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- ItemDiverging importance of drought stress for maize and winter wheat in Europe([London] : Nature Publishing Group UK, 2018) Webber, Heidi; Ewert, Frank; Olesen, Jørgen E.; MĂ¼ller, Christoph; Fronzek, Stefan; Ruane, Alex C.; Bourgault, Maryse; Martre, Pierre; Ababaei, Behnam; Bindi, Marco; Ferrise, Roberto; Finger, Robert; Fodor, NĂ¡ndor; GabaldĂ³n-Leal, Clara; Gaiser, Thomas; Jabloun, Mohamed; Kersebaum, Kurt-Christian; Lizaso, Jon I.; Lorite, Ignacio J.; Manceau, Loic; Moriondo, Marco; Nendel, Claas; RodrĂguez, Alfredo; Ruiz-Ramos, Margarita; Semenov, Mikhail A.; Siebert, Stefan; Stella, Tommaso; Stratonovitch, Pierre; Trombi, Giacomo; Wallach, DanielUnderstanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.
- ItemProjected changes in persistent extreme summer weather events: The role of quasi-resonant amplification(Washington, DC [u.a.] : Assoc., 2018) Mann, Michael E.; Rahmstorf, Stefan; Kornhuber, Kai; Steinman, Byron A.; Miller, Sonya K.; Petri, Stefan; Coumou, DimPersistent episodes of extreme weather in the Northern Hemisphere summer have been associated with highamplitude quasi-stationary atmospheric Rossby waves, with zonal wave numbers 6 to 8 resulting from the phenomenon of quasi-resonant amplification (QRA). A fingerprint for the occurrence of QRA can be defined in terms of the zonally averaged surface temperature field. Examining state-of-the-art [Coupled Model Intercomparison Project Phase 5 (CMIP5)] climate model projections, we find that QRA events are likely to increase by ∼50% this century under business-as-usual carbon emissions, but there is considerable variation among climate models. Some predict a near tripling of QRA events by the end of the century, while others predict a potential decrease. Models with amplified Arctic warming yield the most pronounced increase in QRA events. The projections are strongly dependent on assumptions regarding the nature of changes in radiative forcing associated with anthropogenic aerosols over the next century. One implication of our findings is that a reduction in midlatitude aerosol loading could actually lead to Arctic de-amplification this century, ameliorating potential increases in persistent extreme weather events.
- ItemSpatial variations in crop growing seasons pivotal to reproduce global fluctuations in maize and wheat yields(Washington, DC [u.a.] : Assoc., 2018) Jägermeyr, Jonas; Frieler, KatjaTesting our understanding of crop yield responses to weather fluctuations at global scale is notoriously hampered by limited information about underlying management conditions, such as cultivar selection or fertilizer application. Here, we demonstrate that accounting for observed spatial variations in growing seasons increases the variance in reported national maize and wheat yield anomalies that can be explained by process-based model simulations from 34 to 58% and 47 to 54% across the 10 most weather-sensitive main producers, respectively. For maize, the increase in explanatory power is similar to the increase achieved by accounting for water stress, as compared to simulations assuming perfect water supply in both rainfed and irrigated agriculture. Representing water availability constraints in irrigation is of second-order importance. We improve the model’s explanatory power by better representing crops’ exposure to observed weather conditions, without modifying the weather response itself. This growing season adjustment now allows for a close reproduction of heat wave and drought impacts on crop yields.