J. Bessembinder

Framing climate uncertainty: socio-economic and climate scenarios in vulnerability and adaptation assessments

Abstract Scenarios have become a powerful tool in integrated assessment and policy analysis for climate change. Socio-economic and climate scenarios are often combined to assess climate change impacts and vulnerabilities across different sectors and to inform risk management strategies. Such combinations of scenarios can also play an important role in enabling the interaction between experts and other stakeholders, framing issues and providing a means for making explicit and dealing with uncertainties. Drawing on experience with the application of scenarios to climate change assessments in recent Dutch research, the paper argues that scenario approaches need to be matched to the frames of stakeholders who are situated in specific decision contexts. Differentiated approaches (top-down, bottom-up and interactive) are needed to address the different frames and decision-making contexts of stakeholders. A framework is proposed to map scenarios and decision contexts onto two dimensions: the spatial scale of the context and the starting point of approach used in scenario development (top-down, bottom-up or incident-driven). Future climate and socio-economic scenario development will be shaped by the need to become better aligned with multiple interacting uncertainties salient to stakeholders.

Climate Adaptation Services for the Netherlands: an operational approach to support spatial adaptation planning

There is a growing availability of climate change information, offered to scientists and policy makers through climate services. However, climate services are not well taken up by the policy-making and planning community. Climate services focus on primary impacts of climate change, e.g., the disclosure of precipitation and temperature data, and this seems insufficient in meeting their needs. In this paper, we argue that, in order to reach the spatial planning community, climate services should take on a wider perspective by translating climate data to policy-relevant indicators and by offering support in the design of adaptation strategies. We argue there should be more focus on translating consequences of climate change to land-use claims and subsequently discuss the validity, consequences and implications of these claims with stakeholders, so they can play a role in spatial planning processes where much of the climate adaptation takes place. The term Climate Adaptation Services is introduced as being a stepwise approach supporting the assessment of vulnerability in a wider perspective and include the design and appraisal of adaptation strategies in a multi-stakeholder setting. We developed the Climate Adaptation Atlas and the Climate Ateliers as tools within the Climate Adaptation Services approach to support decision-making and planning processes. In this paper, we describe the different steps of our approach and report how some of the challenges were addressed.

Exploring the efficiency of bias corrections of regional climate model output for the assessment of future crop yields in Europe

Excessive summer drying and reduced growing season length are expected to reduce European crop yields in future. This may be partly compensated by adapted crop management, increased CO2 concentration and technological development. For food security, changes in regional to continental crop yield variability may be more important than changes in mean yields. The assessment of changes in regional and larger scale crop variability requires high resolution and spatially consistent future weather, matching a specific climate scenario. Such data could be derived from regional climate models (RCMs), which provide changes in weather patterns. In general, RCM output is heavily biased with respect to observations. Due to the strong nonlinear relation between meteorological input and crop yields, the application of this biased output may result in large biases in the simulated crop yield changes. The use of RCM output only makes sense after sufficient bias correction. This study explores how RCM output can be bias corrected for the assessment of changes in European and subregional scale crop yield variability due to climate change. For this, output of the RCM RACMO of the Royal Netherlands Meteorological Institute was bias corrected and applied within the crop simulation model WOrld FOod STudies to simulate potential and water limited yields of three divergent crops: winter wheat, maize and sugar beets. The bias correction appeared necessary to successfully reproduce the mean yields as simulated with observational data. It also substantially improved the year-to-year variability of seasonal precipitation and radiation within RACMO, but some bias in the interannual variability remained. This is caused by the fact that the applied correction focuses on mean and daily variability. The interannual variability of growing season length, and as a consequence the potential yields too, appeared even deteriorated. Projected decrease in mean crop yields is well in line with earlier studies. No significant change in crop yield variability was found. Yet, only one RCM is analysed in this study, and it is recommended to extend this study with more climate models and a slightly adjusted bias correction taking into account the variability of larger time scales as well.