Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4873-2018
© Author(s) 2018. 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-11-4873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
06 Dec 2018
Model evaluation paper |
| 06 Dec 2018
| 06 Dec 2018
Global sensitivity analysis of parameter uncertainty in landscape evolution models
Christopher J. Skinner
CORRESPONDING AUTHOR
School of Environmental Sciences, University of Hull, Hull, UK
Tom J. Coulthard
School of Environmental Sciences, University of Hull, Hull, UK
Wolfgang Schwanghart
Institute of Earth and Environmental Science, Potsdam University,
Potsdam-Golm, Germany
Marco J. Van De Wiel
Centre for Agroecology, Water and Resilience, Coventry University,
Coventry, UK
Greg Hancock
University of Newcastle, Callaghan, Australia
Related authors
Joshua M. Wolstenholme, Christopher J. Skinner, David Milan, Robert E. Thomas, and Daniel R. Parsons
Geosci. Model Dev., 18, 1395–1411, https://doi.org/10.5194/gmd-18-1395-2025, https://doi.org/10.5194/gmd-18-1395-2025, 2025
Short summary
Short summary
Leaky wooden dams are a type of natural flood management intervention that aims to reduce flood risk downstream by temporarily holding back water during a storm event and releasing it afterwards. These structures alter the river hydrology, and therefore the geomorphology, yet often this is excluded from numerical models. Here we show that by not simulating geomorphology, we are currently underestimating the efficacy of these structures to reduce the flood peak and store water.
Joshua M. Wolstenholme, Christopher J. Skinner, David J. Milan, Robert E. Thomas, and Daniel R. Parsons
EGUsphere, https://doi.org/10.5194/egusphere-2024-3001, https://doi.org/10.5194/egusphere-2024-3001, 2024
This preprint is open for discussion and under review for Earth Surface Dynamics (ESurf).
Short summary
Short summary
Leaky wooden dams are a popular form of natural flood management used to slow the flow of water by increasing floodplain connectivity whilst decreasing connectivity along the river profile. By monitoring two leaky wooden dams in North Yorkshire, UK, we present the geomorphological response to their installation, highlighting that the structures significantly increase channel complexity in response to different river flow conditions.
Christopher J. Skinner and Thomas J. Coulthard
Earth Surf. Dynam., 11, 695–711, https://doi.org/10.5194/esurf-11-695-2023, https://doi.org/10.5194/esurf-11-695-2023, 2023
Short summary
Short summary
Landscape evolution models allow us to simulate the way the Earth's surface is shaped and help us to understand relevant processes, in turn helping us to manage landscapes better. The models typically represent the land surface using a grid of square cells of equal size, averaging heights in those squares. This study shows that the size chosen by the modeller for these grid cells is important, with larger sizes making sediment output events larger but less frequent.
Chris Skinner
Geosci. Commun., 3, 1–17, https://doi.org/10.5194/gc-3-1-2020, https://doi.org/10.5194/gc-3-1-2020, 2020
Short summary
Short summary
This study demonstrates how the popular mediums of video games, virtual reality, and science festivals can be combined with research data to produce useful tools for engaging the public with geosciences. Using the Flash Flood! simulation, it is demonstrated that the approach produces positive engagements and increases curiosity about flood risk and geomorphology; this is hoped to "plant the seeds" for fruitful engagements in the future with relevant agencies.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
Short summary
Short summary
Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Rolf Hut, Casper Albers, Sam Illingworth, and Chris Skinner
Geosci. Commun., 2, 117–124, https://doi.org/10.5194/gc-2-117-2019, https://doi.org/10.5194/gc-2-117-2019, 2019
Short summary
Short summary
Game worlds in modern computer games, while they include very Earth-like landscapes, are ultimately fake. Since games can be used for learning, we wondered if people pick up wrong information from games. Using a survey we tested if people with a background in geoscience are better than people without such a background at distinguishing if game landscapes are realistic. We found that geoscientists are significantly better at this, but the difference is small and overall everyone is good at it.
Tom J. Coulthard and Christopher J. Skinner
Earth Surf. Dynam., 4, 757–771, https://doi.org/10.5194/esurf-4-757-2016, https://doi.org/10.5194/esurf-4-757-2016, 2016
Short summary
Short summary
Landscape evolution models are driven by climate or precipitation data. We show that higher-resolution data lead to greater basin sediment yields (> 100 % increase) despite minimal changes in hydrological outputs. Spatially, simulations over 1000 years show finer-resolution data lead to a systematic bias of more erosion in headwater streams with more deposition in valley floors. This could have important implications for the long-term predictions of past and present landscape evolution models.
Joshua M. Wolstenholme, Christopher J. Skinner, David Milan, Robert E. Thomas, and Daniel R. Parsons
Geosci. Model Dev., 18, 1395–1411, https://doi.org/10.5194/gmd-18-1395-2025, https://doi.org/10.5194/gmd-18-1395-2025, 2025
Short summary
Short summary
Leaky wooden dams are a type of natural flood management intervention that aims to reduce flood risk downstream by temporarily holding back water during a storm event and releasing it afterwards. These structures alter the river hydrology, and therefore the geomorphology, yet often this is excluded from numerical models. Here we show that by not simulating geomorphology, we are currently underestimating the efficacy of these structures to reduce the flood peak and store water.
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard
Geosci. Model Dev., 18, 803–818, https://doi.org/10.5194/gmd-18-803-2025, https://doi.org/10.5194/gmd-18-803-2025, 2025
Short summary
Short summary
In geosciences, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. We introduce a generalizable framework for calibrating numerical models, with a case study of the geomorphological model CAESAR-Lisflood. This approach efficiently identifies the optimal set of parameters for a given numerical model, enabling retrospective and prospective analyses at various temporal resolutions.
Joshua M. Wolstenholme, Christopher J. Skinner, David J. Milan, Robert E. Thomas, and Daniel R. Parsons
EGUsphere, https://doi.org/10.5194/egusphere-2024-3001, https://doi.org/10.5194/egusphere-2024-3001, 2024
This preprint is open for discussion and under review for Earth Surface Dynamics (ESurf).
Short summary
Short summary
Leaky wooden dams are a popular form of natural flood management used to slow the flow of water by increasing floodplain connectivity whilst decreasing connectivity along the river profile. By monitoring two leaky wooden dams in North Yorkshire, UK, we present the geomorphological response to their installation, highlighting that the structures significantly increase channel complexity in response to different river flow conditions.
Boris Gailleton, Philippe Steer, Philippe Davy, Wolfgang Schwanghart, and Thomas Bernard
Earth Surf. Dynam., 12, 1295–1313, https://doi.org/10.5194/esurf-12-1295-2024, https://doi.org/10.5194/esurf-12-1295-2024, 2024
Short summary
Short summary
We use cutting-edge algorithms and conceptual simplifications to solve the equations that describe surface water flow. Using quantitative data on rainfall and elevation, GraphFlood calculates river width and depth and approximates erosive power, making it a suitable tool for large-scale hazard management and understanding the relationship between rivers and mountains.
Wolfgang Schwanghart, Ankit Agarwal, Kristen Cook, Ugur Ozturk, Roopam Shukla, and Sven Fuchs
Nat. Hazards Earth Syst. Sci., 24, 3291–3297, https://doi.org/10.5194/nhess-24-3291-2024, https://doi.org/10.5194/nhess-24-3291-2024, 2024
Short summary
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The Himalayan landscape is particularly susceptible to extreme events, which interfere with increasing populations and the expansion of settlements and infrastructure. This preface introduces and summarizes the nine papers that are part of the special issue,
Estimating and predicting natural hazards and vulnerabilities in the Himalayan region.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
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The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
Sebastian Vogel, Katja Emmerich, Ingmar Schröter, Eric Bönecke, Wolfgang Schwanghart, Jörg Rühlmann, Eckart Kramer, and Robin Gebbers
SOIL, 10, 321–333, https://doi.org/10.5194/soil-10-321-2024, https://doi.org/10.5194/soil-10-321-2024, 2024
Short summary
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To rapidly obtain high-resolution soil pH data, pH sensors can measure the pH value directly in the field under the current soil moisture (SM) conditions. The influence of SM on pH and on its measurement quality was studied. An SM increase causes a maximum pH increase of 1.5 units. With increasing SM, the sensor pH value approached the standard pH value measured in the laboratory. Thus, at high soil moisture, calibration of the sensor pH values to the standard pH value is negligible.
Charlotte Lyddon, Nguyen Chien, Grigorios Vasilopoulos, Michael Ridgill, Sogol Moradian, Agnieszka Olbert, Thomas Coulthard, Andrew Barkwith, and Peter Robins
Nat. Hazards Earth Syst. Sci., 24, 973–997, https://doi.org/10.5194/nhess-24-973-2024, https://doi.org/10.5194/nhess-24-973-2024, 2024
Short summary
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Recent storms in the UK, like Storm Ciara in 2020, show how vulnerable estuaries are to the combined effect of sea level and river discharge. We show the combinations of sea levels and river discharges that cause flooding in the Conwy estuary, N Wales. The results showed flooding was amplified under moderate conditions in the middle estuary and elsewhere sea state or river flow dominated the hazard. Combined sea and river thresholds can improve prediction and early warning of compound flooding.
Anna-Maartje de Boer, Wolfgang Schwanghart, Jürgen Mey, Basanta Raj Adhikari, and Tony Reimann
Geochronology, 6, 53–70, https://doi.org/10.5194/gchron-6-53-2024, https://doi.org/10.5194/gchron-6-53-2024, 2024
Short summary
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This study tested the application of single-grain feldspar luminescence for dating and reconstructing sediment dynamics of an extreme mass movement event in the Himalayan mountain range. Our analysis revealed that feldspar signals can be used to estimate the age range of the deposits if the youngest subpopulation from a sample is retrieved. The absence of clear spatial relationships with our bleaching proxies suggests that sediments were transported under extremely limited light exposure.
Jürgen Mey, Wolfgang Schwanghart, Anna-Maartje de Boer, and Tony Reimann
Geochronology, 5, 377–389, https://doi.org/10.5194/gchron-5-377-2023, https://doi.org/10.5194/gchron-5-377-2023, 2023
Short summary
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This study presents the results of an outdoor flume experiment to evaluate the effect of turbidity on the bleaching of fluvially transported sediment. Our main conclusions are that even small amounts of sediment lead to a substantial change in the intensity and frequency distribution of light within the suspension and that flow turbulence is an important prerequisite for bleaching grains during transport.
Monika Pfau, Georg Veh, and Wolfgang Schwanghart
The Cryosphere, 17, 3535–3551, https://doi.org/10.5194/tc-17-3535-2023, https://doi.org/10.5194/tc-17-3535-2023, 2023
Short summary
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Cast shadows have been a recurring problem in remote sensing of glaciers. We show that the length of shadows from surrounding mountains can be used to detect gains or losses in glacier elevation.
Christopher J. Skinner and Thomas J. Coulthard
Earth Surf. Dynam., 11, 695–711, https://doi.org/10.5194/esurf-11-695-2023, https://doi.org/10.5194/esurf-11-695-2023, 2023
Short summary
Short summary
Landscape evolution models allow us to simulate the way the Earth's surface is shaped and help us to understand relevant processes, in turn helping us to manage landscapes better. The models typically represent the land surface using a grid of square cells of equal size, averaging heights in those squares. This study shows that the size chosen by the modeller for these grid cells is important, with larger sizes making sediment output events larger but less frequent.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
Short summary
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During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-295, https://doi.org/10.5194/nhess-2022-295, 2023
Manuscript not accepted for further review
Short summary
Short summary
The current socioeconomic development in the Himalayan region leads to a rapid expansion of the road network and an increase in the exposure to landslides. Our study along the NH-7 demonstrates the scale of this challenge as we detect more than one partially or fully road-blocking landslide per road kilometer. We identify the main controlling variables, i.e. slope angle, rainfall amount and lithology. As our approach uses a minimum of data, it can be extended to more complicated road networks.
Chloe Leach, Tom Coulthard, Andrew Barkwith, Daniel R. Parsons, and Susan Manson
Geosci. Model Dev., 14, 5507–5523, https://doi.org/10.5194/gmd-14-5507-2021, https://doi.org/10.5194/gmd-14-5507-2021, 2021
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Numerical models can be used to understand how coastal systems evolve over time, including likely responses to climate change. However, many existing models are aimed at simulating 10- to 100-year time periods do not represent a vertical dimension and are thus unable to include the effect of sea-level rise. The Coastline Evolution Model 2D (CEM2D) presented in this paper is an advance in this field, with the inclusion of the vertical coastal profile against which the water level can be altered.
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
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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.
Abraham J. Gibson, Danielle C. Verdon-Kidd, Greg R. Hancock, and Garry Willgoose
Hydrol. Earth Syst. Sci., 24, 1985–2002, https://doi.org/10.5194/hess-24-1985-2020, https://doi.org/10.5194/hess-24-1985-2020, 2020
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To be better prepared for drought, we need to be able to characterize how they begin, translate to on-ground impacts and how they end. We created a 100-year drought record for an area on the east coast of Australia and compared this with soil moisture and vegetation data. Drought reduces vegetation and soil moisture, but recovery rates are different across different catchments. Our methods can be universally applied and show the need to develop area-specific data to inform drought management.
Dirk Scherler and Wolfgang Schwanghart
Earth Surf. Dynam., 8, 245–259, https://doi.org/10.5194/esurf-8-245-2020, https://doi.org/10.5194/esurf-8-245-2020, 2020
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Drainage divides are believed to provide clues about divide migration and the instability of landscapes. Here, we present a novel approach to extract drainage divides from digital elevation models and to order them in a drainage divide network. We present our approach by studying natural and artificial landscapes generated with a landscape evolution model and disturbed to induce divide migration.
Dirk Scherler and Wolfgang Schwanghart
Earth Surf. Dynam., 8, 261–274, https://doi.org/10.5194/esurf-8-261-2020, https://doi.org/10.5194/esurf-8-261-2020, 2020
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Drainage divides are believed to provide clues about divide migration and the instability of landscapes. Here, we present a novel approach to extract drainage divides from digital elevation models and to order them in a drainage divide network. We present our approach by studying natural and artificial landscapes generated with a landscape evolution model and disturbed to induce divide migration.
Chris Skinner
Geosci. Commun., 3, 1–17, https://doi.org/10.5194/gc-3-1-2020, https://doi.org/10.5194/gc-3-1-2020, 2020
Short summary
Short summary
This study demonstrates how the popular mediums of video games, virtual reality, and science festivals can be combined with research data to produce useful tools for engaging the public with geosciences. Using the Flash Flood! simulation, it is demonstrated that the approach produces positive engagements and increases curiosity about flood risk and geomorphology; this is hoped to "plant the seeds" for fruitful engagements in the future with relevant agencies.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
Short summary
Short summary
Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Rolf Hut, Casper Albers, Sam Illingworth, and Chris Skinner
Geosci. Commun., 2, 117–124, https://doi.org/10.5194/gc-2-117-2019, https://doi.org/10.5194/gc-2-117-2019, 2019
Short summary
Short summary
Game worlds in modern computer games, while they include very Earth-like landscapes, are ultimately fake. Since games can be used for learning, we wondered if people pick up wrong information from games. Using a survey we tested if people with a background in geoscience are better than people without such a background at distinguishing if game landscapes are realistic. We found that geoscientists are significantly better at this, but the difference is small and overall everyone is good at it.
W. D. Dimuth P. Welivitiya, Garry R. Willgoose, and Greg R. Hancock
Earth Surf. Dynam., 7, 591–607, https://doi.org/10.5194/esurf-7-591-2019, https://doi.org/10.5194/esurf-7-591-2019, 2019
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The paper describes a model that simultaneously evolves both the soil profile and the landform, creating a coupled soilscape–landscape evolution model. The physics in the model is presented and justified from physical processes. The behaviour of the model is then explored for a variety of process formulations for a one-dimensional hillslope consisting of a flat upslope, steep midslope, and flat lowlands, exploring the erosion and deposition behaviour, and soil profile evolution over time.
Wolfgang Schwanghart and Dirk Scherler
Earth Surf. Dynam., 5, 821–839, https://doi.org/10.5194/esurf-5-821-2017, https://doi.org/10.5194/esurf-5-821-2017, 2017
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River profiles derived from digital elevation models are affected by errors. Here we present two new algorithms – quantile carving and the CRS algorithm – to hydrologically correct river profiles. Both algorithms preserve the downstream decreasing shape of river profiles, while CRS additionally smooths profiles to avoid artificial steps. Our algorithms are able to cope with the problems of overestimation and asymmetric error distributions.
Sagy Cohen, Tal Svoray, Shai Sela, Greg Hancock, and Garry Willgoose
Earth Surf. Dynam., 5, 101–112, https://doi.org/10.5194/esurf-5-101-2017, https://doi.org/10.5194/esurf-5-101-2017, 2017
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Soil-depleted hillslopes across the Mediterranean and Europe are thought to be the result of human activity in the last 2–5 millennia. We study a site on the margin between Mediterranean and desert climates which was subject to intense wind-borne soil accumulation for tens of thousands of years but is now mostly bare. Using a numerical simulator we investigated the processes that may have led to this landscape and identified the specific signatures of different processes and drivers.
Benjamin Campforts, Wolfgang Schwanghart, and Gerard Govers
Earth Surf. Dynam., 5, 47–66, https://doi.org/10.5194/esurf-5-47-2017, https://doi.org/10.5194/esurf-5-47-2017, 2017
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Despite a growing interest in landscape evolution models, accuracy assessment of the numerical methods they are based on has received little attention. We test a higher-order flux-limiting finite-volume method to simulate river incision and tectonic displacement. We show that this scheme significantly influences the evolution of simulated landscapes and the spatial and temporal variability of erosion rates. Moreover, it allows for the simulation of lateral tectonic displacement on a fixed grid.
Jorge A. Ramirez, Umamaheshwaran Rajasekar, Dhruvesh P. Patel, Tom J. Coulthard, and Margreth Keiler
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-544, https://doi.org/10.5194/hess-2016-544, 2016
Preprint retracted
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Surat, India has a population of 4.5 million and lies on the banks of the river Tapi and is located downstream from a dam that repeatedly floods the city. Floods in Surat may increase in occurrence due to urbanization and climate change. We have developed a model that floods 50 % of the city and exposes > 60 % of the population and critical infrastructure. We highlight how modeling has contributed to changes in flood risk management and resulted in actions that increase city resilience.
Tom J. Coulthard and Christopher J. Skinner
Earth Surf. Dynam., 4, 757–771, https://doi.org/10.5194/esurf-4-757-2016, https://doi.org/10.5194/esurf-4-757-2016, 2016
Short summary
Short summary
Landscape evolution models are driven by climate or precipitation data. We show that higher-resolution data lead to greater basin sediment yields (> 100 % increase) despite minimal changes in hydrological outputs. Spatially, simulations over 1000 years show finer-resolution data lead to a systematic bias of more erosion in headwater streams with more deposition in valley floors. This could have important implications for the long-term predictions of past and present landscape evolution models.
W. D. Dimuth P. Welivitiya, Garry R. Willgoose, Greg R. Hancock, and Sagy Cohen
Earth Surf. Dynam., 4, 607–625, https://doi.org/10.5194/esurf-4-607-2016, https://doi.org/10.5194/esurf-4-607-2016, 2016
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This paper generalises the physical dependence of the relationship between contributing area, local slope, and the surface soil grading first described by Cohen et al. (2009, 2010) using a soil evolution model called SSSPAM. We show the influence of weathering on the equilibrium soil profile and its spatial distribution. We conclude that the soil grading relationship is robust and will occur for most equilibrium soils. This spatial organisation is also true below the surface.
N. K. Meyer, W. Schwanghart, O. Korup, and F. Nadim
Nat. Hazards Earth Syst. Sci., 15, 985–995, https://doi.org/10.5194/nhess-15-985-2015, https://doi.org/10.5194/nhess-15-985-2015, 2015
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In the past decades the importance of and reliance on all kinds of transport networks has grown extensively making them more vulnerable to any kind of hazard. The linear structure of road networks is especially sensitive to debris flows, a process frequently occurring in the mountainous area of Norway. The paper quantifies the functional risk associated with these processes. The results reveal that the costs related to route closures are strongly related to the information status of drivers.
C. C. Clason, D. W. F. Mair, P. W. Nienow, I. D. Bartholomew, A. Sole, S. Palmer, and W. Schwanghart
The Cryosphere, 9, 123–138, https://doi.org/10.5194/tc-9-123-2015, https://doi.org/10.5194/tc-9-123-2015, 2015
W. Schwanghart and D. Scherler
Earth Surf. Dynam., 2, 1–7, https://doi.org/10.5194/esurf-2-1-2014, https://doi.org/10.5194/esurf-2-1-2014, 2014
T. J. Coulthard and M. J. Van de Wiel
Earth Surf. Dynam., 1, 13–27, https://doi.org/10.5194/esurf-1-13-2013, https://doi.org/10.5194/esurf-1-13-2013, 2013
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An automatic mesh generator for coupled 1D–2D hydrodynamic models
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 2: A semi-discrete error analysis framework for assessing coupling schemes
jsmetrics v0.2.0: a Python package for metrics and algorithms used to identify or characterise atmospheric jet streams
P3D-BRNS v1.0.0: a three-dimensional, multiphase, multicomponent, pore-scale reactive transport modelling package for simulating biogeochemical processes in subsurface environments
MinVoellmy v1: a lightweight model for simulating rapid mass movements based on a modified Voellmy rheology
Scalable Feature Extraction and Tracking (SCAFET): a general framework for feature extraction from large climate data sets
Sweep interpolation: a cost-effective semi-Lagrangian scheme in the Global Environmental Multiscale model
CHONK 1.0: landscape evolution framework: cellular automata meets graph theory
Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations
Calibration of absorbing boundary layers for geoacoustic wave modeling in pseudo-spectral time-domain methods
GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling
Parameterization and tuning of the Bay of Biscay Atlantis model v1
A comparison of Eulerian and Lagrangian methods for vertical particle transport in the water column
AutoQS v1: automatic parametrization of QuickSampling based on training images analysis
Implementation and application of ensemble optimal interpolation on an operational chemistry weather model for improving PM2.5 and visibility predictions
A dynamical core based on a discontinuous Galerkin method for higher-order finite-element sea ice modeling
GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation
Leveraging Google's Tensor Processing Units for tsunami-risk mitigation planning in the Pacific Northwest and beyond
An improved subgrid channel model with upwind-form artificial diffusion for river hydrodynamics and floodplain inundation simulation
Joshua M. Wolstenholme, Christopher J. Skinner, David Milan, Robert E. Thomas, and Daniel R. Parsons
Geosci. Model Dev., 18, 1395–1411, https://doi.org/10.5194/gmd-18-1395-2025, https://doi.org/10.5194/gmd-18-1395-2025, 2025
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Leaky wooden dams are a type of natural flood management intervention that aims to reduce flood risk downstream by temporarily holding back water during a storm event and releasing it afterwards. These structures alter the river hydrology, and therefore the geomorphology, yet often this is excluded from numerical models. Here we show that by not simulating geomorphology, we are currently underestimating the efficacy of these structures to reduce the flood peak and store water.
Jiayi Lai, Lanning Wang, Qizhong Wu, Yizhou Yang, and Fang Wang
Geosci. Model Dev., 18, 1089–1102, https://doi.org/10.5194/gmd-18-1089-2025, https://doi.org/10.5194/gmd-18-1089-2025, 2025
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High-performance computing limitations often hinder numerical model development. Traditional models use double precision for accuracy, which is computationally expensive. Lower precision reduces costs but can introduce errors. The quasi-double-precision (QDP) algorithm helps mitigate these errors. This study applies the QDP algorithm to the Model for Prediction Across Scales – Atmosphere, showing reduced errors and computational time, making it an efficient solution for large-scale simulations.
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Bödecker, Carsten F. Dormann, Florian Pappenberger, and Gianpaolo Balsamo
Geosci. Model Dev., 18, 921–937, https://doi.org/10.5194/gmd-18-921-2025, https://doi.org/10.5194/gmd-18-921-2025, 2025
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We compared spatiotemporal forecasts of three machine learning models that learned water and energy
states on the land surface from a physical model scheme. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the globe. We found that all approaches deliver highly accurate approximations of the physical dynamic at long time horizons, implying their usefulness to advance land surface forecasting with synthetic data.
states on the land surface from a physical model scheme. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the globe. We found that all approaches deliver highly accurate approximations of the physical dynamic at long time horizons, implying their usefulness to advance land surface forecasting with synthetic data.
Maarten van Ormondt, Tim Leijnse, Roel de Goede, Kees Nederhoff, and Ap van Dongeren
Geosci. Model Dev., 18, 843–861, https://doi.org/10.5194/gmd-18-843-2025, https://doi.org/10.5194/gmd-18-843-2025, 2025
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Accurate flood risk assessments are crucial for storm protection. To achieve efficiency, computational costs must be minimized. This paper introduces a novel subgrid approach for linear inertial equations (LIEs) with bed level and friction variations, implemented in the Super-Fast INundation of CoastS (SFINCS) model. Pre-processed lookup tables enhance simulation precision with lower costs. Validations show significant accuracy improvement even at coarser resolutions.
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard
Geosci. Model Dev., 18, 803–818, https://doi.org/10.5194/gmd-18-803-2025, https://doi.org/10.5194/gmd-18-803-2025, 2025
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In geosciences, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. We introduce a generalizable framework for calibrating numerical models, with a case study of the geomorphological model CAESAR-Lisflood. This approach efficiently identifies the optimal set of parameters for a given numerical model, enabling retrospective and prospective analyses at various temporal resolutions.
Yuta Kawai and Hirofumi Tomita
Geosci. Model Dev., 18, 725–762, https://doi.org/10.5194/gmd-18-725-2025, https://doi.org/10.5194/gmd-18-725-2025, 2025
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When considering future high-resolution atmospheric simulations with O(10–100 m) grid spacing, such as global large-eddy simulations, numerical errors with the conventional low-order dynamical cores can contaminate the effects of turbulent parameterization. To achieve high-order discretization, we developed a global atmospheric dynamical core using the discontinuous Galerkin method (DGM). By conducting several validation tests, we discussed the impact of a high-order DGM on atmospheric flows.
Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 17, 8853–8872, https://doi.org/10.5194/gmd-17-8853-2024, https://doi.org/10.5194/gmd-17-8853-2024, 2024
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Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
Joonlee Lee, Myong-In Lee, Sunlae Tak, Eunkyo Seo, and Yong-Keun Lee
Geosci. Model Dev., 17, 8799–8816, https://doi.org/10.5194/gmd-17-8799-2024, https://doi.org/10.5194/gmd-17-8799-2024, 2024
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We developed an advanced snow water equivalent (SWE) data assimilation framework using satellite data based on a land surface model. The results of this study highlight the beneficial impact of data assimilation by effectively combining land surface model and satellite-derived data according to their relative uncertainty, thereby controlling not only transitional regions but also the regions with heavy snow accumulation that are difficult to detect by satellite.
Frédéric Parrenin, Marie Bouchet, Christo Buizert, Emilie Capron, Ellen Corrick, Russell Drysdale, Kenji Kawamura, Amaëlle Landais, Robert Mulvaney, Ikumi Oyabu, and Sune Olander Rasmussen
Geosci. Model Dev., 17, 8735–8750, https://doi.org/10.5194/gmd-17-8735-2024, https://doi.org/10.5194/gmd-17-8735-2024, 2024
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The Paleochrono-1.1 probabilistic dating model allows users to derive a common and optimized chronology for several paleoclimatic sites from various archives (ice cores, speleothems, marine cores, lake cores, etc.). It combines prior sedimentation scenarios with chronological information such as dated horizons, dated intervals, stratigraphic links and (for ice cores) Δdepth observations. Paleochrono-1.1 is available under an open-source license.
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 17, 8399–8420, https://doi.org/10.5194/gmd-17-8399-2024, https://doi.org/10.5194/gmd-17-8399-2024, 2024
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This paper introduces a numerical method for simulating particle-based aerosol transport in atmospheric models. We detail the various numerical properties of the advection order method and demonstrate its implementation in a 3D weather prediction model (WRF) for the first time. Particle-based techniques improve the accuracy of aerosol size and composition predictions, which are key for aerosol–cloud and aerosol–radiation interactions.
John Thuburn
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-153, https://doi.org/10.5194/gmd-2024-153, 2024
Revised manuscript accepted for GMD
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A new computational fluid dynamics code for simulating the atmospheric boundary layer and convection is presented. Moist thermodynamics is formulated via thermodynamic potentials, avoiding inconsistencies that can be introduced with conventional approaches. Numerical methods typical of weather and climate models are used, with no explicit subgrid scheme. Results highlight some advantages (e.g., large time steps) and disadvantages (e.g., weak vertical fluxes near the surface) of this approach.
Matt J. Fischer
Geosci. Model Dev., 17, 6745–6760, https://doi.org/10.5194/gmd-17-6745-2024, https://doi.org/10.5194/gmd-17-6745-2024, 2024
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In paleoclimate research, proxy system models (PSMs) model chemical or biological systems which receive environmental input and output (e.g., geochemical signals). The environmental inputs are rarely noiseless, which causes problems when calibrating multi-input PSMs. Here a PSM is developed which includes generalized noise in both model inputs and outputs and prior information. A quasi-Bayesian method enhances the stability of the solution of the Measurement Error Proxy System Model.
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024, https://doi.org/10.5194/gmd-17-6227-2024, 2024
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We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Úa for solving level-set equations, specifically those related to the dynamic representation of moving ice fronts within numerical ice sheet models. Our results demonstrate that the streamline upwind Petrov–Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.
Hugo Dominguez, Nicolas Riel, and Pierre Lanari
Geosci. Model Dev., 17, 6105–6122, https://doi.org/10.5194/gmd-17-6105-2024, https://doi.org/10.5194/gmd-17-6105-2024, 2024
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Predicting the behaviour of magmatic systems is important for understanding Earth's matter and heat transport. Numerical modelling is a technique that can predict complex systems at different scales of space and time by solving equations using various techniques. This study tests four algorithms to find the best way to transport the melt composition. The "weighted essentially non-oscillatory" algorithm emerges as the best choice, minimising errors and preserving system mass well.
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
Geosci. Model Dev., 17, 5369–5386, https://doi.org/10.5194/gmd-17-5369-2024, https://doi.org/10.5194/gmd-17-5369-2024, 2024
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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
Geosci. Model Dev., 17, 5009–5021, https://doi.org/10.5194/gmd-17-5009-2024, https://doi.org/10.5194/gmd-17-5009-2024, 2024
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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.
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Short summary
Landscape evolution models are computer models used to understand how the Earth’s surface changes over time. Although designed to look at broad changes over very long time periods, they could potentially be used to predict smaller changes over shorter periods. However, to do this we need to better understand how the models respond to changes in their set-up – i.e. their behaviour. This work presents a method which can be applied to these models in order to better understand their behaviour.
Landscape evolution models are computer models used to understand how the Earth’s surface...
