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.

Alien species in a warmer world: risks and opportunities

Abstract: Climate change and biological invasions are key processes affecting global biodiversity, yet their effects have usually been considered separately. Here, we emphasise that global warming has enabled alien species to expand into regions in which they previously could not survive and reproduce. Based on a review of climate-mediated biological invasions of plants, invertebrates, fishes and birds, we discuss the ways in which climate change influences biological invasions. We emphasise the role of alien species in a more dynamic context of shifting species' ranges and changing communities. Under these circumstances, management practices regarding the occurrence of 'new' species could range from complete eradication to tolerance and even consideration of the 'new' species as an enrichment of local biodiversity and key elements to maintain ecosystem services.

People at Risk of Flooding: Why Some Residents Take Precautionary Action While Others Do Not

Abstract: Self-protective behavior by residents of flood-prone urban areas can reduce monetary flood damage by 80%, and reduce the need for public risk management. But, research on the determinants of private households’ prevention of damage by natural hazards is rare, especially in Germany. To answer the question of why some people take precautionary action while others do not, a socio-psychological model based on Protection Motivation Theory (PMT) is developed, explaining private precautionary damage prevention by residents’ perceptions of previous flood experience, risk of future floods, reliability of public flood protection, the efficacy and costs of self-protective behavior, their perceived ability to perform these actions, and non-protective responses like wishful thinking. The validity of the proposed model is explored by means of representative quantitative telephone surveys and regression analyses, and compared with a socio-economic model (including residents’ age, gender, income, school degree and being owner or tenant). Participants were 157 residents of flood-prone homes in Cologne, Germany, a city that has traditionally been subject to minor and major flood events. Results of the study show the explanatory power of the socio-psychological model, with important implications for public risk communication efforts. To motivate residents in flood-prone areas to take their share in damage prevention, it is essential to communicate not only the risk of flooding and its potential consequences, but also the possibility, effectiveness and cost of private precautionary measures.

Uncertainty in Simulating Wheat Yields Under Climate Change

Abstract: Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.

Rapid changes of glacial climate simulated in a coupled climate model.

Abstract: Abrupt changes in climate, termed Dansgaard-Oeschger and Heinrich events, have punctuated the last glacial period (approximately 100-10 kyr ago) but not the Holocene (the past 10 kyr). Here we use an intermediate-complexity climate model to investigate the stability of glacial climate, and we find that only one mode of Atlantic Ocean circulation is stable: a cold mode with deep water formation in the Atlantic Ocean south of Iceland. However, a 'warm' circulation mode similar to the present-day Atlantic Ocean is only marginally unstable, and temporary transitions to this warm mode can easily be triggered. This leads to abrupt warm events in the model which share many characteristics of the observed Dansgaard-Oeschger events. For a large freshwater input (such as a large release of icebergs), the model's deep water formation is temporarily switched off, causing no strong cooling in Greenland but warming in Antarctica, as is observed for Heinrich events. Our stability analysis provides an explanation why glacial climate is much more variable than Holocene climate.