Some implications of a new approach to the water vapour feedback

The water vapour feedback is the largest physical climate feedback. It also gives the second-largest contribution to the range of uncertainty in climate sensitivity in General Circulation Models (GCMs). Tracing these differences back to their physical causes in the hope of constraining climate sensitivity requires an appropriate quantification. Yet the Intergovernmental Panel on Climate Change judge that the conventional diagnosis of a “water vapour feedback” and a “lapse rate feedback” provides little insight into differences between GCMs’ climate sensitivities. We show that the conventionally diagnosed water vapour feedback is in fact formally useless for investigating differences between GCMs’ climate sensitivities—the anticorrelation between conventional “water vapour feedback” and “lapse rate feedback” makes the correlation between the “water vapour feedback” and their sum insignificant: i.e. statistically, knowing this “feedback” allows one to conclude nothing about the sum and thence about climate sensitivity. This follows primarily from how little relative humidity (RH) changes with climate change in GCMs. A more detailed physical analysis concludes that the overall mean decrease of RH on warming seen in GCMs is robustly physically based. This and other physical arguments then suggest that the stronger the positive “water vapour feedback”, the less sensitive climate can be expected to be. A diagnosis based on the “partly-Simpsonian” model of water vapour feedback avoids these problems. On the conventional view of the water vapour feedback, naive extrapolation of variations within present-day climate suggests that parts of our planet are close to locally reaching conditions that would allow a run-away water vapour greenhouse effect once they were extensive enough. Of course this has never occurred in geological history, and is not seen in Earth-like GCMs. Again, the “partly-Simpsonian” approach provides a simple qualitative explanation, by showing that the water vapour feedback can only cancel part of the basic Planck’s Law negative feedback.     

Climate feedbacks in a general circulation model incorporating prognostic clouds

 This study performs a comprehensive feedback analysis on the Bureau of Meteorology Research Centre General Circulation Model, quantifying all important feedbacks operating under an increase in atmospheric CO₂. The individual feedbacks are analysed in detail, using an offline radiation perturbation method, looking at long- and shortwave components, latitudinal distributions, cloud impacts, non-linearities under 2xCO₂ and 4xCO₂ warmings and at interannual variability. The water vapour feedback is divided into terms due to moisture height and amount changes. The net cloud feedback is separated into terms due to cloud amount, height, water content, water phase, physical thickness and convective cloud fraction. Globally the most important feedbacks were found to be (from strongest positive to strongest negative) those due to water vapour, clouds, surface albedo, lapse rate and surface temperature. For the longwave (LW) response the most important term of the cloud ‘optical property’ feedbacks is due to the water content. In the shortwave (SW), both water content and water phase changes are important. Cloud amount and height terms are also important for both LW and SW. Feedbacks due to physical cloud thickness and convective cloud fraction are found to be relatively small. All cloud component feedbacks (other than height) produce conflicting LW/SW feedbacks in the model. Furthermore, the optical property and cloud fraction feedbacks are also of opposite sign. The result is that the net cloud feedback is the (relatively small) product of conflicting physical processes. Non-linearities in the feedbacks are found to be relatively small for all but the surface albedo response and some cloud component contributions. The cloud impact on non-cloud feedbacks is also discussed: greatest impact is on the surface albedo, but impact on water vapour feedback is also significant. The analysis method here proves to be a␣powerful tool for detailing the contributions from different model processes (and particularly those of the clouds) to the final climate model sensitivity. Received: 15 June 2000 / Accepted: 10 January 2001     

Evaluation of a component of the cloud response to climate change in an intercomparison of climate models

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.     

On atmospheric radiative feedbacks associated with climate variability and change

Using the method of radiative ‘kernels’ an analysis is made of water vapour, lapse rate and ‘Planck’ (uniform vertical temperature) long wave feedbacks in models participating in the World Climate Research Program (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3). Feedbacks are calculated at climate change timescales from the A1B scenario, and at three ‘variability’ timescales from the corresponding preindustrial experiments: seasonal, interannual and decadal. Surface temperature responses show different meridional patterns for the different timescales, which are then manifest in the structures of the individual feedbacks. Despite these differences, mean water vapour feedback strength in models is positive for all models and timescales, and of comparable global magnitude across all timescales except for seasonal, where it is much weaker. Taking into consideration the strong positive lapse rate feedback at seasonal timescales, combined water vapour/lapse rate feedback is indeed similar across all timescales. To a good approximation, global water vapour feedback is found to be well represented by the temperature response along with an assumption of unchanged relative humidity under both variability and climate change. A comparison is also made of model feedbacks with reanalysis derived feedbacks for seasonal and interannual timescales. No strong relationships between individual modelled feedbacks at different timescales are evident: i.e., strong feedbacks in models at variability timescales do not in general predict strong climate change feedback, with the possible exception of seasonal timescales. There are caveats on this (and other) findings however, from uncertainties associated with the kernel technique and from, at times, very large uncertainties in estimating variability related feedbacks from temperature regressions.     

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.     

Atmospheric radiative feedbacks associated with transient climate change and climate variability

This study examines in detail the ‘atmospheric’ radiative feedbacks operating in a coupled General Circulation Model (GCM). These feedbacks (defined as the change in top of atmosphere radiation per degree of global surface temperature change) are due to responses in water vapour, lapse rate, clouds and surface albedo. Two types of radiative feedback in particular are considered: those arising from century scale ‘transient’ warming (from a 1% per annum compounded CO₂ increase), and those operating under the model’s own unforced ‘natural’ variability. The time evolution of the transient (or ‘secular’) feedbacks is first examined. It is found that both the global strength and the latitudinal distributions of these feedbacks are established within the first two or three decades of warming, and thereafter change relatively little out to 100 years. They also closely approximate those found under equilibrium warming from a ‘mixed layer’ ocean version of the same model forced by a doubling of CO₂. These secular feedbacks are then compared with those operating under unforced (interannual) variability. For water vapour, the interannual feedback is only around two-thirds the strength of the secular feedback. The pattern reveals widespread regions of negative feedback in the interannual case, in turn resulting from patterns of circulation change and regions of decreasing as well as increasing surface temperature. Considering the vertical structure of the two, it is found that although positive net mid to upper tropospheric contributions dominate both, they are weaker (and occur lower) under interannual variability than under secular change and are more narrowly confined to the tropics. Lapse rate feedback from variability shows weak negative feedback over low latitudes combined with strong positive feedback in mid-to-high latitudes resulting in no net global feedback—in contrast to the dominant negative low to mid-latitude response seen under secular climate change. Surface albedo feedback is, however, slightly stronger under interannual variability—partly due to regions of extremely weak, or even negative, feedback over Antarctic sea ice in the transient experiment. Both long and shortwave global cloud feedbacks are essentially zero on interannual timescales, with the shortwave term also being very weak under climate change, although cloud fraction and optical property components show correlation with global temperature both under interannual variability and transient climate change. The results of this modelling study, although for a single model only, suggest that the analogues provided by interannual variability may provide some useful pointers to some aspects of climate change feedback strength, particularly for water vapour and surface albedo, but that structural differences will need to be heeded in such an analysis.     

Climate feedbacks determined using radiative kernels in a multi-thousand member ensemble of AOGCMs

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.     

Quantifying the water vapour feedback associated with post-Pinatubo global cooling

There is an ongoing important debate about the role of water vapour in climate change. Predictions of future climate change depend strongly on the magnitude of the water vapour feedback and until now models have almost exclusively been relied upon to quantify this feedback. In this work we employ observations of water vapour changes, together with detailed radiative calculations to estimate the water vapour feedback for the case of the Mt. Pinatubo eruption. We then compare our observed estimate with that calculated from a relatively large ensemble of simulations from a complex coupled climate model. We calculate an observed water vapour feedback parameter of –1.6 Wm^–2 K^–1, with uncertainty placing the feedback parameter between –0.9 to –2.5 Wm^–2 K^–1. The uncertain is principally from natural climate variations that contaminate the volcanic cooling. The observed estimates are consistent with that found in the climate model, with the ensemble average model feedback parameter being –2.0 Wm^–2 K^–1, with a 5–95% range of –0.4 to –3.6 Wm^–2 K^–1 (as in the case of the observations, the spread is due to an inability to separate the forced response from natural variability). However, in both the upper troposphere and Southern Hemisphere the observed model water vapour response differs markedly from the observations. The observed range represents a 40%–400% increase in the magnitude of surface temperature change when compared to a fixed water vapour response and is in good agreement with values found in other studies. Variability, both in the observed value and in the climate models feedback parameter, between different ensemble members, suggests that the long-term water vapour feedback associated with global climate change could still be a factor of 2 or 3 different than the mean observed value found here and the model water vapour feedback could be quite different from this value; although a small water vapour feedback appears unlikely. We also discuss where in the atmosphere water vapour changes have their largest effect on surface climate.     

Towards evaluating cloud response to climate change using clustering technique identification of cloud regimes

Most of the discrepancies in the climate sensitivity of general circulation models (GCMs) are believed to be due to differences in cloud radiative feedback. Analysis of cloud response to climate change in different ‘regimes’ may offer a more detailed understanding of how the cloud response differs between GCMs. In which case, evaluation of simulated cloud regimes against observations in terms of both their cloud properties and frequency of occurrence will assist in assessing confidence in the cloud response to climate change in a particular GCM. In this study, we use a clustering technique on International Satellite Cloud Climatology Project (ISCCP) data and on ISCCP-like diagnostics from two versions of the Hadley Centre GCM to identify cloud regimes over four different geographical regions. The two versions of the model are evaluated against observational data and their cloud response to climate change compared within the cloud regime framework. It is found that cloud clusters produced by the more recent GCM, HadSM4, compare more favourably with observations than HadSM3. In response to climate change, although the net cloud response over particular regions is often different in the two models, in several instances the same basic processes may be seen to be operating. Overall, both changes in the frequency of occurrence of cloud regimes and changes in the properties (optical depth and cloud top height) of the cloud regimes contribute to the cloud response to climate change.     

CLIMBER-2: a climate system model of intermediate complexity. Part II: model sensitivity

 A set of sensitivity experiments with the climate system model of intermediate complexity CLIMBER-2 was performed to compare its sensitivity to changes in different types of forcings and boundary conditions with the results of comprehensive models (GCMs). We investigated the climate system response to changes in freshwater flux into the Northern Atlantic, CO₂ concentration, solar insolation, and vegetation cover in the boreal zone and in the tropics. All these experiments were compared with the results of corresponding experiments performed with different GCMs. Qualitative, and in many respects, quantitative agreement between the results of CLIMBER-2 and GCMs demonstrate the ability of our climate system model of intermediate complexity to address diverse aspects of the climate change problem. In addition, we used our model for a series of experiments to assess the impact of some climate feedbacks and uncertainties in model parameters on the model sensitivity to different forcings. We studied the role of freshwater feedback and vertical ocean diffusivity for the stability properties of the thermohaline ocean circulation. We show that freshwater feedback plays a minor role, while changes of vertical diffusivity in the ocean considerably affect the circulation stability. In global warming experiments we analysed the impact of hydrological sensitivity and vertical diffusivity on the long-term evolution of the thermohaline circulation. In the boreal and tropical deforestation experiments we assessed the role of an interactive ocean and showed that for both types of deforestation scenarios, an interactive ocean leads to an additional cooling due to albedo and water vapour feedbacks. Received: 28 May 2000 / Accepted: 9 November 2000     

On the simulation of Laurentian Great Lakes water levels under projections of global climate change

A new method is proposed to estimate future net basin supplies and lake levels for the Laurentian Great Lakes based on GCM projections of global climate change. The method first dynamically downscales the GCM simulation with a regional climate model, and then bias—corrects the simulated net basin supply in order to be used directly in a river—routing/lake level scheme. This technique addresses two weaknesses in the traditional approach, whereby observed sequences of climate variables are perturbed with fixed ratios or differences derived directly from GCMs in order to run evaporation and runoff models. Specifically, (1) land surface—atmosphere feedback processes are represented, and (2) changes in variability can be analyzed with the new approach. The method is demonstrated with a single, high resolution simulation, where small changes in future mean lake levels for all the upper Great Lakes are found, and an increase in seasonal range—especially for Lake Superior—is indicated. Analysis of a small ensemble of eight lower resolution regional climate model simulations supports these findings. In addition, a direct comparison with the traditional approach based on the same GCM projections used as the driving simulations in this ensemble shows that the new method indicates smaller declines in level for all the upper Great Lakes than has been reported previously based on the traditional method, though median differences are only a few centimetres in each case.     

Terrestrial biosphere carbon storage under alternative climate projections

This study investigates commonalities and differences in projected land biosphere carbon storage among climate change projections derived from one emission scenario by five different general circulation models (GCMs). Carbon storage is studied using a global biogeochemical process model of vegetation and soil that includes dynamic treatment of changes in vegetation composition, a recently enhanced version of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). Uncertainty in future terrestrial carbon storage due to differences in the climate projections is large. Changes by the end of the century range from −106 to +201 PgC, thus, even the sign of the response whether source or sink, is uncertain. Three out of five climate projections produce a land carbon source by the year 2100, one is approximately neutral and one a sink. A regional breakdown shows some robust qualitative features. Large areas of the boreal forest are shown as a future CO₂ source, while a sink appears in the arctic. The sign of the response in tropical and sub-tropical ecosystems differs among models, due to the large variations in simulated precipitation patterns. The largest uncertainty is in the response of tropical rainforests of South America and Central Africa.     

On tropospheric adjustment to forcing and climate feedbacks

Motivated by findings that major components of so-called cloud ??feedbacks?? are best understood as rapid responses to CO₂ forcing (Gregory and Webb in J Clim 21:58?C71, 2008), the top of atmosphere (TOA) radiative effects from forcing, and the subsequent responses to global surface temperature changes from all ??atmospheric feedbacks?? (water vapour, lapse rate, surface albedo, ??surface temperature?? and cloud) are examined in detail in a General Circulation Model. Two approaches are used: applying regressions to experiments as they approach equilibrium, and equilibrium experiments forced separately by CO₂ and patterned sea surface temperature perturbations alone. Results are analysed using the partial radiative perturbation (??PRP??) technique. In common with Gregory and Webb (J Clim 21:58?C71, 2008) a strong positive addition to ??forcing?? is found in the short wave (SW) from clouds. There is little evidence, however, of significant global scale rapid responses from long wave (LW) cloud, nor from surface albedo, SW water vapour or ??surface temperature??. These responses may be well understood to first order as classical ??feedbacks????i.e. as a function of global mean temperature alone and linearly related to it. Linear regression provides some evidence of a small rapid negative response in the LW from water vapour, related largely to decreased relative humidity (RH), but the response here, too, is dwarfed by subsequent response to warming. The large rapid SW cloud response is related to cloud fraction changes??and not optical properties??resulting from small cloud decreases ranging from the tropical mid troposphere to the mid latitude lower troposphere, in turn associated with decreased lower tropospheric RH. These regions correspond with levels of enhanced heating rates and increased temperatures from the CO₂ increase. The pattern of SW cloud fraction response to SST changes differs quite markedly to this, with large positive radiation responses originating in the upper troposphere, positive contributions in the lowest levels and patterns of positive/negative contributions in mid latitude low levels. Overall SW cloud feedback was diagnosed as negative, due to the substantial negative SW feedback in cloud optical properties more than offsetting these. This study therefore suggests the rapid response to CO₂ forcing is (apart from a possible small negative response from LW water vapour) essentially confined to cloud fraction changes affecting SW radiation, and further that significant feedbacks with temperature occur in all cloud components (including this one), and indeed in all other classically understood ??feedbacks??.     

A regional response in mean westerly circulation and rainfall to projected climate warming over Tasmania, Australia

Coupled ocean–atmosphere general circulation models (GCMs) lack sufficient resolution to model the regional detail of changes to mean circulation and rainfall with projected climate warming. In this paper, changes in mean circulation and rainfall in GCMs are compared to those in a variable resolution regional climate model, the Conformal Cubic Atmospheric Model (CCAM), under a high greenhouse gas emissions scenario. The study site is Tasmania, Australia, which is positioned within the mid-latitude westerlies of the southern hemisphere. CCAM projects a different response in mean sea level pressure and mid-latitude westerly circulation to climate warming to the GCMs used as input, and shows greater regional detail of the boundaries between regions of increasing and decreasing rainfall. Changes in mean circulation dominate the mean rainfall response in western Tasmania, whereas changes to rainfall in the East Coast are less related to mean circulation changes. CCAM projects an amplification of the dominant westerly circulation over Tasmania and this amplifies the seasonal cycle of wet winters and dry summers in the west. There is a larger change in the strength than in the incidence of westerly circulation and rainfall events. We propose the regional climate model displays a more sensitive atmospheric response to the different rates of warming of land and sea than the GCMs as input. The regional variation in these results highlight the need for dynamical downscaling of coupled general circulation models to finely resolve the influence of mean circulation and boundaries between regions of projected increases and decreases in rainfall.     

A quantitative performance assessment of cloud regimes in climate models

Differences in the radiative feedback from clouds account for much of the variation in climate sensitivity amongst General Circulation Models (GCMs). Therefore metrics of model performance which are demonstrated to be relevant to the cloud response to climate change form an important contribution to the overall evaluation of GCMs. In this paper we demonstrate an alternative method for assigning model data to observed cloud regimes obtained from clustering histograms of cloud amount in joint cloud optical depth—cloud top pressure classes. The method removes some of the subjectivity that exists in previous GCM cloud clustering studies. We apply the method to ten GCMs submitted to the Cloud Feedback Model Intercomparison Project (CFMIP), evaluate the simulated cloud regimes and analyse the climate change response in the context of these regimes. We also propose two cloud regime metrics, one of which is specifically targeted at assessing GCMs for the purpose of obtaining the global cloud radiative response to climate change. Most of the global variance in the cloud radiative response between GCMs is due to low clouds, with 47% arising from the stratocumulus regime and 18% due to the regime characterised by clouds undergoing transition from stratocumulus to cumulus. This result is found to be dominated by two structurally similar GCMs. The shallow cumulus regime, though widespread, has a smaller contribution and reduces the variance. For the stratocumulus and transition regimes, part of the variance results from a large model spread in the radiative properties of the regime in the control simulation. Comparison with observations reveals a systematic bias for both the stratocumulus and transition regimes to be overly reflective. If this bias was corrected with all other aspects of the response unchanged, the variance in the low cloud response would reduce. The response of some regimes with high cloud tops differ between the GCMs. These regimes are simulated too infrequently in a few of the models. If the frequency in the control simulation were more realistic and changes within the regimes were unaltered, the variance in the cloud radiative response from high-top clouds would increase. As a result, use of observations of the mean present-day cloud regimes suggests that whilst improvements in the simulation of the cloud regimes would impact the climate sensitivity, the inter-model variance may not reduce. When the cloud regime metric is calculated for the GCMs analysed here, only one model is on average consistent with observations within their uncertainty (and even this model is not consistent with the observations for all regimes), indicating scope for improvement in the simulation of cloud regimes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Assessment of different metrics for physical climate feedbacks

We quantify the feedbacks from the physical climate system on the radiative forcing for idealized climate simulations using four different methods. The results differ between the methods and differences are largest for the cloud feedback. The spatial and temporal variability of each feedback is used to estimate the averaging scale necessary to satisfy the feedback concept of one constant global mean value. We find that the year-to-year variability, combined with the methodological differences, in estimates of the feedback strength from a single model is comparable to the model-to-model spread in feedback strength of the CMIP3 ensemble. The strongest spatial and temporal variability is in the short-wave component of the cloud feedback. In our simulations, where many sources of natural variability are neglected, long-term averages are necessary to get reliable feedback estimates. Considering the large natural variability and relatively small forcing present in the real world, as compared to the forcing imposed by doubling CO₂ concentrations in the simulations, implies that using observations to constrain feedbacks is a challenging task and requires reliable long-term measurements.     

The respective roles of surface temperature driven feedbacks and tropospheric adjustment to CO2 in CMIP5 transient climate simulations

An overview of radiative climate feedbacks and ocean heat uptake efficiency diagnosed from idealized transient climate change experiments of 14 CMIP5 models is presented. Feedbacks explain about two times more variance in transient climate response across the models than ocean heat uptake efficiency. Cloud feedbacks can clearly be identified as the main source of inter-model spread. Models with strong longwave feedbacks in the tropics feature substantial increases in cloud ice around the tropopause suggestive of changes in cloud-top heights. The lifting of the tropical tropopause goes together with a general weakening of the tropical circulation. Distinctive inter-model differences in cloud shortwave feedbacks occur in the subtropics including the equatorward flanks of the storm-tracks. Related cloud fraction changes are not confined to low clouds but comprise middle level clouds as well. A reduction in relative humidity through the lower and mid troposphere can be identified as being the main associated large-scale feature. Experiments with prescribed sea surface temperatures are analyzed in order to investigate whether the diagnosed feedbacks from the transient climate simulations contain a tropospheric adjustment component that is not conveyed through the surface temperature response. The strengths of the climate feedbacks computed from atmosphere-only experiments with prescribed increases in sea surface temperatures, but fixed CO₂ concentrations, are close to the ones derived from the transient experiment. Only the cloud shortwave feedback exhibits discernible differences which, however, can not unequivocally be attributed to tropospheric adjustment to CO₂. Although for some models a tropospheric adjustment component is present in the global mean shortwave cloud feedback, an analysis of spatial patterns does not lend support to the view that cloud feedbacks are dominated by their tropospheric adjustment part. Nevertheless, there is positive correlation between the strength of tropospheric adjustment processes and cloud feedbacks across different climate models.     

Limitations of time-slice experiments for predicting regional climate change over South Asia

While time-slice simulations with atmospheric general circulation models (GCMs) have been used for many years to regionalize climate projections and/or assess their uncertainties, there is still no consensus about the method used to prescribe sea surface temperature (SST) in such experiments. In the present study, the response of the Indian summer monsoon to increasing amounts of greenhouse gases and sulfate aerosols is compared between a reference climate scenario and three sets of time-slice experiments, consisting of parallel integrations for present-day and future climates. Different monthly mean SST boundary conditions have been tested in the present-day integrations: raw climatological SST derived from the reference scenario, observed climatological SST, and observed SST with interannual variability. For future climate, the SST forcing has been obtained by superimposing climatological monthly mean SST anomalies derived from the reference scenario onto the present-day SST boundary conditions. None of these sets of time-slice experiments is able to capture accurately the response of the Indian summer monsoon simulated in the transient scenario. This finding suggests that the ocean–atmosphere coupling is a fundamental feature of the climate system. Neglecting the SST feedback and variability at the intraseasonal to interannual time scales has a significant impact on the projected monsoon response to global warming. Adding interannual variability in the prescribed SST boundary conditions does not mitigate the problem, but can on the contrary reinforce the discrepancies between the forced and coupled experiments. The monsoon response is also shown to depend on the simulated control climate, and can therefore be sensitive to the use of observed rather than model-derived SSTs to drive the present-day atmospheric simulation, as well as to any approximation in the prescribed radiative forcing. While such results do not challenge the use of time-slice experiments for assessing uncertainties and understanding mechanisms in transient scenarios, they emphasize the need for high-resolution coupled atmosphere-ocean GCMs for dynamical downscaling, or at least for high-resolution atmospheric GCMs coupled with a slab or a regional ocean model.     

Drivers of mean climate change around the Netherlands derived from CMIP5

For the construction of regional climate change scenarios spanning a relevant fraction of the spread in climate model projections, an inventory of major drivers of regional climate change is needed. For the Netherlands, a previous set of regional climate change scenarios was based on the decomposition of local temperature/precipitation changes into components directly linked to the level of global warming, and components related to changes in the regional atmospheric circulation. In this study this decomposition is revisited utilizing the extensive modelling results from the CMIP5 model ensemble in support for the 5th IPCC assessment. Rather than selecting a number of GCMs based on performance metrics or relevant response features, a regression technique was developed to utilize all available model projections. The large number of projections allows a quantification of the separate contributions of emission scenarios, systematic model responses and natural variability to the total likelihood range. Natural variability plays a minor role in modelled differences in the global mean temperature response, but contributes for up to 50 % to the range of mean sea level pressure responses and local precipitation. Using key indicators (“steering variables”) for the temperature and circulation response, the range in local seasonal mean temperature and precipitation responses can be fairly well reproduced.     

Climate response to the physiological impact of carbon dioxide on plants in the Met Office Unified Model HadCM3

The concentration of carbon dioxide in the atmosphere acts to control the stomatal conductance of plants. There is observational and modelling evidence that an increase in the atmospheric concentration of CO₂ would suppress the evapotranspiration (ET) rate over land. This process is known as CO₂ physiological forcing and has been shown to induce changes in surface temperature and continental runoff. We analyse two transient climate simulations for the twenty-first century to isolate the climate response to the CO₂ physiological forcing. The land surface warming associated with the decreased ET rate is accompanied by an increase in the atmospheric lapse rate, an increase in specific humidity, but a decrease in relative humidity and stratiform cloud over land. We find that the water vapour feedback more than compensates for the decrease in latent heat flux over land as far as the budget of atmospheric water vapour is concerned. There is evidence that surface snow, water vapour and cloudiness respond to the CO₂ physiological forcing and all contribute to further warm the climate system. The climate response to the CO₂ physiological forcing has a quite different signature to that from the CO₂ radiative forcing, especially in terms of the changes in the temperature vertical profile and surface energy budget over land.