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Kuhnert, M.; Yeluripati, J.; Smith, P.; Hoffmann, H.; van Oijen, M.; Zhao, G.; Constantin, J.; Raynal, H.; Coucheney, E.; Lewan, E.; Eckersten, H.; Specka, X.; Sosa, C.; Kersebaum, K.-C.; Nendel, C.; Grosz, B.; Dechow, R.; Kiese, R.; Haas, E.; Klatt, S.; Teixeira, E.; Zhao, Z.; Wang, E.; Weihermüller, L.; Gaiser, T.; Ewert, F. |
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Impact of climate aggregation over different scales on regional NPP modelling |
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2016 |
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CropM; |
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Vienna (Austria) |
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European Geosciences Union General Assembly 2016, 2016-04-17 to 2016-04-22, Vienna |
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MA @ admin @ |
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2578 |
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Höglind, M.; Persson, T.; van Oijen, M. |
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Breeding forage grasses: simulation modelling as a tool to identify important cultivar characteristics for winter survival and yield under future climate conditions in Norway |
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2014 |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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MA @ admin @ |
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2487 |
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Höglind, M.; Persson, T.; van Oijen, M. |
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Breeding forage grasses: simulation modelling as a tool to identify important cultivar characteristics for winter survival and yield under future climate conditions in Norway |
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2014 |
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Conference on Genetic Resources for Food and Agriculture in a Changing Climate, Lillehammer, Norway., 2014-01-27 to 2014-01-29 |
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MA @ admin @ |
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2488 |
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Höglind, M.; Persson, T.; van Oijen, M. |
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Identifying target traits for forage grass breeding under a changing climate in Norway using the BASGRA model |
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2013 |
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Proceedings of the 22nd International Grasslands Congress, Sydney, Australia, 2013-09-15 to 2013-09-19 |
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MA @ admin @ |
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2483 |
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Van Oijen, M. |
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Methods for risk analysis and spatial upscaling of process-based models: Experiences from projects Carbo-Extreme and GREENHOUSE |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-69 |
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In the recently finished EU-funded project Carbo-Extreme, we developed a simple probabilistic method for quantifying vulnerabilities and risks to ecosystems (http://iopscience.iop.org/1748-9326/8/1/015032). The method defines risk as expected loss due to environmental hazards, and shows how such risk can be calculated as the product of ecosystem vulnerability and hazard probability. The method was used with six different vegetation models to estimate current and future drought risks for crops, grasslands and forests across Europe (http://www.biogeosciences.net/11/6357/2014/bg-11-6357-2014.html).In the still ongoing UK-funded project GREENHOUSE, the focus is on spatial upscaling of local measurements and model predictions of greenhouse gas emissions to wider regions. As part of this work, we are comparing different model upscaling methods – ranging from naive input aggregation to geostatistics – and quantify the uncertainties associated with the upscaling. This work builds on an earlier inventory of model upscaling methods that was produced in a collaboration of CEH-Edinburgh and the University of Bonn (https://www.stat.aau.at/Tagungen/statgis/2009/StatGIS2009Van%20Oijen1.pdf). Here we show a comparison of the methods using model predictions for the border region of England and Scotland. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2184 |
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