Articles | Volume 16, issue 18
https://doi.org/10.5194/gmd-16-5339-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5339-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
19 Sep 2023
Development and technical paper |
| 19 Sep 2023
| 19 Sep 2023
A comparison of Eulerian and Lagrangian methods for vertical particle transport in the water column
SINTEF Ocean AS, Trondheim, Norway
Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
Ruben Kristiansen
Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway
Raymond Nepstad
SINTEF Ocean AS, Trondheim, Norway
Erik van Sebille
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Andy M. Booth
SINTEF Ocean AS, Trondheim, Norway
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Geosci. Model Dev., 13, 5935–5957, https://doi.org/10.5194/gmd-13-5935-2020, https://doi.org/10.5194/gmd-13-5935-2020, 2020
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In applied oceanography, a common task is to calculate the trajectory of objects floating at the sea surface or submerged in the water. We have investigated different numerical methods for doing such calculations and discuss the benefits and challenges of some common methods. We then propose a small change to some common methods that make them more efficient for this particular application. This will allow researchers to obtain more accurate answers with fewer computer resources.
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Simulations of hypothetical oil spills are presented to investigate how the vertical mixing of oil affects transport towards various directions. It is shown that the horizontal transport of oil greatly varies for different oil types and weather conditions. These differences are a consequence of the entrainment of oil from the surface into the ocean. While oil spills often get entrained into the water by waves, we show that submerged oil typically resurfaces after a few hours or days.
Frances Wijnen, Madelijn Strick, Mark Bos, and Erik van Sebille
EGUsphere, https://doi.org/10.5194/egusphere-2023-2730, https://doi.org/10.5194/egusphere-2023-2730, 2023
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Climate scientists are urged to communicate climate science, there is very little evidence about what types of communication work well for which audiences. We have performed a systematic literature review to analyse what is known about the efficacy of climate communication by scientists. While we have found more than 60 articles in the last ten years about climate communication activities by scientists, only seven of these included some form of evaluation of the impact of the activity.
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EGUsphere, https://doi.org/10.5194/egusphere-2023-315, https://doi.org/10.5194/egusphere-2023-315, 2023
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Stefanie L. Ypma, Quinten Bohte, Alexander Forryan, Alberto C. Naveira Garabato, Andy Donnelly, and Erik van Sebille
Ocean Sci., 18, 1477–1490, https://doi.org/10.5194/os-18-1477-2022, https://doi.org/10.5194/os-18-1477-2022, 2022
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Biogeosciences, 19, 2211–2234, https://doi.org/10.5194/bg-19-2211-2022, https://doi.org/10.5194/bg-19-2211-2022, 2022
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Victor Onink, Erik van Sebille, and Charlotte Laufkötter
Geosci. Model Dev., 15, 1995–2012, https://doi.org/10.5194/gmd-15-1995-2022, https://doi.org/10.5194/gmd-15-1995-2022, 2022
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Turbulent mixing is a vital process in 3D modeling of particle transport in the ocean. However, since turbulence occurs on very short spatial scales and timescales, large-scale ocean models generally have highly simplified turbulence representations. We have developed parametrizations for the vertical turbulent transport of buoyant particles that can be easily applied in a large-scale particle tracking model. The predicted vertical concentration profiles match microplastic observations well.
Mikael L. A. Kaandorp, Stefanie L. Ypma, Marijke Boonstra, Henk A. Dijkstra, and Erik van Sebille
Ocean Sci., 18, 269–293, https://doi.org/10.5194/os-18-269-2022, https://doi.org/10.5194/os-18-269-2022, 2022
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A large amount of marine litter, such as plastics, is located on or around beaches. Both the total amount of this litter and its transport are poorly understood. We investigate this by training a machine learning model with data of cleanup efforts on Dutch beaches between 2014 and 2019, obtained by about 14 000 volunteers. We find that Dutch beaches contain up to 30 000 kg of litter, largely depending on tides, oceanic transport, and how exposed the beaches are.
Peter D. Nooteboom, Peter K. Bijl, Christian Kehl, Erik van Sebille, Martin Ziegler, Anna S. von der Heydt, and Henk A. Dijkstra
Earth Syst. Dynam., 13, 357–371, https://doi.org/10.5194/esd-13-357-2022, https://doi.org/10.5194/esd-13-357-2022, 2022
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Having descended through the water column, microplankton in ocean sediments represents the ocean surface environment and is used as an archive of past and present surface oceanographic conditions. However, this microplankton is advected by turbulent ocean currents during its sinking journey. We use simulations of sinking particles to define ocean bottom provinces and detect these provinces in datasets of sedimentary microplankton, which has implications for palaeoclimate reconstructions.
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ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2021, 217–224, https://doi.org/10.5194/isprs-annals-V-4-2021-217-2021, https://doi.org/10.5194/isprs-annals-V-4-2021-217-2021, 2021
Rebeca de la Fuente, Gábor Drótos, Emilio Hernández-García, Cristóbal López, and Erik van Sebille
Ocean Sci., 17, 431–453, https://doi.org/10.5194/os-17-431-2021, https://doi.org/10.5194/os-17-431-2021, 2021
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Plastic pollution is a major environmental issue affecting the oceans. The number of floating and sedimented pieces has been quantified by several studies. But their abundance in the water column remains mostly unknown. To fill this gap we model the dynamics of a particular type of particle, rigid microplastics sinking rapidly in open sea in the Mediterranean. We find they represent a small but appreciable fraction of the total sea plastic and discuss characteristics of their sinking motion.
David Wichmann, Christian Kehl, Henk A. Dijkstra, and Erik van Sebille
Nonlin. Processes Geophys., 28, 43–59, https://doi.org/10.5194/npg-28-43-2021, https://doi.org/10.5194/npg-28-43-2021, 2021
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Fluid parcels transported in complicated flows often contain subsets of particles that stay close over finite time intervals. We propose a new method for detecting finite-time coherent sets based on the density-based clustering technique of ordering points to identify the clustering structure (OPTICS). Unlike previous methods, our method has an intrinsic notion of coherent sets at different spatial scales. OPTICS is readily implemented in the SciPy sklearn package, making it easy to use.
Chris S. M. Turney, Richard T. Jones, Nicholas P. McKay, Erik van Sebille, Zoë A. Thomas, Claus-Dieter Hillenbrand, and Christopher J. Fogwill
Earth Syst. Sci. Data, 12, 3341–3356, https://doi.org/10.5194/essd-12-3341-2020, https://doi.org/10.5194/essd-12-3341-2020, 2020
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The Last Interglacial (129–116 ka) experienced global temperatures and sea levels higher than today. The direct contribution of warmer conditions to global sea level (thermosteric) are uncertain. We report a global network of sea surface temperatures. We find mean global annual temperature anomalies of 0.2 ± 0.1˚C and an early maximum peak of 0.9 ± 0.1˚C. Our reconstruction suggests warmer waters contributed on average 0.08 ± 0.1 m and a peak contribution of 0.39 ± 0.1 m to global sea level.
Tor Nordam and Rodrigo Duran
Geosci. Model Dev., 13, 5935–5957, https://doi.org/10.5194/gmd-13-5935-2020, https://doi.org/10.5194/gmd-13-5935-2020, 2020
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Linda K. Dämmer, Lennart de Nooijer, Erik van Sebille, Jan G. Haak, and Gert-Jan Reichart
Clim. Past, 16, 2401–2414, https://doi.org/10.5194/cp-16-2401-2020, https://doi.org/10.5194/cp-16-2401-2020, 2020
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David Wichmann, Christian Kehl, Henk A. Dijkstra, and Erik van Sebille
Nonlin. Processes Geophys., 27, 501–518, https://doi.org/10.5194/npg-27-501-2020, https://doi.org/10.5194/npg-27-501-2020, 2020
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The surface transport of heat, nutrients and plastic in the North Atlantic Ocean is organized into large-scale flow structures. We propose a new and simple method to detect such features in ocean drifter data sets by identifying groups of trajectories with similar dynamical behaviour using network theory. We successfully detect well-known regions such as the Subpolar and Subtropical gyres, the Western Boundary Current region and the Caribbean Sea.
Mirjam van der Mheen, Erik van Sebille, and Charitha Pattiaratchi
Ocean Sci., 16, 1317–1336, https://doi.org/10.5194/os-16-1317-2020, https://doi.org/10.5194/os-16-1317-2020, 2020
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A large percentage of global ocean plastic enters the Indian Ocean through rivers, but the fate of these plastics is generally unknown. In this paper, we use computer simulations to show that floating plastics
beachand end up on coastlines throughout the Indian Ocean. Coastlines where a lot of plastic enters the ocean are heavily affected by beaching plastic, but plastics can also beach far from the source on remote islands and countries that contribute little plastic pollution of their own.
Erik van Sebille, Philippe Delandmeter, John Schofield, Britta Denise Hardesty, Jen Jones, and Andy Donnelly
Ocean Sci., 15, 1341–1349, https://doi.org/10.5194/os-15-1341-2019, https://doi.org/10.5194/os-15-1341-2019, 2019
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The Galápagos Archipelago and Galápagos Marine Reserve are among the world's most iconic wildlife refuges. Yet, plastic litter is now found even in this remote archipelago. It is unclear where this plastic originates from. In this study, we show that remote coastal sources of plastic pollution are fairly localized and limited to South American and Central American coastlines. Identifying how plastic ends up in the Galápagos aids integrated management opportunities to reduce plastic pollution.
Philippe Delandmeter and Erik van Sebille
Geosci. Model Dev., 12, 3571–3584, https://doi.org/10.5194/gmd-12-3571-2019, https://doi.org/10.5194/gmd-12-3571-2019, 2019
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Parcels is a framework to compute how ocean currents transport
stuffsuch as plankton and plastic around. In the latest version 2.0 of Parcels, we focus on more accurate interpolation schemes and implement methods to seamlessly combine data from different sources (such as winds and currents, possibly in different regions). We show that this framework is very efficient for tracking how microplastic is transported through the North Sea into the Arctic.
Johannes Röhrs, Knut-Frode Dagestad, Helene Asbjørnsen, Tor Nordam, Jørgen Skancke, Cathleen E. Jones, and Camilla Brekke
Ocean Sci., 14, 1581–1601, https://doi.org/10.5194/os-14-1581-2018, https://doi.org/10.5194/os-14-1581-2018, 2018
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Simulations of hypothetical oil spills are presented to investigate how the vertical mixing of oil affects transport towards various directions. It is shown that the horizontal transport of oil greatly varies for different oil types and weather conditions. These differences are a consequence of the entrainment of oil from the surface into the ocean. While oil spills often get entrained into the water by waves, we show that submerged oil typically resurfaces after a few hours or days.
Fabrice Ardhuin, Yevgueny Aksenov, Alvise Benetazzo, Laurent Bertino, Peter Brandt, Eric Caubet, Bertrand Chapron, Fabrice Collard, Sophie Cravatte, Jean-Marc Delouis, Frederic Dias, Gérald Dibarboure, Lucile Gaultier, Johnny Johannessen, Anton Korosov, Georgy Manucharyan, Dimitris Menemenlis, Melisa Menendez, Goulven Monnier, Alexis Mouche, Frédéric Nouguier, George Nurser, Pierre Rampal, Ad Reniers, Ernesto Rodriguez, Justin Stopa, Céline Tison, Clément Ubelmann, Erik van Sebille, and Jiping Xie
Ocean Sci., 14, 337–354, https://doi.org/10.5194/os-14-337-2018, https://doi.org/10.5194/os-14-337-2018, 2018
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The Sea surface KInematics Multiscale (SKIM) monitoring mission is a proposal for a future satellite that is designed to measure ocean currents and waves. Using a Doppler radar, the accurate measurement of currents requires the removal of the mean velocity due to ocean wave motions. This paper describes the main processing steps needed to produce currents and wave data from the radar measurements. With this technique, SKIM can provide unprecedented coverage and resolution, over the global ocean.
Michael Lange and Erik van Sebille
Geosci. Model Dev., 10, 4175–4186, https://doi.org/10.5194/gmd-10-4175-2017, https://doi.org/10.5194/gmd-10-4175-2017, 2017
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Here, we present version 0.9 of Parcels (Probably A Really Computationally Efficient Lagrangian Simulator). Parcels is an experimental prototype code aimed at exploring novel approaches for Lagrangian tracking of virtual ocean particles in the petascale age. The modularity, flexibility and scalability will allow the code to be used to track water, nutrients, microbes, plankton, plastic and even fish.
Chris S. M. Turney, Christopher J. Fogwill, Jonathan G. Palmer, Erik van Sebille, Zoë Thomas, Matt McGlone, Sarah Richardson, Janet M. Wilmshurst, Pavla Fenwick, Violette Zunz, Hugues Goosse, Kerry-Jayne Wilson, Lionel Carter, Mathew Lipson, Richard T. Jones, Melanie Harsch, Graeme Clark, Ezequiel Marzinelli, Tracey Rogers, Eleanor Rainsley, Laura Ciasto, Stephanie Waterman, Elizabeth R. Thomas, and Martin Visbeck
Clim. Past, 13, 231–248, https://doi.org/10.5194/cp-13-231-2017, https://doi.org/10.5194/cp-13-231-2017, 2017
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The Southern Ocean plays a fundamental role in global climate but suffers from a dearth of observational data. As the Australasian Antarctic Expedition 2013–2014 we have developed the first annually resolved temperature record using trees from subantarctic southwest Pacific (52–54˚S) to extend the climate record back to 1870. With modelling we show today's high climate variability became established in the ~1940s and likely driven by a Rossby wave response originating from the tropical Pacific.
Christopher J. Fogwill, Erik van Sebille, Eva A. Cougnon, Chris S. M. Turney, Steve R. Rintoul, Benjamin K. Galton-Fenzi, Graeme F. Clark, E. M. Marzinelli, Eleanor B. Rainsley, and Lionel Carter
The Cryosphere, 10, 2603–2609, https://doi.org/10.5194/tc-10-2603-2016, https://doi.org/10.5194/tc-10-2603-2016, 2016
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Here we report new data from in situ oceanographic surveys and high-resolution ocean modelling experiments in the Commonwealth Bay region of East Antarctica, where in 2010 there was a major reconfiguration of the regional icescape due to the collision of the 97 km long iceberg B09B with the Mertz Glacier tongue. Here we compare post-calving observations with high-resolution ocean modelling which suggest that this reconfiguration has led to the development of a new polynya off Commonwealth Bay.
Paulina Cetina-Heredia, Erik van Sebille, Richard Matear, and Moninya Roughan
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-53, https://doi.org/10.5194/bg-2016-53, 2016
Revised manuscript not accepted
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Characterizing phytoplankton growth influences fisheries and climate. We use a lagrangian approach to identify phytoplankton blooms in the Great Australian Bight (GAB), and associate them with nitrate sources. We find that 88 % of the nitrate utilized in blooms is originated between the GAB and the SubAntarctic Front. Large nitrate concentrations are supplied at depth but do not reach the euphotic zone often. As a result, 55 % of blooms utilize nitrate supplied in the top 100 m.
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A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
Xiaqiong Zhou and Hann-Ming Henry Juang
Geosci. Model Dev., 16, 3263–3274, https://doi.org/10.5194/gmd-16-3263-2023, https://doi.org/10.5194/gmd-16-3263-2023, 2023
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The National Centers for Environmental Prediction Global Forecast System version 16 experienced model instability failures in real-time runs resolved by increasing the minimum thickness depth parameter. Further investigation revealed that the issue was caused by the advection of geopotential heights at the model's layer interfaces. By replacing high-order boundary conditions with zero-gradient boundary conditions for interface-wind reconstruction, the instability was effectively addressed.
Grant T. Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott D. King
Geosci. Model Dev., 16, 3221–3239, https://doi.org/10.5194/gmd-16-3221-2023, https://doi.org/10.5194/gmd-16-3221-2023, 2023
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Due to the increasing availability of high-performance computing over the past few decades, numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously known information to modern methodologies.
Arjun Babu Nellikkattil, Travis Allen O’Brien, Danielle Lemmon, June-Yi Lee, and Jung-Eun Chu
EGUsphere, https://doi.org/10.5194/egusphere-2023-592, https://doi.org/10.5194/egusphere-2023-592, 2023
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The exponential increases in the climate and weather data demand computationally efficient and mathematically sound feature extraction algorithms to identify phenomenons such as atmospheric rivers, cyclones, sea surface temperature fronts, jet streams, etc. In this study, we present an innovative generalized framework for extracting two and three-dimensional features from gridded datasets using the local geometric shape of the input fields.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
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This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
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We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendriks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-309, https://doi.org/10.5194/gmd-2022-309, 2023
Revised manuscript accepted for GMD
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
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Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
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In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
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This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
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This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, https://doi.org/10.5194/gmd-16-961-2023, 2023
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We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
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We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
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In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Boris Gailleton, Luca Malatesta, Guillaume Cordonnier, and Jean Braun
EGUsphere, https://doi.org/10.5194/egusphere-2022-1394, https://doi.org/10.5194/egusphere-2022-1394, 2023
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This contribution presents a new method to numerically explore the evolution of mountain ranges and surroundings area. The methods helps monitoring with details the timing and travel path of material eroded from the mountain ranges. It suits particularly well studies juxtaposing different domains – lakes or multiple rock types for example – and allow the combination of different process together.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
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While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
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A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764, https://doi.org/10.5194/gmd-15-8749-2022, https://doi.org/10.5194/gmd-15-8749-2022, 2022
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Knowledge of the internal structures of the major continental ice sheets is improving, thanks to new investigative techniques. These structures are an essential indication of the flow behavior and dynamics of ice transport, which in turn is important for understanding the actual impact of the vast amounts of water trapped in continental ice sheets on global sea-level rise. The software studied here is specifically designed to simulate such structures and their evolution.
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667, https://doi.org/10.5194/gmd-15-8639-2022, https://doi.org/10.5194/gmd-15-8639-2022, 2022
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Finite-element methods (FEMs) permit the use of more flexible unstructured meshes but are rarely used in full waveform inversions (FWIs), an iterative process that reconstructs velocity models of earth’s subsurface, due to computational and memory storage costs. To reduce those costs, novel software is presented allowing the use of high-order mass-lumped FEMs on triangular meshes, together with a material-property mesh-adaptation performance-enhancing strategy, enabling its use in FWIs.
Konstantinos Papadakis, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Markku Alho, Maxime Grandin, Maxime Dubart, Lucile Turc, Hongyang Zhou, Konstantinos Horaites, Ivan Zaitsev, Giulia Cozzani, Maarja Bussov, Evgeny Gordeev, Fasil Tesema, Harriet George, Jonas Suni, Vertti Tarvus, and Minna Palmroth
Geosci. Model Dev., 15, 7903–7912, https://doi.org/10.5194/gmd-15-7903-2022, https://doi.org/10.5194/gmd-15-7903-2022, 2022
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Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global scale. As 6D simulations require enormous amounts of computational resources, Vlasiator uses adaptive mesh refinement (AMR) to lighten the computational burden. However, due to Vlasiator’s grid topology, AMR simulations suffer from grid aliasing artifacts that affect the global results. In this work, we present and evaluate the performance of a mechanism for alleviating those artifacts.
Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramón, James Runnalls, Fotis Georgatos, Camille Minaudo, and Jonas Šukys
Geosci. Model Dev., 15, 7715–7730, https://doi.org/10.5194/gmd-15-7715-2022, https://doi.org/10.5194/gmd-15-7715-2022, 2022
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Reconciling the differences between numerical model predictions and observational data is always a challenge. In this paper, we investigate the viability of a novel approach to the calibration of a three-dimensional hydrodynamic model of Lake Geneva, where the target parameters are inferred in terms of distributions. We employ a filtering technique that generates physically consistent model trajectories and implement a neural network to enable bulk-to-skin temperature conversion.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Lixin Wu, Dexun Chen, Yang Gao, Zhiqiang Wei, Dongning Jia, and Xiaopei Lin
Geosci. Model Dev., 15, 6695–6708, https://doi.org/10.5194/gmd-15-6695-2022, https://doi.org/10.5194/gmd-15-6695-2022, 2022
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To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
Vijay S. Mahadevan, Jorge E. Guerra, Xiangmin Jiao, Paul Kuberry, Yipeng Li, Paul Ullrich, David Marsico, Robert Jacob, Pavel Bochev, and Philip Jones
Geosci. Model Dev., 15, 6601–6635, https://doi.org/10.5194/gmd-15-6601-2022, https://doi.org/10.5194/gmd-15-6601-2022, 2022
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Coupled Earth system models require transfer of field data between multiple components with varying spatial resolutions to determine the correct climate behavior. We present the Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol to evaluate the accuracy, conservation properties, monotonicity, and local feature preservation of four different remapper algorithms for various unstructured mesh problems of interest. Future extensions to more practical use cases are also discussed.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
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Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Andrew M. Bradley, Peter A. Bosler, and Oksana Guba
Geosci. Model Dev., 15, 6285–6310, https://doi.org/10.5194/gmd-15-6285-2022, https://doi.org/10.5194/gmd-15-6285-2022, 2022
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Tracer transport in atmosphere models can be computationally expensive. We describe a flexible and efficient interpolation semi-Lagrangian method, the Islet method. It permits using up to three grids that share an element grid: a dynamics grid for computing quantities such as the wind velocity; a physics parameterizations grid; and a tracer grid. The Islet method performs well on a number of verification problems and achieves high performance in the E3SM Atmosphere Model version 2.
Léo Pujol, Pierre-André Garambois, and Jérôme Monnier
Geosci. Model Dev., 15, 6085–6113, https://doi.org/10.5194/gmd-15-6085-2022, https://doi.org/10.5194/gmd-15-6085-2022, 2022
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This contribution presents a new numerical model for representing hydraulic–hydrological quantities at the basin scale. It allows modeling large areas at a low computational cost, with fine zooms where needed. It allows the integration of local and satellite measurements, via data assimilation methods, to improve the model's match to observations. Using this capability, good matches to in situ observations are obtained on a model of the complex Adour river network with fine zooms on floodplains.
Ludovic Räss, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
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Continuum mechanics-based modelling of physical processes at large scale requires huge computational resources provided by massively parallel hardware such as graphical processing units. We present a suite of numerical algorithms, implemented using the Julia language, that efficiently leverages the parallelism. We demonstrate that our implementation is efficient, scalable and robust and showcase applications to various geophysical problems.
Meriem Krouma, Pascal Yiou, Céline Déandreis, and Soulivanh Thao
Geosci. Model Dev., 15, 4941–4958, https://doi.org/10.5194/gmd-15-4941-2022, https://doi.org/10.5194/gmd-15-4941-2022, 2022
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We evaluated the skill of a stochastic weather generator (SWG) to forecast precipitation at different time scales and in different areas of western Europe from analogs of Z500 hPa. The SWG has the skill to simulate precipitation for 5 and 10 d. We found that forecast weaknesses can be associated with specific weather patterns. The comparison with ECMWF forecasts confirms the skill of our model. This work is important because it provides information about weather forecasts over specific areas.
Piotr Dziekan and Piotr Zmijewski
Geosci. Model Dev., 15, 4489–4501, https://doi.org/10.5194/gmd-15-4489-2022, https://doi.org/10.5194/gmd-15-4489-2022, 2022
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Detailed computer simulations of clouds are important for understanding Earth's atmosphere and climate. The paper describes how the UWLCM has been adapted to work on supercomputers. A distinctive feature of UWLCM is that air flow is calculated by processors at the same time as cloud droplets are modeled by graphics cards. Thanks to this, use of computing resources is maximized and the time to complete simulations of large domains is not affected by communications between supercomputer nodes.
Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-86, https://doi.org/10.5194/gmd-2022-86, 2022
Revised manuscript accepted for GMD
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Coupled reaction-transport modeling is an established and highly beneficial method for studying natural and synthetic porous material with applications ranging from industrial processes to natural decompositions in terrestrial environments. Up to now, a framework that explicitly considers the porous structure (e.g., from µ-CT images), for modeling the transport of reactive species is missing. We presented a model that overcomes this limitation and represents a novel numerical simulation toolbox.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 15, 4147–4161, https://doi.org/10.5194/gmd-15-4147-2022, https://doi.org/10.5194/gmd-15-4147-2022, 2022
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A scale-dependent error growth described by a power law or by a quadratic hypothesis is studied in Lorenz’s system with three spatiotemporal levels. The validity of power law is extended by including a saturation effect. The quadratic hypothesis can only serve as a first guess. In addition, we study the initial error growth for the ECMWF forecast system. Fitting the parameters, we conclude that there is an intrinsic limit of predictability after 22 days.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
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In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Navjot Kukreja, Jan Hückelheim, Mathias Louboutin, John Washbourne, Paul H. J. Kelly, and Gerard J. Gorman
Geosci. Model Dev., 15, 3815–3829, https://doi.org/10.5194/gmd-15-3815-2022, https://doi.org/10.5194/gmd-15-3815-2022, 2022
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Full waveform inversion (FWI) is a partial-differential equation (PDE)-constrained optimization problem that is notorious for its high computational load and memory footprint. In this paper we present a method that combines recomputation with lossy compression to accelerate the computation with minimal loss of precision in the results. We show this using experiments running FWI with a variety of compression settings on a popular academic dataset.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 15, 3641–3662, https://doi.org/10.5194/gmd-15-3641-2022, https://doi.org/10.5194/gmd-15-3641-2022, 2022
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This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Romit Maulik, Vishwas Rao, Jiali Wang, Gianmarco Mengaldo, Emil Constantinescu, Bethany Lusch, Prasanna Balaprakash, Ian Foster, and Rao Kotamarthi
Geosci. Model Dev., 15, 3433–3445, https://doi.org/10.5194/gmd-15-3433-2022, https://doi.org/10.5194/gmd-15-3433-2022, 2022
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In numerical weather prediction, data assimilation is frequently utilized to enhance the accuracy of forecasts from equation-based models. In this work we use a machine learning framework that approximates a complex dynamical system given by the geopotential height. Instead of using an equation-based model, we utilize this machine-learned alternative to dramatically accelerate both the forecast and the assimilation of data, thereby reducing need for large computational resources.
Hiromasa Yoshimura
Geosci. Model Dev., 15, 2561–2597, https://doi.org/10.5194/gmd-15-2561-2022, https://doi.org/10.5194/gmd-15-2561-2022, 2022
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This paper proposes a new double Fourier series (DFS) method on a sphere that improves the numerical stability of a model compared with conventional DFS methods. The shallow-water model and the advection model using the new DFS method give stable results without the appearance of high-wavenumber noise near the poles. The model using the new DFS method is faster than the model using spherical harmonics (especially at high resolutions) and gives almost the same results.
Mirko Mälicke
Geosci. Model Dev., 15, 2505–2532, https://doi.org/10.5194/gmd-15-2505-2022, https://doi.org/10.5194/gmd-15-2505-2022, 2022
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I preset SciKit-GStat, a well-documented and tested Python package for variogram estimation. The variogram is the core means of geostatistics, which almost all other methods rely on. Geostatistical interpolation and field generation are widely spread in geoscience, i.e., for data assimilation or modeling.
While SciKit-GStat focuses on effective and intuitive variogram estimation, it can interface with other prominent packages and make its variograms available for a multitude of methods.
Christopher J. L. D'Amboise, Michael Neuhauser, Michaela Teich, Andreas Huber, Andreas Kofler, Frank Perzl, Reinhard Fromm, Karl Kleemayr, and Jan-Thomas Fischer
Geosci. Model Dev., 15, 2423–2439, https://doi.org/10.5194/gmd-15-2423-2022, https://doi.org/10.5194/gmd-15-2423-2022, 2022
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The term gravitational mass flow (GMF) covers various natural hazard processes such as snow avalanches, rockfall, landslides, and debris flows. Here we present the open-source GMF simulation tool Flow-Py. The model equations are based on simple geometrical relations in three-dimensional terrain. We show that Flow-Py is an educational, innovative GMF simulation tool with three computational experiments: 1. validation of implementation, 2. performance, and 3. expandability.
Evan Baker, Anna B. Harper, Daniel Williamson, and Peter Challenor
Geosci. Model Dev., 15, 1913–1929, https://doi.org/10.5194/gmd-15-1913-2022, https://doi.org/10.5194/gmd-15-1913-2022, 2022
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We have adapted machine learning techniques to build a model of the land surface in Great Britain. The model was trained using data from a very complex land surface model called JULES. Our model is faster at producing simulations and predictions and can investigate many different scenarios, which can be used to improve our understanding of the climate and could also be used to help make local decisions.
Daichun Wang, Wei You, Zengliang Zang, Xiaobin Pan, Yiwen Hu, and Yanfei Liang
Geosci. Model Dev., 15, 1821–1840, https://doi.org/10.5194/gmd-15-1821-2022, https://doi.org/10.5194/gmd-15-1821-2022, 2022
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This paper presents a 3D variational data assimilation system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, which was developed for a size-resolved sectional model in WRF-Chem. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was designed. The results show that Himawari-8 AOT assimilation can significantly improve model aerosol analyses and forecasts.
Kevin Bulthuis and Eric Larour
Geosci. Model Dev., 15, 1195–1217, https://doi.org/10.5194/gmd-15-1195-2022, https://doi.org/10.5194/gmd-15-1195-2022, 2022
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We present and implement a stochastic solver to sample spatially and temporal varying uncertain input parameters in the Ice-sheet and Sea-level System Model, such as ice thickness or surface mass balance. We represent these sources of uncertainty using Gaussian random fields with Matérn covariance function. We generate random samples of this random field using an efficient computational approach based on solving a stochastic partial differential equation.
Cited articles
Abuhegazy, M., Talaat, K., Anderoglu, O., and Poroseva, S. V.: Numerical
investigation of aerosol transport in a classroom with relevance to COVID-19,
Phys. Fluids, 32, 103311, https://doi.org/10.1063/5.0029118, 2020. a
Benson, D. A., Aquino, T., Bolster, D., Engdahl, N., Henri, C. V., and
Fernandez-Garcia, D.: A comparison of Eulerian and Lagrangian transport and
non-linear reaction algorithms, Adv. Water Resour., 99, 15–37,
https://doi.org/10.1016/j.advwatres.2016.11.003, 2017. a
Craig, P. D. and Banner, M. L.: Modeling wave-enhanced turbulence in the ocean
surface layer, J. Phys. Oceanogr., 24, 2546–2559,
https://doi.org/10.1175/1520-0485(1994)024<2546:MWETIT>2.0.CO;2, 1994. a
Cui, F., Boufadel, M. C., Geng, X., Gao, F., Zhao, L., King, T., and Lee, K.:
Oil Droplets Transport Under a Deep-Water Plunging Breaker: Impact of Droplet
Inertia, J. Geophys. Res.-Oceans, 123, 9082–9100,
https://doi.org/10.1029/2018JC014495, 2018. a
Cui, F., Zhao, L., Daskiran, C., King, T., Lee, K., Katz, J., and Boufadel,
M. C.: Modeling oil dispersion under breaking waves. Part II: Coupling
Lagrangian particle tracking with population balance model, Environ. Fluid
Mech., 20, 1553–1578, https://doi.org/10.1007/s10652-020-09759-1, 2020. a, b
de la Fuente, R., Drótos, G., Hernández-García, E., López, C., and van Sebille, E.: Sinking microplastics in the water column: simulations in the Mediterranean Sea, Ocean Sci., 17, 431–453, https://doi.org/10.5194/os-17-431-2021, 2021. a
Delandmeter, P. and van Sebille, E.: The Parcels v2.0 Lagrangian framework: new field interpolation schemes, Geosci. Model Dev., 12, 3571–3584, https://doi.org/10.5194/gmd-12-3571-2019, 2019. a
Devroye, L.: Non-uniform random variate generation, Springer-Verlag, New York, https://doi.org/10.1007/978-1-4613-8643-8,
1986. a
Dissanayake, A. L., DeGraff, J. A., Yapa, P. D., Nakata, K., Ishihara, Y., and
Yabe, I.: Modeling the impact of CO2 releases in Kagoshima Bay, Japan, J.
Hydro-Environ. Res., 6, 195–208, https://doi.org/10.1016/j.jher.2012.02.001, 2012. a
Dissanayake, A. L., Yapa, P. D., and Nakata, K.: Simulation of hydrothermal
vents in the Izena Cauldron, Mid Okinawa trough, Japan and other Pacific
locations, J. Hydro-Environ. Res., 8, 343–357,
https://doi.org/10.1016/j.jher.2014.05.003, 2014. a
Dugstad, J. S., Koszalka, I. M., Isachsen, P. E., Dagestad, K.-F., and Fer, I.:
Vertical Structure and Seasonal Variability of the Inflow to the Lofoten
Basin Inferred From High-Resolution Lagrangian Simulations, J. Geophys.
Res.-Oceans, 124, 9384–9403, https://doi.org/10.1029/2019JC015474, 2019. a
Elliott, A., Hurford, N., and Penn, C.: Shear diffusion and the spreading of
oil slicks, Mar. Pollut. Bull., 17, 308–313, 1986. a
Fay, B., Glaab, H., Jacobsen, I., and Schrodin, R.: Evaluation of Eulerian and
Lagrangian atmospheric transport models at the Deutscher Wetterdienst using
ANATEX surface tracer data, Atmos. Environ., 29, 2485–2497,
https://doi.org/10.1016/1352-2310(95)00144-N, 1995. a
Fischer, R., Lobelle, D., Kooi, M., Koelmans, A., Onink, V., Laufkötter, C., Amaral-Zettler, L., Yool, A., and van Sebille, E.: Modelling submerged biofouled microplastics and their vertical trajectories, Biogeosciences, 19, 2211–2234, https://doi.org/10.5194/bg-19-2211-2022, 2022. a
Gill, A. E.: Atmosphere-Ocean Dynamics, vol. 30 of International
Geophysics Series, Academic Press, New York, ISBN 9780122835223, 1982. a
Gräwe, U.: Implementation of high-order particle-tracking schemes in a
water column model, Ocean Model., 36, 80–89,
https://doi.org/10.1016/j.ocemod.2010.10.002, 2011. a
Gräwe, U., Deleersnijder, E., Shah, S. H. A. M., and Heemink, A. W.: Why
the Euler scheme in particle tracking is not enough: the shallow-sea
pycnocline test case, Ocean Dynam., 62, 501–514,
https://doi.org/10.1007/s10236-012-0523-y, 2012. a
Gustafsson, B.: High order difference methods for time dependent PDE,
Springer-Verlag, Berlin Heidelberg, https://doi.org/10.1007/978-3-540-74993-6, 2008. a, b
Isachenko, I.: Catching the variety: Obtaining the distribution of terminal
velocities of microplastics particles in a stagnant fluid by a stochastic
simulation, Mar. Pollut. Bull., 159, 111464,
https://doi.org/10.1016/j.marpolbul.2020.111464, 2020. a
Israelsson, P. H., Do Kim, Y., and Adams, E. E.: A comparison of three
Lagrangian approaches for extending near field mixing calculations, Environ.
Modell. Softw., 21, 1631–1649, https://doi.org/10.1016/j.envsoft.2005.07.008, 2006. a
Johansen, Ø., Reed, M., and Bodsberg, N. R.: Natural dispersion revisited,
Mar. Pollut. Bull., 93, 20–26, https://doi.org/10.1016/j.marpolbul.2015.02.026, 2015. a, b
Li, Z., Spaulding, M. L., and French-McCay, D.: An algorithm for modeling
entrainment and naturally and chemically dispersed oil droplet size
distribution under surface breaking wave conditions, Mar. Pollut. Bull.,
119, 145–152, 2017. a
Lien, F.-S. and Leschziner, M.: Upstream monotonic interpolation for scalar
transport with application to complex turbulent flows, Int. J. Numer. Meth.
Fl., 19, 527–548, https://doi.org/10.1002/fld.1650190606, 1994. a
Longest, P. W. and Xi, J.: Effectiveness of direct Lagrangian tracking models
for simulating nanoparticle deposition in the upper airways, Aerosol Sci.
Tech., 41, 380–397, https://doi.org/10.1080/02786820701203223, 2007. a
Lynch, D. R., Greenberg, D. A., Bilgili, A., McGillicuddy Jr, D. J., Manning,
J. P., and Aretxabaleta, A. L.: Particles in the Coastal Ocean: Theory and
Applications, Cambridge University Press, ISBN 9781107061750, 2014. a
Madec, G., Bourdallé-Badie, R., Chanut, J., Clementi, E., Coward, A., Ethé,
C., Iovino, D., Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S.,
Mocavero, S., Rousset, C., Storkey, D., Müeller, S., Nurser, G., Bell, M.,
Samson, G., Mathiot, P., Mele, F., and Moulin, A.: NEMO ocean engine, vol. 27
of Scientific Notes of IPSL Climate Modelling Center, Zenodo,
https://doi.org/10.5281/zenodo.6334656, 2022. a
Marsh, R., Ivchenko, V. O., Skliris, N., Alderson, S., Bigg, G. R., Madec, G., Blaker, A. T., Aksenov, Y., Sinha, B., Coward, A. C., Le Sommer, J., Merino, N., and Zalesny, V. B.: NEMO–ICB (v1.0): interactive icebergs in the NEMO ocean model globally configured at eddy-permitting resolution, Geosci. Model Dev., 8, 1547–1562, https://doi.org/10.5194/gmd-8-1547-2015, 2015. a
Matsumura, Y. and Ohshima, K. I.: Lagrangian modelling of frazil ice in the
ocean, Ann. Glaciol., 56, 373–382, https://doi.org/10.3189/2015AoG69A657, 2015. a
Mountford, A. and Morales Maqueda, M.: Eulerian Modeling of the
Three-Dimensional Distribution of Seven Popular Microplastic Types in the
Global Ocean, J. Geophys. Res.-Oceans, 124, 8558–8573,
https://doi.org/10.1029/2019JC015050, 2019. a
Nepstad, R., Liste, M., Alver, M. O., Nordam, T., Davies, E., and Glette, T.:
High-resolution numerical modelling of a marine mine tailings discharge in
Western Norway, Regional Studies in Marine Science, 39, 101404,
https://doi.org/10.1016/j.rsma.2020.101404, 2020. a
Nepstad, R., Nordam, T., Ellingsen, I. H., Eisenhauer, L., Litzler, E., and
Kotzakoulakis, K.: Impact of flow field resolution on produced water
transport in Lagrangian and Eulerian models, Mar. Pollut. Bull., 182,
113928, https://doi.org/10.1016/j.marpolbul.2022.113928, 2022. a, b
Nooteboom, P. D., Bijl, P. K., van Sebille, E., von der Heydt, A. S., and
Dijkstra, H. A.: Transport Bias by Ocean Currents in Sedimentary
Microplankton Assemblages: Implications for Paleoceanographic
Reconstructions, Paleoceanogr. Paleoclim., 34, 1178–1194,
https://doi.org/10.1029/2019PA003606, 2019. a
Nordam, T.: nordam/Eulerian-and-Lagrangian-methods: 1.2, Zenodo [code],
https://doi.org/10.5281/zenodo.8164812, 2023. a
Nordam, T., Kristiansen, R., Nepstad, R., and Röhrs, J.: Numerical analysis
of boundary conditions in a Lagrangian particle model for vertical mixing,
transport and surfacing of buoyant particles in the water column, Ocean
Model., 136, 107–119, https://doi.org/10.1016/j.ocemod.2019.03.003,
2019a. a, b, c, d, e, f, g
Nordam, T., Nepstad, R., Litzler, E., and Röhrs, J.: On the use of random
walk schemes in oil spill modelling, Mar. Pollut. Bull., 146, 631–638,
https://doi.org/10.1016/j.marpolbul.2019.07.002, 2019b. a, b, c, d
Pavliotis, G. A.: Stochastic Processes and Applications, Springer
Science+Business Media, New York, ISBN 9781493913220, 2014. a
Powers, M. C.: A new roundness scale for sedimentary particles, J. Sediment.
Res., 23, 117–119, https://doi.org/10.1306/D4269567-2B26-11D7-8648000102C1865D, 1953. a
Rodean, H. C.: Stochastic Lagrangian Models of Turbulent Diffusion, vol. 26 of
Meteorological Monographs, American Meteorological Society, Boston,
MA, ISBN 1878220233, 1996. a
Röhrs, J., Christensen, K. H., Vikebø, F., Sundby, S., Saetra, Ø.,
and Broström, G.: Wave-induced transport and vertical mixing of pelagic
eggs and larvae, Limnol. Oceanogr., 59, 1213–1227,
https://doi.org/10.4319/lo.2014.59.4.1213, 2014. a, b
Röhrs, J., Dagestad, K.-F., Asbjørnsen, H., Nordam, T., Skancke, J., Jones, C. E., and Brekke, C.: The effect of vertical mixing on the horizontal drift of oil spills, Ocean Sci., 14, 1581–1601, https://doi.org/10.5194/os-14-1581-2018, 2018. a
Ross, O. N. and Sharples, J.: Recipe for 1-D Lagrangian particle tracking
models in space-varying diffusivity, Limnol. Oceanogr.-Meth., 2, 289–302,
https://doi.org/10.4319/lom.2004.2.289, 2004. a
Rowe, M., Anderson, E., Wynne, T., Stumpf, R., Fanslow, D., Kijanka, K.,
Vanderploeg, H., Strickler, J., and Davis, T.: Vertical distribution of
buoyant Microcystis blooms in a Lagrangian particle tracking model for
short-term forecasts in Lake Erie, J. Geophys. Res.-Oceans, 121, 5296–5314,
https://doi.org/10.1002/2016JC011720, 2016. a
Saharia, A. M., Zhu, Z., Aich, N., Baalousha, M., and Atkinson, J. F.: Modeling
the transport of titanium dioxide nanomaterials from combined sewer overflows
in an urban river, Sci. Total Environ., 696, 133904,
https://doi.org/10.1016/j.scitotenv.2019.133904, 2019. a
Scutt Phillips, J., Gupta, A. S., Senina, I., van Sebille, E., Lange, M.,
Lehodey, P., Hampton, J., and Nicol, S.: An individual-based model of
skipjack tuna (Katsuwonus pelamis) movement in the tropical Pacific ocean,
Prog. Oceanogr., 164, 63–74, https://doi.org/10.1016/j.pocean.2018.04.007, 2018. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system
(ROMS): a split-explicit, free-surface, topography-following-coordinate
oceanic model, Ocean Model., 9, 347–404, https://doi.org/10.1016/j.ocemod.2004.08.002,
2005. a
Skorokhod, A. V.: Stochastic equations for diffusion processes in a bounded
region, Theor. Probab. Appl+., 6, 264–274, https://doi.org/10.1137/1106035, 1961. a, b
Skorokhod, A. V.: Stochastic equations for diffusion processes in a bounded
region II, Theor. Probab. Appl+., 7, 3–23, https://doi.org/10.1137/1107002, 1962. a
Strauss, R. D. T. and Effenberger, F.: A hitch-hiker’s guide to stochastic
differential equations, Space Sci. Rev., 212, 151–192,
https://doi.org/10.1007/s11214-017-0351-y, 2017. a
Sundby, S. and Kristiansen, T.: The principles of buoyancy in marine fish eggs
and their vertical distributions across the world oceans, PLoS One, 10,
e0138821, https://doi.org/10.1371/journal.pone.0138821, 2015. a
Tayfun, M. A. and Wang, H.: Monte Carlo simulation of oil slick movements, J.
Waterway Div.-ASCE, 99, 309–324, https://doi.org/10.1061/AWHCAR.0000197, 1973. a
Tegen, I. and Lacis, A. A.: Modeling of particle size distribution and its
influence on the radiative properties of mineral dust aerosol, J. Geophys.
Res.-Atmos., 101, 19237–19244, https://doi.org/10.1029/95JD03610, 1996. a
Thorpe, S. A.: The turbulent ocean, Cambridge University Press, Cambridge, UK, https://doi.org/10.1017/CBO9780511819933,
2005. a
Tkalich, P. and Chan, E. S.: Vertical mixing of oil droplets by breaking waves,
Mar. Pollut. Bull., 44, 1219–1229, https://doi.org/10.1016/S0025-326X(02)00178-9,
2002. a
Umlauf, L., Burchard, H., and Bolding, K.: GOTM – Scientific Documentation:
version 3.2, Marine Science Reports, Leibniz-Institute for Baltic Sea
Research, Warnemuende, Germany, https://www.io-warnemuende.de/files/forschung/meereswissenschaftliche-berichte/mebe63_2005-gotm.pdf (last access: 11 September 2023), 2005.
a
Van Sebille, E., Scussolini, P., Durgadoo, J. V., Peeters, F. J., Biastoch, A.,
Weijer, W., Turney, C., Paris, C. B., and Zahn, R.: Ocean currents generate
large footprints in marine palaeoclimate proxies, Nat. Commun., 6, 1–8,
https://doi.org/10.1038/ncomms7521, 2015. a
van Sebille, E., Griffies, S. M., Abernathey, R., Adams, T. P., Berloff, P.,
Biastoch, A., Blanke, B., Chassignet, E. P., Cheng, Y., Cotter, C. J.,
Deleersnijder, E., Döös, K., Drake, H. F., Drijfhout, S., Gary,
S. F., Heemink, A. W., Kjellsson, J., Koszalka, I. M., Lange, M., Lique, C.,
MacGilchrist, G. A., Marsh, R., Mayorga Adame, C. G., McAdam, R., Nencioli,
F., Paris, C. B., Piggott, M. D., Polton, J. A., Rühs, S., Shah, S. H.,
Thomas, M. D., Wang, J., Wolfram, P. J., Zanna, L., and Zika, J. D.:
Lagrangian ocean analysis: Fundamentals and practices, Ocean Model., 121,
49–75, https://doi.org/10.1016/j.ocemod.2017.11.008, 2018. a
Warner, J. C., Sherwood, C. R., Signell, R. P., Harris, C. K., and Arango,
H. G.: Development of a three-dimensional, regional, coupled wave, current,
and sediment-transport model, Comput. Geosci., 34, 1284–1306,
https://doi.org/10.1016/j.cageo.2008.02.012, 2008. a
Wichmann, D., Delandmeter, P., and van Sebille, E.: Influence of near-surface
currents on the global dispersal of marine microplastic, J. Geophys.
Res.-Oceans, 124, 6086–6096, https://doi.org/10.1029/2019JC015328, 2019. a, b
Wilson, J. D. and Flesch, T. K.: Flow boundaries in random-flight dispersion
models: enforcing the well-mixed condition, J. Appl. Meteorol. Clim., 32,
1695–1707, https://doi.org/10.1175/1520-0450(1993)032<1695:FBIRFD>2.0.CO;2, 1993. a
Wimalaratne, M. R., Yapa, P. D., Nakata, K., and Premathilake, L. T.: Transport
of dissolved gas and its ecological impact after a gas release from
deepwater, Mar. Pollut. Bull., 100, 279–288,
https://doi.org/10.1016/j.marpolbul.2015.08.039, 2015. a
Young, E. F., Belchier, M., Hauser, L., Horsburgh, G. J., Meredith, M. P.,
Murphy, E. J., Pascoal, S., Rock, J., Tysklind, N., and Carvalho, G. R.:
Oceanography and life history predict contrasting genetic population
structure in two Antarctic fish species, Evol. Appl., 8, 486–509,
https://doi.org/10.1111/eva.12259, 2015. a
Zender, C. S., Bian, H., and Newman, D.: Mineral Dust Entrainment and
Deposition (DEAD) model: Description and 1990s dust climatology, J. Geophys.
Res.-Atmos., 108, 4416, https://doi.org/10.1029/2002JD002775, 2003. a
Short summary
We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the...
