Articles | Volume 15, issue 6
https://doi.org/10.5194/gmd-15-2423-2022
© 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-15-2423-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
21 Mar 2022
Model description paper |
| 21 Mar 2022
| 21 Mar 2022
Flow-Py v1.0: a customizable, open-source simulation tool to estimate runout and intensity of gravitational mass flows
Christopher J. L. D'Amboise
CORRESPONDING AUTHOR
Department of Natural Hazards, Austrian Research Centre for Forests (BFW), 6020 Innsbruck, Austria
Michael Neuhauser
Department of Natural Hazards, Austrian Research Centre for Forests (BFW), 6020 Innsbruck, Austria
Michaela Teich
Department of Natural Hazards, Austrian Research Centre for Forests (BFW), 6020 Innsbruck, Austria
Andreas Huber
Unit of Hydraulic Engineering, Institute for Infrastructure Engineering, University of Innsbruck, 6020 Innsbruck, Austria
Andreas Kofler
in.ge.na. Associated technical office, 39100 Bozen, Italy
Frank Perzl
Department of Natural Hazards, Austrian Research Centre for Forests (BFW), 6020 Innsbruck, Austria
Reinhard Fromm
Department of Natural Hazards, Austrian Research Centre for Forests (BFW), 6020 Innsbruck, Austria
Karl Kleemayr
Department of Natural Hazards, Austrian Research Centre for Forests (BFW), 6020 Innsbruck, Austria
deceased, February 2021
Jan-Thomas Fischer
Department of Natural Hazards, Austrian Research Centre for Forests (BFW), 6020 Innsbruck, Austria
Related authors
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Michael Neuhauser, Anselm Köhler, Anna Wirbel, Felix Oesterle, Wolfgang Fellin, Johannes Gerstmayr, Falko Dressler, and Jan-Thomas Fischer
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-164, https://doi.org/10.5194/nhess-2024-164, 2024
Preprint under review for NHESS
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This study examines how particles move in snow avalanches. The researchers used AvaNodes, a sensor system that tracks particle movement, in combination with radar data and simulations from the open avalanche framework AvaFrame. By comparing measurements and simulations, particle velocity and avalanche front position were matched with high accuracy. The study illustrates how multiple parameter sets can yield appropriate results and highlights the complexity of avalanche simulation.
Matthias Tonnel, Anna Wirbel, Felix Oesterle, and Jan-Thomas Fischer
Geosci. Model Dev., 16, 7013–7035, https://doi.org/10.5194/gmd-16-7013-2023, https://doi.org/10.5194/gmd-16-7013-2023, 2023
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Avaframe - the open avalanche framework - provides open-source tools to simulate and investigate snow avalanches. It is utilized for multiple purposes, the two main applications being hazard mapping and scientific research of snow processes. We present the theory, conversion to a computer model, and testing for one of the core modules used for simulations of a particular type of avalanche, the so-called dense-flow avalanches. Tests check and confirm the applicability of the utilized method.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
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The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Nora Helbig, David Moeser, Michaela Teich, Laure Vincent, Yves Lejeune, Jean-Emmanuel Sicart, and Jean-Matthieu Monnet
Hydrol. Earth Syst. Sci., 24, 2545–2560, https://doi.org/10.5194/hess-24-2545-2020, https://doi.org/10.5194/hess-24-2545-2020, 2020
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Snow retained in the forest canopy (snow interception) drives spatial variability of the subcanopy snow accumulation. As such, accurately describing snow interception in models is of importance for various applications such as hydrological, weather, and climate predictions. We developed descriptions for the spatial mean and variability of snow interception. An independent evaluation demonstrated that the novel models can be applied in coarse land surface model grid cells.
Martin Mergili, Shiva P. Pudasaini, Adam Emmer, Jan-Thomas Fischer, Alejo Cochachin, and Holger Frey
Hydrol. Earth Syst. Sci., 24, 93–114, https://doi.org/10.5194/hess-24-93-2020, https://doi.org/10.5194/hess-24-93-2020, 2020
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In 1941, the glacial lagoon Lake Palcacocha in the Cordillera Blanca (Peru) drained suddenly. The resulting outburst flood/debris flow consumed another lake and had a disastrous impact on the town of Huaraz 23 km downstream. We reconstuct this event through a numerical model to learn about the possibility of prediction of similar processes in the future. Remaining challenges consist of the complex process interactions and the lack of experience due to the rare occurrence of such process chains.
Anselm Köhler, Jan-Thomas Fischer, Riccardo Scandroglio, Mathias Bavay, Jim McElwaine, and Betty Sovilla
The Cryosphere, 12, 3759–3774, https://doi.org/10.5194/tc-12-3759-2018, https://doi.org/10.5194/tc-12-3759-2018, 2018
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Snow avalanches show complicated flow behaviour, characterized by several flow regimes which coexist in one avalanche. In this work, we analyse flow regime transitions where a powder snow avalanche transforms into a plug flow avalanche by incorporating warm snow due to entrainment. Prediction of such a transition is very important for hazard mitigation, as the efficiency of protection dams are strongly dependent on the flow regime, and our results should be incorporated into avalanche models.
Matthias Rauter, Andreas Kofler, Andreas Huber, and Wolfgang Fellin
Geosci. Model Dev., 11, 2923–2939, https://doi.org/10.5194/gmd-11-2923-2018, https://doi.org/10.5194/gmd-11-2923-2018, 2018
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We present a physical model for the simulation of dense snow avalanches and other gravitational mass flows. The model is solved with OpenFOAM, a popular open-source toolkit for the numerical solution of partial differential equations. The solver has a modular design and is easy to extend. Therefore, it represents an ideal platform for implementing and testing new model approaches.
Reinhard Fromm, Sonja Baumgärtner, Georg Leitinger, Erich Tasser, and Peter Höller
Nat. Hazards Earth Syst. Sci., 18, 1891–1903, https://doi.org/10.5194/nhess-18-1891-2018, https://doi.org/10.5194/nhess-18-1891-2018, 2018
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Snow gliding is a key factor for snow glide avalanche formation and soil erosion. This study considers atmospheric and snow variables, vegetation characteristics, and soil properties, and determines their relevance for snow gliding. The soil moisture, the soil temperature, the liquid water content of snow, the phytomass of mosses, and the friction coefficient have major influence.
However, further investigations may be focused on the freezing and melting processes in the uppermost soil layers.
M. S. Adams, T. Gigele, and R. Fromm
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W4, 537–540, https://doi.org/10.5194/isprs-archives-XLII-4-W4-537-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W4-537-2017, 2017
Thomas Zieher, Martin Rutzinger, Barbara Schneider-Muntau, Frank Perzl, David Leidinger, Herbert Formayer, and Clemens Geitner
Nat. Hazards Earth Syst. Sci., 17, 971–992, https://doi.org/10.5194/nhess-17-971-2017, https://doi.org/10.5194/nhess-17-971-2017, 2017
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At catchment scale, it is challenging to provide the required input parameters for physically based slope stability models. In the present study, the parameterization of such a model is optimized against observed shallow landslides during two triggering rainfall events. With the resulting set of parameters the model reproduces the location and the triggering timing of most observed landslides. Based on that, potential effects of increasing precipitation intensity on slope stability are assessed.
Martin Mergili, Jan-Thomas Fischer, Julia Krenn, and Shiva P. Pudasaini
Geosci. Model Dev., 10, 553–569, https://doi.org/10.5194/gmd-10-553-2017, https://doi.org/10.5194/gmd-10-553-2017, 2017
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r.avaflow represents a GIS-based, multi-functional open-source tool for the simulation of debris flows, rock avalanches, snow avalanches, or two-phase (solid and fluid) process chains. It further facilitates parameter studies and validation of the simulation results against observed patterns. r.avaflow shall inform strategies to reduce the risks related to the interaction of mass flow processes with society.
Matthias Rauter, Jan-Thomas Fischer, Wolfgang Fellin, and Andreas Kofler
Nat. Hazards Earth Syst. Sci., 16, 2325–2345, https://doi.org/10.5194/nhess-16-2325-2016, https://doi.org/10.5194/nhess-16-2325-2016, 2016
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Kinetic theory describes granular material under rapid motion. Macroscopic phenomena are determined by statistically describing collisions between particles. Recently, the theory has been extended to slow motion and quasi-static cases. Simplifications allow to apply this theory to snow avalanche simulations, where friction models with similar structure have been developed. Different test cases, comparing simulation and measurement data prove the applicability and highlight the improvements.
M. Teich, J.-T. Fischer, T. Feistl, P. Bebi, M. Christen, and A. Grêt-Regamey
Nat. Hazards Earth Syst. Sci., 14, 2233–2248, https://doi.org/10.5194/nhess-14-2233-2014, https://doi.org/10.5194/nhess-14-2233-2014, 2014
J.-T. Fischer
Nat. Hazards Earth Syst. Sci., 13, 1655–1667, https://doi.org/10.5194/nhess-13-1655-2013, https://doi.org/10.5194/nhess-13-1655-2013, 2013
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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
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Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
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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 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.
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
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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
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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 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
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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
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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
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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
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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.
Stefania Renna, Francesco Granella, Lara Aleluia Reis, and Paulina Estela Schulz-Antipa
EGUsphere, https://doi.org/10.2139/ssrn.4591252, https://doi.org/10.2139/ssrn.4591252, 2024
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The Country Level Air Quality Calculator (CLAQC) is a new fast modeling tool that predicts globally country-level monthly and annual concentrations of two major air pollutants, fine particulate matter (PM2.5) and tropospheric ozone (O3). It was designed to inform national and regional climate and pollution mitigation policies. It is easy to use and computationally efficient, allowing the simulation of a large number of policy scenarios for policy assessments and optimization frameworks.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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.
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
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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.
Ane Lopez de Gamiz-Zearra, Cecilie Hansen, Xavier Corrales, Iñaki Quincoces, Izaskun Preciado, and Eider Andonegi
EGUsphere, https://doi.org/10.5194/egusphere-2023-1368, https://doi.org/10.5194/egusphere-2023-1368, 2023
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This paper describes the development of the first calibrated end-to-end Atlantis model for the Bay of Biscay that will help us improve the comprehension of the spatial functioning of the Bay of Biscay ecosystem and help establishing management measures of human activities. Our results highlighted the importance of lower trophic levels to the pelagic system and demonstrate the importance of having accurate and precise data for biological processes.
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.
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.
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.
Cited articles
Ancey, C., Meunier, M., and Richard, D.: Inverse problem in avalanche dynamics
models, Water Resour. Res., 39, 1099, https://doi.org/10.1029/2002WR001749,
2003. a
Barbolini, M., Gruber, U., Keylock, C. J., Naaim, M., and Savi, F.:
Application of statistical and hydraulic-continuum dense-snow avalanche
models to five real European sites, Cold Reg. Sci. Technol., 31, 133–149, 2000. a
Brenning, A.: Spatial prediction models for landslide hazards: review,
comparison and evaluation, Nat. Hazards Earth Sys., 5,
853–862, 2005. a
Christen, M., Bartelt, P., and Gruber, U.: AVAL-1D: An avalanche dynamics
program for the practice, in: International Congress Interpraevent 2002 in the Pacific Rim – Matsumoto/Japan, Congress publication, 2,
715–725, 2002. a
Crozier, M. J. and Glade, T.: Landslide hazard and risk: issues, concepts and
approach, Landslide hazard and risk, chap. 1, 1–40, https://doi.org/10.1002/9780470012659.ch1, 2005. a
D'Amboise, C. J. L., Neuhauser, M., Teich, M., and Fischer, J.-T.:
Maverick-bfw/Flow_py_inputs_results: First releases (Version v1), Zenodo [data set], https://doi.org/10.5281/zenodo.5154787, 2021a. a, b
D’Amboise, C. J. L., Teich, M., Hormes, A., Steger, S., and Berger, F.: “Modeling Protective Forests for Gravitational Natural Hazards and How It Relates to Risk-Based Decision Support Tools”, in: Protective forests as Ecosystem-based solution for Disaster Risk Reduction (ECO-DRR), edited by: edited by: Teich, M., Accastello, C., Perzl, F., and Kleemayr, K., London: IntechOpen, https://www.intechopen.com/online-first/78979 (last access: 1 March 2022), 2021b. a, b, c, d
Dorren, L.: A review of rockfall mechanics and modelling approaches, Prog. Phys. Geog., 27, 69, https://doi.org/10.1191/0309133303pp359ra, 2003. a
Dorren, L.: Rockyfor3D (v4.1) revealed – Transparent description of the
complete 3D rockfall model, ecorisQ paper, https://www.ecorisq.org/ (last access: 1 June 2021), 2012. a
Dorren, L. K., Domaas, U., Kronholm, K., and Labiouse, V.: Methods for
predicting rockfall trajectories and runout zones, edited by: Lambert, S., Tech. Rep., John Wiley & Sons, ISTE Ltd, 143–173, ISBN 9781848212565, 2011. a
Eckert, N., Naaim, M., and Parent, E.: Long-term avalanche hazard assessment
with a Bayesian depth-averaged propagation model, J. Glaciol., 56,
563–586, 2010. a
Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., Savage, W. Z.,
and the JTC-1 Joint Technical Committee on Landslides and Engineered Slopes: Guidelines for landslide susceptibility, hazard and risk zoning for
land-use planning, Eng. Geol., 102, 99–111, 2008. a
Fischer, J. T., Kofler, A., Fellin, W., Granig, M., and Kleemayr, K.:
Multivariate parameter optimization for computational snow avalanche
simulation, J. Glaciol., 61, 875–888,
https://doi.org/10.3189/2015JoG14J168, 2015. a
Fischer, J.-T., Kofler, A., Huber, A., Fellin, W., Mergili, M., and
Oberguggenberger, M.: Bayesian Inference in Snow Avalanche Simulation with
r. avaflow, Geosciences, 10, 191, https://doi.org/10.3390/geosciences10050191, 2020. a
Fressard, M., Thiery, Y., and Maquaire, O.: Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes (Normandy, France), Nat. Hazards Earth Syst. Sci., 14, 569–588, https://doi.org/10.5194/nhess-14-569-2014, 2014. a
Fuchs, S., Thöni, M., McAlpin, M. C., Gruber, U., and Bründl, M.:
Avalanche hazard mitigation strategies assessed by cost effectiveness
analyses and cost benefit analyses – evidence from Davos, Switzerland,
Nat. Hazards, 41, 113–129, 2007. a
Guillard, C. and Zezere, J.: Landslide susceptibility assessment and validation
in the framework of municipal planning in Portugal: the case of Loures
Municipality, Environ. Manage., 50, 721–735, 2012. a
Huggel, C., Kääb, A., Haeberli, W., and Krummenacher, B.: Regional-scale GIS-models for assessment of hazards from glacier lake outbursts: evaluation and application in the Swiss Alps, Nat. Hazards Earth Syst. Sci., 3, 647–662, https://doi.org/10.5194/nhess-3-647-2003, 2003. a, b
Huggel, C., Caplan-Auerbach, J., Waythomas, C., and Wessels, R.: Monitoring
and modeling ice-rock avalanches from ice-capped vocanoes: A case study of
frequent large avalanches of Iliamna Volcano, Alaksa, J. Volcanol. Geoth. Res., 168, 114–136, 2007. a
Köhler, A., McElwaine, J., and Sovilla, B.: GEODAR data and the flow regimes
of snow avalanches, J. Geophys. Res.-Earth, 123, 1272–1294, 2018. a
Larsen, H., Sykes, J., Schauer, A., Hendrikx, J., Langford, R., Statham, G.,
Campbell, C., Neuhauser, M., and Fischer, J. T.: Development of automated avalanche
terrain exposure scale maps: current and future, in: Virtual Snow Science
Workshop, Fernie, Canada, 2020. a
Maggioni, M. and Gruber, U.: The influence of topographic parameters on
avalanche release dimension and frequency, Cold Reg. Sci. Technol., 37, 407–419, https://doi.org/10.1016/S0165-232X(03)00080-6, 2003. a
McClung, D. and Lied, K.: Statistical and geometrical definition of snow
avalanche runout, Cold Reg. Sci. Technol., 13, 107–119, 1987. a
Mergili, M., Krenn, J., and Chu, H.-J.: r.randomwalk v1, a multi-functional conceptual tool for mass movement routing, Geosci. Model Dev., 8, 4027–4043, https://doi.org/10.5194/gmd-8-4027-2015, 2015. a
Mergili, M., Fischer, J.-T., Krenn, J., and Pudasaini, S. P.: r.avaflow v1, an advanced open-source computational framework for the propagation and interaction of two-phase mass flows, Geosci. Model Dev., 10, 553–569, https://doi.org/10.5194/gmd-10-553-2017, 2017. a
Moos, C., Fehlmann, M., Trappmann, D., Stoffel, M., and Dorren, L.: Integrating
the mitigating effect of forests into quantitative rockfall risk
analysis–Two case studies in Switzerland, Int. J. Disast. Risk Re., 32, 55–74, 2018. a
Noetzli, J., Huggel, C., Hoelzle, M., and Haeberli, W.: GIS-based modelling of
rock-ice avalanches from Alpine permafrost areas, Computat. Geosci.,
10, 161–178, 2006. a
Okuda, S.: Rapid mass movements, Field Experiments and Measurement Programs in Geomorphology, edited by: Slaymaker, O., CRC Press, 61–105, ISBN 9789061919964, 1991. a
Pistocchi, A. and Notarnicola, C.: Data-driven mapping of avalanche release
areas: a case study in South Tyrol, Italy, Nat. Hazards, 65, 1313–1330,
2013. a
Plörer, M. and Stöhr, D.: Gries am Brenner/Vals Pilot Action Region: The Tyrolean Ski Tour Steering Concept – A Contribution to the Protection of Wildlife and Object Protective Forests in Best Practice Examples of Implementing Ecosystem-Based Natural Hazard Risk Management in the GreenRisk4ALPs Pilot Action Regions, edited by: Beguš, J., Berger, F., and Kleemayr, K., London, IntechOpen, https://doi.org/10.5772/intechopen.99011, 2021. a
Pudasaini, S. P. and Mergili, M.: A multi-phase mass flow model, J.
Geophys. Res.-Earth, 124, 2920–2942, 2019. a
Rauter, M., Kofler, A., Huber, A., and Fellin, W.: faSavageHutterFOAM 1.0: depth-integrated simulation of dense snow avalanches on natural terrain with OpenFOAM, Geosci. Model Dev., 11, 2923–2939, https://doi.org/10.5194/gmd-11-2923-2018, 2018. a
Sampl, P. and Granig, M.: Avalanche simulation with SAMOS-AT, in:
Proceedings of the International Snow Science Workshop, Montana State University Library, Davos, 27, 519–523, 2009. a
Sampl, P. and Zwinger, T.: Avalanche simulation with SAMOS, Ann. Glaciol., 38, 393–398, 2004. a
Sauermoser, S.: Avalanche hazard mapping – 30 years experience in Austria, in: Proceedings of the 2006 International Snow Science Workshop in Telluride,
Colorado, 1–6, Citeseer, 2006. a
Scheidl, C. and Rickenmann, D.: TopFlowDF - a simple GIS based model to
simulate debris-flow runout on the fan., in: Proceedings of the 5th
international Conference on Debris-Flow Hazards: Mitigation, Mechanics,
Prediction and Assessment, edited by: Genevois, R., Hamiltion, D., and
Prestininzi, A., 253–262, https://doi.org/10.4408/IJEGE.2011-03.B-030, 2011. a
Tarboton, D. G., Dash, P., and Sazib, N.: TauDEM 5.3: Guide to Using the TauDEM Command Line Functions, 2015. a
Teich, M. and Bebi, P.: Evaluating the benefit of avalanche protection forest
with GIS-based risk analyses – A case study in Switzerland, Forest Ecol. Manag., 257, 1910–1919, 2009. a
Van Rossum, G. and Drake, F. L.: Python 3 Reference Manual, CreateSpace, Scotts Valley, CA, ISBN 9781441412690, 2009. a
Van Westen, C., Van Asch, T. W., and Soeters, R.: Landslide hazard and risk
zonation—why is it still so difficult?, B. Eng. Geol. Environ., 65, 167–184, 2006. a
Van Westen, C. J., Castellanos, E., and Kuriakose, S. L.: Spatial data for
landslide susceptibility, hazard, and vulnerability assessment: An overview, Eng. Geol., 102, 112–131, 2008. a
Veitinger, J., Purves, R. S., and Sovilla, B.: Potential slab avalanche release area identification from estimated winter terrain: a multi-scale, fuzzy logic approach, Nat. Hazards Earth Syst. Sci., 16, 2211–2225, https://doi.org/10.5194/nhess-16-2211-2016, 2016. a
Voellmy, A.: Über die Zerstörungskraft von Lawinen, Schweizerische
Bauzeitung, Sonderdruck aus dem 73. Jahrgang, 1–25, 1955. a
Wichmann, V.: The Gravitational Process Path (GPP) model (v1.0) – a GIS-based simulation framework for gravitational processes, Geosci. Model Dev., 10, 3309–3327, https://doi.org/10.5194/gmd-10-3309-2017, 2017. a, b
Wirbel, A., Oesterle, F., Tonnel, M., and Fischer, J.-T.: avaframe/AvaFrame:
Version 0.5, Zenodo [code], https://doi.org/10.5281/zenodo.5094509, 2021. a, b, c
Short summary
The term gravitational mass flow (GMF) covers various natural hazard processes such as snow avalanches, rockfall, landslides, and debris flows. Here we present the open-source GMF simulation tool Flow-Py. The model equations are based on simple geometrical relations in three-dimensional terrain. We show that Flow-Py is an educational, innovative GMF simulation tool with three computational experiments: 1. validation of implementation, 2. performance, and 3. expandability.
The term gravitational mass flow (GMF) covers various natural hazard processes such as snow...
