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Author |
Challinor, A.; Martre, P.; Asseng, S.; Thornton, P.; Ewert, F. |
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Title |
Making the most of climate impacts ensembles |
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Journal Article |
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Year |
2014 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
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4 |
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2 |
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77-80 |
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Keywords  |
uncertainty; model; adaptation |
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Increasing use of regionally and globally oriented impacts studies, coordinated across international modelling groups, promises to bring about a new era in climate impacts research. Coordinated cycles of model improvement and projection are needed to make the most of this potential. |
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English |
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1758-678x 1758-6798 |
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Commentary |
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CropM |
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Call Number |
MA @ admin @ |
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4516 |
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Author |
Montesino-San Martín, M.; Olesen, J.E.; Porter, J.R. |
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Title |
Can crop-climate models be accurate and precise? A case study for wheat production in Denmark |
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Journal Article |
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Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
202 |
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51-60 |
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Keywords |
Uncertainty; Model intercomparison; Bayesian approach; Climate change; Wheat; Denmark; uncertainty analysis; simulation-models; bayesian-approach; change; impact; yields; variability; projections; scale; calibration; framework |
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Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical and mechanistic wheat models to assess how differences in the extent of process understanding in models affects uncertainties in projected impact. Predictive power of the models was tested via both accuracy (bias) and precision (or tightness of grouping) of yield projections for extrapolated weather conditions. Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher accuracy comes at the cost of precision of the mechanistic model to embrace all observations within given boundaries. The approaches showed complementarity in sensitivity to weather variables and in accuracy for different extrapolation domains. Their differences in model precision and accuracy make them suitable for generic model ensembles for near-term agricultural impact assessments of climate change. |
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0168-1923 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4572 |
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Author |
Zimmermann, A.; Adenäuer, M. |
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Title |
Exploring yield trends and gaps in the EU |
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Conference Article |
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Year |
2014 |
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TradeM; |
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Hurdal (Norway) |
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MACSUR TradeM International Workshop »Economics of integrated assessment approaches for agriculture and the food sector«, 2014-11-25 to 2014-11-27, Hurdal |
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MA @ admin @ |
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2928 |
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Author |
Kirchner, M.; Schmid, E.; Mitter, H.; Schönhart, M. |
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Title |
Modeling the Impacts of Climate Change and Market Integration on Agricultural Production and Land Use Management in Austria |
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2015 |
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IIASA Interim Report Young Scientists Summer Program |
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TradeM C6 - |
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MA @ admin @ |
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2065 |
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Author |
Schechter, M. |
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Welcome Address of the Founder and Distinguished Chair of Natural Resource and Environmental Research Center |
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2013 |
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TradeM |
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MACSUR TradeM workshop: Exploring new ideas for trade and agriculture model integration for assessing the impacts of climate change on food security, The Natural Resource and Environmental Research Center (NRERC), University of Haifa, Israel, 2013-03-03 t |
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MA @ admin @ |
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2797 |
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