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Author |
Kipling, R.; Özkan, S. |
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Communicating Modelling |
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Conference Article |
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2014 |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, Hurdalsjøen, Norway, 2014-11-25 to 2014-11-27 |
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MA @ admin @ |
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2532 |
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Author |
Kipling, R. |
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Communicating Modelling |
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2015 |
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FACCE MACSUR Reports |
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4 |
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SP4-7 |
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No abstract. No Label |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, 25–27 November 2014, Hurdalsjø, Norway |
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MA @ admin @ |
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2197 |
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Author |
Rivington, M.; Wallach, D. |
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Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Communication strategy, including design of tools for more effective communication of uncertainty |
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Report |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C4.1.4 |
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Communication is the key link between the generation of information by MACSUR about the uncertainty of climate change impacts on future food security and how information is used by decision makers. It is therefore important to make available the common tools for reporting uncertainty, with a discussion of the advantages or difficulties of each. That is the purpose of this report. No Label |
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MA @ admin @ |
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2099 |
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Tsutsumi, Y. |
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Comparing bio-economic farm models: evaluating uncertainty of impacts of climate and socio-economic changes on arable farming in Flevoland (the Netherlands) |
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Book Whole |
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2015 |
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Master's thesis |
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Wageningen University |
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Wageningen |
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M.Sc. |
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M.Sc. |
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CropM |
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no |
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MA @ admin @ |
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5156 |
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Author |
Ruiz-Ramos, M.; Rodriguez, A.; Dosio, A.; Goodess, C.M.; Harpham, C.; Minguez, M.I.; Sanchez, E. |
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Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century |
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Journal Article |
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2016 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
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134 |
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1-2 |
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283-297 |
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regional climate model; bias correction; weather generator; circulation model; simulations; temperature; precipitation; ensemble; uncertainty; extremes |
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Abstract |
Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management. |
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2016-10-31 |
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English |
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0165-0009 |
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CropM, ft_macsur |
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MA @ admin @ |
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4805 |
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