Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 440253
Title Uncertainty in simulating wheat yields under climate change : Letter
Author(s) Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Supit, I.
Source Nature Climate Change 3 (2013)9. - ISSN 1758-678X - p. 827 - 832.
DOI https://doi.org/10.1038/nclimate1916
Department(s) Earth System Science
WIMEK
Publication type Refereed Article in a scientific journal
Publication year 2013
Keyword(s) tarwe - gewasproductie - klimaatverandering - gewasgroeimodellen - wheat - crop production - climatic change - crop growth models - models - food - co2 - temperature - projections - adaptation - scenarios - ensemble - impacts
Categories Climatic Change
Abstract Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.
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