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- ItemFreshwater resources under success and failure of the Paris climate agreement(Göttingen : Copernicus Publ., 2019) Heinke, Jens; Müller, Christoph; Lannerstad, Mats; Gerten, Dieter; Lucht, WolfgangPopulation growth will in many regions increase the pressure on water resources and likely increase the number of people affected by water scarcity. In parallel, global warming causes hydrological changes which will affect freshwater supply for human use in many regions. This study estimates the exposure of future population to severe hydrological changes relevant from a freshwater resource perspective at different levels of global mean temperature rise above pre-industrial level (ΔTglob). The analysis is complemented by an assessment of water scarcity that would occur without additional climate change due to population change alone; this is done to identify the population groups that are faced with particularly high adaptation challenges. The results are analysed in the context of success and failure of implementing the Paris Agreement to evaluate how climate mitigation can reduce the future number of people exposed to severe hydrological change. The results show that without climate mitigation efforts, in the year 2100 about 4.9 billion people in the SSP2 population scenario would more likely than not be exposed to severe hydrological change, and about 2.1 billion of them would be faced with particularly high adaptation challenges due to already prevailing water scarcity. Limiting warming to 2 °C by a successful implementation of the Paris Agreement would strongly reduce these numbers to 615 million and 290 million, respectively. At the regional scale, substantial water-related risks remain at 2 °C, with more than 12% of the population exposed to severe hydrological change and high adaptation challenges in Latin America and the Middle East and north Africa region. Constraining δTglob to 1.5 °C would limit this share to about 5% in these regions. ©2019 Author(s).
- ItemThe GGCMI Phase 2 emulators: Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)(Katlenburg-Lindau : Copernicus, 2020) Franke, James A.; Müller, Christoph; Elliott, Joshua; Ruane, Alex C.; Jägermeyr, Jonas; Snyder, Abigail; Dury, Marie; Falloon, Pete D.; Folberth, Christian; François, Louis; Hank, Tobias; Izaurralde, R. Cesar; Jacquemin, Ingrid; Jones, Curtis; Li, Michelle; Liu, Wenfeng; Olin, Stefan; Phillips, Meridel; Pugh, Thomas A. M.; Reddy, Ashwan; Williams, Karina; Wang, Ziwei; Zabel, Florian; Moyer, Elisabeth J.Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: Atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: That growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts. © 2020 EDP Sciences. All rights reserved.