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Now showing 1 - 6 of 6
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    Abrupt transitions in time series with uncertainties
    (London : Nature Publishing Group, 2018) Goswami, B.; Boers, N.; Rheinwalt, A.; Marwan, N.; Heitzig, J.; Breitenbach, S.F.M.; Kurths, J.
    Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.
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    Two-thirds of global cropland area impacted by climate oscillations
    (London : Nature Publishing Group, 2018) Heino, M.; Puma, M.J.; Ward, P.J.; Gerten, D.; Heck, V.; Siebert, S.; Kummu, M.
    The El Niño Southern Oscillation (ENSO) peaked strongly during the boreal winter 2015-2016, leading to food insecurity in many parts of Africa, Asia and Latin America. Besides ENSO, the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) are known to impact crop yields worldwide. Here we assess for the first time in a unified framework the relationships between ENSO, IOD and NAO and simulated crop productivity at the sub-country scale. Our findings reveal that during 1961-2010, crop productivity is significantly influenced by at least one large-scale climate oscillation in two-thirds of global cropland area. Besides observing new possible links, especially for NAO in Africa and the Middle East, our analyses confirm several known relationships between crop productivity and these oscillations. Our results improve the understanding of climatological crop productivity drivers, which is essential for enhancing food security in many of the most vulnerable places on the planet.
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    Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE - Part 2: Carbon emissions and the role of fires in the global carbon balance
    (München : European Geopyhsical Union, 2015) Yue, C.; Ciais, P.; Cadule, P.; Thonicke, K.; van Leeuwen, T.T.
    Carbon dioxide emissions from wild and anthropogenic fires return the carbon absorbed by plants to the atmosphere, and decrease the sequestration of carbon by land ecosystems. Future climate warming will likely increase the frequency of fire-triggering drought, so that the future terrestrial carbon uptake will depend on how fires respond to altered climate variation. In this study, we modelled the role of fires in the global terrestrial carbon balance for 1901–2012, using the ORCHIDEE global vegetation model equipped with the SPITFIRE model. We conducted two simulations with and without the fire module being activated, using a static land cover. The simulated global fire carbon emissions for 1997–2009 are 2.1 Pg C yr−1, which is close to the 2.0 Pg C yr−1 as estimated by GFED3.1. The simulated land carbon uptake after accounting for emissions for 2003–2012 is 3.1 Pg C yr−1, which is within the uncertainty of the residual carbon sink estimation (2.8 ± 0.8 Pg C yr−1). Fires are found to reduce the terrestrial carbon uptake by 0.32 Pg C yr−1 over 1901–2012, or 20% of the total carbon sink in a world without fire. The fire-induced land sink reduction (SRfire) is significantly correlated with climate variability, with larger sink reduction occurring in warm and dry years, in particular during El Niño events. Our results suggest a "fire respiration partial compensation". During the 10 lowest SRfire years (SRfire = 0.17 Pg C yr−1), fires mainly compensate for the heterotrophic respiration that would occur in a world without fire. By contrast, during the 10 highest SRfire fire years (SRfire = 0.49 Pg C yr−1), fire emissions far exceed their respiration partial compensation and create a larger reduction in terrestrial carbon uptake. Our findings have important implications for the future role of fires in the terrestrial carbon balance, because the capacity of terrestrial ecosystems to sequester carbon will be diminished by future climate change characterized by increased frequency of droughts and extreme El Niño events.
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    Regional and inter-regional effects in evolving climate networks
    (Göttingen : Copernicus GmbH, 2014) Hlinka, J.; Hartman, D.; Jajcay, N.; Vejmelka, M.; Donner, R.; Marwan, N.; Kurths, J.; Paluš, M.
    Complicated systems composed of many interacting subsystems are frequently studied as complex networks. In the simplest approach, a given real-world system is represented by an undirected graph composed of nodes standing for the subsystems and non-oriented unweighted edges for interactions present among the nodes; the characteristic properties of the graph are subsequently studied and related to the system's behaviour. More detailed graph models may include edge weights, orientations or multiple types of links; potential time-dependency of edges is conveniently captured in so-called evolving networks. Recently, it has been shown that an evolving climate network can be used to disentangle different types of El Niño episodes described in the literature. The time evolution of several graph characteristics has been compared with the intervals of El Niño and La Niña episodes. In this study we identify the sources of the evolving network characteristics by considering a reduced-dimensionality description of the climate system using network nodes given by rotated principal component analysis. The time evolution of structures in local intra-component networks is studied and compared to evolving inter-component connectivity.
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    A tale of shifting relations: East Asian summer and winter monsoon variability during the Holocene
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Kaboth-Bahr, Stefanie; Bahr, André; Zeeden, Christian; Yamoah, Kweku A.; Lone, Mahjoor Ahmad; Chuang, Chih-Kai; Löwemark, Ludvig; Wei, Kuo-Yen
    Understanding the dynamics between the East Asian summer (EASM) and winter monsoon (EAWM) is needed to predict their variability under future global warming scenarios. Here, we investigate the relationship between EASM and EAWM as well as the mechanisms driving their variability during the last 10,000 years by stacking marine and terrestrial (non-speleothem) proxy records from the East Asian realm. This provides a regional and proxy independent signal for both monsoonal systems. The respective signal was subsequently analysed using a linear regression model. We find that the phase relationship between EASM and EAWM is not time-constant and significantly depends on orbital configuration changes. In addition, changes in the Atlantic Meridional Overturning circulation, Arctic sea-ice coverage, El Niño-Southern Oscillation and Sun Spot numbers contributed to millennial scale changes in the EASM and EAWM during the Holocene. We also argue that the bulk signal of monsoonal activity captured by the stacked non-speleothem proxy records supports the previously argued bias of speleothem climatic archives to moisture source changes and/or seasonality.
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    Network-based identification and characterization of teleconnections on different scales
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2019) Agarwal, Ankit; Caesar, Levke; Marwan, Norbert; Maheswaran, Rathinasamy; Merz, Bruno; Kurths, Jürgen
    Sea surface temperature (SST) patterns can – as surface climate forcing – affect weather and climate at large distances. One example is El Niño-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of – at a certain timescale – similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole.