Articles | Volume 17, issue 10
https://doi.org/10.5194/gmd-17-4355-2024
© Author(s) 2024. 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-17-4355-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
24 May 2024
Model description paper |
| 24 May 2024
| 24 May 2024
VISIR-2: ship weather routing in Python
Gianandrea Mannarini
CORRESPONDING AUTHOR
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Lecce, Italy
Mario Leonardo Salinas
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Lecce, Italy
Lorenzo Carelli
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Lecce, Italy
Nicola Petacco
DITEN, Università degli Studi di Genova, via Montallegro 1, 16145 Genoa, Italy
Josip Orović
Maritime Department, University of Zadar, Ul. Mihovila Pavlinovića, 23000 Zadar, Croatia
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Geosci. Model Dev., 12, 3449–3480, https://doi.org/10.5194/gmd-12-3449-2019, https://doi.org/10.5194/gmd-12-3449-2019, 2019
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The VISIR ship-routing model is updated in order to deal with ocean currents.
The optimal tracks we computed through VISIR in the Atlantic ocean show great seasonal and regional variability, following a variable influence of surface gravity waves and currents. We assess how these tracks contribute to voyage energy-efficiency gains through a standard indicator (EEOI) of the International Maritime Organization. Also, the new model features are validated against an exact analytical benchmark.
Giovanni Coppini, Palmalisa Marra, Rita Lecci, Nadia Pinardi, Sergio Cretì, Mario Scalas, Luca Tedesco, Alessandro D'Anca, Leopoldo Fazioli, Antonio Olita, Giuseppe Turrisi, Cosimo Palazzo, Giovanni Aloisio, Sandro Fiore, Antonio Bonaduce, Yogesh Vittal Kumkar, Stefania Angela Ciliberti, Ivan Federico, Gianandrea Mannarini, Paola Agostini, Roberto Bonarelli, Sara Martinelli, Giorgia Verri, Letizia Lusito, Davide Rollo, Arturo Cavallo, Antonio Tumolo, Tony Monacizzo, Marco Spagnulo, Rorberto Sorgente, Andrea Cucco, Giovanni Quattrocchi, Marina Tonani, Massimiliano Drudi, Paola Nassisi, Laura Conte, Laura Panzera, Antonio Navarra, and Giancarlo Negro
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SeaConditions aims to support the users by providing the environmental information in due time and with adequate accuracy in the marine and coastal environments, enforcing users' sea situational awareness. SeaConditions consists of a web and mobile application for the provision of meteorological and oceanographic observation and forecasting products. The iOS/Android apps were downloaded by more than 105 000 users and more than 100 000 users have visited the web version (www.sea-conditions.com).
Alessandro D'Anca, Laura Conte, Paola Nassisi, Cosimo Palazzo, Rita Lecci, Sergio Cretì, Marco Mancini, Alessandra Nuzzo, Maria Mirto, Gianandrea Mannarini, Giovanni Coppini, Sandro Fiore, and Giovanni Aloisio
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Updated situational sea awareness requires an advanced technological system to make data available for decision makers, improving the capacity of intervention and supporting users in managing emergency situations due to natural hazards. The TESSA data platform meets the request of near-real-time access to heterogeneous data with different accuracy, resolution or degrees of aggregation providing efficient and secure data access and strong support to operational oceanographic high-level services.
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A new web-based and mobile Decision Support System (DSS) for Search-And-Rescue (SAR) at sea is presented, and its performance is evaluated using real case scenarios. The system, named OCEAN-SAR, is accessible via the website http://www.ocean-sar.com. OCEAN-SAR simulates drifting objects at sea, using as input ocean currents and wind. The performance of the service is evaluated by comparing simulations to data from the Italian Coast Guard pertaining to actual incidents in the Mediterranean Sea.
Gianandrea Mannarini, Giuseppe Turrisi, Alessandro D'Anca, Mario Scalas, Nadia Pinardi, Giovanni Coppini, Francesco Palermo, Ivano Carluccio, Matteo Scuro, Sergio Cretì, Rita Lecci, Paola Nassisi, and Luca Tedesco
Nat. Hazards Earth Syst. Sci., 16, 1791–1806, https://doi.org/10.5194/nhess-16-1791-2016, https://doi.org/10.5194/nhess-16-1791-2016, 2016
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Safety and efficiency of navigation can be enhanced through a better situational awareness at sea. We designed and realized an operational infrastructure for providing the navigators with optimal routes through various devices: PC, tablets, and smartphones. Sea-state and wind forecasts are used as inputs. Both motor- and sailboat routes are addressed by VISIR.
Gianandrea Mannarini, Nadia Pinardi, Giovanni Coppini, Paolo Oddo, and Alessandro Iafrati
Geosci. Model Dev., 9, 1597–1625, https://doi.org/10.5194/gmd-9-1597-2016, https://doi.org/10.5194/gmd-9-1597-2016, 2016
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VISIR is a new numerical model for the computation of optimal ship routes from meteo-marine forecasts. VISIR offers the scientific community an open platform whereby various ideas and methods for ship route optimization can be shared, tested, and compared to each other.
Gianandrea Mannarini and Lorenzo Carelli
Geosci. Model Dev., 12, 3449–3480, https://doi.org/10.5194/gmd-12-3449-2019, https://doi.org/10.5194/gmd-12-3449-2019, 2019
Short summary
Short summary
The VISIR ship-routing model is updated in order to deal with ocean currents.
The optimal tracks we computed through VISIR in the Atlantic ocean show great seasonal and regional variability, following a variable influence of surface gravity waves and currents. We assess how these tracks contribute to voyage energy-efficiency gains through a standard indicator (EEOI) of the International Maritime Organization. Also, the new model features are validated against an exact analytical benchmark.
Giovanni Coppini, Palmalisa Marra, Rita Lecci, Nadia Pinardi, Sergio Cretì, Mario Scalas, Luca Tedesco, Alessandro D'Anca, Leopoldo Fazioli, Antonio Olita, Giuseppe Turrisi, Cosimo Palazzo, Giovanni Aloisio, Sandro Fiore, Antonio Bonaduce, Yogesh Vittal Kumkar, Stefania Angela Ciliberti, Ivan Federico, Gianandrea Mannarini, Paola Agostini, Roberto Bonarelli, Sara Martinelli, Giorgia Verri, Letizia Lusito, Davide Rollo, Arturo Cavallo, Antonio Tumolo, Tony Monacizzo, Marco Spagnulo, Rorberto Sorgente, Andrea Cucco, Giovanni Quattrocchi, Marina Tonani, Massimiliano Drudi, Paola Nassisi, Laura Conte, Laura Panzera, Antonio Navarra, and Giancarlo Negro
Nat. Hazards Earth Syst. Sci., 17, 533–547, https://doi.org/10.5194/nhess-17-533-2017, https://doi.org/10.5194/nhess-17-533-2017, 2017
Short summary
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SeaConditions aims to support the users by providing the environmental information in due time and with adequate accuracy in the marine and coastal environments, enforcing users' sea situational awareness. SeaConditions consists of a web and mobile application for the provision of meteorological and oceanographic observation and forecasting products. The iOS/Android apps were downloaded by more than 105 000 users and more than 100 000 users have visited the web version (www.sea-conditions.com).
Alessandro D'Anca, Laura Conte, Paola Nassisi, Cosimo Palazzo, Rita Lecci, Sergio Cretì, Marco Mancini, Alessandra Nuzzo, Maria Mirto, Gianandrea Mannarini, Giovanni Coppini, Sandro Fiore, and Giovanni Aloisio
Nat. Hazards Earth Syst. Sci., 17, 171–184, https://doi.org/10.5194/nhess-17-171-2017, https://doi.org/10.5194/nhess-17-171-2017, 2017
Short summary
Short summary
Updated situational sea awareness requires an advanced technological system to make data available for decision makers, improving the capacity of intervention and supporting users in managing emergency situations due to natural hazards. The TESSA data platform meets the request of near-real-time access to heterogeneous data with different accuracy, resolution or degrees of aggregation providing efficient and secure data access and strong support to operational oceanographic high-level services.
Giovanni Coppini, Eric Jansen, Giuseppe Turrisi, Sergio Creti, Elena Yurievna Shchekinova, Nadia Pinardi, Rita Lecci, Ivano Carluccio, Yogesh Vittal Kumkar, Alessandro D'Anca, Gianandrea Mannarini, Sara Martinelli, Palmalisa Marra, Tommaso Capodiferro, and Tommaso Gismondi
Nat. Hazards Earth Syst. Sci., 16, 2713–2727, https://doi.org/10.5194/nhess-16-2713-2016, https://doi.org/10.5194/nhess-16-2713-2016, 2016
Short summary
Short summary
A new web-based and mobile Decision Support System (DSS) for Search-And-Rescue (SAR) at sea is presented, and its performance is evaluated using real case scenarios. The system, named OCEAN-SAR, is accessible via the website http://www.ocean-sar.com. OCEAN-SAR simulates drifting objects at sea, using as input ocean currents and wind. The performance of the service is evaluated by comparing simulations to data from the Italian Coast Guard pertaining to actual incidents in the Mediterranean Sea.
Gianandrea Mannarini, Giuseppe Turrisi, Alessandro D'Anca, Mario Scalas, Nadia Pinardi, Giovanni Coppini, Francesco Palermo, Ivano Carluccio, Matteo Scuro, Sergio Cretì, Rita Lecci, Paola Nassisi, and Luca Tedesco
Nat. Hazards Earth Syst. Sci., 16, 1791–1806, https://doi.org/10.5194/nhess-16-1791-2016, https://doi.org/10.5194/nhess-16-1791-2016, 2016
Short summary
Short summary
Safety and efficiency of navigation can be enhanced through a better situational awareness at sea. We designed and realized an operational infrastructure for providing the navigators with optimal routes through various devices: PC, tablets, and smartphones. Sea-state and wind forecasts are used as inputs. Both motor- and sailboat routes are addressed by VISIR.
Gianandrea Mannarini, Nadia Pinardi, Giovanni Coppini, Paolo Oddo, and Alessandro Iafrati
Geosci. Model Dev., 9, 1597–1625, https://doi.org/10.5194/gmd-9-1597-2016, https://doi.org/10.5194/gmd-9-1597-2016, 2016
Short summary
Short summary
VISIR is a new numerical model for the computation of optimal ship routes from meteo-marine forecasts. VISIR offers the scientific community an open platform whereby various ideas and methods for ship route optimization can be shared, tested, and compared to each other.
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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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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.
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
EGUsphere, https://doi.org/10.5194/egusphere-2023-2930, https://doi.org/10.5194/egusphere-2023-2930, 2023
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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.
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.
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.
Niko Schmidt, Angelika Humbert, and Thomas Slawig
EGUsphere, https://doi.org/10.5194/egusphere-2023-1569, https://doi.org/10.5194/egusphere-2023-1569, 2023
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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 becomes affordable.
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.
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
EGUsphere, https://doi.org/10.48550/arXiv.2304.06058, https://doi.org/10.48550/arXiv.2304.06058, 2023
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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 hard-to-measure quantities. We highlight an approach that ensures accurate results from point data sources (such as height measurements) by evaluating the numerical solution at true point locations. This method improves accuracy, can aid communication between scientists, and is well suited for integration with specialised software that automates the processes.
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.
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.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
EGUsphere, https://doi.org/10.5194/egusphere-2022-863, https://doi.org/10.5194/egusphere-2022-863, 2023
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This paper applies cutting-edge numerical methods to show how uncertain climate change and technological progress affect the future utilization of the scarce world's land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The more uncertain the future crop yields are, the more forest conversion will be necessary to sustain human welfare. Some of that conversion takes place even when crop yields are not actually affected.
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.
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764, https://doi.org/10.5194/gmd-15-8749-2022, https://doi.org/10.5194/gmd-15-8749-2022, 2022
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Knowledge of the internal structures of the major continental ice sheets is improving, thanks to new investigative techniques. These structures are an essential indication of the flow behavior and dynamics of ice transport, which in turn is important for understanding the actual impact of the vast amounts of water trapped in continental ice sheets on global sea-level rise. The software studied here is specifically designed to simulate such structures and their evolution.
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667, https://doi.org/10.5194/gmd-15-8639-2022, https://doi.org/10.5194/gmd-15-8639-2022, 2022
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Finite-element methods (FEMs) permit the use of more flexible unstructured meshes but are rarely used in full waveform inversions (FWIs), an iterative process that reconstructs velocity models of earth’s subsurface, due to computational and memory storage costs. To reduce those costs, novel software is presented allowing the use of high-order mass-lumped FEMs on triangular meshes, together with a material-property mesh-adaptation performance-enhancing strategy, enabling its use in FWIs.
Konstantinos Papadakis, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Markku Alho, Maxime Grandin, Maxime Dubart, Lucile Turc, Hongyang Zhou, Konstantinos Horaites, Ivan Zaitsev, Giulia Cozzani, Maarja Bussov, Evgeny Gordeev, Fasil Tesema, Harriet George, Jonas Suni, Vertti Tarvus, and Minna Palmroth
Geosci. Model Dev., 15, 7903–7912, https://doi.org/10.5194/gmd-15-7903-2022, https://doi.org/10.5194/gmd-15-7903-2022, 2022
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Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global scale. As 6D simulations require enormous amounts of computational resources, Vlasiator uses adaptive mesh refinement (AMR) to lighten the computational burden. However, due to Vlasiator’s grid topology, AMR simulations suffer from grid aliasing artifacts that affect the global results. In this work, we present and evaluate the performance of a mechanism for alleviating those artifacts.
Artur Safin, Damien Bouffard, Firat Ozdemir, Cintia L. Ramón, James Runnalls, Fotis Georgatos, Camille Minaudo, and Jonas Šukys
Geosci. Model Dev., 15, 7715–7730, https://doi.org/10.5194/gmd-15-7715-2022, https://doi.org/10.5194/gmd-15-7715-2022, 2022
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Reconciling the differences between numerical model predictions and observational data is always a challenge. In this paper, we investigate the viability of a novel approach to the calibration of a three-dimensional hydrodynamic model of Lake Geneva, where the target parameters are inferred in terms of distributions. We employ a filtering technique that generates physically consistent model trajectories and implement a neural network to enable bulk-to-skin temperature conversion.
Cited articles
Al-Aboosi, F. Y., El-Halwagi, M. M., Moore, M., and Nielsen, R. B.: Renewable ammonia as an alternative fuel for the shipping industry, Current Opinion in Chemical Engineering, 31, 100670, https://doi.org/10.1016/j.coche.2021.100670, 2021. a
Begovic, E., Bertorello, C., Rinauro, B., and Rosano, G.: Simplified operational guidance for second generation intact stability criteria, Ocean Eng., 270, 113583, https://doi.org/10.1016/j.oceaneng.2022.113583, 2023. a
Bentley, J. L.: Multidimensional binary search trees used for associative searching, Communications of the ACM, 18, 509–517, 1975. a
Bouman, E. A., Lindstad, E., Rialland, A. I., and Strømman, A. H.: State-of-the-art technologies, measures, and potential for reducing GHG emissions from shipping – A review, Transport. Res. D-Tr. E., 52, 408–421, https://doi.org/10.1016/j.trd.2017.03.022, 2017. a, b, c, d
Breithaupt, S. A., Copping, A., Tagestad, J., and Whiting, J.: Maritime Route Delineation using AIS Data from the Atlantic Coast of the US, J. Navigation, 70, 379–394, https://doi.org/10.1017/S0373463316000606, 2017. a
Breivik, Ø. and Allen, A. A.: An operational search and rescue model for the Norwegian Sea and the North Sea, J. Marine Syst., 69, 99–113, 2008. a
Bullock, S., Mason, J., Broderick, J., and Larkin, A.: Shipping and the Paris climate agreement: a focus on committed emissions, BMC Energy, 2, 5, https://doi.org/10.1186/s42500-020-00015-2, 2020. a, b, c
Carchen, A., Gaggero, T., Besio, G., Mazzino, A., and Villa, D.: A method for the probabilistic assessment of the on-board comfort on a passenger vessel route, Ocean Eng., 225, 108702, https://doi.org/10.1016/j.oceaneng.2021.108, 2021. a
Claughton, A.: Developments in the IMS VPP Formulations, in: Fourteenth Chesapeake sailing yacht symposium, Annapolis, Maryland, 1–20, 1999. a
Claughton, A. R.: Developments in hydrodynamic force models for velocity prediction programs, in: Proceedings of the International Conference The Modern Yacht, The Royal Institution of Naval Architects, RINA, Paper: P2003-4 Proceedings, ISBN 0 903055 91 0, 2003. a
Dijkstra, E. W.: A note on two problems in connexion with graphs, Numerische Mathematik, 1.1, 269–271, https://doi.org/10.1145/3544585.3544600, 1959. a
DoS: Green Shipping Corridors Framework, Tech. rep., US Department of State, https://www.state.gov/green-shipping-corridors-framework/ (last access: 20 May 2024), 2022. a
Faber, J., van Seters, D., and Scholten, P.: Shipping GHG emissions 2030: Analysis of the maximum technical abatement potential, Tech. rep., CE Delft, 2023. a
Farkas, A., Parunov, J., and Katalinić, M.: Wave statistics for the middle Adriatic Sea, Pomorski zbornik, 52, 33–47, https://doi.org/10.18048/2016.52.02, 2016. a
Feeman, T. G.: Portraits of the Earth: A mathematician looks at maps, American Mathematical Soc., 18, 62–64, ISBN 0-8218-3255-7, 2002. a
Filipiak, D., Węcel, K., Stróżyna, M., Michalak, M., and Abramowicz, W.: Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm, Bus. Inf. Syst. Eng., 62, 435–450, https://doi.org/10.1007/s12599-020-00661-0, 2020. a
gov.uk: Clydebank Declaration, Tech. rep., UK Department for Transport, https://www.gov.uk/government/publications/cop-26-clydebank-declaration-for-green-shipping-corridors (last access: 20 May 2024), 2021. a
Guedes Soares, C.: Effect of heavy weather maneuvering on the wave-induced vertical bending moments in ship structures, J. Ship Res., 34, 60–68, 1990. a
IMO: MEPC.304(72) Initial IMO strategy on reduction of GHG emissions from ships, Tech. Rep. Annex 11, International Maritime Organization, London, UK, 2018a. a
IMO: SDC 5/J/7 Finalization of second generation intact stability criteria, Tech. rep., International Maritime Organization, London, UK, 2018b. a
IMO: MEPC.80/(WP.12) Report of the Working Group on Reduction of GHG Emissions from Ships Report of the Working Group on Reduction of GHG Emissions from Ships, Tech. rep., International Maritime Organization, London, UK, 2023. a
IPCC: Sixth Assessment Report, WG3, Ch.10, Tech. rep., IPCC, https://www.ipcc.ch/report/ar6/wg3/ (last access: 20 May 2024), 2022. a
IPCC: AR6 Synthesis Report: Climate Change 2023, Tech. rep., IPCC, https://www.ipcc.ch/report/ar6/syr/ (last access: 20 May 2024), 2023. a
Ladany, S. P. and Levi, O.: Search for optimal sailing policy, European J. Oper. Res., 260, 222–231, https://doi.org/10.1016/j.ejor.2016.12.013, 2017. a
Laxague, N. J., Özgökmen, T. M., Haus, B. K., Novelli, G., Shcherbina, A., Sutherland, P., Guigand, C. M., Lund, B., Mehta, S., Alday, M., and Molemaker, J.: Observations of near-surface current shear help describe oceanic oil and plastic transport, Geophys. Res. Lett., 45, 245–249, 2018. a
Le Goff, C., Boussidi, B., Mironov, A., Guichoux, Y., Zhen, Y., Tandeo, P., Gueguen, S., and Chapron, B.: Monitoring the greater Agulhas Current with AIS data information, J. Geophys. Res.-Oceans, 126, e2021JC017228, https://doi.org/10.1029/2021JC017228, 2021. a
Li, H. and Yang, Z.: Incorporation of AIS data-based machine learning into unsupervised route planning for maritime autonomous surface ships, Transport. Res. E-Log., 176, 103171, https://doi.org/10.1016/j.tre.2023.103171, 2023. a
Lindstad, H., Asbjørnslett, B. E., and Jullumstrø, E.: Assessment of profit, cost and emissions by varying speed as a function of sea conditions and freight market, Transport. Res. D-Tr. E., 19, 5–12, https://doi.org/10.1016/j.trd.2012.11.001, 2013. a
Lionello, P., Cogo, S., Galati, M., and Sanna, A.: The Mediterranean surface wave climate inferred from future scenario simulations, Global Planet. Change, 63, 152–162, https://doi.org/10.1016/j.gloplacha.2008.03.004, 2008. a
Lolla, S. V. T.: Path planning and adaptive sampling in the coastal ocean, Ph.D. thesis, Massachusetts Institute of Technology, http://hdl.handle.net/1721.1/103438 (last access: 20 May 2024), 2016. a
Maneewongvatana, S. and Mount, D. M.: It's okay to be skinny, if your friends are fat, in: Center for geometric computing 4th annual workshop on computational geometry, 2, 1–8, 1999. a
Mannarini, G. and Carelli, L.: [VISIR-1.b ship routing model] source code (Matlab), Zenodo [code], https://doi.org/10.5281/zenodo.2563074, 2019a. a
Mannarini, G., Lecci, R., and Coppini, G.: Introducing sailboats into ship routing system VISIR, in: 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA), IEEE, 1–6, https://doi.org/10.1109/IISA.2015.7387962, 2015. a
Mannarini, G., Turrisi, G., D'Anca, A., Scalas, M., Pinardi, N., Coppini, G., Palermo, F., Carluccio, I., Scuro, M., Cretì, S., Lecci, R., Nassisi, P., and Tedesco, L.: VISIR: technological infrastructure of an operational service for safe and efficient navigation in the Mediterranean Sea, Nat. Hazards Earth Syst. Sci., 16, 1791–1806, https://doi.org/10.5194/nhess-16-1791-2016, 2016b. a
Mannarini, G., Carelli, L., Zissis, D., Spiliopoulos, G., and Chatzikokolakis, K.: Preliminary inter-comparison of AIS data and optimal ship tracks, TransNav, 13, 53–61, https://doi.org/10.12716/1001.13.01.04, 2019a. a
Mannarini, G., Carelli, L., Orović, J., Martinkus, C. P., and Coppini, G.: Towards Least-CO2 Ferry Routes in the Adriatic Sea, J. Marine Sci. Eng., 9, 115, https://doi.org/10.3390/jmse9020115, 2021. a
Mason, J., Larkin, A., Bullock, S., van der Kolk, N., and Broderick, J. F.: Quantifying voyage optimisation with wind propulsion for short-term CO2 mitigation in shipping, Ocean Eng., 289, 116065, https://doi.org/10.1016/j.oceaneng.2023.116065, 2023a. a, b
Mason, J., Larkin, A., and Gallego-Schmid, A.: Mitigating stochastic uncertainty from weather routing for ships with wind propulsion, Ocean Eng., 281, 114674, https://doi.org/10.1016/j.oceaneng.2023.114674, 2023b. a, b, c, d
Miola, A., Marra, M., and Ciuffo, B.: Designing a climate change policy for the international maritime transport sector: Market-based measures and technological options for global and regional policy actions, Energy Policy, 39, 5490–5498, https://doi.org/10.1016/j.enpol.2011.05.013, 2011. a
Orda, A. and Rom, R.: Shortest-path and Minimum-delay Algorithms in Networks with Time-dependent Edge-length, J. ACM, 37, 607–625, https://doi.org/10.1145/79147.214078, 1990. a, b, c
Salinas, M.: Ferry case study, TIB AVPortal [video], https://doi.org/10.5446/s_1687, 2024a. a
Salinas, M.: Sailboat case study, TIB AVPortal [video], https://doi.org/10.5446/s_1688, 2024b. a
Salinas, M. L., Carelli, L., and Mannarini, G.: [VISIR-2 ship weather routing model] raw data, Zenodo [data set], https://doi.org/10.5281/zenodo.10674079, 2024b. a
Salinas, M. L., Carelli, L., and Mannarini, G.: [VISIR-2 ship weather routing model] intermediate products, Zenodo [data set], https://doi.org/10.5281/zenodo.10674082, 2024c. a
Sidoti, D., Avvari, G. V., Mishra, M., Zhang, L., Nadella, B. K., Peak, J. E., Hansen, J. A., and Pattipati, K. R.: A Multiobjective Path-Planning Algorithm With Time Windows for Asset Routing in a Dynamic Weather-Impacted Environment, IEEE T. Syst. Man Cyb., 47, 3256–3271, https://doi.org/10.1109/TSMC.2016.2573271, 2017. a
Sidoti, D., Pattipati, K. R., and Bar-Shalom, Y.: Minimum Time Sailing Boat Path Algorithm, IEEE J. Ocean. Eng., 48, 307–322, https://doi.org/10.1109/JOE.2022.3227985, 2023. a, b
Smith, T. and Shaw, A.: An overview of the discussions from IMO MEPC 80 and Frequently Asked Questions, Tech. rep., UMAS, 2023. a
Svanberg, M., Ellis, J., Lundgren, J., and Landälv, I.: Renewable methanol as a fuel for the shipping industry, Renew. Sustain. Energ. Rev., 94, 1217–1228, https://doi.org/10.1016/j.rser.2018.06.058, 2018. a
Szlapczynska, J.: Multi-objective weather routing with customised criteria and constraints, J. Navigation, 68, 338–354, https://doi.org/10.1017/S0373463314000691, 2015. a
Tagliaferri, F., Philpott, A., Viola, I., and Flay, R.: On risk attitude and optimal yacht racing tactics, Ocean Eng., 90, 149–154, https://doi.org/10.1016/j.oceaneng.2014.07.020, 2014. a
Theocharis, A., Balopoulos, E., Kioroglou, S., Kontoyiannis, H., and Iona, A.: A synthesis of the circulation and hydrography of the South Aegean Sea and the Straits of the Cretan Arc (March 1994–January 1995), Prog. Oceanogr., 44, 469–509, https://doi.org/10.1016/S0079-6611(99)00041-5, 1999. a
van den Bremer, T. S. and Breivik, Ø.: Stokes drift, Philos. T. Roy. Soc. A, 376, 20170104, https://doi.org/10.1098/rsta.2017.0104, 2018. a
Vettor, R. and Guedes Soares, C.: Development of a ship weather routing system, Ocean Eng., 123, 1–14, https://doi.org/10.1016/j.oceaneng.2016.06.035, 2016. a, b
Wilson, G., Aruliah, D., Brown, C. T., Hong, N. P. C., Davis, M., Guy, R. T., Haddock, S. H., Huff, K. D., Mitchell, I. M., Plumbley, M. D., Waugh, B., White, E. P., and Wilson, P: Best practices for scientific computing, PLoS Biol., 12, e1001745, https://doi.org/10.1371/journal.pbio.1001745, 2014. a, b
Zis, T. P., Psaraftis, H. N., and Ding, L.: Ship weather routing: A taxonomy and survey, Ocean Eng., 213, 107697, https://doi.org/10.1016/j.oceaneng.2020.107697, 2020. a, b, c
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Short summary
Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and...
