Articles | Volume 15, issue 20
Geosci. Model Dev., 15, 7903–7912, 2022
https://doi.org/10.5194/gmd-15-7903-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 15, 7903–7912, 2022
https://doi.org/10.5194/gmd-15-7903-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
27 Oct 2022
Development and technical paper
| 27 Oct 2022
Spatial filtering in a 6D hybrid-Vlasov scheme to alleviate adaptive mesh refinement artifacts: a case study with Vlasiator (versions 5.0, 5.1, and 5.2.1)
Konstantinos Papadakis et al.
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Vertti Tarvus, Lucile Turc, Markus Battarbee, Jonas Suni, Xóchitl Blanco-Cano, Urs Ganse, Yann Pfau-Kempf, Markku Alho, Maxime Dubart, Maxime Grandin, Andreas Johlander, Konstantinos Papadakis, and Minna Palmroth
Ann. Geophys., 39, 911–928, https://doi.org/10.5194/angeo-39-911-2021, https://doi.org/10.5194/angeo-39-911-2021, 2021
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We use simulations of Earth's magnetosphere and study the formation of transient wave structures in the region where the solar wind first interacts with the magnetosphere. These transients move earthward and play a part in the solar wind–magnetosphere interaction. We show that the transients are a common feature and their properties are altered as they move earthward, including an increase in temperature, decrease in solar wind speed and an alteration in their propagation properties.
Minna Palmroth, Maxime Grandin, Theodoros Sarris, Eelco Doornbos, Stelios Tourgaidis, Anita Aikio, Stephan Buchert, Mark A. Clilverd, Iannis Dandouras, Roderick Heelis, Alex Hoffmann, Nickolay Ivchenko, Guram Kervalishvili, David J. Knudsen, Anna Kotova, Han-Li Liu, David M. Malaspina, Günther March, Aurélie Marchaudon, Octav Marghitu, Tomoko Matsuo, Wojciech J. Miloch, Therese Moretto-Jørgensen, Dimitris Mpaloukidis, Nils Olsen, Konstantinos Papadakis, Robert Pfaff, Panagiotis Pirnaris, Christian Siemes, Claudia Stolle, Jonas Suni, Jose van den IJssel, Pekka T. Verronen, Pieter Visser, and Masatoshi Yamauchi
Ann. Geophys., 39, 189–237, https://doi.org/10.5194/angeo-39-189-2021, https://doi.org/10.5194/angeo-39-189-2021, 2021
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This is a review paper that summarises the current understanding of the lower thermosphere–ionosphere (LTI) in terms of measurements and modelling. The LTI is the transition region between space and the atmosphere and as such of tremendous importance to both the domains of space and atmosphere. The paper also serves as the background for European Space Agency Earth Explorer 10 candidate mission Daedalus.
Markus Battarbee, Thiago Brito, Markku Alho, Yann Pfau-Kempf, Maxime Grandin, Urs Ganse, Konstantinos Papadakis, Andreas Johlander, Lucile Turc, Maxime Dubart, and Minna Palmroth
Ann. Geophys., 39, 85–103, https://doi.org/10.5194/angeo-39-85-2021, https://doi.org/10.5194/angeo-39-85-2021, 2021
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We investigate local acceleration dynamics of electrons with a new numerical simulation method, which is an extension of a world-leading kinetic plasma simulation. We describe how large supercomputer simulations can be used to initialize the electron simulations and show numerical stability for the electron method. We show that features of our simulated electrons match observations from Earth's magnetic tail region.
Vertti Tarvus, Lucile Turc, Markus Battarbee, Jonas Suni, Xóchitl Blanco-Cano, Urs Ganse, Yann Pfau-Kempf, Markku Alho, Maxime Dubart, Maxime Grandin, Andreas Johlander, Konstantinos Papadakis, and Minna Palmroth
Ann. Geophys., 39, 911–928, https://doi.org/10.5194/angeo-39-911-2021, https://doi.org/10.5194/angeo-39-911-2021, 2021
Short summary
Short summary
We use simulations of Earth's magnetosphere and study the formation of transient wave structures in the region where the solar wind first interacts with the magnetosphere. These transients move earthward and play a part in the solar wind–magnetosphere interaction. We show that the transients are a common feature and their properties are altered as they move earthward, including an increase in temperature, decrease in solar wind speed and an alteration in their propagation properties.
Andrei Runov, Maxime Grandin, Minna Palmroth, Markus Battarbee, Urs Ganse, Heli Hietala, Sanni Hoilijoki, Emilia Kilpua, Yann Pfau-Kempf, Sergio Toledo-Redondo, Lucile Turc, and Drew Turner
Ann. Geophys., 39, 599–612, https://doi.org/10.5194/angeo-39-599-2021, https://doi.org/10.5194/angeo-39-599-2021, 2021
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In collisionless systems like space plasma, particle velocity distributions contain fingerprints of ongoing physical processes. However, it is challenging to decode this information from observations. We used hybrid-Vlasov simulations to obtain ion velocity distribution functions at different locations and at different stages of the Earth's magnetosphere dynamics. The obtained distributions provide valuable examples that may be directly compared with observations by satellites in space.
Minna Palmroth, Savvas Raptis, Jonas Suni, Tomas Karlsson, Lucile Turc, Andreas Johlander, Urs Ganse, Yann Pfau-Kempf, Xochitl Blanco-Cano, Mojtaba Akhavan-Tafti, Markus Battarbee, Maxime Dubart, Maxime Grandin, Vertti Tarvus, and Adnane Osmane
Ann. Geophys., 39, 289–308, https://doi.org/10.5194/angeo-39-289-2021, https://doi.org/10.5194/angeo-39-289-2021, 2021
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Magnetosheath jets are high-velocity features within the Earth's turbulent magnetosheath, separating the Earth's magnetic domain from the solar wind. The characteristics of the jets are difficult to assess statistically as a function of their lifetime because normally spacecraft observe them only at one position within the magnetosheath. This study first confirms the accuracy of the model used, Vlasiator, by comparing it to MMS spacecraft, and then carries out the first jet lifetime statistics.
Minna Palmroth, Maxime Grandin, Theodoros Sarris, Eelco Doornbos, Stelios Tourgaidis, Anita Aikio, Stephan Buchert, Mark A. Clilverd, Iannis Dandouras, Roderick Heelis, Alex Hoffmann, Nickolay Ivchenko, Guram Kervalishvili, David J. Knudsen, Anna Kotova, Han-Li Liu, David M. Malaspina, Günther March, Aurélie Marchaudon, Octav Marghitu, Tomoko Matsuo, Wojciech J. Miloch, Therese Moretto-Jørgensen, Dimitris Mpaloukidis, Nils Olsen, Konstantinos Papadakis, Robert Pfaff, Panagiotis Pirnaris, Christian Siemes, Claudia Stolle, Jonas Suni, Jose van den IJssel, Pekka T. Verronen, Pieter Visser, and Masatoshi Yamauchi
Ann. Geophys., 39, 189–237, https://doi.org/10.5194/angeo-39-189-2021, https://doi.org/10.5194/angeo-39-189-2021, 2021
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Short summary
This is a review paper that summarises the current understanding of the lower thermosphere–ionosphere (LTI) in terms of measurements and modelling. The LTI is the transition region between space and the atmosphere and as such of tremendous importance to both the domains of space and atmosphere. The paper also serves as the background for European Space Agency Earth Explorer 10 candidate mission Daedalus.
Markus Battarbee, Thiago Brito, Markku Alho, Yann Pfau-Kempf, Maxime Grandin, Urs Ganse, Konstantinos Papadakis, Andreas Johlander, Lucile Turc, Maxime Dubart, and Minna Palmroth
Ann. Geophys., 39, 85–103, https://doi.org/10.5194/angeo-39-85-2021, https://doi.org/10.5194/angeo-39-85-2021, 2021
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Short summary
We investigate local acceleration dynamics of electrons with a new numerical simulation method, which is an extension of a world-leading kinetic plasma simulation. We describe how large supercomputer simulations can be used to initialize the electron simulations and show numerical stability for the electron method. We show that features of our simulated electrons match observations from Earth's magnetic tail region.
Maxime Dubart, Urs Ganse, Adnane Osmane, Andreas Johlander, Markus Battarbee, Maxime Grandin, Yann Pfau-Kempf, Lucile Turc, and Minna Palmroth
Ann. Geophys., 38, 1283–1298, https://doi.org/10.5194/angeo-38-1283-2020, https://doi.org/10.5194/angeo-38-1283-2020, 2020
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Plasma waves are ubiquitous in the Earth's magnetosphere. They are responsible for many energetic processes happening in Earth's atmosphere, such as auroras. In order to understand these processes, thorough investigations of these waves are needed. We use a state-of-the-art numerical model to do so. Here we investigate the impact of different spatial resolutions in the model on these waves in order to improve in the future the model without wasting computational resources.
Markus Battarbee, Xóchitl Blanco-Cano, Lucile Turc, Primož Kajdič, Andreas Johlander, Vertti Tarvus, Stephen Fuselier, Karlheinz Trattner, Markku Alho, Thiago Brito, Urs Ganse, Yann Pfau-Kempf, Mojtaba Akhavan-Tafti, Tomas Karlsson, Savvas Raptis, Maxime Dubart, Maxime Grandin, Jonas Suni, and Minna Palmroth
Ann. Geophys., 38, 1081–1099, https://doi.org/10.5194/angeo-38-1081-2020, https://doi.org/10.5194/angeo-38-1081-2020, 2020
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We investigate the dynamics of helium in the foreshock, a part of near-Earth space found upstream of the Earth's bow shock. We show how the second most common ion in interplanetary space reacts strongly to plasma waves found in the foreshock. Spacecraft observations and supercomputer simulations both give us a new understanding of the foreshock edge and how to interpret future observations.
Lucile Turc, Vertti Tarvus, Andrew P. Dimmock, Markus Battarbee, Urs Ganse, Andreas Johlander, Maxime Grandin, Yann Pfau-Kempf, Maxime Dubart, and Minna Palmroth
Ann. Geophys., 38, 1045–1062, https://doi.org/10.5194/angeo-38-1045-2020, https://doi.org/10.5194/angeo-38-1045-2020, 2020
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Using global computer simulations, we study properties of the magnetosheath, the region of near-Earth space where the stream of particles originating from the Sun, the solar wind, is slowed down and deflected around the Earth's magnetic field. One of our main findings is that even for idealised solar wind conditions as used in our model, the magnetosheath density shows large-scale spatial and temporal variation in the so-called quasi-parallel magnetosheath, causing varying levels of asymmetry.
Harriet George, Emilia Kilpua, Adnane Osmane, Timo Asikainen, Milla M. H. Kalliokoski, Craig J. Rodger, Stepan Dubyagin, and Minna Palmroth
Ann. Geophys., 38, 931–951, https://doi.org/10.5194/angeo-38-931-2020, https://doi.org/10.5194/angeo-38-931-2020, 2020
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We compared trapped outer radiation belt electron fluxes to high-latitude precipitating electron fluxes during two interplanetary coronal mass ejections (ICMEs) with opposite magnetic cloud rotation. The electron response had many similarities and differences between the two events, indicating that different acceleration mechanisms acted. Van Allen Probe data were used for trapped electron flux measurements, and Polar Operational Environmental Satellites were used for precipitating flux data.
Milla M. H. Kalliokoski, Emilia K. J. Kilpua, Adnane Osmane, Drew L. Turner, Allison N. Jaynes, Lucile Turc, Harriet George, and Minna Palmroth
Ann. Geophys., 38, 683–701, https://doi.org/10.5194/angeo-38-683-2020, https://doi.org/10.5194/angeo-38-683-2020, 2020
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We present a comprehensive statistical study of the response of the Earth's space environment in sheath regions prior to interplanetary coronal mass ejections. The inner magnetospheric wave activity is enhanced in sheath regions, and the sheaths cause significant changes to the outer radiation belt electron fluxes over short timescales. We also show that non-geoeffective sheaths can result in a significant response.
Markus Battarbee, Urs Ganse, Yann Pfau-Kempf, Lucile Turc, Thiago Brito, Maxime Grandin, Tuomas Koskela, and Minna Palmroth
Ann. Geophys., 38, 625–643, https://doi.org/10.5194/angeo-38-625-2020, https://doi.org/10.5194/angeo-38-625-2020, 2020
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The structure and medium-scale dynamics of Earth's bow shock and how charged solar wind particles are reflected by it are studied in order to better understand space weather effects. We use advanced supercomputer simulations to model the shock and reflected ions. We find that the thickness of the shock depends on solar wind conditions but also has small-scale variations. Charged particle reflection is shown to be non-localized. Magnetic fields are important for ion reflection.
Theodoros E. Sarris, Elsayed R. Talaat, Minna Palmroth, Iannis Dandouras, Errico Armandillo, Guram Kervalishvili, Stephan Buchert, Stylianos Tourgaidis, David M. Malaspina, Allison N. Jaynes, Nikolaos Paschalidis, John Sample, Jasper Halekas, Eelco Doornbos, Vaios Lappas, Therese Moretto Jørgensen, Claudia Stolle, Mark Clilverd, Qian Wu, Ingmar Sandberg, Panagiotis Pirnaris, and Anita Aikio
Geosci. Instrum. Method. Data Syst., 9, 153–191, https://doi.org/10.5194/gi-9-153-2020, https://doi.org/10.5194/gi-9-153-2020, 2020
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Daedalus aims to measure the largely unexplored area between Eart's atmosphere and space, the Earth's
ignorosphere. Here, intriguing and complex processes govern the deposition and transport of energy. The aim is to quantify this energy by measuring effects caused by electrodynamic processes in this region. The concept is based on a mother satellite that carries a suite of instruments, along with smaller satellites carrying a subset of instruments that are released into the atmosphere.
Emilia Kilpua, Liisa Juusola, Maxime Grandin, Antti Kero, Stepan Dubyagin, Noora Partamies, Adnane Osmane, Harriet George, Milla Kalliokoski, Tero Raita, Timo Asikainen, and Minna Palmroth
Ann. Geophys., 38, 557–574, https://doi.org/10.5194/angeo-38-557-2020, https://doi.org/10.5194/angeo-38-557-2020, 2020
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Coronal mass ejection sheaths and ejecta are key drivers of significant space weather storms, and they cause dramatic changes in radiation belt electron fluxes. Differences in precipitation of high-energy electrons from the belts to the upper atmosphere are thus expected. We investigate here differences in sheath- and ejecta-induced precipitation using the Finnish riometer (relative ionospheric opacity meter) chain.
Maxime Grandin, Markus Battarbee, Adnane Osmane, Urs Ganse, Yann Pfau-Kempf, Lucile Turc, Thiago Brito, Tuomas Koskela, Maxime Dubart, and Minna Palmroth
Ann. Geophys., 37, 791–806, https://doi.org/10.5194/angeo-37-791-2019, https://doi.org/10.5194/angeo-37-791-2019, 2019
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When the terrestrial magnetic field is disturbed, particles from the near-Earth space can precipitate into the upper atmosphere. This work presents, for the first time, numerical simulations of proton precipitation in the energy range associated with the production of aurora (∼1–30 keV) using a global kinetic model of the near-Earth space: Vlasiator. We find that nightside proton precipitation can be regulated by the transition region between stretched and dipolar geomagnetic field lines.
Antti Lakka, Tuija I. Pulkkinen, Andrew P. Dimmock, Emilia Kilpua, Matti Ala-Lahti, Ilja Honkonen, Minna Palmroth, and Osku Raukunen
Ann. Geophys., 37, 561–579, https://doi.org/10.5194/angeo-37-561-2019, https://doi.org/10.5194/angeo-37-561-2019, 2019
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We study how the Earth's space environment responds to two different amplitude interplanetary coronal mass ejection (ICME) events that occurred in 2012 and 2014 by using the GUMICS-4 global MHD model. We examine local and large-scale dynamics of the Earth's space environment and compare simulation results to in situ data. It is shown that during moderate driving simulation agrees well with the measurements; however, GMHD results should be interpreted cautiously during strong driving.
Liisa Juusola, Sanni Hoilijoki, Yann Pfau-Kempf, Urs Ganse, Riku Jarvinen, Markus Battarbee, Emilia Kilpua, Lucile Turc, and Minna Palmroth
Ann. Geophys., 36, 1183–1199, https://doi.org/10.5194/angeo-36-1183-2018, https://doi.org/10.5194/angeo-36-1183-2018, 2018
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The solar wind interacts with the Earth’s magnetic field, forming a magnetosphere. On the night side solar wind stretches the magnetosphere into a long tail. A process called magnetic reconnection opens the magnetic field lines and reconnects them, accelerating particles to high energies. We study this in the magnetotail using a numerical simulation model of the Earth’s magnetosphere. We study the motion of the points where field lines reconnect and the fast flows driven by this process.
Minna Palmroth, Heli Hietala, Ferdinand Plaschke, Martin Archer, Tomas Karlsson, Xóchitl Blanco-Cano, David Sibeck, Primož Kajdič, Urs Ganse, Yann Pfau-Kempf, Markus Battarbee, and Lucile Turc
Ann. Geophys., 36, 1171–1182, https://doi.org/10.5194/angeo-36-1171-2018, https://doi.org/10.5194/angeo-36-1171-2018, 2018
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Magnetosheath jets are high-velocity plasma structures that are commonly observed within the Earth's magnetosheath. Previously, they have mainly been investigated with spacecraft observations, which do not allow us to infer their spatial sizes, temporal evolution, or origin. This paper shows for the first time their dimensions, evolution, and origins within a simulation whose dimensions are directly comparable to the Earth's magnetosphere. The results are compared to previous observations.
Xochitl Blanco-Cano, Markus Battarbee, Lucile Turc, Andrew P. Dimmock, Emilia K. J. Kilpua, Sanni Hoilijoki, Urs Ganse, David G. Sibeck, Paul A. Cassak, Robert C. Fear, Riku Jarvinen, Liisa Juusola, Yann Pfau-Kempf, Rami Vainio, and Minna Palmroth
Ann. Geophys., 36, 1081–1097, https://doi.org/10.5194/angeo-36-1081-2018, https://doi.org/10.5194/angeo-36-1081-2018, 2018
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We use the Vlasiator code to study the characteristics of transient structures that exist in the Earth's foreshock, i.e. upstream of the bow shock. The structures are cavitons and spontaneous hot flow anomalies (SHFAs). These transients can interact with the bow shock. We study the changes the shock suffers via this interaction. We also investigate ion distributions associated with the cavitons and SHFAs. A very important result is that the arrival of multiple SHFAs results in shock erosion.
Liisa Juusola, Yann Pfau-Kempf, Urs Ganse, Markus Battarbee, Thiago Brito, Maxime Grandin, Lucile Turc, and Minna Palmroth
Ann. Geophys., 36, 1027–1035, https://doi.org/10.5194/angeo-36-1027-2018, https://doi.org/10.5194/angeo-36-1027-2018, 2018
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The Earth's magnetic field is shaped by the solar wind. On the dayside the field is compressed and on the nightside it is stretched as a long tail. The tail has been observed to occasionally undergo flapping motions, but the origin of these motions is not understood. We study the flapping using a numerical simulation of the near-Earth space. We present a possible explanation for how the flapping could be initiated by a passing disturbance and then maintained as a standing wave.
Minna Palmroth, Sanni Hoilijoki, Liisa Juusola, Tuija I. Pulkkinen, Heli Hietala, Yann Pfau-Kempf, Urs Ganse, Sebastian von Alfthan, Rami Vainio, and Michael Hesse
Ann. Geophys., 35, 1269–1274, https://doi.org/10.5194/angeo-35-1269-2017, https://doi.org/10.5194/angeo-35-1269-2017, 2017
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Much like solar flares, substorms occurring within the Earth's magnetic domain are explosive events that cause vivid auroral displays. A decades-long debate exists to explain the substorm onset. We devise a simulation encompassing the entire near-Earth space and demonstrate that detailed modelling of magnetic reconnection explains the central substorm observations. Our results help to understand the unpredictable substorm process, which will significantly improve space weather forecasts.
Antti Lakka, Tuija I. Pulkkinen, Andrew P. Dimmock, Adnane Osmane, Ilja Honkonen, Minna Palmroth, and Pekka Janhunen
Ann. Geophys., 35, 907–922, https://doi.org/10.5194/angeo-35-907-2017, https://doi.org/10.5194/angeo-35-907-2017, 2017
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We studied the impact on global MHD simulations from different simulation initialisation methods. While the global MHD code used is GUMICS-4 we conclude that the results might be generalisable to other codes as well. It is found that different initialisation methods affect the dynamics of the Earth's space environment by creating differences in momentum transport several hours afterwards. These differences may even grow as a response to rapid solar wind condition changes.
Yann Pfau-Kempf, Heli Hietala, Steve E. Milan, Liisa Juusola, Sanni Hoilijoki, Urs Ganse, Sebastian von Alfthan, and Minna Palmroth
Ann. Geophys., 34, 943–959, https://doi.org/10.5194/angeo-34-943-2016, https://doi.org/10.5194/angeo-34-943-2016, 2016
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We have simulated the interaction of the solar wind – the charged particles and magnetic fields emitted by the Sun into space – with the magnetic field of the Earth. The solar wind flows supersonically and creates a shock when it encounters the obstacle formed by the geomagnetic field. We have identified a new chain of events which causes phenomena in the downstream region to eventually cause perturbations at the shock and even upstream. This is confirmed by ground and satellite observations.
P. T. Verronen, M. E. Andersson, A. Kero, C.-F. Enell, J. M. Wissing, E. R. Talaat, K. Kauristie, M. Palmroth, T. E. Sarris, and E. Armandillo
Ann. Geophys., 33, 381–394, https://doi.org/10.5194/angeo-33-381-2015, https://doi.org/10.5194/angeo-33-381-2015, 2015
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Electron concentrations observed by EISCAT radars can be reasonable well represented using AIMOS v1.2 satellite-data-based ionization model and SIC D-region ion chemistry model. SIC-EISCAT difference varies from event to event, probably because the statistical nature of AIMOS ionization is not capturing all the spatio-temporal fine structure of electron precipitation. Below 90km, AIMOS overestimates electron ionization because of proton contamination of the satellite electron detectors.
L. Turc, D. Fontaine, P. Savoini, and E. K. J. Kilpua
Ann. Geophys., 32, 1247–1261, https://doi.org/10.5194/angeo-32-1247-2014, https://doi.org/10.5194/angeo-32-1247-2014, 2014
L. Turc, D. Fontaine, P. Savoini, and E. K. J. Kilpua
Ann. Geophys., 32, 157–173, https://doi.org/10.5194/angeo-32-157-2014, https://doi.org/10.5194/angeo-32-157-2014, 2014
D. Pokhotelov, S. von Alfthan, Y. Kempf, R. Vainio, H. E. J. Koskinen, and M. Palmroth
Ann. Geophys., 31, 2207–2212, https://doi.org/10.5194/angeo-31-2207-2013, https://doi.org/10.5194/angeo-31-2207-2013, 2013
A. T. Aikio, T. Pitkänen, I. Honkonen, M. Palmroth, and O. Amm
Ann. Geophys., 31, 1021–1034, https://doi.org/10.5194/angeo-31-1021-2013, https://doi.org/10.5194/angeo-31-1021-2013, 2013
L. Turc, D. Fontaine, P. Savoini, H. Hietala, and E. K. J. Kilpua
Ann. Geophys., 31, 1011–1019, https://doi.org/10.5194/angeo-31-1011-2013, https://doi.org/10.5194/angeo-31-1011-2013, 2013
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Porosity and permeability prediction through forward stratigraphic simulations using GPM™ and Petrel™: application in shallow marine depositional settings
Effects of transient processes for thermal simulations of the Central European Basin
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.
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.
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681, https://doi.org/10.5194/gmd-15-7641-2022, https://doi.org/10.5194/gmd-15-7641-2022, 2022
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Iterative optimization techniques, the state of the art in data assimilation, have largely focused on extending forecast accuracy to moderate- to long-range forecast systems. However, current methodology may not be cost-effective in reducing forecast errors in online, short-range forecast systems. We propose a novel optimization of these techniques for online, short-range forecast cycles, simultaneously providing an improvement in forecast accuracy and a reduction in the computational cost.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Lixin Wu, Dexun Chen, Yang Gao, Zhiqiang Wei, Dongning Jia, and Xiaopei Lin
Geosci. Model Dev., 15, 6695–6708, https://doi.org/10.5194/gmd-15-6695-2022, https://doi.org/10.5194/gmd-15-6695-2022, 2022
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To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
Vijay S. Mahadevan, Jorge E. Guerra, Xiangmin Jiao, Paul Kuberry, Yipeng Li, Paul Ullrich, David Marsico, Robert Jacob, Pavel Bochev, and Philip Jones
Geosci. Model Dev., 15, 6601–6635, https://doi.org/10.5194/gmd-15-6601-2022, https://doi.org/10.5194/gmd-15-6601-2022, 2022
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Coupled Earth system models require transfer of field data between multiple components with varying spatial resolutions to determine the correct climate behavior. We present the Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol to evaluate the accuracy, conservation properties, monotonicity, and local feature preservation of four different remapper algorithms for various unstructured mesh problems of interest. Future extensions to more practical use cases are also discussed.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
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Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Andrew M. Bradley, Peter A. Bosler, and Oksana Guba
Geosci. Model Dev., 15, 6285–6310, https://doi.org/10.5194/gmd-15-6285-2022, https://doi.org/10.5194/gmd-15-6285-2022, 2022
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Tracer transport in atmosphere models can be computationally expensive. We describe a flexible and efficient interpolation semi-Lagrangian method, the Islet method. It permits using up to three grids that share an element grid: a dynamics grid for computing quantities such as the wind velocity; a physics parameterizations grid; and a tracer grid. The Islet method performs well on a number of verification problems and achieves high performance in the E3SM Atmosphere Model version 2.
John Mern and Jef Caers
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-166, https://doi.org/10.5194/gmd-2022-166, 2022
Revised manuscript accepted for GMD
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In this work, we formulate sequential geoscientific data acquisition problem as 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.
Léo Pujol, Pierre-André Garambois, and Jérôme Monnier
Geosci. Model Dev., 15, 6085–6113, https://doi.org/10.5194/gmd-15-6085-2022, https://doi.org/10.5194/gmd-15-6085-2022, 2022
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This contribution presents a new numerical model for representing hydraulic–hydrological quantities at the basin scale. It allows modeling large areas at a low computational cost, with fine zooms where needed. It allows the integration of local and satellite measurements, via data assimilation methods, to improve the model's match to observations. Using this capability, good matches to in situ observations are obtained on a model of the complex Adour river network with fine zooms on floodplains.
Ludovic Räss, Ivan Utkin, Thibault Duretz, Samuel Omlin, and Yuri Y. Podladchikov
Geosci. Model Dev., 15, 5757–5786, https://doi.org/10.5194/gmd-15-5757-2022, https://doi.org/10.5194/gmd-15-5757-2022, 2022
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Continuum mechanics-based modelling of physical processes at large scale requires huge computational resources provided by massively parallel hardware such as graphical processing units. We present a suite of numerical algorithms, implemented using the Julia language, that efficiently leverages the parallelism. We demonstrate that our implementation is efficient, scalable and robust and showcase applications to various geophysical problems.
Meriem Krouma, Pascal Yiou, Céline Déandreis, and Soulivanh Thao
Geosci. Model Dev., 15, 4941–4958, https://doi.org/10.5194/gmd-15-4941-2022, https://doi.org/10.5194/gmd-15-4941-2022, 2022
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We evaluated the skill of a stochastic weather generator (SWG) to forecast precipitation at different time scales and in different areas of western Europe from analogs of Z500 hPa. The SWG has the skill to simulate precipitation for 5 and 10 d. We found that forecast weaknesses can be associated with specific weather patterns. The comparison with ECMWF forecasts confirms the skill of our model. This work is important because it provides information about weather forecasts over specific areas.
Piotr Dziekan and Piotr Zmijewski
Geosci. Model Dev., 15, 4489–4501, https://doi.org/10.5194/gmd-15-4489-2022, https://doi.org/10.5194/gmd-15-4489-2022, 2022
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Detailed computer simulations of clouds are important for understanding Earth's atmosphere and climate. The paper describes how the UWLCM has been adapted to work on supercomputers. A distinctive feature of UWLCM is that air flow is calculated by processors at the same time as cloud droplets are modeled by graphics cards. Thanks to this, use of computing resources is maximized and the time to complete simulations of large domains is not affected by communications between supercomputer nodes.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 15, 4147–4161, https://doi.org/10.5194/gmd-15-4147-2022, https://doi.org/10.5194/gmd-15-4147-2022, 2022
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A scale-dependent error growth described by a power law or by a quadratic hypothesis is studied in Lorenz’s system with three spatiotemporal levels. The validity of power law is extended by including a saturation effect. The quadratic hypothesis can only serve as a first guess. In addition, we study the initial error growth for the ECMWF forecast system. Fitting the parameters, we conclude that there is an intrinsic limit of predictability after 22 days.
Michael A. Olesik, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, Simon Unterstrasser, and Sylwester Arabas
Geosci. Model Dev., 15, 3879–3899, https://doi.org/10.5194/gmd-15-3879-2022, https://doi.org/10.5194/gmd-15-3879-2022, 2022
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In systems such as atmospheric clouds, droplets undergo growth through condensation of vapor. The broadness of the resultant size spectrum of droplets influences precipitation likelihood and the radiative properties of clouds. One of the inherent limitations of simulations of the problem is the so-called numerical diffusion causing overestimation of the spectrum width, hence the term numerical broadening. In the paper, we take a closer look at one of the algorithms used in this context: MPDATA.
Navjot Kukreja, Jan Hückelheim, Mathias Louboutin, John Washbourne, Paul H. J. Kelly, and Gerard J. Gorman
Geosci. Model Dev., 15, 3815–3829, https://doi.org/10.5194/gmd-15-3815-2022, https://doi.org/10.5194/gmd-15-3815-2022, 2022
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Full waveform inversion (FWI) is a partial-differential equation (PDE)-constrained optimization problem that is notorious for its high computational load and memory footprint. In this paper we present a method that combines recomputation with lossy compression to accelerate the computation with minimal loss of precision in the results. We show this using experiments running FWI with a variety of compression settings on a popular academic dataset.
Richard Scalzo, Mark Lindsay, Mark Jessell, Guillaume Pirot, Jeremie Giraud, Edward Cripps, and Sally Cripps
Geosci. Model Dev., 15, 3641–3662, https://doi.org/10.5194/gmd-15-3641-2022, https://doi.org/10.5194/gmd-15-3641-2022, 2022
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This paper addresses numerical challenges in reasoning about geological models constrained by sensor data, especially models that describe the history of an area in terms of a sequence of events. Our method ensures that small changes in simulated geological features, such as the position of a boundary between two rock layers, do not result in unrealistically large changes to resulting sensor measurements, as occur presently using several popular modeling packages.
Romit Maulik, Vishwas Rao, Jiali Wang, Gianmarco Mengaldo, Emil Constantinescu, Bethany Lusch, Prasanna Balaprakash, Ian Foster, and Rao Kotamarthi
Geosci. Model Dev., 15, 3433–3445, https://doi.org/10.5194/gmd-15-3433-2022, https://doi.org/10.5194/gmd-15-3433-2022, 2022
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In numerical weather prediction, data assimilation is frequently utilized to enhance the accuracy of forecasts from equation-based models. In this work we use a machine learning framework that approximates a complex dynamical system given by the geopotential height. Instead of using an equation-based model, we utilize this machine-learned alternative to dramatically accelerate both the forecast and the assimilation of data, thereby reducing need for large computational resources.
Hiromasa Yoshimura
Geosci. Model Dev., 15, 2561–2597, https://doi.org/10.5194/gmd-15-2561-2022, https://doi.org/10.5194/gmd-15-2561-2022, 2022
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This paper proposes a new double Fourier series (DFS) method on a sphere that improves the numerical stability of a model compared with conventional DFS methods. The shallow-water model and the advection model using the new DFS method give stable results without the appearance of high-wavenumber noise near the poles. The model using the new DFS method is faster than the model using spherical harmonics (especially at high resolutions) and gives almost the same results.
Mirko Mälicke
Geosci. Model Dev., 15, 2505–2532, https://doi.org/10.5194/gmd-15-2505-2022, https://doi.org/10.5194/gmd-15-2505-2022, 2022
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I preset SciKit-GStat, a well-documented and tested Python package for variogram estimation. The variogram is the core means of geostatistics, which almost all other methods rely on. Geostatistical interpolation and field generation are widely spread in geoscience, i.e., for data assimilation or modeling.
While SciKit-GStat focuses on effective and intuitive variogram estimation, it can interface with other prominent packages and make its variograms available for a multitude of methods.
Christopher J. L. D'Amboise, Michael Neuhauser, Michaela Teich, Andreas Huber, Andreas Kofler, Frank Perzl, Reinhard Fromm, Karl Kleemayr, and Jan-Thomas Fischer
Geosci. Model Dev., 15, 2423–2439, https://doi.org/10.5194/gmd-15-2423-2022, https://doi.org/10.5194/gmd-15-2423-2022, 2022
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The term gravitational mass flow (GMF) covers various natural hazard processes such as snow avalanches, rockfall, landslides, and debris flows. Here we present the open-source GMF simulation tool Flow-Py. The model equations are based on simple geometrical relations in three-dimensional terrain. We show that Flow-Py is an educational, innovative GMF simulation tool with three computational experiments: 1. validation of implementation, 2. performance, and 3. expandability.
Evan Baker, Anna B. Harper, Daniel Williamson, and Peter Challenor
Geosci. Model Dev., 15, 1913–1929, https://doi.org/10.5194/gmd-15-1913-2022, https://doi.org/10.5194/gmd-15-1913-2022, 2022
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We have adapted machine learning techniques to build a model of the land surface in Great Britain. The model was trained using data from a very complex land surface model called JULES. Our model is faster at producing simulations and predictions and can investigate many different scenarios, which can be used to improve our understanding of the climate and could also be used to help make local decisions.
Daichun Wang, Wei You, Zengliang Zang, Xiaobin Pan, Yiwen Hu, and Yanfei Liang
Geosci. Model Dev., 15, 1821–1840, https://doi.org/10.5194/gmd-15-1821-2022, https://doi.org/10.5194/gmd-15-1821-2022, 2022
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This paper presents a 3D variational data assimilation system for aerosol optical properties, including aerosol optical thickness (AOT) retrievals and lidar-based aerosol profiles, which was developed for a size-resolved sectional model in WRF-Chem. To directly assimilate aerosol optical properties, an observation operator based on the Mie scattering theory was designed. The results show that Himawari-8 AOT assimilation can significantly improve model aerosol analyses and forecasts.
Kevin Bulthuis and Eric Larour
Geosci. Model Dev., 15, 1195–1217, https://doi.org/10.5194/gmd-15-1195-2022, https://doi.org/10.5194/gmd-15-1195-2022, 2022
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We present and implement a stochastic solver to sample spatially and temporal varying uncertain input parameters in the Ice-sheet and Sea-level System Model, such as ice thickness or surface mass balance. We represent these sources of uncertainty using Gaussian random fields with Matérn covariance function. We generate random samples of this random field using an efficient computational approach based on solving a stochastic partial differential equation.
Urmas Raudsepp and Ilja Maljutenko
Geosci. Model Dev., 15, 535–551, https://doi.org/10.5194/gmd-15-535-2022, https://doi.org/10.5194/gmd-15-535-2022, 2022
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A model's ability to reproduce the state of a simulated object is always a subject of discussion. A new method for the multivariate assessment of numerical model skills uses the K-means algorithm for clustering model errors. All available data that fall into the model domain and simulation period are incorporated into the skill assessment. The clustered errors are used for spatial and temporal analysis of the model accuracy. The method can be applied to different types of geoscientific models.
Emmanuel Wyser, Yury Alkhimenkov, Michel Jaboyedoff, and Yury Y. Podladchikov
Geosci. Model Dev., 14, 7749–7774, https://doi.org/10.5194/gmd-14-7749-2021, https://doi.org/10.5194/gmd-14-7749-2021, 2021
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We propose an implementation of the material point method using graphical processing units (GPUs) to solve elastoplastic problems in three-dimensional configurations, such as the granular collapse or the slumping mechanics, i.e., landslide. The computational power of GPUs promotes fast code executions, compared to a traditional implementation using central processing units (CPUs). This allows us to study complex three-dimensional problems tackling high spatial resolution.
Rafael Lago, Thomas Gastine, Tilman Dannert, Markus Rampp, and Johannes Wicht
Geosci. Model Dev., 14, 7477–7495, https://doi.org/10.5194/gmd-14-7477-2021, https://doi.org/10.5194/gmd-14-7477-2021, 2021
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In this work we discuss a two-dimensional distributed parallelization of MagIC, an open-source code for the numerical solution of the magnetohydrodynamics equations. Such a parallelization involves several challenges concerning the distribution of work and data. We detail our algorithm and compare it with the established, optimized, one-dimensional distribution in the context of the dynamo benchmark and discuss the merits of both implementations.
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev., 14, 7411–7424, https://doi.org/10.5194/gmd-14-7411-2021, https://doi.org/10.5194/gmd-14-7411-2021, 2021
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This study aims to replicate computationally expensive high-resolution large-eddy simulations (LESs) with regression models to simulate urban air quality and pollutant dispersion. The model development, including feature selection, model training and cross-validation, and detection of concept drift, has been described in detail. Of the models applied, log-linear regression shows the best performance. A regression model can replace LES unless high accuracy is needed.
Hynek Bednář, Aleš Raidl, and Jiří Mikšovský
Geosci. Model Dev., 14, 7377–7389, https://doi.org/10.5194/gmd-14-7377-2021, https://doi.org/10.5194/gmd-14-7377-2021, 2021
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Forecast errors in numerical weather prediction systems grow in time. To quantify the impacts of this growth, parametric error growth models may be employed. This study recalculates and newly defines parameters for several statistic models approximating error growth in the ECMWF forecasting system. Accurate values of parameters are important because they are used to evaluate improvements of the forecasting systems or to estimate predictability.
Denise Degen, Cameron Spooner, Magdalena Scheck-Wenderoth, and Mauro Cacace
Geosci. Model Dev., 14, 7133–7153, https://doi.org/10.5194/gmd-14-7133-2021, https://doi.org/10.5194/gmd-14-7133-2021, 2021
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In times of worldwide energy transitions, an understanding of the subsurface is increasingly important to provide renewable energy sources such as geothermal energy. To validate our understanding of the subsurface we require data. However, the data are usually not distributed equally and introduce a potential misinterpretation of the subsurface. Therefore, in this study we investigate the influence of measurements on temperature distribution in the European Alps.
Geoffroy Kirstetter, Olivier Delestre, Pierre-Yves Lagrée, Stéphane Popinet, and Christophe Josserand
Geosci. Model Dev., 14, 7117–7132, https://doi.org/10.5194/gmd-14-7117-2021, https://doi.org/10.5194/gmd-14-7117-2021, 2021
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The development of forecasting tools may help to limit the impacts of flash floods. Our purpose here is to demonstrate the possibility of using b-flood, which is a 2D tool based on shallow-water equations and adaptive mesh refinement.
Sojung Park and Seon K. Park
Geosci. Model Dev., 14, 6241–6255, https://doi.org/10.5194/gmd-14-6241-2021, https://doi.org/10.5194/gmd-14-6241-2021, 2021
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One of the biggest uncertainties in numerical weather predictions (NWPs) comes from treating subgrid-scale physical processes. Physical processes, such as cumulus, microphysics, and planetary boundary layer processes, are parameterized in NWP models by empirical and theoretical backgrounds. We developed an interface between a micro-genetic algorithm and the WRF model for a combinatorial optimization of physics for heavy rainfall events in Korea. The system improved precipitation forecasts.
Olivier Pannekoucke and Philippe Arbogast
Geosci. Model Dev., 14, 5957–5976, https://doi.org/10.5194/gmd-14-5957-2021, https://doi.org/10.5194/gmd-14-5957-2021, 2021
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This contributes to research on uncertainty prediction, which is important either for determining the weather today or estimating the risk in prediction. The problem is that uncertainty prediction is numerically very expensive. An alternative has been proposed wherein uncertainty is presented in a simplified form with only the dynamics of certain parameters required. This tool allows for the determination of the symbolic equations of these parameter dynamics and their numerical computation.
Annika Günther, Johannes Gütschow, and Mairi Louise Jeffery
Geosci. Model Dev., 14, 5695–5730, https://doi.org/10.5194/gmd-14-5695-2021, https://doi.org/10.5194/gmd-14-5695-2021, 2021
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The mitigation components of the nationally determined contributions (NDCs) under the Paris Agreement are essential in our fight against climate change. Regular updates with increased ambition are requested to limit global warming to 1.5–2 °C. The new and easy-to-update open-source tool NDCmitiQ can be used to quantify the NDCs' mitigation targets and construct resulting emissions pathways. In use cases, we show target uncertainties from missing clarity, data, and methodological challenges.
Futo Tomizawa and Yohei Sawada
Geosci. Model Dev., 14, 5623–5635, https://doi.org/10.5194/gmd-14-5623-2021, https://doi.org/10.5194/gmd-14-5623-2021, 2021
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A new method to predict chaotic systems from observation and process-based models is proposed by combining machine learning with data assimilation. Our method is robust to the sparsity of observation networks and can predict more accurately than a process-based model when it is biased. Our method effectively works when both observations and models are imperfect, which is often the case in geoscience. Therefore, our method is useful to solve a wide variety of prediction problems in this field.
Chloe Leach, Tom Coulthard, Andrew Barkwith, Daniel R. Parsons, and Susan Manson
Geosci. Model Dev., 14, 5507–5523, https://doi.org/10.5194/gmd-14-5507-2021, https://doi.org/10.5194/gmd-14-5507-2021, 2021
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Numerical models can be used to understand how coastal systems evolve over time, including likely responses to climate change. However, many existing models are aimed at simulating 10- to 100-year time periods do not represent a vertical dimension and are thus unable to include the effect of sea-level rise. The Coastline Evolution Model 2D (CEM2D) presented in this paper is an advance in this field, with the inclusion of the vertical coastal profile against which the water level can be altered.
Steven J. Phipps, Jason L. Roberts, and Matt A. King
Geosci. Model Dev., 14, 5107–5124, https://doi.org/10.5194/gmd-14-5107-2021, https://doi.org/10.5194/gmd-14-5107-2021, 2021
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Simplified schemes, known as parameterisations, are sometimes used to describe physical processes within numerical models. However, the values of the parameters are uncertain. This introduces uncertainty into the model outputs. We develop a simple approach to identify plausible ranges for model parameters. Using a model of the Antarctic Ice Sheet, we find that the value of one parameter can depend on the values of others. We conclude that a single optimal set of parameter values does not exist.
Axel Peytavin, Bruno Sainte-Rose, Gael Forget, and Jean-Michel Campin
Geosci. Model Dev., 14, 4769–4780, https://doi.org/10.5194/gmd-14-4769-2021, https://doi.org/10.5194/gmd-14-4769-2021, 2021
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We present a new algorithm developed at The Ocean Cleanup to update ocean plastic models based on measurements from the field to improve future cleaning operations. Prepared in collaboration with MIT researchers, this initial study presents its use in several analytical and real test cases in which two observers in a flow field record regular observations to update a plastic forecast. We demonstrate this improves the prediction, even with inaccurate knowledge of the water flows driving plastic.
Kang Pan, Mei Qi Lim, Markus Kraft, and Epaminondas Mastorakos
Geosci. Model Dev., 14, 4509–4534, https://doi.org/10.5194/gmd-14-4509-2021, https://doi.org/10.5194/gmd-14-4509-2021, 2021
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A new moving point source (MPS) model was developed to simulate the dispersion of emissions generated by the moving ships. Compared to the commonly used line source (LS) or fixed point source (FPS) model, the MPS model provides more emission distribution details generated by the moving ships and matches reasonably with the measurements. Therefore, the MPS model should be a valuable alternative for the environmental society to evaluate the pollutant dispersion contributed from the moving ships.
Sebastian Springer, Heikki Haario, Jouni Susiluoto, Aleksandr Bibov, Andrew Davis, and Youssef Marzouk
Geosci. Model Dev., 14, 4319–4333, https://doi.org/10.5194/gmd-14-4319-2021, https://doi.org/10.5194/gmd-14-4319-2021, 2021
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Model predictions always contain uncertainty. But in some cases, such as weather forecasting or climate modeling, chaotic unpredictability increases the difficulty to say exactly how much uncertainty there is. We combine two recently proposed mathematical methods to show how the uncertainty can be analyzed in models that are simplifications of true weather models. The results can be extended in the future to show how forecasts from large-scale models can be improved.
Alexander Schaaf, Miguel de la Varga, Florian Wellmann, and Clare E. Bond
Geosci. Model Dev., 14, 3899–3913, https://doi.org/10.5194/gmd-14-3899-2021, https://doi.org/10.5194/gmd-14-3899-2021, 2021
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Uncertainty is an inherent property of any model of the subsurface. We show how geological topology information – how different regions of rocks in the subsurface are connected – can be used to train uncertain geological models to reduce uncertainty. More widely, the method demonstrates the use of probabilistic machine learning (Bayesian inference) to train structural geological models on auxiliary geological knowledge that can be encoded in graph structures.
Matthew Ozon, Aku Seppänen, Jari P. Kaipio, and Kari E. J. Lehtinen
Geosci. Model Dev., 14, 3715–3739, https://doi.org/10.5194/gmd-14-3715-2021, https://doi.org/10.5194/gmd-14-3715-2021, 2021
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Experimental research has provided large amounts of high-quality data on aerosol over the last 2 decades. However, inference of the process rates (e.g., the rates at which particles are generated) is still typically done by simple curve-fitting methods and does not assess the credibility of the estimation. The devised method takes advantage of the Bayesian framework to not only retrieve the state of the observed aerosol system but also to estimate the process rates (e.g., growth rate).
Colton J. Conroy and Einat Lev
Geosci. Model Dev., 14, 3553–3575, https://doi.org/10.5194/gmd-14-3553-2021, https://doi.org/10.5194/gmd-14-3553-2021, 2021
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Lava flows present a natural hazard to communities around volcanoes and are usually slow-moving (< 1-5 cm/s). Lava flows during the 2018 eruption of Kilauea volcano, Hawai’i, however, reached speeds as high as 11 m/s. To investigate these dynamics we develop a new lava flow computer model that incorporates a nonlinear expression for the fluid viscosity. Model results indicate that the lava flows at Site 8 of the eruption displayed shear thickening behavior due to the flow's high bubble content.
Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch
Geosci. Model Dev., 14, 3185–3214, https://doi.org/10.5194/gmd-14-3185-2021, https://doi.org/10.5194/gmd-14-3185-2021, 2021
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Large-eddy simulation (LES) of the urban atmospheric boundary layer involves a large separation of turbulent scales, leading to prohibitive computational costs. An online LES–LES nesting scheme is implemented into the PALM model system 6.0 to overcome this problem. Test results show that the accuracy within the high-resolution nest domains approach the non-nested high-resolution reference results. The nesting can reduce the CPU by time up to 80 % compared to the fine-resolution reference runs.
Yumeng Chen, Konrad Simon, and Jörn Behrens
Geosci. Model Dev., 14, 2289–2316, https://doi.org/10.5194/gmd-14-2289-2021, https://doi.org/10.5194/gmd-14-2289-2021, 2021
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Mesh adaptivity can reduce overall model error by only refining meshes in specific areas where it us necessary in the runtime. Here we suggest a way to integrate mesh adaptivity into an existing Earth system model, ECHAM6, without having to redesign the implementation from scratch. We show that while the additional computational effort is manageable, the error can be reduced compared to a low-resolution standard model using an idealized test and relatively realistic dust transport tests.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Mathieu Lachâtre
Geosci. Model Dev., 14, 2221–2233, https://doi.org/10.5194/gmd-14-2221-2021, https://doi.org/10.5194/gmd-14-2221-2021, 2021
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Representing the advection of thin polluted plumes in numerical models is a challenging task since these models usually tend to excessively diffuse these plumes in the vertical direction. This numerical diffusion process is the cause of major difficulties in representing such dense and thin polluted plumes in numerical models. We propose here, and test in an academic framework, a novel method to solve this problem through the use of an antidiffusive advection scheme in the vertical direction.
Daniel Otoo and David Hodgetts
Geosci. Model Dev., 14, 2075–2095, https://doi.org/10.5194/gmd-14-2075-2021, https://doi.org/10.5194/gmd-14-2075-2021, 2021
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The forward stratigraphic simulation method is used to predict lithofacies, porosity, and permeability in a reservoir model. The objective of using this approach is to enhance subsurface property modelling through geologic realistic 3-D stratigraphic patterns.
Results show realistic stratigraphic sequences. Given this, we can derive spatial and geometric data as secondary data to constrain property simulation in a reservoir model. The approach can reduce the uncertainty of property modelling.
Denise Degen and Mauro Cacace
Geosci. Model Dev., 14, 1699–1719, https://doi.org/10.5194/gmd-14-1699-2021, https://doi.org/10.5194/gmd-14-1699-2021, 2021
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In this work, we focus on improving the understanding of subsurface processes with respect to interactions with climate dynamics. We present advanced, open-source mathematical methods that enable us to investigate the influence of various model properties on the final outcomes. By relying on our approach, we have been able to showcase their importance in improving our understanding of the subsurface and highlighting the current shortcomings of currently adopted models.
Cited articles
Battarbee, M., Hannuksela, O. A., Pfau-Kempf, Y., von Alfthan, S., Ganse, U., Jarvinen, R., Suni, L. J., Alho, M., Turc, L., Honkonen, I., Brito, T., and Grandin, M.: fmihpc/analysator: v0.9 (v0.9), Zenodo [code], https://doi.org/10.5281/zenodo.4462515, 2021. a
Birchfield, S.: Image processing and analysis, Cengage Learning,
https://www.vlebooks.com/vleweb/product/openreader?id=none&isbn=9781337515627 (last access: March 2022),
oCLC: 1256700118, 2017. a
Cook, R. L.: Stochastic sampling in computer graphics, ACM Transactions on
Graphics, 5, 51–72, https://doi.org/10.1145/7529.8927, 1986. a
Grandin, M., Battarbee, M., Osmane, A., Ganse, U., Pfau-Kempf, Y., Turc, L., Brito, T., Koskela, T., Dubart, M., and Palmroth, M.: Hybrid-Vlasov modelling of nightside auroral proton precipitation during southward interplanetary magnetic field conditions, Ann. Geophys., 37, 791–806, https://doi.org/10.5194/angeo-37-791-2019, 2019. a
Hesse, M., Aunai, N., Birn, J., Cassak, P., Denton, R. E., Drake, J. F.,
Gombosi, T., Hoshino, M., Matthaeus, W., Sibeck, D., and Zenitani, S.: Theory
and Modeling for the Magnetospheric Multiscale Mission, Space Sci.
Rev., 199, 577–630, https://doi.org/10.1007/s11214-014-0078-y, 2014. a
Honkonen, I.: DCCRG: Distributed cartesian cell-refinable grid, GitHub,
https://github.com/fmihpc/dccrg/ (last access: June 2022), 2022. a
Honkonen, I., von Alfthan, S., Sandroos, A., Janhunen, P., and Palmroth, M.:
Parallel grid library for rapid and flexible simulation development, Comput.
Phys. Commun., 184, 1297–1309, https://doi.org/10.1016/j.cpc.2012.12.017,
2013. a
Kempf, Y., Pokhotelov, D., Gutynska, O., III, L. B. W., Walsh, B. M., von
Alfthan, S., Hannuksela, O., Sibeck, D. G., and Palmroth, M.: Ion
distributions in the Earth′s foreshock: Hybrid-Vlasov
simulation and THEMIS observations, J. Geophys. Res.-Space
Physics, 120, 3684–3701, https://doi.org/10.1002/2014ja020519, 2015. a
Londrillo, P. and del Zanna, L.: On the divergence-free condition in
Godunov-type schemes for ideal magnetohydrodynamics: the upwind constrained
transport method, J. Comput. Phys., 195, 17–48,
https://doi.org/10.1016/j.jcp.2003.09.016, 2004. a
Nishikawa, K., Duţan, I., Köhn, C., and Mizuno, Y.: PIC methods in
astrophysics: simulations of relativistic jets and kinetic physics in
astrophysical systems, Living Rev. Comput. Astrophys, 7, 1,
https://doi.org/10.1007/s41115-021-00012-0, 2021. a
Palmroth, M. and the Vlasiator team: FsGrid – a lightweight, static, cartesian
grid for field solvers, GitHub [code], https://github.com/fmihpc/fsgrid/ (last access: June 2022), 2020. a
Palmroth, M. and the Vlasiator team: Vlasiator: Hybrid-Vlasov Simulation Code, GitHub [code],
https://github.com/fmihpc/vlasiator/ (last access: June 2022), 2022. a
Palmroth, M., Hoilijoki, S., Juusola, L., Pulkkinen, T. I., Hietala, H., Pfau-Kempf, Y., Ganse, U., von Alfthan, S., Vainio, R., and Hesse, M.: Tail reconnection in the global magnetospheric context: Vlasiator first results, Ann. Geophys., 35, 1269–1274, https://doi.org/10.5194/angeo-35-1269-2017, 2017.
a
Palmroth, M., Ganse, U., Pfau-Kempf, Y., Battarbee, M., Turc, L., Brito, T.,
Grandin, M., Hoilijoki, S., Sandroos, A., and von Alfthan, S.: Vlasov methods
in space physics and astrophysics, Living Reviews in Computational
Astrophysics, 4, 1 https://doi.org/10.1007/s41115-018-0003-2, 2018. a, b
Pfau-Kempf, Y., Von Alfthan, S., Sandroos, A., Ganse, U., Koskela, T.,
Battarbee, M., Hannuksela, O. A., Honkonen, I., Papadakis, K., Grandin, M.,
Pokhotelov, D., Zhou, H., Kotipalo, L., and Alho, M.: fmihpc/vlasiator:
Vlasiator 5.1, Zenodo [code], https://doi.org/10.5281/ZENODO.4719554, 2021. a
Pfau-Kempf, Y., Von Alfthan, S., Ganse, U., Sandroos, A., Battarbee, M.,
Koskela, T., Hannuksela, O., Honkonen, I., Papadakis, K., Kotipalo, L., Zhou,
H., Grandin, M., Pokhotelov, D., and Alho, M.: fmihpc/vlasiator: Vlasiator
5.2.1, Zenodo [code], https://doi.org/10.5281/ZENODO.6782211, 2022. a
Roscoe, A. J. and Blair, S. M.: Choice and properties of adaptive and tunable
digital boxcar (moving average) filters for power systems and other signal
processing applications, in: 2016 IEEE International Workshop on Applied
Measurements for Power Systems (AMPS), IEEE,
https://doi.org/10.1109/amps.2016.7602853, 2016. a
Turc, L., Roberts, O. W., Archer, M. O., Palmroth, M., Battarbee, M., Brito,
T., Ganse, U., Grandin, M., Pfau-Kempf, Y., Escoubet, C. P., and Dandouras,
I.: First Observations of the Disruption of the Earth's
Foreshock Wave Field During Magnetic Clouds, Geophys. Res. Lett.,
46, 12644–12653, https://doi.org/10.1029/2019gl084437, 2019. a
Vay, J.-L. and Godfrey, B. B.: Modeling of relativistic plasmas with the
Particle-In-Cell method, Comptes Rendus Mécanique, 342, 610–618,
https://doi.org/10.1016/j.crme.2014.07.006, 2014. a
Vay, J.-L., Almgren, A., Bell, J., Ge, L., Grote, D., Hogan, M., Kononenko, O.,
Lehe, R., Myers, A., Ng, C., Park, J., Ryne, R., Shapoval, O.,
Thévenet, M., and Zhang, W.: Warp-X: A new exascale computing platform
for beam–plasma simulations, Nuclear Instruments and Methods in
Physics Research Section A: Accelerators, Spectrometers, Detectors and
Associated Equipment, 909, 476–479, https://doi.org/10.1016/j.nima.2018.01.035, 2018. a
von Alfthan, S., Pokhotelov, D., Kempf, Y., Hoilijoki, S., Honkonen, I.,
Sandroos, A., and Palmroth, M.: Vlasiator: First global hybrid-Vlasov
simulations of Earth's foreshock and magnetosheath, J. Atmos. Sol.-Terr. Phys., 120, 24–35,
https://doi.org/10.1016/j.jastp.2014.08.012, 2014. a
von Alfthan, S., Pfau-Kempf, Y., Sandroos, A., Ganse, U., Hannuksela, O.,
Honkonen, I., Battarbee, M., Koskela, T., and Pokhotelov, D.:
fmihpc/vlasiator: Vlasiator 5.0, Zenodo [code], https://doi.org/10.5281/ZENODO.3640594, 2020. a
Zerroukat, M. and Allen, T.: A three-dimensional monotone and conservative
semi-Lagrangian scheme (SLICE-3D) for transport problems, Q. J. Roy. Meteorol. Soc., 138, 1640–1651, https://doi.org/10.1002/qj.1902,
2012. a
Short summary
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.
Vlasiator is a plasma simulation code that simulates the entire near-Earth space at a global...
