TY - JOUR A1 - Katzenberger, Anja A1 - Levermann, Anders A1 - Schewe, Jacob A1 - Pongratz, Julia T1 - Intensification of very wet monsoon seasons in India under global warming JF - Geophysical research letters N2 - Rainfall-intense summer monsoon seasons on the Indian subcontinent that are exceeding long-term averages cause widespread floods and landslides. Here we show that the latest generation of coupled climate models robustly project an intensification of very rainfall-intense seasons (June-September). Under the shared socioeconomic pathway SSP5-8.5, very wet monsoon seasons as observed in only 5 years in the period 1965-2015 are projected to occur 8 times more often in 2050-2100 in the multi-model average. Under SSP2-4.5, these seasons become only a factor of 6 times more frequent, showing that even modest efforts to mitigate climate change can have a strong impact on the frequency of very strong rainfall seasons. Besides, we find that the increasing risk of extreme seasonal rainfall is accompanied by a shift from days with light rainfall to days with moderate or heavy rainfall. Additionally, the number of wet days is projected to increase. KW - Indian monsoon KW - climate modeling KW - extreme seasons KW - climate change KW - CMIP6 KW - India Y1 - 2022 U6 - https://doi.org/10.1029/2022GL098856 SN - 0094-8276 SN - 1944-8007 VL - 49 IS - 15 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Mester, Benedikt A1 - Willner, Sven N. A1 - Frieler, Katja A1 - Schewe, Jacob T1 - Evaluation of river flood extent simulated with multiple global hydrological models and climate forcings JF - Environmental research letters : ERL / Institute of Physics N2 - Global flood models (GFMs) are increasingly being used to estimate global-scale societal and economic risks of river flooding. Recent validation studies have highlighted substantial differences in performance between GFMs and between validation sites. However, it has not been systematically quantified to what extent the choice of the underlying climate forcing and global hydrological model (GHM) influence flood model performance. Here, we investigate this sensitivity by comparing simulated flood extent to satellite imagery of past flood events, for an ensemble of three climate reanalyses and 11 GHMs. We study eight historical flood events spread over four continents and various climate zones. For most regions, the simulated inundation extent is relatively insensitive to the choice of GHM. For some events, however, individual GHMs lead to much lower agreement with observations than the others, mostly resulting from an overestimation of inundated areas. Two of the climate forcings show very similar results, while with the third, differences between GHMs become more pronounced. We further show that when flood protection standards are accounted for, many models underestimate flood extent, pointing to deficiencies in their flood frequency distribution. Our study guides future applications of these models, and highlights regions and models where targeted improvements might yield the largest performance gains. KW - global flood model KW - validation KW - model intercomparison KW - flood risk KW - global hydrological model Y1 - 2021 U6 - https://doi.org/10.1088/1748-9326/ac188d SN - 1748-9326 VL - 16 IS - 9 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Rikani, Albano A1 - Schewe, Jacob T1 - Global bilateral migration projections accounting for diasporas, transit and return flows, and poverty constraints JF - Demographic research N2 - BACKGROUND Anticipating changes in international migration patterns is useful for demographic studies and for designing policies that support the well-being of those involved. Existing forecasting methods do not account for a number of stylized facts that emerge from large-scale migration observations and theories: existing migrant communities - diasporas - act to lower migration costs and thereby provide a mechanism of self-amplification; return migration and transit migration are important components of global migration flows; and poverty constrains emigration. OBJECTIVE Here we present hindcasts and future projections of international migration that explicitly account for these nonlinear features. METHODS We develop a dynamic model that simulates migration flows by origin, destination, and place of birth. We calibrate the model using recently constructed global datasets of bilateral migration. RESULTS We show that the model reproduces past patterns and trends well based only on initial migrant stocks and changes in national incomes. We then project migration flows under future scenarios of global socioeconomic development. CONCLUSIONS Different assumptions about income levels and between-country inequality lead to markedly different migration trajectories, with migration flows either converging towards net zero if incomes in presently poor countries catch up with the rest of the world; or remaining high or even rising throughout the 21st century if economic development is slower and more unequal. Importantly, diasporas induce significant inertia and sizable return migration flows. KW - diaspora KW - international migration KW - migration transition KW - return migration KW - simulation model KW - transit migration Y1 - 2021 U6 - https://doi.org/10.4054/DemRes.2021.45.4 SN - 2363-7064 VL - 45 SP - 87 EP - 140 PB - Max Planck Inst. for Demographic Research CY - Rostock ER - TY - JOUR A1 - Kluge, Lucas A1 - Schewe, Jacob T1 - Evaluation and extension of the radiation model for internal migration JF - Physical review : E, Statistical, nonlinear and soft matter physics N2 - Human migration is often studied using gravity models. These models, however, have known limitations, including analytic inconsistencies and a dependence on empirical data to calibrate multiple parameters for the region of interest. Overcoming these limitations, the radiation model has been proposed as an alternative, universal approach to predicting different forms of human mobility, but has not been adopted for studying migration. Here we show, using data on within-country migration from the USA and Mexico, that the radiation model systematically underpredicts long-range moves, while the traditional gravity model performs well for large distances. The universal opportunity model, an extension of the radiation model, shows an improved fit of long-range moves compared to the original radiation model, but at the cost of introducing two additional parameters. We propose a more parsimonious extension of the radiation model that introduces a single parameter. We demonstrate that it fits the data over the full distance spectrum and also-unlike the universal opportunity model-preserves the analytical property of the original radiation model of being equivalent to a gravity model in the limit of a uniform population distribution. Y1 - 2021 U6 - https://doi.org/10.1103/PhysRevE.104.054311 SN - 2470-0045 SN - 2470-0053 SN - 2470-0061 VL - 104 IS - 5 PB - American Physical Society CY - College Park ER - TY - JOUR A1 - Frieler, Katja A1 - Schauberger, Bernhard A1 - Arneth, Almut A1 - Balkovic, Juraj A1 - Chryssanthacopoulos, James A1 - Deryng, Delphine A1 - Elliott, Joshua A1 - Folberth, Christian A1 - Khabarov, Nikolay A1 - Müller, Christoph A1 - Olin, Stefan A1 - Pugh, Thomas A. M. A1 - Schaphoff, Sibyll A1 - Schewe, Jacob A1 - Schmid, Erwin A1 - Warszawski, Lila A1 - Levermann, Anders T1 - Understanding the weather signal in national crop-yield variability JF - Earths future N2 - Year-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. Y1 - 2017 U6 - https://doi.org/10.1002/2016EF000525 SN - 2328-4277 VL - 5 SP - 605 EP - 616 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Schewe, Jacob A1 - Levermann, Anders T1 - Non-linear intensification of Sahel rainfall as a possible dynamic response to future warming JF - Earth system dynamics Y1 - 2017 U6 - https://doi.org/10.5194/esd-8-495-2017 SN - 2190-4979 SN - 2190-4987 VL - 8 SP - 495 EP - 505 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Schleussner, Carl-Friedrich A1 - Lissner, Tabea K. A1 - Fischer, Erich M. A1 - Wohland, Jan A1 - Perrette, Mahe A1 - Golly, Antonius A1 - Rogelj, Joeri A1 - Childers, Katelin A1 - Schewe, Jacob A1 - Frieler, Katja A1 - Mengel, Matthias A1 - Hare, William A1 - Schaeffer, Michiel T1 - Differential climate impacts for policy-relevant limits to global warming: the case of 1.5 degrees C and 2 degrees C JF - Earth system dynamics N2 - Robust 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 degrees C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 degrees 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 degrees C and 2 degrees 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 degrees C and 2 degrees 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 degrees 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 degrees 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 degrees 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 degrees C and 2 degrees 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 degrees C scenario, and about 10 cm lower levels for a 1.5 degrees C scenario. In a 1.5 degrees C scenario, the rate of sea-level rise in 2100 would be reduced by about 30% compared to a 2 degrees 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 degrees C and 2 degrees C warming. Y1 - 2016 U6 - https://doi.org/10.5194/esd-7-327-2016 SN - 2190-4979 SN - 2190-4987 VL - 7 SP - 327 EP - 351 PB - Copernicus CY - Göttingen ER - TY - GEN A1 - Levermann, Anders A1 - Petoukhov, Vladimir A1 - Schewe, Jacob A1 - Schellnhuber, Hans Joachim T1 - Abrupt monsoon transitions as seen in paleorecords can be explained by moisture-advection feedback T2 - Proceedings of the National Academy of Sciences of the United States of America Y1 - 2016 U6 - https://doi.org/10.1073/pnas.1603130113 SN - 0027-8424 VL - 113 SP - E2348 EP - E2349 PB - National Acad. of Sciences CY - Washington ER - TY - GEN A1 - Schewe, Jacob A1 - Levermann, Anders T1 - Non-linear intensification of Sahel rainfall as a possible dynamic response to future warming T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Projections 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 630 KW - moisture-advection feedback KW - abrupt monsoon transitions KW - West African monsoon KW - CMIP5 KW - Holocene KW - climate KW - ocean KW - jet Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419114 IS - 630 SP - 495 EP - 505 ER - TY - GEN A1 - Frieler, Katja A1 - Levermann, Anders A1 - Elliott, J. A1 - Heinke, J. A1 - Arneth, A. A1 - Bierkens, M. F. P. A1 - Ciais, Philippe A1 - Clark, D. B. A1 - Deryng, D. A1 - Doell, P. A1 - Falloon, P. A1 - Fekete, B. A1 - Folberth, Christian A1 - Friend, A. D. A1 - Gellhorn, C. A1 - Gosling, S. N. A1 - Haddeland, I. A1 - Khabarov, N. A1 - Lomas, M. A1 - Masaki, Y. A1 - Nishina, K. A1 - Neumann, K. A1 - Oki, T. A1 - Pavlick, R. A1 - Ruane, A. C. A1 - Schmid, E. A1 - Schmitz, C. A1 - Stacke, T. A1 - Stehfest, E. A1 - Tang, Q. A1 - Wisser, D. A1 - Huber, V. A1 - Piontek, Franziska A1 - Warszawski, L. A1 - Schewe, Jacob A1 - Lotze-Campen, Hermann A1 - Schellnhuber, Hans Joachim T1 - A framework for the cross-sectoral integration of multi-model impact projections BT - land use decisions under climate impacts uncertainties T2 - Earth system dynamics N2 - Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 457 KW - global food demand KW - water availability KW - elevated CO2 KW - future KW - carbon KW - system KW - productivity KW - agriculture KW - emissions KW - scarcity Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-407968 ER -