercomparison and evaluation

Climate of the Past 3 (2007) 591-599

MN Juckes, MR Allen, KR Briffa, J Esper, GC Hegerl, A Moberg, TJ Osborn, SL Weber

There has been considerable recent interest in paleoclimate reconstructions of the temperature history of the last millennium. A wide variety of techniques have been used. The interrelation among the techniques is sometimes unclear, as different studies often use distinct data sources as well as distinct methodologies. Here recent work is reviewed and some new calculations performed with an aim to clarifying the consequences of the different approaches used. A range of proxy data collections introduced by different authors is used to estimate Northern Hemispheric annual mean temperatures with two reconstruction algorithms: (1) inverse regression and, (2) compositing followed by variance matching (CVM). It is found that inverse regression tends to give large weighting to a small number of proxies and that the second approach (CVM) is more robust to varying proxy input. The choice of proxy records is one reason why different reconstructions show different ranges. A reconstruction using 13 proxy records extending back to AD 1000 shows a maximum pre-industrial temperature of 0.25 K (relative to the 1866 to 1970 mean). The standard error on this estimate, based on the residual in the calibration period, is 0.14 K. Instrumental temperatures for two recent years (1998 and 2005) have exceeded the pre-industrial estimated maximum by more than 4 standard deviations of the calibration period residual.


Constraining climate sensitivity from the seasonal cycle in surface temperature

Journal of Climate 19 (2006) 4224-4233

R Knutti, GA Meehl, MR Allen, DA Stainforth

The estimated range of climate sensitivity has remained unchanged for decades, resulting in large uncertainties in long-term projections of future climate under increased greenhouse gas concentrations. Here the multi-thousand-member ensemble of climate model simulations from the climateprediction.net project and a neural network are used to establish a relation between climate sensitivity and the amplitude of the seasonal cycle in regional temperature. Most models with high sensitivities are found to overestimate the seasonal cycle compared to observations. A probability density function for climate sensitivity is then calculated from the present-day seasonal cycle in reanalysis and instrumental datasets. Subject to a number of assumptions on the models and datasets used, it is found that climate sensitivity is very unlikely (5% probability) to be either below 1.5-2 K or above about 5-6.5 K, with the best agreement found for sensitivities between 3 and 3.5 K. This range is narrower than most probabilistic estimates derived from the observed twentieth-century warming. The current generation of general circulation models are within that range but do not sample the highest values. © 2006 American Meteorological Society.


Incorporating model uncertainty into attribution of observed temperature change

Geophysical Research Letters 33 (2006)

C Huntingford, PA Stott, MR Allen, FH Lambert

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.


Alternatives to stabilization scenarios

Geophysical Research Letters 33 (2006)

DJ Frame, DJ Frame, DJ Frame, DA Stone, DA Stone, DA Stone, PA Stott, PA Stott, MR Allen, MR Allen

Studies attempting to constrain climate sensitivity, or equilibrium surface warming in response to a doubling of atmospheric carbon dioxide, by comparing models with observations report a wide range of distributions, particularly regarding the upper bound. There is, by contrast, a considerable consensus surrounding the transient climate response, in large part because it is directly related to observed warming attributable to greenhouse gases. We argue that scenarios which can exploit this consensus may be preferable to stabilization scenarios for practical policy-making purposes. The difficulty of ruling out a high equilibrium warming response to elevated carbon dioxide levels may provide an opportunity for reassessment of the stabilization scenario as the centerpiece of climate policy in favour of scenarios that are more directly constrained by the transient response. Copyright 2006 by the American Geophysical Union.


Observational constraints on past attributable warming and predictions of future global warming

Journal of Climate 19 (2006) 3055-3069

PA Stott, JFB Mitchell, MR Allen, TL Delworth, JM Gregory, JM Gregory, GA Meehl, BD Santer

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.


Quantifying anthropogenic influence on recent near-surface temperature change

Surveys in Geophysics 27 (2006) 491-544

MR Allen, NP Gillett, NP Gillett, JA Kettleborough, JA Kettleborough, G Hegerl, R Schnur, PA Stott, G Boer, C Covey, TL Delworth, GS Jones, JFB Mitchell, TP Barnett

We assess the extent to which observed large-scale changes in near-surface temperatures over the latter half of the twentieth century can be attributed to anthropogenic climate change as simulated by a range of climate models. The hypothesis that observed changes are entirely due to internal climate variability is rejected at a high confidence level independent of the climate model used to simulate either the anthropogenic signal or the internal variability. Where the relevant simulations are available, we also consider the alternative hypothesis that observed changes are due entirely to natural external influences, including solar variability and explosive volcanic activity. We allow for the possibility that feedback processes, other than those simulated by the models considered, may be amplifying the observed response to these natural influences by an unknown amount. Even allowing for this possibility, the hypothesis of no anthropogenic influence can be rejected at the 5% level in almost all cases. The influence of anthropogenic greenhouse gases emerges as a substantial contributor to recent observed climate change, with the estimated trend attributable to greenhouse forcing similar in magnitude to the total observed warming over the 20th century. Much greater uncertainty remains in the response to other external influences on climate, particularly the response to anthropogenic sulphate aerosols and to solar and volcanic forcing. Our results remain dependent on model-simulated signal patterns and internal variability, and would benefit considerably from a wider range of simulations, particularly of the responses to natural external forcing. © Springer Science+Business Media, Inc. 2006.


Uncertainty in continental-scale temperature predictions

Geophysical Research Letters 33 (2006)

PA Stott, JA Kettleborough, JA Kettleborough, MR Allen

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.


The end-to-end attribution problem: From emissions to impacts

Climatic Change 71 (2005) 303-318

DA Stone, MR Allen

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.


Constraints on climate change from a multi-thousand member ensemble of simulations

Geophysical Research Letters 32 (2005) 1-5

C Piani, DJ Frame, DA Stainforth, MR Allen

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.


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

Nature 433 (2005) 403-406

MR Allen, Carl Christensen, David A. Stainfrorth, Tolu Aina


Attribution of global surface warming without dynamical models

Geophysical Research Letters 32 (2005) 1-4

DA Stone, DA Stone, MR Allen

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.

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