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Author (up) Van Oijen, M. url  openurl
  Title Methods for risk analysis and spatial upscaling of process-based models: Experiences from projects Carbo-Extreme and GREENHOUSE Type
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 5 Issue Pages Sp5-69  
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  Abstract 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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  Area Expedition Conference MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2184  
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