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Author Bindi, M.; Palosuo, T.; Trnka, M.; Semenov, M.A.
Title Modelling climate change impacts on crop production for food security INTRODUCTION Type Journal Article
Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.
Volume 65 Issue Pages 3-5
Keywords Crop production; Climate change impact and adaptation assessments; Upscaling; Model ensembles
Abstract Process-based crop models that synthesise the latest scientific understanding of biophysical processes are currently the primary scientific tools available to assess potential impacts of climate change on crop production. Important obstacles are still present, however, and must be overcome for improving crop modelling application in integrated assessments of risk, of sustainability and of crop-production resilience in the face of climate change (e.g. uncertainty analysis, model integration, etc.). The research networks MACSUR and AGMIP organised the CropM International Symposium and Workshop in Oslo, on 10-12 February 2014, and present this CR Special, discussing the state-of-the-art-as well as future perspectives-of crop modelling applications in climate change risk assessment, including the challenges of integrated assessments for the agricultural sector.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0936-577x ISBN Medium (up) Editorial Material
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4785
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Author Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S.
Title Lessons from climate modeling on the design and use of ensembles for crop modeling Type Journal Article
Year 2016 Publication Climatic Change Abbreviated Journal Clim. Change
Volume Issue Pages
Keywords Model ensembles; Crop models; Climate models; Model weighting; Super ensembles
Abstract Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0165-0009 1573-1480 ISBN Medium (up) Review
Area CropM Expedition Conference
Notes CropM; wos; ft=macsur; wsnotyet; Approved no
Call Number MA @ admin @ Serial 4781
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