Developed and Developing World Contributions to Climate System Change Based on Carbon Dioxide, Methane and Nitrous Oxide Emissions
Ting WEI1,
Wenjie DONG2,
Qing YAN3,
Jieming CHOU2,
Zhiyong YANG2,
Di TIAN2
Chinese Academy of Meteorological Sciences, Beijing 100081
State Key Laboratory of Earth Surface Processes and Resource Ecology, Future Earth Research Institute, Beijing Normal University, Zhuhai 519087
Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
One of the key issues in international climate negotiations is the formulation of targets for emissions reduction for all countries based on the principle of "common but differentiated responsibilities". This formulation depends primarily on the quantitative attribution of the responsibilities of developed and developing countries for historical climate change. Using the Commuity Earth System Model (CESM), we estimate the responsibilities of developed countries and developing countries for climatic change from 1850 to 2005 using their carbon dioxide, methane and nitrous oxide emissions. The results indicate that developed countries contribute approximately 53%-61%, and developing countries approximately 39%-47%, to the increase in global air temperature, upper oceanic warming, sea-ice reduction in the NH, and permafrost degradation. In addition, the spatial heterogeneity of these changes from 1850 to 2005 is primarily attributed to the emissions of greenhouse gases (GHGs) in developed countries. Although uncertainties remain in the climate model and the external forcings used, GHG emissions in developed countries are the major contributor to the observed climate system changes in the 20th century.
greenhouse gases,
earth system model,
climate modeling
Allen M. R., D. J. Frame, C. Huntingford, C. D. Jones, J. A. Lowe, M. Meinshausen, and N. Meinshausen, 2009: Warming caused by cumulative carbon emissions towards the trillionth tonne. Nature, 458, 1163- 1166.10.1038/nature0801919407800162c647a8fad3e69dc8ddedadf370ecfhttp%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM19407800http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM19407800Global efforts to mitigate climate change are guided by projections of future temperatures. But the eventual equilibrium global mean temperature associated with a given stabilization level of atmospheric greenhouse gas concentrations remains uncertain, complicating the setting of stabilization targets to avoid potentially dangerous levels of global warming. Similar problems apply to the carbon ...
Andres R. J., T. A. Boden, and G. Marland, 2013: Annual fossil-fuel CO2 emissions: Isomass of emissions gridded by one degree latitude by one degree longitude. CDIAC, doi: 10.3334/ CDIAC/ffe.AnnualIsomass.a07946a369560fd5dd66e5725e588b86http%3A%2F%2Fcdiac.esd.ornl.gov%2Fpub%2Fdb1013_v2011%2Fgridded%2Freadme.db1013_v2011.gridded.txthttp://cdiac.esd.ornl.gov/pub/db1013_v2011/gridded/readme.db1013_v2011.gridded.txtAnnual Fossil-Fuel CO2 Emissions: Isomass of Emissions Gridded by One Degree Latitude byOne Degree Longitude RJ Andres, TA Boden, and G. Marland Carbon Dioxide InformationAnalysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak
Andronova N., M. Schlesinger, 2004: Importance of sulfate aerosol in evaluating the relative contributions of regional emissions to the historical global temperature change. Mitigation and Adaptation Strategies for Global Change, 9, 383- 390.10.1023/B:MITI.0000038845.44341.bbf5560f3cd5163476f1dfa8d9e86e136chttp%3A%2F%2Fwww.springerlink.com%2Fcontent%2Fn531nr122x424x77%2Fhttp://www.springerlink.com/content/n531nr122x424x77/During the negotiations of the KyotoProtocol the delegation of Brazil presentedan approach for distributing the burden ofemissions reductions among the Partiesbased on the effect of their cumulativehistorical emissions on the global-averagenear-surface temperature. The Letter tothe Parties does not limit the emissions tobe considered to be only greenhouse gas(GHG) emissions. Thus, in this paper weexplore the importance of anthropogenicSO x emissions that are converted tosulfate aerosol in the atmosphere, togetherwith the cumulative greenhouse gasemissions, in attributing historicaltemperature change. We use historicalemissions and our simple climate model toestimate the relative contributions toglobal warming of the regional emissions byfour Parties: OECD90, Africa and LatinAmerica, Asia, and Eastern Europe and theFormer Soviet Union. Our results show thatfor most Parties the large warmingcontributed by their GHG emissions islargely offset by the correspondingly largecooling by their SO x emissions. Thus,OECD90 has become the dominant contributorto recent global warming following itslarge reduction in SO x emissions after1980.
Davis S. P., G. P. Peters, and K. Caldeira, 2011: The supply chain of CO2 emissions. Proc. Natl. Acad. Sci.USA, 108, 18554- 18559.770a3d71-6614-4d54-af6a-5d24c7695a64f654227a6316404130f1fae6b7aaa16fhttp%3A%2F%2Fwww.jstor.org%2Fstable%2F41352752refpaperuri:(fc70374b430429807d92e3994052ca11)http://www.jstor.org/stable/41352752CO60 emissions from the burning of fossil fuels are conventionally attributed to the country where the emissions are produced (i.e., where the fuels are burned). However, these production-based accounts represent a single point in the value chain of fossil fuels, which may have been extracted elsewhere and may be used to provide goods or services to consumers elsewhere. We present a consistent set of carbon inventories that spans the full supply chain of global CO60 emissions, finding that 10.2 billion tons CO60 or 37% of global emissions are from fossil fuels traded internationally and an additional 6.4 billion tons CO60 or 23% of global emissions are embodied in traded goods. Our results reveal vulnerabilities and benefits related to current patterns of energy use that are relevant to climate and energy policy. In particular, if a consistent and unavoidable price were imposed on CO60 emissions somewhere along the supply chain, then all of the parties along the supply chain would seek to impose that price to generate revenue from taxes collected or permits sold. The geographical concentration of carbon-based fuels and relatively small number of parties involved in extracting and refining those fuels suggest that regulation at the wellhead, mine mouth, or refinery might minimize transaction costs as well as opportunities for leakage.
den Elzen, M. G. J., M. Berk, M. Schaeffer, J. Olivier, C. Hendriks, B. Metz, 1999: The Brazilian proposal and other options for international burden sharing: An evaluation of methodological and policy aspects using the FAIR model. RIVM Report 728001011,129 pp.46ec0c6074388801d4a34389de351398http%3A%2F%2Fwww.narcis.nl%2Fpublication%2FRecordID%2Foai%253Arivm.openrepository.com%253A10029%252F259842http://www.narcis.nl/publication/RecordID/oai%3Arivm.openrepository.com%3A10029%2F259842Tijdens de onderhandelingen over het Kyoto Protocol, werd door Brazilie het zogenaamde Braziliaanse voorstel ingediend. Dit bevat een methodiek om de relatieve bijdrage van Annex I landen (de geindustrialiseerde landen) aan emissiereducties te koppelen aan hun bijdrage aan de gerealiseerde mondiaal gemiddelde temperatuurstijging. Het Braziliaanse voorstel is niet in het Kyoto Protocol opgenomen, maar door de Conference of Parties in Kyoto (CoP-3) verwezen naar SBSTA (Subsidiary Body on Scientific and Technical Advise) voor een nadere bestudering van wetenschappelijke en methodologische aspecten van het voorstel. In de tussentijd vond een herziening van het Brazilianen plaats. In dit rapport worden zowel de originele als de herziene methodologie geevalueerd. De oorspronkelijke methodologie is wetenschappelijk incorrect bevonden. Het herziene model vormt een aanzienlijke, maar bevat nog steeds een aantal tekortkomingen. Deze kunnen alle worden opgelost door een verbeterde parametrisatie, en door de toevoeging van een aantal extra processen of benaderingen te kiezen die al in andere modellen zijn getest en toegepast. Voor het evalueren van het Braziliaanse voorstel en het vergelijken van het voorstel met andere opties voor internationale is een nieuw model ontwikkeld: FAIR (Framework to Assess International Regimes for burden sharing). Lastenverdelingscriteria die rekening houden met historische emissies en/of gebaseerd zijn op een per capita benadering zijn gunstig voor de ontwikkelingslanden. Daarentegen is het meenemen van de antropogene emissies van alle broeikasgassen en de emissies ten gevolge van landgebruiksveranderingen gunstig voor de geindustrialiseerde landen. Een indicator later in de oorzaak-effect keten van het klimaatsprobleem, zoals de bijdrage aan mondiale temperatuurstijging in plaats van emissies, is gunstig voor de ontwikkelingslanden. Toepassing van het Braziliaanse voorstel op wereldschaal zou betekenen dat alle landen onmiddellijk hun emissies zouden moeten reduceren, ongeacht hun niveau van economische ontwikkeling. Om rekening te houden met de verschillen in ontwikkelingsniveau, kan een deelname drempel worden ingevoerd. Daarbij lijkt met name het gebruik van een deelnamedrempel gebaseerd op mondiaal gemiddelde emissie per hoofd interessant, omdat het resulteert in een mondiale convergentie van hoofdelijke emissieruimte. Het beloont reductie-inspanningen van de geindustrialiseerde landen, terwijl het een ontwikkelingslanden stimuleert de groei in hun emissies te beperken. Tenslotte is ook een sector-georienteerde aanpak van internationale lastenverdeling. De resultaten van een eerste voorlopige toepassing van deze benadering op een mondiale schaal, worden hier tevens gepresenteerd.<br>
den Elzen, M. G. J., M. Schaeffer, P. L. Lucas, 2005: Differentiating future commitments on the basis of countries' relative historical responsibility for climate change: uncertainties in the "Brazilian proposal" in the context of a policy implementation. Climatic Change, 71, 277- 301.10.1007/s10584-005-5382-9f0397437-d43c-4909-8209-e9f9b11707d674acf21f93de7b8162e62eeadcd4a9eehttp%3A%2F%2Flink.springer.com%2F10.1007%2Fs10584-005-5382-9refpaperuri:(8d1fa6c151bf02a101f4d3165dafad68)http://link.springer.com/10.1007/s10584-005-5382-9During the negotiations on the Kyoto Protocol, Brazil proposed allocating the greenhouse gas emission reductions of Annex I Parties according to the relative effect of a country- historical emissions on global temperature increase. This paper analyses the impact of scientific uncertainties and of different options in policy implementation (policy choices) on the contribution of countries- historical emissions to indicators of historical responsibility for climate change. The influence of policy choices was found to be at least as large as the impact of the scientific uncertainties analysed here. Building on this, the paper then proceeds to explore the implications of applying the Brazilian Proposal as a climate regime for differentiation of future commitments on the global scale combined with an income threshold for participation of the non-Annex I regions. Under stringent climate targets, such a regime leads to high emission reductions for Annex I regions by 2050, in particular for Europe and Japan. The income threshold assumptions strongly affect the Annex I reductions, even more than the impact of another burden-sharing key. A variant of the Brazilian Proposal, allocating emission reductions on the basis of cumulative emissions since 1990, would lead to a more balanced distribution of emission reductions.
den Elzen, M. G. J., J. G. J. Olivier, N. Höhne, G. Janssens-Michel, 2013: Countries' contributions to climate change: Effect of accounting for all greenhouse gases, recent trends, Basic needs and technological progress. Climatic Change, 121, 397- 412.
Ding Z. L., X. N. Duan, Q. S. Ge, and Z. Q. Zhang, 2009: Control of atmospheric CO2 concentrations by 2050: A calculation on the emission rights of different countries. Science in China Series D: Earth Sciences, 52, 1447- 1469.10.1007/s11430-009-0155-35fcd0a6b-7a70-4d4c-ab89-9ebe948751d896327c04f43795233102b4646977b735http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11430-009-0155-3refpaperuri:(d66fc43737225bdc42697caa5358513d)http://www.cnki.com.cn/Article/CJFDTotal-JDXG200910001.htmThis paper is to provide quantitative data on some critical issues in anticipation of the forthcoming international negotiations in Denmark on the control of atmospheric CO 2 concentrations. Instead of letting only a small number of countries dominate a few controversial dialogues about emissions reductions, a comprehensive global system must be established based on emissions allowances for different countries, to realize the long-term goal of controlling global atmospheric CO 2 concentrations. That a system rooted in "cumulative emissions per capita," the best conception of the "common but differentiated responsibilities" principle affirmed by the Kyoto Protocol according to fundamental standards of fairness and justice, was demonstrated. Based on calculations of various countries' cumulative emissions per capita, estimates of their cumulative emissions from 1900 to 2005, and their annual emissions allowances into the future (2006–2050), a 470 ppmv atmospheric CO 2 concentration target was set. According to the following four objective indicators-total emissions allowance from 1900 to 2050, actual emissions from 1900 to 2005, emissions levels in 2005, and the average growth rate of emissions from 1996 to 2005-all countries and regions whose population was more than 300000 in 2005 were divided into four main groups: countries with emissions deficits, countries and regions needing to reduce their gross emissions, countries and regions needing to reduce their emissions growth rates, and countries that can maintain the current emissions growth rates. Based on this proposal, most G8 countries by 2005 had already expended their 2050 emissions allowances. The accumulated financial value based on emissions has reached more than 5.5 trillion US dollars (20 dollars per ton of CO 2 ). Even if these countries could achieve their ambitious emissions reduction targets in the future, their per capita emissions from 2006 to 2050 would still be much higher than those of developing countries; under such circumstance, these future emissions would create more than 6.3 trillion US dollars in emissions deficits. Because of their low cumulative emissions per capita, most developing countries fall within one of the latter two groups, which means that they have leeway for making emissions decisions in the future. Although China accounts for more than 30% of the total global emissions allowance from 2006 to 2050, its total emissions can be controlled within that allowance by no other way than reducing its future emissions growth rates. In the end, nine key issues related to international climate negotiations were briefly addressed.
Feng J. M., T. Wei, W. J. Dong, Q. Z. Wu, and Y. L. Wang, 2014: CMIP5/AMIP GCM simulations of East Asian summer monsoon. Adv. Atmos. Sci.,31, 836-850, doi: 10.1007/s00376-013-3131-y.10.1007/s00376-013-3131-yc9680700-d57c-42b7-a3b7-99ca2d4aae6231bfaec48a836cca82a52c8ef20c79a2http%3A%2F%2Fd.wanfangdata.com.cn%2FPeriodical_dqkxjz-e201404010.aspxrefpaperuri:(8b3f85d64f6aeb7632ed393954778eb2)http://d.wanfangdata.com.cn/Periodical_dqkxjz-e201404010.aspxThe East Asian summer monsoon(EASM) is a distinctive component of the Asian climate system and critically influences the economy and society of the region. To understand the ability of AGCMs in capturing the major features of EASM, 10 models that participated in Coupled Model Intercomparison Project/Atmospheric Model Intercomparison Project(CMIP5/AMIP), which used observational SST and sea ice to drive AGCMs during the period 1979-2008, were evaluated by comparing with observations and AMIP II simulations. The results indicated that the multi-model ensemble(MME) of CMIP5/AMIP captures the main characteristics of precipitation and monsoon circulation, and shows the best skill in EASM simulation, better than the AMIP II MME. As for the Meiyu/Changma/Baiyu rainbelt, the intensity of rainfall is underestimated in all the models. The biases are caused by a weak western Pacific subtropical high(WPSH) and accompanying eastward southwesterly winds in group I models, and by a too strong and west-extended WPSH as well as westerly winds in group II models. Considerable systematic errors exist in the simulated seasonal migration of rainfall, and the notable northward jumps and rainfall persistence remain a challenge for all the models. However, the CMIP5/AMIP MME is skillful in simulating the western North Pacific monsoon index(WNPMI).
Flato G., Coauthors, 2013: Evaluation of Climate Models. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker et al., Eds. Cambridge University Press, 741- 866.fd007fcad35c77fd4cfd40bbca30aba8http%3A%2F%2Felib.dlr.de%2F95697%2Fhttp://elib.dlr.de/95697/Climate models have continued to be developed and improved since the AR4, and many models have been extended into Earth System models by including the representation of biogeochemical cycles important to climate change. These models allow for policy-relevant calculations such as the carbon dioxide (CO2) emissions compatible with a specified climate stabilization target. In addition, the range of climate variables and processes that have been evaluated has greatly expanded, and differences between models and observations are increasingly quantified using -榩erformance metrics-. In this chapter, model evaluation covers simulation of the mean climate, of historical climate change, of variability on multiple time scales and of regional modes of variability. This evaluation is based on recent internationally coordinated model experiments, including simulations of historic and paleo climate, specialized experiments designed to provide insight into key climate processes and feedbacks and regional climate downscaling. Figure 9.44 provides an overview of model capabilities as assessed in this chapter, including improvements, or lack thereof, relative to models assessed in the AR4. The chapter concludes with an assessment of recent work connecting model performance to the detection and attribution of climate change as well as to future projections.
Frank D. C., J. Esper, C. C. Raible, U. Büntgen V. Trouet, B. Stocker, and F. Joos, 2010: Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate. Nature, 463, 527- 530.10.1038/nature08769201109993f6e0a73d4187807df2e62614f8df48ahttp%3A%2F%2Fonlinelibrary.wiley.com%2Fresolve%2Freference%2FADS%3Fid%3D2010Natur.463..527Fhttp://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM20110999Abstract The processes controlling the carbon flux and carbon storage of the atmosphere, ocean and terrestrial biosphere are temperature sensitive and are likely to provide a positive feedback leading to amplified anthropogenic warming. Owing to this feedback, at timescales ranging from interannual to the 20-100-kyr cycles of Earth's orbital variations, warming of the climate system causes a net release of CO(2) into the atmosphere; this in turn amplifies warming. But the magnitude of the climate sensitivity of the global carbon cycle (termed gamma), and thus of its positive feedback strength, is under debate, giving rise to large uncertainties in global warming projections. Here we quantify the median gamma as 7.7 p.p.m.v. CO(2) per degrees C warming, with a likely range of 1.7-21.4 p.p.m.v. CO(2) per degrees C. Sensitivity experiments exclude significant influence of pre-industrial land-use change on these estimates. Our results, based on the coupling of a probabilistic approach with an ensemble of proxy-based temperature reconstructions and pre-industrial CO(2) data from three ice cores, provide robust constraints for gamma on the policy-relevant multi-decadal to centennial timescales. By using an ensemble of >200,000 members, quantification of gamma is not only improved, but also likelihoods can be assigned, thereby providing a benchmark for future model simulations. Although uncertainties do not at present allow exclusion of gamma calculated from any of ten coupled carbon-climate models, we find that gamma is about twice as likely to fall in the lowermost than in the uppermost quartile of their range. Our results are incompatibly lower (P < 0.05) than recent pre-industrial empirical estimates of approximately 40 p.p.m.v. CO(2) per degrees C (refs 6, 7), and correspondingly suggest approximately 80% less potential amplification of ongoing global warming.
Fung I. Y., S. C. Donry, K. Lindsay, and J. John, 2005: Evolution of carbon sinks in a changing climate. Proc. Natl. Acad. Sci.USA, 102, 11 201- 11 206.10.1073/pnas.050494910216061800b9289939ed32095117ca97c1cef8c6c9http%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM16061800http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM16061800ABSTRACT Climate change is expected to influence the capacities of the land and oceans to act as repositories for anthropogenic CO2 and hence provide a feedback to climate change. A series of experiments with the National Center for Atmospheric Research-Climate System Model 1 coupled carbon-climate model shows that carbon sink strengths vary with the rate of fossil fuel emissions, so that carbon storage capacities of the land and oceans decrease and climate warming accelerates with faster CO2 emissions. Furthermore, there is a positive feedback between the carbon and climate systems, so that climate warming acts to increase the airborne fraction of anthropogenic CO2 and amplify the climate change itself. Globally, the amplification is small at the end of the 21st century in this model because of its low transient climate response and the near-cancellation between large regional changes in the hydrologic and ecosystem responses. Analysis of our results in the context of comparable models suggests that destabilization of the tropical land sink is qualitatively robust, although its degree is uncertain.
Gent, P. R., Coauthors, 2011: The community climate system model version 4. J. Climate, 24, 4973- 4991.10.1175/2011JCLI4083.129ea5917-d3e1-42e9-940c-59df742c81311262048e87cc58728918a5ed03f21f04http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F224017881_The_Community_Climate_System_Model_Version_4%3Fev%3Dauth_pubrefpaperuri:(00848f71c6cb0bc7a12384180928d7e8)http://www.researchgate.net/publication/224017881_The_Community_Climate_System_Model_Version_4?ev=auth_pubAbstract The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1° results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4°-resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in CCSM4 producing El Ni09o–Southern Oscillation variability with a much more realistic frequency distribution than in CCSM3, although the amplitude is too large compared to observations. These changes also improve the Madden–Julian oscillation and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the Gulf Stream path and the North Atlantic Ocean meridional overturning circulation. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than CCSM3, and for several reasons the Arctic sea ice concentration is improved in CCSM4. An ensemble of twentieth-century simulations produces a good match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4°C. This is consistent with the fact that CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of shortwave and longwave cloud forcings.
Giorgi F., R. Francisco, 2000: Uncertainties in regional climate change prediction: A regional analysis of ensemble simulations with the HADCM2 coupled AOGCM. Climate Dyn., 16, 169- 182.10.1007/PL00013733c8b085d5582125e701031d306af815c3http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2FPL00013733http://link.springer.com/article/10.1007/PL00013733We analyze ensembles (four realizations) of historical and future climate transient experiments carried out with the coupled atmosphere-ocean general circulation model (AOGCM) of the Hadley Centre for Climate Prediction and Research, version HADCM2, with four scenarios of greenhouse gas (GHG) and sulfate forcing. The analysis focuses on the regional scale, and in particular on 21 regions covering all land areas in the World (except Antarctica). We examine seasonally averaged surface air temperature and precipitation for the historical period of 1961-1990 and the future climate period of 2046-2075. Compared to previous AOGCM simulations, the HADCM2 model shows a good performance in reproducing observed regional averages of summer and winter temperature and precipitation. The model, however, does not reproduce well observed interannual variability. We find that the uncertainty in regional climate change predictions associated with the spread of different realizations in an ensemble (i.e. the uncertainty related to the internal model variability) is relatively low for all scenarios and regions. In particular, this uncertainty is lower than the uncertainty due to inter-scenario variability and (by comparison with previous regional analyses of AOGCMs) with inter-model variability. The climate biases and sensitivities found for different realizations of the same ensemble were similar to the corresponding ensemble averages and the averages associated with individual realizations of the same ensemble did not differ from each other at the 5% confidence level in the vast majority of cases. These results indicate that a relatively small number of realizations (3 or 4) is sufficient to characterize an AOGCM transient climate change prediction at the regional scale.
Harvey, D., Coauthors, 1997: An introduction to simple climate models used in the IPCC second assessment report,T. H. John et al., Eds. IPCC technical paper II-February 1997, IPCC, Geneva, Switzerland, 52 pp.8512aeaeb104424f9bdbebea0fbdb793http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F250590661_An_Introduction_to_Simple_Climate_Models_used_in_the_IPCC_Second_Assessment_Reporthttp://www.researchgate.net/publication/250590661_An_Introduction_to_Simple_Climate_Models_used_in_the_IPCC_Second_Assessment_ReportUniversity Publications
He J. K., W. Y. Chen, F. Teng, and B. Liu, 2009: Long-term climate change mitigation target and carbon permit allocation. Advances in Climate Change Research, 5, 362- 368. (in Chinese)10.1002/9780470686812.ch11f778fe0f38e93ebeaec6fa184af1101http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-QHBH200906012.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-QHBH200906012.htmLong-term climate change mitigation target would highly constrain global carbon emissions in future.Carbon permit allocation under the long-term mitigation target would impact development space for all countries,involving the fundamental interests.Some developed countries advocate the principle of per capita emission convergence while China and other developing countries propose the principle of convergence of accumulative emission per capita to consider historical responsibility.If the latter is used for carbon permit allocation,CO2 emissions of developed countries since the industrial revolution have far exceeded their allocated permits.Developed countries- high per capita emissions at present and for quite a long period in future would continue to occupy emission spaces for developing countries.Therefore,developed countries must commit deeper emission reduction rate for the next commitment period at the Copenhagen conference in order to achieve the emission pathway under the long-term emission reduction target,and to save necessary development space for developing countries.At the same time,developed countries should provide adequate financial and technical support as compensation for their overuse of the development space for developing countries,to improve developing countries- capacity to respond to climate change under the framework of sustainable development.On the one hand,we should insist on the principle of equity to obtain reasonable emission space for our country in the international climate change negotiation;while on the other hand,we should enhance development toward low-carbon economy to protect global environment and to achieve sustainable development.
Höhne N., K. Blok, 2005: Calculating historical contributions to climate change-discussing the "Brazilian Proposal". Climatic Change, 71, 141- 173.10.1007/s10584-005-5929-965b23a52-a10d-47ca-83df-8110227f3f337989835455fe68a8fa5eb11795452234http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10584-005-5929-9refpaperuri:(4a6b933d80ba5ce6f08beca495317569)http://link.springer.com/10.1007/s10584-005-5929-9This paper discusses methodological issues relevant to the calculation of historical responsibility of countries for climate change ('The Brazilian Proposal'). Using a simple representation of the climate system, the paper compares contributions to climate change using different indicators: current radiative forcing, current GWP-weighted emissions, radiative forcing from increased concentrations, cumulative GWP-weighted emissions, global-average surface-air temperature increase and two new indicators: weighted concentrations (analogue to GWP-weighted emissions) and integrated temperature increase. Only the last two indicators are at the same time 'backward looking' (take into account historical emissions), 'backward discounting' (early emissions weigh less, depending on the decay in the atmosphere) and 'forward looking' (future effects of the emissions are considered) and are comparable for all gases. Cumulative GWP-weighted emissions are simple to calculate but are not 'backward discounting'. 'Radiative forcing' and 'temperature increase' are not 'forward looking'. 'Temperature increase' discounts the emissions of the last decade due to the slow response of the climate system. It therefore gives low weight to regions that have recently significantly increased emissions. Results of the five different indicators are quite similar for large groups (but possibly not for individual countries): industrialized countries contributed around 60% to today's climate change, developing countries around 40% (using the available data for fossil, industrial and forestry CO 2 , CH 4 and N 2 O). The paper further argues including non-linearities of the climate system or using a simplified linear system is a political choice. The paper also notes that results of contributions to climate change need to be interpreted with care: Countries that developed early benefited economically, but have high historical emission, and countries developing at a later period can profit from developments in other countries and are therefore likely to have a lower contribution to climate change.
Höhne N., Coauthors, 2011: Contributions of individual countries' emissions to climate change and their uncertainty. Climatic Change, 106, 359- 391.10.1007/s10584-010-9930-6ef2e7925-b6ee-4a00-b6d6-16f20ec7e0b2slarticleid_215471d620ecc725c998dcf4287c8fbaed1372http%3A%2F%2Flink.springer.com%2F10.1007%2Fs10584-010-9930-6refpaperuri:(d2df702a2ab871b167a0a7a818e6e547)http://link.springer.com/10.1007/s10584-010-9930-6We have compiled historical greenhouse gas emissions and their uncertainties on country and sector level and assessed their contribution to cumulative emissions and to global average temperature increase in the past and for a the future emission scenario. We find that uncertainty in historical contribution estimates differs between countries due to different shares of greenhouse gases and time development of emissions. Although historical emissions in the distant past are very uncertain, their influence on countries&#8217; or sectors&#8217; contributions to temperature increase is relatively small in most cases, because these results are dominated by recent (high) emissions. For relative contributions to cumulative emissions and temperature rise, the uncertainty introduced by unknown historical emissions is larger than the uncertainty introduced by the use of different climate models. The choice of different parameters in the calculation of relative contributions is most relevant for countries that are different from the world average in greenhouse gas mix and timing of emissions. The choice of the indicator (cumulative GWP weighted emissions or temperature increase) is very important for a few countries (altering contributions up to a factor of 2) and could be considered small for most countries (in the order of 10%). The choice of the year, from which to start accounting for emissions (e.g. 1750 or 1990), is important for many countries, up to a factor of 2.2 and on average of around 1.3. Including or excluding land-use change and forestry or non-CO<sub>2</sub> gases changes relative contributions dramatically for a third of the countries (by a factor of 5 to a factor of 90). Industrialised countries started to increase CO<sub>2</sub> emissions from energy use much earlier. Developing countries&#8217; emissions from land-use change and forestry as well as of CH<sub>4</sub> and N<sub>2</sub>O were substantial before their emissions from energy use.
IPCC, 1996: Climate Change 1995: The Science of Climate Change. Contribution of Working Group I to the Second Assessment Report of the Intergovernmental Panel on Climate Change,J. T. Houghton et al., Eds. Cambridge University Press, 572 pp.10.1126/science.292.5520.1261e1c88eb3ff7a1da711eb4d6a9afb06fahttp%3A%2F%2Fci.nii.ac.jp%2Fncid%2FBA27797439http://ci.nii.ac.jp/ncid/BA27797439ABSTRACT Climate Change 1995--The Science of Climate Change is the most comprehensive assessment available of current scientific understanding of human influences on past, present and future climate. Prepared under the auspices of the Intergovernmental Panel on Climate Change (IPCC), each chapter is written by teams of lead authors and contributors recognized internationally as leading experts in their field. Climate Change 1995 is the first full sequel to the original 1990 IPCC scientific assessment, bringing us completely up to date on the full range of scientific aspects of climate change. This assessment forms the standard scientific reference for all those concerned with climate change and its consequences, including policy makers in governments and industry worldwide, and researchers and senior-level students in environmental science, meteorology, climatology, biology, ecology and atmospheric chemistry.
IPCC, 2013: Summary for Policymakers. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker et al., Eds. Cambridge University Press, 1- 30.10.1080/02666280600694342be0de0218f3f2e5068bcf40dc05a7bdehttp%3A%2F%2Fwww.ingentaconnect.com%2Fcontent%2Fmscp%2Fene%2F2007%2F00000018%2FF0020003%2Fart00009http://www.ingentaconnect.com/content/mscp/ene/2007/00000018/F0020003/art00009The article discusses the author's comment concerning Intergovernmental Panel on Climate Change scientific report for 1990, 1995, 2001, and 2007. The author has expressed disagreement on report citing that it was inappropriate as no model had ever been validated and there seem to be no attempt to do so. He pointed out that the 2007 report was the most distasteful because it has unreliable data, inadequate statistical treatment and gross exaggeration of model capacity.
Jones, C., Coauthors, 2013: Twenty-first-century compatible CO2 Emissions and airborne fraction simulated by CMIP5 earth system models under four representative concentration pathways. J. Climate, 26, 4398- 413.
Lachenbruch A. H., B. V. Marshall, 1986: Changing climate: Geothermal evidence from permafrost in the Alaskan Arctic. Science, 234, 689- 696.10.1126/science.234.4777.68917744468b1cda7a59937524f8d5b19c4444092b1http%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM17744468http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM17744468Temperature profiles measured in permafrost in northernmost Alaska usually have anomalous curvature in the upper 100 meters or so. When analyzed by heat-conduction theory, the profiles indicate a variable but widespread secular warming of the permafrost surface, generally in the range of 2 to 4 Celsius degrees during the last few decades to a century. Although details of the climatic change cannot be resolved with existing data, there is little doubt of its general magnitude and timing; alternative explanations are limited by the fact that heat transfer in cold permafrost is exclusively by conduction. Since models of greenhouse warming predict climatic change will be greatest in the Arctic and might already be in progress, it is prudent to attempt to understand the rapidly changing thermal regime in this region.
Le Quéré, Coauthors, 2009: Trends in the sources and sinks of carbon dioxide. Nature Geoscience, 2, 831- 836.10.1038/ngeo689c6c761efb721eb15b72b86da0af861a3http%3A%2F%2Fwww.cabdirect.org%2Fabstracts%2F20103018943.htmlhttp://www.cabdirect.org/abstracts/20103018943.htmlABSTRACT Efforts to control climate change require the stabilization of atmospheric CO2 concentrations. This can only be achieved through a drastic reduction of global CO2 emissions. Yet fossil fuel emissions increased by 29% between 2000 and 2008, in conjunction with increased contributions from emerging economies, from the production and international trade of goods and services, and from the use of coal as a fuel source. In contrast, emissions from land-use changes were nearly constant. Between 1959 and 2008, 43% of each year's CO2 emissions remained in the atmosphere on average; the rest was absorbed by carbon sinks on land and in the oceans. In the past 50 years, the fraction of CO2 emissions that remains in the atmosphere each year has likely increased, from about 40% to 45%, and models suggest that this trend was caused by a decrease in the uptake of CO2 by the carbon sinks in response to climate change and variability. Changes in the CO2 sinks are highly uncertain, but they could have a significant influence on future atmospheric CO2 levels. It is therefore crucial to reduce the uncertainties.
Liu Z., Coauthors, 2015: Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature, 524, 335- 338.10.1038/nature1467726289204465cb849bd4ecf457619108f5174d907http%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM26289204http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM26289204Nearly three-quarters of the growth in global carbon emissions from the burning of fossil fuels and cement production between 2010 and 2012 occurred in China1,172. Yet estimates of Chinese emissions remain subject to large uncertainty; inventories of China?s total fossil fuel carbon emissions in 2008 differ by 0.3 gigatonnes of carbon, or 15 per cent1,173,174,5. The primary sources of this uncertainty are conflicting estimates of energy consumption and emission factors, the latter being uncertain because of very few actual measurements representative of the mix of Chinese fuels. Here we re-evaluate China?s carbon emissions using updated and harmonized energy consumption and clinker production data and two new and comprehensive sets of measured emission factors for Chinese coal. We find that total energy consumption in China was 10 per cent higher in 2000?2012 than the value reported by China?s national statistics6, that emission factors for Chinese coal are on average 40 per cent lower than the default values recommended by the Intergovernmental Panel on Climate Change7, and that emissions from China?s cement production are 45 per cent less than recent estimates1,174. Altogether, our revised estimate of China?s CO2emissions from fossil fuel combustion and cement production is 2.49 gigatonnes of carbon (2 standard deviations = ±7.3 per cent) in 2013, which is 14 per cent lower than the emissions reported by other prominent inventories1,174,178. Over the full period 2000 to 2013, our revised estimates are 2.9 gigatonnes of carbon less than previous estimates of China?s cumulative carbon emissions1,174. Our findings suggest that overestimation of China?s emissions in 2000?2013 may be larger than China?s estimated total forest sink in 1990?2007 (2.66 gigatonnes of carbon)917or China?s land carbon sink in 2000?2009 (2.6 gigatonnes of carbon)10.
Matthews H. D., N. P. Gillett, P. A. Stott, and K. Zickfeld, 2009: The proportionality of global warming to cumulative carbon emissions. Nature, 459, 829- 832.10.1038/nature080471951633816a3c062b3f0a6c2aa6509235a48d54chttp%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM19516338http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM19516338The global temperature response to increasing atmospheric CO(2) is often quantified by metrics such as equilibrium climate sensitivity and transient climate response. These approaches, however, do not account for carbon cycle feedbacks and therefore do not fully represent the net response of the Earth system to anthropogenic CO(2) emissions. Climate-carbon modelling experiments have shown that: (1) the warming per unit CO(2) emitted does not depend on the background CO(2) concentration; (2) the total allowable emissions for climate stabilization do not depend on the timing of those emissions; and (3) the temperature response to a pulse of CO(2) is approximately constant on timescales of decades to centuries. Here we generalize these results and show that the carbon-climate response (CCR), defined as the ratio of temperature change to cumulative carbon emissions, is approximately independent of both the atmospheric CO(2) concentration and its rate of change on these timescales. From observational constraints, we estimate CCR to be in the range 1.0-2.1 degrees C per trillion tonnes of carbon (Tt C) emitted (5th to 95th percentiles), consistent with twenty-first-century CCR values simulated by climate-carbon models. Uncertainty in land-use CO(2) emissions and aerosol forcing, however, means that higher observationally constrained values cannot be excluded. The CCR, when evaluated from climate-carbon models under idealized conditions, represents a simple yet robust metric for comparing models, which aggregates both climate feedbacks and carbon cycle feedbacks. CCR is also likely to be a useful concept for climate change mitigation and policy; by combining the uncertainties associated with climate sensitivity, carbon sinks and climate-carbon feedbacks into a single quantity, the CCR allows CO(2)-induced global mean temperature change to be inferred directly from cumulative carbon emissions.
Matthews H. D., T. L. Graham, S. Keverian, C. Lamontagne, D. Seto, and T. J. Smith, 2014: National contributions to observed global warming. Environmental Research Letters, 9, 014010.10.1088/1748-9326/9/1/014010e74c480bc3f5c4d724f63a2c5cb9c2f0http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014ERL.....9a4010Dhttp://adsabs.harvard.edu/abs/2014ERL.....9a4010DThere is considerable interest in identifying national contributions to global warming as a way of allocating historical responsibility for observed climate change. This task is made difficult by uncertainty associated with national estimates of historical emissions, as well as by difficulty in estimating the climate response to emissions of gases with widely varying atmospheric lifetimes. Here, we present a new estimate of national contributions to observed climate warming, including CO 2 emissions from fossil fuels and land-use change, as well as methane, nitrous oxide and sulfate aerosol emissions While some countries' warming contributions are reasonably well defined by fossil fuel CO 2 emissions, many countries have dominant contributions from land-use CO 2 and non-CO 2 greenhouse gas emissions, emphasizing the importance of both deforestation and agriculture as components of a country's contribution to climate warming. Furthermore, because of their short atmospheric lifetime, recent sulfate aerosol emissions have a large impact on a country's current climate contribution We show also that there are vast disparities in both total and per-capita climate contributions among countries, and that across most developed countries, per-capita contributions are not currently consistent with attempts to restrict global temperature change to less than 202°C above pre-industrial temperatures.
Neale R.B., Coauthors, 2010: Description of the NCAR community atmosphere model (CAM 5.0). NCAR Tech. Note NCAR/TN-486+ STR.6f26a10149886a88be2ebcc7d84fd037http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F224017878_Description_of_the_NCAR_Community_Atmosphere_Modelhttp://www.researchgate.net/publication/224017878_Description_of_the_NCAR_Community_Atmosphere_ModelThe Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR Scientific Divisions; copies may be obtained on request from the Publications Office of NCAR. Designation symbols for the series include: EDD: IA: PPR: Engineering, Design, or Development Reports Equipment descriptions, test results, instrumentation, and operating and maintenance manuals. Instructional Aids Instruction manuals, bibliographies, film supplements, and other research or instructional aids. Program Progress Reports Field program reports, interim and working reports, survey reports, and plans for experiments. PROC: Proceedings Documentation of symposia, colloquia, conferences, workshops, and lectures. (Distribution may be limited to attendees.) STR: Scientific and Technical Reports Data compilations, theoretical and numerical
Osterkamp T. E., 2005: The recent warming of permafrost in Alaska. Global and Planetary Change, 49, 187- 20210.1016/j.gloplacha.2005.09.0015e548f0e502e1232fededce68a167968http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0921818105001505http://www.sciencedirect.com/science/article/pii/S0921818105001505The observed warming has not produced an increasing trend in maximum active layer thicknesses due to its seasonality. Near Healy, permafrost has been thawing at the top since the late 1980s at about 10 cm/yr. At Gulkana, permafrost was thawing from the bottom at a rate of 4 cm/yr that accelerated to 9 cm/yr after 2000.
Peters G. P., J. C. Minx, C. L. Weber and O. Edenhofer, 2011: Growth in emission transfers via international trade from 1990 to 2008. Proc. Natl. Acad. Sci.USA, 108, 8903- 8908.10.1073/pnas.10063881082151887938d541f0fce472cd1865001abae56defhttp%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM21518879http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM21518879Abstract Despite the emergence of regional climate policies, growth in global CO(2) emissions has remained strong. From 1990 to 2008 CO(2) emissions in developed countries (defined as countries with emission-reduction commitments in the Kyoto Protocol, Annex B) have stabilized, but emissions in developing countries (non-Annex B) have doubled. Some studies suggest that the stabilization of emissions in developed countries was partially because of growing imports from developing countries. To quantify the growth in emission transfers via international trade, we developed a trade-linked global database for CO(2) emissions covering 113 countries and 57 economic sectors from 1990 to 2008. We find that the emissions from the production of traded goods and services have increased from 4.3 Gt CO(2) in 1990 (20% of global emissions) to 7.8 Gt CO(2) in 2008 (26%). Most developed countries have increased their consumption-based emissions faster than their territorial emissions, and non-energy-intensive manufacturing had a key role in the emission transfers. The net emission transfers via international trade from developing to developed countries increased from 0.4 Gt CO(2) in 1990 to 1.6 Gt CO(2) in 2008, which exceeds the Kyoto Protocol emission reductions. Our results indicate that international trade is a significant factor in explaining the change in emissions in many countries, from both a production and consumption perspective. We suggest that countries monitor emission transfers via international trade, in addition to territorial emissions, to ensure progress toward stabilization of global greenhouse gas emissions.
Prather, M. J., Coauthors, 2009: Tracking uncertainties in the causal chain from human activities to climate. Geophys. Res. Lett.,36,L05707, doi: 10.1029/2008GL036474.10.1029/2008GL0364746d1cdeaf1d48685d25bad078c98189a3http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2008GL036474%2Ffullhttp://onlinelibrary.wiley.com/doi/10.1029/2008GL036474/fullAttribution of climate change to individual countries is a part of ongoing policy discussions, e.g., the Brazil proposal, and requires a quantifiable link between emissions and climate change. We present a constrained propagation of errors that tracks uncertainties from human activities to greenhouse gas emissions, to increasing abundances of greenhouse gases, to radiative forcing of climate, a...
Rigor I. G., J. M. Wallace, and R. L. Colony, 2002: Response of sea ice to the Arctic Oscillation. J. Climate, 15, 2648- 2663.10.1175/1520-0442(2002)0152.0.CO;2db2ff2396f4fc185d65598f638377b3bhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2002JCli...15.2648Rhttp://adsabs.harvard.edu/abs/2002JCli...15.2648RAbstract Data collected by the International Arctic Buoy Programme from 1979 to 1998 are analyzed to obtain statistics of sea level pressure (SLP) and sea ice motion (SIM). The annual and seasonal mean fields agree with those obtained in previous studies of Arctic climatology. The data show a 3-hPa decrease in decadal mean SLP over the central Arctic Ocean between 1979–88 and 1989–98. This decrease in SLP drives a cyclonic trend in SIM, which resembles the structure of the Arctic Oscillation (AO). Regression maps of SIM during the wintertime (January–March) AO index show 1) an increase in ice advection away from the coast of the East Siberian and Laptev Seas, which should have the effect of producing more new thin ice in the coastal flaw leads; 2) a decrease in ice advection from the western Arctic into the eastern Arctic; and 3) a slight increase in ice advection out of the Arctic through Fram Strait. Taken together, these changes suggest that at least part of the thinning of sea ice recently observed over the Arctic Ocean can be attributed to the trend in the AO toward the high-index polarity. Rigor et al. showed that year-to-year variations in the wintertime AO imprint a distinctive signature on surface air temperature (SAT) anomalies over the Arctic, which is reflected in the spatial pattern of temperature change from the 1980s to the 1990s. Here it is shown that the memory of the wintertime AO persists through most of the subsequent year: spring and autumn SAT and summertime sea ice concentration are all strongly correlated with the AO index for the previous winter. It is hypothesized that these delayed responses reflect the dynamical influence of the AO on the thickness of the wintertime sea ice, whose persistent "footprint" is reflected in the heat fluxes during the subsequent spring, in the extent of open water during the subsequent summer, and the heat liberated in the freezing of the open water during the subsequent autumn.
Rosa L. P., S. K. Ribeiro, M. S. Muylaert, and C. P. de Campos, 2004: Comments on the Brazilian proposal and contributions to global temperature increase with different climate responses CO2 emissions due to fossil fuels, CO2 emissions due to land use change. Energy Policy, 32, 1499- 1510.
Shu Q., Z. Song, and F. Qiao, 2015: Assessment of sea ice simulations in the CMIP5 models. Cryosphere, 9, 399- 409.10.5194/tc-9-399-20153fcfa87b2fbd22e344b14c27b438f3cdhttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014TCD.....8.3413Shttp://adsabs.harvard.edu/abs/2014TCD.....8.3413SThe historical simulations of sea ice during 1979 to 2005 by the Coupled Model Intercomparison Project Phase 5 (CMIP5) are compared with satellite observations and Global Ice-Ocean Modeling and Assimilation System (GIOMAS) data in this study. Forty-nine models, almost all of the CMIP5 climate models and Earth System Models, are used. For the Antarctic, multi-model ensemble mean (MME) results can give good climatology of sea ice extent (SIE), but the linear trend is incorrect. The linear trend of satellite-observed Antarctic SIE is 1.56 × 10kmdecade; only 1/7 CMIP5 models show increasing trends, and the linear trend of CMIP5 MME is negative (-3.36 × 10kmdecade). For the Arctic, both climatology and linear trend are better reproduced. Sea ice volume (SIV) is also evaluated in this study, and this is a first attempt to evaluate the SIV in all CMIP5 models. Compared with the GIOMAS data, the SIV values in both Antarctic and Arctic are too small, especially in spring and winter. The GIOMAS SIV in September is 16.7 × 10km, while the corresponding Antarctic SIV of CMIP5 MME is 13.0 × 10km, almost 22% less. The Arctic SIV of CMIP5 in April is 26.8 × 10km, which is also less than the GIOMAS SIV (29.3 × 10km). This means that the sea ice thickness simulated in CMIP5 is too thin although the SIE is fairly well simulated.
Slater A. G., D. M. Lawrence, 2013: Diagnosing present and future permafrost from climate models. J. Climate, 26, 5608- 5623.10.1175/JCLI-D-12-00341.1f5d2f174-0c8f-4c06-a926-96bcabd4d236746552fd19ccd66ec8c4214051acc1b6http%3A%2F%2Fconnection.ebscohost.com%2Fc%2Farticles%2F89396224%2Fdiagnosing-present-future-permafrost-from-climate-modelsrefpaperuri:(ff303f96d873bf4bfea06f093b161db1)http://connection.ebscohost.com/c/articles/89396224/diagnosing-present-future-permafrost-from-climate-modelsAbstract Permafrost is a characteristic aspect of the terrestrial Arctic and the fate of near-surface permafrost over the next century is likely to exert strong controls on Arctic hydrology and biogeochemistry. Using output from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the authors assess its ability to simulate present-day and future permafrost. Permafrost extent diagnosed directly from each climate model's soil temperature is a function of the modeled surface climate as well as the ability of the land surface model to represent permafrost physics. For each CMIP5 model these two effects are separated by using indirect estimators of permafrost driven by climatic indices and compared to permafrost extent directly diagnosed via soil temperatures. Several robust conclusions can be drawn from this analysis. Significant air temperature and snow depth biases exist in some model's climates, which degrade both directly and indirectly diagnosed permafrost conditions. The range of directly calculated present-day (1986–2005) permafrost area is extremely large (~4–25 × 10 6 km 2 ). Several land models contain structural weaknesses that limit their skill in simulating cold region subsurface processes. The sensitivity of future permafrost extent to temperature change over the present-day observed permafrost region averages (1.67 ± 0.7) × 10 6 km 2 °C 611 but is a function of the spatial and temporal distribution of climate change. Because of sizable differences in future climates for the representative concentration pathway (RCP) emission scenarios, a wide variety of future permafrost states is predicted by 2100. Conservatively, the models suggest that for RCP4.5, permafrost will retreat from the present-day discontinuous zone. Under RCP8.5, sustainable permafrost will be most probable only in the Canadian Archipelago, Russian Arctic coast, and east Siberian uplands.
Taylor K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485- 498.10.1175/BAMS-D-11-00094.10a93ff62-7ac1-4eaa-951b-da834bb5d6acd378bae55de68ca8b37ba4ba57a3c0b9http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2012BAMS...93..485Trefpaperuri:(102c64f576f0dc49ca552e6df691421b)http://adsabs.harvard.edu/abs/2012BAMS...93..485TThe fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes "long term" simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of "near term" simulations focusing on recent decades and the future to year 2035. These "decadal predictions" are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
Trudinger C., I. Enting, 2005: Comparison of formalisms for attributing responsibility for climate change: Non-linearities in the Brazilian Proposal. Climatic Change, 68, 67- 99.
UNFCCC, 1997: Paper No. 1: Brazil; proposed elements of a protocol to the United Nations framework convention on climate change. No. UNFCCC/AGBM/1997/MISC.1/Add.3 GE.97. Bonn.
UNFCCC, 2002: Methodological issues. Scientific and methodological assessment of contributions to climate change. Report of the Expert Meeting, Note by theSecretariat. FCCC/SBSTA/2002/INF. 14.
Ward, D. S. and N. M. Mahowald, 2014: Contributions of developed and developing countries to global climate forcing and surface temperature change. Environmental Research Letters, 9, 074008.10.1088/1748-9326/9/7/07400833f8509e58f077f505c87d5809410301http%3A%2F%2Fwww.ingentaconnect.com%2Fcontent%2Fiop%2Ferl%2F2014%2F00000009%2F00000007%2Fart074008http://www.ingentaconnect.com/content/iop/erl/2014/00000009/00000007/art074008attributable to developing countries is increasing, led by emissions from China and India, and we estimate that this will surpass the contribution from developed countries around year 2030.
Wei, T., Coauthors, 2012: Developed and developing world responsibilities for historical climate change and CO2 mitigation. Proc. Natl. Acad. Sci.USA, 109, 12 911- 12 915.10.1073/pnas.1203282109228262574357037d-261d-4d0d-9bd4-90b3a4edd7a86abdbf3f8aaff13ad34c4b18b969e0c3http%3A%2F%2Fmed.wanfangdata.com.cn%2FPaper%2FDetail%2FPeriodicalPaper_PM22826257refpaperuri:(978778cf505a3acaa3a4e481fb50b5aa)http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM22826257At the United Nations Framework Convention on Climate Change Conference in Cancun, in November 2010, the Heads of State reached an agreement on the aim of limiting the global temperature rise to 2 C relative to preindustrial levels. They recognized that long-term future warming is primarily constrained by cumulative anthropogenic greenhouse gas emissions, that deep cuts in global emissions are required, and that action based on equity must be taken to meet this objective. However, negotiations on emission reduction among countries are increasingly fraught with difficulty, partly because of arguments about the responsibility for the ongoing temperature rise. Simulations with two earth-system models (NCAR/CESM and BNU-ESM) demonstrate that developed countries had contributed about 60-80%, developing countries about 20-40%, to the global temperature rise, upper ocean warming, and sea-ice reduction by 2005. Enacting pledges made at Cancun with continuation to 2100 leads to a reduction in global temperature rise relative to business as usual with a 1/3-2/3 (CESM 33-67%, BNU-ESM 35-65%) contribution from developed and developing countries, respectively. To prevent a temperature rise by 2 C or more in 2100, it is necessary to fill the gap with more ambitious mitigation efforts.
Wei T., W. J. Dong, W. P. Yuan, X. D. Yan, and Y. Guo, 2014: Influence of the carbon cycle on the attribution of responsibility for climate change. Chinese Science Bulletin, 59, 2356- 2362.10.1007/s11434-014-0196-777e35128efb23f814bfd282d1746e876http%3A%2F%2Fwww.cqvip.com%2FQK%2F86894X%2F201419%2F50172452.htmlhttp://www.cnki.com.cn/Article/CJFDTotal-JXTW201419020.htmThe carbon cycle is one of the fundamental climate change issues. Its long-term evolution largely affects the amplitude and trend of human-induced climate change, as well as the formulation and implementation of emission reduction policy and technology for stabilizing the atmospheric CO 2 concentration. Two earth system models incorporating the global carbon cycle, the Community Earth System Model and the Beijing Normal University-Earth System Model, were used to investigate the effect of the carbon cycle on the attribution of the historical responsibility for climate change. The simulations show that when compared with the criterion based on cumulative emissions, the developed (developing) countries' responsibility is reduced (increased) by 602%–1002% using atmospheric CO 2 concentration as the criterion. This discrepancy is attributed to the fact that the developed world contributed approximately 6102%–6802% (6102%–6402%) to the change in global oceanic (terrestrial) carbon sequestration for the period from 1850 to 2005, whereas the developing world contributed approximately 3202%–4902% (3602%–3902%). Under a developed world emissions scenario, the relatively larger uptake of global carbon sinks reduced the developed countries' responsibility for carbon emissions but increased their responsibility for global ocean acidification (6802%). In addition, the large emissions from the developed world reduced the efficiency of the global carbon sinks, which may affect the long-term carbon sequestration and exacerbate global warming in the future. Therefore, it is necessary to further consider the interaction between carbon emissions and the carbon cycle when formulating emission reduction policy.
Wei T., W. J. Dong, B. Y. Wu, S. L. Yang, and Q. Yan, 2015: Influence of recent carbon emissions on the attribution of responsibility for climate change. Chinese Science Bulletin, 60, 674- 680. (in Chinese)10.1360/N972014-009647ea359d8d4ef29f7ac90f4cdd362daf1http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-KXTB201507012.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-KXTB201507012.htmInternational negotiations on carbon emission reduction largely depend on the attribution of historical responsibility for climate change. In recent years, carbon emissions of developing countries have clearly increased because of rapid industrialization and now exceed those of developed countries. However, recent carbon emissions(2006–2011) have not been considered in previous attribution studies. In this study, we investigate the influence of recent carbon emissions on historical responsibilities of developed and developing countries, using a fully coupled global climate–carbon model CESM(Community Earth System Model). The simulations demonstrate that developed(developing) countries contributed about 55%–62%(38%–45%) to global CO2 increase, temperature rise, upper ocean warming, and sea ice reduction by 2011. Compared with results excluding recent carbon emissions, the responsibility of developed(developing) countries is reduced(increased) by 1%–2%. These results indicate that carbon emissions in recent years have little influence on the long-term attribution of historical responsibility. Although recent carbon emissions in developing countries have grown significantly and now exceed those of developed countries, emissions and corresponding responsibility transferred from the developed to developing world through international trade have been ignored. This is a topic that requires further study.
Yan Q., H. J. Wang, O. M. Johannessen, and Z. S. Zhang, 2014: Greenland ice sheet contribution to future global sea level rise based on CMIP5 models. Adv. Atmos. Sci., 31, 8- 16,doi: 10.1007/s00376-013-3002-6.10.1007/s00376-013-3002-64d49239b8aeba55e4002ecd53a261203http%3A%2F%2Flink.springer.com%2F10.1007%2Fs00376-013-3002-6http://d.wanfangdata.com.cn/Periodical_dqkxjz-e201401002.aspxSea level rise(SLR) is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet(GrIS) will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS(SImulation COde for POLythermal Ice Sheets) driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project(CMIP5) to estimate the GrIS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0–16(0–27) cm to global SLR by 2100 under the Representative Concentration Pathways(RCP) 4.5(RCP 8.5) scenarios. The projected SLR increases further to 7–22(7–33) cm with 2×basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm(10 cm and 13 cm with 2×basal sliding) under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.
Zhang Z. Q., J. S. Qu, and J. J. Zeng, 2008: A quantitative comparison and analytical study on the assessment indicators of greenhouse gases emissions. Acta Geographica Sinica, 63, 693- 702. (in Chinese)10.3321/j.issn:0375-5444.2008.07.003807e651e3c50ebcea6858e6f5d3de033http%3A%2F%2Fwww.oalib.com%2Fpaper%2F1564775http://www.oalib.com/paper/1564775Currently the main assessment indicators for GHG emissions include national indicator,per capita indicator,per GDP indicator,and international trade indicator. Based on the GHG emission data from World Resource Institute (WRI),US Energy Information Administration (EIA),and Carbon Dioxide Information Analysis Center(CDIAC),the results of each indictor are calculated for the world and especially for the eight main industrialized countries of US,UK,Canada,Japan,Germany,France,Italy and Russia (G8 Nations),and the five major developing countries of China,Brazil,India,South Africa and Mexico,and their merits and demerits are analyzed. It points out that all these indicators have some limitations. The indicator of Industrialized Accumulative Emission per Capita (IAEC) is identified to evaluate the industrialized historical accumulative emission per capita of every country. IAEC indicator is an equitable indicator for GHG emission assessment,which reflects the economic achievement of GHG emission enjoyed by the current generations in every country and their commitments. The analysis of IAEC indicates that the historical accumulative emissions per capita in industrialized countries such as UK and USA were typically higher than those in the world average level and the developing countries. Emission indicator per capita per unit GDP,consumptive emission indicator and survival emission indicator are also put forward and discussed in the paper.
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PDF downloads: 89 Times
Manuscript received: 16 June 2015
Manuscript accepted: 27 October 2015
1. Chinese Academy of Meteorological Sciences, Beijing 100081
2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Future Earth Research Institute, Beijing Normal University, Zhuhai 519087
3. Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
Manuscript accepted: 2015-10-27
Abstract: One of the key issues in international climate negotiations is the formulation of targets for emissions reduction for all countries based on the principle of "common but differentiated responsibilities". This formulation depends primarily on the quantitative attribution of the responsibilities of developed and developing countries for historical climate change. Using the Commuity Earth System Model (CESM), we estimate the responsibilities of developed countries and developing countries for climatic change from 1850 to 2005 using their carbon dioxide, methane and nitrous oxide emissions. The results indicate that developed countries contribute approximately 53%-61%, and developing countries approximately 39%-47%, to the increase in global air temperature, upper oceanic warming, sea-ice reduction in the NH, and permafrost degradation. In addition, the spatial heterogeneity of these changes from 1850 to 2005 is primarily attributed to the emissions of greenhouse gases (GHGs) in developed countries. Although uncertainties remain in the climate model and the external forcings used, GHG emissions in developed countries are the major contributor to the observed climate system changes in the 20th century.
Humans have changed the composition of Earth's atmosphere, leading to significant climate change over recent centuries (IPCC, 2013). To avoid the serious environmental threat posed by the exponential growth of greenhouse gas emissions, the international community has for 20 years attempted to reduce global carbon emissions through climate negotiations. One of the critical issue for climate negotiations is to differentiate the contributions of different countries to historical climate change, which potentially affects the formulation of emissions reduction programs (UNFCCC, 1997).
Previous studies have estimated a country's contribution to historical climate change as its share of global greenhouse gas (GHG) emissions over a certain period (Rosa et al., 2004; Allen et al., 2009; Ding et al., 2009; He et al., 2009;den Elzen et al., 2013). Using World Resources Institute and U.S. Energy Information Administration data, (Zhang et al., 2008) showed that the G8 countries (the U.S., Canada, Japan, Britain, Germany, France, Italy and Russia) accounted for 61% of the cumulative GHG emissions from 1850 to 2004, and five large developing countries (China, Brazil, India, South Africa and Mexico) accounted for 13%. As indicated by (den Elzen et al., 2013), developed countries and developing countries contributed 51.9% and 48.1% to the global GHG emissions from 1850 to 2010, respectively. Note that the GHG concentration remaining in the atmosphere is directly related to the climate change (Frank et al., 2010; Jones et al., 2013). The atmospheric GHG concentration depends not only on anthropogenic emissions but also on the response of natural sinks/uptake to the changes in the atmospheric composition and climate (Fung et al., 2005; Le Quéré et al., 2009). Therefore, attributing the contributions of countries to global warming based on GHG emissions is insufficient because the emissions lack direct links to climate change (Wei et al., 2014).
To consider the uptake/sink of GHGs along with their relationship with temperature, simple models have been developed to measure national contributions to the global temperature rise due to their GHG emissions (UNFCCC, 2002; Andronova and Schlesinger, 2004; Trudinger and Enting, 2005; Matthews et al., 2009). Based on the original Brazilian model, (den Elzen et al., 1999) showed that developed countries and developing countries should bear responsibility for 54% and 46%, respectively, of the historical contribution to global warming from 1890 to 2000. By considering GHG concentrations and their effects on radiative forcings and changes in global temperature, (Höhne and Blok, 2005) indicated that 60% (40%) of the contribution to climate change from 1750 to 2000 was from developed countries (developing countries). Using MAGICC (Model for the Assessment of Greenhouse Gas Induced Climate Change), (Prather et al., 2009) controlled the errors along with the causal chain of climate change and showed that the GHG emissions from 1990 to 2002 in developed countries led to an increase in the global mean temperature by 0.11 °C 0.03°C in 2003. (Ward and Mahowald, 2014) used the radiative forcing of anthropogenic emissions of long-lived greenhouse gases, ozone precursors, aerosols, and from albedo changes from land cover change, together with a simple climate model, to evaluate country contributions to climate change. Generally, simple models track the causal chain of climate change from human activities to GHG emissions, to radiative forcing and, finally, to global warming. The causal chain includes the basic processes through which anthropogenic GHGs affect climate but lacks a description of the spatial and temporal details of the entire climate system. Therefore, a comprehensive evaluation of the historical contribution to climate change cannot be achieved with simple models.
Current state-of-the-art earth system models, which contain longwave radiative processes of GHGs and complex interactions among different components of the climate system, can overcome certain shortcomings of statistical methods and simple model approaches in attributing national responsibilities for climate change. Matthews et al. (2014) used an intermediate-complexity global climate model UVic ESCM to simulate the change in temperature resulting from observed historical increases in the forcing for each of methane (CH4), nitrous oxide (N2O), and sulfate aerosols, from 1970 to 2005. (Wei et al., 2012) designed numerical experiments with two earth system models and demonstrated that developed countries (developing countries) contributed approximately 60%-80% (20%-40%) to the global temperature rise, upper oceanic warming, and sea-ice reduction, by 2005. However, (Wei et al., 2012) only considered the industrial carbon emissions from different countries and ignored other important GHGs, such as CH4 and N2O. Note that CH4 and N2O account for 14% and 8% of all anthropogenic GHGs emissions, respectively, and their global warming potential (GWP) is 21 times and 310 times the GWP of carbon dioxide (CO2), respectively (IPCC, 1996). Excluding CO2, other GHGs significantly change the relative share of global emissions for many countries (UNFCCC, 2002; den Elzen et al., 2005; den Elzen et al., 2013). Therefore, it is more accurate and more meaningful to estimate the historical responsibilities of countries based on the variations of all of these important GHGs.
In this study, using a state-of-the-art coupled earth system model, we estimate the responsibilities of developed and developing countries for the changes in each component of the climate system from 1850 to 2005. We attempt to provide results by considering the effect of CO2, CH4 and N2O emissions. In addition, we hope that our results provide information to partially resolve the controversial climate negotiations on emissions reduction. The remainder of the paper is organized as follows: Section 2 briefly describes the CESM, the construction of the GHG data, and the experimental setup. Section 3 evaluates the influences of the GHG emissions from different groups of countries on climate system change, obtained by modeling. Finally, section 4 concludes and discusses the likely effect of recent emissions and transferred emissions on the attribution.
2.1. Model description
CESM version 1.0.2 is a fully coupled, global climate model developed at NCAR. It is composed of an atmospheric model (CAM4/CAM5), an ocean model (POP2), a land surface model (CLM4), a sea-ice model (CICE4), and a central coupler component (CPL7). The principal GHGs with longwave radiative effects included in CAM5 are water vapor, CO2, ozone (O3), CH4, N2O, CFC11, and CFC12. CO2 is assumed to be well mixed. The latter four (CH4, N2O, CFC11, and CFC12) are specified at globally uniform surface concentrations. In this study, the horizontal resolution of CAM5 is 1.9°(lat) times 2.5° (lon), with 26 levels in the vertical direction. The horizontal resolution of the ocean component is g16, corresponding to a nominal grid size of 1°, and there are 60 isopycnic vertical layers. Additional information concerning CESM can be found in (Neale et al., 2010) and (Gent et al., 2011). CESM has been proven to be able to capture the majority of characteristics of present-day climate (e.g., Feng et al., 2014; Yan et al., 2014). Specifically, CESM performs well in reproducing the trends of sea-ice extent and ocean heat content changes in recent decades and in capturing the relationship between the decrease in permafrost area and the warming air temperature over the present-day NH permafrost region (Flato et al., 2013; Slater and Lawrence, 2013; Shu et al., 2015).
2.2. Data
We first collected and constructed the CO2, CH4 and N2O emissions datasets from developed and developing countries. Next, we converted the emissions data (units: Tg) to GHG concentrations (units: ppmv), which served as the external forcings of CESM.
2.2.1. Carbon dioxide
Based on gridded industrial carbon emissions (Andres et al., 2013), (Wei et al., 2012) simulated the evolution of the CO2 concentration from 1850 to 2005 under the scenarios of all countries emitting (ALLGHGs), only developed countries emitting (AX1GHGs), and only developing countries emitting (NX1GHGs), using CESM. The simulated CO2 variations, which included the interaction between the varying climate and carbon sinks, matched well with observations, with a correlation coefficient of 0.99. Although simulation biases existed over the last 50 years because of the high climate sensitivity of CESM, they were not critical in the evaluation of the relative contributions (Wei et al., 2012). Therefore, we employ the simulated CO2 concentrations in the three scenarios as the external forcings in this study (Fig. 1a).
Figure 1. Observed (black; supplied by CMIP5) and modeled time series of the annual (a) CO$_2$, (b) CH$_4$ and (c) N$_2$O concentration under the ALLGHGs (red; historical emissions), AX1GHGs (blue; developed world emissions only), and NX1GHGs (green; developing world emissions only) scenarios.
2.2.2. Methane
(Höhne et al., 2011) compiled historical (1890-2005) CH4 and N2O emission datasets with the results from 192 countries or regions for energy, industry and agriculture/waste sectors. We divided the national CH4 emissions into developed and developing country groups and found that CH4 from developing countries, which are consistently higher than those from developed countries from 1890 to 2005, markedly increased with the economic reconstruction occurring since the 1950s. Over the past 15 years, CH4 emissions from developed countries have been greatly reduced, while the rising trend from developing countries has been maintained (figure not shown).
In the original and revised Brazilian proposal (UNFCCC, 1997; den Elzen et al., 1999), the concentration of CH4 is a function of its emissions and is calculated using an exponential decay function with a constant atmospheric lifetime [Eq. (1)]. In a more general formulation, as used in IMAGE (Integrated Model to Assess the Greenhouse Effect) and MAGICC, the concentration of a non-CO2 greenhouse gas follows a mass balance equation. These functions are referred to as the Brazilian model: \begin{equation} \rho_{g}(t)=C_{g}\int_{-\infty}^t\varepsilon_{g}(t')e^{-(t-t')/\tau_{g}}dt' , (1)\end{equation} where subscript g is a specie of gas, ρ g(t) is the atmospheric concentration at time t (ppbv); t' is the variable for time integral; C g is a mass-to-concentration conversion factor and is set equal to 3.8 (ppbv Tg-1), as in Meta-IMAGE/IMAGE; ε g is the annual rate of anthropogenic emissions (Tg yr-1); and τ g is the atmospheric exponential decay time or lifetime (yr), which considers the soil carbon sequestration τ g=τ atm,g+τ soil,g in which τ atm,g is atmospheric sink, τ atm,g=9.08 yr in 1990 and τ soil,g is soil sink, τ soil,g=150 yr (Harvey et al., 1997). The constant lifetime ignores the indirect effect of methane on atmospheric chemistry (such as hydroxyls and tropospheric O3) and the chemical interaction of CH4 with oxidants in the atmosphere, which could lead to a change in the CH4 lifetime by 10%-20% over a historical period (IPCC, 1996). Therefore, we use the historical concentration data to validate the modeling approach and to obtain the value of 7.5 yr for τ atm,g.
Figure 1b shows the observed and calculated CH4 concentration from Eq. (1). The CH4 concentration and its rising trend are overestimated prior to 1970. This result is attributed to the uncertainties in the model parameters, which are suitable for the prediction after 1990 and in the application for the constant lifetime, which neglects the chemical interaction between CH4 and the atmosphere. However, the bias is not critical in the evaluation of the relative contributions. In addition, the CH4 concentration due to the emissions of developing countries is higher than that caused by the emissions of developed countries, and the difference is substantially larger after the 1950s, simultaneous with the post-war reconstruction period.
2.2.3. Nitrous Oxide
The anthropogenic N2O emission data covering 192 countries or regions were also derived from (Höhne et al., 2011). These data, spanning from 1890 to 2005, are the longest time series of N2O emissions currently available. From 1890 to 1990, the N2O emitted by developed countries was slightly higher than that emitted by developing countries. N2O emitted by developing countries shows an obvious linear increasing trend from 1990 to 2005, while this amount is substantially reduced for developed countries (figure not shown).
The Brazilian model can also be used to calculate the concentration of N2O but with different model parameters. However, the gap between the modeled N2O concentration and the historical observation is large and increases with time. In addition, the lifetime of N2O, which is relatively different from the lifetime of CO2 and CH4, is quasi-steady and relatively long (120 years; den Elzen et al., 1999), allowing us to use the curve fitting method to calculate the atmospheric N2O concentration during the historical period. Because the concentration of greenhouse gases in the atmosphere is determined by their long-term emissions, we calculate the atmospheric N2O concentrations with a cubic function [Eq. (2)] and the cumulative emissions of anthropogenic N2O since 1890: \begin{equation} \rho_{g}(t)=a+b1\times E_{g}(t)+b2\times E_{g}^2(t)+b3\times E_{g}^2(t) , (2)\end{equation} where ρ g(t) is the atmospheric concentration at time t (ppbv); E g(t) is the cumulative anthropogenic emissions from 1890 to time t (Tg N2O); and a, b1, b2 and b3 are fitting coefficients with values of 279.888, 0.165, 0.0, and 4.32× 10-7, respectively.
The correlation coefficient between the calculated N2O concentration in the ALLGHGs scenario and the observation is 0.995, at the 99% significance level (Fig 1c). The fitting result is especially close to the observation since the 1920s. In addition, the change in the N2O concentration caused by developed countries is close to that caused by developing countries.
2.3. Experimental design
To examine the historical responsibilities of developed and developing countries, we designed four experiments using CESM under four different emissions scenarios (Table 1). In each experiment, the model used the results of a 351-year preindustrial control run as its initial field and was then integrated over the historical period from 1850 to 2005. The four emissions scenarios we designed are summarized as follows: (1) A00GHGs: anthropogenic GHG (CO2, CH4 and N2O) emissions from all countries were set to zero (considered as the reference scenario)——thus, the concentrations of CO2, CH4 and N2O were maintained at pre-industrial (i.e., 1850) levels; (2) ALLGHGs: global anthropogenic GHG emissions the same as in the 20th century historical experiment in CMIP5 (Taylor et al., 2012); (3) AX1GHGs: anthropogenic GHG emissions were only allowed from developed countries (i.e., Annex I countries); (4) NX1GHGs: anthropogenic GHG emissions were only allowed from developing countries (i.e., non-Annex I countries). The annual concentrations of CO2, CH4 and N2O under these emissions scenarios are shown in Fig. 1. The other forcings, including aerosols, CFC gases, volcanoes and solar irradiance, were maintained the same in each of the experiments.
3. Accounting the contribution to climate system change
3.1. Atmospheric warming
Air temperature is an important indicator reflecting the overall features of the climate system. Figure 2a shows the global mean air temperature anomalies under different emissions scenarios relative to the A00GHGs scenario, revealing that human-induced GHG emissions have led to significant global warming since 1850. However, the magnitudes of warming caused by the emissions from different country groups show substantial differences. The warming trend under the AX1GHGs scenario is similar to that under the ALLGHGs scenario but substantially larger than that under the NX1GHGs scenario since the 1900s. Over the last 20 years of the study period (1986-2005), the gap in the warming trends between the AX1GHGs and NX1GHGs scenarios reduced due to the rapid industrialization of developing countries. Compared with the A00GHGs reference scenario, the global annual mean temperature averaged over 1986-2005 increased by 0.93°C, 0.71°C and 0.56°C under the ALLGHGs, AX1GHGs and NX1GHGs scenarios, respectively. We use the "normalized proportional" method (Höhne et al., 2011; Wei et al., 2012) to obtain the relative contributions from developed and developing countries. The results show that 56% of the contribution to the rising air temperature is from the emissions of developed countries, and 44% is from the emissions of developing countries. The gap in the contribution rates between the two country groups is smaller than the result from (Wei et al., 2012), in which only CO2 emissions were considered. Therefore, considering the influence of other important GHGs (i.e., CH4 and N2O) could increase (decrease) the contribution of developing (developed) countries. And this result is similar with those of some previous studies (Höhne et al., 2011; den Elzen et al., 2013; Matthews et al., 2014; Ward and Mahowald, 2014).
Figure 2. Differences between the air temperature in the ALLGHGs, AX1GHGs and NX1GHGs scenarios and the A00GHGs reference scenario. (a) Time series of global mean air temperature. The thin dashed lines are the annual values, and the thick solid lines are the 11-year running values. Simulated patterns of air temperature under the (b) ALLGHGs, (c) AX1GHGs and (d) NX1GHGs scenarios relative to the A00GHGs scenario from 1956 to 2005. Units: $^\circ$C.
Figure 3. Similar to Fig. 2 but for the time series of heat content in the global upper (0-700 m) ocean (units: $\times10^22$ J) and latitude-depth section of the oceanic potential temperature (unit: $^\circ$C).
Figure 4. Similar to Fig. 2 but for the time series of Arctic sea-ice extent (units: $\times 10^6$ km$^2$) and the patterns of Arctic sea-ice fraction (units: %) in September.
Due to the spatial heterogeneity of climate change, we further investigate the spatial patterns of temperature changes relative to the A00GHGs scenario. Figure 2b shows that the largest warming due to the increased GHGs is primarily located in the Arctic regions, with little change in the temperature over the oceans at midlatitudes. The spatial distribution of the temperature trends under the AX1GHGs scenario is very similar to that under the ALLGHGs scenario but differs with that under the NX1GHGs scenario (Figs. 2c and d). At northern high latitudes, the warming magnitude under the NX1GHGs scenario is 1°C smaller compared with that under the ALLGHGs scenario. In addition, the temperature changes over Oceania are more sensitive to the emissions scenarios. Generally, GHGs emitted by developed countries contributed 52%-61% of the warming in each continent (Table 2).
3.2. Oceanic warming
Ocean warming dominates the increase in the energy stored in the climate system, accounting for more than 90% of the energy accumulated from 1971 to 2010, and more than 60% of the net energy increase in the climate system is stored in the upper ocean (0-700 m) (IPCC, 2013). Figure 3a shows the simulated heat content in the global upper ocean under different scenarios relative to the A00GHGs scenario. The time series shows an increasing trend of heat content in the global ocean in response to GHG emissions. It appears that the differences in the ocean content among the different scenarios are more noticeable than the differences in the air temperature. The warming trend under the NX1GHGs scenario is substantially smaller than that under the AX1GHGs scenario that is consistent with that under the ALLGHGs scenario. From 1986 to 2005, the heat content in the upper ocean under the ALLGHGs, AX1GHGs and NX1GHGs scenarios relative to the A00GHGs scenario is 24.57× 1022 J, 22.22× 1022 J and 14.56× 1022 J, respectively. Using the normalized proportional approach, 61% (39%) of the simulated upper ocean warming is attributed to developed countries (developing countries).
As shown in Figures 3b-d, the majority of the ocean regions experiences significant warming because of increasing GHGs. The maximum warming appears in the global upper ocean, and the largest warming depth appears in the North Atlantic Ocean. Notably, the warming amplitude in each region under the AX1GHGs scenario is larger than that under the NX1GHGs scenario, especially at the surface of the global ocean and the North Atlantic Ocean. Thus, the spatial heterogeneity of the global ocean warming primarily responds to the GHG emissions of developed countries.
3.3. Sea-ice reduction
Observations have shown that one of the most significant features of global warming is the accelerated reduction of Arctic sea ice. From 1979 to 2012, the Arctic sea-ice extent decreased at a rate of 3.5% (10 yr)-1-4.1% (10 yr)-1 [or 0.45-0.51 million km2 (10 yr)-1], with the most significant decrease occurring in summer (IPCC, 2013). From the relative changes in the Arctic sea-ice extent in Fig. 4a, we can see that the increasing GHGs have led to a reduction in Arctic sea ice since 1850, and the decreasing rate became faster after the 1970s. Compared with the A00GHGs scenario, the Arctic sea-ice extent from 1986 to 2005 under the ALLGHGs, AX1GHGs and NX1GHGs scenarios decreased by 2.29× 106 km2, 1.61× 106 km2 and 1.44× 106 km2, respectively. Using the normalized proportional approach, the contribution rate to the decrease in Arctic sea-ice extent is 53% and 47% in developed and developing countries, respectively. The gap in the contribution rate between the two country groups is smaller than the results for the air temperature and oceanic heat content. This result may be because, aside from anthropogenic GHGs, the change in the sea-ice extent is also affected by the natural variability of large-scale atmospheric circulation (e.g., Arctic Oscillation) (Rigor et al., 2002).
Figures 4b-d show the patterns of Arctic sea-ice extent in September from 1956 to 2005 simulated by CESM. Because of the increasing GHGs, the sea ice in most of the Arctic regions, especially in the East Siberian Sea and Chukchi Sea, decreased significantly. The magnitude of sea-ice reduction in the Chukchi Sea under the AX1GHGs scenario is similar to that under the ALLGHGs scenario but larger than that under the ALLGHGs scenario. In the East Siberian Sea, however, the change in the sea-ice extent in the NX1GHGs case is larger than that in the AX1GHGs case.
3.4. Permafrost degradation
In terms of area extent, frozen ground is the largest component of the cryosphere (IPCC, 2013). The permafrost temperature regime is a sensitive indicator of decadal to centennial climatic variability (Lachenbruch and Marshall, 1986; Osterkamp, 2005). Observations have shown that the permafrost has degenerated, and the thickness of the active layer over the permafrost has increased in most regions since 1975 (IPCC, 2013). Figure 5a shows that GHGs have led to a significant decrease in surface (0-4.7 m) permafrost since the industrial revolution, and the degeneration rate is especially high after the 1960s. Because the sensitivity of permafrost to anthropogenic GHGs is relatively high, the magnitudes of its degeneration caused by emissions from different country groups show large differences. The decreasing trend of the permafrost area under the AX1GHGs scenario is substantially larger than that under the NX1GHGs scenario since the 1900s. From 1986 to 2005, the surface permafrost area in the ALLGHGs, AX1GHGs and NX1GHGs scenarios decreased by 2.53× 106 km2, 2.05× 106 km2 and 1.61× 106 km2, respectively, compared with the A00GHGs scenario. Using the normalized proportional approach, developed and developing countries contribute 56% and 44% to global permafrost degeneration, respectively.
The thickness of the active layer over permafrost increases with the GHG emissions (Figs. 5b-d). In the Stanovoy Mountains and Alaska Mountains, the incrassation of the active layer is substantially more significant. The spatial distribution of the change in the active layer over the permafrost under the AX1GHGs scenario is very similar to that under the ALLGHGs scenario, while it differs to that under the NX1GHGs scenario. In the regions along 60°N, especially in the Stanovoy Mountains and central Canada areas, which are sensitive regions to human-induced GHGs, the difference in the permafrost degeneration between the AX1GHGs and NX1GHGs scenarios is even larger.
4. Conclusions and discussion
The key issue in international climate negotiations is the formulation of targets for emissions reduction for all countries based on the principle of "common but differentiated responsibilities" (UNFCCC, 1997). This formulation depends primarily on the quantitative attribution of the responsibilities of developed and developing countries for historical climate change. In this study, a state-of-the-art model, CESM, was used to attribute the responsibilities of developed/developing countries for climate change due to their GHG emissions (i.e., CO2, CH4 and N2O). Simulations with CESM demonstrate the following:
(1) The contribution rate to the rising air temperature since pre-industrial times is 56% from the GHGs (i.e., CO2, CH4 and N2O) emitted by developed countries and 44% from that emitted by developing countries. Different regions show various sensitivities to the emissions scenarios. GHGs emitted by developed countries are the major driver (52%-61%) for the warming in each continent and for the global warming patterns.
(2) CESM attributes 61% of the contribution to global ocean warming to developed countries and 39% to developing countries. In most of the regions, especially at the surface of the global ocean and the North Atlantic Ocean, which are the most sensitive regions to GHGs, the GHG emissions from developed countries exert a greater effect on warming.
(3) The contributions from developed and developing countries to the decrease in Arctic sea-ice extent are 53% and 47%, respectively. Because of the increasing GHGs, the sea ice in the East Siberian Sea and Chukchi Sea has decreased significantly. However, the sea-ice extent, which is also affected by the natural variability of large-scale atmospheric circulation, shows various sensitivities to GHG emissions scenarios.
(4) For the change in global permafrost degeneration, the contributions of developed and developing countries are 56% and 44%, respectively. Developed countries are the major contributor to the incrassation of the active layer over permafrost in the regions along 60°N, especially in the Stanovoy Mountains and central Canada areas.
Figure 5. Similar to Fig. 2 but for the time series of surface (0-4.7 m) permafrost area (units: $\times 10^6$ km$^2$) and the patterns of the active layer over the permafrost (units: m).
The simulation results presented in this study show that the total relative contribution to climate change is 53%-61% from developed countries and 39%-47% from developing countries, from 1850 to 2005. Based on statistical cumulative GHG emissions, (den Elzen et al., 2013) calculated the relative contribution to be 54.1% from developed countries and 45.9% from developing countries, from 1850 to 2000. The discrepancy between the two studies may be because of the different metrics applied. (den Elzen et al., 2013) compared cumulative emissions of CO2-equivalents, whereas we are comparing climate variables. (Liu et al., 2015) argued that China emitted 2.9 GtC less than previously thought over the period 2000 to 2013. However, the amount of overestimated carbon emissions is ignorable compared to the difference in cumulative carbon emissions (∼67.1 GtC) between developed and developing countries from 1850 to 2013, and hence has limited influence in attributing historical responsibility for developed and developing countries. As a preliminary step, we investigated the relative contribution of developed and developing countries in this study. To provide a more useful reference for climate negotiations and the formulation of emissions reduction policy, assessments of individual countries' responsibilities for climate change is urgently needed.
In recent years, the GHG emissions of developing countries have continuously increased due to rapid industrialization and have even exceeded the emissions of developed countries. This result challenges previous attribution studies that have excluded recent carbon emissions. A recent study demonstrated that carbon emissions from 2006 to 2011 that accounted for the largest proportion of GHGs have a limited influence (1%-2%) on the attribution of historical contributions from developed and developing countries (Wei et al., 2015). (den Elzen et al., 2013) found that the contribution of developed countries to global GHGs emissions was approximately 54.1% (51.9%) during the period 1850-2010 (1850-2000). Taking into account changes in GHGs, ozone precursors, aerosols and land cover, (Ward and Mahowald, 2014) pointed out that developed countries were the major contributor to observed temperature changes during 1850-2010. The aforementioned results indicate that the rapidly increasing GHGs emissions from developing countries in recent years do not significantly alter the developed/developing countries contribution to long-term climate change.
Additionally, throughout the second half of the 20th century, developed economies effectively exported their carbon emissions through their imports of manufactured products from developing countries (Davis et al., 2011; Peters et al., 2011). The transferred carbon emissions and the contributions from the developed world to the developing world through international trade have been largely ignored. Therefore, the influence of transferred emissions on the attribution of historical contribution must be investigated to partially solve the disputes in climate negotiations.