Stefan Pfenninger

Knowledge and information needs of adaptation policy-makers: a European study

Across Europe, national governments have started to strategically plan adaptation to climate change. Making adaptation decisions is difficult in the light of uncertainties and the complexity of adaptation problems. Already large amounts of research results on climate impacts and adaptive measures are available, and more are produced and need to be mediated across the boundary between science and policy. Both researchers and policy-makers have started to intensify efforts to coproduce knowledge that is valuable to both communities, particularly in the context of climate change adaptation. In this paper, we present results from a study of adaptation governance and information needs, comparing eight European countries. We identify sources and means for the retrieval of information as well as gaps and problems with the knowledge provided by scientists and analyzed whether these appear to be contingent on the point in the policy-making cycle where countries are. We find that in this early phase of adaptation planning, the quality of the definition of needs, the way uncertainty is dealt with, and the quality of science–policy interaction are indeed contingent on the stage of adaptation planning, while information needs and sources are not. We conclude that a well-developed science–policy interface is of key importance for effective decision-making for adaptation.

Balancing Europe/'s wind-power output through spatial deployment informed by weather regimes

Summary As wind and solar power provide a growing share of Europe’s electricity1, understanding and accommodating their variability on multiple timescales remains a critical problem. On weekly timescales, variability is related to long-lasting weather conditions, called weather regimes2–5, which can cause lulls with a loss of wind power across neighbouring countries6. Here we show that weather regimes provide a meteorological explanation for multi-day fluctuations in Europe’s wind power and can help guide new deployment pathways which minimise this variability. Mean generation during different regimes currently ranges from 22 GW to 44 GW and is expected to triple by 2030 with current planning strategies. However, balancing future wind capacity across regions with contrasting inter-regime behaviour – specifically deploying in the Balkans instead of the North Sea – would almost eliminate these output variations, maintain mean generation, and increase fleet-wide minimum output. Solar photovoltaics could balance low-wind regimes locally, but only by expanding current capacity tenfold. New deployment strategies based on an understanding of continent-scale wind patterns and pan-European collaboration could enable a high share of wind energy whilst minimising the negative impacts of output variability.

Vulnerability of solar energy infrastructure and output to climate change

This paper reviews the potential vulnerability of solar energy systems to future extreme event risks as a consequence of climate change. We describe the three main technologies likely to be used to harness sunlight—thermal heating, photovoltaic (PV), and concentrating solar power (CSP)—and identify critical climate vulnerabilities for each one. We then compare these vulnerabilities with assessments of future changes in mean conditions and extreme event risk levels. We do not identify any vulnerabilities severe enough to halt development of any of the technologies mentioned, although we do find a potential value in exploring options for making PV cells more heat-resilient and for improving the design of cooling systems for CSP.

Governance Barriers to Renewable Energy in North Africa

Solar power in the North African region has the potential to provide electricity for local energy needs and export to Europe. Nevertheless, despite the technical feasibility of solar energy projects, stakeholders still perceive projects in the region as risky because of existing governance issues. Certain areas of solar projects, such as construction, operation and management, are the most prone to governance risks, including lack of transparency and accountability, perceived as barriers for deployment of the projects. It is likely that large-scale foreign direct investment into solar energy will not eliminate existing risks, but might even increase them. Furthermore, the recent political changes in the region have addressed some governance risks but not all of them, especially bureaucratic corruption. Stakeholders recommend a broad set of measures to facilitate development of solar projects in the region, ranging from auditing of individual projects to simplification and unification of bureaucratic procedures.

Impacts of Inter-annual Wind and Solar Variations on the European Power System

Summary Weather-dependent renewable energy resources are playing a key role in decarbonizing electricity. There is a growing body of analysis on the impacts of wind and solar variability on power system operation. Existing studies tend to use a single or typical year of generation data, which overlooks the substantial year-to-year fluctuation in weather, or to only consider variation in the meteorological inputs, which overlooks the complex response of an interconnected power system. Here, we address these gaps by combining detailed continent-wide modeling of Europes future power system with 30 years of historical weather data. The most representative single years are 1989 and 2012, but using multiple years reveals a 5-fold increase in Europes inter-annual variability of CO2 emissions and total generation costs from 2015 to 2030. We also find that several metrics generalize to linear functions of variable renewable penetration: CO2 emissions, curtailment of renewables, wholesale prices, and total system costs.

Controlling the self-organizing dynamics in a sandpile model on complex networks by failure tolerance

In this paper, we propose a strategy to control the self-organizing dynamics of the Bak-Tang-Wiesenfeld (BTW) sandpile model on complex networks by allowing some degree of failure tolerance for the nodes and introducing additional active dissipation while taking the risk of possible node damage. We show that the probability for large cascades significantly increases or decreases respectively when the risk for node damage outweighs the active dissipation and when the active dissipation outweighs the risk for node damage. By considering the potential additional risk from node damage, a non-trivial optimal active dissipation control strategy which minimizes the total cost in the system can be obtained. Under some conditions the introduced control strategy can decrease the total cost in the system compared to the uncontrolled model. Moreover, when the probability of damaging a node experiencing failure tolerance is greater than the critical value, then no matter how successful the active dissipation control is, the total cost of the system will have to increase. This critical damage probability can be used as an indicator of the robustness of a network or system.

Introduction to Systems Analysis

This book builds an understanding of what systems are and how they can be described mathematically. In the context of natural science, this knowledge is of great importance. The intended audience are students in applied sciences such as earth and environmental science, geoecology, environmental chemistry and forestry. The focus is on the methods of modeling, with the aim to let readers develop models of their own as well as analyze the properties of models they encounter. Numerous practical examples from the environmental sciences illustrate the concepts, and exercises accompany each chapter. The book is written so as to be easily understandable and includes humorous cartoons. There is no derivation of mathematical formulas or technical description of modeling software. It does, however, require an understanding of calculus for the reader to apply the mathematical methods it introduces.

Chapter 5 Linear Models with Several Variables

So far we have only dealt with models described by a single system variable. We called these models one-dimensional. To adequately describe a system, however, we often need several variables that interact with each other. This is where multi-dimensional models come into play.

Chapter 8 Models in Time and Space

Natural systems have a spatial structure, but until now, we either com6 pletely ignored it (as in the case of the one-box model) or we described it in a highly simplified manner (as in the two-box model of a stratified lake, Example 5.8).

Chapter 6 Nonlinear Models

Natural systems are rarely linear. Even if they are, that linearity often exists only within a limited range of the system variables Vi 5. Indeed, the surprising diversity in the behavior of natural systems is mostly a result nonlinear processes. Despite ever more powerful computers, the behavior of many nonlinear systems can only be predicted over small periods: the weather forecast is a prime example of this.