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Most deliberations on climate policy are based on a mitigation response that assumes a gradually increasing reduction over time. However, situations may occur where a more urgent response is needed. A key question for climate policy in general, but even more in the case a rapid response is needed, is: what are the characteristic response times of the response options, such as rapid mitigation or solar radiation management (SRM)? This paper explores this issue, which has not received a lot of attention yet, by looking into the role of both societal and physical response times. For mitigation, technological and economic inertia clearly limit reduction rates with considerable uncertainty corresponding to political inertia and societies’ ability to organize rapid mitigation action at what costs. The paper looks into a rapid emission reductions of 4–6 % annually. Reduction rates at the top end of this range (up to 6 %) could effectively reduce climate change, but only with a noticeable delay. Temperatures could be above those in the year of policy introduction for more than 70 years, with unknown consequences of overshoot. A strategy based on SRM is shown to have much shorter response times (up to decades), but introduces an important element of risk, such as ocean acidification and the risk of extreme temperature shifts in case action is halted. Above all, the paper highlights the role of response times in designing effective policy strategies implying that a better understanding of these crucial factors is required. [ABSTRACT FROM AUTHOR]

Abstract: Scenarios are used to explore the consequences of different adaptation and mitigation strategies under uncertainty. In this paper, two scenarios are used to explore developments with (1) no mitigation leading to an increase of global mean temperature of 4°C by 2100 and (2) an ambitious mitigation strategy leading to 2°C increase by 2100. For the second scenario, uncertainties in the climate system imply that a global mean temperature increase of 3°C or more cannot be ruled out. Our analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but adaptation will still be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which, from a global and purely monetary perspective, adaptation (up to 2100) seems more effective than mitigation. From the perspective of poorer and small island countries, however, stringent mitigation is necessary to keep risks at manageable levels. For agriculture, only a scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts. [Copyright &y& Elsevier]

The relationship between long-term climate goals and short/medium-term emission targets forms crucial information for the design of international climate policy. Since IPCC's 4th Assessment Report (AR4), a large number of new scenario studies have been published. This paper reviews this new literature and finds that there is more flexibility in the timing of short-term emission reductions compared to the earlier scenarios assessed by the AR4. For instance, the current literature suggests that a peak of emissions in 2020 and even 2030 would be consistent with limiting temperature change to about 2°C in the long term. The timing when emissions peak depends on whether negative emissions in the long-term can be achieved. The recent scenarios further indicate that global emissions by 2050 should be 40-80% below 2000 levels. Above all, the paper argues that there is no clear, single 'law' that would directly determine the required emissions levels in 2020, but that instead policy-makers need to consider trade-offs between the likelihood of achieving long-term targets, the short-term costs, and their expectation with respect to future technologies (and their possible failure). The higher flexibility might be important in finding acceptable agreements on international climate policy. [ABSTRACT FROM AUTHOR]

Long-term scenarios developed by integrated assessment models are used in climate research to provide an indication of plausible long-term emissions of greenhouse gases and other radiatively active substances based on developments in the global energy system, land-use and the emissions associated with these systems. The phenomena that determine these long-term developments (several decades or even centuries) are very different than those that operate on a shorter time-scales (a few years). Nevertheless, in the literature, we still often find direct comparisons between short-term observations and long-term developments that do not take into account the differing dynamics over these time scales. In this letter, we discuss some of the differences between the factors that operate in the short term and those that operate in the long term. We use long-term historical emissions trends to show that short-term observations are very poor indicators of long-term future emissions developments. Based on this, we conclude that the performance of long-term scenarios should be evaluated against the appropriate, corresponding long-term variables and trends. The research community may facilitate this by developing appropriate data sets and protocols that can be used to test the performance of long-term scenarios and the models that produce them. [ABSTRACT FROM AUTHOR]

Probabilistic climate projections based on two SRES scenarios, an IMAGE reference scenario and five IMAGE mitigation scenarios (all of them multi-gas scenarios) using the Bern2.5D climate model are calculated. Probability distributions of climate model parameters that are constrained by observations are employed as input for the climate model. The sensitivity of the resulting distributions with respect to prior assumptions on climate sensitivity is then assessed. Due to system inertia, prior assumptions on climate sensitivity play a minor role in the case of temperature projections for the first half of the 21st century, but these assumptions have a considerable influence on the distributions of the projected temperature increase in the year 2100. Upper and lower probabilities for exceeding 2°C by the year 2100 are calculated for the different scenarios. Only the most stringent mitigation measures lead to low probabilities for exceeding the 2°C threshold. This finding is robust with respect to our prior assumptions on climate sensitivity. Further, probability distributions of total present-value damages over the period 2000-2100 for the different scenarios are calculated assuming a wide range of damage cost functions, and the sensitivity of these distributions with respect to the assumed discount rate is investigated. Absolute values of damage costs depend heavily on the chosen damage cost function and discount rate. Nevertheless, some robust conclusions are possible. [ABSTRACT FROM AUTHOR]

Adaptation is an important element on the climate change policy agenda. Integrated assessment models, which are key tools to assess climate change policies, have begun to address adaptation, either by including it implicitly in damage cost estimates, or by making it an explicit control variable. We analyze how modelers have chosen to describe adaptation within an integrated framework, and suggest many ways they could improve the treatment of adaptation by considering more of its bottom-up characteristics. Until this happens, we suggest, models may be too optimistic about the net benefits adaptation can provide, and therefore may underestimate the amount of mitigation they judge to be socially optimal. Under some conditions, better modeling of adaptation costs and benefits could have important implications for defining mitigation targets. [ABSTRACT FROM AUTHOR]

Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth’s climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community. [ABSTRACT FROM AUTHOR]

In order to limit global mean temperature increase to less than 2°C, long-term greenhouse gas concentrations must remain low. This paper discusses how such low concentrations can be reached, based on results from the IMAGE modelling framework (including TIMER and FAIR). We show that the attainability of low greenhouse gas concentration targets, in particular 450 and 400 ppm CO2 equivalent critically depends on model assumptions, such as bio-energy potentials. Under standard model assumptions, these targets can be reached, although the lowest requires the use of bio-energy in combination with carbon-capture-and-storage. Regions are affected differently by ambitious climate policies in terms of energy and land use, although stringent emission reductions will be required in all regions. Resulting co-benefits of climate policy (such as energy security and air pollution) are also different across world regions. [ABSTRACT FROM AUTHOR]

Model analysis within the ADAM project has shown that achieving low greenhouse gas concentration levels, e.g. at 400ppm CO2-e is technologically feasible at costs of a few percent of GDP. However, models simplify the dynamics involved in implementing climate policy and the results depend on critical model assumptions such as global participation in climate policy and full availability of current and newly evolving technologies. The design of a low stabilization policy regime in the real world depends on factors that can only be partly covered by models. In this context, the paper reflects on limits of the integrated assessment models used to explore climate policy and addresses the issues of (i) how global participation might be achieved, (ii) which kind of options are available to induce deep GHG reductions inside and outside the energy sector, and (iii) which risks and which co-benefits of mitigation options are not assessed by the models. [ABSTRACT FROM AUTHOR]

One approach in climate-change policy is to set normative long-term targets first and then infer the implied emissions pathways. An important example of a normative target is to limit the global-mean temperature change to a certain maximum. In general. reported cost estimates for limiting global warming often rise rapidly, even exponentially, as the scale of emission reductions from a reference level increases. This rapid rise may suggest that more ambitious policies may be prohibitively expensive. Here, we propose a probabilistic perspective, focused on the relationship between mitigation costs and the likelihood of achieving a climate target. We investigate the qualitative, functional relationship between the likelihood of achieving a normative target and the costs of climate-change mitigation. In contrast to the example of exponentially rising costs for lowering concentration levels, we show that the mitigation costs rise proportionally to the likelihood of meeting a temperature target, across a range of concentration levels. In economic terms investing in climate mitigation to increase the probability of achieving climate targets yields "constant returns to scale," because of a counterbalancing rapid rise in the probabilities of meeting a temperature target as concentration is lowered. [ABSTRACT FROM AUTHOR]

Abstract: The Stern Review on the Economics of Climate Change compares costs and benefits of stringent climate policy and concludes that the benefits of stringent policy considerably outweigh the costs. Many other cost–benefit analyses have come up with less ambitious optimal emission reductions. In this study, we systematically explore the impacts of scientific uncertainties and value judgements on the suggested “optimal target” for international climate policy. In this context, we have varied the most important parameters using a range of values from several widely used Integrated Assessment Modes in one consistent framework. Our analysis shows that uncertainties about abatement and damage costs play an almost equally important role as the discount rate. Both stringent and moderate climate policy can be justified by using other parameter settings. Furthermore, for most parameter settings there is a wide range of concentration levels close to the optimal target, providing a much wider range for political choices than often suggested. [Copyright &y& Elsevier]

Aim Over the next 100 years, human-driven climate change and resulting changes in species occurrences will have global impacts on biodiversity, ecosystem function, and human health. Here we examine how climate change may affect the occurrences of tick species in Africa and alter the suitability of habitat outside Africa for African ticks. Location Africa and the world. Methods We predicted continental and global changes in habitat suitability for each of 73 African tick species, using multiple regression models in different climate change scenarios that cover a wide range of uncertainty. Results Global habitat suitability improves for nearly all tick species under each of a representative range of eight climate change scenarios. Depending on the scenario, African tick species experience an average increase in global habitat suitability of between 1 million and 9 million square kilometres between 1990 and 2100. Main conclusions The potential for successful translocations of ticks and their pathogens from Africa to the rest of the world is likely to increase over the next 100 years. Although the general trend is one of range expansion, there are winners and losers among tick species in each scenario, suggesting that tick community composition will be disrupted substantially by climate change. If this is also typical of other invertebrates, then climate change will disrupt not only the geographic location of communities but also their structure. Changes in tick communities are also likely to influence tick-borne pathogens. [ABSTRACT FROM AUTHOR]

The greenhouse gas emissions scenarios published by the IPCC in the Special Report on Emission Scenarios (SRES) continue to serve as a primary basis for assessing future climate change and possible response strategies. These scenarios were developed between 1996 and 1999 and sufficient time has now passed to make it worth examining their consistency with more recent data and projections. The comparison performed in this paper includes population, GDP, energy use, and emissions of CO2, non-CO2 gases and sulfur. We find the SRES scenarios to be largely consistent with historical data for the 1990-2000 period and with recent projections. Exceptions to this general observation include (1) in the long-term, relatively high population growth assumptions in some regions, particularly in the A2 scenario; (2) in the medium-term, relatively high economic growth assumptions in the LAM (Latin America, Africa and Middle East) region in the A1 scenario; (3) in the short-term, CO2 emissions projections in Al that are somewhat higher than the range of current scenarios; and (4) substantially higher sulfur emissions in some scenarios than in historical data and recent projections. In conclusion, given the relatively small inconsistencies for use as global scenarios there seems to be no immediate need for a large-scale IPCC-led update of the SRES scenarios that is solely based on the SRES scenario performance vis-a-vis data for the 1990-2000 period and/or more recent projections. Based on reported findings, individual research teams could make, and in some cases already have made, useful updates of the scenarios. [ABSTRACT FROM AUTHOR]

• Integrated Assessment Models are key in exploring future climate action. • Their key role can be explained from historic science-policy interactions. • From 1970 to 2015, this role differed from agenda-setting to monitoring ambition. • Explanatory factors include the model structure and the pro-active model community. Integrated Assessment Models (IAMs) have gained a prominent role in the climate science-policy interface. The article reconstructs the evolution of IAMs and their changing role in this interface, investigating how and why IAMs have become so prominent. Based on literature analysis, quantitative document analysis and semi-structured interviews, we describe the historic evolution of the interactions between IAMs and policy-making between 1970 and 2015. We identify five historic phases in which IAMs played distinct mediating roles between science and policy, succeeding to adjust their scenario efforts to the continuously changing demands for knowledge from the policy community. In explaining the prominent role of IAMs, we differentiate between background conditions (material and sociological) and more contextual factors, most notably the flexible, hybrid and broad nature of IAMs as well as the pro-active character of the IAM community to enhance their policy relevance. We draw on the notion of institutional work to explain this success. In light of the urgency of responding to the climate crisis, we suggest that the IAM community may expand their scope of anticipated futures and consider engaging a wider range of publics and societal stakeholders beyond the science-policy interface. [ABSTRACT FROM AUTHOR]

• Rooftop PV key driver in the PV market, thus modelled in IMAGE IAM. • Global estimated potential 8.3 PWh y−1: 1.5 times residential electricity demand. • Scenarios show key role for rooftop PV but regional characteristics crucial. • Income levels and grid electricity prices dominate regional deployment. • Low-irradiation western Europe better than high-irradiation Middle East. The use of solar photovoltaic has strongly increased in the last decade. A significant part of this growth comes from home owners installing rooftop photovoltaic. Despite this key role, most long-term model-based scenarios do not consider decentralized supply of rooftop photovoltaic but concentrate on utility-scale photovoltaic instead. In this paper, we implement rooftop photovoltaic in the Integrated Assessment Model IMAGE to study its possible role in energy and climate scenarios. We first calculated the global technical and economic potential to derive regional cost-supply curves for rooftop photovoltaic. Next, we have added a new decision in the IMAGE model allowing household investment in rooftop photovoltaic based on the comparison of the whole-sale electricity price with the price of rooftop photovoltaic. The global suitable roof surface area was assessed at 36 billion m2, or 4.7 m2 capita−1, leading to a potential for rooftop photovoltaic of 8.3 PWh y−1, roughly 1.5 times the 2015 global residential electricity demand. In the baseline scenario, adding rooftop photovoltaic could lead to a 80–280% increased share of photovoltaic electricity production in 2050 (i.e. from 6% to 17% in total power production). This increase depends on regional characteristics that are essential to the deployment of rooftop photovoltaic: differences in social-economic and policy factors (capital costs, household income, and electricity prices) are considerably more important than physical factors, such as solar irradiance. [ABSTRACT FROM AUTHOR]