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Maiorano, A.; Martre, P.; Asseng, S.; Ewert, F.; Müller, C.; Rötter, R.P.; Ruane, A.C.; Semenov, M.A.; Wallach, D.; Wang, E.; Alderman, P.D.; Kassie, B.T.; Biernath, C.; Basso, B.; Cammarano, D.; Challinor, A.J.; Doltra, J.; Dumont, B.; Rezaei, E.E.; Gayler, S.; Kersebaum, K.C.; Kimball, B.A.; Koehler, A.-K.; Liu, B.; O’Leary, G.J.; Olesen, J.E.; Ottman, M.J.; Priesack, E.; Reynolds, M.; Stratonovitch, P.; Streck, T.; Thorburn, P.J.; Waha, K.; Wall, G.W.; White, J.W.; Zhao, Z.; Zhu, Y. |
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Title |
Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles |
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Journal Article |
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Year |
2016 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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Volume |
202 |
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5-20 |
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Keywords |
Impact uncertainty; High temperature; Model improvement; Multi-model ensemble; Wheat crop model |
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Abstract |
To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT world-wide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures >24 °C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively. |
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2016-09-13 |
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Newsletter July 2016 |
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0378-4290 |
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CropM |
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CropMwp;wos; ft=macsur; wsnot_yet; |
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no |
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MA @ admin @ |
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4776 |
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Liu, X.; Lehtonen, H.; Purola, T.; Pavlova, Y.; Rötter, R.P., T. |
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Title |
Dynamic economic modelling of crop rotation with adaptation practices |
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Conference Article |
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2014 |
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TradeM |
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14th EAAE Congress, Ljubljana (Slovenia), 2014-08-26 to 2014-08-29 |
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MA @ admin @ |
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2604 |
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Lehtonen, H.; Rötter, R.; T., P. |
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Farm level analysis as a key to integrated regional case studies in Finland |
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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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2596 |
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Kersebaum, C.; Nendel, C.; Rötter, R.P. |
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Title |
Documentation of temperature algorithms in the models HERMES, MONICA and WOFOST |
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Conference Article |
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2013 |
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AgMIP workshop “Wheat Response to High Temperature”, El Batan/Mexico., 2013-06-19 to 2013-06-21 |
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no |
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MA @ admin @ |
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2522 |
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Kersebaum, C.; Kollas, C.; Bindi, M.; Nendel, C.; Ferrise, R.; Moriondo, M.; Olesen, J.E.; Sharif, B.; Öztürk, I.; Hoffmann, H.; Launay, M.; Ripoche, D.; Ruget, F.; Bertuzzi, P.; Cortazar, I.G.D.; Beaudoin, N.; Armas-Herrera, C.; Mary, B.; Müller, C.; Waha, K.; Ventrella, D.; Palosuo, T.; Rötter, R.; Trnka, M.; Hlavinka, P.; Wu, L.; Wegehenkel, M.; Mirschel, W.; Conradt, T.; Wechsung, F.; Weigel, H.-J.; Manderscheid, R.; Eitzinger, J. |
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Modelling complex crop rotations and management across sites in Europe with an ensemble of models |
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2014 |
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CropM |
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ASA-CSSA-SSSA Int. Annual Meeting, Long Beach, CA, 2-5 November 2014, 2014-11-02 to 2014-11-05 |
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MA @ admin @ |
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2526 |
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