362 resultados para flood risk,intermediate-complexity model,climate change adaptation
Resumo:
We use a soil carbon (C) model (RothC), driven by a range of climate models for a range of climate scenarios to examine the impacts of future climate on global soil organic carbon (SOC) stocks. The results suggest an overall global increase in SOC stocks by 2100 under all scenarios, but with a different extent of increase among the climate model and emissions scenarios. The impacts of projected land use changes are also simulated, but have relatively minor impacts at the global scale. Whether soils gain or lose SOC depends upon the balance between C inputs and decomposition. Changes in net primary production (NPP) change C inputs to the soil, whilst decomposition usually increases under warmer temperatures, but can also be slowed by decreased soil moisture. Underlying the global trend of increasing SOC under future climate is a complex pattern of regional SOC change. SOC losses are projected to occur in northern latitudes where higher SOC decomposition rates due to higher temperatures are not balanced by increased NPP, whereas in tropical regions, NPP increases override losses due to higher SOC decomposition. The spatial heterogeneity in the response of SOC to changing climate shows how delicately balanced the competing gain and loss processes are, with subtle changes in temperature, moisture, soil type and land use, interacting to determine whether SOC increases or decreases in the future. Our results suggest that we should stop looking for a single answer regarding whether SOC stocks will increase or decrease under future climate, since there is no single answer. Instead, we should focus on improving our prediction of the factors that determine the size and direction of change, and the land management practices that can be implemented to protect and enhance SOC stocks.
Resumo:
A favoured method of assimilating information from state-of-the-art climate models into integrated assessment models of climate impacts is to use the transient climate response (TCR) of the climate models as an input, sometimes accompanied by a pattern matching approach to provide spatial information. More recent approaches to the problem use TCR with another independent piece of climate model output: the land-sea surface warming ratio (φ). In this paper we show why the use of φ in addition to TCR has such utility. Multiple linear regressions of surface temperature change onto TCR and φ in 22 climate models from the CMIP3 multi-model database show that the inclusion of φ explains a much greater fraction of the inter-model variance than using TCR alone. The improvement is particularly pronounced in North America and Eurasia in the boreal summer season, and in the Amazon all year round. The use of φ as the second metric is beneficial for three reasons: firstly it is uncorrelated with TCR in state-of-the-art climate models and can therefore be considered as an independent metric; secondly, because of its projected time-invariance, the magnitude of φ is better constrained than TCR in the immediate future; thirdly, the use of two variables is much simpler than approaches such as pattern scaling from climate models. Finally we show how using the latest estimates of φ from climate models with a mean value of 1.6—as opposed to previously reported values of 1.4—can significantly increase the mean time-integrated discounted damage projections in a state-of-the-art integrated assessment model by about 15 %. When compared to damages calculated without the inclusion of the land-sea warming ratio, this figure rises to 65 %, equivalent to almost 200 trillion dollars over 200 years.
Resumo:
Climate models consistently predict a strengthened Brewer–Dobson circulation in response to greenhouse gas (GHG)-induced climate change. Although the predicted circulation changes are clearly the result of changes in stratospheric wave drag, the mechanism behind the wave-drag changes remains unclear. Here, simulations from a chemistry–climate model are analyzed to show that the changes in resolved wave drag are largely explainable in terms of a simple and robust dynamical mechanism, namely changes in the location of critical layers within the subtropical lower stratosphere, which are known from observations to control the spatial distribution of Rossby wave breaking. In particular, the strengthening of the upper flanks of the subtropical jets that is robustly expected from GHG-induced tropospheric warming pushes the critical layers (and the associated regions of wave drag) upward, allowing more wave activity to penetrate into the subtropical lower stratosphere. Because the subtropics represent the critical region for wave driving of the Brewer–Dobson circulation, the circulation is thereby strengthened. Transient planetary-scale waves and synoptic-scale waves generated by baroclinic instability are both found to play a crucial role in this process. Changes in stationary planetary wave drag are not so important because they largely occur away from subtropical latitudes.
Resumo:
A version of the Canadian Middle Atmosphere Model that is coupled to an ocean is used to investigate the separate effects of climate change and ozone depletion on the dynamics of the Southern Hemisphere (SH) stratosphere. This is achieved by performing three sets of simulations extending from 1960 to 2099: 1) greenhouse gases (GHGs) fixed at 1960 levels and ozone depleting substances (ODSs) varying in time, 2) ODSs fixed at 1960 levels and GHGs varying in time, and 3) both GHGs and ODSs varying in time. The response of various dynamical quantities to theGHGand ODS forcings is shown to be additive; that is, trends computed from the sum of the first two simulations are equal to trends from the third. Additivity is shown to hold for the zonal mean zonal wind and temperature, the mass flux into and out of the stratosphere, and the latitudinally averaged wave drag in SH spring and summer, as well as for final warming dates. Ozone depletion and recovery causes seasonal changes in lower-stratosphere mass flux, with reduced polar downwelling in the past followed by increased downwelling in the future in SH spring, and the reverse in SH summer. These seasonal changes are attributed to changes in wave drag caused by ozone-induced changes in the zonal mean zonal winds. Climate change, on the other hand, causes a steady decrease in wave drag during SH spring, which delays the breakdown of the vortex, resulting in increased wave drag in summer
Resumo:
The time-dependent climate response to changing concentrations of greenhouse gases and sulfate aerosols is studied using a coupled general circulation model of the atmosphere and the ocean (ECHAM4/OPYC3). The concentrations of the well-mixed greenhouse gases like CO2, CH4, N2O, and CFCs are prescribed for the past (1860–1990) and projected into the future according to International Panel on Climate Change (IPCC) scenario IS92a. In addition, the space–time distribution of tropospheric ozone is prescribed, and the tropospheric sulfur cycle is calculated within the coupled model using sulfur emissions of the past and projected into the future (IS92a). The radiative impact of the aerosols is considered via both the direct and the indirect (i.e., through cloud albedo) effect. It is shown that the simulated trend in sulfate deposition since the end of the last century is broadly consistent with ice core measurements, and the calculated radiative forcings from preindustrial to present time are within the uncertainty range estimated by IPCC. Three climate perturbation experiments are performed, applying different forcing mechanisms, and the results are compared with those obtained from a 300-yr unforced control experiment. As in previous experiments, the climate response is similar, but weaker, if aerosol effects are included in addition to greenhouse gases. One notable difference to previous experiments is that the strength of the Indian summer monsoon is not fundamentally affected by the inclusion of aerosol effects. Although the monsoon is damped compared to a greenhouse gas only experiment, it is still more vigorous than in the control experiment. This different behavior, compared to previous studies, is the result of the different land–sea distribution of aerosol forcing. Somewhat unexpected, the intensity of the global hydrological cycle becomes weaker in a warmer climate if both direct and indirect aerosol effects are included in addition to the greenhouse gases. This can be related to anomalous net radiative cooling of the earth’s surface through aerosols, which is balanced by reduced turbulent transfer of both sensible and latent heat from the surface to the atmosphere.
Resumo:
This paper presents an assessment of the impacts of climate change on a series of indicators of hydrological regimes across the global domain, using a global hydrological model run with climate scenarios constructed using pattern-scaling from 21 CMIP3 (Coupled Model Intercomparison Project Phase 3) climate models. Changes are compared with natural variability, with a significant change being defined as greater than the standard deviation of the hydrological indicator in the absence of climate change. Under an SRES (Special Report on Emissions Scenarios) A1b emissions scenario, substantial proportions of the land surface (excluding Greenland and Antarctica) would experience significant changes in hydrological behaviour by 2050; under one climate model scenario (Hadley Centre HadCM3), average annual runoff increases significantly over 47% of the land surface and decreases over 36%; only 17% therefore sees no significant change. There is considerable variability between regions, depending largely on projected changes in precipitation. Uncertainty in projected river flow regimes is dominated by variation in the spatial patterns of climate change between climate models (hydrological model uncertainty is not included). There is, however, a strong degree of consistency in the overall magnitude and direction of change. More than two-thirds of climate models project a significant increase in average annual runoff across almost a quarter of the land surface, and a significant decrease over 14%, with considerably higher degrees of consistency in some regions. Most climate models project increases in runoff in Canada and high-latitude eastern Europe and Siberia, and decreases in runoff in central Europe, around the Mediterranean, the Mashriq, central America and Brasil. There is some evidence that projecte change in runoff at the regional scale is not linear with change in global average temperature change. The effects of uncertainty in the rate of future emissions is relatively small
Resumo:
The currently available model-based global data sets of atmospheric circulation are a by-product of the daily requirement of producing initial conditions for numerical weather prediction (NWP) models. These data sets have been quite useful for studying fundamental dynamical and physical processes, and for describing the nature of the general circulation of the atmosphere. However, due to limitations in the early data assimilation systems and inconsistencies caused by numerous model changes, the available model-based global data sets may not be suitable for studying global climate change. A comprehensive analysis of global observations based on a four-dimensional data assimilation system with a realistic physical model should be undertaken to integrate space and in situ observations to produce internally consistent, homogeneous, multivariate data sets for the earth's climate system. The concept is equally applicable for producing data sets for the atmosphere, the oceans, and the biosphere, and such data sets will be quite useful for studying global climate change.
Resumo:
In recent years, the potential role of planned, internal resettlement as a climate change adaptation measure has been highlighted by national governments and the international policy community. However, in many developing countries, resettlement is a deeply political process that often results in an unequal distribution of costs and benefits amongst relocated persons. This paper examines these tensions in Mozambique, drawing on a case study of flood-affected communities in the Lower Zambezi River valley. It takes a political ecology approach – focusing on discourses of human-environment interaction, as well as the power relationships that are supported by such discourses – to show how a dominant narrative of climate change-induced hazards for small-scale farmers is contributing to their involuntary resettlement to higher-altitude, less fertile areas of land. These forced relocations are buttressed by a series of wider economic and political interests in the Lower Zambezi River region, such dam construction for hydroelectric power generation and the extension of control over rural populations, from which resettled people derive little direct benefit. Rather than engaging with these challenging issues, most international donors present in the country accept the ‘inevitability’ of extreme weather impacts and view resettlement as an unfortunate and, in some cases, necessary step to increase people’s ‘resilience’, thus rationalising the top-down imposition of unpopular social policies. The findings add weight to the argument that a depoliticised interpretation of climate change can deflect attention away from underlying drivers of vulnerability and poverty, as well as obscure the interests of governments that are intent on reordering poor and vulnerable populations.
Resumo:
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.
Resumo:
Increased risks of extinction to populations of animals and plants under changing climate have now been demonstrated for many taxa. This study assesses the extinction risks to species within an important genus of pollinating bees (Colletes: Apidae) by estimating the expected changes in the area and isolation of suitable habitat under predicted climatic condition for 2050. Suitable habitat was defined on the basis of the presence of known forage plants as well as climatic suitability. To investigate whether ecological specialisation was linked to extinction risk we compared three species which were generalist pollen foragers on several plant families with three species which specialised on pollen from a single plant species. Both specialist and generalist species showed an increased risk of extinction with shifting climate, and this was particularly high for the most specialised species (Colletes anchusae and C. wolfi). The forage generalist C. impunctatus, which is associated with Boreo-Alpine environments, is potentially threatened through significant reduction in available climatic niche space. Including the distribution of the principal or sole pollen forage plant, when modelling the distribution of monolectic or narrowly oligolectic species, did not improve the predictive accuracy of our models as the plant species were considerably more widespread than the specialised bees associated with them.
Resumo:
Accelerated climate change affects components of complex biological interactions differentially, often causing changes that are difficult to predict. Crop yield and quality are affected by climate change directly, and indirectly, through diseases that themselves will change but remain important. These effects are difficult to dissect and model as their mechanistic bases are generally poorly understood. Nevertheless, a combination of integrated modelling from different disciplines and multi-factorial experimentation will advance our understanding and prioritisation of the challenges. Food security brings in additional socio-economic, geographical and political factors. Enhancing resilience to the effects of climate change is important for all these systems and functional diversity is one of the most effective targets for improved sustainability.
Resumo:
Many reasons are being advanced for the current ‘food crisis’ including financial speculation,increased demand for grains, export bans on selected foodstuffs, inadequate grain stocks, higher oil prices, poor harvests and the use of crop lands for the production of biofuels. This paper reviews the present knowledge of recorded impacts of climate change and variability on crop production, in order to estimate its contribution to the current situation. Many studies demonstrate increased regional temperatures over the last 40 years (often through greater increases in minimum rather than maximum temperatures), but effects on crop yields are mixed. Distinguishing climate effects from changes in yield resulting from improved crop management and genotypes is difficult, but phenological changes affecting sowing, maturity and disease incidence are emerging. Anthropogenic factors appear to be a significant contributory factor to the observed decline in rainfall in southwestern and southeastern Australia, which reduced tradable wheat grain during 2007. Indirect effects of climate change through actions to mitigate or adapt to anticipated changes in climate are also evident. The amount of land diverted from crop production to biofuel production is small but has had a disproportionate effect on tradable grains from the USA. Adaptation of crop production practices and other components of the food system contributing to food security in response to variable and changing climates have occurred, but those households without adequate livelihoods are most in danger of becoming food insecure. Overall, we conclude that changing climate is a small contributor to the current food crisis but cannot be ignored.
Resumo:
Societal concern is growing about the consequences of climate change for food systems and, in a number of regions, for food security. There is also concern that meeting the rising demand for food is leading to environmental degradation thereby exacerbating factors in part responsible for climate change, and further undermining the food systems upon which food security is based. A major emphasis of climate change/food security research over recent years has addressed the agronomic aspects of climate change, and particularly crop yield. This has provided an excellent foundation for assessments of how climate change may affect crop productivity, but the connectivity between these results and the broader issues of food security at large are relatively poorly explored; too often discussions of food security policy appear to be based on a relatively narrow agronomic perspective. To overcome the limitation of current agronomic research outputs there are several scientific challenges where further agronomic effort is necessary, and where agronomic research results can effectively contribute to the broader issues underlying food security. First is the need to better understand how climate change will affect cropping systems including both direct effects on the crops themselves and indirect effects as a result of changed pest and weed dynamics and altered soil and water conditions. Second is the need to assess technical and policy options for either reducing the deleterious impacts or enhancing the benefits of climate change on cropping systems while minimising further environmental degradation. Third is the need to understand how best to address the information needs of policy makers and report and communicate agronomic research results in a manner that will assist the development of food systems adapted to climate change. There are, however, two important considerations regarding these agronomic research contributions to the food security/climate change debate. The first concerns scale. Agronomic research has traditionally been conducted at plot scale over a growing season or perhaps a few years, but many of the issues related to food security operate at larger spatial and temporal scales. Over the last decade, agronomists have begun to establish trials at landscape scale, but there are a number of methodological challenges to be overcome at such scales. The second concerns the position of crop production (which is a primary focus of agronomic research) in the broader context of food security. Production is clearly important, but food distribution and exchange also determine food availability while access to food and food utilisation are other important components of food security. Therefore, while agronomic research alone cannot address all food security/climate change issues (and hence the balance of investment in research and development for crop production vis à vis other aspects of food security needs to be assessed), it will nevertheless continue to have an important role to play: it both improves understanding of the impacts of climate change on crop production and helps to develop adaptation options; and also – and crucially – it improves understanding of the consequences of different adaptation options on further climate forcing. This role can further be strengthened if agronomists work alongside other scientists to develop adaptation options that are not only effective in terms of crop production, but are also environmentally and economically robust, at landscape and regional scales. Furthermore, such integrated approaches to adaptation research are much more likely to address the information need of policy makers. The potential for stronger linkages between the results of agronomic research in the context of climate change and the policy environment will thus be enhanced.
Resumo:
Atmospheric turbulence causes most weather-related aircraft incidents1. Commercial aircraft encounter moderate-or-greater turbulence tens of thousands of times each year worldwide, injuring probably hundreds of passengers (occasionally fatally), costing airlines tens of millions of dollars and causing structural damage to planes1, 2, 3. Clear-air turbulence is especially difficult to avoid, because it cannot be seen by pilots or detected by satellites or on-board radar4, 5. Clear-air turbulence is linked to atmospheric jet streams6, 7, which are projected to be strengthened by anthropogenic climate change8. However, the response of clear-air turbulence to projected climate change has not previously been studied. Here we show using climate model simulations that clear-air turbulence changes significantly within the transatlantic flight corridor when the concentration of carbon dioxide in the atmosphere is doubled. At cruise altitudes within 50–75° N and 10–60° W in winter, most clear-air turbulence measures show a 10–40% increase in the median strength of turbulence and a 40–170% increase in the frequency of occurrence of moderate-or-greater turbulence. Our results suggest that climate change will lead to bumpier transatlantic flights by the middle of this century. Journey times may lengthen and fuel consumption and emissions may increase. Aviation is partly responsible for changing the climate9, but our findings show for the first time how climate change could affect aviation.
Resumo:
Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO2 doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change.