Articles | Volume 14, issue 9
https://doi.org/10.5194/gmd-14-5507-2021
© Author(s) 2021. 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-14-5507-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Sep 2021
Development and technical paper |
| 07 Sep 2021
| 07 Sep 2021
The Coastline Evolution Model 2D (CEM2D) V1.1
School of Geography, The University of Melbourne, Parkville,
Melbourne, VIC 3010, Australia
Tom Coulthard
Department of Geography, Geology and Environmental Science, University of Hull, Hull, HU6 7RX, UK
Andrew Barkwith
British Geological Survey, Environmental Science Centre, Keyworth,
Nottingham, NG12 5GG, UK
Daniel R. Parsons
Department of Geography, Geology and Environmental Science, University of Hull, Hull, HU6 7RX, UK
Susan Manson
Environment Agency, Crosskill House, Mill Lane, Beverley, HU17 9JW, UK
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Solomon H. Gebrechorkos, Julian Leyland, Simon J. Dadson, Sagy Cohen, Louise Slater, Michel Wortmann, Philip J. Ashworth, Georgina L. Bennett, Richard Boothroyd, Hannah Cloke, Pauline Delorme, Helen Griffith, Richard Hardy, Laurence Hawker, Stuart McLelland, Jeffrey Neal, Andrew Nicholas, Andrew J. Tatem, Ellie Vahidi, Yinxue Liu, Justin Sheffield, Daniel R. Parsons, and Stephen E. Darby
Hydrol. Earth Syst. Sci., 28, 3099–3118, https://doi.org/10.5194/hess-28-3099-2024, https://doi.org/10.5194/hess-28-3099-2024, 2024
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This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard
EGUsphere, https://doi.org/10.5194/egusphere-2024-1191, https://doi.org/10.5194/egusphere-2024-1191, 2024
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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.
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
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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.
Xuxu Wu, Jonathan Malarkey, Roberto Fernández, Jaco H. Baas, Ellen Pollard, and Daniel R. Parsons
Earth Surf. Dynam., 12, 231–247, https://doi.org/10.5194/esurf-12-231-2024, https://doi.org/10.5194/esurf-12-231-2024, 2024
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The seabed changes from flat to rippled in response to the frictional influence of waves and currents. This experimental study has shown that the speed of this change, the size of ripples that result and even whether ripples appear also depend on the amount of sticky mud present. This new classification on the basis of initial mud content should lead to improvements in models of seabed change in present environments by engineers and the interpretation of past environments by geologists.
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
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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
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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.
Elena Bastianon, Julie A. Hope, Robert M. Dorrell, and Daniel R. Parsons
Earth Surf. Dynam., 10, 1115–1140, https://doi.org/10.5194/esurf-10-1115-2022, https://doi.org/10.5194/esurf-10-1115-2022, 2022
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Biological activity in shallow tidal environments significantly influence sediment dynamics and morphology. Here, a bio-morphodynamic model is developed that accounts for hydro-climate variations in biofilm development to estimate the effect of biostabilisation on the bed. Results reveal that key parameters such as growth rate and temperature strongly influence the development of biofilm under a range of disturbance periodicities and intensities, shaping the channel equilibrium profile.
Chengbin Zou, Paul Carling, Zetao Feng, Daniel Parsons, and Xuanmei Fan
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-119, https://doi.org/10.5194/tc-2022-119, 2022
Manuscript not accepted for further review
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Climate change is causing mountain lakes behind glacier barriers to drain through ice tunnels as catastrophe floods, threatening people and infrastructure downstream. Understanding of how process works can mitigate the impacts by providing advanced warnings. A laboratory study of ice tunnel development improved understanding of how floods evolve. The principles of ice tunnel development were defined numerically and can be used to better model natural floods leading to improved prediction.
Christopher R. Hackney, Grigorios Vasilopoulos, Sokchhay Heng, Vasudha Darbari, Samuel Walker, and Daniel R. Parsons
Earth Surf. Dynam., 9, 1323–1334, https://doi.org/10.5194/esurf-9-1323-2021, https://doi.org/10.5194/esurf-9-1323-2021, 2021
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Unsustainable sand mining poses a threat to the stability of river channels. We use satellite imagery to estimate volumes of material removed from the Mekong River, Cambodia, over the period 2016–2020. We demonstrate that current rates of extraction now exceed previous estimates for the entire Mekong Basin and significantly exceed the volume of sand naturally transported by the river. Our work highlights the importance of satellite imagery in monitoring sand mining activity over large areas.
Sepehr Eslami, Piet Hoekstra, Herman W. J. Kernkamp, Nam Nguyen Trung, Dung Do Duc, Hung Nguyen Nghia, Tho Tran Quang, Arthur van Dam, Stephen E. Darby, Daniel R. Parsons, Grigorios Vasilopoulos, Lisanne Braat, and Maarten van der Vegt
Earth Surf. Dynam., 9, 953–976, https://doi.org/10.5194/esurf-9-953-2021, https://doi.org/10.5194/esurf-9-953-2021, 2021
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Increased salt intrusion jeopardizes freshwater supply to the Mekong Delta, and the current trends are often inaccurately associated with sea level rise. Using observations and models, we show that salinity is highly sensitive to ocean surge, tides, water demand, and upstream discharge. We show that anthropogenic riverbed incision has significantly amplified salt intrusion, exemplifying the importance of preserving sediment budget and riverbed levels to protect deltas against salt intrusion.
Andrew Barkwith, Stan E. Beaubien, Thomas Barlow, Karen Kirk, Thomas R. Lister, Maria C. Tartarello, and Helen Taylor-Curran
Geosci. Instrum. Method. Data Syst., 9, 483–490, https://doi.org/10.5194/gi-9-483-2020, https://doi.org/10.5194/gi-9-483-2020, 2020
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Soil gas flux describes the movement of various gases either to or from the ground. Identifying changes in soil gas flux can lead to a better understanding and detection of leakage from carbon capture and storage (CCS) schemes, diffuse degassing in volcanic and geothermal areas, and greenhouse gas emissions. Traditional chamber-based techniques may require weeks of fieldwork to assess a site. We present a new method to speed up the assessment of diffuse leakage.
Louise Arnal, Liz Anspoks, Susan Manson, Jessica Neumann, Tim Norton, Elisabeth Stephens, Louise Wolfenden, and Hannah Louise Cloke
Geosci. Commun., 3, 203–232, https://doi.org/10.5194/gc-3-203-2020, https://doi.org/10.5194/gc-3-203-2020, 2020
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The Environment Agency (EA), responsible for flood risk management in England, is moving towards the use of probabilistic river flood forecasts. By showing the likelihood of future floods, they can allow earlier anticipation. But making decisions on probabilistic information is complex and interviews with EA decision-makers highlight the practical challenges and opportunities of this transition. We make recommendations to support a successful transition for flood early warning in England.
Christopher J. Skinner, Tom J. Coulthard, Wolfgang Schwanghart, Marco J. Van De Wiel, and Greg Hancock
Geosci. Model Dev., 11, 4873–4888, https://doi.org/10.5194/gmd-11-4873-2018, https://doi.org/10.5194/gmd-11-4873-2018, 2018
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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.
Andres Payo, Bismarck Jigena Antelo, Martin Hurst, Monica Palaseanu-Lovejoy, Chris Williams, Gareth Jenkins, Kathryn Lee, David Favis-Mortlock, Andrew Barkwith, and Michael A. Ellis
Geosci. Model Dev., 11, 4317–4337, https://doi.org/10.5194/gmd-11-4317-2018, https://doi.org/10.5194/gmd-11-4317-2018, 2018
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We describe a new algorithm that automatically delineates the cliff top and toe of a cliffed coastline from a digital elevation model (DEM). The algorithm builds upon existing methods but is specifically designed to resolve very irregular planform coastlines with many bays and capes, such as parts of the coastline of Great Britain.
Wietse I. van de Lageweg, Stuart J. McLelland, and Daniel R. Parsons
Earth Surf. Dynam., 6, 203–215, https://doi.org/10.5194/esurf-6-203-2018, https://doi.org/10.5194/esurf-6-203-2018, 2018
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Sticky sediments are an important component of many rivers and coasts. Stickiness depends on many factors including the presence of micro-organisms, also known as biofilms. We performed a laboratory study to better understand the role of biofilms in controlling sediment transport and dynamics. We find that sand with biofilms requires significantly higher flow velocities to be mobilised compared to uncolonised sand. This will help improve predictions of sediment in response to currents and waves.
Christopher W. Thomas, A. Brad Murray, Andrew D. Ashton, Martin D. Hurst, Andrew K. A. P. Barkwith, and Michael A. Ellis
Earth Surf. Dynam., 4, 871–884, https://doi.org/10.5194/esurf-4-871-2016, https://doi.org/10.5194/esurf-4-871-2016, 2016
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Complex sandy coastlines, such as capes and spits, are important socio-economically while underpinning and protecting important natural habitats. Although they may protect inshore areas, they are inherently fragile and susceptible to erosion. We have explored how spits and capes might adapt to changing wave climate through modelling. We find that coastlines may not be in equilibrium with current conditions, and past shapes may strongly influence those adapting to new wave climates.
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
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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. A. Marra, S. J. McLelland, D. R. Parsons, B. J. Murphy, E. Hauber, and M. G. Kleinhans
Earth Surf. Dynam., 3, 389–408, https://doi.org/10.5194/esurf-3-389-2015, https://doi.org/10.5194/esurf-3-389-2015, 2015
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Groundwater seepage creates valleys with typical theater-shaped valley heads, which are found on Earth and on Mars. For a better interpretation of these systems, we conducted scale experiments on the formation such valleys. We find that entire landscapes, instead of just the shape of the valleys, provide insights into the source of groundwater. Landscapes filled with valleys indicate a local groundwater source in contrast to sparsely dissected landscapes formed by a distal source of groundwater.
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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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.
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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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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.
Hugo Dominguez, Nicolas Riel, and Pierre Lanari
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-189, https://doi.org/10.5194/gmd-2023-189, 2023
Revised manuscript accepted for GMD
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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, minimizing errors and preserving system mass.
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-194, https://doi.org/10.5194/gmd-2023-194, 2023
Revised manuscript accepted for GMD
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We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Ua 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 Upwinding Petrov Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.
Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
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We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
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Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
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Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
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Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
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Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
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To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
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A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
Xiaqiong Zhou and Hann-Ming Henry Juang
Geosci. Model Dev., 16, 3263–3274, https://doi.org/10.5194/gmd-16-3263-2023, https://doi.org/10.5194/gmd-16-3263-2023, 2023
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The National Centers for Environmental Prediction Global Forecast System version 16 experienced model instability failures in real-time runs resolved by increasing the minimum thickness depth parameter. Further investigation revealed that the issue was caused by the advection of geopotential heights at the model's layer interfaces. By replacing high-order boundary conditions with zero-gradient boundary conditions for interface-wind reconstruction, the instability was effectively addressed.
Grant T. Euen, Shangxin Liu, Rene Gassmöller, Timo Heister, and Scott D. King
Geosci. Model Dev., 16, 3221–3239, https://doi.org/10.5194/gmd-16-3221-2023, https://doi.org/10.5194/gmd-16-3221-2023, 2023
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Due to the increasing availability of high-performance computing over the past few decades, numerical models have become an important tool for research. Here we test two geodynamic codes that produce such models: ASPECT, a newer code, and CitcomS, an older one. We show that they produce solutions that are extremely close. As methods and codes become more complex over time, showing reproducibility allows us to seamlessly link previously known information to modern methodologies.
Mohammad Kazem Sharifian, Georges Kesserwani, Alovya Ahmed Chowdhury, Jeffrey Neal, and Paul Bates
Geosci. Model Dev., 16, 2391–2413, https://doi.org/10.5194/gmd-16-2391-2023, https://doi.org/10.5194/gmd-16-2391-2023, 2023
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This paper describes a new release of the LISFLOOD-FP model for fast and efficient flood simulations. It features a new non-uniform grid generator that uses multiwavelet analyses to sensibly coarsens the resolutions where the local topographic variations are smooth. Moreover, the model is parallelised on the graphical processing units (GPUs) to further boost computational efficiency. The performance of the model is assessed for five real-world case studies, noting its potential applications.
Matt J. Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2023-643, https://doi.org/10.5194/egusphere-2023-643, 2023
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In paleoclimate research, proxy system models or PSMs model chemical or biological systems which receive environmental inputs, 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.
Bruno K. Zürcher
Geosci. Model Dev., 16, 1697–1711, https://doi.org/10.5194/gmd-16-1697-2023, https://doi.org/10.5194/gmd-16-1697-2023, 2023
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We present a novel algorithm to efficiently compute Barnes interpolation, which is a method for transforming data values recorded at irregularly spaced points into a corresponding regular grid. In contrast to naive implementations with an algorithmic complexity that depends on the product of the number of sample points and the number of grid points, our approach reduces this dependency to their sum.
David H. Marsico and Paul A. Ullrich
Geosci. Model Dev., 16, 1537–1551, https://doi.org/10.5194/gmd-16-1537-2023, https://doi.org/10.5194/gmd-16-1537-2023, 2023
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Climate models involve several different components, such as the atmosphere, ocean, and land models. Information needs to be exchanged, or remapped, between these models, and devising algorithms for performing this exchange is important for ensuring the accuracy of climate simulations. In this paper, we examine the efficacy of several traditional and novel approaches to remapping on the sphere and demonstrate where our approaches offer improvement.
Moritz Liebl, Jörg Robl, Stefan Hergarten, David Lundbek Egholm, and Kurt Stüwe
Geosci. Model Dev., 16, 1315–1343, https://doi.org/10.5194/gmd-16-1315-2023, https://doi.org/10.5194/gmd-16-1315-2023, 2023
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In this study, we benchmark a topography-based model for glacier erosion (OpenLEM) with a well-established process-based model (iSOSIA). Our experiments show that large-scale erosion patterns and particularly the transformation of valley length geometry from fluvial to glacial conditions are very similar in both models. This finding enables the application of OpenLEM to study the influence of climate and tectonics on glaciated mountains with reasonable computational effort on standard PCs.
James Kent, Thomas Melvin, and Golo Albert Wimmer
Geosci. Model Dev., 16, 1265–1276, https://doi.org/10.5194/gmd-16-1265-2023, https://doi.org/10.5194/gmd-16-1265-2023, 2023
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This paper introduces the Met Office's new shallow water model. The shallow water model is a building block towards the Met Office's new atmospheric dynamical core. The shallow water model is tested on a number of standard spherical shallow water test cases, including flow over mountains and unstable jets. Results show that the model produces similar results to other shallow water models in the literature.
Anthony Gruber, Max Gunzburger, Lili Ju, Rihui Lan, and Zhu Wang
Geosci. Model Dev., 16, 1213–1229, https://doi.org/10.5194/gmd-16-1213-2023, https://doi.org/10.5194/gmd-16-1213-2023, 2023
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This work applies a novel technical tool, multifidelity Monte Carlo (MFMC) estimation, to three climate-related benchmark experiments involving oceanic, atmospheric, and glacial modeling. By considering useful quantities such as maximum sea height and total (kinetic) energy, we show that MFMC leads to predictions which are more accurate and less costly than those obtained by standard methods. This suggests MFMC as a potential drop-in replacement for estimation in realistic climate models.
Piyoosh Jaysaval, Glenn E. Hammond, and Timothy C. Johnson
Geosci. Model Dev., 16, 961–976, https://doi.org/10.5194/gmd-16-961-2023, https://doi.org/10.5194/gmd-16-961-2023, 2023
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We present a robust and highly scalable implementation of numerical forward modeling and inversion algorithms for geophysical electrical resistivity tomography data. The implementation is publicly available and developed within the framework of PFLOTRAN (http://www.pflotran.org), an open-source, state-of-the-art massively parallel subsurface flow and transport simulation code. The paper details all the theoretical and implementation aspects of the new capabilities along with test examples.
Lucas Schauer, Michael J. Schmidt, Nicholas B. Engdahl, Stephen D. Pankavich, David A. Benson, and Diogo Bolster
Geosci. Model Dev., 16, 833–849, https://doi.org/10.5194/gmd-16-833-2023, https://doi.org/10.5194/gmd-16-833-2023, 2023
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We develop a multi-dimensional, parallelized domain decomposition strategy for mass-transfer particle tracking methods in two and three dimensions, investigate different procedures for decomposing the domain, and prescribe an optimal tiling based on physical problem parameters and the number of available CPU cores. For an optimally subdivided diffusion problem, the parallelized algorithm achieves nearly perfect linear speedup in comparison with the serial run-up to thousands of cores.
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313, https://doi.org/10.5194/gmd-16-289-2023, https://doi.org/10.5194/gmd-16-289-2023, 2023
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In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
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While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784, https://doi.org/10.5194/gmd-15-8765-2022, https://doi.org/10.5194/gmd-15-8765-2022, 2022
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A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.
Cited articles
Antolínez, J. A. A., Méndez, F. J., Anderson, D., Ruggiero, P., and
Kaminsky, G. M.: Predicting Climate-Driven Coastlines With a Simple and
Efficient Multiscale Model, J. Geophys. Res.-Earth Surf.,
124, 1596–1624, https://doi.org/10.1029/2018JF004790, 2019.
Ashton, A. and Murray, B.: High-angle wave instability and emergent
shoreline shapes: 1. Modeling of sand waves, flying spits, and capes,
J. Geophys. Res., 111, F04011, https://doi.org/10.1029/2005JF000422,
2006a.
Ashton, A. and Murray, B.: High-angle wave instability and emergent
shoreline shapes: 2. Wave climate analysis and comparisons to nature,
J. Geophys. Res.-Earth Surf., 111, F04012, https://doi.org/10.1029/2005JF000423, 2006b.
Ashton, A., Murray, B., and Littlewood, R.: The response of spit shapes to
wave-angle climates, in: Coastal Sediments'07, edited by: Kraus, N. and
Rosati, N., American Society of Civil Engineers, New Orleans, LA, 2007.
Ashton, A., Murray, B., and Arnault, O.: Formation of coastline features by
large-scale instabilities induced by high-angle waves, Nature, 414,
296–300, https://doi.org/10.1038/35104541, 2001.
Bird, B.: Coastal Geomorphology: An Introduction, John Wiley & Sons,
2011.
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening
design for sensitivity analysis of large models, Environ. Model.
Softw., 22, 1509–1518, https://doi.org/10.1016/J.ENVSOFT.2006.10.004, 2007.
Coulthard, T.: Landscape evolution models: a software review, Hydrol.
Process., 15, 165–173, https://doi.org/10.1002/hyp.426, 2001.
Dickson, M. E., Walkden, M. J. A., and Hall, J. W.: Systemic impacts of
climate change on an eroding coastal region over the twenty-first century,
Clim. Change, 84, 141–166, https://doi.org/10.1007/s10584-006-9200-9,
2007.
French, J., Payo, A., Murray, B., Orford, J., Eliot, M., and Cowell, P.:
Appropriate complexity for the prediction of coastal and estuarine
geomorphic behaviour at decadal to centennial scales, Geomorphology, 256,
3–16, https://doi.org/10.1016/j.geomorph.2015.10.005, 2015.
Gelfenbaum, G. and Kaminsky, G.: Large-scale coastal change in the Columbia
River littoral cell: An overview, Mar. Geol., 273, 1–10, https://doi.org/10.1016/j.margeo.2010.02.007, 2010.
Hallermeier, R.: Uses for a Calculated Limit Depth to Beach Erosion, Coast.
Eng., 1493–1512, https://doi.org/10.1061/9780872621909.090,
1978.
Hanson, H.: GENESIS: a generalized shoreline change numerical model, J. Coast. Res., 5, 1–27, 1989.
Hanson, H. and Kraus, N.: GENESIS: Generalized Model for Simulating
Shoreline Change. Report 1. Technical Reference, No. CERC-TR-89-19-1,
Coastal Engineering Research Center, Vicksburg, MS, 1989.
Hurst, M., Barkwith, A., Thomas, C., and Ellis, M.: Vector-based one-line
model for shoreline evolution: application to explore wave-climate control
on bay morphology, in: AGU Fall Meeting Abstracts, San Franciso, 15–19 December 2014.
Komar, P. D., Lanfredi, N., Baba, M., Dean, R. G., Dyer, K., Healy, T., Ibe,
A. C., Terwindt, J. H. J., and Thom, B. G.: The response of beaches to sea-level
changes – a review of predictive models, J. Coast. Res., 7,
895–921, 1991.
Leach, C.: CEM2D Source Code, Zenodo [code],
https://doi.org/10.5281/zenodo.3341888, 2019.
Leach, C., Coulthard, T., Barkwith, A., Parsons, D., and Manson, S.: CEM2D_Dataset, Zenodo [data set], https://doi.org/10.5281/zenodo.5242895, 2021.
Lesser, G., Roelvink, J., van Kester, J., and Stelling, G.: Development and
validation of a three-dimensional morphological model, Coast. Eng.,
51, 883–915, https://doi.org/10.1016/j.coastaleng.2004.07.014, 2004.
Lowe, J. A., Howard, T. P., Pardaens, A., Tinker, J., Holt, J., Wakelin, S.,
Milne, G., Leake, J., Wolf, J., Horsburgh, K., and Reeder, T.: UK Climate
Projections science report: Marine and coastal projections, Exeter, UK 2009.
McLean, R. and Kirk, R.: Relationships between grain size, size-sorting,
and foreshore slope on mixed sand – shingle beaches, New Zeal. J.
Geol. Geop., 12, 138–155, https://doi.org/10.1080/00288306.1969.10420231, 1969.
Morris, M.: Factorial sampling plans for preliminary computational
experiments, Technometrics, 33,, 161–174, https://doi.org/10.1080/00401706.1991.10484804, 1991.
Murray, B.: Reducing model complexity for explanation and prediction,
Geomorphology, 90, 178–191, https://doi.org/10.1016/j.geomorph.2006.10.020,
2007.
Nam, P., Larson, M., Hanson, H., and Hoan, Le X.: A numerical model of
nearshore waves, currents, and sediment transport, Coast. Eng.,
56, 1084–1096, https://doi.org/10.1016/j.coastaleng.2009.06.007, 2009.
Nicholls, R., Bradbury, A., Burningham, H., Dix, J., Ellis, M., French, J.,
Hall, J., Karunarathna, H., Lawn, J., Pan, S., Reeve, D., Rogers, B., Souza,
A., Stansby, P., Sutherland, J., Tarrant, O., Walkden, M., and Whitehouse,
R.: iCOASST – Integrating Coastal Sediment Systems, Coast. Eng.
Proc., 1, 100, https://doi.org/10.9753/icce.v33.sediment.100, 2012.
Nicholls, R., Birkemeier, W., and Hallermeier, R.: Application of the depth
of closure concept, Proceedings of the Coastal Engineering Conference, 4,
3874–3887, https://doi.org/10.9753/icce.v25, 1997.
Park, J.-Y. and Wells, J.: Longshore Transport at Cape Lookout, North
Carolina: Shoal Evolution and the Regional Sediment Budget, J.
Coast. Res., 211, 1–17, https://doi.org/10.2112/02051.1, 2005.
Pinet, P.: Invitation to Oceanography, Jones & Bartlett Publishers, 2011.
Robinet, A., Idier, D., Castelle, B., and Marieu, V.: A reduced-complexity
shoreline change model combining longshore and cross-shore processes: The
LX-Shore model, Environ. Model. Softw., 109, 1–16,
https://doi.org/10.1016/j.envsoft.2018.08.010, 2018.
Shaw, J., Fader, G. B., and Taylor, R. B.: Submerged early Holocene coastal and
terrestrial landforms on the inner shelves of Atlantic Canada, Quatern.
Int., 206, 24–34, https://doi.org/10.1016/j.quaint.2008.07.017,
2009.
Skinner, C. J., Coulthard, T. J., Schwanghart, W., Van De Wiel, M. J., and Hancock, G.: Global sensitivity analysis of parameter uncertainty in landscape evolution models, Geosci. Model Dev., 11, 4873–4888, https://doi.org/10.5194/gmd-11-4873-2018, 2018.
Stive, M. and de Vriend, H.: Modelling shoreface profile evolution, Mar.
Geol., 126, 235–248, https://doi.org/10.1016/0025-3227(95)00080-I, 1995.
Thomas, C. W., Murray, A. B., Ashton, A. D., Hurst, M. D., Barkwith, A. K. A. P., and Ellis, M. A.: Complex coastlines responding to climate change: do shoreline shapes reflect present forcing or “remember” the distant past?, Earth Surf. Dynam., 4, 871–884, https://doi.org/10.5194/esurf-4-871-2016, 2016.
Tucker, G. and Slingerland, R.: Erosional dynamics, flexural isostasy, and
long-lived escarpments: A numerical modeling study, J. Geophys. Res.-Sol. Ea., 99, 12229–12243, https://doi.org/10.1029/94JB00320, 1994.
Wainwright, J. and Mulligan, M.: Environmental Modelling: Finding
Simplicity in Complexity, Wiley-Blackwell, 2002.
Warren, I. and Bach, H.: MIKE 21: A Modelling System for Estuaries, Coastal
Waters and Seas, Environ. Softw., 7, 229–240, https://doi.org/10.1016/0266-9838(92)90006-P, 1992.
Willgoose, G., Bras, R., and Rodriguez-Iturbe, I.: Results from a new model
of river basin evolution', Earth Surf. Process. Land., 16,
237–254, https://doi.org/10.1002/esp.3290160305, 1991.
Wong, P., Losada, I., Gattuso, J., Hinkel, J., Khattabi, A., McInnes, K.,
Saito, Y., Sallenger, A., Nicholls, R., Santos, F., and Amez, S.: Coastal
systems and low-lying areas, in: Climate Change 2014 Impacts, Adaptation and
Vulnerability: Part A: Global and Sectoral Aspects, Contribution of Working
Group II to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Field, C. B., Barros, V. R., Dokken, D. J., Mach, K. J., Mastrandrea, M. D., Bilir, T. E., Chatterjee, M., Ebi, K. L., Estrada, Y. O., Genova, R. C., Girma, B., Kissel, E. S., Levy, A. N.,
MacCracken, S., Mastrandrea, P. R., and White, L. L., Cambridge University
Press, Cambridge, UK, New York, NY, USA, 361–409, 2014.
van Maanen, B., Barkwith, A., Bonaldo, D., Burningham, H., Murray, B., Payo,
A., Sutherland, J., Thornhill, G., Townend, I., van der Wegen, M., and
Walkden, M.: Simulating mesoscale coastal evolution for decadal coastal
management: A new framework integrating multiple, complementary modelling
approaches, Geomorphology, 256, 68–80, https://doi.org/10.1016/j.geomorph.2015.10.026,
2016.
Vitousek, S., Barnard, P. L., Limber, P., Erikson, L., and Cole, B.: A model
integrating longshore and cross-shore processes for predicting long-term
shoreline response to climate change, J. Geophys. Res.-Earth
Surf., 122, 782–806, https://doi.org/10.1002/2016JF004065, 2017.
Wright, L. and Short, A.: Morphodynamic variability of surf zones and
beaches: A synthesis, Mar. Geol., 56, 93–118, https://doi.org/10.1016/0025-3227(84)90008-2, 1984.
Ziliani, L., Surian, N., Coulthard, T., and Tarantola, S.:
Reduced-complexity modeling of braided rivers: Assessing model performance
by sensitivity analysis, calibration, and validation, J. Geophys. Res.-Earth Surf., 118, 2243–2262, https://doi.org/10.1002/jgrf.20154, 2013.
Short summary
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.
Numerical models can be used to understand how coastal systems evolve over time, including...
