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  • Nature Publishing Group  (6)
  • Association for Computing Machinery  (2)
  • Arctic Monitoring and Assessment Programme (AMAP)  (1)
  • 1
    Publication Date: 2019-02-25
    Description: Fossils of marine microorganisms such as planktic foraminifera are among the cornerstones of palaeoclimatological studies. It is often assumed that the proxies derived from their shells represent ocean conditions above the location where they were deposited. Planktic foraminifera, however, are carried by ocean currents and, depending on the life traits of the species, potentially incorporate distant ocean conditions. Here we use high-resolution ocean models to assess the footprint of planktic foraminifera and validate our method with proxy analyses from two locations. Results show that foraminifera, and thus recorded palaeoclimatic conditions, may originate from areas up to several thousands of kilometres away, reflecting an ocean state significantly different from the core site. In the eastern equatorial regions and the western boundary current extensions, the offset may reach 1.5 °C for species living for a month and 3.0 °C for longer-living species. Oceanic transport hence appears to be a crucial aspect in the interpretation of proxy signals.
    Type: Article , PeerReviewed
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  • 2
    Publication Date: 2019-09-23
    Description: Predicting the evolution of climate over decadal timescales requires a quantitative understanding of the dynamics that govern the meridional overturning circulation (MOC)1. Comprehensive ocean measurement programmes aiming to monitor MOC variations have been established in the subtropical North Atlantic2, 3 (RAPID, at latitude 26.5° N, and MOVE, at latitude 16° N) and show strong variability on intraseasonal to interannual timescales. Observational evidence of longer-term changes in MOC transport remains scarce, owing to infrequent sampling of transoceanic sections over past decades4, 5. Inferences based on long-term sea surface temperature records, however, supported by model simulations, suggest a variability with an amplitude of plusminus1.5–3 Sv (1 Sv = 106 m3 s-1) on decadal timescales in the subtropics6. Such variability has been attributed to variations of deep water formation in the sub-arctic Atlantic, particularly the renewal rate of Labrador Sea Water7. Here we present results from a model simulation that suggest an additional influence on decadal MOC variability having a Southern Hemisphere origin: dynamic signals originating in the Agulhas leakage region at the southern tip of Africa. These contribute a MOC signal in the tropical and subtropical North Atlantic that is of the same order of magnitude as the northern source. A complete rationalization of observed MOC changes therefore also requires consideration of signals arriving from the south.
    Type: Article , PeerReviewed
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  • 3
    Publication Date: 2020-11-23
    Description: Large amounts of the greenhouse gas methane are released from the seabed to the water column1, where it may be consumed by aerobic methanotrophic bacteria2. The size and activity of methanotrophic communities, which determine the amount of methane consumed in the water column, are thought to be mainly controlled by nutrient and redox dynamics3–7. Here, we report repeated measurements of methanotrophic activity and community size at methane seeps west of Svalbard, and relate them to physical water mass properties and modelled ocean currents. We show that cold bottom water, which contained a large number of aerobic methanotrophs, was displaced by warmer water with a considerably smaller methanotrophic community within days. Ocean current simulations using a global ocean/sea-ice model suggest that this water mass exchange is consistent with short-term variations in the meandering West Spitsbergen Current. We conclude that the shift from an offshore to a nearshore position of the current can rapidly and severely reduce methanotrophic activity in the water column. Strong fluctuating currents are common at many methane seep systems globally, and we suggest that they affect methane oxidation in the water column at other sites, too.
    Type: Article , PeerReviewed
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  • 4
    Publication Date: 2019-02-25
    Description: The interoceanic transfer of seawater between the Indian Ocean and the Atlantic, ‘Agulhas leakage’, forms a choke point for the overturning circulation in the global ocean. Here, by combining output from a series of high-resolution ocean and climate models with in situ and satellite observations, we construct a time series of Agulhas leakage for the period 1870–2014. The time series demonstrates the impact of Southern Hemisphere westerlies on decadal timescales. Agulhas leakage shows a correlation with the Atlantic Multi-decadal Oscillation on multi-decadal timescales; the former leading by 15 years. This is relevant for climate in the North Atlantic
    Type: Article , PeerReviewed
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  • 5
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    Arctic Monitoring and Assessment Programme (AMAP)
    In:  In: AMAP Assessment 2015: Methane as an Arctic climate forcer. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway, pp. 27-38. ISBN 978-82-7971-091-2
    Publication Date: 2019-02-26
    Type: Book chapter , NonPeerReviewed , info:eu-repo/semantics/bookPart
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  • 6
    Publication Date: 2023-09-28
    Description: A special focus in data mining is to identify agglomerations of data points in spatial or spatio-temporal databases. Multiple applications have been presented to make use of such clustering algorithms. However, applications exist, where not only dense areas have to be identified, but also requirements regarding the correlation of the cluster to a specific shape must be met, i.e. circles. This is the case for eddy detection in marine science, where eddies are not only specified by their density, but also their circular-shaped rotation. Traditional clustering algorithms lack the ability to take such aspects into account. In this paper, we introduce Vortex Correlation Clustering which aims to identify those correlated groups of objects oriented along a vortex. This can be achieved by adapting the Circle Hough Transformation, already known from image analysis. The presented adaptations not only allow to cluster objects depending on their location next to each other, but also allows to take the orientation of individual objects into considerations. This allows for a more precise clustering of objects. A multi-step approach allows to analyze and aggregate cluster candidates, to also include final clusters, which do not perfectly satisfy the shape condition. We evaluate our approach upon a real world application, to cluster particle simulations composing such shapes. Our approach outperforms comparable methods of clustering for this application both in terms of effectiveness and efficiency.
    Type: Conference or Workshop Item , NonPeerReviewed
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  • 7
    Publication Date: 2019-09-23
    Description: The transport of warm and salty Indian Ocean waters into the Atlantic Ocean—the Agulhas leakage—has a crucial role in the global oceanic circulation1 and thus the evolution of future climate. At present these waters provide the main source of heat and salt for the surface branch of the Atlantic meridional overturning circulation (MOC)2. There is evidence from past glacial-to-interglacial variations in foraminiferal assemblages3 and model studies4 that the amount of Agulhas leakage and its corresponding effect on the MOC has been subject to substantial change, potentially linked to latitudinal shifts in the Southern Hemisphere westerlies5. A progressive poleward migration of the westerlies has been observed during the past two to three decades and linked to anthropogenic forcing6, but because of the sparse observational records it has not been possible to determine whether there has been a concomitant response of Agulhas leakage. Here we present the results of a high-resolution ocean general circulation model7, 8 to show that the transport of Indian Ocean waters into the South Atlantic via the Agulhas leakage has increased during the past decades in response to the change in wind forcing. The increased leakage has contributed to the observed salinification9 of South Atlantic thermocline waters. Both model and historic measurements off South America suggest that the additional Indian Ocean waters have begun to invade the North Atlantic, with potential implications for the future evolution of the MOC.
    Type: Article , PeerReviewed
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  • 8
    Publication Date: 2022-02-18
    Description: The Atlantic Ocean receives warm, saline water from the Indo-Pacific Ocean through Agulhas leakage around the southern tip of Africa. Recent findings suggest that Agulhas leakage is a crucial component of the climate system and that ongoing increases in leakage under anthropogenic warming could strengthen the Atlantic overturning circulation at a time when warming and accelerated meltwater input in the North Atlantic is predicted to weaken it. Yet in comparison with processes in the North Atlantic, the overall Agulhas system is largely overlooked as a potential climate trigger or feedback mechanism. Detailed modelling experiments—backed by palaeoceanographic and sustained modern observations—are required to establish firmly the role of the Agulhas system in a warming climate.
    Type: Article , PeerReviewed
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  • 9
    Publication Date: 2024-02-05
    Description: Mining spatio-temporal correlation patterns for traffic prediction is a well-studied field. However, most approaches are based on the assumption of the availability of and accessibility to a sufficiently dense data source, which is rather the rare case in reality. Traffic sensors in road networks are generally highly sparse in their distribution: fleet-based traffic sensing is sparse in space but also sparse in time. There are also other traffic application, besides road traffic, like moving objects in the marine space, where observations are sparsely and arbitrarily distributed in space. In this paper, we tackle the problem of traffic prediction on sparse and spatially irregular and non-deterministic traffic observations. We draw a border between imputations and this work as we consider high sparsity rates and no fixed sensor locations. We advance correlation mining methods with a Sparse Unstructured Spatio Temporal Reconstruction (SUSTeR) framework that reconstructs traffic states from sparse non-stationary observations. For the prediction the framework creates a hidden context traffic state which is enriched in a residual fashion with each observation. Such an assimilated hidden traffic state can be used by existing traffic prediction methods to predict future traffic states. We query these states with query locations from the spatial domain.
    Type: Conference or Workshop Item , NonPeerReviewed
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