Simple Climate Model Research Articles

Heat wave hazard classification and risk assessment using artificial intelligence fuzzy logic

The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.

Intercomparison of the capabilities of simplified climate models to project the effects of aviation CO2 on climate

This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air–sea and air–biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.

Reducing CO<sub>2</sub> from shipping – do non-CO<sub>2</sub> effects matter?

Abstract. Shipping is a growing sector in the global economy, and it contributions to global CO2 emissions are expected to increase. CO2 emissions from the world shipping fleet will likely be regulated in the near future, and studies have shown that significant emission reductions can be achieved at low cost. Regulations are being discussed for both existing ships as well as for future additions to the fleet. In this study a plausible CO2 emission reduction inventory is constructed for the cargo fleet existing in 2010, as well as for container ships, bulk ships and tankers separately. In the reduction inventories, CO2 emissions are reduced by 25–32% relative to baseline by applying 15 technical and operational emission reduction measures in accordance with a ship-type-specific cost-effectiveness criterion, and 9 other emission compounds are changed as a technical implication of reducing CO2. The overall climate and environmental effects of the changes to all 10 emission components in the reduction inventory are assessed using a chemical transport model, radiative forcing (RF) models and a simple climate model. We find substantial environmental and health benefits with up to 5% reduction in surface ozone levels, 15% reductions in surface sulfate and 10% reductions in wet deposition of sulfate in certain regions exposed to heavy ship traffic. The major ship types show distinctly different contributions in specific locations. For instance, the container fleet contributes 50% of the sulfate decline on the west coast of North America. The global radiative forcing from a 1 yr emission equal to the difference between baseline and reduction inventory shows an initial strong positive forcing from non-CO2 compounds. This warming effect is due to reduced cooling by aerosols and methane. After approximately 25 yr, the non-CO2 forcing is balanced by the CO2 forcing. For the global mean temperature change, we find a shift from warming to cooling after approximately 60 yr. The major ship types show significant differences in the short-term radiative forcing. For instance, the direct SO4 forcing from tankers is 30% higher than for container and bulk. The net long-term effects on RF are similar due to similar CO2 forcing. We assess an emission scenario where the reduction inventory is sustained on the fleet as it steadily diminishes over time due to scrapping and disappears in 2040. We find a net temperature increase lasting until approximately 2080. We conclude that changes in non-CO2 emission does matter significantly if reductions of CO2 emissions are made on the year 2010 cargo shipping fleet. In sum, we find that emission changes motivated by CO2 reductions in shipping will be beneficial from a long-term climate perspective, and that there are positive environmental and health effects identified as concentrations of key short-lived pollutants are reduced.

A new method to diagnose the contribution of anthropogenic activities to temperature: temperature tagging

Abstract. This study presents a new methodology, called temperature tagging. It keeps track of the contributions of individual processes to temperature within a climate model simulation. As a first step and as a test bed, a simple box climate model is regarded. The model consists of an atmosphere, which absorbs and emits radiation, and of a surface, which reflects, absorbs and emits radiation. The tagging methodology is used to investigate the impact of the atmosphere on surface temperature. Four processes are investigated in more detail and their contribution to the surface temperature quantified: (i) shortwave influx and shortwave atmospheric absorption ("sw"), (ii) longwave atmospheric absorption due to non-CO2 greenhouse gases ("nC"), (iii) due to a base case CO2 concentration ("bC"), and (iv) due to an enhanced CO2 concentration ("eC"). The differential equation for the temperature in the box climate model is decomposed into four equations for the tagged temperatures. This method is applied to investigate the contribution of longwave absorption to the surface temperature (greenhouse effect), which is calculated to be 68 K. This estimate contrasts an alternative calculation of the greenhouse effect of slightly more than 30 K based on the difference of the surface temperature with and without an atmosphere. The difference of the two estimates is due to a shortwave cooling effect and a reduced contribution of the shortwave to the total downward flux: the shortwave absorption of the atmosphere results in a reduced net shortwave flux at the surface of 192 W m−2, leading to a cooling of the surface by 14 K. Introducing an atmosphere results in a downward longwave flux at the surface due to atmospheric absorption of 189 W m−2, which roughly equals the net shortwave flux of 192 W m−2. This longwave flux is a result of both the radiation due to atmospheric temperatures and its longwave absorption. Hence the longwave absorption roughly accounts for 91 W m−2 out of a total of 381 W m−2 (roughly 25%) and therefore accounts for a temperature change of 68 K. In a second experiment, the CO2 concentration is doubled, which leads to an increase in surface temperature of 1.2 K, resulting from a temperature increase due to CO2 of 1.9 K, due to non-CO2 greenhouse gases of 0.6 K and a cooling of 1.3 K due to a reduced importance of the solar heating for the surface and atmospheric temperatures. These two experiments show the feasibility of temperature tagging and its potential as a diagnostic for climate simulations.

Surface response to stratospheric aerosol changes in a coupled atmosphere–ocean model

AbstractPrevious work with a simple climate model has suggested a global cooling impact of increasing stratospheric aerosol. Here we use a comprehensive Earth System Model including coupled atmosphere and ocean components to show that increasing stratospheric aerosol since the late 1990s has reduced global warming by at least 0.07 C to present and that a further global cooling impact will occur if the observed stratospheric aerosol trend continues to the end of this decade. This result confirms the previous work and suggests that climate models that do not account for stratospheric aerosol increase will overestimate global warming to a small but notable degree. An additional new finding is that increasing stratospheric aerosol since the late 1990s has reduced the rise in global mean precipitation.Finally, regional patterns of change in simulations with stratospheric aerosol increase to year 2020 show ~40% less equatorial precipitation increase and ~60% greater surface pressure decrease around Antarctica, relative to simulations without such stratospheric aerosol changes.

Probabilistic projections of transient climate change

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.

A scaling approach to project regional sea level rise and its uncertainties

Abstract. Climate change causes global mean sea level to rise due to thermal expansion of seawater and loss of land ice from mountain glaciers, ice caps and ice sheets. Locally, sea level can strongly deviate from the global mean rise due to changes in wind and ocean currents. In addition, gravitational adjustments redistribute seawater away from shrinking ice masses. However, the land ice contribution to sea level rise (SLR) remains very challenging to model, and comprehensive regional sea level projections, which include appropriate gravitational adjustments, are still a nascent field (Katsman et al., 2011; Slangen et al., 2011). Here, we present an alternative approach to derive regional sea level changes for a range of emission and land ice melt scenarios, combining probabilistic forecasts of a simple climate model (MAGICC6) with the new CMIP5 general circulation models. The contribution from ice sheets varies considerably depending on the assumptions for the ice sheet projections, and thus represents sizeable uncertainties for future sea level rise. However, several consistent and robust patterns emerge from our analysis: at low latitudes, especially in the Indian Ocean and Western Pacific, sea level will likely rise more than the global mean (mostly by 10–20%). Around the northeastern Atlantic and the northeastern Pacific coasts, sea level will rise less than the global average or, in some rare cases, even fall. In the northwestern Atlantic, along the American coast, a strong dynamic sea level rise is counteracted by gravitational depression due to Greenland ice melt; whether sea level will be above- or below-average will depend on the relative contribution of these two factors. Our regional sea level projections and the diagnosed uncertainties provide an improved basis for coastal impact analysis and infrastructure planning for adaptation to climate change.

Physically Consistent Responses of the Global Atmospheric Hydrological Cycle in Models and Observations

Abstract Robust and physically understandable responses of the global atmospheric water cycle to a warming climate are presented. By considering interannual responses to changes in surface temperature (T), observations and AMIP5 simulations agree on an increase in column integrated water vapor at the rate 7 %/K (in line with the Clausius–Clapeyron equation) and of precipitation at the rate 2–3 %/K (in line with energetic constraints). Using simple and complex climate models, we demonstrate that radiative forcing by greenhouse gases is currently suppressing global precipitation (P) at ∼−0.15 %/decade. Along with natural variability, this can explain why observed trends in global P over the period 1988−2008 are close to zero. Regional responses in the global water cycle are strongly constrained by changes in moisture fluxes. Model simulations show an increased moisture flux into the tropical wet region at 900 hPa and an enhanced outflow (of smaller magnitude) at around 600 hPa with warming. Moisture transport explains an increase in P in the wet tropical regions and small or negative changes in the dry regions of the subtropics in CMIP5 simulations of a warming climate. For AMIP5 simulations and satellite observations, the heaviest 5-day rainfall totals increase in intensity at ∼15 %/K over the ocean with reductions at all percentiles over land. The climate change response in CMIP5 simulations shows consistent increases in P over ocean and land for the highest intensities, close to the Clausius−Clapeyron scaling of 7 %/K, while P declines for the lowest percentiles, indicating that interannual variability over land may not be a good proxy for climate change. The local changes in precipitation and its extremes are highly dependent upon small shifts in the large-scale atmospheric circulation and regional feedbacks.

Modeling the Global Warming Potential of Greenhouse Gases due to Climatic Change

The Global Warming Potential (GWP) is used within the Kyoto Protocol to the United Nations Framework Convention on Climate Change as a metric for weighting the climatic impact of emission of different greenhouse gases. Here, two metrics are proposed, which are based on a simple analytical climate model. The first metric is called the Global Temperature Change Potential model and represents the temperature change at a given time due to a pulse emission of a gas (GTPp); the second is similar but represents the effect of a sustained emission change model (GTPs). Both GTPp and GTPs are presented as relative to the temperature change due to a similar emission change of a reference gas, carbon dioxide.

Interactions between perturbations to different Earth system components simulated by a fully-coupled climate model

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.

Soil water availability strongly modulates soil CO2 efflux in different Mediterranean ecosystems: Model calibration using the Bayesian approach

Soil respiration in drought prone regions is highly dependent on the precipitation regime and soil moisture conditions, which are expected to change in a global warming context. In the present study we used an extensive collection of field chamber measurements of soil respiration (Rs) from forest and grassland sites of centre and south of Portugal distributed over a 10 year period. This data were summarized and analysed with the objective to describe seasonal variability of Rs as affected by soil moisture (Hs) and soil temperature (Ts). A Bayesian framework was used to test the effectiveness of soil bioclimatic models in estimating Rs on a daily and monthly time step. Rs seasonality was similar between sites, reaching a maximum in spring and autumn and a minimum in the dry season (July–September). No differences were observed for Rs between sites with different standing biomass or soil carbon stocks either on an annual or seasonal timescale. Hs, and not Ts, was the driving factor of Rs during most of the year. Ts drove Rs response only above certain Hs limits: 10% for forest sites and 15% for grassland sites leading to a Q10 of 2.01, 1.61 and 1.31 for closed forests, open forests and grasslands, respectively. The Bayesian analysis showed that models using Hs as an independent variable performed better than models driven by Ts alone. Monthly estimates of Rs in grasslands can be predicted by simple climatic models based on Hs but none of them was suitable for forest ecosystems, stressing the need for a process-based approach. This study adds to the evidence that Hs controls Rs fluxes for Mediterranean ecosystems and should always be taken into account for extrapolation purposes.

Lower bounds to future sea-level rise

Sea-level rise is among the most important changes expected as a consequence of anthropogenic global warming. Climate model-based projections made until the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) yield a 21st century rise spanning nearly 20–60cm. However, it is known that current climate models are likely to underestimate sea-level change in response to rapid climatic variations. Recent alternative semi-empirical approaches predict a much higher sea-level rise than the IPCC AR4 projections. Nevertheless, the underway depletion of conventional fossil fuels might, at least in principle, constrain future fossil CO2 emissions and, in turn, affect also the extent of sea-level rise. Here we project 2000–2200 sea-level rise with a semi-empirical method coupled to a simple climate model that is run under a range of fossil-fuel exhaustion scenarios. We find that, in spite of fossil-fuel depletion, sea level is predicted to rise by at least ~80cm at the end of this century and is expected to continue rising for at least the next two hundred years. The present results support the need for prompt and substantial emission cuts in order to slow down future sea-level rise and implement adaptation measures.

Global-Mean Temperature Change from Shipping toward 2050: Improved Representation of the Indirect Aerosol Effect in Simple Climate Models

We utilize a range of emission scenarios for shipping to determine the induced global-mean radiative forcing and temperature change. Ship emission scenarios consistent with the new regulations on nitrogen oxides (NO(x)) and sulfur dioxide (SO(2)) from the International Maritime Organization and two of the Representative Concentration Pathways are used as input to a simple climate model (SCM). Based on a complex aerosol-climate model we develop and test new parametrizations of the indirect aerosol effect (IAE) in the SCM that account for nonlinearities in radiative forcing of ship-induced IAE. We find that shipping causes a net global cooling impact throughout the period 1900-2050 across all parametrizations and scenarios. However, calculated total net global-mean temperature change in 2050 ranges from -0.03[-0.07,-0.002]°C to -0.3[-0.6,-0.2]°C in the A1B scenario. This wide range across parametrizations emphasizes the importance of properly representing the IAE in SCMs and to reflect the uncertainties from complex global models. Furthermore, our calculations show that the future ship-induced temperature response is likely a continued cooling if SO(2) and NO(x) emissions continue to increase due to a strong increase in activity, despite current emission regulations. However, such cooling does not negate the need for continued efforts to reduce CO(2) emissions, since residual warming from CO(2) is long-lived.

Colorado River Basin Hydroclimatic Variability

Abstract An analysis of annual hydroclimatic variability in the Upper Colorado River basin (UCRB) for the period of 1906–2006 was performed to understand the dominant modes of multidecadal variability. First, wavelet-based spectral analysis was employed for streamflow at Lees Ferry, Arizona (aggregate location for UCRB flow), which identified two significant modes: a “low frequency” (~64-yr period) mode and a strong “decadal” (~15-yr period) component active only in recent decades. Subsequent investigation of temperature and precipitation data for the UCRB indicated that the low-frequency variability is associated with temperature via modulation of runoff efficiency while the decadal is strongly tied to moisture delivery. Simple hydrology and climate model experiments are also provided to support the aforementioned findings. Correlation of UCRB precipitation with global sea surface temperature (SST) anomalies showed a strong link with the equatorial and northern Pacific during periods of heightened variability of the decadal mode. The correlation of UCRB temperature with global SST anomalies showed strongest values in the Atlantic consistent with the Atlantic multidecadal oscillation mode. Wavelet spectral analysis of paleo-reconstructed streamflow at Lees Ferry shows both the low-frequency and decadal flow variability features. Furthermore, the strength of the decadal mode is modulated at an ~75-yr time scale, and these are consistent with epochal variations of overall streamflow variance.

Climatic impacts of stochastic fluctuations in air–sea fluxes

Air–sea fluxes vary partly on scales that are too small or fast to be resolved explicitly by global climate models. This paper proposes a nonlinear physical mechanism by which stochastic fluctuations in the air–sea buoyancy flux may modify the mean climate. The paper then demonstrates the mechanism in climate simulations with a comprehensive coupled general circulation model. Significant changes are detected in the time‐mean oceanic mixed‐layer depth, sea‐surface temperature, atmospheric Hadley circulation, and net upward water flux at the sea surface. Also, El Niño Southern Oscillation (ENSO) variability is significantly increased. The findings demonstrate that noise‐induced drift and noise‐enhanced variability, which are familiar concepts from simple climate models, continue to apply in comprehensive climate models with millions of degrees of freedom. The findings also suggest that the lack of representation of sub‐grid variability in air–sea fluxes may contribute to some of the biases exhibited by contemporary climate models.

Sensitivity of Cloud Liquid Water Content Estimates to the Temperature-Dependent Thermodynamic Phase: A Global Study Using CloudSat Data

Abstract The main purpose of this study is to underline the sensitivity of cloud liquid water content (LWC) estimates purely to 1) the shape of computationally simplified temperature-dependent thermodynamic phase and 2) the range of subzero temperatures covered to partition total cloud condensate into liquid and ice fractions. Linear, quadratic, or sigmoid-shaped functions for subfreezing temperatures (down to −20° or −40°C) are often used in climate models and reanalysis datasets for partitioning total condensate. The global vertical profiles of clouds obtained from CloudSat for the 4-yr period June 2006–May 2010 are used for sensitivity analysis and the quantitative estimates of sensitivities based on these realistic cloud profiles are provided. It is found that three cloud regimes in particular—convective clouds in the tropics, low-level clouds in the northern high latitudes, and middle-level clouds over the midlatitudes and Southern Ocean—are most sensitive to assumptions on thermodynamic phase. In these clouds, the LWC estimates based purely on quadratic or sigmoid-shaped functions with a temperature range down to −20°C can differ by up to 20%–40% over the tropics (in seasonal means), 10%–30% over the midlatitudes, and up to 50% over high latitudes compared to a linear assumption. When the temperature range is extended down to −40°C, LWC estimates in the sigmoid case can be much higher than the above values over high-latitude regions compared to the commonly used case with quadratic dependency down to −20°C. This sensitivity study emphasizes the need to critically investigate radiative impacts of cloud thermodynamic phase assumptions in simplified climate models and reanalysis datasets.

Reversibility in an Earth System model in response to CO2 concentration changes

We use the HadGEM2-ES Earth System model to examine the degree of reversibility of a wide range of components of the Earth System under idealized climate change scenarios where the atmospheric CO2 concentration is gradually increased to four times the pre-industrial level and then reduced at a similar rate from several points along this trajectory. While some modelled quantities respond almost immediately to the atmospheric CO2 concentrations, others exhibit a time lag relative to the change in CO2. Most quantities also exhibit a lag relative to the global-mean surface temperature change, which can be described as a hysteresis behaviour. The most surprising responses are from low-level clouds and ocean stratification in the Southern Ocean, which both exhibit hysteresis on timescales longer than expected. We see no evidence of critical thresholds in these simulations, although some of the hysteresis phenomena become more apparent above 2 × CO2 or 3 × CO2. Our findings have implications for the parametrization of climate impacts in integrated assessment and simple climate models and for future climate studies of geoengineering scenarios.

Climate Effects of Emission Standards: The Case for Gasoline and Diesel Cars

Passenger transport affects climate through various mechanisms involving both long-lived and short-lived climate forcers. Because diesel cars generally emit less CO(2) than gasoline cars, CO(2) emission taxes for vehicle registrations and fuels enhance the consumer preference for diesel cars over gasoline cars. However, with the non-CO(2) components, which have been changed and will be changed under the previous and upcoming vehicle emission standards, what does the shift from gasoline to diesel cars mean for the climate mitigation? By using a simple climate model, we demonstrate that, under the earlier emissions standards (EURO 3 and 4), a diesel car causes a larger warming up to a decade after the emissions than a similar gasoline car due to the higher emissions of black carbon and NO(X) (enhancing the O(3) production). Beyond a decade, the warming caused by a diesel car becomes, however, weaker because of the lower CO(2) emissions. As the latter emissions standards (EURO 5 and 6) are phased in, the short-term warming due to a diesel car becomes smaller primarily due to the lower black carbon emissions. Thus, although results are subject to restrictive assumptions and uncertainties, the switch from gasoline to diesel cars encouraged by CO(2) taxes does not contradict with the climate mitigation focusing on long-term consequences.

Broad range of 2050 warming from an observationally constrained large climate model ensemble

Incomplete understanding of three aspects of the climate system—equilibrium climate sensitivity, rate of ocean heat uptake and historical aerosol forcing—and the physical processes underlying them lead to uncertainties in our assessment of the global-mean temperature evolution in the twenty-first century 1,2 . Explorations of these uncertainties have so far relied on scaling approaches 3,4 , large ensembles of simplified climate models 1,2 , or small ensembles of complex coupled atmosphere‐ocean general circulation models 5,6 which under-represent uncertainties in key climate system properties derived from independent sources 7‐9 . Here we present results from a multi-thousand-member perturbed-physics ensemble of transient coupled atmosphere‐ocean general circulation model simulations. We find that model versions that reproduce observed surface temperature changes over the past 50 years show global-mean temperature increases of 1.4‐3 K by 2050, relative to 1961‐1990, under a mid-range forcing scenario. This range of warming is broadly consistent with the expert assessment provided by the Intergovernmental Panel on Climate Change Fourth Assessment Report 10 , but extends towards larger warming than observed in ensemblesof-opportunity 5 typically used for climate impact assessments. From our simulations, we conclude that warming by the middle of the twenty-first century that is stronger than earlier estimates is consistent with recent observed temperature changes and a mid-range ‘no mitigation’ scenario for greenhouse-gas emissions. In the latest generation of coupled atmosphereocean general circulation models (AOGCMs) contributing to the Coupled Model Intercomparison Project phase 3 (CMIP-3), uncertainties in key propertiescontrollingthetwenty-firstcenturyresponsetosustained anthropogenic greenhouse-gas forcing were not fully sampled, partially owing to a correlation between climate sensitivity and aerosol forcing 7,8 , a tendency to overestimate ocean heat uptake 11,12 and compensation between short-wave and long-wave feedbacks 9 . This complicates the interpretation of the ensemble spread as a direct uncertainty estimate, a point reflected in the fact that the ‘likely’ (>66% probability) uncertainty range on the transient response was explicitly subjectively assessed as40% to C60% of

What influence will future solar activity changes over the 21st century have on projected global near‐surface temperature changes?

During the 20th century, solar activity increased in magnitude to a so‐called grand maximum. It is probable that this high level of solar activity is at or near its end. It is of great interest whether any future reduction in solar activity could have a significant impact on climate that could partially offset the projected anthropogenic warming. Observations and reconstructions of solar activity over the last 9000 years are used as a constraint on possible future variations to produce probability distributions of total solar irradiance over the next 100 years. Using this information, with a simple climate model, we present results of the potential implications for future projections of climate on decadal to multidecadal timescales. Using one of the most recent reconstructions of historic total solar irradiance, the likely reduction in the warming by 2100 is found to be between 0.06 and 0.1 K, a very small fraction of the projected anthropogenic warming. However, if past total solar irradiance variations are larger and climate models substantially underestimate the response to solar variations, then there is a potential for a reduction in solar activity to mitigate a small proportion of the future warming, a scenario we cannot totally rule out. While the Sun is not expected to provide substantial delays in the time to reach critical temperature thresholds, any small delays it might provide are likely to be greater for lower anthropogenic emissions scenarios than for higher‐emissions scenarios.