Impact of global warming on the interannual and interdecadal climate modes in a coupled GCM

In this study, we investigated the impact of global warming on the variabilities of large-scale interannual and interdecadal climate modes and teleconnection patterns with two long-term integrations of the coupled general circulation model of ECHAM4/OPYC3 at the Max-Planck-Institute for Meteorology, Hamburg. One is the control (CTRL) run with fixed present-day concentrations of greenhouse gases. The other experiment is a simulation of transient greenhouse warming, named GHG run. In the GHG run the averaged geopotential height at 500 hPa is increased significantly, and a negative phase of the Pacific/North American (PNA) teleconnection-like distribution pattern is intensified. The standard deviation over the tropics (high latitudes) is enhanced (reduced) on the interdecadal time scales and reduced (enhanced) on the interannual time scales in the GHG run. Except for an interdecadal mode related to the Southern Oscillation (SO) in the GHG run, the spatial variation patterns are similar for different (interannual + interdecadal, interannual, and interdecadal) time scales in the GHG and CTRL runs. Spatial distributions of the teleconnection patterns on the interannual and interdecadal time scales in the GHG run are also similar to those in the CTRL run. But some teleconnection patterns show linear trends and changes of variances and frequencies in the GHG run. Apart from the positive linear trend of the SO, the interdecadal modulation to the El Niño/SO cycle is enhanced during the GHG 2040 ∼ 2099. This is the result of an enhancement of the Walker circulation during that period. La Niña events intensify and El Niño events relatively weaken during the GHG 2070 ∼ 2090. It is interesting to note that with increasing greenhouse gas concentrations the relation between the SO and the PNA pattern is reversed significantly from a negative to a positive correlation on the interdecadal time scales and weakened on the interannual time scales. This suggests that the increase of the greenhouse gas concentrations will trigger the nonstationary correlation between the SO and the PNA pattern both on the interdecadal and interannual time scales.

The effect of nonlinearity in CO2 heating rates on the attribution of stratospheric ozone and temperature changes

An analysis of the attribution of past and future changes in stratospheric ozone and temperature to anthropogenic forcings is presented. The analysis is an extension of the study of Shepherd and Jonsson (2008) who analyzed chemistry-climate simulations from the Canadian Middle Atmosphere Model (CMAM) and attributed both past and future changes to changes in the external forcings, i.e. the abundances of ozone-depleting substances (ODS) and well-mixed greenhouse gases. The current study is based on a new CMAM dataset and includes two important changes. First, we account for the nonlinear radiative response to changes in CO2. It is shown that over centennial time scales the radiative response in the upper stratosphere to CO2 changes is significantly nonlinear and that failure to account for this effect leads to a significant error in the attribution. To our knowledge this nonlinearity has not been considered before in attribution analysis, including multiple linear regression studies. For the regression analysis presented here the nonlinearity was taken into account by using CO2 heating rate, rather than CO2 abundance, as the explanatory variable. This approach yields considerable corrections to the results of the previous study and can be recommended to other researchers. Second, an error in the way the CO2 forcing changes are implemented in the CMAM was corrected, which significantly affects the results for the recent past. As the radiation scheme, based on Fomichev et al. (1998), is used in several other models we provide some description of the problem and how it was fixed.

Dynamics, stratospheric ozone, and climate change

Dynamics affects the distribution and abundance of stratospheric ozone directly through transport of ozone itself and indirectly through its effect on ozone chemistry via temperature and transport of other chemical species. Dynamical processes must be considered in order to understand past ozone changes, especially in the northern hemisphere where there appears to be significant low-frequency variability which can look “trend-like” on decadal time scales. A major challenge is to quantify the predictable, or deterministic, component of past ozone changes. Over the coming century, changes in climate will affect the expected recovery of ozone. For policy reasons it is important to be able to distinguish and separately attribute the effects of ozone-depleting substances and greenhouse gases on both ozone and climate. While the radiative-chemical effects can be relatively easily identified, this is not so evident for dynamics — yet dynamical changes (e.g., changes in the Brewer-Dobson circulation) could have a first-order effect on ozone over particular regions. Understanding the predictability and robustness of such dynamical changes represents another major challenge. Chemistry-climate models have recently emerged as useful tools for addressing these questions, as they provide a self-consistent representation of dynamical aspects of climate and their coupling to ozone chemistry. We can expect such models to play an increasingly central role in the study of ozone and climate in the future, analogous to the central role of global climate models in the study of tropospheric climate change.

Detection of anthropogenic climate change using a fingerprint method

A fingerprint method for detecting anthropogenic climate change is applied to new simulations with a coupled ocean-atmosphere general circulation model (CGCM) forced by increasing concentrations of greenhouse gases and aerosols covering the years 1880 to 2050. In addition to the anthropogenic climate change signal, the space-time structure of the natural climate variability for near-surface temperatures is estimated from instrumental data over the last 134 years and two 1000 year simulations with CGCMs. The estimates are compared with paleoclimate data over 570 years. The space-time information on both the signal and the noise is used to maximize the signal-to-noise ratio of a detection variable obtained by applying an optimal filter (fingerprint) to the observed data. The inclusion of aerosols slows the predicted future warming. The probability that the observed increase in near-surface temperatures in recent decades is of natural origin is estimated to be less than 5%. However, this number is dependent on the estimated natural variability level, which is still subject to some uncertainty.

Feeding nine billion: the challenge to sustainable crop production

In the recent past there was a widespread working assumption in many countries that problems of food production had been solved, and that food security was largely a matter of distribution and access to be achieved principally by open markets. The events of 2008 challenged these assumptions, and made public a much wider debate about the costs of current food production practices to the environment and whether these could be sustained. As in the past 50 years, it is anticipated that future increases in crop production will be achieved largely by increasing yields per unit area rather than by increasing the area of cropped land. However, as yields have increased, so the ratio of photosynthetic energy captured to energy expended in crop production has decreased. This poses a considerable challenge: how to increase yield while simultaneously reducing energy consumption (allied to greenhouse gas emissions) and utilizing resources such as water and phosphate more efficiently. Given the timeframe in which the increased production has to be realized, most of the increase will need to come from crop genotypes that are being bred now, together with known agronomic and management practices that are currently under-developed.

Multimodel assessment of the factors driving stratospheric ozone evolution over the 21st century

The evolution of stratospheric ozone from 1960 to 2100 is examined in simulations from 14 chemistry‐climate models, driven by prescribed levels of halogens and greenhouse gases. There is general agreement among the models that total column ozone reached a minimum around year 2000 at all latitudes, projected to be followed by an increase over the first half of the 21st century. In the second half of the 21st century, ozone is projected to continue increasing, level off, or even decrease depending on the latitude. Separation into partial columns above and below 20 hPa reveals that these latitudinal differences are almost completely caused by differences in the model projections of ozone in the lower stratosphere. At all latitudes, upper stratospheric ozone increases throughout the 21st century and is projected to return to 1960 levels well before the end of the century, although there is a spread among models in the dates that ozone returns to specific historical values. We find decreasing halogens and declining upper atmospheric temperatures, driven by increasing greenhouse gases, contribute almost equally to increases in upper stratospheric ozone. In the tropical lower stratosphere, an increase in upwelling causes a steady decrease in ozone through the 21st century, and total column ozone does not return to 1960 levels in most of the models. In contrast, lower stratospheric and total column ozone in middle and high latitudes increases during the 21st century, returning to 1960 levels well before the end of the century in most models.

Issues in stratosphere-troposphere coupling

An overview is given of current issues concerning the coupling between the stratosphere and troposphere. The tropopause region, more generally the upper troposphere/lower stratosphere, is the region of direct contact where exchange of material takes place. Dynamical coupling through angular momentum transfer by waves occurs nonlocally, and provides a generally negative torque on the stratosphere which drives an equator-to-pole circulation (i.e., towards the Earth’s axis of rotation). This wave-driven circulation is the principal mechanism for intraseasonal and interannual variability in the extratropical stratosphere. Although such variability is generally dynamical in origin, there are important chemical and radiative feedbacks. The location of the tropopause has implications for radiative forcing of climate, through its effect on the distribution of relatively short-lived greenhouse gases (ozone and water vapour). Some outstanding puzzles in our current understanding are identified. Attention is focused on possible climate sensitivities, and how these may be tested and constrained. Results from the Canadian Middle Atmosphere Model (CMAM), a fully interactive radiative-chemical-dynamical general circulation model, are used to illustrate some of the points.

Addressing uncertainty in adaptation planning for agriculture

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

Determination of the gas diffusion coefficient of a peat grassland soil

Peatland habitats are important carbon stocks that also have the potential to be significant sources of greenhouse gases, particularly when subject to changes such as artificial drainage and application of fertilizer. Models aiming to estimate greenhouse gas release from peatlands require an accurate estimate of the diffusion coefficient of gas transport through soil (Ds). The availability of specific measurements for peatland soils is currently limited. This study measured Ds for a peat soil with an overlying clay horizon and compared values with those from widely available models. The Ds value of a sandy loam reference soil was measured for comparison. Using the Currie (1960) method, Ds was measured between an air-filled porosity (ϵ) range of 0 and 0.5 cm3 cm−3. Values of Ds for the peat cores ranged between 3.2 × 10−4 and 4.4 × 10−3 m2 hour−1, for loamy clay cores between 0 and 4.7 × 10−3 m2 hour−1 and for the sandy reference soil they were between 5.4 × 10−4 and 3.4 × 10−3 m2 hour−1. The agreement of measured and modelled values of relative diffusivity (Ds/D0, with D0 the diffusion coefficient through free air) varied with soil type; however, the Campbell (1985) model provided the best replication of measured values for all soils. This research therefore suggests that the use of the Campbell model in the absence of accurately measured Ds and porosity values for a study soil would be appropriate. Future research into methods to reduce shrinkage of peat during measurement and therefore allow measurement of Ds for a greater range of ϵ would be beneficial.

Post-occupancy evaluation studies in recently refurbished office building: energy performance and employees' satisfaction

Existing buildings contribute greatly to global energy use and greenhouse gas emissions. In the UK, about 18% of carbon emissions are generated by non-domestic buildings; sustainable building refurbishment can play an important role in reducing carbon emissions. This paper looks at the performance of a recently refurbished 5-storey office building in London, in terms of energy consumption as well as occupants’ satisfaction. Pre- and post-occupancy evaluation studies were conducted using online questionnaire surveys and energy consumption evaluation. Results from pre-occupancy and post-occupancy evaluation studies showed that employees, in general, were more satisfied with their work environment at the refurbished building than with that of their previous office. Employees’ self-reported productivity improved after the move to Elms House. These surveys showed a positive relationship between employees’ satisfaction with their work environment and their self-reported productivity, well-being and enjoyment at work. The factor that contributed to increasing employee satisfaction the most was: better use of interior space. Although the refurbishment was a success in terms of reducing energy consumption per m2, the performance gap was almost 3 times greater than that estimated. Unregulated loads, problems with building control, ineffective use of space and occupants’ behaviour are argued to be reasons for this gap.

Uncertainty in simulating wheat yields under climate change

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

The AVOID programme’s new simulations of the global benefits of stringent climate change mitigation

Quantitative simulations of the global-scale benefits of climate change mitigation are presented, using a harmonised, self-consistent approach based on a single set of climate change scenarios. The approach draws on a synthesis of output from both physically-based and economics-based models, and incorporates uncertainty analyses. Previous studies have projected global and regional climate change and its impacts over the 21st century but have generally focused on analysis of business-as-usual scenarios, with no explicit mitigation policy included. This study finds that both the economics-based and physically-based models indicate that early, stringent mitigation would avoid a large proportion of the impacts of climate change projected for the 2080s. However, it also shows that not all the impacts can now be avoided, so that adaptation would also therefore be needed to avoid some of the potential damage. Delay in mitigation substantially reduces the percentage of impacts that can be avoided, providing strong new quantitative evidence for the need for stringent and prompt global mitigation action on greenhouse gas emissions, combined with effective adaptation, if large, widespread climate change impacts are to be avoided. Energy technology models suggest that such stringent and prompt mitigation action is technologically feasible, although the estimated costs vary depending on the specific modelling approach and assumptions.

Tackling regional climate change by leaf albedo bio-geoengineering

The likelihood that continuing greenhouse-gas emissions will lead to an unmanageable degree of climate change [1] has stimulated the search for planetary-scale technological solutions for reducing global warming [2] (“geoengineering”), typically characterized by the necessity for costly new infrastructures and industries [3]. We suggest that the existing global infrastructure associated with arable agriculture can help, given that crop plants exert an important influence over the climatic energy budget 4 and 5 because of differences in their albedo (solar reflectivity) compared to soils and to natural vegetation [6]. Specifically, we propose a “bio-geoengineering” approach to mitigate surface warming, in which crop varieties having specific leaf glossiness and/or canopy morphological traits are specifically chosen to maximize solar reflectivity. We quantify this by modifying the canopy albedo of vegetation in prescribed cropland areas in a global-climate model, and thereby estimate the near-term potential for bio-geoengineering to be a summertime cooling of more than 1°C throughout much of central North America and midlatitude Eurasia, equivalent to seasonally offsetting approximately one-fifth of regional warming due to doubling of atmospheric CO2[7]. Ultimately, genetic modification of plant leaf waxes or canopy structure could achieve greater temperature reductions, although better characterization of existing intraspecies variability is needed first.

High-latitude climate sensitivity to ice-sheet forcing over the last 120kyr

Interpretation of ice-core records is currently limited by paucity of modelling at adequate temporal and spatial resolutions. Several key questions relate to mechanisms of polar amplification and inter-hemispheric coupling on glacial/interglacial timescales. Here, we present the first results from a large set of global ocean–atmosphere climate model ‘snap-shot’ simulations covering the last 120 000 years using the Hadley Centre climate model (HadCM3) at up to 1 kyr temporal resolution. Two sets of simulations were performed in order to examine the roles of orbit and greenhouse gases versus ice-sheet forcing of orbital-scale climate change. A series of idealised Heinrich events were also simulated, but no changes to aerosols or vegetation were prescribed. This paper focuses on high latitudes and inter-hemispheric linkages. The simulations reproduce polar temperature trends well compared to ice-core reconstructions, although the magnitude is underestimated. Polar amplification varies with obliquity, but this variability is dampened by including variations in land ice coverage, while the overall amplification factor increases. The relatively constant amplification of Antarctic temperatures (with ice-sheet forcing included) suggests it is possible to use Antarctic temperature reconstructions to estimate global changes (which are roughly half the magnitude). Atlantic Ocean overturning circulation varies considerably only with the introduction of Northern Hemisphere ice sheets, but only weakens in the North Atlantic in the deep glacial, when ocean–sea-ice feedbacks result in the movement of the region of deep convection to lower latitudes and with the introduction of freshwater to the surface North Atlantic in order to simulate Heinrich events.