161 resultados para Greenhouse gas


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Previous assessments of the impacts of climate change on heat-related mortality use the "delta method" to create temperature projection time series that are applied to temperature-mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heatrelated mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature-mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heatrelated mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2°C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.

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Relationships between clear-sky longwave radiation and aspects of the atmospheric hydrological cycle are quantified in models, reanalyses, and observations over the period 1980-2000. The robust sensitivity of clear-sky surface net longwave radiation (SNLc) to column-integrated water vapor (CWV) of 1-1.5 Wm(-2) mm(-1) combined with the positive relationship between CWV and surface temperature (T-s) explains substantial increases in clear-sky longwave radiative cooling of the atmosphere (Q(LWc)) to the surface over the period. Clear-sky outgoing longwave radiation (OLRc) is highly sensitive to changes in aerosol and greenhouse gas concentrations in addition to temperature and humidity. Over tropical ocean regions of mean descent, Q(LWc) increases with T-s at similar to 3.5-5.5 W m(-2) K-1 for reanalyses, estimates derived from satellite data, and models without volcanic forcing included. Increased Q(LWc) with warming across the tropical oceans helps to explain model ensemble mean increases in precipitation of 0.1-0.15 mm day(-1) K-1, which are primarily determined by ascent regions where precipitation increases at the rate expected from the Clausius-Clapeyron equation. The implications for future projections in the atmospheric hydrological cycle are discussed

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Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only

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The purpose of Research Theme 4 (RT4) was to advance understanding of the basic science issues at the heart of the ENSEMBLES project, focusing on the key processes that govern climate variability and change, and that determine the predictability of climate. Particular attention was given to understanding linear and non-linear feedbacks that may lead to climate surprises,and to understanding the factors that govern the probability of extreme events. Improved understanding of these issues will contribute significantly to the quantification and reduction of uncertainty in seasonal to decadal predictions and projections of climate change. RT4 exploited the ENSEMBLES integrations (stream 1) performed in RT2A as well as undertaking its own experimentation to explore key processes within the climate system. It was working at the cutting edge of problems related to climate feedbacks, the interaction between climate variability and climate change � especially how climate change pertains to extreme events, and the predictability of the climate system on a range of time-scales. The statisticalmethodologies developed for extreme event analysis are new and state-of-the-art. The RT4-coordinated experiments, which have been conducted with six different atmospheric GCMs forced by common timeinvariant sea surface temperature (SST) and sea-ice fields (removing some sources of inter-model variability), are designed to help to understand model uncertainty (rather than scenario or initial condition uncertainty) in predictions of the response to greenhouse-gas-induced warming. RT4 links strongly with RT5 on the evaluation of the ENSEMBLES prediction system and feeds back its results to RT1 to guide improvements in the Earth system models and, through its research on predictability, to steer the development of methods for initialising the ensembles

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Under global warming, the predicted intensification of the global freshwater cycle will modify the net freshwater flux at the ocean surface. Since the freshwater flux maintains ocean salinity structures, changes to the density-driven ocean circulation are likely. A modified ocean circulation could further alter the climate, potentially allowing rapid changes, as seen in the past. The relevant feedback mechanisms and timescales are poorly understood in detail, however, especially at low latitudes where the effects of salinity are relatively subtle. In an attempt to resolve some of these outstanding issues, we present an investigation of the climate response of the low-latitude Pacific region to changes in freshwater forcing. Initiated from the present-day thermohaline structure, a control run of a coupled ocean-atmosphere general circulation model is compared with a perturbation run in which the net freshwater flux is prescribed to be zero over the ocean. Such an extreme experiment helps to elucidate the general adjustment mechanisms and their timescales. The atmospheric greenhouse gas concentrations are held constant, and we restrict our attention to the adjustment of the upper 1,000 m of the Pacific Ocean between 40°N and 40°S, over 100 years. In the perturbation run, changes to the surface buoyancy, near-surface vertical mixing and mixed-layer depth are established within 1 year. Subsequently, relative to the control run, the surface of the low-latitude Pacific Ocean in the perturbation run warms by an average of 0.6°C, and the interior cools by up to 1.1°C, after a few decades. This vertical re-arrangement of the ocean heat content is shown to be achieved by a gradual shutdown of the heat flux due to isopycnal (i.e. along surfaces of constant density) mixing, the vertical component of which is downwards at low latitudes. This heat transfer depends crucially upon the existence of density-compensating temperature and salinity gradients on isopycnal surfaces. The timescale of the thermal changes in the perturbation run is therefore set by the timescale for the decay of isopycnal salinity gradients in response to the eliminated freshwater forcing, which we demonstrate to be around 10-20 years. Such isopycnal heat flux changes may play a role in the response of the low-latitude climate to a future accelerated freshwater cycle. Specifically, the mechanism appears to represent a weak negative sea surface temperature feedback, which we speculate might partially shield from view the anthropogenically-forced global warming signal at low latitudes. Furthermore, since the surface freshwater flux is shown to play a role in determining the ocean's thermal structure, it follows that evaporation and/or precipitation biases in general circulation models are likely to cause sea surface temperature biases.

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This paper discusses the risks of a shutdown of the thermohaline circulation (THC) for the climate system, for ecosystems in and around the North Atlantic as well as for fisheries and agriculture by way of an Integrated Assessment. The climate model simulations are based on greenhouse gas scenarios for the 21st century and beyond. A shutdown of the THC, complete by 2150, is triggered if increased freshwater input from inland ice melt or enhanced runoff is assumed. The shutdown retards the greenhouse gas-induced atmospheric warming trend in the Northern Hemisphere, but does not lead to a persistent net cooling. Due to the simulated THC shutdown the sea level at the North Atlantic shores rises by up to 80 cm by 2150, in addition to the global sea level rise. This could potentially be a serious impact that requires expensive coastal protection measures. A reduction of marine net primary productivity is associated with the impacts of warming rather than a THC shutdown. Regional shifts in the currents in the Nordic Seas could strongly deteriorate survival chances for cod larvae and juveniles. This could lead to cod fisheries becoming unprofitable by the end of the 21st century. While regional socioeconomic impacts might be large, damages would be probably small in relation to the respective gross national products. Terrestrial ecosystem productivity is affected much more by the fertilization from the increasing CO2 concentration than by a THC shutdown. In addition, the level of warming in the 22nd to 24th century favours crop production in northern Europe a lot, no matter whether the THC shuts down or not. CO2 emissions corridors aimed at limiting the risk of a THC breakdown to 10% or less are narrow, requiring departure from business-as-usual in the next few decades. The uncertainty about THC risks is still high. This is seen in model analyses as well as in the experts’ views that were elicited. The overview of results presented here is the outcome of the Integrated Assessment project INTEGRATION.

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Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in delta C-13 for the six chronosequences where measured 813 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO, emissions from land use change in national greenhouse gas inventories. (0 2007 Elsevier B.V. All rights reserved.

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The nature and magnitude of climatic variability during the period of middle Pliocene warmth (ca 3.29–2.97 Ma) is poorly understood. We present a suite of palaeoclimate modelling experiments incorporating an advanced atmospheric general circulation model (GCM), coupled to a Q-flux ocean model for 3.29, 3.12 and 2.97 Ma BP. Astronomical solutions for the periods in question were derived from the Berger and Loutre BL2 astronomical solution. Boundary conditions, excluding sea surface temperatures (SSTs) which were predicted by the slab-ocean model, were provided from the USGS PRISM2 2°×2° digital data set. The model results indicate that little annual variation (0.5°C) in SSTs, relative to a ‘control’ experiment, occurred during the middle Pliocene in response to the altered orbital configurations. Annual surface air temperatures also displayed little variation. Seasonally, surface air temperatures displayed a trend of cooler temperatures during December, January and February, and warmer temperatures during June, July and August. This pattern is consistent with altered seasonality resulting from the prescribed orbital configurations. Precipitation changes follow the seasonal trend observed for surface air temperature. Compared to present-day, surface wind strength and wind stress over the North Atlantic, North Pacific and Southern Ocean remained greater in each of the Pliocene experiments. This suggests that wind-driven gyral circulation may have been consistently greater during the middle Pliocene. The trend of climatic variability predicted by the GCM for the middle Pliocene accords with geological data. However, it is unclear if the model correctly simulates the magnitude of the variation. This uncertainty is derived from, (a) the relative insensitivity of the GCM to perturbation in the imposed boundary conditions, (b) a lack of detailed time series data concerning changes to terrestrial ice cover and greenhouse gas concentrations for the middle Pliocene and (c) difficulties in representing the effects of ‘climatic history’ in snap-shot GCM experiments.

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Nitrous oxide (N2O) emission from soils is a major contributor to the atmospheric loading of this potent greenhouse gas. It is thought that autotrophic ammonia oxidizing bacteria (AOB) are a significant source of soil-derived N2O and a denitrification pathway (i.e. reduction of NO2- to NO and N2O), so-called nitrifier denitrification, has been demonstrated as a N2O production mechanism in Nitrosomonas europaea. It is thought that Nitrosospira spp. are the dominant AOB in soil, but little information is available on their ability to produce N2O or on the existence of a nitrifier denitrification pathway in this lineage. This study aims to characterize N2O production and nitrifier denitrification in seven strains of AOB representative of clusters 0, 2 and 3 in the cultured Nitrosospira lineage. Nitrosomonas europaea ATCC 19718 and ATCC 25978 were analysed for comparison. The aerobically incubated test strains produced significant (P < 0.001) amounts of N2O and total N2O production rates ranged from 2.0 amol cell(-1) h(-1), in Nitrosospira tenuis strain NV12, to 58.0 amol cell(-1) h(-1), in N. europaea ATCC 19718. Nitrosomonas europaea ATCC 19718 was atypical in that it produced four times more N2O than the next highest producing strain. All AOB tested were able to carry out nitrifier denitrification under aerobic conditions, as determined by production of N-15-N2O from applied N-15-NO2-. Up to 13.5% of the N2O produced was derived from the exogenously applied N-15-NO2-. The results suggest that nitrifier denitrification could be a universal trait in the betaproteobacterial AOB and its potential ecological significance is discussed.

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The Greenland ice sheet will decline in volume in a warmer climate. If a sufficiently warm climate is maintained for a few thousand years, the ice sheet will be completely melted. This raises the question of whether the decline would be reversible: would the ice sheet regrow if the climate cooled down? To address this question, we conduct a number of experiments using a climate model and a high-resolution ice-sheet model. The experiments are initialised with ice sheet states obtained from various points during its decline as simulated in a high-CO2 scenario, and they are then forced with a climate simulated for pre-industrial greenhouse gas concentrations, to determine the possible trajectories of subsequent ice sheet evolution. These trajectories are not the reverse of the trajectory during decline. They converge on three different steady states. The original ice-sheet volume can be regained only if the volume has not fallen below a threshold of irreversibility, which lies between 80 and 90% of the original value. Depending on the degree of warming and the sensitivity of the climate and the ice-sheet, this point of no return could be reached within a few hundred years, sooner than CO2 and global climate could revert to a pre-industrial state, and in that case global sea level rise of at least 1.3 m would be irreversible. An even larger irreversible change to sea level rise of 5 m may occur if ice sheet volume drops below half of its current size. The set of steady states depends on the CO2 concentration. Since we expect the results to be quantitatively affected by resolution and other aspects of model formulation, we would encourage similar investigations with other models.

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This paper investigates the impact of aerosol forcing uncertainty on the robustness of estimates of the twentieth-century warming attributable to anthropogenic greenhouse gas emissions. Attribution analyses on three coupled climate models with very different sensitivities and aerosol forcing are carried out. The Third Hadley Centre Coupled Ocean - Atmosphere GCM (HadCM3), Parallel Climate Model (PCM), and GFDL R30 models all provide good simulations of twentieth-century global mean temperature changes when they include both anthropogenic and natural forcings. Such good agreement could result from a fortuitous cancellation of errors, for example, by balancing too much ( or too little) greenhouse warming by too much ( or too little) aerosol cooling. Despite a very large uncertainty for estimates of the possible range of sulfate aerosol forcing obtained from measurement campaigns, results show that the spatial and temporal nature of observed twentieth-century temperature change constrains the component of past warming attributable to anthropogenic greenhouse gases to be significantly greater ( at the 5% level) than the observed warming over the twentieth century. The cooling effects of aerosols are detected in all three models. Both spatial and temporal aspects of observed temperature change are responsible for constraining the relative roles of greenhouse warming and sulfate cooling over the twentieth century. This is because there are distinctive temporal structures in differential warming rates between the hemispheres, between land and ocean, and between mid- and low latitudes. As a result, consistent estimates of warming attributable to greenhouse gas emissions are obtained from all three models, and predictions are relatively robust to the use of more or less sensitive models. The transient climate response following a 1% yr(-1) increase in CO2 is estimated to lie between 2.2 and 4 K century(-1) (5-95 percentiles).

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The modelled El Nino-mean state-seasonal cycle interactions in 23 coupled ocean-atmosphere GCMs, including the recent IPCC AR4 models, are assessed and compared to observations and theory. The models show a clear improvement over previous generations in simulating the tropical Pacific climatology. Systematic biases still include too strong mean and seasonal cycle of trade winds. El Nino amplitude is shown to be an inverse function of the mean trade winds in agreement with the observed shift of 1976 and with theoretical studies. El Nino amplitude is further shown to be an inverse function of the relative strength of the seasonal cycle. When most of the energy is within the seasonal cycle, little is left for inter-annual signals and vice versa. An interannual coupling strength (ICS) is defined and its relation with the modelled El Nino frequency is compared to that predicted by theoretical models. An assessment of the modelled El Nino in term of SST mode (S-mode) or thermocline mode (T-mode) shows that most models are locked into a S-mode and that only a few models exhibit a hybrid mode, like in observations. It is concluded that several basic El Nino-mean state-seasonal cycle relationships proposed by either theory or analysis of observations seem to be reproduced by CGCMs. This is especially true for the amplitude of El Nino and is less clear for its frequency. Most of these relationships, first established for the pre-industrial control simulations, hold for the double and quadruple CO2 stabilized scenarios. The models that exhibit the largest El Nino amplitude change in these greenhouse gas (GHG) increase scenarios are those that exhibit a mode change towards a T-mode (either from S-mode to hybrid or hybrid to T-mode). This follows the observed 1976 climate shift in the tropical Pacific, and supports the-still debated-finding of studies that associated this shift to increased GHGs. In many respects, these models are also among those that best simulate the tropical Pacific climatology (ECHAM5/MPI-OM, GFDL-CM2.0, GFDL-CM2.1, MRI-CGM2.3.2, UKMO-HadCM3). Results from this large subset of models suggest the likelihood of increased El Nino amplitude in a warmer climate, though there is considerable spread of El Nino behaviour among the models and the changes in the subsurface thermocline properties that may be important for El Nino change could not be assessed. There are no clear indications of an El Nino frequency change with increased GHG.

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Future stratospheric ozone concentrations will be determined both by changes in the concentration of ozone depleting substances (ODSs) and by changes in stratospheric and tropospheric climate, including those caused by changes in anthropogenic greenhouse gases (GHGs). Since future economic development pathways and resultant emissions of GHGs are uncertain, anthropogenic climate change could be a significant source of uncertainty for future projections of stratospheric ozone. In this pilot study, using an "ensemble of opportunity" of chemistry-climate model (CCM) simulations, the contribution of scenario uncertainty from different plausible emissions pathways for ODSs and GHGs to future ozone projections is quantified relative to the contribution from model uncertainty and internal variability of the chemistry-climate system. For both the global, annual mean ozone concentration and for ozone in specific geographical regions, differences between CCMs are the dominant source of uncertainty for the first two-thirds of the 21st century, up-to and after the time when ozone concentrations return to 1980 values. In the last third of the 21st century, dependent upon the set of greenhouse gas scenarios used, scenario uncertainty can be the dominant contributor. This result suggests that investment in chemistry-climate modelling is likely to continue to refine projections of stratospheric ozone and estimates of the return of stratospheric ozone concentrations to pre-1980 levels.

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Climate science is coming under increasing pressure to deliver projections of future climate change at spatial scales as small as a few kilometres for use in impacts studies. But is our understanding and modelling of the climate system advanced enough to offer such predictions? Here we focus on the Atlantic–European sector, and on the effects of greenhouse gas forcing on the atmospheric and, to a lesser extent, oceanic circulations. We review the dynamical processes which shape European climate and then consider how each of these leads to uncertainty in the future climate. European climate is unique in many regards, and as such it poses a unique challenge for climate prediction. Future European climate must be considered particularly uncertain because (i) the spread between the predictions of current climate models is still considerable and (ii) Europe is particularly strongly affected by several processes which are known to be poorly represented in current models.

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The paper outlines EU policy on bioenergy, including biofuels, in the context of its policy initiatives to promote renewable energy to combat greenhouse gas emissions and climate change. The EU's Member States are responsible for implementing EU policy: thus, the UK's Renewables Obligation on electricity suppliers and its Renewable Transport Fuel Obligation and road-fuel tax rebates are examined. It is unlikely that EU policy is in conflict with the WTO Agreement on Agriculture or that on Subsidies and Countervailing Measures, but its provisions on environmental sustainability criteria could be problematic.