Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5757-2022
© Author(s) 2022. 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-15-5757-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
25 Jul 2022
Development and technical paper |
| 25 Jul 2022
| 25 Jul 2022
Assessing the robustness and scalability of the accelerated pseudo-transient method
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Ivan Utkin
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia
Thibault Duretz
Institut für Geowissenschaften, Goethe‐Universität Frankfurt, Frankfurt, Germany
Univ. Rennes, CNRS, Géosciences Rennes UMR 6118, 35000 Rennes, France
Samuel Omlin
Swiss National Supercomputing Centre (CSCS), ETH Zurich, Lugano, Switzerland
Yuri Y. Podladchikov
Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia
Institute of Earth Sciences, University of Lausanne, Lausanne, Switzerland
Swiss Geocomputing Centre, University of Lausanne, Lausanne, Switzerland
Related authors
Anjali Sandip, Ludovic Räss, and Mathieu Morlighem
Geosci. Model Dev., 17, 899–909, https://doi.org/10.5194/gmd-17-899-2024, https://doi.org/10.5194/gmd-17-899-2024, 2024
Short summary
Short summary
We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a pseudo-transient method on graphics processing units (GPUs) and compare it to a standard central processing unit (CPU) implementation. We justify the GPU implementation by applying the price-to-performance metric for up to million-grid-point spatial resolutions. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions.
Ludovic Räss, Aleksandar Licul, Frédéric Herman, Yury Y. Podladchikov, and Jenny Suckale
Geosci. Model Dev., 13, 955–976, https://doi.org/10.5194/gmd-13-955-2020, https://doi.org/10.5194/gmd-13-955-2020, 2020
Short summary
Short summary
Accurate predictions of future sea level rise require numerical models that predict rapidly deforming ice. Localised ice deformation can be captured numerically only with high temporal and spatial resolution. This paper’s goal is to propose a parallel FastICE solver for modelling ice deformation. Our model is particularly useful for improving our process-based understanding of localised ice deformation. Our solver reaches a parallel efficiency of 99 % on GPU-based supercomputers.
Yury Alkhimenkov, Lyudmila Khakimova, and Yury Podladchikov
EGUsphere, https://doi.org/10.5194/egusphere-2024-3237, https://doi.org/10.5194/egusphere-2024-3237, 2024
Short summary
Short summary
This study examines stress drops and earthquake nucleation in elasto-plastic media using 2D simulations, highlighting the importance of high temporal and spatial resolutions in capturing stress evolution and strain fields. Stress drops reflect fault rupture mechanics and emulate earthquake behavior. The non-Gaussian distribution of stress drop amplitudes resembles "solid turbulence." Elasto-plastic models simulate key earthquake processes and could improve seismic hazard assessment.
Yury Alkhimenkov and Yury Y. Podladchikov
EGUsphere, https://doi.org/10.5194/egusphere-2024-3238, https://doi.org/10.5194/egusphere-2024-3238, 2024
Short summary
Short summary
This paper presents a rigorous derivation of Gassmann's equations, grounded in thermodynamic principles and conservation laws, addressing gaps and potential inconsistencies in the original formulation. It also explores Biot's poroelastic equations, demonstrating that Gassmann's equations are a specific case within Biot’s framework. The study affirms the robustness of Gassmann's equations when assumptions are met, and symbolic Maple routines are provided to ensure reproducibility of the results.
Yury Alkhimenkov and Yury Y. Podladchikov
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-160, https://doi.org/10.5194/gmd-2024-160, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The Accelerated Pseudo-Transient (APT) method is an efficient way to solve partial differential equations, particularly well-suited for parallel computing. This paper explores the APT method's effectiveness in solving elastic, viscoelastic, and hydro-mechanical problems, focusing on quasi-static conditions in 1D, 2D, and 3D. The study examines the best numerical settings for fast and accurate solutions. The paper shows how the APT can handle complex problems in high-resolution models.
Anjali Sandip, Ludovic Räss, and Mathieu Morlighem
Geosci. Model Dev., 17, 899–909, https://doi.org/10.5194/gmd-17-899-2024, https://doi.org/10.5194/gmd-17-899-2024, 2024
Short summary
Short summary
We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a pseudo-transient method on graphics processing units (GPUs) and compare it to a standard central processing unit (CPU) implementation. We justify the GPU implementation by applying the price-to-performance metric for up to million-grid-point spatial resolutions. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions.
Emmanuel Wyser, Yury Alkhimenkov, Michel Jaboyedoff, and Yury Y. Podladchikov
Geosci. Model Dev., 14, 7749–7774, https://doi.org/10.5194/gmd-14-7749-2021, https://doi.org/10.5194/gmd-14-7749-2021, 2021
Short summary
Short summary
We propose an implementation of the material point method using graphical processing units (GPUs) to solve elastoplastic problems in three-dimensional configurations, such as the granular collapse or the slumping mechanics, i.e., landslide. The computational power of GPUs promotes fast code executions, compared to a traditional implementation using central processing units (CPUs). This allows us to study complex three-dimensional problems tackling high spatial resolution.
Lorenzo G. Candioti, Thibault Duretz, Evangelos Moulas, and Stefan M. Schmalholz
Solid Earth, 12, 1749–1775, https://doi.org/10.5194/se-12-1749-2021, https://doi.org/10.5194/se-12-1749-2021, 2021
Short summary
Short summary
We quantify the relative importance of forces driving the dynamics of mountain building using two-dimensional computer simulations of long-term coupled lithosphere–upper-mantle deformation. Buoyancy forces can be as high as shear forces induced by far-field plate motion and should be considered when studying the formation of mountain ranges. The strength of rocks flooring the oceans and the density structure of the crust control deep rock cycling and the topographic elevation of orogens.
Martin Franz, Michel Jaboyedoff, Ryan P. Mulligan, Yury Podladchikov, and W. Andy Take
Nat. Hazards Earth Syst. Sci., 21, 1229–1245, https://doi.org/10.5194/nhess-21-1229-2021, https://doi.org/10.5194/nhess-21-1229-2021, 2021
Short summary
Short summary
A landslide-generated tsunami is a complex phenomenon that involves landslide dynamics, wave dynamics and their interaction. This phenomenon threatens numerous lives and infrastructures around the world. To assess this natural hazard, we developed an efficient numerical model able to simulate the landslide, the momentum transfer and the wave all at once. The good agreement between the numerical simulations and physical experiments validates our model and its novel momentum transfer approach.
Emmanuel Wyser, Yury Alkhimenkov, Michel Jaboyedoff, and Yury Y. Podladchikov
Geosci. Model Dev., 13, 6265–6284, https://doi.org/10.5194/gmd-13-6265-2020, https://doi.org/10.5194/gmd-13-6265-2020, 2020
Short summary
Short summary
In this work, we present an efficient and fast material point method (MPM) implementation in MATLAB. We first discuss the vectorization strategies to adapt this numerical method to a MATLAB implementation. We report excellent agreement of the solver compared with classical analysis among the MPM community, such as the cantilever beam problem. The solver achieves a performance gain of 28 compared with a classical iterative implementation.
Lorenzo G. Candioti, Stefan M. Schmalholz, and Thibault Duretz
Solid Earth, 11, 2327–2357, https://doi.org/10.5194/se-11-2327-2020, https://doi.org/10.5194/se-11-2327-2020, 2020
Short summary
Short summary
With computer simulations, we study the interplay between thermo-mechanical processes in the lithosphere and the underlying upper mantle during a long-term (> 100 Myr) tectonic cycle of extension–cooling–convergence. The intensity of mantle convection is important for (i) subduction initiation, (ii) the development of single- or double-slab subduction zones, and (iii) the forces necessary to initiate subduction. Our models are applicable to the opening and closure of the western Alpine Tethys.
Ludovic Räss, Aleksandar Licul, Frédéric Herman, Yury Y. Podladchikov, and Jenny Suckale
Geosci. Model Dev., 13, 955–976, https://doi.org/10.5194/gmd-13-955-2020, https://doi.org/10.5194/gmd-13-955-2020, 2020
Short summary
Short summary
Accurate predictions of future sea level rise require numerical models that predict rapidly deforming ice. Localised ice deformation can be captured numerically only with high temporal and spatial resolution. This paper’s goal is to propose a parallel FastICE solver for modelling ice deformation. Our model is particularly useful for improving our process-based understanding of localised ice deformation. Our solver reaches a parallel efficiency of 99 % on GPU-based supercomputers.
Dániel Kiss, Thibault Duretz, and Stefan Markus Schmalholz
Solid Earth, 11, 287–305, https://doi.org/10.5194/se-11-287-2020, https://doi.org/10.5194/se-11-287-2020, 2020
Short summary
Short summary
In this paper, we investigate the physical mechanisms of tectonic nappe formation by high-resolution numerical modeling. Tectonic nappes are key structural features of many mountain chains which are packets of rocks displaced, sometimes even up to 100 km, from their original position. However, the physical mechanisms involved are not fully understood. We solve numerical equations of fluid and solid dynamics to improve our knowledge. The results are compared with data from the Helvetic Alps.
Related subject area
Numerical methods
Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0)
The Measurement Error Proxy System Model: MEPSM v0.2
Numerical stabilization methods for level-set-based ice front migration
Modelling chemical advection during magma ascent
Consistent point data assimilation in Firedrake and Icepack
A Joint Reconstruction and Model Selection Approach for Large Scale Inverse Modeling
A computationally efficient parameterization of aerosol, cloud and precipitation pH for application at global and regional scale (EQSAM4Clim-v12)
Assessing the benefits of approximately exact step sizes for Picard and Newton solver in simulating ice flow (FEniCS-full-Stokes v.1.3.2)
Assessing effects of climate and technology uncertainties in large natural resource allocation problems
VISIR-2: ship weather routing in Python
Incremental analysis update (IAU) in the Model for Prediction Across Scales coupled with the Joint Effort for Data assimilation Integration (MPAS–JEDI 2.0.0)
Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0
Developing meshing workflows in Gmsh v4.11 for the geologic uncertainty assessment of high-temperature aquifer thermal energy storage
Development and preliminary validation of a land surface image assimilation system based on the Common Land Model
NorSand4AI: a comprehensive triaxial test simulation database for NorSand constitutive model materials
ParticleDA.jl v.1.0: a distributed particle-filtering data assimilation package
HETerogeneous vectorized or Parallel (HETPv1.0): an updated inorganic heterogeneous chemistry solver for the metastable-state NH4+–Na+–Ca2+–K+–Mg2+–SO42−–NO3−–Cl−–H2O system based on ISORROPIA II
Three-dimensional geological modelling of igneous intrusions in LoopStructural v1.5.10
Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17)
Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding
An automatic mesh generator for coupled 1D–2D hydrodynamic models
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 2: A semi-discrete error analysis framework for assessing coupling schemes
jsmetrics v0.2.0: a Python package for metrics and algorithms used to identify or characterise atmospheric jet streams
The Paleochrono-1.1 probabilistic model to derive optimized and consistent chronologies for several paleoclimatic sites
P3D-BRNS v1.0.0: a three-dimensional, multiphase, multicomponent, pore-scale reactive transport modelling package for simulating biogeochemical processes in subsurface environments
MinVoellmy v1: a lightweight model for simulating rapid mass movements based on a modified Voellmy rheology
Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets
Sweep interpolation: a cost-effective semi-Lagrangian scheme in the Global Environmental Multiscale model
CHONK 1.0: landscape evolution framework: cellular automata meets graph theory
Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations
Calibration of absorbing boundary layers for geoacoustic wave modeling in pseudo-spectral time-domain methods
Assimilation of snow water equivalent from AMSR2 and IMS satellite data utilizing the local ensemble transform Kalman filter
GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling
A comparison of Eulerian and Lagrangian methods for vertical particle transport in the water column
AutoQS v1: automatic parametrization of QuickSampling based on training images analysis
Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions
A dynamical core based on a discontinuous Galerkin method for higher-order finite-element sea ice modeling
GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation
Leveraging Google's Tensor Processing Units for tsunami-risk mitigation planning in the Pacific Northwest and beyond
An improved subgrid channel model with upwind-form artificial diffusion for river hydrodynamics and floodplain inundation simulation
A model instability issue in the National Centers for Environmental Prediction Global Forecast System version 16 and potential solutions
A comparison of 3-D spherical shell thermal convection results at low to moderate Rayleigh number using ASPECT (version 2.2.0) and CitcomS (version 3.3.1)
LISFLOOD-FP 8.1: new GPU-accelerated solvers for faster fluvial/pluvial flood simulations
Fast approximate Barnes interpolation: illustrated by Python-Numba implementation fast-barnes-py v1.0
Strategies for conservative and non-conservative monotone remapping on the sphere
Modeling large‐scale landform evolution with a stream power law for glacial erosion (OpenLEM v37): benchmarking experiments against a more process-based description of ice flow (iSOSIA v3.4.3)
A mixed finite-element discretisation of the shallow-water equations
Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling
Massively parallel modeling and inversion of electrical resistivity tomography data using PFLOTRAN
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 17, 8399–8420, https://doi.org/10.5194/gmd-17-8399-2024, https://doi.org/10.5194/gmd-17-8399-2024, 2024
Short summary
Short summary
This paper introduces a numerical method for simulating particle-based aerosol transport in atmospheric models. We detail the various numerical properties of the advection order method and demonstrate its implementation in a 3D weather prediction model (WRF) for the first time. Particle-based techniques improve the accuracy of aerosol size and composition predictions, which are key for aerosol–cloud and aerosol–radiation interactions.
Matt J. Fischer
Geosci. Model Dev., 17, 6745–6760, https://doi.org/10.5194/gmd-17-6745-2024, https://doi.org/10.5194/gmd-17-6745-2024, 2024
Short summary
Short summary
In paleoclimate research, proxy system models (PSMs) model chemical or biological systems which receive environmental input and output (e.g., geochemical signals). The environmental inputs are rarely noiseless, which causes problems when calibrating multi-input PSMs. Here a PSM is developed which includes generalized noise in both model inputs and outputs and prior information. A quasi-Bayesian method enhances the stability of the solution of the Measurement Error Proxy System Model.
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024, https://doi.org/10.5194/gmd-17-6227-2024, 2024
Short summary
Short summary
We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Úa for solving level-set equations, specifically those related to the dynamic representation of moving ice fronts within numerical ice sheet models. Our results demonstrate that the streamline upwind Petrov–Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.
Hugo Dominguez, Nicolas Riel, and Pierre Lanari
Geosci. Model Dev., 17, 6105–6122, https://doi.org/10.5194/gmd-17-6105-2024, https://doi.org/10.5194/gmd-17-6105-2024, 2024
Short summary
Short summary
Predicting the behaviour of magmatic systems is important for understanding Earth's matter and heat transport. Numerical modelling is a technique that can predict complex systems at different scales of space and time by solving equations using various techniques. This study tests four algorithms to find the best way to transport the melt composition. The "weighted essentially non-oscillatory" algorithm emerges as the best choice, minimising errors and preserving system mass well.
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
Geosci. Model Dev., 17, 5369–5386, https://doi.org/10.5194/gmd-17-5369-2024, https://doi.org/10.5194/gmd-17-5369-2024, 2024
Short summary
Short summary
Scientists often use models to study complex processes, like the movement of ice sheets, and compare them to measurements for estimating quantities that are hard to measure. We highlight an approach that ensures accurate results from point data sources (e.g. height measurements) by evaluating the numerical solution at true point locations. This method improves accuracy, aids communication between scientists, and is well-suited for integration with specialised software that automates processes.
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot Miller, and Arvind Saibaba
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-90, https://doi.org/10.5194/gmd-2024-90, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
Geosci. Model Dev., 17, 5009–5021, https://doi.org/10.5194/gmd-17-5009-2024, https://doi.org/10.5194/gmd-17-5009-2024, 2024
Short summary
Short summary
EQSAM4Clim has recently been revised to provide an accurate and efficient method for calculating the acidity of atmospheric particles. It is based on an analytical concept that is sufficiently fast and free of numerical noise, which makes it attractive for air quality forecasting. Version 12 allows the calculation of aerosol composition based on the gas–liquid–solid and the reduced gas–liquid partitioning with the associated water uptake for both cases, including the acidity of the aerosols.
Niko Schmidt, Angelika Humbert, and Thomas Slawig
Geosci. Model Dev., 17, 4943–4959, https://doi.org/10.5194/gmd-17-4943-2024, https://doi.org/10.5194/gmd-17-4943-2024, 2024
Short summary
Short summary
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 become affordable.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
Geosci. Model Dev., 17, 4791–4819, https://doi.org/10.5194/gmd-17-4791-2024, https://doi.org/10.5194/gmd-17-4791-2024, 2024
Short summary
Short summary
This paper applies a cutting-edge numerical method, SCEQ, to show how uncertain climate change and technological progress affect the future utilization of the world's scarce land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The study finds the range of outcomes for land use change to be smaller when using this novel method compared to existing deterministic models.
Gianandrea Mannarini, Mario Leonardo Salinas, Lorenzo Carelli, Nicola Petacco, and Josip Orović
Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, https://doi.org/10.5194/gmd-17-4355-2024, 2024
Short summary
Short summary
Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024, https://doi.org/10.5194/gmd-17-4199-2024, 2024
Short summary
Short summary
To mitigate the imbalances in the initial conditions, this study introduces our recent implementation of the incremental analysis update (IAU) in the Model for Prediction Across Scales – Atmospheric (MPAS-A) component coupled with the Joint Effort for Data assimilation Integration (JEDI) through the cycling system. A month-long cycling run demonstrates the successful implementation of the IAU capability in the MPAS–JEDI cycling system.
Federica Castino, Feijia Yin, Volker Grewe, Hiroshi Yamashita, Sigrun Matthes, Simone Dietmüller, Sabine Baumann, Manuel Soler, Abolfazl Simorgh, Maximilian Mendiguchia Meuser, Florian Linke, and Benjamin Lührs
Geosci. Model Dev., 17, 4031–4052, https://doi.org/10.5194/gmd-17-4031-2024, https://doi.org/10.5194/gmd-17-4031-2024, 2024
Short summary
Short summary
We introduce SolFinder 1.0, a decision-making tool to select trade-offs between different objective functions for optimal aircraft trajectories, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel and uses weather conditions simulated by the EMAC atmospheric model. This paper focuses on the ability of SolFinder to identify eco-efficient trajectories, reducing a flight's climate impact at limited cost penalties.
Ali Dashti, Jens C. Grimmer, Christophe Geuzaine, Florian Bauer, and Thomas Kohl
Geosci. Model Dev., 17, 3467–3485, https://doi.org/10.5194/gmd-17-3467-2024, https://doi.org/10.5194/gmd-17-3467-2024, 2024
Short summary
Short summary
This study developed new meshing workflows to enable the automatic generation of meshes that follow geological models. The workflow allows for importing several geological models as input for Gmsh and later exporting the same number of high-quality meshes. This way, geological uncertainty is directly included in the numerical simulations. This study evaluates the impact of the geological uncertainty on thermohydraulic performance of two reservoirs for high-temperature heat storage applications.
Wangbin Shen, Zhaohui Lin, Zhengkun Qin, and Juan Li
Geosci. Model Dev., 17, 3447–3465, https://doi.org/10.5194/gmd-17-3447-2024, https://doi.org/10.5194/gmd-17-3447-2024, 2024
Short summary
Short summary
In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The findings demonstrate that the assimilation of surface soil moisture observation images effectively and reasonably enhances the spatial structure of soil moisture analysis field.
Luan Carlos de Sena Monteiro Ozelim, Michéle Dal Toé Casagrande, and André Luís Brasil Cavalcante
Geosci. Model Dev., 17, 3175–3197, https://doi.org/10.5194/gmd-17-3175-2024, https://doi.org/10.5194/gmd-17-3175-2024, 2024
Short summary
Short summary
The paper addresses synthetic dataset challenges in nonlinear constitutive modeling of soils, providing two datasets: one with 2000 soil types, 40 test conditions each (160 000 triaxial tests), and a second with 2048 soil types, 42 test conditions each (172 032 triaxial tests). Each dataset is a 4000×10 matrix applicable for multivariate forecasting and geotechnical simulations. In addition, a new Python code is introduced, empowering researchers to leverage Python packages for NorSand analyses.
Daniel Giles, Matthew M. Graham, Mosè Giordano, Tuomas Koskela, Alexandros Beskos, and Serge Guillas
Geosci. Model Dev., 17, 2427–2445, https://doi.org/10.5194/gmd-17-2427-2024, https://doi.org/10.5194/gmd-17-2427-2024, 2024
Short summary
Short summary
Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across a wide range of settings. Progress for researchers is currently limited by a lack of tools to run these models effectively and efficiently. A key challenge is the optimal use of high-performance computing environments. The work presented here focuses on a developed open-source software platform which aims to improve this usage, with an emphasis placed on flexibility, efficiency, and scalability.
Stefan J. Miller, Paul A. Makar, and Colin J. Lee
Geosci. Model Dev., 17, 2197–2219, https://doi.org/10.5194/gmd-17-2197-2024, https://doi.org/10.5194/gmd-17-2197-2024, 2024
Short summary
Short summary
This work outlines a new solver written in Fortran to calculate the partitioning of metastable aerosols at thermodynamic equilibrium based on the forward algorithms of ISORROPIA II. The new code includes numerical improvements that decrease the computational speed (compared to ISORROPIA II) while improving the accuracy of the partitioning solution.
Fernanda Alvarado-Neves, Laurent Ailleres, Lachlan Grose, Alexander R. Cruden, and Robin Armit
Geosci. Model Dev., 17, 1975–1993, https://doi.org/10.5194/gmd-17-1975-2024, https://doi.org/10.5194/gmd-17-1975-2024, 2024
Short summary
Short summary
Previous work has demonstrated that adding geological knowledge to modelling methods creates more accurate and reliable models. Following this reasoning, we added constraints from magma emplacement mechanisms into existing modelling frameworks to improve the 3D characterisation of igneous intrusions. We tested the method on synthetic and real-world case studies, and the results show that our method can reproduce intrusion morphologies with no manual processing and using realistic datasets.
André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum, and Nina Kristiansen
Geosci. Model Dev., 17, 1957–1974, https://doi.org/10.5194/gmd-17-1957-2024, https://doi.org/10.5194/gmd-17-1957-2024, 2024
Short summary
Short summary
It is vital to know the extent and concentration of volcanic ash in the atmosphere during a volcanic eruption. Whilst satellite imagery may give an estimate of the ash right now (assuming no cloud coverage), we also need to know where it will be in the coming hours. This paper presents a method for estimating parameters for a volcanic eruption based on satellite observations of ash in the atmosphere. The software package is open source and applicable to similar inversion scenarios.
Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, José Antonio Álvarez Antolínez, Tim Leijnse, and Dano Roelvink
Geosci. Model Dev., 17, 1789–1811, https://doi.org/10.5194/gmd-17-1789-2024, https://doi.org/10.5194/gmd-17-1789-2024, 2024
Short summary
Short summary
Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
Younghun Kang and Ethan J. Kubatko
Geosci. Model Dev., 17, 1603–1625, https://doi.org/10.5194/gmd-17-1603-2024, https://doi.org/10.5194/gmd-17-1603-2024, 2024
Short summary
Short summary
Models used to simulate the flow of coastal and riverine waters, including flooding, require a geometric representation (or mesh) of geographic features that exhibit a range of disparate spatial scales from large, open waters to small, narrow channels. Representing these features in an accurate way without excessive computational overhead presents a challenge. Here, we develop an automatic mesh generation tool to help address this challenge. Our results demonstrate the efficacy of our approach.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024, https://doi.org/10.5194/gmd-17-1387-2024, 2024
Short summary
Short summary
Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
Short summary
Short summary
Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Tom Keel, Chris Brierley, and Tamsin Edwards
Geosci. Model Dev., 17, 1229–1247, https://doi.org/10.5194/gmd-17-1229-2024, https://doi.org/10.5194/gmd-17-1229-2024, 2024
Short summary
Short summary
Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Frédéric Parrenin, Marie Bouchet, Christo Buizert, Emilie Capron, Ellen Corrick, Russell Drysdale, Kenji Kawamura, Amaëlle Landais, Robert Mulvaney, Ikumi Oyabu, and Sune Rasmussen
EGUsphere, https://doi.org/10.5194/egusphere-2023-2911, https://doi.org/10.5194/egusphere-2023-2911, 2024
Short summary
Short summary
The Paleochrono1 probablistic dating model allows to derive a common and optimized chronology for several paleoclimatic sites from various archives (ice cores, speleothems, marine cores, lake cores, etc.). It combines prior sedimentation scenarios with chronological information such as dated horizons, dated intervals, stratigraphic links and (for ice cores) Delta-depth observations. Paleochrono1 is available under the MIT open-source license.
Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev., 17, 881–898, https://doi.org/10.5194/gmd-17-881-2024, https://doi.org/10.5194/gmd-17-881-2024, 2024
Short summary
Short summary
Coupled reaction transport modelling is an established and 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 modelling the transport of reactive species is missing. We presented a model that overcomes this limitation and represents a novel numerical simulation toolbox.
Stefan Hergarten
Geosci. Model Dev., 17, 781–794, https://doi.org/10.5194/gmd-17-781-2024, https://doi.org/10.5194/gmd-17-781-2024, 2024
Short summary
Short summary
The Voellmy rheology has been widely used for simulating snow and rock avalanches. Recently, a modified version of this rheology was proposed, which turned out to be able to predict the observed long runout of large rock avalanches theoretically. The software MinVoellmy presented here is the first numerical implementation of the modified rheology. It consists of MATLAB and Python classes, where simplicity and parsimony were the design goals.
Arjun Babu Nellikkattil, Danielle Lemmon, Travis Allen O'Brien, June-Yi Lee, and Jung-Eun Chu
Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, https://doi.org/10.5194/gmd-17-301-2024, 2024
Short summary
Short summary
This study introduces a new computational framework called Scalable Feature Extraction and Tracking (SCAFET), designed to extract and track features in climate data. SCAFET stands out by using innovative shape-based metrics to identify features without relying on preconceived assumptions about the climate model or mean state. This approach allows more accurate comparisons between different models and scenarios.
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
Short summary
Short summary
The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
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
Short summary
Short summary
This contribution presents a new method to numerically explore the evolution of mountain ranges and surrounding areas. The method helps in monitoring with details on the timing and travel path of material eroded from the mountain ranges. It is particularly well suited to studies juxtaposing different domains – lakes or multiple rock types, for example – and enables the combination of different processes.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
Short summary
Short summary
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
Short summary
Short summary
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.
Joonlee Lee, Myong-In Lee, Sunlae Tak, Eunkyo Seo, and Yong-Keun Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-221, https://doi.org/10.5194/gmd-2023-221, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We developed a snow assimilation system using satellite data based on a land surface model. The snow states produced by the assimilation system demonstrate high performance in all regions, including transition regions, compared to the satellite data and land model. As snow significantly influences energy and water balance at the atmosphere-land boundary, this approach allows for a more accurate prediction of atmospheric conditions by realistically representing atmosphere-land interactions.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Alamatian, J.: A new formulation for fictitious mass of the Dynamic Relaxation
method with kinetic damping, Comput. Struct., 90–91, 42–54,
https://doi.org/10.1016/j.compstruc.2011.10.010, 2012. a
Alkhimenkov, Y., Khakimova, L., and Podladchikov, Y.: Stability of discrete
schemes of Biot's poroelastic equations,
Geophys. J. Int.,
225, 354–377, https://doi.org/10.1093/gji/ggaa584, 2021a. a, b
Alkhimenkov, Y., Räss, L., Khakimova, L., Quintal, B., and Podladchikov,
Y.: Resolving Wave Propagation in Anisotropic Poroelastic Media
Using Graphical Processing Units (GPUs),
J. Geophys. Res.-Sol. Ea., 126, 7, https://doi.org/10.1029/2020JB021175, 2021b. a
Bakhvalov, N. S.: On the convergence of a relaxation method with natural
constraints on the elliptic operator,
USSR Comp. Math. Math.+, 6, 101–135, https://doi.org/10.1016/0041-5553(66)90118-2, 1966. a
Barnes, M. R.: Form Finding and Analysis of Tension Structures by Dynamic
Relaxation, International Journal of Space Structures, 14, 89–104,
https://doi.org/10.1260/0266351991494722, 1999. a
Baumgardner, J. R.: Three-dimensional treatment of convective flow in the
earth's mantle, J. Stat. Phys., 39, 501–511,
https://doi.org/10.1007/BF01008348, 1985. a
Besard, T., Foket, C., and De Sutter, B.: Effective Extensible Programming:
Unleashing Julia on GPUs,
IEEE T. Parall. Distr., 30, 827–841, https://doi.org/10.1109/TPDS.2018.2872064, 2018. a
Besard, T., Churavy, V., Edelman, A., and De Sutter, B.: Rapid software
prototyping for heterogeneous and distributed platforms,
Adv. Eng. Softw., 132, 29–46, 2019. a
Bezanson, J., Edelman, A., Karpinski, S., and Shah, V. B.: Julia: A fresh
approach to numerical computing, SIAM Rev., 59, 65–98,
https://doi.org/10.1137/141000671, 2017. a, b
Brandt, A.: Multi-level adaptive solutions to boundary-value problems,
Math. Comput., 31, 333–390,
https://doi.org/10.1090/S0025-5718-1977-0431719-X, 1977. a, b
Byrne, S., Wilcox, L. C., and Churavy, V.: MPI.jl: Julia bindings for the
Message Passing Interface, Proceedings of the JuliaCon Conferences, 1, 68,
https://doi.org/10.21105/jcon.00068, 2021. a
Cassell, A. C. and Hobbs, R. E.: Numerical stability of dynamic relaxation
analysis of non-linear structures,
Int. J. Numer. Meth. Eng., 10, 1407–1410, https://doi.org/10.1002/nme.1620100620, 1976. a
Chester, M.: Second sound in solids, Phys. Rev., 131, 2013–2015,
https://doi.org/10.1103/PhysRev.131.2013, 1963. a
Costa, A.: Permeability-porosity relationship: A reexamination of the
Kozeny-Carman equation based on a fractal pore-space geometry assumption,
Geophys. Res. Lett., 33, L02318, https://doi.org/10.1029/2005GL025134, 2006. a
Cox, S. and Zuazua, E.: The rate at which energy decays in a damped string,
Commun. Part. Diff. Eq., 19, 213–243,
https://doi.org/10.1080/03605309408821015, 1994. a
Cundall, A. P.: Explicit finite differnce method in geomechanics, Second Int.
Conf. Numerical Methods in Geomechanics, Blacksburg, 1976, 1, 132–150, 1976. a
Eager, D. L., Zahorjan, J., and Lazowska, E. D.: Speedup versus efficiency in
parallel systems, IEEE T. Comput., 38, 408–423,
https://doi.org/10.1109/12.21127, 1989. a
Fuhrer, O., Chadha, T., Hoefler, T., Kwasniewski, G., Lapillonne, X., Leutwyler, D., Lüthi, D., Osuna, C., Schär, C., Schulthess, T. C., and Vogt, H.: Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0, Geosci. Model Dev., 11, 1665–1681, https://doi.org/10.5194/gmd-11-1665-2018, 2018. a
Gaitonde, A. L.: A dual-time method for two-dimensional unsteady incompressible
flow calculations, Int. J. Numer. Meth. Eng., 41, 1153–1166,
https://doi.org/10.1002/(SICI)1097-0207(19980330)41:6<1153::AID-NME334>3.0.CO;2-9,
1998. a
Gustafson, J. L.: Reevaluating Amdahl's law, Commun. ACM, 31,
532–533, https://doi.org/10.1145/42411.42415, 1988. a
Hackbusch, W.: Multi-Grid Methods and Applications, vol. 4, Springer
Series in Computational Mathematics, Springer, Berlin,
Heidelberg, https://doi.org/10.1007/978-3-662-02427-0, 1985. a
Hoemmen, M. F.: Communication-avoiding Krylov subspace methods, PhD thesis,
EECS Department, University of California, Berkeley,
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-37.html (last access: 16 May 2022),
2010. a
Jordan, P. M. and Puri, A.: Digital signal propagation in dispersive media,
J. Appl. Phys., 85, 1273–1282, https://doi.org/10.1063/1.369258, 1999. a
Kaus, B. J. P., Popov, A. A., Baumann, T. S., Püsök, A. E., Bauville,
A., Fernandez, N., and Collignon, M.: Forward and Inverse Modelling of
Lithospheric Deformation on Geological Timescales, in: NIC Symposium 2016, Jülich, Germany, 11–12 February 2016,
edited by: Binder, K., Müller, M., Kremer, A., and Schnurpfeil, A.,
48, 299–307, Forschungszentrum Jülich, Jülich, 2016. a
Kilic, B. and Madenci, E.: Structural stability and failure analysis using
peridynamic theory, Int. J. NonLin. Mech., 44,
845–854, https://doi.org/10.1016/j.ijnonlinmec.2009.05.007, 2009. a
Kumar, V., Grama, A., Gupta, A., and Karypis, G.: Introduction to parallel
computing, Benjamin/Cummings Redwood City, CA, 110, ISBN 0805331700, 1994. a
Mandal, J., Sonawane, C., Iyer, A., and GosaviInamdar, S.: Incompressible flow
computations over moving boundary using a novel upwind method, Comput.
Fluid., 46, 348–352, 2011. a
Maxwell, J. C.: IV. On the dynamical theory of gases,
Philos. T. R. Soc. Lond., 157, 49–88,
https://doi.org/10.1098/rstl.1867.0004, 1867. a
May, D., Brown, J., and Le Pourhiet, L.: A scalable, matrix-free multigrid
preconditioner for finite element discretizations of heterogeneous Stokes
flow, Comput. Method Appl. M., 290,
496–523, https://doi.org/10.1016/j.cma.2015.03.014, 2015. a, b
McCalpin, J. D.: Memory bandwidth and machine balance in current high
performance computers, IEEE computer society technical committee on computer
architecture (TCCA) newsletter, 2, 19–25, 1995. a
McKee, S., Tomé, M., Ferreira, V., Cuminato, J., Castelo, A., Sousa, F.,
and Mangiavacchi, N.: The MAC method, Comput. Fluid., 37, 907–930,
https://doi.org/10.1016/j.compfluid.2007.10.006, 2008. a
Omlin, S.: Development of massively parallel near peak performance solvers for
three-dimensional geodynamic modelling, PhD thesis, University of Lausanne, https://doi.org/10.48550/ARXIV.2207.08716,
2017. a
Omlin, S. and Räss, L.: ImplicitGlobalGrid.jl,
https://github.com/eth-cscs/ImplicitGlobalGrid.jl (last access: 16 May 2022),
2021a. a
Omlin, S., Räss, L., and Podladchikov, Y.: HPC.m – the MATLAB HPC
Compiler and its Use for Solving 3D Poromechanics on Supercomputers, in:
Platform for Advanced Scientific Computing Conference (PASC15), 1–3 June 2015, Zurich, Switzerland, ETH Zurich,
Zurich, Switzerland, 2015a. a
Omlin, S., Räss, L., and Podladchikov, Y.: From MATLAB to
Supercomputing: the MATLAB HPC-Compiler, in: 2nd Frontiers in Computational
Physics: Energy Sciences Conference 2015, 3–5 June 2015, Zurich, Switzerland, ETH Zurich, Zurich, Switzerland,
2015b. a
Otter, J.: Computations for prestressed concrete reactor pressure vessels
using dynamic relaxation, Nuclear Structural Engineering, 1, 61–75,
https://doi.org/10.1016/0369-5816(65)90097-9, 1965. a
Otter, J. R. H., Cassell, A. C., and Hobbs, R. E.: Dynamic relaxation,
35,
633–656,
https://doi.org/10.1680/IICEP.1966.8604, 1966. a
Papadrakakis, M.: A method for the automatic evaluation of the dynamic
relaxation parameters, Comput. Method Appl. M., 25, 35–48, https://doi.org/10.1016/0045-7825(81)90066-9, 1981. a, b
Pascal, H.: Pressure wave propagation in a fluid flowing through a porous
medium and problems related to interpretation of Stoneley's wave attenuation
in acoustical well logging, Int. J. Eng. Sci., 24,
1553–1570, https://doi.org/10.1016/0020-7225(86)90163-1, 1986. a
Patankar, S.: Numerical heat transfer and fluid flow, CRC press, https://doi.org/10.1201/9781482234213, 1980. a
Podladtchikov, I. and Podladchikov, Y. Y.: Memory Bound Wave Propagation at
Hardware Limit,
http://on-demand.gputechconf.com/gtc/2013/video/S3176-Memory-Bound-Wave-Propagation-Hardware-Limit.flv (last access: 16 May 2022),
2013. a
Poliakov, A. N., Cundall, P. A., Podladchikov, Y. Y., and Lyakhovsky, V. A.:
An explicit inertial method for the simulation of viscoelastic flow: an
evaluation of elastic effects on diapiric flow in two- and three- layers
models, Flow and creep in the solar system: observations, modeling and
theory, NATO ASI Series, vol. 391, Springer, Dordrecht, 175–195, https://doi.org/10.1007/978-94-015-8206-3_12, 1993. a
Poliakov, A. N. B., Herrmann, H. J., Podladchikov, Y. Y., and Roux, S.:
Fractal plastic shear bands, Fractals, 2, 567–581,
https://doi.org/10.1142/s0218348x9400079x, 1994. a
Ramesh, G. and Krishnamoorthy, C. S.: Post‐buckling analysis of structures
by dynamic relaxation, Int. J. Numer. Meth. Eng., 36, 1339–1364, https://doi.org/10.1002/nme.1620360806, 1993. a
Räss, L. and Omlin, S.: ParallelRandomFields.jl,
https://github.com/luraess/ParallelRandomFields.jl (last access: 16 May 2022), 2021. a
Räss, L. and Utkin, I.: PTsolvers/PseudoTransientDiffusion.jl:
PseudoTransientDiffusion.jl 1.0.0, Zenodo [code], https://doi.org/10.5281/zenodo.6553699,
2022a. a, b
Räss, L. and Utkin, I.: PTsolvers/PseudoTransientStokes.jl:
PseudoTransientStokes.jl 1.0.0, Zenodo [code], https://doi.org/10.5281/zenodo.6553714,
2022b. a, b
Räss, L., Duretz, T., Podladchikov, Y. Y., and Schmalholz, S. M.: M2Di:
Concise and efficient MATLAB 2-D Stokes solvers using the Finite
Difference Method, Geochem. Geophy. Geosy., 18, 755–768,
https://doi.org/10.1002/2016GC006727, 2017. a, b
Räss, L., Kolyukhin, D., and Minakov, A.: Efficient parallel random field
generator for large 3-D geophysical problems, Comput. Geosci.,
131, 158–169, https://doi.org/10.1016/j.cageo.2019.06.007, 2019b. a
Räss, L., Omlin, S., and Podladchikov, Y. Y.: Resolving Spontaneous
Nonlinear Multi-Physics Flow Localization in 3-D: Tackling Hardware Limit,
https://developer.nvidia.com/gtc/2019/video/S9368 (last access: 16 May 2022), 2019c. a
Räss, L., Licul, A., Herman, F., Podladchikov, Y. Y., and Suckale, J.: Modelling thermomechanical ice deformation using an implicit pseudo-transient method (FastICE v1.0) based on graphical processing units (GPUs), Geosci. Model Dev., 13, 955–976, https://doi.org/10.5194/gmd-13-955-2020, 2020. a, b, c, d, e, f
Reuber, G. S., Holbach, L., and Räss, L.: Adjoint-based inversion for
porosity in shallow reservoirs using pseudo-transient solvers for non-linear
hydro-mechanical processes, J. Comput. Phys., 423, 109797,
https://doi.org/10.1016/j.jcp.2020.109797, 2020. a
Rezaiee-Pajand, M., Kadkhodayan, M., Alamatian, J., and Zhang, L. C.: A new
method of fictitious viscous damping determination for the dynamic relaxation
method, Comput. Struct., 89, 783–794,
https://doi.org/10.1016/J.COMPSTRUC.2011.02.002, 2011. a, b
Richardson, L. F.: IX. The approximate arithmetical solution by finite
differences of physical problems involving differential equations, with an
application to the stresses in a masonry dam, Philos. T.
R. Soc. A, 210, 307–357, https://doi.org/10.1098/rsta.1911.0009, 1911. a
Riley, J. D.: Iteration Procedures for the Dirichlet Difference
Problem, Mathematical Tables and Other Aids to Computation, 8, 125–131,
https://doi.org/10.2307/2001924, 1954. a, b
Saad, Y.: Iterative methods for linear systems of equations: A brief
historical journey, in: Contemporary Mathematics, edited by: Brenner, S.,
Shparlinski, I., Shu, C.-W., and Szyld, D., American
Mathematical Society, Providence, Rhode Island, 754, 197–215, https://doi.org/10.1090/conm/754/15141,
2020. a, b
Shin, D. and Strikwerda, J. C.: Inf-sup conditions for finite-difference
approximations of the Stokes equations, J. Aust.
Math. Soc. B, 39, 121–134, 1997. a
Swirydowicz, K., Langou, J., Ananthan, S., Yang, U., and Thomas, S.: Low
synchronization Gram-Schmidt and generalized minimal residual algorithms,
Numer. Linear Algebr., 28, e2343, https://doi.org/10.1002/nla.2343, 2020.
a
Tackley, P. J.: Effects of strongly variable viscosity on three-dimensional
compressible convection in planetary mantles, J. Geophys. Res.-Sol. Ea., 101, 3311–3332,
https://doi.org/10.1029/95JB03211, 1996. a
Trottenberg, U., Oosterlee, C. W. C. W., and Schüller, A.: Multigrid,
Academic Press, hardcover ISBN 9780127010700,
eBook ISBN 9780080479569, 2001. a
Virieux, J.: P-SV wave propagation in heterogeneous media: Velocity‐stress
finite‐difference method, Geophysics, 51, 889–901,
https://doi.org/10.1190/1.1442147, 1986. a
Wang, L. H., Yarushina, V., Alkhimenkov, Y., and Podladchikov, Y.:
Physics-inspired pseudo-transient method and its application in modelling
focused fluid flow with geological complexity, Geophys. J. Int., 229, 1–20, https://doi.org/10.1093/GJI/GGAB426, 2021. a, b, c
Wulf, W. A. and McKee, S. A.: Hitting the memory wall: implications of the
obvious, ACM Comp. Ar., 23, 20–24,
https://doi.org/10.1145/216585.216588, 1995. a
Young, D. M.: Second-degree iterative methods for the solution of large linear
systems, J. Approx. Theory, 5, 137–148,
https://doi.org/10.1016/0021-9045(72)90036-6, 1972. a
Zheng, L., Gerya, T., Knepley, M., Yuen, D. A., Zhang, H., and Shi, Y.: GPU
implementation of multigrid solver for stokes equation with strongly variable
viscosity, in: Lecture Notes in Earth System Sciences, 0, 321–333,
Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-16405-7_21, 2013. a
Short summary
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.
Continuum mechanics-based modelling of physical processes at large scale requires huge...
