Articles | Volume 8, issue 3
https://doi.org/10.5194/gmd-8-533-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-8-533-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
09 Mar 2015
Model description paper |
| 09 Mar 2015
Firedrake-Fluids v0.1: numerical modelling of shallow water flows using an automated solution framework
C. T. Jacobs
CORRESPONDING AUTHOR
Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ, UK
M. D. Piggott
Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ, UK
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Shuaib Rasheed, Simon C. Warder, Yves Plancherel, and Matthew D. Piggott
Nat. Hazards Earth Syst. Sci., 24, 737–755, https://doi.org/10.5194/nhess-24-737-2024, https://doi.org/10.5194/nhess-24-737-2024, 2024
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Here we use a high-resolution bathymetry dataset of the Maldives archipelago, as well as corresponding high numerical model resolution, to carry out a scenario-based tsunami hazard assessment for the entire Maldives archipelago to investigate the potential impact of plausible far-field tsunamis across the Indian Ocean at the island scale. The results indicate that several factors contribute to mitigating and amplifying tsunami waves at the island scale.
Jennifer R. Shadrick, Dylan H. Rood, Martin D. Hurst, Matthew D. Piggott, Klaus M. Wilcken, and Alexander J. Seal
Earth Surf. Dynam., 11, 429–450, https://doi.org/10.5194/esurf-11-429-2023, https://doi.org/10.5194/esurf-11-429-2023, 2023
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This study uses a coastal evolution model to interpret cosmogenic beryllium-10 concentrations and topographic data and, in turn, quantify long-term cliff retreat rates for four chalk sites on the south coast of England. By using a process-based model, clear distinctions between intertidal weathering rates have been recognised between chalk and sandstone rock coast sites, advocating the use of process-based models to interpret the long-term behaviour of rock coasts.
Mariana C. A. Clare, Tim W. B. Leijnse, Robert T. McCall, Ferdinand L. M. Diermanse, Colin J. Cotter, and Matthew D. Piggott
Nat. Hazards Earth Syst. Sci., 22, 2491–2515, https://doi.org/10.5194/nhess-22-2491-2022, https://doi.org/10.5194/nhess-22-2491-2022, 2022
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Assessing uncertainty is computationally expensive because it requires multiple runs of expensive models. We take the novel approach of assessing uncertainty from coastal flooding using a multilevel multifidelity (MLMF) method which combines the efficiency of less accurate models with the accuracy of more expensive models at different resolutions. This significantly reduces the computational cost but maintains accuracy, making previously unfeasible real-world studies possible.
Jennifer R. Shadrick, Martin D. Hurst, Matthew D. Piggott, Bethany G. Hebditch, Alexander J. Seal, Klaus M. Wilcken, and Dylan H. Rood
Earth Surf. Dynam., 9, 1505–1529, https://doi.org/10.5194/esurf-9-1505-2021, https://doi.org/10.5194/esurf-9-1505-2021, 2021
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Here we use topographic and 10Be concentration data to optimise a coastal evolution model. Cliff retreat rates are calculated for two UK sites for the past 8000 years and, for the first time, highlight a strong link between the rate of sea level rise and long-term cliff retreat rates. This method enables us to study past cliff response to sea level rise and so to greatly improve forecasts of future responses to accelerations in sea level rise that will result from climate change.
Shuaib Rasheed, Simon C. Warder, Yves Plancherel, and Matthew D. Piggott
Ocean Sci., 17, 319–334, https://doi.org/10.5194/os-17-319-2021, https://doi.org/10.5194/os-17-319-2021, 2021
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Environmental issues arising due to coastal modification and future sea level scenarios are a major environmental hazard facing the Maldives today. Here, we carry out high-resolution tidal modelling of a Maldivian atoll for the first time and show that coastal modification in the island scale is capable of driving large-scale change in the wider atoll basin in a short time, comparable to that of long-term sea level rise scenarios and on par with observations.
Tuomas Kärnä, Stephan C. Kramer, Lawrence Mitchell, David A. Ham, Matthew D. Piggott, and António M. Baptista
Geosci. Model Dev., 11, 4359–4382, https://doi.org/10.5194/gmd-11-4359-2018, https://doi.org/10.5194/gmd-11-4359-2018, 2018
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Unstructured meshes are attractive for coastal ocean modeling, as they allow more accurate representation of complex coastal topography. Unstructured mesh models are, however, often perceived as slow and inaccurate. We present a novel discontinuous Galerkin ocean model: Thetis. We demonstrate that the model is able to simulate baroclinic ocean flows with high accuracy on a triangular prismatic mesh. This work paves the way for highly accurate and efficient three-dimensional coastal ocean models.
Samuel D. Parkinson, Simon W. Funke, Jon Hill, Matthew D. Piggott, and Peter A. Allison
Geosci. Model Dev., 10, 1051–1068, https://doi.org/10.5194/gmd-10-1051-2017, https://doi.org/10.5194/gmd-10-1051-2017, 2017
A. S. Candy, A. Avdis, J. Hill, G. J. Gorman, and M. D. Piggott
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-5993-2014, https://doi.org/10.5194/gmdd-7-5993-2014, 2014
Revised manuscript has not been submitted
S. D. Parkinson, J. Hill, M. D. Piggott, and P. A. Allison
Geosci. Model Dev., 7, 1945–1960, https://doi.org/10.5194/gmd-7-1945-2014, https://doi.org/10.5194/gmd-7-1945-2014, 2014
J. Hill, E. E. Popova, D. A. Ham, M. D. Piggott, and M. Srokosz
Ocean Sci., 10, 323–343, https://doi.org/10.5194/os-10-323-2014, https://doi.org/10.5194/os-10-323-2014, 2014
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Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
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Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024, https://doi.org/10.5194/gmd-17-71-2024, 2024
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Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
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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.
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, https://doi.org/10.5194/gmd-16-7237-2023, 2023
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This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
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Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
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Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
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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.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
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Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Niko Schmidt, Angelika Humbert, and Thomas Slawig
EGUsphere, https://doi.org/10.5194/egusphere-2023-1569, https://doi.org/10.5194/egusphere-2023-1569, 2023
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Future sea-level rise is of big significance for coastal regions. The melting and acceleration of glaciers plays a major role in sea-level change. Computer simulation of glaciers costs a lot of computational resources. In this publication, we test a new way of simulating glaciers. This approach produces the same results but has the advantage that it needs much less computation time. As simulations can be obtained with fewer computation resources, higher resolution and physics becomes affordable.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
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Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
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Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
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Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
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To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
EGUsphere, https://doi.org/10.48550/arXiv.2304.06058, https://doi.org/10.48550/arXiv.2304.06058, 2023
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Scientists often use models to study complex processes, like the movement of ice sheets, and compare them to measurements for estimating hard-to-measure quantities. We highlight an approach that ensures accurate results from point data sources (such as height measurements) by evaluating the numerical solution at true point locations. This method improves accuracy, can aid communication between scientists, and is well suited for integration with specialised software that automates the processes.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
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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.
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.
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.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
EGUsphere, https://doi.org/10.5194/egusphere-2022-863, https://doi.org/10.5194/egusphere-2022-863, 2023
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This paper applies cutting-edge numerical methods to show how uncertain climate change and technological progress affect the future utilization of the scarce world's land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The more uncertain the future crop yields are, the more forest conversion will be necessary to sustain human welfare. Some of that conversion takes place even when crop yields are not actually affected.
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.
Cited articles
Alnæs, M. S., Logg, A., Ø}lgaard, K. B., Rognes, M. E., and Wells, G. N.: {Unified Form Language: A domain-specific language for weak formulations of partial differential equations, ACM Trans. Math. Softw., 40, 9, https://doi.org/10.1145/2566630, 2014.
Arnold, D. N.: An Interior Penalty Finite Element Method with Discontinuous Elements, SIAM J. Num. Analysis, 19, 742–760, https://doi.org/10.1137/0719052, 1982.
Balay, S., Abhyankar, S., Adams, M., Brown, J., Brune, P., Buschelman, K., Eijkhout, V., Gropp, W., Kaushik, D., Knepley, M., Curfman McInnes, L., Rupp, K., Smith, B., and Zhang, H.: PETSc Users Manual, Tech. Rep. Revision 3.5, Argonne National Laboratory, 2014.
Bangerth, W., Hartmann, R., and Kanschat, G.: deal.II–A general-purpose object-oriented finite element library, ACM Trans. Math. Softw., 33, 24, https://doi.org/10.1145/1268776.1268779, 2007.
Bassi, F. and Rebay, S.: A High-Order Accurate Discontinuous Finite Element Method for the Numerical Solution of the Compressible Navier-Stokes Equations, J. Comput. Phys., 131, 267–279, https://doi.org/10.1006/jcph.1996.5572, 1997.
Bermudez, A. and Vazquez, M. E.: Upwind methods for hyperbolic conservation laws with source terms, Comput. Fluids, 23, 1049–1071, https://doi.org/10.1016/0045-7930(94)90004-3, 1994.
Brown, J., Knepley, M. G., May, D. A., McInnes, L. C., and Smith, B. F.: Composable Linear Solvers for Multiphysics, in: Proceeedings of the 11th International Symposium on Parallel and Distributed Computing (ISPDC 2012), 55–62, https://doi.org/10.1109/ISPDC.2012.16, 2012.
Capart, H. and Young, D. L.: Formation of a jump by the dam-break wave over a granular bed, J. Fluid Mech., 372, 165–187, https://doi.org/10.1017/S0022112098002250, 1998.
Deardorff, J.: A numerical study of three-dimensional turbulent channel flow at large Reynolds numbers, J. Fluid Mech., 41, 453–480, https://doi.org/10.1017/S0022112070000691, 1970.
Deardorff, J. W.: On the magnitude of the subgrid scale eddy coefficient, J. Comput. Phys., 7, 120–133, https://doi.org/10.1016/0021-9991(71)90053-2, 1971.
Dedner, A., Klöfkorn, R., Nolte, M., and Ohlberger, M.: A generic interface for parallel and adaptive discretization schemes: Abstraction principles and the DUNE-FEM module, Computing, 90, 165–196, https://doi.org/10.1007/s00607-010-0110-3, 2010.
Divett, T., Vennell, R., and Stevens, C.: Optimization of multiple turbine arrays in a channel with tidally reversing flow by numerical modelling with adaptive mesh, Philos. Trans. Roy. Soc. A, 371, 1471–2962, https://doi.org/10.1098/rsta.2012.0251, 2013.
Elman, H., Howle, V. E., Shadid, J., Shuttleworth, R., and Tuminaro, R.: A taxonomy and comparison of parallel block multi-level preconditioners for the incompressible Navier-Stokes equations, J. Computat. Phys., 227, 1790–1808, https://doi.org/10.1098/rsta.2012.0251, 2008.
Elman, H. C., Silvester, D. J., and Wathen, A. J.: Finite Elements and Fast Iterative Solvers: with applications in incompressible fluid dynamics, Oxford University Press, 2005.
Farrell, P. E., Piggott, M. D., Gorman, G. J., Ham, D. A., Wilson, C. R., and Bond, T. M.: Automated continuous verification for numerical simulation, Geosci. Model Dev., 4, 435–449, https://doi.org/10.5194/gmd-4-435-2011, 2011.
Farrell, P. E., Ham, D. A., Funke, S. W., and Rognes, M. E.: Automated derivation of the adjoint of high-level transient finite element programs, SIAM J. Scientific Comput., 35, C369–C393, https://doi.org/10.1137/120873558, 2013.
Flather, R. A.: A tidal model of the northwest European continental shelf, Memoires de la Société Royale des Sciences de Liège, 10, 141–164, 1976.
Funke, S. W. and Farrell, P. E.:A framework for automated PDE-constrained optimisation, arXiv:1302.3894, submitted, 2013.
Funke, S. W., Farrell, P. E., and Piggott, M. D.: Tidal turbine array optimisation using the adjoint approach, Renewable Energy, 63, 658–673, https://doi.org/10.1016/j.renene.2013.09.031, 2014.
Geuzaine, C. and Remacle, J.-F.: Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities, Int. J. Num. Methods Eng., 79, 1309–1331, https://doi.org/10.1002/nme.2579, 2009.
Ham, D. A., Farrell, P. E., Gorman, G. J., Maddison, J. R., Wilson, C. R., Kramer, S. C., Shipton, J., Collins, G. S., Cotter, C. J., and Piggott, M. D.: Spud 1.0: generalising and automating the user interfaces of scientific computer models, Geosci. Model Dev., 2, 33–42, https://doi.org/10.5194/gmd-2-33-2009, 2009.
Hecht, F.: New development in FreeFem++, J. Num. Math., 20, 251–265, https://doi.org/10.1515/jnum-2012-0013, 2012.
Hill, J., Collins, G. S., Avdis, A., Kramer, S. C., and Piggott, M. D.: How does multiscale modelling and inclusion of realistic palaeobathymetry affect numerical simulation of the Storegga Slide tsunami?, Ocean Model., 83, 11–25, https://doi.org/10.1016/j.ocemod.2014.08.007, 2014.
Katz, R. F., Knepley, M. G., Smith, B., Spiegelman, M., and Coon, E. T.: Numerical simulation of geodynamic processes with the Portable Extensible Toolkit for Scientific Computation, Phys. Earth Planet. Int., 163, 52–68, https://doi.org/10.1016/j.pepi.2007.04.016, 2007.
Kirby, R. C.: Algorithm 839: FIAT, a New Paradigm for Computing Finite Element Basis Functions, ACM Trans. Math. Softw., 30, 502–516, https://doi.org/10.1145/1039813.1039820, 2004.
Kirby, R. C. and Logg, A.: A compiler for variational forms, ACM Trans. Math. Softw., 32, 417–444, https://doi.org/10.1145/1163641.1163644, 2006.
Kramer, S. C., Piggott, M. D., Hill, J., Kregting, L., Pritchard, D., and Elsaesser, B.: The modelling of tidal turbine farms using multi-scale, unstructured mesh models, in: Proceedings of the 2nd International Conference on Environmental Interactions of Marine Renewable Energy Technologies, (EIMR2014), Stornoway, Scotland, 2014.
Liang, S.-J., Tang, J.-H., and Wu, M.-S.: Solution of shallow-water equations using least-squares finite-element method, Acta Mechanica Sinica, 24, 523–532, https://doi.org/10.1007/s10409-008-0151-4, 2008.
Lloyd, P. M. and Stansby, P. K.: Shallow-Water Flow around Model Conical Islands of Small Side Slope. II: Submerged, J. Hydraul. Eng., 123, 1068–1077, https://doi.org/10.1061/(ASCE)0733-9429(1997)123:12(1068), 1997.
Logg, A. and Wells, G. N.: DOLFIN: Automated finite element computing, ACM Trans. Math. Softw., 37, 20, https://doi.org/10.1145/1731022.1731030, 2010.
Logg, A., Mardal, K.-A., Wells, G. N., Alnæs, M. S., Clark, S. R., Davidson, D. B., Vilela de Abreu, R., Degirmenci, C., Haga, J. B., Hake, J., Hoffman, J., Jansson, J., Jansson, N., Johnson, C., Kirby, R. C., Knepley, M. G., Langtangen, H. P., Lezar, E., Linge, S., Logg, A., Lopes, N. D., Løvgren, A. E., Mardal, K.-A., Mortensen, M., Narayanan, H., Nazarov, M., Nikbakht, M., Pereira, P. J. S., Ring, J., Rognes, M. E., Schroll, H. J., Scott, L. R., Selim, K., Støle-Hentschel, S., Terrel, A. R., Trabucho, L., Valen-Sendstad, K., Vynnytska, L., Wells, G. N., Wilbers, I. M., and Ølgaard, K. B.: Automated Solution of Differential Equations by the Finite Element Method, Springer, https://doi.org/10.1007/978-3-642-23099-8, 2012.
Luporini, F., Varbanescu, A. L., Rathgeber, F., Bercea, G.-T., Ramanujam, J., Ham, D. A., and Kelly, P. H. J.: Cross-Loop Optimization of Arithmetic Intensity for Finite Element Local Assembly, ACM Trans. Archi. Code Optimization, 11, 57, https://doi.org/10.1145/2687415, 2015.
Lyn, D. A. and Rodi, W.: The flapping shear layer formed by flow separation from the forward corner of a square cylinder, J. Fluid Mech., 267, 353–376, https://doi.org/10.1017/S0022112094001217, 1994.
Lyn, D. A., Einav, S., Rodi, W., and Park, J.-H.: A laser-Doppler velocimetry study of ensemble-averaged characteristics of the turbulent near wake of a square cylinder, J. Fluid Mech., 304, 285–319, https://doi.org/10.1017/S0022112095004435, 1995.
Maddison, J. R. and Farrell, P. E.: Rapid development and adjoining of transient finite element models, Comput. Meth. Appl. Mech. Eng., 276, 95–121, https://doi.org/10.1016/j.cma.2014.03.010, 2014.
Markall, G. R., Rathgeber, F., Mitchell, L., Loriant, N., Bertolli, C., Ham, D. A., and Kelly, P. H.: Performance-Portable Finite Element Assembly Using PyOP2 and FEniCS, in: 28th International Supercomputing Conference, ISC, Proceedings, vol. 7905 of Lecture Notes in Computer Science, 279–289, Springer, 2013.
Martin-Short, R., Hill, J., Kramer, S. C., Avdis, A., Allison, P. A., and Piggott, M. D.: Tidal resource extraction in the Pentland Firth, UK: potential impacts on flow regime and sediment transport in the Inner Sound of Stroma, Renewable Energy, 76, 596–607, https://doi.org/10.1016/j.renene.2014.11.079, 2015.
Mingham, C. G. and Causon, D. M.: High-Resolution Finite-Volume Method for Shallow Water Flows, J. Hydraul. Eng., 124, 605–614, https://doi.org/10.1061/(ASCE)0733-9429(1998)124:6(605), 1998.
Mortensen, M., Langtangen, H. P., and Wells, G. N.: A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations, Adv. Water Resour., 34, 1082–1101, https://doi.org/10.1016/j.advwatres.2011.02.013, 2011.
Ølgaard, K. B. and Wells, G. N.: Optimisations for quadrature representations of finite element tensors through automated code generation, ACM Trans. Math. Softw., 37, 8, https://doi.org/10.1145/1644001.1644009, 2010.
OpenFOAM: OpenFOAM User Guide, Version 2.3.1, 2014.
Piggott, M. D., Gorman, G. J., Pain, C. C., Allison, P. A., Candy, A. S., Martin, B. T., and Wells, M. R.: A new computational framework for multi-scale ocean modelling based on adapting unstructured meshes, Int. J. Num. Methods Fluids, 56, 1003–1015, https://doi.org/10.1002/fld.1663, 2008.
Rathgeber, F.: Productive and Efficient Computational Science Through Domain-specific Abstractions, Ph.D. thesis, Imperial College London, 2014.
Rathgeber, F., Markall, G. R., Mitchell, L., Loriant, N., Ham, D. A., Bertolli, C., and Kelly, P. H.: PyOP2: A High-Level Framework for Performance-Portable Simulations on Unstructured Meshes, in: High Performance Computing, Networking Storage and Analysis, SC Companion, IEEE Computer Society, 1116–1123, 2012.
Rathgeber, F., Ham, D. A., Mitchell, L., Lange, M., Luporini, F., McRae, A. T. T., Bercea, G.-T., Markall, G. R., and Kelly, P. H. J.: Firedrake: automating the finite element method by composing abstractions, ACM Trans. Math. Softw., http://arxiv.org/abs/1501.01809, submitted, 2015.
Roache, P. J.: Code Verification by the Method of Manufactured Solutions, J. Fluids Eng., 124, 4–10, https://doi.org/10.1115/1.1436090, 2002.
Rodi, W., Ferziger, J. H., Breuer, M., and Porquié, M.: Status of Large Eddy Simulation: Results of a Workshop, Trans. ASME, 119, 248–262, 1997.
Rognes, M. E., Ham, D. A., Cotter, C. J., and McRae, A. T. T.: Automating the solution of PDEs on the sphere and other manifolds in FEniCS 1.2, Geosci. Model Dev., 6, 2099–2119, https://doi.org/10.5194/gmd-6-2099-2013, 2013.
Saad, Y. and Schultz, M. H.: GMRES: A generalized minimal residual algorithm for solving nonsymmetric linear systems, SIAM J. Scient. Stat. Compu., 7, 856–869, https://doi.org/10.1137/0907058, 1986.
Smagorinsky, J.: General Circulation Experiments with the Primitive Equations, Mon. Weather Rev., 91, 99–164, https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963.
Trangenstein, J. A.: Numerical Solution of Hyperbolic Partial Differential Equations, Cambridge University Press, 2009.
Wilson, C.: Modelling Multiple-Material Flows on Adaptive Unstructured Meshes, Ph.D. thesis, Imperial College London, 2009.
Zhou, J. G.: Lattice Boltzmann Methods for Shallow Water Flows, Springer, 2004.
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