China's role in attaining the global 2°C target

In the recent climate change negotiations it was declared that the increase in global temperature should be kept below 2°C by 2100, relative to pre-industrial levels. China's CO₂ emissions from energy and cement processes already account for nearly 24% of global emissions, a trend that is expected to keep increasing. Thus the role of China in global GHG mitigation is crucial. A scenario analysis of China's CO₂ emissions is presented here and the feasibility of China reaching a low-carbon scenario is discussed. The results suggest that recent and continued technological progress will make it possible for China to limit its CO₂ emissions and for these emissions to peak before 2025 and therefore that the global 2°C target can be achieved.

Policy relevance

In signing the Copenhagen Accord, China agreed to the global 2°C target. Results from this article could be used to justify low-carbon development policies and negotiations. While many still doubt the feasibility of a low-carbon pathway to support the global 2°C target, the results suggest that such a pathway can be realistically achieved. This conclusion should increase confidence and guide the policy framework further to make possible China's low-carbon development. Related policies and measures, such as renewable energy development, energy efficiency, economic structure optimization, technology innovation, low-carbon investment, and carbon capture and storage (CCS) development, should be further enhanced. Furthermore, China can play a larger role in the international negotiations process. In the global context, the 2°C target could be reaffirmed and a global regime on an emissions mitigation protocol could be framed with countries’ emissions target up to 2050.     

The impacts avoided with a 1.5 °C climate target: a global and regional assessment

The 2015 Paris Agreement commits countries to pursue efforts to limit the increase in global mean temperature to 1.5 °C above pre-industrial levels. We assess the consequences of achieving this target in 2100 for the impacts that are avoided, using several indicators of impact (exposure to drought, river flooding, heat waves and demands for heating and cooling energy). The proportion of impacts that are avoided is not simply equal to the proportional reduction in temperature. At the global scale, the median proportion of projected impacts avoided by the 1.5 °C target relative to a rise of 4 °C ranges between 62 and 95% across sectors: the greatest reduction is for heat wave impacts. The 1.5 °C target results in impacts that would be between 27 and 62% lower than with the 2 °C target. For each indicator, there are differences in the proportions of impacts avoided between regions depending on exposure and the regional changes in climate (particularly precipitation). Uncertainty in the proportion of impacts that are avoided for a specific sector depends on the range in the shape of the relationship between global temperature change and impact, and this varies between sectors.     

Existing infrastructure and the 2°C target

To clarify the link between existing infrastructure legacy and the 2°C target, we extend the work of Davis et al. (Science 329:1330–1333, 2010) by introducing non-CO₂ greenhouse gases and the inertia in transportation-needs drivers. We conclude that climate policies able to maintain climate change below 2°C cannot disregard existing infrastructure.     

Assessing the strength of regional changes in near-surface climate associated with a global warming of 2°C

In this study, the strength of the regional changes in near-surface climate associated with a global warming of 2°C with respect to pre-industrial times is assessed, distinguishing between 26 different regions. Also, the strength of these regional climate changes is compared to the strength of the respective changes associated with a markedly stronger global warming of 4.5°C. The magnitude of the regional changes in climate is estimated by means of a normalized regional climate change index, which considers changes in the mean as well as changes in the interannual variability of both near-surface temperature and precipitation. The study is based on two sets of four ensemble simulations with the ECHAM5/MPI-OM coupled climate model, each starting from different initial conditions. In one set of simulations (1860–2200), the greenhouse gas concentrations and sulphate aerosol load have been prescribed according to observations until 2000 and according to the SRES A1B scenario after 2000. In the other set of simulations (2020–2200), the greenhouse gas concentrations and sulphate aerosol load have been prescribed in such a way that the simulated global warming does not exceed 2°C with respect to pre-industrial times. The study reveals the strongest changes in near-surface climate in the same regions for both scenarios, i.e., the Sahara, Northern Australia, Southern Australia and Amazonia. The regions with the weakest changes in near-surface climate, on the other hand, vary somewhat between the two scenarios except for Western North America and Southern South America, where both scenarios show rather weak changes. The comparison between the magnitude of the regional changes in near-surface climate for the two scenarios reveals relatively strong changes in the 2°C-stabilization scenario at high northern latitudes, i.e., Northeastern Europe, Alaska and Greenland, and in Amazonia. Relatively weak regional climate changes in this scenario, on the other hand, are found for Eastern Asia, Central America, Central South America and Southern South America. The ratios between the regional changes in the near-surface climate for the two scenarios vary considerably between different regions. This illustrates a limitation of obtaining regional changes in near-surface climate associated with a particular scenario by means of scaling the regional changes obtained from a widely used “standard” scenario with the ratio of the changes in the global mean temperature projected by these two scenarios.     

China’s future emission reduction challenge and implications for global climate policy

In December 2015, China joined 190 plus nations at Paris in committing to the goal of limiting the rise in global average temperature to ‘well below’ 2°C. Carbon budget analysis indicates that goal will require not only that the European Union and US reduce their emissions by greater than 80% by 2050, but that China at least comes close to doing so as well, if any budget is to be left over for the rest of the world (RoW). Given that RoW emissions are, and will come from, low-income and emerging nations, China’s emission reduction potential is of no small consequence. In this paper, we use the Kaya identity to back out changes in the drivers of CO₂ emissions, including gross domestic product (GDP), energy intensity (E/GDP) and the carbon content of energy (C/E), the latter two calculated to be consistent with China’s long-term GDP growth rate forecasts and specified 2050 CO₂ emission reduction targets. Our results suggest that even achieving China’s highly optimistic renewable energy targets will be very far from sufficient to reduce China’s CO₂ emissions from 9.1?Gt it emitted in 2015 to much below 3?Gt by 2050. Even reducing its emissions to 5?Gt will be challenging, yet this falls far short of what is needed if the world is to meet its ‘well below’ 2°C commitment.

Key policy insights

• Under the Paris Agreement there is great pressure on China to very substantially reduce its emissions by 2050.

• While China has attached great importance to renewables and nuclear energy development, even achieving the most optimistic targets would not be sufficient to reduce China’s emissions from 9.1?Gt in 2015 to much below 3?Gt by 2050.

• China’s emission reduction potential falls far short of what is needed if the world is to meet its Paris ‘well below’ 2°C commitment, even if the EU and US reduce their emissions to zero by 2050.

• Emission cuts consistent with the Paris Agreement will require that China and the world give much greater weight to advancing research and development of scalable low-, zero- and negative-carbon sources and technologies.

     

Intensification of seasonal extremes given a 2°C global warming target

Current international efforts to reduce greenhouse gas emissions and limit human-induced global-mean near-surface temperature increases to 2°C, relative to the pre-industrial era, are intended to avoid possibly significant and dangerous impacts to physical, biological, and socio-economic systems. However, it is unknown how these various systems will respond to such a temperature increase because their relevant spatial scales are much different than those represented by numerical global climate models—the standard tool for climate change studies. This deficiency can be addressed by using higher-resolution regional climate models, but at great computational expense. The research presented here seeks to determine how a 2°C global-mean temperature increase might change the frequency of seasonal temperature extremes, both in the United States and around the globe, without necessarily resorting to these computationally-intensive model experiments. Results indicate that in many locations the regional temperature increases that accompany a 2°C increase in global mean temperatures are significantly larger than the interannual-to-decadal variations in seasonal-mean temperatures; in these locations a 2°C global mean temperature increase results in seasonal-mean temperatures that consistently exceed the most extreme values experienced during the second half of the 20th Century. Further, results indicate that many tropical regions, despite having relatively modest overall temperature increases, will have the most substantial increase in number of hot extremes. These results highlight that extremes very well could become the norm, even given the 2°C temperature increase target.     

Uncertainty in the 2°C warming threshold related to climate sensitivity and climate feedback

Climate sensitivity is an important index that measures the relationship between the increase in greenhouse gases and the magnitude of global warming. Uncertainties in climate change projection and climate modeling are mostly related to the climate sensitivity. The climate sensitivities of coupled climate models determine the magnitudes of the projected global warming. In this paper, the authors thoroughly review the literature on climate sensitivity, and discuss issues related to climate feedback processes and the methods used in estimating the equilibrium climate sensitivity and transient climate response (TCR), including the TCR to cumulative CO₂ emissions. After presenting a summary of the sources that affect the uncertainty of climate sensitivity, the impact of climate sensitivity on climate change projection is discussed by addressing the uncertainties in 2°C warming. Challenges that call for further investigation in the research community, in particular the Chinese community, are discussed.     

Emission metrics under the 2 °C climate stabilization target

In multi-gas climate policies such as the Kyoto Protocol one has to decide how to compare the emissions of different greenhouse gases. The choice of metric could have significant implications for mitigation priorities considered under the prospective negotiations for climate mitigation agreements. Several metrics have been proposed for this task with the Global Warming Potential (GWP) being the most common. However, these metrics have not been systematically compared to each other in the context of the 2 °C climate stabilization target. Based on a single unified modeling framework, we demonstrate that metric values span a wide range, depending on the metric structure and the treatment of the time dimension. Our finding confirms the basic salient point that metrics designed to represent different aspects of the climate and socio-economic system behave differently. Our result also reflects a complex interface between science and policy surrounding metrics. Thus, it is important to select or design a metric suitable for climate stabilization based on an interaction among practitioners, policymakers, and scientists.     

Near-term increase in frequency of seasonal temperature extremes prior to the 2°C global warming target

Given current international efforts to reduce greenhouse gas emissions and limit human-induced global-mean near-surface temperature increases to 2°C, relative to the pre-industrial era, we seek to determine the impact such a temperature increase might have upon the frequency of seasonal-mean temperature extremes; further we seek to determine what global-mean temperature increase would prevent extreme temperature values from becoming the norm. Results indicate that given a 2°C global mean temperature increase it is expected that for 70–80% of the land surface maximum seasonal-mean temperatures will exceed historical extremes (as determined from the 95th percentile threshold value over the second half of the 20th Century) in at least half of all years, i.e. the current historical extreme values will effectively become the norm. Many regions of the globe—including much of Africa, the southeastern and central portions of Asia, Indonesia, and the Amazon—will reach this point given the “committed” future global-mean temperature increase of 0.6°C (1.4°C relative to the pre-industrial era) and 50% of the land surface will reach it given a future global-mean temperature increase of between 0.8 and 0.95°C (1.6–1.75°C relative to the pre-industrial era). These results suggest substantial fractions of the globe could experience seasonal-mean temperature extremes with high regularity, even if the global-mean temperature increase remains below the 2°C target.     

Why are climate policies of the present decade so crucial for keeping the 2 °C target credible?

Decision-makers have confirmed the long term objective of preventing a temperature increase greater than 2 °C. This paper aims at appraising by means of a cost-benefit analysis whether decision makers’ commitment to meet the 2 °C objective is credible or not. Within the framework of a cost-benefit type integrated assessment model, we consider that the economy faces climate damages with a threshold at 2 °C. We run the model for a broad set of scenarios accounting for the diversity of “worldviews” in the climate debate. For a significant share of scenarios we observe that it is considered optimal to exceed the threshold. Among those “non-compliers” we discriminate ”involuntary non-compliers” who cannot avoid the exceedance due to physical constraint from ”deliberate compliers” for whom the exceedance results from a deliberate costs-benefit analysis. A second result is that the later mitigation efforts begin, the more difficult it becomes to prevent the exceedance. In particular, the number of ”deliberate non-compliers” dramatically increases if mitigation efforts do not start by 2020, and the influx of involuntary non-compliers become overwhelming f efforts are delayed to 2040. In light of these results we argue that the window of opportunity for reaching the 2 °C objective with a credible chance of success is rapidly closing during the present decade. Further delay in finding a climate agreement critically undermines the credibility of the objective.     

Does the model regional bias affect the projected regional climate change? An analysis of global model projections

An analysis is presented of the dependence of the regional temperature and precipitation change signal on systematic regional biases in global climate change projections. The CMIP3 multi-model ensemble is analyzed over 26 land regions and for the A1B greenhouse gas emission scenario. For temperature, the model regional bias has a negligible effect on the projected regional change. For precipitation, a significant correlation between change and bias is found in about 30% of the seasonal/regional cases analyzed, covering a wide range of different climate regimes. For these cases, a performance-based selection of models in producing climate change scenarios can affect the resulting change estimate, and it is noted that a minimum of four to five models is needed to obtain robust precipitation change estimates. In a number of cases, models with largely different precipitation biases can still produce changes of consistent sign. Overall, it is assessed that in the present generation of models the regional bias does not appear to be a dominant factor in determining the simulated regional change in the majority of cases.     

Sharing the reduction effort to limit global warming to 2°C

In order to stabilize long-term greenhouse gas concentrations at 450 ppm CO₂-eq or lower, developed countries as a group should reduce emissions by 25–40% below 1990 levels by 2020, while developing countries' emissions need to be reduced by around 15–30%, relative to their baseline levels, according to the IPCC and our earlier work. This study examines 19 other studies on the emission reductions attributed to the developed and developing countries for meeting a 450 ppm target. These studies considered different allocation approaches, according to equity principles. The effect of the assumed global emissions cap in these studies is analysed. For developed countries, the original reduction range of 25–40% by 2020 is still within the average range of all studies, but does not cover it completely. Comparing the studies shows that assuming a global emissions cap of 5–15% above 1990 levels by 2020 generally leads to more stringent reduction targets than when a global emissions cap of 20–30% above 1990 levels is assumed. For developing countries, the reduction range of 15–30% below their baseline levels by 2020 corresponds to an increase on the 1990 level from 70% (about the 2006 level) to 120%. Reducing deforestation emissions by 50% below baseline levels by 2020 may relax the emission reductions for either group of countries; for developing countries by about 7% or for developed countries by about 15% (but not for both).     

Evaluating climate change at the Croatian Adriatic from observations and regional climate models’ simulations

The 2m temperature (T2m) and precipitation from five regional climate models (RCMs), which participated in the ENSEMBLES project and were integrated at a 25-km horizontal resolution, are compared with observed climatological data from 13 stations located in the Croatian coastal zone. The twentieth century climate was simulated by forcing RCMs with identical boundary conditions from the ERA-40 reanalysis and the ECHAM5/MPI-OM global climate model (GCM); climate change in the twenty-first century is based on the A1B scenario and assessed from the GCM-forced RCMs’ integrations. When forced by ERA-40, most RCMs exhibit cold bias in winter which contributes to an overestimation of the T2m annual cycle amplitude and the errors in interannual variability are in all RCMs smaller than those in the climatological mean. All models underestimate observed warming trends in the period 1951–2010. The largest precipitation biases coincide with locations/seasons with small observed amounts but large precipitation amounts near high orography are relatively well reproduced. When forced by the same GCM all RCMs exhibit a warming in the cold half-year and a cooling (or weak warming) in the warm period, implying a strong impact of GCM boundary forcing. The future eastern Adriatic climate is characterised by a warming, up to +5 °C towards the end of the twenty-first century; for precipitation, no clear signal is evident in the first half of the twenty-first century, but a reduction in precipitation during summer prevails in the second half. It is argued that land-sea contrast and complex coastal configuration of the Croatian coast, i.e. multitude of island and well indented coastline, have a major impact on small-scale variability. Orography plays important role only at small number of coastal locations. We hypothesise that the parameterisations related to land surface processes and soil hydrology have relatively stronger impact on variability than orography at those locations that include a relatively large fraction of land (most coastal stations), but affecting less strongly locations at the Adriatic islands.     

Distributive justice in global climate finance – Recipients’ climate vulnerability and the allocation of climate funds

The ‘climate justice’ lens is increasingly being used in framing discussions and debates on global climate finance. A variant of such justice – distributive justice – emphasises recipient countries’ vulnerability to be an important consideration in funding allocation. The extent to which this principle is pursued in practice has been of widespread and ongoing concerns. Empirical evidence in this regard however remains inadequate and methodologically weak. This research examined the effect of recipients’ climate vulnerability on the allocation of climate funds by controlling for other commonly-identified determinants. A dynamic panel regression method based on Generalised Method of Moments (GMM) was used on a longitudinal dataset, containing approved funds for more than 100,000 projects covering three areas of climate action (mitigation, adaptation, and overlap) in 133 countries over two decades (2000–2018). Findings indicated a non-significant effect of recipients’ vulnerability on mitigation funding, but significant positive effects on adaptation and overlap fundings. ‘Most vulnerable’ countries were likely to receive higher amounts of these two types of funding than the ‘least vulnerable’ countries. All these provided evidence of distributive justice. However, the relationship between vulnerability and funding was parabolic, suggesting ‘moderately vulnerable’ countries likely to receive more funding than the ‘most vulnerable’ countries. Whilst, for mitigation funding, this observation was not a reason for concern, for adaptation and overlap fundings this was not in complete harmony with distributive justice. Paradoxically, countries with better investment readiness were likely to receive more adaptation and overlap funds. In discordance with distributive justice, countries within the Sub-Saharan Africa and South Asia regions, despite their higher climatic vulnerabilities, were likely to receive significantly less adaptation and overlap fundings. Effects of vulnerability were persistent, and past funding had significant effects on current funding. These, coupled with the impact of readiness, suggested a probable Low Funding Trap for the world’s most vulnerable countries. The overarching conclusion is that, although positive changes have occurred since the 2015 Paris Agreement, considerable challenges to distributive justice remain. Significant data and methodological challenges encountered in the research and their implications are also discussed.     

Projected changes in summer water vapor transport over East Asia under the 1.5°C and 2.0°C global warming targets

水汽输送的变化对于降水的变化有重要贡献。基于优选的13个CIV1IP5模式发现:RCP4.5和RCP8.5排放情景下,1.5°C和2.0°C增暖时东亚夏季水汽输送均加强,且2.0°C增暖时模式间一致性更好;水汽含量的增加对东亚南部和北部水汽输送的加强均有贡献,东亚南部水汽输送的加强也与低层环流的加强相联系。0.5°C额外增暖(1.5°C和2.0°C增暖间比较)时,两种排放情景下水汽输送的变化在我国南海与东北地区存在差异,使得两个地区降水变化存在差异;水汽输送的变化与低层环流的变化关系密切,且模式间一致性相对低。     

Governing-by-aspiration? Assessing the nature and implications of including negative emission technologies (NETs) in country long-term climate strategies

In order to address the pressing challenge of climate change, countries are now submitting long-term climate strategies to the United Nations Framework Convention on Climate Change (UNFCCC) process. These strategies include within them potential future use of ‘negative emissions technologies’ (NETs). NETs are interventions that remove carbon from the atmosphere, ranging from large-scale terrestrial carbon sequestration in forests, wetlands and soils, to use of carbon capture and storage technologies. We assess here how NETs are discussed in 29 long-term climate strategies, in order to ascertain the risk that including the promise of future NETs may delay the taking of short-term mitigation actions. Our analysis shows that almost all countries plan to rely on NETs, particularly enhanced use of natural carbon sinks, even as a wide array of challenges and trade-offs in doing so are highlighted. Many strategies call for improved accounting systems and market incentives in realizing future NETs. While no strategy explicitly suggests that NETs can be a substitute for short-term mitigation, most estimate substantial potential for future use of NETs even in the face of acknowledged uncertainties. This, we suggest, may have the consequence of resulting in what we describe here as ‘a spiral of delay’ characterized by the promise of future NET options juxtaposed with the simultaneous uncertainty around these future options. Our analysis highlights that this inter-connected delaying dynamic may be intrinsic to what we term ‘governing-by-aspiration’ within global climate politics, wherein the voicing of lofty future ambition risks replacing current action and accountability.     

The new national climate change documents of Mexico: what do the regional climate change scenarios represent?

This paper presents a review of the methodology applied for generating the regional climate change scenarios utilized in important National Documents of Mexico, such as the Fourth National Communication to the United Nations Framework Convention on Climate Change, the Fourth National Report to the Convention on Biological Diversity and The Economics of Climate Change in Mexico. It is shown that these regional climate change scenarios, which are one of the main inputs to support the assessments presented in these documents, are an example of the erroneous use of statistical downscaling techniques. The arguments presented here imply that the work based on such scenarios should be revised and therefore, these documents are inadequate for supporting national decision- making.     

An atmosphere–ocean regional climate model for the Mediterranean area: assessment of a present climate simulation

We present an atmosphere–ocean regional climate model for the Mediterranean basin, called the PROTHEUS system, composed by the regional climate model RegCM3 as the atmospheric component and by a regional configuration of the MITgcm model as the oceanic component. The model is applied to an area encompassing the Mediterranean Sea and compared to a stand-alone version of its atmospheric component. An assessment of the model performances is done by using available observational datasets. Despite a persistent bias, the PROTHEUS system is able to capture the inter-annual variability of seasonal sea surface temperature (SST) and also the fine scale spatio-temporal evolution of observed SST anomalies, with spatial correlation as high as 0.7 during summer. The close inspection of a 10-day strong wind event during the summer of 2000 proves the capability of the PROTHEUS system to correctly describe the daily evolution of SST under strong air–sea interaction conditions. As a consequence of the model’s skill in reproducing observed SST and wind fields, we expect a reliable estimation of air–sea fluxes. The model skill in reproducing climatological land surface fields is in line with that of state of the art regional climate models.