Potsdam Institute for Climate Impact Research

About: Potsdam Institute for Climate Impact Research is a facility organization based out in Potsdam, Germany. It is known for research contribution in the topics: Climate change & Global warming. The organization has 1519 authors who have published 5098 publications receiving 367023 citations.

A multi-model assessment of food security implications of climate change mitigation

Abstract: Holding the global increase in temperature caused by climate change well below 2 °C above pre-industrial levels, the goal affirmed by the Paris Agreement, is a major societal challenge. Meanwhile, food security is a high-priority area in the UN Sustainable Development Goals, which could potentially be adversely affected by stringent climate mitigation. Here we show the potential negative trade-offs between food security and climate mitigation using a multi-model comparison exercise. We find that carelessly designed climate mitigation policies could increase the number of people at risk of hunger by 160 million in 2050. Avoiding these adverse side effects would entail a cost of about 0.18% of global gross domestic product in 2050. It should be noted that direct impacts of climate change on yields were not assessed and that the direct benefits from mitigation in terms of avoided yield losses could be substantial, further reducing the above cost. Although results vary across models and model implementations, the qualitative implications are robust and call for careful design of climate mitigation policies taking into account agriculture and land prices.

Pinning distributed synchronization of stochastic dynamical networks: a mixed optimization approach.

Abstract: This paper is concerned with the problem of pinning synchronization of nonlinear dynamical networks with multiple stochastic disturbances. Two kinds of pinning schemes are considered: 1) pinned nodes are fixed along the time evolution and 2) pinned nodes are switched from time to time according to a set of Bernoulli stochastic variables. Using Lyapunov function methods and stochastic analysis techniques, several easily verifiable criteria are derived for the problem of pinning distributed synchronization. For the case of fixed pinned nodes, a novel mixed optimization method is developed to select the pinned nodes and find feasible solutions, which is composed of a traditional convex optimization method and a constraint optimization evolutionary algorithm. For the case of switching pinning scheme, upper bounds of the convergence rate and the mean control gain are obtained theoretically. Simulation examples are provided to show the advantages of our proposed optimization method over previous ones and verify the effectiveness of the obtained results.

Assessing River Flood Risk and Adaptation in Europe - Review of Projections for the Future

Abstract: Flood damages have exhibited a rapid upward trend, both globally and in Europe, faster than population and economic growth. Hence, vigorous attempts of attribution of changes have been made. Flood risk and vulnerability tend to change over many areas, due to a range of climatic and nonclimatic impacts whose relative importance is site-specific. Flooding is a complex phenomenon and there are several generating mechanisms, among others intense and/or long-lasting precipitation, snowmelt, ice jam. Projected climate-driven changes in future flood frequency are complex, depending on the generating mechanism, e.g., increasing flood magnitudes where floods result of heavy rainfall and possibly decreasing magnitudes where floods are generated by spring snowmelt. Climate change is likely to cause an increase of the risk of riverine flooding across much of Europe. Projections of flood hazard in Europe based on climatic and hydrological models, reviewed in this paper, illustrate possible changes of recurrence of a 100-year flood (with probability of exceedance being 1-in-100 years) in Europe. What used to be a 100-year flood in the control period is projected to become either more frequent or less frequent in the future time horizon of concern. For a large part of the continent, large flooding is projected to become more commonplace in future, warmer climate. Due to the large uncertainty of climate projections, it is currently not possible to devise a scientifically-sound procedure for redefining design floods (e.g. 100-year flood) in order to adjust flood defenses. For the time being, we recommend to adjust design floods using a “climate change factor” approach.

Utilizing belief functions for the estimation of future climate change

Abstract: We apply belief functions to an analysis of future climate change. It is shown that the lower envelope of a set of probabilities bounded by cumulative probability distributions is a belief function. The large uncertainty about natural and socio-economic factors influencing estimates of future climate change is quantified in terms of bounds on cumulative probability. This information is used to construct a belief function for a simple climate change model, which then is projected onto an estimate of global mean warming in the 21st century. Results show that warming estimates on this basis can generate very imprecise uncertainty models.

Analysing interactions among Sustainable Development Goals with Integrated Assessment Models

Abstract: To achieve all Sustainable Development Goals (SDGs) by 2030, it is necessary to understand how they interact with each other. Integrated Assessment Models (IAMs) represent many human–environment interactions and can inform policymakers about the synergies and trade-offs involved in meeting multiple goals simultaneously. We analyse how IAMs, originally developed to study interactions among energy, the economy, climate, and land, can contribute to a wider analysis of the SDGs in order to inform integrated policies. We compare the key interactions identified among the SDGs in an expert survey, with their current and planned representation in models as identified in a survey among modellers. We also use text mining to reveal past practices by extracting the themes discussed in the IAM literature, linking them to the SDGs, and identifying the interactions among them, thus corroborating our previous results. This combination of methods allowed us to discuss the role of modelling in informing policy coherence and stimulate discussions on future research. The analysis shows that IAMs cover the SDGs related to climate because of their design. It also shows that most IAMs cover several other areas that are related to resource use and the Earth system as well. Some other dimensions of the 2030 Agenda are also covered, but socio-political and equality goals, and others related to human development and governance, are not well represented. Some of these are difficult to capture in models. Therefore, it is necessary to facilitate a better representation of heterogeneity (greater geographical and sectoral detail) by using different types of models (e.g. national and global) and linking different disciplines (especially social sciences) together. Planned developments include increased coverage of human development goals and contribute to policy coherence.