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1.
Integrated assessment models (IAMs) have commonly been used to understand the relationship between the economy, the earth’s climate system and climate impacts. We compare the IPCC simulations of CO2 concentration, radiative forcing, and global mean temperature changes associated with five SRES ‘marker’ emissions scenarios with the responses of three IAMs—DICE, FUND and PAGE—to these same emission scenarios. We also compare differences in simulated temperature increase resulting from moving from a high to a low emissions scenario. These IAMs offer a range of climate outcomes, some of which are inconsistent with those of IPCC, due to differing treatments of the carbon cycle and of the temperature response to radiative forcing. In particular, in FUND temperatures up until 2100 are relatively similar for the four emissions scenarios, and temperature reductions upon switching to lower emissions scenarios are small. PAGE incorporates strong carbon cycle feedbacks, leading to higher CO2 concentrations in the twenty-second century than other models. Such IAMs are frequently applied to determine ‘optimal’ climate policy in a cost–benefit approach. Models such as FUND which show smaller temperature responses to reducing emissions than IPCC simulations on comparable timescales will underestimate the benefits of emission reductions and hence the calculated ‘optimal’ level of investment in mitigation.  相似文献   

2.
The RCP greenhouse gas concentrations and their extensions from 1765 to 2300   总被引：16，自引：2，他引：14  
We present the greenhouse gas concentrations for the Representative Concentration Pathways (RCPs) and their extensions beyond 2100, the Extended Concentration Pathways (ECPs). These projections include all major anthropogenic greenhouse gases and are a result of a multi-year effort to produce new scenarios for climate change research. We combine a suite of atmospheric concentration observations and emissions estimates for greenhouse gases (GHGs) through the historical period (1750?C2005) with harmonized emissions projected by four different Integrated Assessment Models for 2005?C2100. As concentrations are somewhat dependent on the future climate itself (due to climate feedbacks in the carbon and other gas cycles), we emulate median response characteristics of models assessed in the IPCC Fourth Assessment Report using the reduced-complexity carbon cycle climate model MAGICC6. Projected ??best-estimate?? global-mean surface temperature increases (using inter alia a climate sensitivity of 3°C) range from 1.5°C by 2100 for the lowest of the four RCPs, called both RCP3-PD and RCP2.6, to 4.5°C for the highest one, RCP8.5, relative to pre-industrial levels. Beyond 2100, we present the ECPs that are simple extensions of the RCPs, based on the assumption of either smoothly stabilizing concentrations or constant emissions: For example, the lower RCP2.6 pathway represents a strong mitigation scenario and is extended by assuming constant emissions after 2100 (including net negative CO2 emissions), leading to CO2 concentrations returning to 360 ppm by 2300. We also present the GHG concentrations for one supplementary extension, which illustrates the stringent emissions implications of attempting to go back to ECP4.5 concentration levels by 2250 after emissions during the 21st century followed the higher RCP6 scenario. Corresponding radiative forcing values are presented for the RCP and ECPs.  相似文献   

3.
Projections of greenhouse gas (GHG) emissions are critical to enable a better understanding and anticipation of future climate change under different socio-economic conditions and mitigation strategies. The climate projections and scenarios assessed by the Intergovernmental Panel on Climate Change, following the Shared Socioeconomic Pathway (SSP)-Representative Concentration Pathway (RCP) framework, have provided a rich understanding of the constraints and opportunities for policy action. However, the current emissions scenarios lack an explicit treatment of urban emissions within the global context. Given the pace and scale of urbanization, with global urban populations expected to increase from about 4.4 billion today to about 7 billion by 2050, there is an urgent need to fill this knowledge gap. Here, we estimate the share of global GHG emissions driven by urban areas from 1990 to 2100 based on the SSP-RCP framework. The urban consumption-based GHG emissions are presented in five regional aggregates and based on a combination of the urban population share, 2015 urban per capita CO2eq carbon footprint, SSP-based national CO2eq emissions, and recent analysis of urban per capita CO2eq trends. We find that urban areas account for the majority of global GHG emissions in 2015 (61.8%). Moreover, the urban share of global GHG emissions progressively increases into the future, exceeding 80% in some scenarios by the end of the century. The combined urban areas in Asia and Developing Pacific, and Developed Countries account for 65.0% to 73.3% of cumulative urban consumption-based emissions between 2020 and 2100 across the scenarios. Given these dominant roles, we describe the implications for potential urban mitigation in each of the scenario narratives in order to meet the goal of climate neutrality within this century.  相似文献   

4.
Climate policies must consider radiative forcing from Kyoto greenhouse gases, as well as other forcing constituents, such as aerosols and tropospheric ozone that result from air pollutants. Non-Kyoto forcing constituents contribute negative, as well as positive forcing, and overall increases in total forcing result in increases in global average temperature. Non-Kyoto forcing modeling is a relatively new component of climate management scenarios. This paper describes and assesses current non-Kyoto radiative forcing modeling within five integrated assessment models. The study finds negative forcing from aerosols masking (offsetting) approximately 25 % of positive forcing in the near-term in reference non-climate policy projections. However, masking is projected to decline rapidly to 5–10 % by 2100 with increasing Kyoto emissions and assumed reductions in air pollution—with the later declining to as much as 50 % and 80 % below today’s levels by 2050 and 2100 respectively. Together they imply declining importance of non-Kyoto forcing over time. There are however significant uncertainties and large differences across models in projected non-Kyoto emissions and forcing. A look into the modeling reveals differences in base conditions, relationships between Kyoto and non-Kyoto emissions, pollution control assumptions, and other fundamental modeling. In addition, under climate policy scenarios, we find air pollution and resulting non-Kyoto forcing reduced to levels below those produced by air pollution policies alone—e.g., China sulfur emissions fall an additional 45–85 % by 2050. None of the models actively manage non-Kyoto forcing for climate implications. Nonetheless, non-Kyoto forcing may be influencing mitigation results, including allowable carbon dioxide emissions, and further evaluation is merited.  相似文献   

5.
Transportation contributes to a significant and rising share of global energy use and GHG emissions. Therefore modeling future travel demand, its fuel use, and resulting CO2 emission is highly relevant for climate change mitigation. In this study we compare the baseline projections for global service demand (passenger-kilometers, ton-kilometers), fuel use, and CO2 emissions of five different global transport models using harmonized input assumptions on income and population. For four models we also evaluate the impact of a carbon tax. All models project a steep increase in service demand over the century. Technology change is important for limiting energy consumption and CO2 emissions, the study also shows that in order to stabilise or even decrease emissions radical changes would be required. While all models project liquid fossil fuels dominating up to 2050, they differ regarding the use of alternative fuels (natural gas, hydrogen, biofuels, and electricity), because of different fuel price projections. The carbon tax of 200 USD/tCO2 in 2050 stabilizes or reverses global emission growth in all models. Besides common findings many differences in the model assumptions and projections indicate room for further understanding long-term trends and uncertainty in future transport systems.  相似文献   

6.
Probabilistic climate change projections using neural networks   总被引：5，自引：0，他引：5  
Anticipated future warming of the climate system increases the need for accurate climate projections. A central problem are the large uncertainties associated with these model projections, and that uncertainty estimates are often based on expert judgment rather than objective quantitative methods. Further, important climate model parameters are still given as poorly constrained ranges that are partly inconsistent with the observed warming during the industrial period. Here we present a neural network based climate model substitute that increases the efficiency of large climate model ensembles by at least an order of magnitude. Using the observed surface warming over the industrial period and estimates of global ocean heat uptake as constraints for the ensemble, this method estimates ranges for climate sensitivity and radiative forcing that are consistent with observations. In particular, negative values for the uncertain indirect aerosol forcing exceeding –1.2 Wm–2 can be excluded with high confidence. A parameterization to account for the uncertainty in the future carbon cycle is introduced, derived separately from a carbon cycle model. This allows us to quantify the effect of the feedback between oceanic and terrestrial carbon uptake and global warming on global temperature projections. Finally, probability density functions for the surface warming until year 2100 for two illustrative emission scenarios are calculated, taking into account uncertainties in the carbon cycle, radiative forcing, climate sensitivity, model parameters and the observed temperature records. We find that warming exceeds the surface warming range projected by IPCC for almost half of the ensemble members. Projection uncertainties are only consistent with IPCC if a model-derived upper limit of about 5 K is assumed for climate sensitivity.  相似文献   

7.
An emission pathway for stabilization at 6?Wm?2 radiative forcing   总被引：1，自引：0，他引：1  
Representative Concentration Pathway 6.0 (RCP6) is a pathway that describes trends in long-term, global emissions of greenhouse gases (GHGs), short-lived species, and land-use/land-cover change leading to a stabilisation of radiative forcing at 6.0 Watts per square meter (Wm?2) in the year 2100 without exceeding that value in prior years. Simulated with the Asia-Pacific Integrated Model (AIM), GHG emissions of RCP6 peak around 2060 and then decline through the rest of the century. The energy intensity improvement rates changes from 0.9% per year to 1.5% per year around 2060. Emissions are assumed to be reduced cost-effectively in any period through a global market for emissions permits. The exchange of CO2 between the atmosphere and terrestrial ecosystem through photosynthesis and respiration are estimated with the ecosystem model. The regional emissions, except CO2 and N2O, are downscaled to facilitate transfer to climate models.  相似文献   

8.
Terrestrial biosphere carbon storage under alternative climate projections   总被引：2，自引：1，他引：2  
This study investigates commonalities and differences in projected land biosphere carbon storage among climate change projections derived from one emission scenario by five different general circulation models (GCMs). Carbon storage is studied using a global biogeochemical process model of vegetation and soil that includes dynamic treatment of changes in vegetation composition, a recently enhanced version of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). Uncertainty in future terrestrial carbon storage due to differences in the climate projections is large. Changes by the end of the century range from −106 to +201 PgC, thus, even the sign of the response whether source or sink, is uncertain. Three out of five climate projections produce a land carbon source by the year 2100, one is approximately neutral and one a sink. A regional breakdown shows some robust qualitative features. Large areas of the boreal forest are shown as a future CO2 source, while a sink appears in the arctic. The sign of the response in tropical and sub-tropical ecosystems differs among models, due to the large variations in simulated precipitation patterns. The largest uncertainty is in the response of tropical rainforests of South America and Central Africa.  相似文献   

9.
A combination of linear response models is used to estimate the transient changes in the global means of carbon dioxide (CO2) concentration, surface temperature, and sea level due to aviation. Apart from CO2, the forcing caused by ozone (O3) changes due to nitrogen oxide (NOx) emissions from aircraft is also considered. The model is applied to aviation using several CO2 emissions scenarios, based on reported fuel consumption in the past and scenarios for the future, and corresponding NOx emissions. Aviation CO2 emissions from the past until 1995 enlarged the atmospheric CO2 concentration by 1.4 ppmv (1.7% of the anthropogenic CO2 increase since 1800). By 1995, the global mean surface temperature had increased by about 0.004 K, and the sea level had risen by 0.045 cm. In one scenario (Fa1), which assumes a threefold increase in aviation fuel consumption until 2050 and an annual increase rate of 1% thereafter until 2100, the model predicts a CO2 concentration change of 13 ppmv by 2100, causing temperature increases of 0.01, 0.025, 0.05 K and sea level increases of 0.1, 0.3, and 0.5 cm in the years 2015, 2050, and 2100, respectively. For other recently published scenarios, the results range from 5 to 17 ppmv for CO2 concentration increase in the year 2050, and 0.02 to 0.05 K for temperature increase. Under the assumption that present-day aircraft-induced O3 changes cause an equilibrium surface warming of 0.05 K, the transient responses amount to 0.03 K in surface temperature for scenario Fa1 in 1995. The radiative forcing due to an aircraft-induced O3 increase causes a larger temperature change than aircraft CO2 forcing. Also, climate reacts more promptly to changes in O3 than to changes in CO2 emissions from aviation. Finally, even under the assumption of a rather small equilibrium temperature change from aircraft-induced O3 (0.01 K for the 1992 NOx emissions), a proposed new combustor technology which reduces specific NOx emissions will cause a smaller temperature change during the next century than the standard technology does, despite a slightly enhanced fuel consumption. Regional effects are not considered here, but may be larger than the global mean responses.  相似文献   

10.
Summary A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO2 is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO2 was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO2 contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO2 and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.  相似文献   

11.
 Impulse-response-function (IRF) models are designed for applications requiring a large number of climate change simulations, such as multi-scenario climate impact studies or cost-benefit integrated-assessment studies. The models apply linear response theory to reproduce the characteristics of the climate response to external forcing computed with sophisticated state-of-the-art climate models like general circulation models of the physical ocean-atmosphere system and three-dimensional oceanic-plus-terrestrial carbon cycle models. Although highly computer efficient, IRF models are nonetheless capable of reproducing the full set of climate-change information generated by the complex models against which they are calibrated. While limited in principle to the linear response regime (less than about 3 ∘C global-mean temperature change), the applicability of the IRF model presented has been extended into the nonlinear domain through explicit treatment of the climate system's dominant nonlinearities: CO2 chemistry in ocean water, CO2 fertilization of land biota, and sublinear radiative forcing. The resultant nonlinear impulse-response model of the coupled carbon cycle-climate system (NICCS) computes the temporal evolution of spatial patterns of climate change for four climate variables of particular relevance for climate impact studies: near-surface temperature, cloud cover, precipitation, and sea level. The space-time response characteristics of the model are derived from an EOF analysis of a transient 850-year greenhouse warming simulation with the Hamburg atmosphere-ocean general circulation model ECHAM3-LSG and a similar response experiment with the Hamburg carbon cycle model HAMOCC. The model is applied to two long-term CO2 emission scenarios, demonstrating that the use of all currently estimated fossil fuel resources would carry the Earth's climate far beyond the range of climate change for which reliable quantitative predictions are possible today, and that even a freezing of emissions to present-day levels would cause a major global warming in the long term. Received: 28 January 2000 / Accepted: 9 March 2001  相似文献   

12.
Using a coupled climate?Ccarbon cycle model, fossil fuel carbon dioxide (CO2) emissions are derived through a reverse approach of prescribing atmospheric CO2 concentrations according to observations and future projections, respectively. In the second half of the twentieth century, the implied fossil fuel emissions, and also the carbon uptake by land and ocean, are within the range of observational estimates. Larger discrepancies exist in the earlier period (1860?C1960), with small fossil fuel emissions and uncertain emissions from anthropogenic land cover change. In the IPCC SRES A1B scenario, the simulated fossil fuel emissions more than double until 2050 (17 GtC/year) and then decrease to 12 GtC/year by 2100. In addition to A1B, an aggressive mitigation scenario was employed, developed within the European ENSEMBLES project, that peaks at 530 ppm CO2(equiv) around 2050 and then decreases to approach 450 ppm during the twenty-second century. Consistent with the prescribed pathway of atmospheric CO2 in E1, the implied fossil fuel emissions increase from currently 8 GtC/year to about 10 by 2015 and decrease thereafter. In the 2050s (2090s) the emissions decrease to 3.4 (0.5) GtC/year, respectively. As in previous studies, our model simulates a positive climate?Ccarbon cycle feedback which tends to reduce the implied emissions by roughly 1 GtC/year per degree global warming. Further, our results suggest that the 450 ppm stabilization scenario may not be sufficient to fulfill the European Union climate policy goal of limiting the global temperature increase to a maximum of 2°C compared to pre-industrial levels.  相似文献   

13.
Identifying uncertainties in Arctic climate change projections   总被引：2，自引：2，他引：0  
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.  相似文献   

14.
Future climate projections and impact analyses are pivotal to evaluate the potential change in crop yield under climate change. Impact assessment of climate change is also essential to prepare and implement adaptation measures for farmers and policymakers. However, there are uncertainties associated with climate change impact assessment when combining crop models and climate models under different emission scenarios. This study quantifies the various sources of uncertainty associated with future climate change effects on wheat productivity at six representative sites covering dry and wet environments in Australia based on 12 soil types and 12 nitrogen application rates using one crop model driven by 28 global climate models (GCMs) under two representative concentration pathways (RCPs) at near future period 2021–2060 and far future period 2061–2100. We used the analysis of variance (ANOVA) to quantify the sources of uncertainty in wheat yield change. Our results indicated that GCM uncertainty largely dominated over RCPs, nitrogen rates, and soils for the projections of wheat yield at drier locations. However, at wetter sites, the largest share of uncertainty was nitrogen, followed by GCMs, soils, and RCPs. In addition, the soil types at two northern sites in the study area had greater effects on yield change uncertainty probably due to the interaction effect of seasonal rainfall and soil water storage capacity. We concluded that the relative contributions of different uncertainty sources are dependent on climatic location. Understanding the share of uncertainty in climate impact assessment is important for model choice and will provide a basis for producing more reliable impact assessment.  相似文献   

15.
Future climate projections from general circulation models (GCMs) predict an acceleration of the global hydrological cycle throughout the 21st century in response to human-induced rise in temperatures. However, projections of GCMs are too coarse in resolution to be used in local studies of climate change impacts. To cope with this problem, downscaling methods have been developed that transform climate projections into high resolution datasets to drive impact models such as rainfall-runoff models. Generally, the range of changes simulated by different GCMs is considered to be the major source of variability in the results of such studies. However, the cascade of uncertainty in runoff projections is further elongated by differences between impact models, especially where robust calibration is hampered by the scarcity of data. Here, we address the relative importance of these different sources of uncertainty in a poorly monitored headwater catchment of the Ecuadorian Andes. Therefore, we force 7 hydrological models with downscaled outputs of 8 GCMs driven by the A1B and A2 emission scenarios over the 21st century. Results indicate a likely increase in annual runoff by 2100 with a large variability between the different combinations of a climate model with a hydrological model. Differences between GCM projections introduce a gradually increasing relative uncertainty throughout the 21st century. Meanwhile, structural differences between applied hydrological models still contribute to a third of the total uncertainty in late 21st century runoff projections and differences between the two emission scenarios are marginal.  相似文献   

16.
Global and regional climate models (GCM and RCM) are generally biased and cannot be used as forcing variables in ecological impact models without some form of prior bias correction. In this study, we investigated the influence of the bias correction method on drought projections in Mediterranean forests in southern France for the end of the twenty-first century (2071–2100). We used a water balance model with two different atmospheric climate forcings built from the same RCM simulations but using two different correction methods (quantile mapping or anomaly method). Drought, defined here as periods when vegetation functioning is affected by water deficit, was described in terms of intensity, duration and timing. Our results showed that the choice of the bias correction method had little effects on temperature and global radiation projections. However, although both methods led to similar predictions of precipitation amount, they induced strong differences in their temporal distribution, especially during summer. These differences were amplified when the climatic data were used to force the water balance model. On average, the choice of bias correction leads to 45 % uncertainty in the predicted anomalies in drought intensity along with discrepancies in the spatial pattern of the predicted changes and changes in the year-to-year variability in drought characteristics. We conclude that the choice of a bias correction method might have a significant impact on the projections of forest response to climate change.  相似文献   

17.
The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO2 concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO2 concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios.  相似文献   

18.
Global warming caused by anthropogenic CO2 emissions is expected to reduce the capability of the ocean and the land biosphere to take up carbon. This will enlarge the fraction of the CO2 emissions remaining in the atmosphere, which in turn will reinforce future climate change. Recent model studies agree in the existence of such a positive climate–carbon cycle feedback, but the estimates of its amplitude differ by an order of magnitude, which considerably increases the uncertainty in future climate projections. Therefore we discuss, in how far a particular process or component of the carbon cycle can be identified, that potentially contributes most to the positive feedback. The discussion is based on simulations with a carbon cycle model, which is embedded in the atmosphere/ocean general circulation model ECHAM5/MPI-OM. Two simulations covering the period 1860–2100 are conducted to determine the impact of global warming on the carbon cycle. Forced by historical and future carbon dioxide emissions (following the scenario A2 of the Intergovernmental Panel on Climate Change), they reveal a noticeable positive climate–carbon cycle feedback, which is mainly driven by the tropical land biosphere. The oceans contribute much less to the positive feedback and the temperate/boreal terrestrial biosphere induces a minor negative feedback. The contrasting behavior of the tropical and temperate/boreal land biosphere is mostly attributed to opposite trends in their net primary productivity (NPP) under global warming conditions. As these findings depend on the model employed they are compared with results derived from other climate–carbon cycle models, which participated in the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP).
T. J. RaddatzEmail:
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19.
Metrics are often used to compare the climate impacts of emissions from various sources, sectors or nations. These are usually based on global-mean input, and so there is the potential that important information on smaller scales is lost. Assuming a non-linear dependence of the climate impact on local surface temperature change, we explore the loss of information about regional variability that results from using global-mean input in the specific case of heterogeneous changes in ozone, methane and aerosol concentrations resulting from emissions from road traffic, aviation and shipping. Results from equilibrium simulations with two general circulation models are used. An alternative metric for capturing the regional climate impacts is investigated. We find that the application of a metric that is first calculated locally and then averaged globally captures a more complete and informative signal of climate impact than one that uses global-mean input. The loss of information when heterogeneity is ignored is largest in the case of aviation. Further investigation of the spatial distribution of temperature change indicates that although the pattern of temperature response does not closely match the pattern of the forcing, the forcing pattern still influences the response pattern on a hemispheric scale. When the short-lived transport forcing is superimposed on present-day anthropogenic CO2 forcing, the heterogeneity in the temperature response to CO2 dominates. This suggests that the importance of including regional climate impacts in global metrics depends on whether small sectors are considered in isolation or as part of the overall climate change.  相似文献   

20.
The MAGICC (Model for the Assessment of Greenhouse gas Induced Climate Change) model simulation has been carried out for the 2000–2100 period to investigate the impacts of future Indian greenhouse gas emission scenarios on the atmospheric concentrations of carbon dioxide, methane and nitrous oxide besides other parameters like radiative forcing and temperature. For this purpose, the default global GHG (Greenhouse Gases) inventory was modified by incorporation of Indian GHG emission inventories which have been developed using three different approaches namely (a) Business-As-Usual (BAU) approach, (b) Best Case Scenario (BCS) approach and (c) Economy approach (involving the country’s GDP). The model outputs obtained using these modified GHG inventories are compared with various default model scenarios such as A1B, A2, B1, B2 scenarios of AIM (Asia-Pacific Integrated Model) and P50 scenario (median of 35 scenarios given in MAGICC). The differences in the range of output values for the default case scenarios (i.e., using the GHG inventories built into the model) vis-à-vis modified approach which incorporated India-specific emission inventories for AIM and P50 are quite appreciable for most of the modeled parameters. A reduction of 7% and 9% in global carbon dioxide (CO2) emissions has been observed respectively for the years 2050 and 2100. Global methane (CH4) and global nitrous oxide (N2O) emissions indicate a reduction of 13% and 15% respectively for 2100. Correspondingly, global concentrations of CO2, CH4 and N2O are estimated to reduce by about 4%, 4% and 1% respectively. Radiative forcing of CO2, CH4 and N2O indicate reductions of 6%, 14% and 4% respectively for the year 2100. Global annual mean temperature change (incorporating aerosol effects) gets reduced by 4% in 2100. Global annual mean temperature change reduces by 5% in 2100 when aerosol effects have been excluded. In addition to the above, the Indian contributions in global CO2, CH4 and N2O emissions have also been assessed by India Excluded (IE) scenario. Indian contribution in global CO2 emissions was observed in the range of 10%–26%, 6%–36% and 10%–38% respectively for BCS, Economy and BAU approaches, for the years 2020, 2050 and 2100 for P50, A1B-AIM, A2-AIM, B1-AIM & B2-AIM scenarios. CH4 and N2O emissions indicate about 4%–10% and 2%–3% contributions respectively in the global CH4 and N2O emissions for the years 2020, 2050 and 2100. These Indian GHG emissions have significant influence on global GHG concentrations and consequently on climate parameters like RF and ∆T. The study reflects not only the importance of Indian emissions in the global context but also underlines the need of incorporation of country specific GHG emissions in modeling to reduce uncertainties in simulation of climate change parameters.  相似文献   

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