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Potsdam, Germany

The Potsdam Institute for Climate Impact Research , is a government-funded research institute addressing crucial scientific questions in the fields of global change, climate impacts and sustainable development. Ranked among the top environmental think tanks worldwide, it is one of the leading research institutions and part of a global network of scientific and academic institutions working on questions of global environmental change. It is a member of the Leibniz Association, whose institutions perform research on subjects of high relevance to society. Wikipedia.

Gerten D.,Potsdam Institute for Climate Impact Research
Hydrology and Earth System Sciences

This paper argues that the interplay of water, carbon and vegetation dynamics fundamentally links some global trends in the current and conceivable future Anthropocene, such as cropland expansion, freshwater use, and climate change and its impacts. Based on a review of recent literature including geographically explicit simulation studies with the process-based LPJmL global biosphere model, it demonstrates that the connectivity of water and vegetation dynamics is vital for water security, food security and (terrestrial) ecosystem dynamics alike. The water limitation of net primary production of both natural and agricultural plants - already pronounced in many regions - is shown to increase in many places under projected climate change, though this development is partially offset by water-saving direct CO2 effects. Natural vegetation can to some degree adapt dynamically to higher water limitation, but agricultural crops usually require some form of active management to overcome it - among them irrigation, soil conservation and eventually shifts of cropland to areas that are less water-limited due to more favourable climatic conditions. While crucial to secure food production for a growing world population, such human interventions in water-vegetation systems have, as also shown, repercussions on the water cycle. Indeed, land use changes are shown to be the second-most important influence on the terrestrial water balance in recent times. Furthermore, climate change (warming and precipitation changes) will in many regions increase irrigation demand and decrease water availability, impeding rainfed and irrigated food production (if not CO2 effects counterbalance this impact - which is unlikely at least in poorly managed systems). Drawing from these exemplary investigations, some research perspectives on how to further improve our knowledge of human-water-vegetation interactions in the Anthropocene are outlined. © Author(s) 2013. CC Attribution 3.0 License. Source

Muller C.,Potsdam Institute for Climate Impact Research
Annual Review of Nutrition

Climate change impact assessments on agriculture are subject to large uncertainties, as demonstrated in the present review of recent studies for Africa. There are multiple reasons for differences in projections, including uncertainties in greenhouse gas emissions and patterns of climate change; assumptions on future management, aggregation, and spatial extent; and methodological differences. Still, all projections agree that climate change poses a significant risk to African agriculture. Most projections also see the possibility of increasing agricultural production under climate change, especially if suitable adaptation measures are assumed. Climate change is not the only projected pressure on African agriculture, which struggles to meet demand today and may need to feed an additional one billion individuals by 2050. Development strategies are urgently needed, but they will need to consider future climate change and its inherent uncertainties. Science needs to show how existing synergies between climate change adaptation and development can be exploited. © 2013 by Annual Reviews. All rights reserved. Source

Schwanitz V.J.,Potsdam Institute for Climate Impact Research
Environmental Modelling and Software

Integrated Assessment Models of global climate change (IAMs) are an established tool to study interlinkages between the human and the natural system. Insights from these complex models are widely used to advise policy-makers and to inform the general public. But up to now there has been little understanding of how these models can be evaluated and community-wide standards are missing. To answer this urgent question is a challenge because the systems are open and their future behavior is fundamentally unknown. In this paper, we discuss ways to overcome these problems. Reflecting on experience from other modeling communities, we develop an evaluation framework for IAM of global climate change. It builds on a systematic and transparent step-by-step demonstration of a model's usefulness testing the plausibility of its behavior. Steps in the evaluation hierarchy are: setting up an evaluation framework, evaluation of the conceptual model, code verification and documentation, model evaluation, uncertainty and sensitivity analysis, documentation of the evaluation process, and communication with stakeholders. An important element in evaluating IAM of global climate change is the use of stylized behavior patterns derived from historical observation. The discussion of two examples is offered in this paper. © 2013 Elsevier Ltd. Source

While it is generally asserted that those countries who have contributed least to anthropogenic climate change are most vulnerable to its adverse impacts some recently developed indices of vulnerability to climate change come to a different conclusion. Confirmation or rejection of this assertion is complicated by the lack of an agreed metric for measuring countries' vulnerability to climate change and by conflicting interpretations of vulnerability. This paper presents a comprehensive semi-quantitative analysis of the disparity between countries' responsibility for climate change, their capability to act and assist, and their vulnerability to climate change for four climate-sensitive sectors based on a broad range of disaggregated vulnerability indicators. This analysis finds a double inequity between responsibility and capability on the one hand and the vulnerability of food security, human health, and coastal populations on the other. This double inequity is robust across alternative indicator choices and interpretations of vulnerability. The main cause for the higher vulnerability of poor nations who have generally contributed little to climate change is their lower adaptive capacity. In addition, the biophysical sensitivity and socio-economic exposure of poor nations to climate impacts on food security and human health generally exceeds that of wealthier nations. No definite statement can be made on the inequity associated with climate impacts on water supply due to large uncertainties about future changes in regional water availability and to conflicting indicators of current water scarcity. The robust double inequity between responsibility and vulnerability for most climate-sensitive sectors strengthens the moral case for financial and technical assistance from those countries most responsible for climate change to those countries most vulnerable to its adverse impacts. However, the complex and geographically heterogeneous patterns of vulnerability factors for different climate-sensitive sectors suggest that the allocation of international adaptation funds to developing countries should be guided by sector-specific or hazard-specific criteria despite repeated requests from participants in international climate negotiations to develop a generic index of countries' vulnerability to climate change. © 2010 Elsevier Ltd. Source

This paper estimates the welfare-optimal market share of wind and solar power, explicitly taking into account their output variability. We present a theoretical valuation framework that consistently accounts for the impact of fluctuations over time, forecast errors, and the location of generators in the power grid on the marginal value of electricity from renewables. Then the optimal share of wind and solar power in Northwestern Europe's generation mix is estimated from a calibrated numerical model.We find the optimal long-term wind share to be 20%, three times more than today; however, we also find significant parameter uncertainty. Variability significantly impacts results: if winds were constant, the optimal share would be 60%. In addition, the effect of technological change, price shocks, and policies on the optimal share is assessed. We present and explain several surprising findings, including a negative impact of CO2 prices on optimal wind deployment. Copyright © 2015 by the IAEE. All rights reserved. Source

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