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- ItemNon-linear intensification of Sahel rainfall as a possible dynamic response to future warming(München : European Geopyhsical Union, 2017) Schewe, Jacob; Levermann, AndersProjections of the response of Sahel rainfall to future global warming diverge significantly. Meanwhile, paleoclimatic records suggest that Sahel rainfall is capable of abrupt transitions in response to gradual forcing. Here we present climate modeling evidence for the possibility of an abrupt intensification of Sahel rainfall under future climate change. Analyzing 30 coupled global climate model simulations, we identify seven models where central Sahel rainfall increases by 40 to 300% over the 21st century, owing to a northward expansion of the West African monsoon domain. Rainfall in these models is non-linearly related to sea surface temperature (SST) in the tropical Atlantic and Mediterranean moisture source regions, intensifying abruptly beyond a certain SST warming level. We argue that this behavior is consistent with a self-amplifying dynamic–thermodynamical feedback, implying that the gradual increase in oceanic moisture availability under warming could trigger a sudden intensification of monsoon rainfall far inland of today's core monsoon region.
- ItemChanges in crop yields and their variability at different levels of global warming(München : European Geopyhsical Union, 2018) Ostberg, Sebastian; Schewe, Jacob; Childers, Katelin; Frieler, KatjaAn assessment of climate change impacts at different levels of global warming is crucial to inform the policy discussion about mitigation targets, as well as for the economic evaluation of climate change impacts. Integrated assessment models often use global mean temperature change (ΔGMT) as a sole measure of climate change and, therefore, need to describe impacts as a function of ΔGMT. There is already a well-established framework for the scalability of regional temperature and precipitation changes with ΔGMT. It is less clear to what extent more complex biological or physiological impacts such as crop yield changes can also be described in terms of ΔGMT, even though such impacts may often be more directly relevant for human livelihoods than changes in the physical climate. Here we show that crop yield projections can indeed be described in terms of ΔGMT to a large extent, allowing for a fast estimation of crop yield changes for emissions scenarios not originally covered by climate and crop model projections. We use an ensemble of global gridded crop model simulations for the four major staple crops to show that the scenario dependence is a minor component of the overall variance of projected yield changes at different levels of ΔGMT. In contrast, the variance is dominated by the spread across crop models. Varying CO2 concentrations are shown to explain only a minor component of crop yield variability at different levels of global warming. In addition, we find that the variability in crop yields is expected to increase with increasing warming in many world regions. We provide, for each crop model, geographical patterns of mean yield changes that allow for a simplified description of yield changes under arbitrary pathways of global mean temperature and CO2 changes, without the need for additional climate and crop model simulations.
- ItemDifferential climate impacts for policy-relevant limits to global warming: The case of 1.5 °c and 2 °c(München : European Geopyhsical Union, 2016) Schleussner, Carl-Friedrich; Lissner, Tabea K.; Fischer, Erich M.; Wohland, Jan; Perrette, Mahé; Golly, Antonius; Rogelj, Joeri; Childers, Katelin; Schewe, Jacob; Frieler, Katja; Mengel, Matthias; Hare, William; Schaeffer, MichielRobust appraisals of climate impacts at different levels of global-mean temperature increase are vital to guide assessments of dangerous anthropogenic interference with the climate system. The 2015 Paris Agreement includes a two-headed temperature goal: "holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C". Despite the prominence of these two temperature limits, a comprehensive overview of the differences in climate impacts at these levels is still missing. Here we provide an assessment of key impacts of climate change at warming levels of 1.5°C and 2°C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss. Our results reveal substantial differences in impacts between a 1.5°C and 2°C warming that are highly relevant for the assessment of dangerous anthropogenic interference with the climate system. For heat-related extremes, the additional 0.5°C increase in global-mean temperature marks the difference between events at the upper limit of present-day natural variability and a new climate regime, particularly in tropical regions. Similarly, this warming difference is likely to be decisive for the future of tropical coral reefs. In a scenario with an end-of-century warming of 2°C, virtually all tropical coral reefs are projected to be at risk of severe degradation due to temperature-induced bleaching from 2050 onwards. This fraction is reduced to about 90% in 2050 and projected to decline to 70% by 2100 for a 1.5°C scenario. Analyses of precipitation-related impacts reveal distinct regional differences and hot-spots of change emerge. Regional reduction in median water availability for the Mediterranean is found to nearly double from 9% to 17% between 1.5°C and 2°C, and the projected lengthening of regional dry spells increases from 7 to 11%. Projections for agricultural yields differ between crop types as well as world regions. While some (in particular high-latitude) regions may benefit, tropical regions like West Africa, South-East Asia, as well as Central and northern South America are projected to face substantial local yield reductions, particularly for wheat and maize. Best estimate sea-level rise projections based on two illustrative scenarios indicate a 50cm rise by 2100 relative to year 2000-levels for a 2°C scenario, and about 10 cm lower levels for a 1.5°C scenario. In a 1.5°C scenario, the rate of sea-level rise in 2100 would be reduced by about 30% compared to a 2°C scenario. Our findings highlight the importance of regional differentiation to assess both future climate risks and different vulnerabilities to incremental increases in global-mean temperature. The article provides a consistent and comprehensive assessment of existing projections and a good basis for future work on refining our understanding of the difference between impacts at 1.5°C and 2°C warming.
- ItemA multi-model analysis of risk of ecosystem shifts under climate change(Bristol : IOP Publishing, 2013) Warszawski, Lila; Friend, Andrew; Ostberg, Sebastian; Frieler, Katja; Lucht, Wolfgang; Schaphoff, Sibyll; Beerling, David; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B.; Kahana, Ron; Ito, Akihiko; Keribin, Rozenn; Kleidon, Axel; Lomas, Mark; Nishina, Kazuya; Pavlick, Ryan; Rademacher, Tim Tito; Buechner, Matthias; Piontek, Franziska; Schewe, Jacob; Serdeczny, Olivia; Schellnhuber, Hans JoachimClimate change may pose a high risk of change to Earth's ecosystems: shifting climatic boundaries may induce changes in the biogeochemical functioning and structures of ecosystems that render it difficult for endemic plant and animal species to survive in their current habitats. Here we aggregate changes in the biogeochemical ecosystem state as a proxy for the risk of these shifts at different levels of global warming. Estimates are based on simulations from seven global vegetation models (GVMs) driven by future climate scenarios, allowing for a quantification of the related uncertainties. 5–19% of the naturally vegetated land surface is projected to be at risk of severe ecosystem change at 2 ° C of global warming (ΔGMT) above 1980–2010 levels. However, there is limited agreement across the models about which geographical regions face the highest risk of change. The extent of regions at risk of severe ecosystem change is projected to rise with ΔGMT, approximately doubling between ΔGMT = 2 and 3 ° C, and reaching a median value of 35% of the naturally vegetated land surface for ΔGMT = 4 °C. The regions projected to face the highest risk of severe ecosystem changes above ΔGMT = 4 °C or earlier include the tundra and shrublands of the Tibetan Plateau, grasslands of eastern India, the boreal forests of northern Canada and Russia, the savanna region in the Horn of Africa, and the Amazon rainforest.
- ItemUnderstanding the weather signal in national crop‐yield variability(Hoboken, NJ : Wiley, 2017) Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Smith, Steven J.; Pugh, Thomas A.M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, AndersYear‐to‐year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather‐induced crop‐yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state‐of‐the‐art, process‐based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop‐yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process‐based crop models not only account for weather influences on crop yields, but also provide options to represent human‐management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.
- ItemAssessing inter-sectoral climate change risks: The role of ISIMIP(Bristol : IOP Publishing, 2017) Rosenzweig, Cynthia; Arnell, Nigel W.; Ebi, Kristie L.; Lotze-Campen, Hermann; Raes, Frank; Rapley, Chris; Smith, Mark Stafford; Cramer, Wolfgang; Frieler, Katja; Reyer, Christopher P.O.; Schewe, Jacob; van Vuuren, Detlef; Warszawski, LilaThe aims of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) are to provide a framework for the intercomparison of global and regional-scale risk models within and across multiple sectors and to enable coordinated multi-sectoral assessments of different risks and their aggregated effects. The overarching goal is to use the knowledge gained to support adaptation and mitigation decisions that require regional or global perspectives within the context of facilitating transformations to enable sustainable development, despite inevitable climate shifts and disruptions. ISIMIP uses community-agreed sets of scenarios with standardized climate variables and socio-economic projections as inputs for projecting future risks and associated uncertainties, within and across sectors. The results are consistent multi-model assessments of sectoral risks and opportunities that enable studies that integrate across sectors, providing support for implementation of the Paris Agreement under the United Nations Framework Convention on Climate Change.
- ItemAssessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)(München : European Geopyhsical Union, 2017) Frieler, Katja; Lange, Stefan; Piontek, Franziska; Reyer, Christopher P.O.; Schewe, Jacob; Warszawski, Lila; Zhao, Fang; Chini, Louise; Denvil, Sebastien; Emanuel, Kerry; Geiger, Tobias; Halladay, Kate; Hurtt, George; Mengel, Matthias; Murakami, Daisuke; Ostberg, Sebastian; Popp, Alexander; Riva, Riccardo; Stevanovic, Miodrag; Suzuki, Tatsuo; Volkholz, Jan; Burke, Eleanor; Ciais, Philippe; Ebi, Kristie; Eddy, Tyler D.; Elliott, Joshua; Galbraith, Eric; Gosling, Simon N.; Hattermann, Fred; Hickler, Thomas; Hinkel, Jochen; Hof, Christian; Huber, Veronika; Jägermeyr, Jonas; Krysanova, Valentina; Marcé, Rafael; Müller Schmied, Hannes; Mouratiadou, Ioanna; Pierson, Don; Tittensor, Derek P.; Vautard, Robert; van Vliet, Michelle; Biber, Matthias F.; Betts, Richard A.; Bodirsky, Benjamin Leon; Deryng, Delphine; Frolking, Steve; Jones, Chris D.; Lotze, Heike K.; Lotze-Campen, Hermann; Sahajpal, Ritvik; Thonicke, Kirsten; Tian, Hanqin; Yamagata, YoshikiIn Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5°C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).
- ItemThe role of storage dynamics in annual wheat prices(Bristol : IOP Publishing, 2017) Schewe, Jacob; Otto, Christian; Frieler, Katja; Bodirsky, Benjamin Leo; Kriegler, Elmar; Lotze-Campen, Hermann; Popp, AlexanderIdentifying the drivers of global crop price fluctuations is essential for estimating the risks of unexpected weather-induced production shortfalls and for designing optimal response measures. Here we show that with a consistent representation of storage dynamics, a simple supply–demand model can explain most of the observed variations in wheat prices over the last 40 yr solely based on time series of annual production and long term demand trends. Even the most recent price peaks in 2007/08 and 2010/11 can be explained by additionally accounting for documented changes in countries' trade policies and storage strategies, without the need for external drivers such as oil prices or speculation across different commodity or stock markets. This underlines the critical sensitivity of global prices to fluctuations in production. The consistent inclusion of storage into a dynamic supply-demand model closes an important gap when it comes to exploring potential responses to future crop yield variability under climate and land-use change.
- ItemThe critical role of the routing scheme in simulating peak river discharge in global hydrological models(Bristol : IOP Publishing, 2017) Zhao, Fang; Veldkamp, Ted I.E.; Frieler, Katja; Schewe, Jacob; Ostberg, Sebastian; Willner, Sven; Schauberger, Bernhard; Gosling, Simon N.; Müller Schmied, Hannes; Portmann, Felix T.; Leng, Guoyong; Huang, Maoyi; Liu, Xingcai; Tang, Qiuhong; Hanasaki, Naota; Biemans, Hester; Gerten, Dieter; Satoh, Yusuke; Pokhrel, Yadu; Stacke, Tobias; Ciais, Philippe; Chang, Jinfeng; Ducharne, Agnes; Guimberteau, Matthieu; Wada, Yoshihide; Kim, Hyungjun; Yamazaki, DaiGlobal hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge—which is crucial in flood simulations—has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971–2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.
- ItemA statistically predictive model for future monsoon failure in India(Bristol : IOP Publishing, 2012) Schewe, Jacob; Levermann, AndersIndian monsoon rainfall is vital for a large share of the world's population. Both reliably projecting India's future precipitation and unraveling abrupt cessations of monsoon rainfall found in paleorecords require improved understanding of its stability properties. While details of monsoon circulations and the associated rainfall are complex, full-season failure is dominated by large-scale positive feedbacks within the region. Here we find that in a comprehensive climate model, monsoon failure is possible but very rare under pre-industrial conditions, while under future warming it becomes much more frequent. We identify the fundamental intraseasonal feedbacks that are responsible for monsoon failure in the climate model, relate these to observational data, and build a statistically predictive model for such failure. This model provides a simple dynamical explanation for future changes in the frequency distribution of seasonal mean all-Indian rainfall. Forced only by global mean temperature and the strength of the Pacific Walker circulation in spring, it reproduces the trend as well as the multidecadal variability in the mean and skewness of the distribution, as found in the climate model. The approach offers an alternative perspective on large-scale monsoon variability as the result of internal instabilities modulated by pre-seasonal ambient climate conditions.