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Now showing 1 - 10 of 188
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    An integrative quantifier of multistability in complex systems based on ecological resilience
    (London : Nature Publishing Group, 2015) Mitra, C.; Kurths, J.; Donner, R.V.
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    Agent-based modeling to integrate elements from different disciplines for ambitious climate policy
    (Malden, MA : Wiley-Blackwell, 2022) Savin, Ivan; Creutzig, Felix; Filatova, Tatiana; Foramitti, Joël; Konc, Théo; Niamir, Leila; Safarzynska, Karolina; van den Bergh, Jeroen
    Ambitious climate mitigation policies face social and political resistance. One reason is that existing policies insufficiently capture the diversity of relevant insights from the social sciences about potential policy outcomes. We argue that agent-based models can serve as a powerful tool for integration of elements from different disciplines. Having such a common platform will enable a more complete assessment of climate policies, in terms of criteria like effectiveness, equity and public support. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models The Carbon Economy and Climate Mitigation > Policies, Instruments, Lifestyles, Behavior Policy and Governance > Multilevel and Transnational Climate Change Governance.
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    Mid- and long-term climate projections for fragmented and delayed-action scenarios
    (Amsterdam [u.a.] : Elsevier Science, 2013) Schaeffer, Michiel; Gohar, Laila; Kriegler, Elmar; Lowe, Jason; Riahi, Keywan; van Vuuren, Detlef
    This paper explores the climate consequences of “delayed near-term action” and “staged accession” scenarios for limiting warming below 2 °C. The stabilization of greenhouse gas concentrations at low levels requires a large-scale transformation of the energy system. Depending on policy choices, there are alternative pathways to reach this objective. An “optimal” path, as emerging from energy-economic modeling, implies immediate action with stringent emission reductions, while the currently proposed international policies translate into reduction delays and higher near-term emissions. In our delayed action scenarios, low stabilization levels need thus to be reached from comparatively high 2030 emission levels. Negative consequences are higher economic cost as explored in accompanying papers and significantly higher mid-term warming, as indicated by a rate of warming 50% higher by the 2040s. By contrast, both mid- and long-term warming are significantly higher in another class of scenarios of staged accession that lets some regions embark on emission reductions, while others follow later, with conservation of carbon-price pathways comparable to the optimal scenarios. Not only is mid-term warming higher in staged accession cases, but the probability to exceed 2 °C in the 21st century increases by a factor of 1.5.
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    Emotional tendencies in online social networking: a statistical analysis
    (London : Taylor & Francis Open, 2016) Zhang, Xianhan; Zhang, Nan; Zhao, Letong; Zhang, Ruihan; Cao, Jinde; Lu, Jianquan; Kurths, Jürgen; Qian, Cheng
    Numerous previous studies suggested that people's emotional tendency (ET) towards an issue can often be affected by others. But in some cases, people are unwilling to believe opposite points. This paper aims to study whether people's emotional tendencies (ET) are susceptible with exposures to others' ET concerning a special topic. ET contained in 798,057 pieces of private-information-deleted Chinese Weibo posts are carefully investigated via a revised genetic algorithm, a nonlinear method. Note that nearly all of the posts are closely related to a special topic, the terrible earthquake happen in Japan, 11 March 2011. By conducting statistical analysis including coefficient calculations and hypothesis testing, this study shows that concerning this particular topic, Chinese citizens' first impressions about Japan are solid enough to form their ET and would not be easily altered. Moreover, according to analysis and discussion, we discover that node-to-node impact is exaggerated in some theoretical information diffusion models. Instead it is actually the interaction between nodes' properties and the spread information that matters in the process of information diffusions.
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    Effects of climate change on combined labour productivity and supply: an empirical, multi-model study
    (Amsterdam : Elsevier, 2021) Dasgupta, Shouro; van Maanen, Nicole; Gosling, Simon N.; Piontek, Franziska; Otto, Christian; Schleussner, Carl-Friedrich
    Background: Although effects on labour is one of the most tangible and attributable climate impact, our quantification of these effects is insufficient and based on weak methodologies. Partly, this gap is due to the inability to resolve different impact channels, such as changes in time allocation (labour supply) and slowdown of work (labour productivity). Explicitly resolving those in a multi-model inter-comparison framework can help to improve estimates of the effects of climate change on labour effectiveness. Methods: In this empirical, multi-model study, we used a large collection of micro-survey data aggregated to subnational regions across the world to estimate new, robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply. We then assessed the uncertainty in existing labour productivity response functions and derived an augmented mean function. Finally, we combined these two dimensions of labour into a single compound metric (effective labour effects). This combined measure allowed us to estimate the effect of future climate change on both the number of hours worked and on the productivity of workers during their working hours under 1·5°C, 2·0°C, and 3·0°C of global warming. We separately analysed low-exposure (indoors or outdoors in the shade) and high-exposure (outdoor in the sun) sectors. Findings: We found differentiated empirical regional and sectoral ERF's for labour supply. Current climate conditions already negatively affect labour effectiveness, particularly in tropical countries. Future climate change will reduce global total labour in the low-exposure sectors by 18 percentage points (range −48·8 to 5·3) under a scenario of 3·0°C warming (24·8 percentage points in the high-exposure sectors). The reductions will be 25·9 percentage points (–48·8 to 2·7) in Africa, 18·6 percentage points (–33·6 to 5·3) in Asia, and 10·4 percentage points (–35·0 to 2·6) in the Americas in the low-exposure sectors. These regional effects are projected to be substantially higher for labour outdoors in full sunlight compared with indoors (or outdoors in the shade) with the average reductions in total labour projected to be 32·8 percentage points (–66·3 to 1·6) in Africa, 25·0 percentage points (–66·3 to 7·0) in Asia, and 16·7 percentage points (–45·5 to 4·4) in the Americas. Interpretation: Both labour supply and productivity are projected to decrease under future climate change in most parts of the world, and particularly in tropical regions. Parts of sub-Saharan Africa, south Asia, and southeast Asia are at highest risk under future warming scenarios. The heterogeneous regional response functions suggest that it is necessary to move away from one-size-fits-all response functions to investigate the climate effect on labour. Our findings imply income and distributional consequences in terms of increased inequality and poverty, especially in low-income countries, where the labour effects are projected to be high. Funding: COST (European Cooperation in Science and Technology). © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license
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    Forest carbon allocation modelling under climate change
    (Victoria, BC : Heron, 2019) Merganičová, Katarína; Merganič, Ján; Lehtonen, Aleksi; Vacchiano, Giorgio; Ostrogović Sever, Maša Zorana; Augustynczik, Andrey L. D.; Grote, Rüdiger; Kyselová, Ina; Mäkelä, Annikki; Yousefpour, Rasoul; Krejza, Jan; Collalti, Alessio; Reyer, Christopher P. O.
    Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions. © The Author(s) 2019. Published by Oxford University Press.
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    Survivability of deterministic dynamical systems
    (London : Nature Publishing Group, 2016) Hellmann, Frank; Schultz, Paul; Grabow, Carsten; Heitzig, Jobst; Kurths, Jürgen
    The notion of a part of phase space containing desired (or allowed) states of a dynamical system is important in a wide range of complex systems research. It has been called the safe operating space, the viability kernel or the sunny region. In this paper we define the notion of survivability: Given a random initial condition, what is the likelihood that the transient behaviour of a deterministic system does not leave a region of desirable states. We demonstrate the utility of this novel stability measure by considering models from climate science, neuronal networks and power grids. We also show that a semi-analytic lower bound for the survivability of linear systems allows a numerically very efficient survivability analysis in realistic models of power grids. Our numerical and semi-analytic work underlines that the type of stability measured by survivability is not captured by common asymptotic stability measures.
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    Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy
    (Amsterdam [u.a.] : Elsevier Science, 2014) Kriegler, Elmar; Riahi, Keywan; Bauer, Nico; Schwanitz, Valeria Jana; Petermann, Nils; Bosetti, Valentina; Marcucci, Adriana; Otto, Sander; Paroussos, Leonidas; Rao, Shilpa; Currás, Tabaré Arroyo; Ashina, Shuichi; Bollen, Johannes; Eom, Jiyong; Hamdi-Cherif, Meriem; Longden, Thomas; Kitous, Alban; Méjean, Aurélie; Sano, Fuminori; Schaeffer, Michiel; Wada, Kenichi; Capros, Pantelis; van Vuuren, Detlef P.; Edenhofer, Ottmar
    This study explores a situation of staged accession to a global climate policy regime from the current situation of regionally fragmented and moderate climate action. The analysis is based on scenarios in which a front runner coalition – the EU or the EU and China – embarks on immediate ambitious climate action while the rest of the world makes a transition to a global climate regime between 2030 and 2050. We assume that the ensuing regime involves strong mitigation efforts but does not require late joiners to compensate for their initially higher emissions. Thus, climate targets are relaxed, and although staged accession can achieve significant reductions of global warming, the resulting climate outcome is unlikely to be consistent with the goal of limiting global warming to 2 degrees. The addition of China to the front runner coalition can reduce pre-2050 excess emissions by 20–30%, increasing the likelihood of staying below 2 degrees. Not accounting for potential co-benefits, the cost of front runner action is found to be lower for the EU than for China. Regions that delay their accession to the climate regime face a trade-off between reduced short term costs and higher transitional requirements due to larger carbon lock-ins and more rapidly increasing carbon prices during the accession period.
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    Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM) – Part 2: Parameter ensemble analysis
    (Katlenburg-Lindau : Copernicus, 2020) Albrecht, Torsten; Winkelmann, Ricarda; Levermann, Anders
    The Parallel Ice Sheet Model (PISM) is applied to the Antarctic Ice Sheet over the last two glacial cycles (≈210 000 years) with a resolution of 16 km. An ensemble of 256 model runs is analyzed in which four relevant model parameters have been systematically varied using full-factorial parameter sampling. Parameters and plausible parameter ranges have been identified in a companion paper (Albrecht et al., 2020) and are associated with ice dynamics, climatic forcing, basal sliding and bed deformation and represent distinct classes of model uncertainties. The model is scored against both modern and geologic data, including reconstructed grounding-line locations, elevation–age data, ice thickness, surface velocities and uplift rates. An aggregated score is computed for each ensemble member that measures the overall model–data misfit, including measurement uncertainty in terms of a Gaussian error model (Briggs and Tarasov, 2013). The statistical method used to analyze the ensemble simulation results follows closely the simple averaging method described in Pollard et al. (2016). This analysis reveals clusters of best-fit parameter combinations, and hence a likely range of relevant model and boundary parameters, rather than individual best-fit parameters. The ensemble of reconstructed histories of Antarctic Ice Sheet volumes provides a score-weighted likely range of sea-level contributions since the Last Glacial Maximum (LGM) of 9.4±4.1 m (or 6.5±2.0×106km3 ), which is at the upper range of most previous studies. The last deglaciation occurs in all ensemble simulations after around 12 000 years before present and hence after the meltwater pulse 1A (MWP1a). Our ensemble analysis also provides an estimate of parametric uncertainty bounds for the present-day state that can be used for PISM projections of future sea-level contributions from the Antarctic Ice Sheet.
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    Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events
    (London : Nature Publishing Group, 2017) Mann, M.E.; Rahmstorf, S.; Kornhuber, K.; Steinman, B.A.; Miller, S.K.; Coumou, D.
    Persistent episodes of extreme weather in the Northern Hemisphere summer have been shown to be associated with the presence of high-amplitude quasi-stationary atmospheric Rossby waves within a particular wavelength range (zonal wavenumber 6-8). The underlying mechanistic relationship involves the phenomenon of quasi-resonant amplification (QRA) of synoptic-scale waves with that wavenumber range becoming trapped within an effective mid-latitude atmospheric waveguide. Recent work suggests an increase in recent decades in the occurrence of QRA-favorable conditions and associated extreme weather, possibly linked to amplified Arctic warming and thus a climate change influence. Here, we isolate a specific fingerprint in the zonal mean surface temperature profile that is associated with QRA-favorable conditions. State-of-the-art ("CMIP5") historical climate model simulations subject to anthropogenic forcing display an increase in the projection of this fingerprint that is mirrored in multiple observational surface temperature datasets. Both the models and observations suggest this signal has only recently emerged from the background noise of natural variability.