No abstract

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25$$\,\mathrm {km}$$ km (0.22$$^{\circ }$$ ∘ ) versus 50$$\,\mathrm {km}$$ km (0.44$$^{\circ }$$ ∘ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

Climate change will impact urban areas. Decision makers need useful climate information to adapt adequately. This research aims to improve understanding of changes in moisture and temperature projected under climate change in Berlin compared to its surroundings. Simulations for the Representative Concentration Pathway (RCP) 8.5 scenario from the European Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) 0.11 • are analyzed, showing a difference in moisture and temperature variables between Berlin and its surroundings. The running mean over 30 years shows a divergence throughout the twenty-first century for relative humidity between Berlin and its surroundings. Under this scenario, Berlin gets drier over time. The Mann-Kendall test quantifies a robust decreasing trend in relative humidity for the multi-model ensemble throughout the twenty-first century. The Mann-Whitney-Wilcoxon test for relative humidity indicates a robust climate change signal in Berlin. It is drier and warmer in Berlin compared to its surroundings for all months with the largest difference existing in summer. Additionally, the change in humidity for the period 2070-2099 compared to 1971-2000 is larger in the summer months. This study presents results to better understand near surface moisture change and related variables under long-term climate change in urban areas compared to their rural surroundings using a regional climate multi-model ensemble.

Land abandonment and the subsequent re-forestation are important drivers behind the loss of ecosystem services in mountain regions. Agent-based models can help to identify global change impacts on farmland abandonment and can test policy and management options to counteract this development. Realigning the representation of human decision making with time scales of ecological processes such as reforestation presents a major challenge in this context. Models either focus on the agent-specific behavior anchored in the current generation of farmers at the expense of representing longer scale environmental processes or they emphasize the simulation of long-term economic and forest developments OPEN ACCESSLand 2015, 4 476 where representation of human behavior is simplified in time and space. In this context, we compare the representation of individual and aggregated decision-making in the same model structure and by doing so address some implications of choosing short or long term time horizons in land-use modeling. Based on survey data, we integrate dynamic agents into a comparative static economic sector supply model in a Swiss mountain region. The results from an extensive sensitivity analysis show that this agent-based land-use change model can reproduce observed data correctly and that both model versions are sensitive to the same model parameters. In particular, in both models the specification of opportunity costs determines the extent of production activities and land-use changes by restricting the output space. Our results point out that the agent-based model can capture short and medium term developments in land abandonment better than the aggregated version without losing its sensitivity to important socio-economic drivers. For comparative static approaches, extensive sensitivity analysis with respect to opportunity costs, i.e., the measure of benefits forgone due to alternative uses of labor is essential for the assessment of the impact of climate change on land abandonment and re-forestation in mountain regions.