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Now showing 1 - 5 of 5
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    Estimating global mean sea-level rise and its uncertainties by 2100 and 2300 from an expert survey
    (London : Springer Nature, 2020) Horton, Benjamin P.; Khan, Nicole S.; Cahill, Niamh; Lee, Janice S. H.; Shaw, Timothy A.; Garner, Andra J.; Kemp, Andrew C.; Engelhart, Simon E.; Rahmstorf, Stefan
    Sea-level rise projections and knowledge of their uncertainties are vital to make informed mitigation and adaptation decisions. To elicit projections from members of the scientific community regarding future global mean sea-level (GMSL) rise, we repeated a survey originally conducted five years ago. Under Representative Concentration Pathway (RCP) 2.6, 106 experts projected a likely (central 66% probability) GMSL rise of 0.30–0.65 m by 2100, and 0.54–2.15 m by 2300, relative to 1986–2005. Under RCP 8.5, the same experts projected a likely GMSL rise of 0.63–1.32 m by 2100, and 1.67–5.61 m by 2300. Expert projections for 2100 are similar to those from the original survey, although the projection for 2300 has extended tails and is higher than the original survey. Experts give a likelihood of 42% (original survey) and 45% (current survey) that under the high-emissions scenario GMSL rise will exceed the upper bound (0.98 m) of the likely range estimated by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, which is considered to have an exceedance likelihood of 17%. Responses to open-ended questions suggest that the increases in upper-end estimates and uncertainties arose from recent influential studies about the impact of marine ice cliff instability on the meltwater contribution to GMSL rise from the Antarctic Ice Sheet. © 2020, The Author(s).
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    Finding recurrence networks' threshold adaptively for a specific time series
    (Göttingen : Copernicus GmbH, 2014) Eroglu, D.; Marwan, N.; Prasad, S.; Kurths, J.
    Recurrence-plot-based recurrence networks are an approach used to analyze time series using a complex networks theory. In both approaches-recurrence plots and recurrence networks-, a threshold to identify recurrent states is required. The selection of the threshold is important in order to avoid bias of the recurrence network results. In this paper, we propose a novel method to choose a recurrence threshold adaptively. We show a comparison between the constant threshold and adaptive threshold cases to study period-chaos and even period-period transitions in the dynamics of a prototypical model system. This novel method is then used to identify climate transitions from a lake sediment record.
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    Formation and composition of the UTLS aerosol
    (London : Springer Nature, 2019) Martinsson, Bengt G.; Friberg, Johan; Sandvik, Oscar S.; Hermann, Markus; van Velthoven, Peter F. J.; Zahn, Andreas
    Stratospheric aerosol has long been seen as a pure mixture of sulfuric acid and water. Recent measurements, however, found a considerable carbonaceous fraction extending at least 8 km into the stratosphere. This fraction affects the aerosol optical depth (AOD) and the radiative properties, and hence the radiative forcing and climate impact of the stratospheric aerosol. Here we present an investigation based on a decade (2005–2014) of airborne aerosol sampling at 9–12 km altitude in the tropics and the northern hemisphere (NH) aboard the IAGOS-CARIBIC passenger aircraft. We find that the chemical composition of tropospheric aerosol in the tropics differs markedly from that at NH midlatitudes, and, that the carbonaceous stratospheric aerosol is oxygen-poor compared to the tropospheric aerosol. Furthermore, the carbonaceous and sulfurous components of the aerosol in the lowermost stratosphere (LMS) show strong increases in concentration connected with springtime subsidence from overlying stratospheric layers. The LMS concentrations significantly exceed those in the troposphere, thus clearly indicating a stratospheric production of not only the well-established sulfurous aerosol, but also a considerable but less understood carbonaceous component. © 2019, The Author(s).
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    Principal nonlinear dynamical modes of climate variability
    (London : Nature Publishing Group, 2015) Mukhin, D.; Gavrilov, A.; Feigin, A.; Loskutov, E.; Kurths, J.
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    Anticipation-induced social tipping: can the environment be stabilised by social dynamics?
    (Berlin ; Heidelberg : Springer, 2021) Müller, Paul Manuel; Heitzig, Jobst; Kurths, Jürgen; Lüdge, Kathy; Wiedermann, Marc
    In the past decades, human activities caused global Earth system changes, e.g., climate change or biodiversity loss. Simultaneously, these associated impacts have increased environmental awareness within societies across the globe, thereby leading to dynamical feedbacks between the social and natural Earth system. Contemporary modelling attempts of Earth system dynamics rarely incorporate such co-evolutions and interactions are mostly studied unidirectionally through direct or remembered past impacts. Acknowledging that societies have the additional capability for foresight, this work proposes a conceptual feedback model of socio-ecological co-evolution with the specific construct of anticipation acting as a mediator between the social and natural system. Our model reproduces results from previous sociological threshold models with bistability if one assumes a static environment. Once the environment changes in response to societal behaviour, the system instead converges towards a globally stable, but not necessarily desired, attractor. Ultimately, we show that anticipation of future ecological states then leads to metastability of the system where desired states can persist for a long time. We thereby demonstrate that foresight and anticipation form an important mechanism which, once its time horizon becomes large enough, fosters social tipping towards behaviour that can stabilise the environment and prevents potential socio-ecological collapse.