Mixing of passive tracers at the ocean surface and its implications for plastic transport modelling

Wichmann, David; Delandmeter, Philippe; Dijkstra, Henk A.; Sebille, Erik van

doi:10.1088/2515-7620/ab4e77

Cited by 13 publications

(14 citation statements)

References 29 publications

(67 reference statements)

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“…They depend on a parameter q that controls how much fluid volumes are taken into account in the stirring calculation. For our analysis we fix the parameter q equal to one, obtaining a Shannon‐like entropy that can be calculated on the incoming links (backward in time dynamics) or on the outgoing ones (forward in time dynamics) (Ser‐Giacomi et al, 2017; Ser‐Giacomi, Rossi, et al, 2015; Wichmann et al, 2019). The expressions for the in‐entropy H I ( t 0 , τ ) i and the out‐entropy H O ( t 0 , τ ) i are

\begin{matrix} alignleft \\ align-1 H^{I} {(t_{0}, τ)}_{i} & align-2 = - \frac{1}{τ} \sum_{j = 1}^{N} (\frac{P {(t_{0}, τ)}_{j i}}{\sum_{k = 1}^{N} P {(t_{0}, τ)}_{k i}}) \log (\frac{P {(t_{0}, τ)}_{j i}}{\sum_{k = 1}^{N} P {(t_{0}, τ)}_{k i}}), \end{matrix}

\begin{matrix} alignleft \\ align-1 H^{O} {(t_{0}, τ)}_{i} & align-2 = - \frac{1}{τ} \sum_{j = 1}^{N} (\frac{P {(t_{0}, τ)}_{i j}}{\sum_{k = 1}^{N} P {(t_{0}, τ)}_{i k}}) \end{matrix}

…”

Section: Methodsmentioning

confidence: 99%

Impact of Climate Change on Surface Stirring and Transport in the Mediterranean Sea

Ser‐Giacomi

Sánchez

Soto‐Navarro

et al. 2020

Geophysical Research Letters

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Understanding how climate change will affect oceanic fluid transport is crucial for environmental applications and human activities. However, a synoptic characterization of the influence of climate change on mesoscale stirring and transport in the surface ocean is missing. To bridge this gap, we exploit a high-resolution, fully coupled climate model of the Mediterranean basin using a Network Theory approach. We project significant increases of horizontal stirring and kinetic energies in the next century, likely due to increments of available potential energy. The future evolution of basin-scale transport patterns hints at a rearrangement of the main hydrodynamic provinces, defined as regions of the surface ocean that are well mixed internally but with minimal cross-flow across their boundaries. This results in increased heterogeneity of province sizes and stronger mixing in their interiors. Our approach can be readily applied to other oceanic regions, providing information for the present and future marine spatial planning. Plain Language Summary Transport and mixing of water masses driven by ocean currents influence a variety of fundamental processes, including heat redistribution, ecosystem functioning, and pollutants spreading. Therefore, understanding how fluid transport will be affected by climate change is crucial, in particular in the ocean surface, where marine life and human activities are concentrated. Here, we exploit a state-of-the-art climate model over the Mediterranean basin using a novel methodology which integrates Network Theory concepts with Lagrangian modeling. We assess past conditions and future changes at climatic scales of ocean stirring and transport over the entire basin. Our results reveal a significant increment of surface stirring linked to an increase of currents kinetic energy, which in turn could be ascribed to increments of available potential energy. We then provide a regionalization of the ocean surface based on hydrodynamic provinces that are well mixed internally but with little leaking across their boundaries. Our model project an increased heterogeneity of province sizes and a stronger mixing in their interiors, while their mean area and coherence remain unaffected. Our approach could be applied to other oceanic domains and help designing adaptive strategies for marine spatial planning.

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\begin{matrix} alignleft \\ align-1 H^{I} {(t_{0}, τ)}_{i} & align-2 = - \frac{1}{τ} \sum_{j = 1}^{N} (\frac{P {(t_{0}, τ)}_{j i}}{\sum_{k = 1}^{N} P {(t_{0}, τ)}_{k i}}) \log (\frac{P {(t_{0}, τ)}_{j i}}{\sum_{k = 1}^{N} P {(t_{0}, τ)}_{k i}}), \end{matrix}

\begin{matrix} alignleft \\ align-1 H^{O} {(t_{0}, τ)}_{i} & align-2 = - \frac{1}{τ} \sum_{j = 1}^{N} (\frac{P {(t_{0}, τ)}_{i j}}{\sum_{k = 1}^{N} P {(t_{0}, τ)}_{i k}}) \end{matrix}

…”

Section: Methodsmentioning

confidence: 99%

Impact of Climate Change on Surface Stirring and Transport in the Mediterranean Sea

Ser‐Giacomi

Sánchez

Soto‐Navarro

et al. 2020

Geophysical Research Letters

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“…IBMs are particularly well-suited to explicitly modelling 3D aquatic ecosystems in complex flow regimes, wherein agents must interact individually with their local environment (a turbulent eddy, for instance, or a nutrient patch), and/or with each other, and where complex ecosystem dynamics can emerge naturally from the collective behaviour of individuals in the model. IBMs of this kind have already seen active service in ecological research pertaining to questions as diverse as microbial patchiness 32 and evolutionary dynamics 58 , spatial dynamics of fish 59 , fish larvae 60 and sea turtle hatchlings 61 , thermal responses in phytoplankton populations 62 and the dynamics of ocean plastics [63][64][65] . Here we describe the mathematical framework of our microbial motility model and its implementation using the OceanParcels 66,67 Lagrangian analysis toolkit.…”

Section: Gyrotactic Microbe Ibmmentioning

confidence: 99%

Small-scale convective turbulence constrains microbial patchiness

Christensen¹,

Piggott²,

Sebille³

et al. 2021

Preprint

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Microbes play a primary role in aquatic ecosystems and biogeochemical cycles. Patchiness is a critical component of these activities, influencing biological productivity, nutrient cycling and dynamics across trophic levels. Incorporating spatial dynamics into microbial models is a long-standing challenge, particularly where small-scale turbulence is involved. Here, we combine a realistic simulation of turbulence with an individual-based microbial model to test the key hypothesis that the coupling of motility and turbulence drives intense microscale patchiness. We find that such patchiness is depth-structured and requires high motility: Near the fluid surface, strong convective turbulence overpowers motility, homogenising motile and non-motile microbes equally. In deeper, thermocline-like conditions, highly motile microbes are up to 1.6-fold more patch-concentrated than non-motile microbes. Our results demonstrate that the delicate balance of turbulence and motility that triggers micro-scale patchiness is not a ubiquitous consequence of motility, and that the intensity of such patchiness in real-world conditions is modest.

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“…large fluid bodies with homogeneous flow properties. Examples of those are, on a small scale, Lagrangian coherent structures (LCSs) (Haller, 2015, Wichmann et al, 2021, and oceanic basins on a larger scale (Wichmann et al, 2019a. The gain of a Lagrangian approach is the quantification of the connectivity between the basins, hence extracting trends between flow origins-and destinations.…”

Section: Study Objectives In Lagrangian Ocean Analysismentioning

confidence: 99%

Practices, Pitfalls and Guidelines in Visualising Lagrangian Ocean Analyses

Kehl

Fischer

Sebille

2021

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The Lagrangian analysis of particulate matter, biota and drifters, which are dispersed by turbulent fluid currents, is a cornerstone of oceanographic studies, covering diverse study objectives. The results of Lagrangian simulations and observations is predominantly visualised by means of easy-access plotting interfaces and simple presentation techniques. We analysed over 50 publications from the years 2010–2020 with respect to their visual design to deduce common visualisation practices in the domain. Individual figures are analysed towards adherence to visualisation best-practices, algebraic visualisation guidelines and the IPCC visual style guide. In this article, we present the resulting best-practices and common pitfalls in the design of Lagrangian ocean visualisations. Based on this visual study, we highlight that raising awareness of established visual guidelines may have a higher impact on improving the visual quality of publications in oceanography than the vigorous development of more general-purpose visualisation tools.

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Mixing of passive tracers at the ocean surface and its implications for plastic transport modelling

Cited by 13 publications

References 29 publications

Impact of Climate Change on Surface Stirring and Transport in the Mediterranean Sea

Impact of Climate Change on Surface Stirring and Transport in the Mediterranean Sea

Small-scale convective turbulence constrains microbial patchiness

Practices, Pitfalls and Guidelines in Visualising Lagrangian Ocean Analyses

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