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- ItemTracing the Snowball bifurcation of aquaplanets through time reveals a fundamental shift in critical-state dynamics(Göttingen : Copernicus, 2023) Feulner, Georg; Bukenberger, Mona; Petri, StefanThe instability with respect to global glaciation is a fundamental property of the climate system caused by the positive ice-albedo feedback. The atmospheric concentration of carbon dioxide (CO2) at which this Snowball bifurcation occurs changes through Earth's history, most notably because of the slowly increasing solar luminosity. Quantifying this critical CO2 concentration is not only interesting from a climate dynamics perspective but also constitutes an important prerequisite for understanding past Snowball Earth episodes, as well as the conditions for habitability on Earth and other planets. Earlier studies are limited to investigations with very simple climate models for Earth's entire history or studies of individual time slices carried out with a variety of more complex models and for different boundary conditions, making comparisons and the identification of secular changes difficult. Here, we use a coupled climate model of intermediate complexity to trace the Snowball bifurcation of an aquaplanet through Earth's history in one consistent model framework. We find that the critical CO2 concentration decreased more or less logarithmically with increasing solar luminosity until about 1 billion years ago but dropped faster in more recent times. Furthermore, there was a fundamental shift in the dynamics of the critical state about 1.2 billion years ago (unrelated to the downturn in critical CO2 values), driven by the interplay of wind-driven sea-ice dynamics and the surface energy balance: for critical states at low solar luminosities, the ice line lies in the Ferrel cell, stabilised by the poleward winds despite moderate meridional temperature gradients under strong greenhouse warming. For critical states at high solar luminosities, on the other hand, the ice line rests at the Hadley cell boundary, stabilised against the equatorward winds by steep meridional temperature gradients resulting from the increased solar energy input at lower latitudes and stronger Ekman transport in the ocean.
- ItemModeling Antarctic tides in response to ice shelf thinning and retreat(Hoboken, NJ : Blackwell Publishing Ltd, 2014) Rosier, S.H.R.; Green, J.A.M.; Scourse, J.D.; Winkelmann, R.Tides play an important role in ice sheet dynamics by modulating ice stream velocity, fracturing, and moving ice shelves and mixing water beneath them. Any changes in ice shelf extent or thickness will alter the tidal dynamics through modification of water column thickness and coastal topography but these will in turn feed back onto the overall ice shelf stability. Here, we show that removal or reduction in extent and/or thickness of the Ross and Ronne-Filchner ice shelves would have a significant impact on the tides around Antarctica. The Ronne-Filchner appears particularly vulnerable, with an increase in M2 amplitude of over 0.5 m beneath much of the ice shelf potentially leading to tidally induced feedbacks on ice shelf/sheet dynamics. These results highlight the importance of understanding tidal feedbacks on ice shelves/streams due to their influence on ice sheet dynamics.
- ItemMonitoring hillslope moisture dynamics with surface ERT for enhancing spatial significance of hydrometric point measurements(Munich : EGU, 2015) Hübner, R.; Heller, K.; Günther, T.; Kleber, A.Besides floodplains, hillslopes are basic units that mainly control water movement and flow pathways within catchments of subdued mountain ranges. The structure of their shallow subsurface affects water balance, e.g. infiltration, retention, and runoff. Nevertheless, there is still a gap in the knowledge of the hydrological dynamics on hillslopes, notably due to the lack of generalization and transferability. This study presents a robust multi-method framework of electrical resistivity tomography (ERT) in addition to hydrometric point measurements, transferring hydrometric data into higher spatial scales to obtain additional patterns of distribution and dynamics of soil moisture on a hillslope. A geoelectrical monitoring in a small catchment in the eastern Ore Mountains was carried out at weekly intervals from May to December 2008 to image seasonal moisture dynamics on the hillslope scale. To link water content and electrical resistivity, the parameters of Archie's law were determined using different core samples. To optimize inversion parameters and methods, the derived spatial and temporal water content distribution was compared to tensiometer data. The results from ERT measurements show a strong correlation with the hydrometric data. The response is congruent to the soil tension data. Water content calculated from the ERT profile shows similar variations as that of water content from soil moisture sensors. Consequently, soil moisture dynamics on the hillslope scale may be determined not only by expensive invasive punctual hydrometric measurements, but also by minimally invasive time-lapse ERT, provided that pedo-/petrophysical relationships are known. Since ERT integrates larger spatial scales, a combination with hydrometric point measurements improves the understanding of the ongoing hydrological processes and better suits identification of heterogeneities.
- ItemA climate network perspective on the intertropical convergence zone(Göttingen : Copernicus Publ., 2021) Wolf, Frederik; Voigt, Aiko; Donner, Reik V.The intertropical convergence zone (ITCZ) is an important component of the tropical rain belt. Climate models continue to struggle to adequately represent the ITCZ and differ substantially in its simulated response to climate change. Here we employ complex network approaches, which extract spatiotemporal variability patterns from climate data, to better understand differences in the dynamics of the ITCZ in state-of-the-art global circulation models (GCMs). For this purpose, we study simulations with 14 GCMs in an idealized slab-ocean aquaplanet setup from TRACMIP – the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project. We construct network representations based on the spatial correlation patterns of monthly surface temperature anomalies and study the zonal-mean patterns of different topological and spatial network characteristics. Specifically, we cluster the GCMs by means of the distributions of their zonal network measures utilizing hierarchical clustering. We find that in the control simulation, the distributions of the zonal network measures are able to pick up model differences in the tropical sea surface temperature (SST) contrast, the ITCZ position, and the strength of the Southern Hemisphere Hadley cell. Although we do not find evidence for consistent modifications in the network structure tracing the response of the ITCZ to global warming in the considered model ensemble, our analysis demonstrates that coherent variations of the global SST field are linked to ITCZ dynamics. This suggests that climate networks can provide a new perspective on ITCZ dynamics and model differences therein.
- ItemProcess verification of a hydrological model using a temporal parameter sensitivity analysis(Göttingen : Copernicus GmbH, 2015) Pfannerstill, M.; Guse, B.; Reusser, D.; Fohrer, N.
- ItemA vital link: Water and vegetation in the anthropocene(Chichester : John Wiley and Sons Ltd, 2013) Gerten, D.This paper argues that the interplay of water, carbon and vegetation dynamics fundamentally links some global trends in the current and conceivable future Anthropocene, such as cropland expansion, freshwater use, and climate change and its impacts. Based on a review of recent literature including geographically explicit simulation studies with the process-based LPJmL global biosphere model, it demonstrates that the connectivity of water and vegetation dynamics is vital for water security, food security and (terrestrial) ecosystem dynamics alike. The water limitation of net primary production of both natural and agricultural plants - already pronounced in many regions - is shown to increase in many places under projected climate change, though this development is partially offset by water-saving direct CO2 effects. Natural vegetation can to some degree adapt dynamically to higher water limitation, but agricultural crops usually require some form of active management to overcome it - among them irrigation, soil conservation and eventually shifts of cropland to areas that are less water-limited due to more favourable climatic conditions. While crucial to secure food production for a growing world population, such human interventions in water-vegetation systems have, as also shown, repercussions on the water cycle. Indeed, land use changes are shown to be the second-most important influence on the terrestrial water balance in recent times. Furthermore, climate change (warming and precipitation changes) will in many regions increase irrigation demand and decrease water availability, impeding rainfed and irrigated food production (if not CO2 effects counterbalance this impact - which is unlikely at least in poorly managed systems). Drawing from these exemplary investigations, some research perspectives on how to further improve our knowledge of human-water-vegetation interactions in the Anthropocene are outlined.
- ItemMultiscale fractal dimension analysis of a reduced order model of coupled ocean–atmosphere dynamics(Göttingen : Copernicus Publ., 2021) Alberti, Tommaso; Donner, Reik V.; Vannitsem, StéphaneAtmosphere and ocean dynamics display many complex features and are characterized by a wide variety of processes and couplings across different timescales. Here we demonstrate the application of multivariate empirical mode decomposition (MEMD) to investigate the multivariate and multiscale properties of a reduced order model of the ocean–atmosphere coupled dynamics. MEMD provides a decomposition of the original multivariate time series into a series of oscillating patterns with time-dependent amplitude and phase by exploiting the local features of the data and without any a priori assumptions on the decomposition basis. Moreover, each oscillating pattern, usually named multivariate intrinsic mode function (MIMF), represents a local source of information that can be used to explore the behavior of fractal features at different scales by defining a sort of multiscale and multivariate generalized fractal dimensions. With these two complementary approaches, we show that the ocean–atmosphere dynamics presents a rich variety of features, with different multifractal properties for the ocean and the atmosphere at different timescales. For weak ocean–atmosphere coupling, the resulting dimensions of the two model components are very different, while for strong coupling for which coupled modes develop, the scaling properties are more similar especially at longer timescales. The latter result reflects the presence of a coherent coupled dynamics. Finally, we also compare our model results with those obtained from reanalysis data demonstrating that the latter exhibit a similar qualitative behavior in terms of multiscale dimensions and the existence of a scale dependency of the statistics of the phase-space density of points for different regions, which is related to the different drivers and processes occurring at different timescales in the coupled atmosphere–ocean system. Our approach can therefore be used to diagnose the strength of coupling in real applications.
- ItemScaling Laws of Collective Ride-Sharing Dynamics(College Park, Md. : APS, 2020) Molkenthin, Nora; Schröder, Malte; Timme, MarcRide-sharing services may substantially contribute to future sustainable mobility. Their collective dynamics intricately depend on the topology of the underlying street network, the spatiotemporal demand distribution, and the dispatching algorithm. The efficiency of ride-sharing fleets is thus hard to quantify and compare in a unified way. Here, we derive an efficiency observable from the collective nonlinear dynamics and show that it exhibits a universal scaling law. For any given dispatcher, we find a common scaling that yields data collapse across qualitatively different topologies of model networks and empirical street networks from cities, islands, and rural areas. A mean-field analysis confirms this view and reveals a single scaling parameter that jointly captures the influence of network topology and demand distribution. These results further our conceptual understanding of the collective dynamics of ride-sharing fleets and support the evaluation of ride-sharing services and their transfer to previously unserviced regions or unprecedented demand patterns.