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1.
Three simple climate models (SCMs) are calibrated using simulations from atmosphere ocean general circulation models (AOGCMs). In addition to using two conventional SCMs, results from a third simpler model developed specifically for this study are obtained. An easy to implement and comprehensive iterative procedure is applied that optimises the SCM emulation of global-mean surface temperature and total ocean heat content, and, if available in the SCM, of surface temperature over land, over the ocean and in both hemispheres, and of the global-mean ocean temperature profile. The method gives best-fit estimates as well as uncertainty intervals for the different SCM parameters. For the calibration, AOGCM simulations with two different types of forcing scenarios are used: pulse forcing simulations performed with 2 AOGCMs and gradually changing forcing simulations from 15 AOGCMs obtained within the framework of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The method is found to work well. For all possible combinations of SCMs and AOGCMs the emulation of AOGCM results could be improved. The obtained SCM parameters depend both on the AOGCM data and the type of forcing scenario. SCMs with a poor representation of the atmosphere thermal inertia are better able to emulate AOGCM results from gradually changing forcing than from pulse forcing simulations. Correct simultaneous emulation of both atmospheric temperatures and the ocean temperature profile by the SCMs strongly depends on the representation of the temperature gradient between the atmosphere and the mixed layer. Introducing climate sensitivities that are dependent on the forcing mechanism in the SCMs allows the emulation of AOGCM responses to carbon dioxide and solar insolation forcings equally well. Also, some SCM parameters are found to be very insensitive to the fitting, and the reduction of their uncertainty through the fitting procedure is only marginal, while other parameters change considerably. The very simple SCM is found to reproduce the AOGCM results as well as the other two comparably more sophisticated SCMs.  相似文献   

2.
We analyze ensembles (four realizations) of historical and future climate transient experiments carried out with the coupled atmosphere-ocean general circulation model (AOGCM) of the Hadley Centre for Climate Prediction and Research, version HADCM2, with four scenarios of greenhouse gas (GHG) and sulfate forcing. The analysis focuses on the regional scale, and in particular on 21 regions covering all land areas in the World (except Antarctica). We examine seasonally averaged surface air temperature and precipitation for the historical period of 1961–1990 and the future climate period of 2046–2075. Compared to previous AOGCM simulations, the HADCM2 model shows a good performance in reproducing observed regional averages of summer and winter temperature and precipitation. The model, however, does not reproduce well observed interannual variability. We find that the uncertainty in regional climate change predictions associated with the spread of different realizations in an ensemble (i.e. the uncertainty related to the internal model variability) is relatively low for all scenarios and regions. In particular, this uncertainty is lower than the uncertainty due to inter-scenario variability and (by comparison with previous regional analyses of AOGCMs) with inter-model variability. The climate biases and sensitivities found for different realizations of the same ensemble were similar to the corresponding ensemble averages and the averages associated with individual realizations of the same ensemble did not differ from each other at the 5% confidence level in the vast majority of cases. These results indicate that a relatively small number of realizations (3 or 4) is sufficient to characterize an AOGCM transient climate change prediction at the regional scale. Received: 12 January 1998 / Accepted: 7 July 1999  相似文献   

3.
 The Hadley Centre coupled ocean-atmosphere general circulation model (AOGCM) has been used to study the effect of including the historical increase in greenhouse gases from 1860 to 1990 on the response to a subsequent 1% per year increase in CO2. Results from an ensemble of four experiments which include the historical increase, warm start (WS) experiments, are compared with an ensemble of four experiments which do not include the historical increase, cold start (CS) experiments. In the WS experiments, oceanic thermal inertia prevents the model from reaching equilibrium with the historical change in forcing from 1860 to 1990. This implies an unrealised warming at 1990, defined here as the ‘warming commitment’, increasing the subsequent warming in WS relative to that in CS. The difference in response between a WS experiment and a CS experiment is defined as the cold start error. For surface temperature the ensemble-mean cold start error is 20% of the WS response after year 30 and 10% at the time of doubling CO2 (year 70). For sea level the reduction in the CS response is more pronounced, amounting to 60% at year 30 and 40% at the time of doubling. The vertical transfer of heat in the ocean is found to correspond to an equivalent diffusion process. This result supports the use of simple ocean models with constant diffusivity to produce time-dependent scenarios of globally averaged climate change, subject to the caveat that the changes in ocean circulation simulated by the present AOGCM were smaller than in some previous cases. In the WS integrations the vertical temperature gradient is larger than in CS due to the historical forcing influence, leading to more efficient heat loss from the base of the mixed layer and hence a larger effective heat capacity. This explains why the cold start error for surface temperature is smaller than for sea level. By year 50 the global patterns of temperature change in individual integrations are highly correlated in both the WS and CS ensembles, indicating that natural variability is too small to conceal the climate change signal. The simulated regional changes are statistically significant almost everywhere after 30 y. Before year 30, when the signal-to-noise ratio is smaller, ensemble averaging the changes leads to a substantial increase in significance. In contrast to a previous study also based on an ensemble of integrations, significant changes in precipitation and soil moisture are found. For these quantities the area of significant change grows more slowly with time, however ensemble averaging increases the significant area throughout. The characteristic patterns of change in WS and CS are similar, and evident in the simulation of the past record. This suggests that the component of the historical patterns of change, driven by greenhouse gas forcing, is likely to bear significant similarities to the patterns expected in the future. However, significant regional differences do develop between the WS and CS ensembles. The cold start error has a non-uniform pattern which becomes established in the second half of the experiment, and is not a simple amplification or modulation of the CS or WS response pattern. In northern summer the warming and drying over parts of the Northern Hemisphere continents is larger in CS than in WS, due to a smaller net moisture flux from sea to land. The conclusions are: (1) climate predictions should be based on warm start experiments in order to obtain the best estimates of future changes; (2) ensemble means give predictions of regional changes which are statistically more robust than predictions from individual integrations. Note, however, that neither the removal of the cold start error nor the use of ensemble averaging can reduce uncertainties in the regional changes arising from model deficiencies, which remain considerable at the present stage of development. Received: 28 March 1997 / Accepted: 16 June 1997  相似文献   

4.
 We present a method for constraining key properties of the climate system that are important for climate prediction (climate sensitivity and rate of heat penetration into the deep ocean) by comparing a model's response to known forcings over the twentieth century against climate observations for that period. We use the MIT 2D climate model in conjunction with results from the Hadley Centre's coupled atmosphere–ocean general circulation model (AOGCM) to determine these constraints. The MIT 2D model, which is a zonally averaged version of a 3D GCM, can accurately reproduce the global-mean transient response of coupled AOGCMs through appropriate choices of the climate sensitivity and the effective rate of diffusion of heat anomalies into the deep ocean. Vertical patterns of zonal mean temperature change through the troposphere and lower stratosphere also compare favorably with those generated by 3-D GCMs. We compare the height–latitude pattern of temperature changes as simulated by the MIT 2D model with observed changes, using optimal fingerprint detection statistics. Using a linear regression model as in Allen and Tett this approach yields an objective measure of model-observation goodness-of-fit (via the residual sum of squares weighted by differences expected due to internal variability). The MIT model permits one to systematically vary the model's climate sensitivity (by varying the strength of the cloud feedback) and rate of mixing of heat into the deep ocean and determine how the goodness-of-fit with observations depends on these factors. This provides an efficient framework for interpreting detection and attribution results in physical terms. With aerosol forcing set in the middle of the IPCC range, two sets of model parameters are rejected as being implausible when the model response is compared with observations. The first set corresponds to high climate sensitivity and slow heat uptake by the deep ocean. The second set corresponds to low sensitivities for all magnitudes of heat uptake. These results demonstrate that fingerprint patterns must be carefully chosen, if their detection is to reduce the uncertainty of physically important model parameters which affect projections of climate change. Received: 19 April 2000 / Accepted: 13 April 2001  相似文献   

5.
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   

6.
A flexible climate model for use in integrated assessments   总被引：2，自引：0，他引：2  
 Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model’s sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO2 are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM for a variety of transient forcing scenarios. Both surface warming and sea level rise due to thermal expansion of the deep ocean in response to a gradually increasing forcing are reasonably reproduced on time scales of 100–150 y. However a wide range of diffusion coefficients is needed to match the behavior of different AOGCMs. We use results of simulations with the 2-D model to show that the impact on climate change of the implied uncertainty in the rate of heat penetration into the deep ocean is comparable with that of other significant uncertainties. Received: 10 March 1997 / Accepted: 20 October 1997  相似文献   

7.
An analytic solution of an energy balance model (EBM) is presented which can beused as a recursive filter for time series analysis. It is shown that the EBM can reproduce the solution of a coupled atmosphere-ocean general circulation model (AOGCM) experiment. Contrary to the AOGCM, the EBM easily allows for variations in climate sensitivity to satisfy the full range of uncertainty concerned with this parameter. The recursive filter is applied to two natural and two anthropogenic forcing mechanisms which are expressed in terms of heating rate anomaly time series: volcanism, solar activity, greenhouse gases (GHG), and anthropogenic tropospheric aerosols. Thus, we obtain modelled global mean temperature variations as a response to the different forcings and with respect to the uncertainty in the forcing approximations and climate sensitivity. In addition, it is shown that the observed (ENSO-corrected) global mean temperature time series within the period from 1866 to 1997 can be explained by the external forcings which have been considered and an additional white noise forcing. In this way we are able to separate different signals and compare them. As a result, global anthropogenic climate change due to GHG forcing can be detected at a high level of significance without considering spatial patterns of climate change but including natural forcing, which is usually not done. Furthermore, it is shown that solar forcing alone does not lead to significantclimate change, whereas solar and volcanic forcing together lead to a significant natural climate change signal. Anthropogenic climate change due to GHG forcing may partly be masked by anthropogenic aerosol cooling.  相似文献   

8.
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   

9.
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   

10.
To downscale climate change scenarios, long-term regional climatologies employing global model forcing are needed for West Africa. As a first step, this work examines present-day integrations (1981–2000) with a regional climate model (RCM) over West Africa nested in both reanalysis data and output from a coupled atmospheric–ocean general circulation model (AOGCM). Precipitation and temperature from both simulations are compared to the Climate Research Unit observations. Their spatial distributions are shown to be realistic. Annual cycles are considerably correlated. Simulations are also evaluated with respect to the driving large-scale fields. RCM offers some improvements compared to the AOGCM driving field. Evaluation of seasonal precipitation biases reveals that RCM dry biases are highest on June–August around mountains. They are associated to cold biases in temperature which, in turn, are connected to wet biases in precipitation outside orographic zones. Biases brought through AOGCM forcing are relatively low. Despite these errors, the simulations produce encouraging results and show the ability of the AOGCM to drive the RCM for future projections.  相似文献   

11.
Simulated variability and trends in Northern Hemisphere seasonal snow cover are analyzed in large ensembles of climate integrations of the National Center for Atmospheric Research’s Community Earth System Model. Two 40-member ensembles driven by historical radiative forcings are generated, one coupled to a dynamical ocean and the other driven by observed sea surface temperatures (SSTs) over the period 1981–2010. The simulations reproduce many aspects of the observed climatology and variability of snow cover extent as characterized by the NOAA snow chart climate data record. Major features of the simulated snow water equivalent (SWE) also agree with observations (GlobSnow Northern Hemisphere SWE data record), although with a lesser degree of fidelity. Ensemble spread in the climate response quantifies the impact of natural climate variability in the presence and absence of coupling to the ocean. Both coupled and uncoupled ensembles indicate an overall decrease in springtime snow cover that is consistent with observations, although springtime trends in most climate realizations are weaker than observed. In the coupled ensemble, a tendency towards excessive warming in wintertime leads to a strong wintertime snow cover loss that is not found in observations. The wintertime warming bias and snow cover reduction trends are reduced in the uncoupled ensemble with observed SSTs. Natural climate variability generates widely different regional patterns of snow trends across realizations; these patterns are related in an intuitive way to temperature, precipitation and circulation trends in individual realizations. In particular, regional snow loss over North America in individual realizations is strongly influenced by North Pacific SST trends (manifested as Pacific Decadal Oscillation variability) and by sea level pressure trends in the North Pacific/North Atlantic sectors.  相似文献   

12.
Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.  相似文献   

13.
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   

14.
 We demonstrate that a hemispherically averaged upwelling-diffusion energy-balance climate model (UD/EBM) can emulate the surface air temperature change and sea-level rise due to thermal expansion, predicted by the HadCM2 coupled atmosphere-ocean general circulation model, for various scenarios of anthropogenic radiative forcing over 1860–2100. A climate sensitivity of 2.6 °C is assumed, and a representation of the effect of sea-ice retreat on surface air temperature is required. In an extended experiment, with CO2 concentration held constant at twice the control run value, the HadCM2 effective climate sensitivity is found to increase from about 2.0 °C at the beginning of the integration to 3.85 °C after 900 years. The sea-level rise by this time is almost 1.0 m and the rate of rise fairly steady, implying that the final equilibrium value (the `commitment') is large. The base UD/EBM can fit the 900-year simulation of surface temperature change and thermal expansion provided that the time-dependent climate sensitivity is specified, but the vertical profile of warming in the ocean is not well reproduced. The main discrepancy is the relatively large mid-depth warming in the HadCM2 ocean, that can be emulated by (1) diagnosing depth-dependent diffusivities that increase through time; (2) diagnosing depth-dependent diffusivities for a pure-diffusion (zero upwelling) model; or (3) diagnosing higher depth-dependent diffusivities that are applied to temperature perturbations only. The latter two models can be run to equilibrium, and with a climate sensitivity of 3.85 °C, they give sea-level rise commitments of 1.7 m and 1.3 m, respectively. Received: 27 April 1999 / Accepted: 13 September 2000  相似文献   

15.
A regional climate model (RCM) constrained by future anomalies averaged from atmosphere–ocean general circulation model (AOGCM) simulations is used to generate mid-twenty-first century climate change predictions at 30-km resolution over the central U.S. The predictions are compared with those from 15 AOGCM and 7 RCM dynamic downscaling simulations to identify common climate change signals. There is strong agreement among the multi-model ensemble in predicting wetter conditions in April and May over the northern Great Plains and drier conditions over the southern Great Plains in June through August for the mid-twenty-first century. Projected changes in extreme daily precipitation are statistically significant over only a limited portion of the central U.S. in the RCM constrained with future anomalies. Projected changes in monthly mean 2-m air temperature are generally consistent across the AOGCM ensemble average, North American Regional Climate Change Assessment Program RCM ensemble average, and RCM constrained with future anomalies, which produce a maximum increase in August of 2.4–2.9 K over the northern and southern Great Plains and Midwest. Changes in extremes in daily 2-m air temperature from the RCM downscaled with anomalies are statistically significant over nearly the entire Great Plains and Midwest and indicate a positive shift in the warm tail of the daily 2-m temperature distribution that is larger than the positive shift in the cold tail.  相似文献   

16.
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   

17.
The use of radiative kernels to diagnose climate feedbacks is a recent development that may be applied to existing climate change simulations. We apply the radiative kernel technique to transient simulations from a multi-thousand member perturbed physics ensemble of coupled atmosphere-ocean general circulation models, comparing distributions of model feedbacks with those taken from the CMIP-3 multi GCM ensemble. Although the range of clear sky longwave feedbacks in the perturbed physics ensemble is similar to that seen in the multi-GCM ensemble, the kernel technique underestimates the net clear-sky feedbacks (or the radiative forcing) in some perturbed models with significantly altered humidity distributions. In addition, the compensating relationship between global mean atmospheric lapse rate feedback and water vapor feedback is found to hold in the perturbed physics ensemble, but large differences in relative humidity distributions in the ensemble prevent the compensation from holding at a regional scale. Both ensembles show a similar range of response of global mean net cloud feedback, but the mean of the perturbed physics ensemble is shifted towards more positive values such that none of the perturbed models exhibit a net negative cloud feedback. The perturbed physics ensemble contains fewer models with strong negative shortwave cloud feedbacks and has stronger compensating positive longwave feedbacks. A principal component analysis used to identify dominant modes of feedback variation reveals that the perturbed physics ensemble produces very different modes of climate response to the multi-model ensemble, suggesting that one may not be used as an analog for the other in estimates of uncertainty in future response. Whereas in the multi-model ensemble, the first order variation in cloud feedbacks shows compensation between longwave and shortwave components, in the perturbed physics ensemble the shortwave feedbacks are uncompensated, possibly explaining the larger range of climate sensitivities observed in the perturbed simulations. Regression analysis suggests that the parameters governing cloud formation, convection strength and ice fall speed are the most significant in altering climate feedbacks. Perturbations of oceanic and sulfur cycle parameters have relatively little effect on the atmospheric feedbacks diagnosed by the kernel technique.  相似文献   

18.
A simple idealized atmosphere–ocean climate model and an ensemble Kalman filter are used to explore different coupled ensemble data assimilation strategies. The model is a low-dimensional analogue of the North Atlantic climate system, involving interactions between large-scale atmospheric circulation and ocean states driven by the variability of the Atlantic meridional overturning circulation (MOC). Initialization of the MOC is assessed in a range of experiments, from the simplest configuration consisting of forcing the ocean with a known atmosphere to performing fully coupled ensemble data assimilation. “Daily” assimilation (that is, at the temporal frequency of the atmospheric observations) is contrasted with less frequent assimilation of time-averaged observations. Performance is also evaluated under scenarios in which ocean observations are limited to the upper ocean or are non-existent. Results show that forcing the idealized ocean model with atmospheric analyses is inefficient at recovering the slowly evolving MOC. On the other hand, daily assimilation rapidly leads to accurate MOC analyses, provided a comprehensive set of oceanic observations is available for assimilation. In the absence of sufficient observations in the ocean, the assimilation of time-averaged atmospheric observations proves to be more effective for MOC initialization, including the case where only atmospheric observations are available.  相似文献   

19.
We analyse the differences in the properties of the El Niño Southern Oscillation (ENSO) in a set of 17 coupled integrations with the flux-adjusted, 19-level HadCM3 model with perturbed atmospheric parameters. Within this ensemble, the standard deviation of the NINO3.4 deseasonalised SSTs ranges from 0.6 to 1.3 K. The systematic changes in the properties of the ENSO with increasing amplitude confirm that ENSO in HadCM3 is prevalently a surface (or SST) mode. The tropical-Pacific SST variability in the ensemble of coupled integrations correlates positively with the SST variability in the corresponding ensemble of atmosphere models coupled with a static mixed-layer ocean (“slab” models) perturbed with the same changes in atmospheric parameters. Comparison with the respective coupled ENSO-neutral climatologies and with the slab-model climatologies indicates low-cloud cover to be an important controlling factor of the strength of the ENSO within the ensemble. Our analysis suggests that, in the HadCM3 model, increased SST variability localised in the south-east tropical Pacific, not originating from ENSO and associated with increased amounts of tropical stratocumulus cloud, causes increased ENSO variability via an atmospheric bridge mechanism. The relationship with cloud cover also results in a negative correlation between the ENSO activity and the model’s climate sensitivity to doubling CO2.  相似文献   

20.
A method for simulating future climate on regional space scales is developed and applied to northern Africa. Simulation with a regional model allows for the horizontal resolution needed to resolve the region’s strong meridional gradients and the optimization of parameterizations and land-surface model. The control simulation is constrained by reanalysis data, and realistically represents the present day climate. Atmosphere–ocean general circulation model (AOGCM) output provides SST and lateral boundary condition anomalies for 2081–2100 under a business-as-usual emissions scenario, and the atmospheric CO2 concentration is increased to 757 ppmv. A nine-member ensemble of future climate projections is generated by using output from nine AOGCMs. The consistency of precipitation projections for the end of the twenty-first century is much greater for the regional model ensemble than among the AOGCMs. More than 77% of ensemble members produce the same sign rainfall anomaly over much of northern Africa. For West Africa, the regional model projects wetter conditions in spring, but a mid-summer drought develops during June and July, and the heat stoke risk increases across the Sahel. Wetter conditions resume in late summer, and the likelihood of flooding increases. The regional model generally projects wetter conditions over eastern Central Africa in June and drying during August through September. Severe drought impacts parts of East Africa in late summer. Conditions become wetter in October, but the enhanced rainfall does not compensate for the summertime deficit. The risk of heat stroke increases over this region, although the threat is not projected to be as great as in the Sahel.  相似文献   

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