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Author Ewert, F.; Rötter, R. url  openurl
  Title MACSUR CropM – progress overview Type Conference Article
  Year 2014 Publication Abbreviated Journal  
  Volume Issue Pages  
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  Abstract (down) Activities in the first 1 ½ years of CropM were related to key issues identified as critical at the beginning of the FACCE MACSUR the knowledge Hub. These include: Model intercomparisonGeneration of new data for model improvementMethods for scaling and model linkingUncertainty analysisBuilding research capacity Climate scenario data for crop models The key ambition of CropM has been to develop scientific excellence on methods for a comprehensive assessment of climate change impact, adaptation and policy on European crop production, agriculture and food security. Much progress has been made in developing a first shared continental assessment and tool for: A range of important cropsImportant crop rotationsAdvanced scaling methodsAdvanced link to farm and sector modelsNovel impact uncertainty assessment and reportingState-of-the-art scenario construction A number of concrete studies towards this aim have been launched in CropM workpackages (WPs): WP1-2: Two multi-facetted studies on crop rotation, launched in summer 2013 WP3: comprehensive scaling exercises, launched in March 2013WP4: Studies on (a) Climate scenario development, (b) impact response surface method and (c) Extremes, launched in summer 2013WP5: Analysis of transect across Europe with temperature effect (Space for Time) In addition, extended activities related to capacity building including several PhD courses (WP5) workshops (in WPs1-4) and an International Symposium (10-12 Feb, Oslo, Norway) have been organized. Present and future work is and will be focused on framing and advancing crop modelling as integrated part of comprehensive climate risk assessment and modelling of  agricultural systems for food security from farm to supra-national level.  
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  Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference  
  Series Volume 3(S) Sassari, Italy Series Issue Edition  
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  Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy  
  Notes Approved no  
  Call Number MA @ admin @ Serial 5099  
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Author Zhao, G.; Siebert, S.; Enders, A.; Rezaei, E.E.; Yan, C.; Ewert, F. url  doi
openurl 
  Title Demand for multi-scale weather data for regional crop modeling Type Journal Article
  Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology  
  Volume 200 Issue Pages 156-171  
  Keywords multi-scale; spatial heterogeneity; spatial resolution; crop model; climate variability; climate-change scenarios; integrated assessment; large-scale; phenological development; agricultural systems; spatial-resolution; data aggregation; european-union; winter-wheat; input data  
  Abstract (down) A spatial resolution needs to be determined prior to using models to simulate crop yields at a regional scale, but a dilemma exists in compromising between different demands. A fine spatial resolution demands extensive computation load for input data assembly, model runs, and output analysis. A coarse spatial resolution could result in loss of spatial detail in variability. This paper studied the impact of spatial resolution, data aggregation and spatial heterogeneity of weather data on simulations of crop yields, thus providing guidelines for choosing a proper spatial resolution for simulations of crop yields at regional scale. Using a process-based crop model SIMPLACE (LINTUL2) and daily weather data at 1 km resolution we simulated a continuous rainfed winter wheat cropping system at the national scale of Germany. Then we aggregated the weather data to four resolutions from 10 to 100 km, repeated the simulation, compared them with the 1 km results, and correlated the difference with the intra-pixel heterogeneity quantified by an ensemble of four semivariogram models. Aggregation of weather data had small effects over regions with a flat terrain located in northern Germany, but large effects over southern regions with a complex topography. The spatial distribution of yield bias at different spatial resolutions was consistent with the intra-pixel spatial heterogeneity of the terrain and a log-log linear relationship between them was established. By using this relationship we demonstrated the way to optimize the model resolution to minimize both the number of simulation runs and the expected loss of spatial detail in variability due to aggregation effects. We concluded that a high spatial resolution is desired for regions with high spatial environmental heterogeneity, and vice versa. This calls for the development of multi-scale approaches in regional and global crop modeling. The obtained results require substantiation for other production situations, crops, output variables and for different crop models. (C) 2014 Elsevier B.V. All rights reserved.  
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  Language English Summary Language Original Title  
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  ISSN 0168-1923 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4753  
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Author Cammarano, D.; Rötter, P.; Ewert, F.; Palosuo, T.; Bindi, M.; Kersebaum, K.C.; Olesen, J.E.; Trnka, M.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Angulo, C.; Gaiser, T.; Nendel, C.; Martre, P.; de Wit, A. url  openurl
  Title Challenges for Agro-Ecosystem Modelling in Climate Change Risk Assessment for major European Crops and Farming systems Type Conference Article
  Year 2013 Publication Abbreviated Journal  
  Volume Issue Pages 555-564  
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  Area Expedition Conference Impacts World 2013, International Conference on Climate Change Effects, Potsdam, Germany, 2013-05-27 to 2013-05-30  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2765  
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Author Kuhnert, M.; Yeluripati, J.; Smith, P.; Hoffmann, H.; Constantin, J.; Coucheney, E.; Dechow, R.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kersebaum, K.-C.; Kiese, R.; Klatt, S.; Lewan, E.; Nendel, C.; Raynal, H.; Sosa, C.; Specka, X.; Teixeira, E.; Wang, E.; Weihermüller, L.; Zhao, G.; Zhao, Z.; Ogle, S.; Ewert, F. openurl 
  Title Effects of climate data aggregation on regional net primary production modelling Type Conference Article
  Year 2016 Publication Abbreviated Journal  
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  Corporate Author Thesis  
  Publisher Place of Publication Toulouse (France) Editor  
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  Area Expedition Conference 8th International Congress on Environmental Modelling and Software (iEMSs), 2016-07-10 to 2016-10-13, Toulouse, France  
  Notes Approved no  
  Call Number MA @ admin @ Serial 4896  
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Author Tao, F.; Rötter, R.P.; Palosuo, T.; Hernández, C.G.; Mínguez, M.I.; Semenov, M.; Kersebaum, K.C.; Nendel, C.; Cammarano, D.; Hoffmann, H.; Ewert, F.; Dambreville, A.; Martre, P.; Rodríguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Höhn, J.G.; Ferrise, R.; Bindi, M.; Schulman, A. url  openurl
  Title Using crop model ensembles to design future climate-resilient barley cultivars Type Conference Article
  Year 2016 Publication Abbreviated Journal  
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  Corporate Author Thesis  
  Publisher Place of Publication Berlin (Germany) Editor  
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  Area Expedition Conference International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany  
  Notes Approved no  
  Call Number MA @ admin @ Serial 4898  
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