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    State-of-the-art global models underestimate impacts from climate extremes
    ([London] : Nature Publishing Group UK, 2019) Schewe, Jacob; Gosling, Simon N.; Reyer, Christopher; Zhao, Fang; Ciais, Philippe; Elliott, Joshua; Francois, Louis; Huber, Veronika; Lotze, Heike K.; Seneviratne, Sonia I.; van Vliet, Michelle T. H.; Vautard, Robert; Wada, Yoshihide; Breuer, Lutz; Büchner, Matthias; Carozza, David A.; Chang, Jinfeng; Coll, Marta; Deryng, Delphine; de Wit, Allard; Eddy, Tyler D.; Folberth, Christian; Frieler, Katja; Friend, Andrew D.; Gerten, Dieter; Gudmundsson, Lukas; Hanasaki, Naota; Ito, Akihiko; Khabarov, Nikolay; Kim, Hyungjun; Lawrence, Peter; Morfopoulos, Catherine; Müller, Christoph; Müller Schmied, Hannes; Orth, René; Ostberg, Sebastian; Pokhrel, Yadu; Pugh, Thomas A. M.; Sakurai, Gen; Satoh, Yusuke; Schmid, Erwin; Stacke, Tobias; Steenbeek, Jeroen; Steinkamp, Jörg; Tang, Qiuhong; Tian, Hanqin; Tittensor, Derek P.; Volkholz, Jan; Wang, Xuhui; Warszawski, Lila
    Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
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    Global crop yields can be lifted by timely adaptation of growing periods to climate change
    ([London] : Nature Publishing Group UK, 2022) Minoli, Sara; Jägermeyr, Jonas; Asseng, Senthold; Urfels, Anton; Müller, Christoph
    Adaptive management of crop growing periods by adjusting sowing dates and cultivars is one of the central aspects of crop production systems, tightly connected to local climate. However, it is so far underrepresented in crop-model based assessments of yields under climate change. In this study, we integrate models of farmers’ decision making with biophysical crop modeling at the global scale to simulate crop calendars adaptation and its effect on crop yields of maize, rice, sorghum, soybean and wheat. We simulate crop growing periods and yields (1986-2099) under counterfactual management scenarios assuming no adaptation, timely adaptation or delayed adaptation of sowing dates and cultivars. We then compare the counterfactual growing periods and corresponding yields at the end of the century (2080-2099). We find that (i) with adaptation, temperature-driven sowing dates (typical at latitudes >30°N-S) will have larger shifts than precipitation-driven sowing dates (at latitudes <30°N-S); (ii) later-maturing cultivars will be needed, particularly at higher latitudes; (iii) timely adaptation of growing periods would increase actual crop yields by ~12%, reducing climate change negative impacts and enhancing the positive CO2 fertilization effect. Despite remaining uncertainties, crop growing periods adaptation require consideration in climate change impact assessments.