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- ItemProjecting Exposure to Extreme Climate Impact Events Across Six Event Categories and Three Spatial Scales(Hoboken, NJ : Wiley-Blackwell, 2020) Lange, Stefan; Volkholz, Jan; Geiger, Tobias; Zhao, Fang; Vega, Iliusi; Veldkamp, Ted; Reyer, Christopher P.O.; Warszawski, Lila; Huber, Veronika; Jägermeyr, Jonas; Schewe, Jacob; Bresch, David N.; Büchner, Matthias; Chang, Jinfeng; Ciais, Philippe; Dury, Marie; Emanuel, Kerry; Folberth, Christian; Gerten, Dieter; Gosling, Simon N.; Grillakis, Manolis; Hanasaki, Naota; Henrot, Alexandra-Jane; Hickler, Thomas; Honda, Yasushi; Ito, Akihiko; Khabarov, Nikolay; Koutroulis, Aristeidis; Liu, Wenfeng; Müller, Christoph; Nishina, Kazuya; Ostberg, Sebastian; Müller Schmied, Hannes; Seneviratne, Sonia I.; Stacke, Tobias; Steinkamp, Jörg; Thiery, Wim; Wada, Yoshihide; Willner, Sven; Yang, Hong; Yoshikawa, Minoru; Yue, Chao; Frieler, KatjaThe extent and impact of climate-related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter-Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than fivefold increase in cross-category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia. ©2020. The Authors.
- ItemMapping the yields of lignocellulosic bioenergy crops from observations at the global scale(Katlenburg-Lindau : Copernics Publications, 2020) Li, Wei; Ciais, Philippe; Stehfest, Elke; van Vuuren, Detlef; Popp, Alexander; Arneth, Almut; Di Fulvio, Fulvio; Doelma, Jonathan; Humpenöder, Florian; Harper, Anna B.; Park, Taejin; Makowski, David; Havlik, Petr; Obersteiner, Michael; Wang, Jingmeng; Krause, Andreas; Liu, WenfengMost scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0:5 0:5 spatial resolution. We also provide a combined "best bioenergy crop" yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 tDMha1 yr1 (DM dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are 50% higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0:5 0:5 global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenodo.3274254 (Li, 2019). © 2019 Cambridge University Press. All rights reserved.
- 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.
- ItemMultimodel assessments of human and climate impacts on mean annual streamflow in China(Munich : EGU, 2019) Liu, Xingcai; Liu, Wenfeng; Yang, Hong; Tang, Qiuhong; Flörke, Martina; Masaki, Yoshimitsu; Müller Schmied, Hannes; Ostberg, Sebastian; Pokhrel, Yadu; Satoh, Yusuke; Wada, YoshihideHuman activities, as well as climate variability, have had increasing impacts on natural hydrological systems, particularly streamflow. However, quantitative assessments of these impacts are lacking on large scales. In this study, we use the simulations from six global hydrological models driven by three meteorological forcings to investigate direct human impact (DHI) and climate impact on streamflow in China. Results show that, in the sub-periods of 1971-1990 and 1991-2010, one-fifth to one-third of mean annual streamflow (MAF) was reduced due to DHI in northern basins, and much smaller ( 4 %) MAF was reduced in southern basins. From 1971-1990 to 1991-2010, total MAF changes range from-13%to 10%across basins wherein the relative contributions of DHI change and climate variability show distinct spatial patterns. DHI change caused decreases in MAF in 70% of river segments, but climate variability dominated the total MAF changes in 88% of river segments of China. In most northern basins, climate variability results in changes of-9% to 18% in MAF, while DHI change results in decreases of 2% to 8% in MAF. In contrast with the climate variability that may increase or decrease streamflow, DHI change almost always contributes to decreases in MAF over time, with water withdrawals supposedly being the major impact on streamflow. This quantitative assessment can be a reference for attribution of streamflow changes at large scales, despite remaining uncertainty. We highlight the significant DHI in northern basins and the necessity to modulate DHI through improved water management towards a better adaptation to future climate change. © 2019 Author(s).
- ItemGlobal Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation(Hoboken, NJ : Wiley-Blackwell, 2019) Minoli, Sara; Müller, Christoph; Elliott, Joshua; Ruane, Alex C.; Jägermeyr, Jonas; Zabel, Florian; Dury, Marie; Folberth, Christian; François, Louis; Hank, Tobias; Jacquemin, Ingrid; Liu, Wenfeng; Olin, Stefan; Pugh, Thomas A.M.Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas. ©2019. The Authors.