Impact of future climate changes on high pollution levels

Changes in climate variability as well as changes in extreme weather and climate events in the 20th century, especially those that took place during the last two to three decades of the 20th century, have been discussed in many recent scientific publications. Attempts to project the results of such studies in the future have been made under different assumptions. In this paper, we have chosen one of the well-known scenarios predicting changes of the climate in the world during the last 30 years of the 21st century. This scenario is used, together with several general predictions related to the future climate, to produce three climatic scenarios. The derived climatic scenarios are used to calculate predictions for future pollution levels in Denmark and in Europe by applying the Unified Danish Eulerian Model (UNI-DEM), on a space domain containing the whole of Europe.

Scenarios as the basis for assessment of mitigation and adaptation

The possibilities and need for adaptation and mitigation depends on uncertain future developments with respect to socio-economic factors and the climate system. Scenarios are used to explore the impacts of different strategies under uncertainty. In this chapter, some scenarios are presented that are used in the ADAM project for this purpose. One scenario explores developments with no mitigation, and thus with high temperature increase and high reliance on adaptation (leading to 4oC increase by 2100 compared to pre-industrial levels). A second scenario explores an ambitious mitigation strategy (leading to 2oC increase by 2100 compared to pre-industrial levels). In the latter scenario, stringent mitigation strategies effectively reduces the risks of climate change, but based on uncertainties in the climate system a temperature increase of 3oC or more cannot be excluded. The analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but even then adaptation will be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which adaptation is more cost-effective than mitigation, but mitigation can help reduce damages and the cost of adaptation. For agriculture, finally, only the scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts.

A climate change risk analysis for world ecosystems

We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from 16 climate models and mapping the proportions of model runs showing forest/nonforest shifts or exceedance of natural variability in wildfire frequency and freshwater supply. Our analysis does not assign probabilities to scenarios or weights to models. Instead, we consider distribution of outcomes within three sets of model runs grouped by the amount of global warming they simulate: <2°C (including simulations in which atmospheric composition is held constant, i.e., in which the only climate change is due to greenhouse gases already emitted), 2–3°C, and >3°C. High risk of forest loss is shown for Eurasia, eastern China, Canada, Central America, and Amazonia, with forest extensions into the Arctic and semiarid savannas; more frequent wildfire in Amazonia, the far north, and many semiarid regions; more runoff north of 50°N and in tropical Africa and northwestern South America; and less runoff in West Africa, Central America, southern Europe, and the eastern U.S. Substantially larger areas are affected for global warming >3°C than for <2°C; some features appear only at higher warming levels. A land carbon sink of ≈1 Pg of C per yr is simulated for the late 20th century, but for >3°C this sink converts to a carbon source during the 21st century (implying a positive climate feedback) in 44% of cases. The risks continue increasing over the following 200 years, even with atmospheric composition held constant.

Observed adaptation to climate change: UK evidence of transition to a well-adapting society

This paper investigates whether and to what extent a wide range of actors in the UK are adapting to climate change, and whether this is evidence of a social transition. We document evidence of over 300 examples of early adopters of adaptation practice to climate change in the UK. These examples span a range of activities from small adjustments (or coping) to building adaptive capacity, implementing actions and creating deeper systemic change in public and private organisations in a range of sectors. We find that adaptation in the UK has been dominated by government initiatives and has principally occurred in the form of research into climate change impacts. These actions within government stimulate a further set of actions at other scales in public agencies, regulatory agencies and regional government (or in the devolved administrations), though with little real evidence of climate change adaptation initiatives trickling down to local government level. The water supply and flood defence sectors, requiring significant investment in large scale infrastructure such as reservoirs and coastal defences, have invested more heavily in identifying potential impacts and adaptations. Economic sectors that are not dependent on large scale infrastructure appear to be investing far less effort and resources in preparing for climate change. We conclude that while the government-driven top-down targeted adaptation approach has generated anticipatory action at low cost, it may also have created enough niche activities to allow for diffusion of new adaptation practices in response to real or perceived climate change. These results have significant implications for how climate policy can be developed to support autonomous adaptors in the UK and other countries.

Energetics of climate models: net energy balance and meridional enthalpy transport

We analyze the publicly released outputs of the simulations performed by climate models (CMs) in preindustrial (PI) and Special Report on Emissions Scenarios A1B (SRESA1B) conditions. In the PI simulations, most CMs feature biases of the order of 1 W m −2 for the net global and the net atmospheric, oceanic, and land energy balances. This does not result from transient effects but depends on the imperfect closure of the energy cycle in the fluid components and on inconsistencies over land. Thus, the planetary emission temperature is underestimated, which may explain the CMs' cold bias. In the PI scenario, CMs agree on the meridional atmospheric enthalpy transport's peak location (around 40°N/S), while discrepancies of ∼20% exist on the intensity. Disagreements on the oceanic transport peaks' location and intensity amount to ∼10° and ∼50%, respectively. In the SRESA1B runs, the atmospheric transport's peak shifts poleward, and its intensity increases up to ∼10% in both hemispheres. In most CMs, the Northern Hemispheric oceanic transport decreases, and the peaks shift equatorward in both hemispheres. The Bjerknes compensation mechanism is active both on climatological and interannual time scales. The total meridional transport peaks around 35° in both hemispheres and scenarios, whereas disagreements on the intensity reach ∼20%. With increased CO 2 concentration, the total transport increases up to ∼10%, thus contributing to polar amplification of global warming. Advances are needed for achieving a self-consistent representation of climate as a nonequilibrium thermodynamical system. This is crucial for improving the CMs' skill in representing past and future climate changes.

Transport impacts on atmosphere and climate: metrics

The transport sector emits a wide variety of gases and aerosols, with distinctly different characteristics which influence climate directly and indirectly via chemical and physical processes. Tools that allow these emissions to be placed on some kind of common scale in terms of their impact on climate have a number of possible uses such as: in agreements and emission trading schemes; when considering potential trade-offs between changes in emissions resulting from technological or operational developments; and/or for comparing the impact of different environmental impacts of transport activities. Many of the non-CO2 emissions from the transport sector are short-lived substances, not currently covered by the Kyoto Protocol. There are formidable difficulties in developing metrics and these are particularly acute for such short-lived species. One difficulty concerns the choice of an appropriate structure for the metric (which may depend on, for example, the design of any climate policy it is intended to serve) and the associated value judgements on the appropriate time periods to consider; these choices affect the perception of the relative importance of short- and long-lived species. A second difficulty is the quantification of input parameters (due to underlying uncertainty in atmospheric processes). In addition, for some transport-related emissions, the values of metrics (unlike the gases included in the Kyoto Protocol) depend on where and when the emissions are introduced into the atmosphere – both the regional distribution and, for aircraft, the distribution as a function of altitude, are important. In this assessment of such metrics, we present Global Warming Potentials (GWPs) as these have traditionally been used in the implementation of climate policy. We also present Global Temperature Change Potentials (GTPs) as an alternative metric, as this, or a similar metric may be more appropriate for use in some circumstances. We use radiative forcings and lifetimes from the literature to derive GWPs and GTPs for the main transport-related emissions, and discuss the uncertainties in these estimates. We find large variations in metric (GWP and GTP) values for NOx, mainly due to the dependence on location of emissions but also because of inter-model differences and differences in experimental design. For aerosols we give only global-mean values due to an inconsistent picture amongst available studies regarding regional dependence. The uncertainty in the presented metric values reflects the current state of understanding; the ranking of the various components with respect to our confidence in the given metric values is also given. While the focus is mostly on metrics for comparing the climate impact of emissions, many of the issues are equally relevant for stratospheric ozone depletion metrics, which are also discussed.

A model study of factors influencing projected changes in regional sea level over the 21st century

In addition to projected increases in global mean sea level over the 21st century, model simulations suggest there will also be changes in the regional distribution of sea level relative to the global mean. There is a considerable spread in the projected patterns of these changes by current models, as shown by the recent Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment (AR4). This spread has not reduced from that given by the Third Assessment models. Comparison with projections by ensembles of models based on a single structure supports an earlier suggestion that models of similar formulation give more similar patterns of sea level change. Analysing an AR4 ensemble of model projections under a business-as-usual scenario shows that steric changes (associated with subsurface ocean density changes) largely dominate the sea level pattern changes. The relative importance of subsurface temperature or salinity changes in contributing to this differs from region to region and, to an extent, from model-to-model. In general, thermosteric changes give the spatial variations in the Southern Ocean, halosteric changes dominate in the Arctic and strong compensation between thermosteric and halosteric changes characterises the Atlantic. The magnitude of sea level and component changes in the Atlantic appear to be linked to the amount of Atlantic meridional overturning circulation (MOC) weakening. When the MOC weakening is substantial, the Atlantic thermosteric patterns of change arise from a dominant role of ocean advective heat flux changes.

Emulating AOGCM results using simple climate models

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

Climate change and the British Uplands: evidence for decision-making

We summarise the work of an interdisciplinary network set up to explore the impacts of climate change in the British Uplands. In this CR Special, the contributors present the state of knowledge and this introduction synthesises this knowledge and derives implications for decision makers. The Uplands are valued semi-natural habitats, providing ecosystem services that have historically been taken for granted. For example, peat soils, which are mostly found in the Uplands, contain around 50% of the terrestrial carbon in the UK. Land management continues to be a driver of ecosystem service delivery. Degraded and managed peatlands are subject to erosion and carbon loss with negative impacts on biodiversity, carbon storage and water quality. Climate change is already being experienced in British Uplands and is likely to exacerbate these pressures. Climate envelope models suggest as much as 50% of British Uplands and peatlands will be exposed to climate stress by the end of the 21st century under low and high emissions scenarios. However, process-based models of the response of organic soils to this climate stress do not give a consistent indication of what this will mean for soil carbon: results range from a very slight increase in uptake, through a clear decline, to a net carbon loss. Preserving existing peat stocks is an important climate mitigation strategy, even if new peat stops forming. Preserving upland vegetation cover is a key win–win management strategy that will reduce erosion and loss of soil carbon, and protect a variety of services such as the continued delivery of a high quality water resource.

A sensitivity study for water availability in the Northern Caucasus based on climate projections

A strong climatic warming is currently observed in the Caucasus mountains, which has profound impact on runoff generation in the glaciated Glavny (Main) Range and on water availability in the whole region. To assess future changes in the hydrological cycle, the output of a general circulation model was downscaled statistically. For the 21st century, a further warming by 4–7 °C and a slight precipitation increase is predicted. Measured and simulated meteorological variables were used as input into a runoff model to transfer climate signals into a hydrological response under both present and future climate forcings. Runoff scenarios for the mid and the end of the 21st century were generated for different steps of deglaciation. The results show a satisfactory model performance for periods with observed runoff. Future water availability strongly depends on the velocity of glacier retreat. In a first phase, a surplus of water will increase flood risk in hot years and after continuing glacier reduction, annual runoff will again approximate current values. However, the seasonal distribution of streamflow will change towards runoff increase in spring and lower flows in summer.

Assessing the vulnerability of blanket peat to climate change using an ensemble of statistical bioclimatic envelope models

We assessed the vulnerability of blanket peat to climate change in Great Britain using an ensemble of 8 bioclimatic envelope models. We used 4 published models that ranged from simple threshold models, based on total annual precipitation, to Generalised Linear Models (GLMs, based on mean annual temperature). In addition, 4 new models were developed which included measures of water deficit as threshold, classification tree, GLM and generalised additive models (GAM). Models that included measures of both hydrological conditions and maximum temperature provided a better fit to the mapped peat area than models based on hydrological variables alone. Under UKCIP02 projections for high (A1F1) and low (B1) greenhouse gas emission scenarios, 7 out of the 8 models showed a decline in the bioclimatic space associated with blanket peat. Eastern regions (Northumbria, North York Moors, Orkney) were shown to be more vulnerable than higher-altitude, western areas (Highlands, Western Isles and Argyle, Bute and The Trossachs). These results suggest a long-term decline in the distribution of actively growing blanket peat, especially under the high emissions scenario, although it is emphasised that existing peatlands may well persist for decades under a changing climate. Observational data from long-term monitoring and manipulation experiments in combination with process-based models are required to explore the nature and magnitude of climate change impacts on these vulnerable areas more fully.

A simple, coherent framework for partitioning uncertainty in climate predictions

A simple and coherent framework for partitioning uncertainty in multi-model climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a measure of total variation additively into scenario uncertainty, model uncertainty and internal variability. This approach requires fewer assumptions than existing methods and can be easily used to quantify uncertainty related to model-scenario interaction - the contribution to model uncertainty arising from the variation across scenarios of model deviations from the ensemble mean. Uncertainty in global mean surface air temperature is quantified as a function of lead time for a subset of the Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with those published by other authors: scenario uncertainty dominates beyond 2050 and internal variability remains approximately constant over the 21st century. Both elements of model uncertainty, due to scenario-independent and scenario-dependent deviations from the ensemble mean, are found to increase with time. Estimates of model deviations that arise as by-products of the framework reveal significant differences between models that could lead to a deeper understanding of the sources of uncertainty in multi-model ensembles. For example, three models are shown diverging pattern over the 21st century, while another model exhibits an unusually large variation among its scenario-dependent deviations.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.

Air flow influences on local climate: observed and simulated mean relationships for the United Kingdom

Synoptic-scale air flow variability over the United Kingdom is measured on a daily time scale by following previous work to define 3 indices: geostrophic flow strength, vorticity and direction. Comparing the observed distribution of air flow index values with those determined from a simulation with the Hadley Centre’s global climate model (HadCM2) identifies some minor systematic biases in the model’s synoptic circulation but demonstrates that the major features are well simulated. The relationship between temperature and precipitation from parts of the United Kingdom and these air flow indices (either singly or in pairs) is found to be very similar in both the observations and model output; indeed the simulated and observed precipitation relationships are found to be almost interchangeable in a quantitative sense. These encouraging results imply that some reliability can be assumed for single grid-box and regional output from this climate model; this applies only to those grid boxes evaluated here (which do not have high or complex orography), only to the portion of variability that is controlled by synoptic air flow variations, and only to those surface variables considered here (temperature and precipitation).

Comparison of results from several AOGCMs for global and regional sea-level change 1900-2100

Sea-level rise is an important aspect of climate change because of its impact on society and ecosystems. Here we present an intercomparison of results from ten coupled atmosphere-ocean general circulation models (AOGCMs) for sea-level changes simulated for the twentieth century and projected to occur during the twenty first century in experiments following scenario IS92a for greenhouse gases and sulphate aerosols. The model results suggest that the rate of sea-level rise due to thermal expansion of sea water has increased during the twentieth century, but the small set of tide gauges with long records might not be adequate to detect this acceleration. The rate of sea-level rise due to thermal expansion continues to increase throughout the twenty first century, and the projected total is consequently larger than in the twentieth century; for 1990-2090 it amounts to 0.20-0.37 in. This wide range results from systematic uncertainty in modelling of climate change and of heat uptake by the ocean. The AOGCMs agree that sea-level rise is expected to be geographically non-uniform, with some regions experiencing as much as twice the global average, and others practically zero, but they do not agree about the geographical pattern. The lack of agreement indicates that we cannot currently have confidence in projections of local sea- level changes, and reveals a need for detailed analysis and intercomparison in order to understand and reduce the disagreements.