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- ItemModelling nonlinear dynamics of interacting tipping elements on complex networks: the PyCascades package(Berlin ; Heidelberg : Springer, 2021) Wunderling, Nico; Krönke, Jonathan; Wohlfarth, Valentin; Kohler, Jan; Heitzig, Jobst; Staal, Arie; Willner, Sven; Winkelmann, Ricarda; Donges, Jonathan F.Tipping elements occur in various systems such as in socio-economics, ecology and the climate system. In many cases, the individual tipping elements are not independent of each other, but they interact across scales in time and space. To model systems of interacting tipping elements, we here introduce the PyCascades open source software package for studying interacting tipping elements (https://doi.org/10.5281/zenodo.4153102). PyCascades is an object-oriented and easily extendable package written in the programming language Python. It allows for investigating under which conditions potentially dangerous cascades can emerge between interacting dynamical systems, with a focus on tipping elements. With PyCascades it is possible to use different types of tipping elements such as double-fold and Hopf types and interactions between them. PyCascades can be applied to arbitrary complex network structures and has recently been extended to stochastic dynamical systems. This paper provides an overview of the functionality of PyCascades by introducing the basic concepts and the methodology behind it. In the end, three examples are discussed, showing three different applications of the software package. First, the moisture recycling network of the Amazon rainforest is investigated. Second, a model of interacting Earth system tipping elements is discussed. And third, the PyCascades modelling framework is applied to a global trade network.
- ItemHydrological extremes and security(Göttingen : Copernicus GmbH, 2015) Kundzewicz, Z.W.; Matczak, P.
- ItemExtreme hydrological events and security(Göttingen : Copernicus GmbH, 2015) Kundzewicz, Z.W.; Matczak, P.
- ItemGlobal root zone storage capacity from satellite-based evaporation(Göttingen : Copernicus GmbH, 2016) Wang-Erlandsson, L.; Bastiaanssen, W.G.M.; Gao, H.; Jägermeyr, J.; Senay, G.B.; Van Dijk, A.I.J.M.; Guerschman, J.P.; Keys, P.W.; Gordon, L.J.; Savenije, H.H.G.
- ItemImpacts of future deforestation and climate change on the hydrology of the Amazon Basin: A multi-model analysis with a new set of land-cover change scenarios(Göttingen : Copernicus GmbH, 2017) Guimberteau, M.; Ciais, P.; Pablo, Boisier, J.; Paula Dutra Aguiar, A.; Biemans, H.; De Deurwaerder, H.; Galbraith, D.; Kruijt, B.; Langerwisch, F.; Poveda, G.; Rammig, A.; Andres Rodriguez, D.; Tejada, G.; Thonicke, K.; Von, Randow, C.; Randow, R.; Zhang, K.; Verbeeck, H.Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3ĝ€°C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14ĝ€%, respectively. However, in south-east Amazonia, precipitation decreases by 10ĝ€% at the end of the dry season and the three LSMs produce a 6ĝ€% decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31ĝ€% in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34ĝ€% over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27ĝ€% in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.
- ItemLandscape matters: Insights from the impact of mega-droughts on Colombia's energy transition(Amsterdam [u.a.] : Elsevier, 2020) Weng, Wei; Becker, Stefanie L.; Lüdeke, Matthias K. B.; Lakes, TobiaMega-droughts can cause disruption to the affected society sparking a transition. We explore the causes and effects of the 2015−2016 mega-drought in Colombia. Using the multi-level perspective as a framework, we found that the mega-drought sparked an energy transition in Colombia whose dynamics were impacted both by the institutionalization of niches as well as the ability to predict the next drought. We were able to trace, using the current understanding of anthropogenic forces, the cause of the mega-drought to socio-technical landscape development influenced by human-induced warming and land use change. We found that the regimes in Bolivia and Brazil were able to influence the landscape through deforestation, and hence contribute to the intensity of a mega-drought in Colombia. The knowledge that a regime can cause disruption in regimes in other geographies and sectors has implications for transition research as well as decision-making for coping with droughts and other disasters. © 2020
- ItemDrought losses in China might double between the 1.5 °C and 2.0 °C warming(Washington, DC : NAS, 2018) Su, Buda; Huang, Jinlong; Fischer, Thomas; Wang, Yanjun; Kundzewicz, Zbigniew W.; Zhai, Jianqing; Sun, Hemin; Wang, Anqian; Zeng, Xiaofan; Wang, Guojie; Tao, Hui; Gemmer, Marco; Li, Xiucang; Jiang, TongWe project drought losses in China under global temperature increase of 1.5 °C and 2.0 °C, based on the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), a cluster analysis method, and “intensity-loss rate” function. In contrast to earlier studies, to project the drought losses, we predict the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration pattern for the 1.5 °C and 2.0 °C global warming above the preindustrial at 2020–2039 and 2040–2059, respectively. With increasing drought intensity and areal coverage across China, drought losses will soar. The estimated loss in a sustainable development pathway at the 1.5 °C warming level increases 10-fold in comparison with the reference period 1986–2005 and nearly threefold relative to the interval 2006–2015. However, limiting the temperature increase to 1.5 °C can reduce the annual drought losses in China by several tens of billions of US dollars, compared with the 2.0 °C warming.