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1.
Towards quantifying uncertainty in transient climate change   总被引：2，自引：3，他引：2  
Ensembles of coupled atmosphere–ocean global circulation model simulations are required to make probabilistic predictions of future climate change. “Perturbed physics” ensembles provide a new approach in which modelling uncertainties are sampled systematically by perturbing uncertain parameters. The aim is to provide a basis for probabilistic predictions in which the impact of prior assumptions and observational constraints can be clearly distinguished. Here we report on the first perturbed physics coupled atmosphere–ocean model ensemble in which poorly constrained atmosphere, land and sea-ice component parameters are varied in the third version of the Hadley Centre model (the variation of ocean parameters will be the subject of future study). Flux adjustments are employed, both to reduce regional sea surface temperature (SST) and salinity biases and also to admit the use of combinations of model parameter values which give non-zero values for the global radiation balance. This improves the extent to which the ensemble provides a credible basis for the quantification of uncertainties in climate change, especially at a regional level. However, this particular implementation of flux-adjustments leads to a weakening of the Atlantic overturning circulation, resulting in the development of biases in SST and sea ice in the North Atlantic and Arctic Oceans. Nevertheless, model versions are produced which are of similar quality to the unperturbed and un-flux-adjusted version. The ensemble is used to simulate pre-industrial conditions and a simple scenario of a 1% per year compounded increase in CO2. The range of transient climate response (the 20 year averaged global warming at the time of CO2 doubling) is 1.5–2.6°C, similar to that found in multi-model studies. Measures of global and large scale climate change from the coupled models show simple relationships with associated measures computed from atmosphere-mixed-layer-ocean climate change experiments, suggesting that recent advances in computing the probability density function of climate change under equilibrium conditions using the perturbed physics approach may be extended to the transient case.  相似文献   

2.
We explore the potential to improve understanding of the climate system by directly targeting climate model analyses at specific indicators of climate change impact. Using the temperature suitability of premium winegrape cultivation as a climate impacts indicator, we quantify the inter- and intra-ensemble spread in three climate model ensembles: a physically uniform multi-member ensemble consisting of the RegCM3 high-resolution climate model nested within the NCAR CCSM3 global climate model; the multi-model NARCCAP ensemble consisting of single realizations of multiple high-resolution climate models nested within multiple global climate models; and the multi-model CMIP3 ensemble consisting of realizations of multiple global climate models. We find that the temperature suitability for premium winegrape cultivation is substantially reduced throughout the high-value growing areas of California and the Columbia Valley region (eastern Oregon and Washington) in all three ensembles in response to changes in temperature projected for the mid-twenty first century period. The reductions in temperature suitability are driven primarily by projected increases in mean growing season temperature and occurrence of growing season severe hot days. The intra-ensemble spread in the simulated climate change impact is smaller in the single-model ensemble than in the multi-model ensembles, suggesting that the uncertainty arising from internal climate system variability is smaller than the uncertainty arising from climate model formulation. In addition, the intra-ensemble spread is similar in the NARCCAP nested climate model ensemble and the CMIP3 global climate model ensemble, suggesting that the uncertainty arising from the model formulation of fine-scale climate processes is not smaller than the uncertainty arising from the formulation of large-scale climate processes. Correction of climate model biases substantially reduces both the inter- and intra-ensemble spread in projected climate change impact, particularly for the multi-model ensembles, suggesting that—at least for some systems—the projected impacts of climate change could be more robust than the projected climate change. Extension of this impacts-based analysis to a larger suite of impacts indicators will deepen our understanding of future climate change uncertainty by focusing on the climate phenomena that most directly influence natural and human systems.  相似文献   

3.
Ocean dynamics play a key role in the climate system, by redistributing heat and freshwater. The uncertainty of how these processes are represented in climate models, and how this uncertainty affects future climate projections can be investigated using perturbed physics ensembles of global circulation models (GCMs). Techniques such as flux adjustments should be avoided since they can impact the sensitivity of the ensemble to the imposed forcing. In this study a method for developing an coupled ensemble with a GCM that does not use flux adjustment is presented. The ensemble is constrained by using information from a prior ensemble with a mixed layer ocean coupled to an atmosphere GCM, to reduce drifts in the coupled ensemble. Constraints on parameter perturbations are derived by using observational constraints on surface temperature, and top of the atmosphere radiative fluxes. As an example of such an ensemble developed with this methodology, uncertainty in response of the meridional overturning circulation (MOC) to increased CO2 concentrations is investigated. The ensemble mean MOC strength is 17.1?Sv and decreases by 2.1?Sv when greenhouse gas concentrations are doubled. No rapid changes or shutdown of the MOC are seen in any of the ensemble members. There is a strong negative relationship between global mean temperature and MOC strength across the ensemble which is not seen in a multimodel ensemble. A positive relationship between climate sensitivity and the decrease of MOC strength is also seen.  相似文献   

4.
Identifying uncertainties in Arctic climate change projections   总被引：2，自引：2，他引：0  
Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO2 doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change.  相似文献   

5.
We describe results from a 57-member ensemble of transient climate change simulations, featuring simultaneous perturbations to 54 parameters in the atmosphere, ocean, sulphur cycle and terrestrial ecosystem components of an earth system model (ESM). These emissions-driven simulations are compared against the CMIP3 multi-model ensemble of physical climate system models, used extensively to inform previous assessments of regional climate change, and also against emissions-driven simulations from ESMs contributed to the CMIP5 archive. Members of our earth system perturbed parameter ensemble (ESPPE) are competitive with CMIP3 and CMIP5 models in their simulations of historical climate. In particular, they perform reasonably well in comparison with HadGEM2-ES, a more sophisticated and expensive earth system model contributed to CMIP5. The ESPPE therefore provides a computationally cost-effective tool to explore interactions between earth system processes. In response to a non-intervention emissions scenario, the ESPPE simulates distributions of future regional temperature change characterised by wide ranges, and warm shifts, compared to those of CMIP3 models. These differences partly reflect the uncertain influence of global carbon cycle feedbacks in the ESPPE. In addition, the regional effects of interactions between different earth system feedbacks, particularly involving physical and ecosystem processes, shift and widen the ESPPE spread in normalised patterns of surface temperature and precipitation change in many regions. Significant differences from CMIP3 also arise from the use of parametric perturbations (rather than a multimodel ensemble) to represent model uncertainties, and this is also the case when ESPPE results are compared against parallel emissions-driven simulations from CMIP5 ESMs. When driven by an aggressive mitigation scenario, the ESPPE and HadGEM2-ES reveal significant but uncertain impacts in limiting temperature increases during the second half of the twenty-first century. Emissions-driven simulations create scope for development of errors in properties that were previously prescribed in coupled ocean–atmosphere models, such as historical CO2 concentrations and vegetation distributions. In this context, historical intra-ensemble variations in the airborne fraction of CO2 emissions, and in summer soil moisture in northern hemisphere continental regions, are shown to be potentially useful constraints, subject to uncertainties in the relevant observations. Our results suggest that future climate-related risks can be assessed more comprehensively by updating projection methodologies to support formal combination of emissions-driven perturbed parameter and multi-model earth system model simulations with suitable observational constraints. This would provide scenarios underpinned by a more complete representation of the chain of uncertainties from anthropogenic emissions to future climate outcomes.  相似文献   

6.
The MIT 2D climate model is used to make probabilistic projections for changes in global mean surface temperature and for thermosteric sea level rise under a variety of forcing scenarios. The uncertainties in climate sensitivity and rate of heat uptake by the deep ocean are quantified by using the probability distributions derived from observed twentieth century temperature changes. The impact on climate change projections of using the smallest and largest estimates of twentieth century deep ocean warming is explored. The impact is large in the case of global mean thermosteric sea level rise. In the MIT reference (“business as usual”) scenario the median rise by 2100 is 27 and 43 cm in the respective cases. The impact on increases in global mean surface air temperature is more modest, 4.9 and 3.9 C in the two respective cases, because of the correlation between climate sensitivity and ocean heat uptake required by twentieth century surface and upper air temperature changes. The results are also compared with the projections made by the IPCC AR4’s multi-model ensemble for several of the SRES scenarios. The multi-model projections are more consistent with the MIT projections based on the largest estimate of ocean warming. However, the range for the rate of heat uptake by the ocean suggested by the lowest estimate of ocean warming is more consistent with the range suggested by the twentieth century changes in surface and upper air temperatures, combined with the expert prior for climate sensitivity.  相似文献   

7.
Palaeoclimate simulations provide an opportunity for climate model evaluation as well as having a potential role in assigning relative likelihood to different ensemble members in probabilistic climate change prediction, supplementing constraints provided by the instrumental record. Here we take some initial steps towards such an approach by performing ensemble experiments with the Hadley Centre HadCM3 model under pre-industrial and mid-Holocene (6,000 years before present) forcing conditions. We examine the changes in both mean tropical climate and El Niño-Southern Oscillation (ENSO) variability, as palaeoclimate records suggest that ENSO amplitude was reduced in the mid-Holocene. Experiments are performed with perturbations to physical parameters in the atmosphere–surface component of the model, and with different implementations of heat and freshwater flux adjustments. Heat flux adjustments are required to stabilise model versions in which perturbations cause a net radiative imbalance. While we find broad agreement between different model versions in terms of changes in mean climate in the mid-Holocene, a detailed and quantitative comparison with the geographically-sparse palaeo-record is limited by systematic model biases. In the simulations without seasonally-varying flux adjustments there are modest reductions in ENSO amplitude of the order of 10–15%, lower than the range of reductions inferred from coral proxy records. We examine the mechanisms for these changes, and discuss the implications for the design of future ensemble experiments to formally quantify uncertainty in climate change predictions using palaeoclimate simulations.  相似文献   

8.
We examine the global mean surface temperature and carbon cycle responses to the A1B emissions scenario for a new 57 member perturbed-parameter ensemble of simulations generated using the fully coupled atmosphere-ocean-carbon cycle climate model HadCM3C. The model variants feature simultaneous perturbation to parameters that control atmosphere, ocean, land carbon cycle and sulphur cycle processes in this Earth system model, and is the first experiment of its kind. The experimental design, based on four earlier ensembles with parameters varied within each individual Earth system component, allows the effects of interactions between uncertainties in the different components to be explored. A large spread in response is obtained, with atmospheric CO2 at the end of the twenty-first century ranging from 615 to 1,100 ppm. On average though, the mean effect of the parameter perturbations is to significantly reduce the amount of atmospheric CO2 compared to that seen in the standard HadCM3C model. Global temperature change for 2090–2099 relative to the pre-industrial period ranges from 2.2 to 7.5 °C, with large temperature responses occurring when atmospheric model versions with high climate sensitivities are combined with carbon cycle components that emit large amounts of CO2 to the atmosphere under warming. A simple climate model, tuned to reproduce the responses of the separate Earth system component ensembles, is used to demonstrate that interactions between uncertainties in the different components play a significant role in determining the spread of responses in global mean surface temperature. This ensemble explores a wide range of interactions and response, and therefore provides a useful resource for the provision of regional climate projections and associated uncertainties.  相似文献   

9.
State-of-the-art coupled general circulation models(CGCMs)are used to predict ocean heat uptake(OHU)and sealevel change under global warming.However,the projections of different models vary,resulting in high uncertainty.Much of the inter-model spread is driven by responses to surface heat perturbations.This study mainly focuses on the response of the ocean to a surface heat flux perturbation F,as prescribed by the Flux-Anomaly-Forced Model Intercomparison Project(FAFMIP).The results of ocean model were compared with those of a CGCM with the same ocean component.On the global scale,the changes in global mean temperature,ocean heat content(OHC),and steric sea level(SSL)simulated in the OGCM are generally consistent with CGCM simulations.Differences in changes in ocean temperature,OHC,and SSL between the two models primarily occur in the Arctic and Atlantic Oceans(AA)and the Southern Ocean(SO)basins.In addition to the differences in surface heat flux anomalies between the two models,differences in heat exchange between basins also play an important role in the inconsistencies in ocean climate changes in the AA and SO basins.These discrepancies are largely due to both the larger initial value and the greater weakening change of the Atlantic meridional overturning circulation(AMOC)in CGCM.The greater weakening of the AMOC in the CGCM is associated with the atmosphere–ocean feedback and the lack of a restoring salinity boundary condition.Furthermore,differences in surface salinity boundary conditions between the two models contribute to discrepancies in SSL changes.  相似文献   

10.
Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO2 and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.  相似文献   

11.

Sea levels of different atmosphere–ocean general circulation models (AOGCMs) respond to climate change forcing in different ways, representing a crucial uncertainty in climate change research. We isolate the role of the ocean dynamics in setting the spatial pattern of dynamic sea-level (ζ) change by forcing several AOGCMs with prescribed identical heat, momentum (wind) and freshwater flux perturbations. This method produces a ζ projection spread comparable in magnitude to the spread that results from greenhouse gas forcing, indicating that the differences in ocean model formulation are the cause, rather than diversity in surface flux change. The heat flux change drives most of the global pattern of ζ change, while the momentum and water flux changes cause locally confined features. North Atlantic heat uptake causes large temperature and salinity driven density changes, altering local ocean transport and ζ. The spread between AOGCMs here is caused largely by differences in their regional transport adjustment, which redistributes heat that was already in the ocean prior to perturbation. The geographic details of the ζ change in the North Atlantic are diverse across models, but the underlying dynamic change is similar. In contrast, the heat absorbed by the Southern Ocean does not strongly alter the vertically coherent circulation. The Arctic ζ change is dissimilar across models, owing to differences in passive heat uptake and circulation change. Only the Arctic is strongly affected by nonlinear interactions between the three air-sea flux changes, and these are model specific.

  相似文献   

12.
We present the implementation and results of a model tuning and ensemble forecasting experiment using an ensemble Kalman filter for the simultaneous estimation of 12 parameters in a low resolution coupled atmosphere-ocean Earth System Model by tuning it to realistic data sets consisting of Levitus ocean temperature/salinity climatology, and NCEP/NCAR atmospheric temperature/humidity reanalysis data. The resulting ensemble of tuned model states is validated by comparing various diagnostics, such as mass and heat transports, to observational estimates and other model results. We show that this ensemble has a very reasonable climatology, with the 3-D ocean in particular having comparable realism to much more expensive coupled numerical models, at least in respect of these averaged indicators. A simple global warming experiment is performed to investigate the response and predictability of the climate to a change in radiative forcing, due to 100 years of 1% per annum atmospheric CO2 increase. The equilibrium surface air temperature rise for this CO2 increase is 4.2±0.1°C, which is approached on a time scale of 1,000 years. The simple atmosphere in this version of the model is missing several factors which, if included, would substantially increase the uncertainty of this estimate. However, even within this ensemble, there is substantial regional variability due to the possibility of collapse of the North Atlantic thermohaline circulation (THC), which switches off in more than one third of the ensemble members. For these cases, the regional temperature is not only 3–5°C colder than in the warmed worlds where the THC remains switched on, but is also 1–2°C colder than the current climate. Our results, which illustrate how objective probabilistic projections of future climate change can be efficiently generated, indicate a substantial uncertainty in the long-term future of the THC, and therefore the regional climate of western Europe. However, this uncertainty is only apparent in long-term integrations, with the initial transient response being similar across the entire ensemble. Application of this ensemble Kalman filtering technique to more complete climate models would improve the objectivity of probabilistic forecasts and hence should lead to significantly increased understanding of the uncertainty of our future climate.  相似文献   

13.
In this study, we constructed a perturbed physics ensemble (PPE) for the MIROC5 coupled atmosphere–ocean general circulation model (CGCM) to investigate the parametric uncertainty of climate sensitivity (CS). Previous studies of PPEs have mainly used the atmosphere-slab ocean models. A few PPE studies using a CGCM applied flux corrections, because perturbations in parameters can lead to large radiation imbalances at the top of the atmosphere and climate drifts. We developed a method to prevent climate drifts in PPE experiments using the MIROC5 CGCM without flux corrections. We simultaneously swept 10 parameters in atmosphere and surface schemes. The range of CS (estimated from our 35 ensemble members) was not wide (2.2–3.2?°C). The shortwave cloud feedback related to changes in middle-level cloud albedo dominated the variations in the total feedback. We found three performance metrics for the present climate simulations of middle-level cloud albedo, precipitation, and ENSO amplitude that systematically relate to the variations in shortwave cloud feedback in this PPE.  相似文献   

14.
This paper describes a Bayesian methodology for prediction of multivariate probability distribution functions (PDFs) for transient regional climate change. The approach is based upon PDFs for the equilibrium response to doubled carbon dioxide, derived from a comprehensive sampling of uncertainties in modelling of surface and atmospheric processes, and constrained by multiannual mean observations of recent climate. These PDFs are sampled and scaled by global mean temperature predicted by a Simple Climate Model (SCM), in order to emulate corresponding transient responses. The sampled projections are then reweighted, based upon the likelihood that they correctly replicate observed historical changes in surface temperature, and combined to provide PDFs for 20 year averages of regional temperature and precipitation changes to the end of the twenty-first century, for the A1B emissions scenario. The PDFs also account for modelling uncertainties associated with aerosol forcing, ocean heat uptake and the terrestrial carbon cycle, sampled using SCM configurations calibrated to the response of perturbed physics ensembles generated using the Hadley Centre climate model HadCM3, and other international climate model simulations. Weighting the projections using observational metrics of recent mean climate is found to be as effective at constraining the future transient response as metrics based on historical trends. The spread in global temperature response due to modelling uncertainty in the carbon cycle feedbacks is determined to be about 65–80 % of the spread arising from uncertainties in modelling atmospheric, oceanic and aerosol processes of the climate system. Early twenty-first century aerosol forcing is found to be extremely unlikely to be less than ?1.7 W m?2. Our technique provides a rigorous and formal method of combining several lines of evidence used in the previous IPCC expert assessment of the Transient Climate Response. The 10th, 50th and 90th percentiles of our observationally constrained PDF for the Transient Climate Response are 1.6, 2.0 and 2.4 °C respectively, compared with the 10–90 % range of 1.0–3.0 °C assessed by the IPCC.  相似文献   

15.
Large ensembles of coupled atmosphere–ocean general circulation model (AOGCM) simulations are required to explore modelling uncertainty and make probabilistic predictions of future transient climate change at regional scales. These are not yet computationally feasible so we have developed a technique to emulate the response of such an ensemble by scaling equilibrium patterns of climate change derived from much cheaper “slab” model ensembles in which the atmospheric component of an AOGCM is coupled to a mixed-layer ocean. Climate feedback parameters are diagnosed for each member of a slab model ensemble and used to drive an energy balance model (EBM) to predict the time-dependent response of global surface temperature expected for different combinations of uncertain AOGCM parameters affecting atmospheric, land and sea-ice processes. The EBM projections are then used to scale normalised patterns of change derived for each slab member, and hence emulate the response of the relevant atmospheric model version when coupled to a dynamic ocean, in response to a 1% per annum increase in CO2. The emulated responses are validated by comparison with predictions from a 17 member ensemble of AOGCM simulations, constructed from variants of HadCM3 using the same parameter combinations as 17 members of the slab model ensemble. Cross-validation permits estimation of the spatial and temporal dependence of emulation error, and also allows estimation of a correction field to correct discrepancies between the scaled equilibrium patterns and the transient response, reducing the emulation error. Emulated transient responses and their associated errors are obtained from the slab ensemble for 129 pseudo-HadCM3 versions containing multiple atmospheric parameter perturbations. These are combined to produce regional frequency distributions for the transient response of annual surface temperature change and boreal winter precipitation change. The technique can be extended to any surface climate variable demonstrating a scaleable, approximately linear response to forcing.  相似文献   

16.
The majority of climate change impacts assessments account for climate change uncertainty by adopting the scenario-based approach. This typically involves assessing the impacts for a small number of emissions scenarios but neglecting the role of climate model physics uncertainty. Perturbed physics ensemble (PPE) climate simulations offer a unique opportunity to explore this uncertainty. Furthermore, PPEs mean it is now possible to make risk-based impacts estimates because they allow for a range of estimates to be presented to decision-makers, which spans the range of climate model physics uncertainty inherent from a given climate model and emissions scenario, due to uncertainty associated with the understanding of physical processes in the climate model. This is generally not possible with the scenario-based approach. Here, we present the first application of a PPE to estimate the impact of climate change on heat-related mortality. By using the estimated impacts of climate change on heat-related mortality in six cities, we demonstrate the benefits of quantifying climate model physics uncertainty in climate change impacts assessment over the more common scenario-based approach. We also show that the impacts are more sensitive to climate model physics uncertainty than they are to emissions scenario uncertainty, and least sensitive to whether the climate change projections are from a global climate model or a regional climate model. The results demonstrate the importance of presenting model uncertainties in climate change impacts assessments if the impacts are to be placed within a climate risk management framework.  相似文献   

17.
The global and regional projected changes in tropical cyclone (TC) genesis due to increased CO2 concentrations has been investigated through a large-scale TC genesis parameter (convective seasonal genesis parameter, ConvGP) in two perturbed physics ensembles. The ensembles are based on the third generation Hadley Centre atmosphere?Cocean general circulation model with the first ensemble using a coupled fully dynamic ocean (HadCM3) and the second coupled to a simplified mixed layer thermodynamic ocean (HadSM3) both consisting of 17 members. In each ensemble, parameters are identically perturbed to provide a wide range of climate sensitivity whilst retaining a credible present-day climate simulation. It is found, by comparing the ConvGP climatology from reanalysis data with the best track genesis, that it is possible to reproduce the observed genesis distribution. Future changes in the spatial ConvGP distribution are explored with respect to each tropical ocean basin. Whilst there is a similarity in the gross pattern of the ensemble-mean projected ConvGP change between HadCM3 and HadSM3, there is a non-trivial difference in the tropical Pacific Ocean, arising from different patterns of tropical Pacific sea surface temperature change. This indicates that ocean representation can be important for regional scale projections. The quantitative contribution of individual constituent parameters (i.e. vorticity parameter, shear parameter and convective potential) to the projected ConvGP change is estimated. It is found that all three large-scale parameters generally contribute constructively, but with different magnitude, in the regions where a large doubled CO2 response is found.  相似文献   

18.
Probabilistic climate change projections using neural networks   总被引：5，自引：0，他引：5  
Anticipated future warming of the climate system increases the need for accurate climate projections. A central problem are the large uncertainties associated with these model projections, and that uncertainty estimates are often based on expert judgment rather than objective quantitative methods. Further, important climate model parameters are still given as poorly constrained ranges that are partly inconsistent with the observed warming during the industrial period. Here we present a neural network based climate model substitute that increases the efficiency of large climate model ensembles by at least an order of magnitude. Using the observed surface warming over the industrial period and estimates of global ocean heat uptake as constraints for the ensemble, this method estimates ranges for climate sensitivity and radiative forcing that are consistent with observations. In particular, negative values for the uncertain indirect aerosol forcing exceeding –1.2 Wm–2 can be excluded with high confidence. A parameterization to account for the uncertainty in the future carbon cycle is introduced, derived separately from a carbon cycle model. This allows us to quantify the effect of the feedback between oceanic and terrestrial carbon uptake and global warming on global temperature projections. Finally, probability density functions for the surface warming until year 2100 for two illustrative emission scenarios are calculated, taking into account uncertainties in the carbon cycle, radiative forcing, climate sensitivity, model parameters and the observed temperature records. We find that warming exceeds the surface warming range projected by IPCC for almost half of the ensemble members. Projection uncertainties are only consistent with IPCC if a model-derived upper limit of about 5 K is assumed for climate sensitivity.  相似文献   

19.
Ensembles of climate model simulations are required for input into probabilistic assessments of the risk of future climate change in which uncertainties are quantified. Here we document and compare aspects of climate model ensembles from the multi-model archive and from perturbed physics ensembles generated using the third version of the Hadley Centre climate model (HadCM3). Model-error characteristics derived from time-averaged two-dimensional fields of observed climate variables indicate that the perturbed physics approach is capable of sampling a relatively wide range of different mean climate states, consistent with simple estimates of observational uncertainty and comparable to the range of mean states sampled by the multi-model ensemble. The perturbed physics approach is also capable of sampling a relatively wide range of climate forcings and climate feedbacks under enhanced levels of greenhouse gases, again comparable with the multi-model ensemble. By examining correlations between global time-averaged measures of model error and global measures of climate change feedback strengths, we conclude that there are no simple emergent relationships between climate model errors and the magnitude of future global temperature change. Algorithms for quantifying uncertainty require the use of complex multivariate metrics for constraining projections.  相似文献   

20.
We have characterized the relative contributions to uncertainty in predictions of global warming amount by year 2100 in the C4MIP model ensemble ( Friedlingstein et al., 2006 ) due to both carbon cycle process uncertainty and uncertainty in the physical climate properties of the Earth system. We find carbon cycle uncertainty to be important. On average the spread in transient climate response is around 40% of that due to the more frequently debated uncertainties in equilibrium climate sensitivity and global heat capacity.
This result is derived by characterizing the influence of different parameters in a global climate-carbon cycle 'box' model that has been calibrated against the 11 General Circulation models (GCMs) and Earth system Models of Intermediate Complexity (EMICs) in the C4MIP ensemble; a collection of current state-of-the-art climate models that include an explicit representation of the global carbon cycle.  相似文献   

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