Articles | Volume 13, issue 3
https://doi.org/10.5194/gmd-13-955-2020
© Author(s) 2020. 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-13-955-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
06 Mar 2020
Model description paper |
| 06 Mar 2020
| 06 Mar 2020
Modelling thermomechanical ice deformation using an implicit pseudo-transient method (FastICE v1.0) based on graphical processing units (GPUs)
Stanford University, Geophysics Department, 397 Panama Mall, Stanford, CA 94305, USA
now at: Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
now at: Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
Aleksandar Licul
Institute of Earth Surface Dynamics, University of Lausanne, 1015 Lausanne, Switzerland
Swiss Geocomputing Centre, University of Lausanne, 1015 Lausanne, Switzerland
Frédéric Herman
Institute of Earth Surface Dynamics, University of Lausanne, 1015 Lausanne, Switzerland
Swiss Geocomputing Centre, University of Lausanne, 1015 Lausanne, Switzerland
Yury Y. Podladchikov
Swiss Geocomputing Centre, University of Lausanne, 1015 Lausanne, Switzerland
Institute of Earth Sciences, University of Lausanne, 1015 Lausanne, Switzerland
Jenny Suckale
Stanford University, Geophysics Department, 397 Panama Mall, Stanford, CA 94305, USA
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, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
Short summary
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.
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 under review 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.
Ian Delaney, Leif Anderson, and Frédéric Herman
Earth Surf. Dynam., 11, 663–680, https://doi.org/10.5194/esurf-11-663-2023, https://doi.org/10.5194/esurf-11-663-2023, 2023
Short summary
Short summary
This paper presents a two-dimensional subglacial sediment transport model that evolves a sediment layer in response to subglacial sediment transport conditions. The model captures sediment transport in supply- and transport-limited regimes across a glacier's bed and considers both the creation and transport of sediment. Model outputs show how the spatial distribution of sediment and water below a glacier can impact the glacier's discharge of sediment and erosion of bedrock.
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.
Ugo Nanni, Dirk Scherler, Francois Ayoub, Romain Millan, Frederic Herman, and Jean-Philippe Avouac
The Cryosphere, 17, 1567–1583, https://doi.org/10.5194/tc-17-1567-2023, https://doi.org/10.5194/tc-17-1567-2023, 2023
Short summary
Short summary
Surface melt is a major factor driving glacier movement. Using satellite images, we have tracked the movements of 38 glaciers in the Pamirs over 7 years, capturing their responses to rapid meteorological changes with unprecedented resolution. We show that in spring, glacier accelerations propagate upglacier, while in autumn, they propagate downglacier – all resulting from changes in meltwater input. This provides critical insights into the interplay between surface melt and glacier movement.
Joanne Elkadi, Benjamin Lehmann, Georgina E. King, Olivia Steinemann, Susan Ivy-Ochs, Marcus Christl, and Frédéric Herman
Earth Surf. Dynam., 10, 909–928, https://doi.org/10.5194/esurf-10-909-2022, https://doi.org/10.5194/esurf-10-909-2022, 2022
Short summary
Short summary
Glacial and non-glacial processes have left a strong imprint on the landscape of the European Alps, but further research is needed to better understand their long-term effects. We apply a new technique combining two methods for bedrock surface dating to calculate post-glacier erosion rates next to a Swiss glacier. Interestingly, the results suggest non-glacial erosion rates are higher than previously thought, but glacial erosion remains the most influential on landscape evolution.
Ludovic Räss, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
Short summary
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.
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.
Sean D. Willett, Frédéric Herman, Matthew Fox, Nadja Stalder, Todd A. Ehlers, Ruohong Jiao, and Rong Yang
Earth Surf. Dynam., 9, 1153–1221, https://doi.org/10.5194/esurf-9-1153-2021, https://doi.org/10.5194/esurf-9-1153-2021, 2021
Short summary
Short summary
The cooling climate of the last few million years leading into the ice ages has been linked to increasing erosion rates by glaciers. One of the ways to measure this is through mineral cooling ages. In this paper, we investigate potential bias in these data and the methods used to analyse them. We find that the data are not themselves biased but that appropriate methods must be used. Past studies have used appropriate methods and are sound in methodology.
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.
Rabiul H. Biswas, Frédéric Herman, Georgina E. King, Benjamin Lehmann, and Ashok K. Singhvi
Clim. Past, 16, 2075–2093, https://doi.org/10.5194/cp-16-2075-2020, https://doi.org/10.5194/cp-16-2075-2020, 2020
Short summary
Short summary
A new approach to reconstruct the temporal variation of rock surface temperature using the thermoluminescence (TL) of feldspar is introduced. Multiple TL signals or thermometers in the range of 210 to 250 °C are sensitive to typical surface temperature fluctuations and can be used to constrain thermal histories of rocks over ~50 kyr. We show that it is possible to recover thermal histories of rocks using inverse modeling and with δ18O anomalies as a priori information.
Benjamin Campforts, Veerle Vanacker, Frédéric Herman, Matthias Vanmaercke, Wolfgang Schwanghart, Gustavo E. Tenorio, Patrick Willems, and Gerard Govers
Earth Surf. Dynam., 8, 447–470, https://doi.org/10.5194/esurf-8-447-2020, https://doi.org/10.5194/esurf-8-447-2020, 2020
Short summary
Short summary
In this contribution, we explore the spatial determinants of bedrock river incision in the tropical Andes. The model results illustrate the problem of confounding between climatic and lithological variables, such as rock strength. Incorporating rock strength explicitly into river incision models strongly improves the explanatory power of all tested models and enables us to clarify the role of rainfall variability in controlling river incision rates.
Georgina E. King, Sumiko Tsukamoto, Frédéric Herman, Rabiul H. Biswas, Shigeru Sueoka, and Takahiro Tagami
Geochronology, 2, 1–15, https://doi.org/10.5194/gchron-2-1-2020, https://doi.org/10.5194/gchron-2-1-2020, 2020
Short summary
Short summary
Rates of landscape evolution over the past million years are difficult to quantify. This study develops a technique which is able to measure changes in rock cooling rates (related to landscape evolution) over this timescale. The technique is based on the electron spin resonance dating of quartz minerals. Measurement protocols and new numerical models are proposed that describe these data, allowing for their translation into rock cooling rates.
Benjamin Lehmann, Frédéric Herman, Pierre G. Valla, Georgina E. King, and Rabiul H. Biswas
Earth Surf. Dynam., 7, 633–662, https://doi.org/10.5194/esurf-7-633-2019, https://doi.org/10.5194/esurf-7-633-2019, 2019
Short summary
Short summary
Assessing the impact of glaciation at the Earth's surface requires simultaneous quantification of the impact of climate variability on past glacier fluctuations and on bedrock erosion. Here we present a new approach for evaluating post-glacial bedrock surface erosion in mountainous environments by combining two different surface exposure dating methods. This approach can be used to estimate how bedrock erosion rates vary spatially and temporally since glacier retreat in an alpine environment.
Lionel Benoit, Aurelie Gourdon, Raphaël Vallat, Inigo Irarrazaval, Mathieu Gravey, Benjamin Lehmann, Günther Prasicek, Dominik Gräff, Frederic Herman, and Gregoire Mariethoz
Earth Syst. Sci. Data, 11, 579–588, https://doi.org/10.5194/essd-11-579-2019, https://doi.org/10.5194/essd-11-579-2019, 2019
Short summary
Short summary
This dataset provides a collection of 10 cm resolution orthomosaics and digital elevation models of the Gornergletscher glacial system (Switzerland). Raw data have been acquired every 2 weeks by intensive UAV surveys and cover the summer 2017. A careful photogrammetric processing ensures the geometrical coherence of the whole dataset.
Raphaël Normand, Guy Simpson, Frédéric Herman, Rabiul Haque Biswas, Abbas Bahroudi, and Bastian Schneider
Earth Surf. Dynam., 7, 321–344, https://doi.org/10.5194/esurf-7-321-2019, https://doi.org/10.5194/esurf-7-321-2019, 2019
Short summary
Short summary
We studied and mapped uplifted marine terraces in southern Iran that are part of the Makran subduction zone. Our results show that most exposed terraces were formed in the last 35 000–250 000 years. Based on their altitude and the paleo sea-level, we derive surface uplift rates of 0.05–5 mm yr−1. The marine terraces, tilted with a short wavelength of 20–30 km, indicate a heterogeneous accumulation of deformation in the overriding plate.
Antoine Cogez, Frédéric Herman, Éric Pelt, Thierry Reuschlé, Gilles Morvan, Christopher M. Darvill, Kevin P. Norton, Marcus Christl, Lena Märki, and François Chabaux
Earth Surf. Dynam., 6, 121–140, https://doi.org/10.5194/esurf-6-121-2018, https://doi.org/10.5194/esurf-6-121-2018, 2018
Short summary
Short summary
Sediments produced by glaciers are transported by rivers and wind toward the ocean. During their journey, these sediments are weathered, and we know that this has an impact on climate. One key factor is time, but the duration of this journey is largely unknown. We were able to measure the average time that sediment spends only in the glacial area. This time is 100–200 kyr, which is long and allows a lot of processes to act on sediments during their journey.
M. Fox, F. Herman, S. D. Willett, and D. A. May
Earth Surf. Dynam., 2, 47–65, https://doi.org/10.5194/esurf-2-47-2014, https://doi.org/10.5194/esurf-2-47-2014, 2014
Related subject area
Cryosphere
Improvements in the land surface configuration to better simulate seasonal snow cover in the European Alps with the CNRM-AROME (cycle 46) convection-permitting regional climate model
A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting
A global–land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: formulation and evaluation at instrumented sites
Design and performance of ELSA v2.0: an isochronal model for ice-sheet layer tracing
Southern Ocean Ice Prediction System version 1.0 (SOIPS v1.0): description of the system and evaluation of synoptic-scale sea ice forecasts
Lagrangian tracking of sea ice in Community Ice CodE (CICE; version 5)
openAMUNDSEN v1.0: an open-source snow-hydrological model for mountain regions
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance
A new 3D full-Stokes calving algorithm within Elmer/Ice (v9.0)
Clustering simulated snow profiles to form avalanche forecast regions
Simulation of snow albedo and solar irradiance profile with the two-stream radiative transfer in snow (TARTES) v2.0 model
Evaluation of MITgcm-based ocean reanalysis for the Southern Ocean
A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers
SnowPappus v1.0, a blowing-snow model for large-scale applications of the Crocus snow scheme
A stochastic parameterization of ice sheet surface mass balance for the Stochastic Ice-Sheet and Sea-Level System Model (StISSM v1.0)
Graphics-processing-unit-accelerated ice flow solver for unstructured meshes using the Shallow-Shelf Approximation (FastIceFlo v1.0.1)
A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)
AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing
Universal differential equations for glacier ice flow modelling
A new model for supraglacial hydrology evolution and drainage for the Greenland Ice Sheet (SHED v1.0)
Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling
A parallel implementation of the confined–unconfined aquifer system model for subglacial hydrology: design, verification, and performance analysis (CUAS-MPI v0.1.0)
Automatic snow type classification of snow micropenetrometer profiles with machine learning algorithms
An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0
A wind-driven snow redistribution module for Alpine3D v3.3.0: adaptations designed for downscaling ice sheet surface mass balance
SnowQM 1.0: A fast R Package for bias-correcting spatial fields of snow water equivalent using quantile mapping
The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere
Glacier Energy and Mass Balance (GEMB): a model of firn processes for cryosphere research
Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean
Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling
SUHMO: an adaptive mesh refinement SUbglacial Hydrology MOdel v1.0
Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau
The Multiple Snow Data Assimilation System (MuSA v1.0)
The Stochastic Ice-Sheet and Sea-Level System Model v1.0 (StISSM v1.0)
Improved representation of the contemporary Greenland ice sheet firn layer by IMAU-FDM v1.2G
Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.
Benchmarking the vertically integrated ice-sheet model IMAU-ICE (version 2.0)
SnowClim v1.0: high-resolution snow model and data for the western United States
Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt
MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes
Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)
Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)
Mapping high-resolution basal topography of West Antarctica from radar data using non-stationary multiple-point geostatistics (MPS-BedMappingV1)
NEMO-Bohai 1.0: a high-resolution ocean and sea ice modelling system for the Bohai Sea, China
An improved regional coupled modeling system for Arctic sea ice simulation and prediction: a case study for 2018
WIFF1.0: a hybrid machine-learning-based parameterization of wave-induced sea ice floe fracture
The Whole Antarctic Ocean Model (WAOM v1.0): development and evaluation
SNICAR-ADv3: a community tool for modeling spectral snow albedo
STEMMUS-UEB v1.0.0: integrated modeling of snowpack and soil water and energy transfer with three complexity levels of soil physical processes
Diego Monteiro, Cécile Caillaud, Matthieu Lafaysse, Adrien Napoly, Mathieu Fructus, Antoinette Alias, and Samuel Morin
Geosci. Model Dev., 17, 7645–7677, https://doi.org/10.5194/gmd-17-7645-2024, https://doi.org/10.5194/gmd-17-7645-2024, 2024
Short summary
Short summary
Modeling snow cover in climate and weather forecasting models is a challenge even for high-resolution models. Recent simulations with CNRM-AROME have shown difficulties when representing snow in the European Alps. Using remote sensing data and in situ observations, we evaluate modifications of the land surface configuration in order to improve it. We propose a new surface configuration, enabling a more realistic simulation of snow cover, relevant for climate and weather forecasting applications.
Alessandro Maissen, Frank Techel, and Michele Volpi
Geosci. Model Dev., 17, 7569–7593, https://doi.org/10.5194/gmd-17-7569-2024, https://doi.org/10.5194/gmd-17-7569-2024, 2024
Short summary
Short summary
By harnessing AI models, this work enables processing large amounts of data, including weather conditions, snowpack characteristics, and historical avalanche data, to predict human-like avalanche forecasts in Switzerland. Our proposed model can significantly assist avalanche forecasters in their decision-making process, thereby facilitating more efficient and accurate predictions crucial for ensuring safety in Switzerland's avalanche-prone regions.
Enrico Zorzetto, Sergey Malyshev, Paul Ginoux, and Elena Shevliakova
Geosci. Model Dev., 17, 7219–7244, https://doi.org/10.5194/gmd-17-7219-2024, https://doi.org/10.5194/gmd-17-7219-2024, 2024
Short summary
Short summary
We describe a new snow scheme developed for use in global climate models, which simulates the interactions of snowpack with vegetation, atmosphere, and soil. We test the new snow model over a set of sites where in situ observations are available. We find that when compared to a simpler snow model, this model improves predictions of seasonal snow and of soil temperature under the snowpack, important variables for simulating both the hydrological cycle and the global climate system.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
Short summary
Short summary
We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Fu Zhao, Xi Liang, Zhongxiang Tian, Ming Li, Na Liu, and Chengyan Liu
Geosci. Model Dev., 17, 6867–6886, https://doi.org/10.5194/gmd-17-6867-2024, https://doi.org/10.5194/gmd-17-6867-2024, 2024
Short summary
Short summary
In this work, we introduce a newly developed Antarctic sea ice forecasting system, namely the Southern Ocean Ice Prediction System (SOIPS). The system is based on a regional sea ice‒ocean‒ice shelf coupled model and can assimilate sea ice concentration observations. By assessing the system's performance in sea ice forecasts, we find that the system can provide reliable Antarctic sea ice forecasts for the next 7 d and has the potential to guide ship navigation in the Antarctic sea ice zone.
Chenhui Ning, Shiming Xu, Yan Zhang, Xuantong Wang, Zhihao Fan, and Jiping Liu
Geosci. Model Dev., 17, 6847–6866, https://doi.org/10.5194/gmd-17-6847-2024, https://doi.org/10.5194/gmd-17-6847-2024, 2024
Short summary
Short summary
Sea ice models are mainly based on non-moving structured grids, which is different from buoy measurements that follow the ice drift. To facilitate Lagrangian analysis, we introduce online tracking of sea ice in Community Ice CodE (CICE). We validate the sea ice tracking with buoys and evaluate the sea ice deformation in high-resolution simulations, which show multi-fractal characteristics. The source code is openly available and can be used in various scientific and operational applications.
Ulrich Strasser, Michael Warscher, Erwin Rottler, and Florian Hanzer
Geosci. Model Dev., 17, 6775–6797, https://doi.org/10.5194/gmd-17-6775-2024, https://doi.org/10.5194/gmd-17-6775-2024, 2024
Short summary
Short summary
openAMUNDSEN is a fully distributed open-source snow-hydrological model for mountain catchments. It includes process representations of an empirical, semi-empirical, and physical nature. It uses temperature, precipitation, humidity, radiation, and wind speed as forcing data and is computationally efficient, of a modular nature, and easily extendible. The Python code is available on GitHub (https://github.com/openamundsen/openamundsen), including documentation (https://doc.openamundsen.org).
Matthias Rauter and Julia Kowalski
Geosci. Model Dev., 17, 6545–6569, https://doi.org/10.5194/gmd-17-6545-2024, https://doi.org/10.5194/gmd-17-6545-2024, 2024
Short summary
Short summary
Snow avalanches can form large powder clouds that substantially exceed the velocity and reach of the dense core. Only a few complex models exist to simulate this phenomenon, and the respective hazard is hard to predict. This work provides a novel flow model that focuses on simple relations while still encapsulating the significant behaviour. The model is applied to reconstruct two catastrophic powder snow avalanche events in Austria.
Till Andreas Soya Rasmussen, Jacob Poulsen, Mads Hvid Ribergaard, Ruchira Sasanka, Anthony P. Craig, Elizabeth C. Hunke, and Stefan Rethmeier
Geosci. Model Dev., 17, 6529–6544, https://doi.org/10.5194/gmd-17-6529-2024, https://doi.org/10.5194/gmd-17-6529-2024, 2024
Short summary
Short summary
Earth system models (ESMs) today strive for better quality based on improved resolutions and improved physics. A limiting factor is the supercomputers at hand and how best to utilize them. This study focuses on the refactorization of one part of a sea ice model (CICE), namely the dynamics. It shows that the performance can be significantly improved, which means that one can either run the same simulations much cheaper or advance the system according to what is needed.
Iain Wheel, Douglas I. Benn, Anna J. Crawford, Joe Todd, and Thomas Zwinger
Geosci. Model Dev., 17, 5759–5777, https://doi.org/10.5194/gmd-17-5759-2024, https://doi.org/10.5194/gmd-17-5759-2024, 2024
Short summary
Short summary
Calving, the detachment of large icebergs from glaciers, is one of the largest uncertainties in future sea level rise projections. This process is poorly understood, and there is an absence of detailed models capable of simulating calving. A new 3D calving model has been developed to better understand calving at glaciers where detailed modelling was previously limited. Importantly, the new model is very flexible. By allowing for unrestricted calving geometries, it can be applied at any location.
Simon Horton, Florian Herla, and Pascal Haegeli
EGUsphere, https://doi.org/10.5194/egusphere-2024-1609, https://doi.org/10.5194/egusphere-2024-1609, 2024
Short summary
Short summary
We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, location, and time. Tested in the Columbia Mountains during winter 2022–23, it accurately matched real forecast regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.
Ghislain Picard and Quentin Libois
EGUsphere, https://doi.org/10.5194/egusphere-2024-1176, https://doi.org/10.5194/egusphere-2024-1176, 2024
Short summary
Short summary
TARTES is a radiative transfer model to compute the reflectivity in the solar domain (albedo), and the profiles of solar light and energy absorption in a multi-layered snowpack whose physical properties are prescribed by the user. It uniquely considers snow grain shape in a flexible way, allowing us to apply the most recent advances showing that snow does not behave as a collection of ice spheres, but instead as a random medium. TARTES is also simple but compares well with other complex models.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Ian Fenty, Matthew Mazloff, Köhl Armin, and Dimitris Menemenlis
EGUsphere, https://doi.org/10.5194/egusphere-2024-727, https://doi.org/10.5194/egusphere-2024-727, 2024
Short summary
Short summary
Global and basin-scale ocean reanalyses are becoming easily accessible. Yet, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluations. We conduct intercomparison analyses of Massachusetts Institute of Technology general circulation model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open ocean temporal variability and Antarctic continental shelves require improvements.
Kévin Fourteau, Julien Brondex, Fanny Brun, and Marie Dumont
Geosci. Model Dev., 17, 1903–1929, https://doi.org/10.5194/gmd-17-1903-2024, https://doi.org/10.5194/gmd-17-1903-2024, 2024
Short summary
Short summary
In this paper, we provide a novel numerical implementation for solving the energy exchanges at the surface of snow and ice. By combining the strong points of previous models, our solution leads to more accurate and robust simulations of the energy exchanges, surface temperature, and melt while preserving a reasonable computation time.
Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis Le Toumelin, Vincent Vionnet, and Mathieu Fructus
Geosci. Model Dev., 17, 1297–1326, https://doi.org/10.5194/gmd-17-1297-2024, https://doi.org/10.5194/gmd-17-1297-2024, 2024
Short summary
Short summary
Increasing the spatial resolution of numerical systems simulating snowpack evolution in mountain areas requires representing small-scale processes such as wind-induced snow transport. We present SnowPappus, a simple scheme coupled with the Crocus snow model to compute blowing-snow fluxes and redistribute snow among grid points at 250 m resolution. In terms of numerical cost, it is suitable for large-scale applications. We present point-scale evaluations of fluxes and snow transport occurrence.
Lizz Ultee, Alexander A. Robel, and Stefano Castruccio
Geosci. Model Dev., 17, 1041–1057, https://doi.org/10.5194/gmd-17-1041-2024, https://doi.org/10.5194/gmd-17-1041-2024, 2024
Short summary
Short summary
The surface mass balance (SMB) of an ice sheet describes the net gain or loss of mass from ice sheets (such as those in Greenland and Antarctica) through interaction with the atmosphere. We developed a statistical method to generate a wide range of SMB fields that reflect the best understanding of SMB processes. Efficiently sampling the variability of SMB will help us understand sources of uncertainty in ice sheet model projections.
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.
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023, https://doi.org/10.5194/gmd-16-7075-2023, 2023
Short summary
Short summary
Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.
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
Short summary
Short summary
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.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687, https://doi.org/10.5194/gmd-16-6671-2023, https://doi.org/10.5194/gmd-16-6671-2023, 2023
Short summary
Short summary
We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Short summary
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Kevin Hank, Lev Tarasov, and Elisa Mantelli
Geosci. Model Dev., 16, 5627–5652, https://doi.org/10.5194/gmd-16-5627-2023, https://doi.org/10.5194/gmd-16-5627-2023, 2023
Short summary
Short summary
Physically meaningful modeling of geophysical system instabilities is numerically challenging, given the potential effects of purely numerical artifacts. Here we explore the sensitivity of ice stream surge activation to numerical and physical model aspects. We find that surge characteristics exhibit a resolution dependency but converge at higher horizontal grid resolutions and are significantly affected by the incorporation of bed thermal and sub-glacial hydrology models.
Yannic Fischler, Thomas Kleiner, Christian Bischof, Jeremie Schmiedel, Roiy Sayag, Raban Emunds, Lennart Frederik Oestreich, and Angelika Humbert
Geosci. Model Dev., 16, 5305–5322, https://doi.org/10.5194/gmd-16-5305-2023, https://doi.org/10.5194/gmd-16-5305-2023, 2023
Short summary
Short summary
Water underneath ice sheets affects the motion of glaciers. This study presents a newly developed code, CUAS-MPI, that simulates subglacial hydrology. It is designed for supercomputers and is hence a parallelized code. We measure the performance of this code for simulations of the entire Greenland Ice Sheet and find that the code works efficiently. Moreover, we validated the code to ensure the correctness of the solution. CUAS-MPI opens new possibilities for simulations of ice sheet hydrology.
Julia Kaltenborn, Amy R. Macfarlane, Viviane Clay, and Martin Schneebeli
Geosci. Model Dev., 16, 4521–4550, https://doi.org/10.5194/gmd-16-4521-2023, https://doi.org/10.5194/gmd-16-4521-2023, 2023
Short summary
Short summary
Snow layer segmentation and snow grain classification are essential diagnostic tasks for cryospheric applications. A SnowMicroPen (SMP) can be used to that end; however, the manual classification of its profiles becomes infeasible for large datasets. Here, we evaluate how well machine learning models automate this task. Of the 14 models trained on the MOSAiC SMP dataset, the long short-term memory model performed the best. The findings presented here facilitate and accelerate SMP data analysis.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
Short summary
Short summary
Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
Short summary
Short summary
Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-298, https://doi.org/10.5194/gmd-2022-298, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better quality maps. The correction can then be extended backwards and forwards in time for periods when better quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the last 60 years at a resolution of one day and one kilometre. This is the first time that such a dataset has been produced.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
Short summary
Short summary
The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
Alex S. Gardner, Nicole-Jeanne Schlegel, and Eric Larour
Geosci. Model Dev., 16, 2277–2302, https://doi.org/10.5194/gmd-16-2277-2023, https://doi.org/10.5194/gmd-16-2277-2023, 2023
Short summary
Short summary
This is the first description of the open-source Glacier Energy and Mass Balance (GEMB) model. GEMB models the ice sheet and glacier surface–atmospheric energy and mass exchange, as well as the firn state. The model is evaluated against the current state of the art and in situ observations and is shown to perform well.
Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
Geosci. Model Dev., 16, 1395–1425, https://doi.org/10.5194/gmd-16-1395-2023, https://doi.org/10.5194/gmd-16-1395-2023, 2023
Short summary
Short summary
State-of-the-art Earth system models simulate the observed sea ice extent relatively well, but this is often due to errors in the dynamic and other processes in the simulated sea ice changes cancelling each other out. We assessed the sensitivity of these processes simulated by the coupled ocean–sea ice model NEMO4.0-SI3 to 18 parameters. The performance of the model in simulating sea ice change processes was ultimately improved by adjusting the three identified key parameters.
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023, https://doi.org/10.5194/gmd-16-719-2023, 2023
Short summary
Short summary
Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.
Anne M. Felden, Daniel F. Martin, and Esmond G. Ng
Geosci. Model Dev., 16, 407–425, https://doi.org/10.5194/gmd-16-407-2023, https://doi.org/10.5194/gmd-16-407-2023, 2023
Short summary
Short summary
We present and validate a novel subglacial hydrology model, SUHMO, based on an adaptive mesh refinement framework. We propose the addition of a pseudo-diffusion to recover the wall melting in channels. Computational performance analysis demonstrates the efficiency of adaptive mesh refinement on large-scale hydrologic problems. The adaptive mesh refinement approach will eventually enable better ice bed boundary conditions for ice sheet simulations at a reasonable computational cost.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
Short summary
Short summary
Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
Short summary
Short summary
Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Vincent Verjans, Alexander A. Robel, Helene Seroussi, Lizz Ultee, and Andrew F. Thompson
Geosci. Model Dev., 15, 8269–8293, https://doi.org/10.5194/gmd-15-8269-2022, https://doi.org/10.5194/gmd-15-8269-2022, 2022
Short summary
Short summary
We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
Geosci. Model Dev., 15, 7121–7138, https://doi.org/10.5194/gmd-15-7121-2022, https://doi.org/10.5194/gmd-15-7121-2022, 2022
Short summary
Short summary
Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
Short summary
Short summary
This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Constantijn J. Berends, Heiko Goelzer, Thomas J. Reerink, Lennert B. Stap, and Roderik S. W. van de Wal
Geosci. Model Dev., 15, 5667–5688, https://doi.org/10.5194/gmd-15-5667-2022, https://doi.org/10.5194/gmd-15-5667-2022, 2022
Short summary
Short summary
The rate at which marine ice sheets such as the West Antarctic ice sheet will retreat in a warming climate and ocean is still uncertain. Numerical ice-sheet models, which solve the physical equations that describe the way glaciers and ice sheets deform and flow, have been substantially improved in recent years. Here we present the results of several years of work on IMAU-ICE, an ice-sheet model of intermediate complexity, which can be used to study ice sheets of both the past and the future.
Abby C. Lute, John Abatzoglou, and Timothy Link
Geosci. Model Dev., 15, 5045–5071, https://doi.org/10.5194/gmd-15-5045-2022, https://doi.org/10.5194/gmd-15-5045-2022, 2022
Short summary
Short summary
We developed a snow model that can be used to quantify snowpack over large areas with a high degree of spatial detail. We ran the model over the western United States, creating a snow and climate dataset for three time periods. Compared to observations of snowpack, the model captured the key aspects of snow across time and space. The model and dataset will be useful in understanding historical and future changes in snowpack, with relevance to water resources, agriculture, and ecosystems.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
Short summary
Short summary
Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, https://doi.org/10.5194/gmd-15-3721-2022, 2022
Short summary
Short summary
We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
Short summary
Short summary
The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Adrian K. Turner, Kara J. Peterson, and Dan Bolintineanu
Geosci. Model Dev., 15, 1953–1970, https://doi.org/10.5194/gmd-15-1953-2022, https://doi.org/10.5194/gmd-15-1953-2022, 2022
Short summary
Short summary
We developed a technique to remap sea ice tracer quantities between circular discrete element distributions. This is needed for a global discrete element method sea ice model being developed jointly by Los Alamos National Laboratory and Sandia National Laboratories that has the potential to better utilize newer supercomputers with graphics processing units and better represent sea ice dynamics. This new remapping technique ameliorates the effect of element distortion created by sea ice ridging.
Zhen Yin, Chen Zuo, Emma J. MacKie, and Jef Caers
Geosci. Model Dev., 15, 1477–1497, https://doi.org/10.5194/gmd-15-1477-2022, https://doi.org/10.5194/gmd-15-1477-2022, 2022
Short summary
Short summary
We provide a multiple-point geostatistics approach to probabilistically learn from training images to fill large-scale irregular geophysical data gaps. With a repository of global topographic training images, our approach models high-resolution basal topography and quantifies the geospatial uncertainty. It generated high-resolution topographic realizations to investigate the impact of basal topographic uncertainty on critical subglacial hydrological flow patterns associated with ice velocity.
Yu Yan, Wei Gu, Andrea M. U. Gierisch, Yingjun Xu, and Petteri Uotila
Geosci. Model Dev., 15, 1269–1288, https://doi.org/10.5194/gmd-15-1269-2022, https://doi.org/10.5194/gmd-15-1269-2022, 2022
Short summary
Short summary
In this study, we developed NEMO-Bohai, an ocean–ice model for the Bohai Sea, China. This study presented the scientific design and technical choices of the parameterizations for the NEMO-Bohai model. The model was calibrated and evaluated with in situ and satellite observations of ocean and sea ice. NEMO-Bohai is intended to be a valuable tool for long-term ocean and ice simulations and climate change studies.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
Geosci. Model Dev., 15, 1155–1176, https://doi.org/10.5194/gmd-15-1155-2022, https://doi.org/10.5194/gmd-15-1155-2022, 2022
Short summary
Short summary
We present an improved coupled modeling system for Arctic sea ice prediction. We perform Arctic sea ice prediction experiments with improved/updated physical parameterizations, which show better skill in predicting sea ice state as well as atmospheric and oceanic state in the Arctic compared with its predecessor. The improved model also shows extended predictive skill of Arctic sea ice after the summer season. This provides an added value of this prediction system for decision-making.
Christopher Horvat and Lettie A. Roach
Geosci. Model Dev., 15, 803–814, https://doi.org/10.5194/gmd-15-803-2022, https://doi.org/10.5194/gmd-15-803-2022, 2022
Short summary
Short summary
Sea ice is a composite of individual pieces, called floes, ranging in horizontal size from meters to kilometers. Variations in sea ice geometry are often forced by ocean waves, a process that is an important target of global climate models as it affects the rate of sea ice melting. Yet directly simulating these interactions is computationally expensive. We present a neural-network-based model of wave–ice fracture that allows models to incorporate their effect without added computational cost.
Ole Richter, David E. Gwyther, Benjamin K. Galton-Fenzi, and Kaitlin A. Naughten
Geosci. Model Dev., 15, 617–647, https://doi.org/10.5194/gmd-15-617-2022, https://doi.org/10.5194/gmd-15-617-2022, 2022
Short summary
Short summary
Here we present an improved model of the Antarctic continental shelf ocean and demonstrate that it is capable of reproducing present-day conditions. The improvements are fundamental and regard the inclusion of tides and ocean eddies. We conclude that the model is well suited to gain new insights into processes that are important for Antarctic ice sheet retreat and global ocean changes. Hence, the model will ultimately help to improve projections of sea level rise and climate change.
Mark G. Flanner, Julian B. Arnheim, Joseph M. Cook, Cheng Dang, Cenlin He, Xianglei Huang, Deepak Singh, S. McKenzie Skiles, Chloe A. Whicker, and Charles S. Zender
Geosci. Model Dev., 14, 7673–7704, https://doi.org/10.5194/gmd-14-7673-2021, https://doi.org/10.5194/gmd-14-7673-2021, 2021
Short summary
Short summary
We present the technical formulation and evaluation of a publicly available code and web-based model to simulate the spectral albedo of snow. Our model accounts for numerous features of the snow state and ambient conditions, including the the presence of light-absorbing matter like black and brown carbon, mineral dust, volcanic ash, and snow algae. Carbon dioxide snow, found on Mars, is also represented. The model accurately reproduces spectral measurements of clean and contaminated snow.
Lianyu Yu, Yijian Zeng, and Zhongbo Su
Geosci. Model Dev., 14, 7345–7376, https://doi.org/10.5194/gmd-14-7345-2021, https://doi.org/10.5194/gmd-14-7345-2021, 2021
Short summary
Short summary
We developed an integrated soil–snow–atmosphere model (STEMMUS-UEB) dedicated to the physical description of snow and soil processes with various complexities. With STEMMUS-UEB, we demonstrated that the snowpack affects not only the soil surface moisture conditions (in the liquid and ice phase) and energy-related states (albedo, LE) but also the subsurface soil water and vapor transfer, which contributes to a better understanding of the hydrothermal implications of the snowpack in cold regions.
Cited articles
Bassis, J.: Hamilton-type principles applied to ice-sheet dynamics: new
approximations for large-scale ice sheet flow, J. Glaciol.,
97, 497–513, 2010. a
Brædstrup, C., Damsgaard, A., and Egholm, D. L.: Ice-sheet modelling
accelerated by graphics cards, Comput. Geosci., 72, 210–220,
2014. a
Brinkerhoff, D. J. and Johnson, J. V.: Data assimilation and prognostic whole ice sheet modelling with the variationally derived, higher order, open source, and fully parallel ice sheet model VarGlaS, The Cryosphere, 7, 1161–1184, https://doi.org/10.5194/tc-7-1161-2013, 2013. a
Brinkerhoff, D. J. and Johnson, J. V.: Dynamics of thermally induced ice
streams simulated with a higher-order flow model, J. Geophys.
Res.-Earth, 120, 1743–1770, 2015. a
Bueler, E. and Brown, J.: Shallow shelf approximation as a “sliding law” in a
thermomechanically coupled ice sheet model, J. Geophys. Res.,
114, F03008, https://doi.org/10.1029/2008JF001179, 2009. a, b
Bueler, E., Brown, J., and Lingle, C.: Exact solutions to the
thermomechanically coupled shallow-ice approximation: effective tools for
verification, J. Glaciol., 53, 499–516, 2007. a
Chorin, A. J.: The numerical solution of the Navier-Stokes equations for an
incompressible fluid, B. Am. Math. Soc., 73,
928–931, 1967. a
Chorin, A. J.: Numerical solution of the Navier-Stokes equations, Math. Comput., 22, 745–762, 1968. a
Clarke, G. K. C., Nitsan, U., and Paterson, W. S. B.: Strain heating and creep
instability in glaciers and ice sheets, Rev. Geophys. Space
Phys., 15, 235–247, 1977. a
Cook, S.: CUDA Programming, Morgan Kaufmann, Elsevier, 2012. a
Crank, J. and Nicolson, P.: A practical method for numerical evaluation of
solutions of partial differential equations of the heat-conduction type,
Mathe. Proc. Cambridge Philos. Soc., 43, 50–67,
https://doi.org/10.1017/S0305004100023197, 1947. a
Egholm, D., M.F., K., Clark, C., and Lesemann, J.: Modeling the flow of
glaciers in steep terrains: The integrated second-order shallow ice
approximation (iSOSIA), J. Geophys. Res.-Earth, 116,
F02012, https://doi.org/10.1029/2010JF001900, 2011. a
Gagliardini, O. and Zwinger, T.: The ISMIP-HOM benchmark experiments performed using the Finite-Element code Elmer, The Cryosphere, 2, 67–76, https://doi.org/10.5194/tc-2-67-2008, 2008. a, b
Gagliardini, O., Zwinger, T., Gillet-Chaulet, F., Durand, G., Favier, L., de Fleurian, B., Greve, R., Malinen, M., Martín, C., Råback, P., Ruokolainen, J., Sacchettini, M., Schäfer, M., Seddik, H., and Thies, J.: Capabilities and performance of Elmer/Ice, a new-generation ice sheet model, Geosci. Model Dev., 6, 1299–1318, https://doi.org/10.5194/gmd-6-1299-2013, 2013. a, b, c, d
Gerya, T.: Introduction to Numerical Geodynamic Modelling, Cambridge
University Press, Cambridge, United Kingdom, 2009. a
Gerya, T. V. and Yuen, D. A.: Characteristics-based marker-in-cell method with
conservative finite-differences schemes for modeling geological flows with
strongly variable transport properties, Phys. Earth Planet.
Int., 140, 293–318, 2003. a
Gilbert, A., Gagliardini, O., Vincent, C., and Wagnon, P.: A 3-D thermal
regime model suitable for cold accumulation zones of polythermal mountain
glaciers, J. Geophys. Res.-Earth, 119, 876–1893,
2014. a
Glen, J. W.: The flow law of ice from measurements in glacier tunnels,
laboratory experiments and the Jungfraufirn borehole experiment, J. Glaciol., 2, 111–114, 1952. a
Goldberg, D.: A variationally-derived, depth-integrated approximation to the
Blatter Pattyn balance, J. Glaciol., 57, 157–170, 2011. a
Gong, Y., Zwinger, T., Åström, J., Altena, B., Schellenberger, T., Gladstone, R., and Moore, J. C.: Simulating the roles of crevasse routing of surface water and basal friction on the surge evolution of Basin 3, Austfonna ice cap, The Cryosphere, 12, 1563–1577, https://doi.org/10.5194/tc-12-1563-2018, 2018. a
Hindmarsh, R. C. A.: Stress gradient damping of thermoviscous ice flow
instabilities, J. Geophys. Res.-Earth., 111, B12409, https://doi.org/10.1029/2005JB004019,
2006. a
Hindmarsh, R. C. A.: Consistent generation of ice-streams via thermo-viscous
instabilities modulated by membrane stresses, Geophys. Res. Lett.,
36, L06502, https://doi.org/10.1029/2008GL036877, 2009. a
Hutter, K.: Theoretical glaciology: material science of ice and the mechanics
of glaciers and ice sheets, Vol. 1, Springer, 1983. a
Huybrechts, P. and Payne, T.: The EISMINT benchmarks for testing ice-sheet
models, Ann. Glaciol., 23, 1–12, 1996. a
Isaac, T., Stadler, G., and Ghattas, O.: Solution of Nonlinear Stokes
Equations Discretized by High-order Finite Elements on Nonconforming and
Anisotropic Meshes, with Application to Ice Sheet Dynamics, SIAM J.
Sci. Comput., 37,
B804–B833, https://doi.org/10.1137/140974407, 2015. a
Jarosch, A.: Icetools: a full Stokes finite element model for glaciers,
Comput. Geosci., 34, 1005–1014, 2008. a
Jouvet, G., Picasso, M., Rappaz, J., and Blatter, H.: A new algorithm to
simulate the dynamics of a glacier: theory and applications, J.
Glaciol., 54, 801–811, 2008. a
Kiss, D., Podladchikov, Y., Duretz, T., and Schmalholz, S. M.: Spontaneous
generation of ductile shear zones by thermal softening: Localization
criterion, 1D to 3D modelling and application to the lithosphere, Earth
Planet. Sci. Lett., 519, 284–296, https://doi.org/10.1016/j.epsl.2019.05.026,
2019. a
Larour, E., Seroussi, H., Morlighem, M., and Rignot, E.: Continental scale,
high order, high spatial resolution, ice sheet modeling using the Ice Sheet
System Model (ISSM), J. Geophys. Res., 117, 1–20, 2012. a
Leng, W., Ju, L., Gunzburger, M., and Ringler, T.: A parallel high- order
accurate finite element nonlinear Stokes ice sheet model and benchmark
experiments, J. Geophys. Res., 117, F01001, https://doi.org/10.1029/2011JF001962, 2012. 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
Morland, L.: Thermomechanical balances of ice sheet flows, Geophys.
Astrophys. Fluid Dynam., 29, 237–266, 1984. a
Nye, J. F.: The flow law of ice from measurements in glacier tunnels,
laboratory experiments and the Jungfraufirn borehole experiment, Proc. Royal Soc. A, 219, 477–489, 1953. a
Ogawa, M., Schubert, G., and Zebib, A.: Numerical simulations of
three-dimensional thermal convection in a fluid with strongly temperature
dependent viscosity, J. Fluid Mech., 233, 299–328, 1991. a
Patankar, S.: Numerical Heat Transfer and Fluid Flow, Comput. Methods Mech.
Thermal Sci. Ser., CRC Press, Boca Raton,Fla, 1980. a
Pattyn, F., Perichon, L., Aschwanden, A., Breuer, B., de Smedt, B., Gagliardini, O., Gudmundsson, G. H., Hindmarsh, R. C. A., Hubbard, A., Johnson, J. V., Kleiner, T., Konovalov, Y., Martin, C., Payne, A. J., Pollard, D., Price, S., Rückamp, M., Saito, F., Souček, O., Sugiyama, S., and Zwinger, T.: Benchmark experiments for higher-order and full-Stokes ice sheet models (ISMIP-HOM), The Cryosphere, 2, 95–108, https://doi.org/10.5194/tc-2-95-2008, 2008. a, b, c, d, e
Payne, T. and Baldwin, D.: Analysis of ice-flow instabilities identified in
the EISMINT intercomparison exercise, Ann. Glaciol., 30, 204–210,
2000. a
Payne, T., Huybrechts, P., Abe-Ouchi, A., Calov, R., Fastook, J., Greve, R.,
Marshall, S., Marsiat, I., Ritz, C., Tarasov, L., and Thomassen, M.: Results
from the EISMINT model intercomparison: the effects of thermomechanical
coupling, J. Glaciol., 46, 227–238, 2000. a
Perego, M., Gunzburger, M., and Burkardt, J.: Parallel finite element
implementation for higher order ice-sheet models, J. Glaciol.,
58, 76–88, 2012. a
Poliakov, A. N. B., 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 Systems: Observations, Modeling and
Theory, 175–195, 1993. a, b
Pollard, D. and DeConto, R. M.: Description of a hybrid ice sheet-shelf model, and application to Antarctica, Geosci. Model Dev., 5, 1273–1295, https://doi.org/10.5194/gmd-5-1273-2012, 2012. a
Räss, L., Simon, N., and Podladchikov, Y.: Spontaneous formation of
fluid escape pipes from subsurface reservoirs, Sci. Rep., 8, 11116, https://doi.org/10.1038/s41598-018-29485-5, 2018. a, b, c
Räss, L., Licul, A., Herman, F., Podladchikov, Y., and Suckale, J.:
FastICE, https://doi.org/10.5281/zenodo.3461171, 2019b. a, b
Robin, G. D. Q.: Ice movement and temperature distribution in glaciers and ice
sheets, J. Glaciol., 2, 523–532, 1955. a
Saito, F., Abe-Ouchi, A., and Blatter, H.: European Ice Sheet Modelling
Initiative (EISMINT) model intercomparison experiments with first-order
mechanics, J. Geophys. Res., 111, F02012, https://doi.org/10.1029/2004JF000273, 2006. a
Schäfer, M., Gillet-Chaulet, F., Gladstone, R., Pettersson, R., A. Pohjola, V., Strozzi, T., and Zwinger, T.: Assessment of heat sources on the control of fast flow of Vestfonna ice cap, Svalbard, The Cryosphere, 8, 1951–1973, https://doi.org/10.5194/tc-8-1951-2014, 2014.
a
Schoof, C. and Hindmarsh, R.: Thin film flows with wall slip: an asymptotic
analysis of higher order glacier flow models, Q. J.
Mechan. Appl. Mathe., 63, 73–114, 2010. a
Shin, D. and Strikwerda, J. C.: Inf-Sup conditions for finite-difference
approximations of the Stokes equations, J. Aust.
Mathe. Soc. B, 39, 121–134, 1997. a
Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., Tignor,
M., and Miller, H.: The physical science basis, 235–337, IPCC report AR4, New York and Cambridge, Cambridge University Press, 2007. a
Tezaur, I. K., Perego, M., Salinger, A. G., Tuminaro, R. S., and Price, S. F.: Albany/FELIX: a parallel, scalable and robust, finite element, first-order Stokes approximation ice sheet solver built for advanced analysis, Geosci. Model Dev., 8, 1197–1220, https://doi.org/10.5194/gmd-8-1197-2015, 2015. a, b
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
Watkins, J., Tezaur, I., and Demeshko, I.: A study on the performance
portability of the finite element assembly process within the Albany Land Ice solver, Elsevier, 2019. a
Weinan, E. and Liu, J.-G.: Projection method I: convergence and numerical
boundary layers, SIAM J. Num. Anal., 1017–1057, 1995. a
Zwinger, T., Greve, R., Gagliardini, O., Shiraiwa, T., and Lyly, M.: A full
Stokes-flow thermo-mechanical model for firn and ice applied to the Gorshkov
crater glacier, Kamchatka, Ann. Glaciol., 45, 29–37, 2007. a
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.
Accurate predictions of future sea level rise require numerical models that predict rapidly...
