Emulating AOGCM results using simple climate models

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.     

Inferring climate sensitivity from volcanic events

The possibility of estimating the equilibrium climate sensitivity of the earth-system from observations following explosive volcanic eruptions is assessed in the context of a perfect model study. Two modern climate models (the CCCma CGCM3 and the NCAR CCSM2) with different equilibrium climate sensitivities are employed in the investigation. The models are perturbed with the same transient volcano-like forcing and the responses analysed to infer climate sensitivities. For volcano-like forcing the global mean surface temperature responses of the two models are very similar, despite their differing equilibrium climate sensitivities, indicating that climate sensitivity cannot be inferred from the temperature record alone even if the forcing is known. Equilibrium climate sensitivities can be reasonably determined only if both the forcing and the change in heat storage in the system are known very accurately. The geographic patterns of clear-sky atmosphere/surface and cloud feedbacks are similar for both the transient volcano-like and near-equilibrium constant forcing simulations showing that, to a considerable extent, the same feedback processes are invoked, and determine the climate sensitivity, in both cases.     

Response to the eruption of Mount Pinatubo in relation to climate sensitivity in the CMIP3 models

The radiative flux perturbations and subsequent temperature responses in relation to the eruption of Mount Pinatubo in 1991 are studied in the ten general circulation models incorporated in the Coupled Model Intercomparison Project, phase 3 (CMIP3), that include a parameterization of volcanic aerosol. Models and observations show decreases in global mean temperature of up to 0.5 K, in response to radiative perturbations of up to 10 W m⁻², averaged over the tropics. The time scale representing the delay between radiative perturbation and temperature response is determined by the slow ocean response, and is estimated to be centered around 4 months in the models. Although the magniude of the temperature response to a volcanic eruption has previously been used as an indicator of equilibrium climate sensitivity in models, we find these two quantities to be only weakly correlated. This may partly be due to the fact that the size of the volcano-induced radiative perturbation varies among the models. It is found that the magnitude of the modelled radiative perturbation increases with decreasing climate sensitivity, with the exception of one outlying model. Therefore, we scale the temperature perturbation by the radiative perturbation in each model, and use the ratio between the integrated temperature perturbation and the integrated radiative perturbation as a measure of sensitivity to volcanic forcing. This ratio is found to be well correlated with the model climate sensitivity, more sensitive models having a larger ratio. Further, if this correspondence between “volcanic sensitivity” and sensitivity to CO₂ forcing is a feature not only among the models, but also of the real climate system, the alleged linear relation can be used to estimate the real climate sensitivity. The observational value of the ratio signifying volcanic sensitivity is hereby estimated to correspond to an equilibrium climate sensitivity, i.e. equilibrium temperature increase due to a doubling of the CO₂ concentration, between 1.7 and 4.1 K. Several sources of uncertainty reside in the method applied, and it is pointed out that additional model output, related to ocean heat storage and radiative forcing, could refine the analysis, as could reduced uncertainty in the observational record, of temperature as well as forcing.     

The importance of precessional signals in the tropical climate

Past research on the climate response to orbital forcing has emphasized the glacial-interglacial variations in global ice volume, global-mean temperature, and the global hydrologic cycle. This emphasis may be inappropriate in the tropics, where the response to precessional forcing is likely to be somewhat independent of the glacial-interglacial variations, particularly in variables relating to the hydrologic cycle. To illustrate this point, we use an atmospheric general circulation model coupled to a slab ocean model, performing experiments that quantify the tropical climates response to (1) opposite phases of precessional forcing, and (2) Last Glacial Maximum boundary conditions. While the glacially-forced tropical temperature changes are typically more than an order of magnitude larger than those arising from precessional forcing, the hydrologic signals stemming from the two forcings are comparable in magnitude. The mechanisms behind these signals are investigated and shown to be quite distinct for the precessional and glacial forcing. Because of strong dynamical linkages in the tropics, the model results illustrate the impossibility of predicting the local hydrologic response to external forcing without understanding the response at much larger spatial scales. Examples from the paleoclimate record are presented as additional evidence for the importance of precessional signals in past variations of the tropical climate.     

Assessment of CMIP5 global model simulations over the subset of CORDEX domains used in the Phase I CREMA

We present an assessment of the CMIP5 global model simulations over a subset of CORDEX domains used in the Phase I CREMA (CORDEX RegCM hyper-MAtrix) experiment (Africa, HYMEX-MED (Mediterranean), South America, Central America and West Asia). Three variants of the transformed Mielke measure are used to assess (1) the model skill in simulating surface temperature and precipitation historical climatology, (2) the degree of surface temperature and precipitation change occurring under greenhouse gas forcing, and (3) the consistency of a model’s projected change with that of the Multi Model Ensemble (MME) mean. The majority of models exhibit varying degrees of skill depending on the region and season; however, a few models are identified as performing well globally. We find that resolution improves the model skill in most regional and seasonal cases, especially for temperature. Models with the highest and lowest climate sensitivity, as well as those whose change most resembles the ensemble mean are also discussed. Although the higher resolution models perform better, we find that resolution does not have a statistically significant impact on the models’ response to GHG forcing, indicating that model biases do not play a primary role in affecting the model response to GHG forcing. We also assess the three selected models for the CREMA Phase I experiment (HADGEM2ES, MPI-ESMMR and GFDL-ESM2M) and find that they are characterized by a relatively good level of performance, a range of high to low climate sensitivities and a good consistency with the MME changes, thereby providing a reasonably representative sample of the CMIP5 ensemble.     

How much information is lost by using global-mean climate metrics? an example using the transport sector

Metrics are often used to compare the climate impacts of emissions from various sources, sectors or nations. These are usually based on global-mean input, and so there is the potential that important information on smaller scales is lost. Assuming a non-linear dependence of the climate impact on local surface temperature change, we explore the loss of information about regional variability that results from using global-mean input in the specific case of heterogeneous changes in ozone, methane and aerosol concentrations resulting from emissions from road traffic, aviation and shipping. Results from equilibrium simulations with two general circulation models are used. An alternative metric for capturing the regional climate impacts is investigated. We find that the application of a metric that is first calculated locally and then averaged globally captures a more complete and informative signal of climate impact than one that uses global-mean input. The loss of information when heterogeneity is ignored is largest in the case of aviation. Further investigation of the spatial distribution of temperature change indicates that although the pattern of temperature response does not closely match the pattern of the forcing, the forcing pattern still influences the response pattern on a hemispheric scale. When the short-lived transport forcing is superimposed on present-day anthropogenic CO₂ forcing, the heterogeneity in the temperature response to CO₂ dominates. This suggests that the importance of including regional climate impacts in global metrics depends on whether small sectors are considered in isolation or as part of the overall climate change.     

On aspects of the concept of radiative forcing

 The concept of radiative forcing has been extensively used as an indicator of the potential importance of climate change mechanisms. It allows a first order estimate of the global-mean surface temperature change; and it is possible to compare forcings from different mechanisms, on the assumption that similar global-mean forcings produce similar global-mean surface temperature changes. This study illustrates two circumstances where simple models show that the conventional definition of radiative forcing needs refining. These problems arise mainly with the calculation of forcing due to stratospheric ozone depletion. The first part uses simple arguments to produce an alternative definition of radiative forcing, using a time-dependent stratospheric adjustment method, which can give different forcings from those calculated using the standard definition. A seasonally varying ozone depletion can produce a quite different seasonal evolution of forcing than fixed dynamical heating arguments would suggest. This is especially true of an idealised and extreme “Antarctic ozone hole” type scenario where a sudden loss of ozone is followed by a sudden recovery. However, for observed ozone changes the annually averaged forcing is usually within 5% of the forcing calculated using the fixed dynamical heating approximation. Another problem with the accepted view of radiative forcing arises from the definition of the tropopause considered in the second part of this study. For a correct radiative forcing estimate the “tropopause” needs to separate the atmosphere into regions with a purely radiative response and those with a radiative-convective response. From radiative-convective model results it is found that radiative equilibrium conditions persist for several kilometres below the tropopause (the tropopause being defined as where the lapse rate reaches 2 K km^-1). This region needs to be included in stratospheric adjustment calculations for an accurate calculation of forcing, as it is only the region between the surface and the top of the convection that can be considered as a single, forced, system. Including temperature changes in this region has a very large effect on stratospheric ozone forcing estimates, and can reduce the magnitude of the forcing by more than a factor of two. Although these experiments are performed using simple climate models, the results are of equal importance for the analysis of forcing-response relationships using general circulation models. Received: 25 October 1996/Accepted: 14 April 1997     

A simple model perturbed physics study of the simulated climate sensitivity uncertainty and its relation to control climate biases

In this study the relationship between climate model biases in the control climate and the simulated climate sensitivity are discussed on the basis of perturbed physics ensemble simulations with a globally resolved energy balance (GREB) model. It is illustrated that the uncertainties in the simulated climate sensitivity (estimated by the transient response to CO₂ forcing scenarios in the twenty first century or idealized 2 × CO₂ forcing experiments) can be conceptually split into two parts: a direct effect of the perturbed physics on the climate sensitivity independent of the control mean climate and an indirect effect of the perturbed physics by changing the control mean climate, which in turn changes the climate sensitivity, as the climate sensitivity itself is depending on the control climate. Biases in the control climate are negatively correlated with the climate sensitivity (colder climates have larger sensitivities), if no physics are perturbed. Perturbed physics that lead to warmer control climate, would in average also lead to larger climate sensitivities, if the control climate is held at the observed reference climate by flux corrections. Thus the effects of control biases and perturbed physics are opposing each other and are partially cancelling each other out. In the GREB model the biases in the control climate are the more important effect for the regional climate sensitivity uncertainties, but for the global mean climate sensitivity both, the biases in the control climate and the perturbed physics, are equally important.     

GCM intercomparison of global cloud regimes: present-day evaluation and climate change response

The radiative feedback from clouds remains the largest source of variation in climate sensitivity amongst general circulation models (GCMs). A cloud clustering methodology is applied to six contemporary GCMs in order to provide a detailed intercomparison and evaluation of the simulated cloud regimes. By analysing GCMs in the context of cloud regimes, processes related to particular cloud types are more likely to be evaluated. In this paper, the mean properties of the global cloud regimes are evaluated, and the cloud response to climate change is analysed in the cloud-regime framework. Most of the GCMs are able to simulate the principal cloud regimes, however none of the models analysed have a good representation of trade cumulus in the tropics. The models also share a difficulty in simulating those regimes with cloud tops at mid-levels, with only ECHAM5 producing a regime of tropical cumulus congestus. Optically thick, high top cloud in the extra-tropics, typically associated with the passage of frontal systems, is simulated considerably too frequently in the ECHAM5 model. This appears to be a result of the cloud type persisting in the model after the meteorological conditions associated with frontal systems have ceased. The simulation of stratocumulus in the MIROC GCMs is too extensive, resulting in the tropics being too reflective. Most of the global-mean cloud response to doubled CO₂ in the GCMs is found to be a result of changes in the cloud radiative properties of the regimes, rather than changes in the relative frequency of occurrence (RFO) of the regimes. Most of the variance in the global cloud response between the GCMs arises from differences in the radiative response of frontal cloud in the extra-tropics and from stratocumulus cloud in the tropics. This variance is largely the result of excessively high RFOs of specific regimes in particular GCMs. It is shown here that evaluation and subsequent improvement in the simulation of the present-day regime properties has the potential to reduce the variance of the global cloud response, and hence climate sensitivity, amongst GCMs. For the ensemble of models considered in this study, the use of observations of the mean present-day cloud regimes suggests a potential reduction in the range of climate sensitivity of almost a third. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates

This study diagnoses the climate sensitivity, radiative forcing and climate feedback estimates from eleven general circulation models participating in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5), and analyzes inter-model differences. This is done by taking into account the fact that the climate response to increased carbon dioxide (CO₂) is not necessarily only mediated by surface temperature changes, but can also result from fast land warming and tropospheric adjustments to the CO₂ radiative forcing. By considering tropospheric adjustments to CO₂ as part of the forcing rather than as feedbacks, and by using the radiative kernels approach, we decompose climate sensitivity estimates in terms of feedbacks and adjustments associated with water vapor, temperature lapse rate, surface albedo and clouds. Cloud adjustment to CO₂ is, with one exception, generally positive, and is associated with a reduced strength of the cloud feedback; the multi-model mean cloud feedback is about 33 % weaker. Non-cloud adjustments associated with temperature, water vapor and albedo seem, however, to be better understood as responses to land surface warming. Separating out the tropospheric adjustments does not significantly affect the spread in climate sensitivity estimates, which primarily results from differing climate feedbacks. About 70 % of the spread stems from the cloud feedback, which remains the major source of inter-model spread in climate sensitivity, with a large contribution from the tropics. Differences in tropical cloud feedbacks between low-sensitivity and high-sensitivity models occur over a large range of dynamical regimes, but primarily arise from the regimes associated with a predominance of shallow cumulus and stratocumulus clouds. The combined water vapor plus lapse rate feedback also contributes to the spread of climate sensitivity estimates, with inter-model differences arising primarily from the relative humidity responses throughout the troposphere. Finally, this study points to a substantial role of nonlinearities in the calculation of adjustments and feedbacks for the interpretation of inter-model spread in climate sensitivity estimates. We show that in climate model simulations with large forcing (e.g., 4 × CO₂), nonlinearities cannot be assumed minor nor neglected. Having said that, most results presented here are consistent with a number of previous feedback studies, despite the very different nature of the methodologies and all the uncertainties associated with them.     

Origins of differences in climate sensitivity, forcing and feedback in climate models

We diagnose climate feedback parameters and CO₂ forcing including rapid adjustment in twelve atmosphere/mixed-layer-ocean (“slab”) climate models from the CMIP3/CFMIP-1 project (the AR4 ensemble) and fifteen parameter-perturbed versions of the HadSM3 slab model (the PPE). In both ensembles, differences in climate feedbacks can account for approximately twice as much of the range in climate sensitivity as differences in CO₂ forcing. In the AR4 ensemble, cloud effects can explain the full range of climate sensitivities, and cloud feedback components contribute four times as much as cloud components of CO₂ forcing to the range. Non-cloud feedbacks are required to fully account for the high sensitivities of some models however. The largest contribution to the high sensitivity of HadGEM1 is from a high latitude clear-sky shortwave feedback, and clear-sky longwave feedbacks contribute substantially to the highest sensitivity members of the PPE. Differences in low latitude ocean regions (30°N/S) contribute more to the range than those in mid-latitude oceans (30–55°N/S), low/mid latitude land (55°N/S) or high latitude ocean/land (55–90°N/S), but contributions from these other regions are required to account fully for the higher model sensitivities, for example from land areas in IPSL CM4. Net cloud feedback components over the low latitude oceans sorted into percentile ranges of lower tropospheric stability (LTS) show largest differences among models in stable regions, mainly due to their shortwave components, most of which are positive in spite of increasing LTS. Differences in the mid-stability range are smaller, but cover a larger area, contributing a comparable amount to the range in climate sensitivity. These are strongly anti-correlated with changes in subsidence. Cloud components of CO₂ forcing also show the largest differences in stable regions, and are strongly anticorrelated with changes in estimated inversion strength (EIS). This is qualitatively consistent with what would be expected from observed relationships between EIS and low-level cloud fraction. We identify a number of cases where individual models show unusually strong forcings and feedbacks compared to other members of the ensemble. We encourage modelling groups to investigate unusual model behaviours further with sensitivity experiments. Most of the models fail to correctly reproduce the observed relationships between stability and cloud radiative effect in the subtropics, indicating that there remains considerable room for model improvements in the future.     

Intercomparsion of regional biases and doubled CO2-sensitivity of coupled atmosphere-ocean general circulation model experiments

 We compared regional biases and transient doubled CO₂ sensitivities of nine coupled atmosphere-ocean general circulation models (GCMs) from six international climate modeling groups. We evaluated biases and responses in winter and summer surface air temperatures and precipitation for seven subcontinental regions, including those in the 1990 Intergovernmental Panel on Climate Change (IPCC) Scientific Assessment. Regional biases were large and exceeded the variance among four climatological datasets, indicating that model biases were not primarily due to uncertainty in observations. Model responses to altered greenhouse forcing were substantial (average temperature change=2.7±0.9 ^°C, range of precipitation change =−35 to +120% of control). While coupled models include more climate system feedbacks than earlier GCMs implemented with mixed-layer ocean models, inclusion of a dynamic ocean alone did not improve simulation of long-term mean climatology nor increase convergence among model responses to altered greenhouse gas forcing. On the other hand, features of some of the coupled models including flux adjustment (which may have simply masked simulation errors), high horizontal resolution, and estimation of screen height temperature contributed to improved simulation of long-term surface climate. The large range of model responses was partly accounted for by inconsistencies in forcing scenarios and transient-simulation averaging periods. Nonetheless, the models generally had greater agreement in their sensitivities than their controls did with observations. This suggests that consistent, large-scale response features from an ensemble of model sensitivity experiments may not depend on details of their representation of present-day climate. Received: 9 September 1996 / Revised: 31 July 1997     

Is there a stratospheric radiative feedback in global warming simulations?

The radiative impacts of the stratosphere in global warming simulations are investigated using abrupt CO₂ quadrupling experiments of the Coupled Model Inter-comparison Project phase 5 (CMIP5), with a focus on stratospheric temperature and water vapor. It is found that the stratospheric temperature change has a robust bullhorn-like zonal-mean pattern due to a strengthening of the stratospheric overturning circulation. This temperature change modifies the zonal mean top-of-the-atmosphere energy balance, but the compensation of the regional effects leads to an insignificant global-mean radiative feedback (?0.02 ± 0.04 W m^?2 K^?1). The stratospheric water vapor concentration generally increases, which leads to a weak positive global-mean radiative feedback (0.02 ± 0.01 W m^?2 K^?1). The stratospheric moistening is related to mixing of elevated upper-tropospheric humidity, and, to a lesser extent, to change in tropical tropopause temperature. Our results indicate that the strength of the stratospheric water vapor feedback is noticeably larger in high-top models than in low-top ones. The results here indicate that although its radiative impact as a forcing adjustment is significant, the stratosphere makes a minor contribution to the overall climate feedback in CMIP5 models.     

Sea-salt optical properties and GCM forcing at solar wavelengths

The single-scattering optical properties of sea-salt solution particles are parameterised as functions of relative humidity for various dry size distributions at solar wavelengths. The accuracy of the parameterisation is typically within 10% as compared to exact Mie calculations. In addition to the optical properties, the growth of the droplet mass ratio and the effective radius of the size distribution are also parameterised in terms of the relative humidity. Two-band models are presented: a four-band model for use in GCMs for climate studies and a 23-band model for use in higher spectral resolution models. The parameterisation is implemented in the Canadian General Circulation Model GCMIII, and an estimate of the first-order globally and yearly averaged solar direct radiative forcing due to sea-salt is estimated to be −0.15 W/m² (cooling). The northern hemisphere forcing is estimated to be −0.11 W/m² and the southern hemisphere is −0.19 W/m². The monthly trends in the forcing for the two hemispheres are presented and discussed. The sensitivity of the forcing to the treatment of the growth of aerosols in the hysteresis region, where aerosol particles are either dry or supersaturated, is investigated along with other sensitivities.     

Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century

Five simple indices of surface temperature are used to investigate the influence of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing on observed climate change during the twentieth century. These indices are based on spatial fingerprints of climate change and include the global-mean surface temperature, the land-ocean temperature contrast, the magnitude of the annual cycle in surface temperature over land, the Northern Hemisphere meridional temperature gradient and the hemispheric temperature contrast. The indices contain information independent of variations in global-mean temperature for unforced climate variations and hence, considered collectively, they are more useful in an attribution study than global mean surface temperature alone. Observed linear trends over 1950–1999 in all the indices except the hemispheric temperature contrast are significantly larger than simulated changes due to internal variability or natural (solar and volcanic aerosol) forcings and are consistent with simulated changes due to anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined, relative influence of these different forcings on observed trends during the twentieth century is investigated using linear regression of the observed and simulated responses of the indices. It is found that anthropogenic forcing accounts for almost all of the observed changes in surface temperature during 1946–1995. We found that early twentieth century changes (1896–1945) in global mean temperature can be explained by a combination of anthropogenic and natural forcing, as well as internal climate variability. Estimates of scaling factors that weight the amplitude of model simulated signals to corresponding observed changes using a combined normalized index are similar to those calculated using more complex, optimal fingerprint techniques.     

Long-term patterns of solar irradiance forcing in model experiments and proxy based surface temperature reconstructions

Comparisons are made of long-term empirical and model-estimated patterns of solar irradiance forcing during a 200-year period (1650-1850), which precedes any apparent anthropogenic influence on climate. This interval encompasses a considerable range (approximately 4 W/m²) of estimated variation in solar output, including the "Maunder" and "Dalton" Minima of solar irradiance, and an intervening interval of relatively high values of irradiance, but does not encroach into the industrial era wherein it is difficult to separate solar and anthropogenic influences. Particular emphasis is placed on comparing empirical and modeled patterns of forced surface temperature variation. The empirical patterns bear a greater similarity to the pattern of forced response of a coupled ocean-atmosphere general circulation model (AOGCM) than with an independent model simulation result using an ocean with specified heat transport, both in terms of the spatial pattern of response and implied global mean sensitivity to forcing. Heightened sensitivity in the western Pacific warm pool apparent in the empirical response pattern, is not observed in the forced response of the coupled model. It is possible that this pattern is the result of feedback processes not currently reproduced in course-resolution coupled models. The greatest empirical response is found at the multidecadal-to-century (> 40 year period) time scale, for which the forcing is dominated by the roughly 90-year Gleissberg Cycle of irradiance. This indicates a global-mean sensitivity (approximately 0.3 K/W/m²), which is close to the coupled model result (approximately 0.4 K/W/m²). At decadal time scales (8-25 year period), for which the forcing is dominated by the 11-year and 22-year period solar cycles), the temperature sensitivity is moderately reduced, and its spatial pattern of response is dominated by an apparent resonance with known decadal modes of climate variability.     

Simulated climate change during the last 1,000 years: comparing the ECHO-G general circulation model with the MAGICC simple climate model

An intercomparison of eight climate simulations, each driven with estimated natural and anthropogenic forcings for the last millennium, indicates that the so-called “Erik” simulation of the ECHO-G coupled ocean-atmosphere climate model exhibits atypical behaviour. The ECHO-G simulation has a much stronger cooling trend from 1000 to 1700 and a higher rate of warming since 1800 than the other simulations, with the result that the overall amplitude of millennial-scale temperature variations in the ECHO-G simulation is much greater than in the other models. The MAGICC (Model for the Assessment of Greenhouse-gas-Induced Climate Change) simple climate model is used to investigate possible causes of this atypical behaviour. It is shown that disequilibrium in the initial conditions probably contributes spuriously to the cooling trend in the early centuries of the simulation, and that the omission of tropospheric sulphate aerosol forcing is the likely explanation for the anomalously large recent warming. The simple climate model results are used to adjust the ECHO-G Erik simulation to mitigate these effects, which brings the simulation into better agreement with the other seven models considered here and greatly reduces the overall range of temperature variations during the last millennium simulated by ECHO-G. Smaller inter-model differences remain which can probably be explained by a combination of the particular forcing histories and model sensitivities of each experiment. These have not been investigated here, though we have diagnosed the effective climate sensitivity of ECHO-G to be 2.39±0.11 K for a doubling of CO₂.     

Constraining climate model properties using optimal fingerprint detection methods

 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     

Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

Understanding the historical and future response of the global climate system to anthropogenic emissions of radiatively active atmospheric constituents has become a timely and compelling concern. At present, however, there are uncertainties in: the total radiative forcing associated with changes in the chemical composition of the atmosphere; the effective forcing applied to the climate system resulting from a (temporary) reduction via ocean-heat uptake; and the strength of the climate feedbacks that subsequently modify this forcing. Here a set of analyses derived from atmospheric general circulation model simulations are used to estimate the effective and total radiative forcing of the observed climate system due to anthropogenic emissions over the last 50 years of the twentieth century. They are also used to estimate the sensitivity of the observed climate system to these emissions, as well as the expected change in global surface temperatures once the climate system returns to radiative equilibrium. Results indicate that estimates of the effective radiative forcing and total radiative forcing associated with historical anthropogenic emissions differ across models. In addition estimates of the historical sensitivity of the climate to these emissions differ across models. However, results suggest that the variations in climate sensitivity and total climate forcing are not independent, and that the two vary inversely with respect to one another. As such, expected equilibrium temperature changes, which are given by the product of the total radiative forcing and the climate sensitivity, are relatively constant between models, particularly in comparison to results in which the total radiative forcing is assumed constant. Implications of these results for projected future climate forcings and subsequent responses are also discussed.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

As carbon dioxide and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how derivative changes in climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using twelve scenarios derived from General Circulation Model (GCM) projections to drive biophysical impact models. These scenarios are described in this paper. The scenarios are first put into the context of recent work on climate-change by the IPCC for the 21st century and span two levels of global-mean temperature change and three sets of spatial patterns of change derived from GCM results. In addition, the effect of either the presence or absence of a CO₂ fertilization effect on vegetation is examined by using two levels of atmospheric CO₂ concentration as a proxy variable. Results from three GCM experiments were used to produce different regional patterns of climate change. The three regional patterns for the conterminous United States range from: an increase in temperature above the global-mean level along with a significant decline in precipitation; temperature increases in line with the global-mean with an average increase in precipitation; and, with a sulfate aerosol effect added to in the same model, temperature increases that are lower than the global-mean. The resulting set of scenarios span a wide range of potential climate changes and allows examination of the relative importance of global-mean temperature change, regional climate patterns, aerosol cooling, and CO₂ fertilization effects.