Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-91-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-91-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
07 Jan 2021
Model description paper |
| 07 Jan 2021
| 07 Jan 2021
An N-dimensional Fortran interpolation programme (NterGeo.v2020a) for geophysics sciences – application to a back-trajectory programme (Backplumes.v2020r1) using CHIMERE or WRF outputs
Bertrand Bessagnet
CORRESPONDING AUTHOR
LMD/IPSL, École Polytechnique, Institut Polytechnique de Paris, ENS, PSL Université, Sorbonne Université, CNRS, 91128 Palaiseau, France
Citepa, Technical Reference Center for Air Pollution and Climate Change, 42, rue de Paradis 75010 Paris, France
Laurent Menut
LMD/IPSL, École Polytechnique, Institut Polytechnique de Paris, ENS, PSL Université, Sorbonne Université, CNRS, 91128 Palaiseau, France
Maxime Beauchamp
IMT Atlantique, Lab-STICC UMR CNRS, 655 Avenue du Technopôle, 29280 Plouzané, France
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Henda Guermazi, Pasquale Sellitto, Juan Cuesta, Maxim Eremenko, Mathieu Lachatre, Sylvain Mailler, Elisa Carboni, Giuseppe Salerno, Tommaso Caltabiano, Laurent Menut, Mohamed Moncef Serbaji, Farhat Rekhiss, and Bernard Legras
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Revised manuscript not accepted
Marwa Majdi, Solene Turquety, Karine Sartelet, Carole Legorgeu, Laurent Menut, and Youngseob Kim
Atmos. Chem. Phys., 19, 785–812, https://doi.org/10.5194/acp-19-785-2019, https://doi.org/10.5194/acp-19-785-2019, 2019
Adrien Deroubaix, Laurent Menut, Cyrille Flamant, Joel Brito, Cyrielle Denjean, Volker Dreiling, Andreas Fink, Corinne Jambert, Norbert Kalthoff, Peter Knippertz, Russ Ladkin, Sylvain Mailler, Marlon Maranan, Federica Pacifico, Bruno Piguet, Guillaume Siour, and Solène Turquety
Atmos. Chem. Phys., 19, 473–497, https://doi.org/10.5194/acp-19-473-2019, https://doi.org/10.5194/acp-19-473-2019, 2019
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This article presents a detailed analysis of anthropogenic and biomass burning pollutants over the Gulf of Guinea coastal region, using observations from the DACCIWA field campaign and modeling. The novelty is that we focus on how these two pollution sources are mixed and transported further inland. We show that during the day pollutants are accumulated along the coastline and transported northward as soon as the daytime convection in the atmospheric boundary layer ceases (16:00 UTC).
Cyrille Flamant, Adrien Deroubaix, Patrick Chazette, Joel Brito, Marco Gaetani, Peter Knippertz, Andreas H. Fink, Gaëlle de Coetlogon, Laurent Menut, Aurélie Colomb, Cyrielle Denjean, Rémi Meynadier, Philip Rosenberg, Regis Dupuy, Pamela Dominutti, Jonathan Duplissy, Thierry Bourrianne, Alfons Schwarzenboeck, Michel Ramonet, and Julien Totems
Atmos. Chem. Phys., 18, 12363–12389, https://doi.org/10.5194/acp-18-12363-2018, https://doi.org/10.5194/acp-18-12363-2018, 2018
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Angela Benedetti, Jeffrey S. Reid, Peter Knippertz, John H. Marsham, Francesca Di Giuseppe, Samuel Rémy, Sara Basart, Olivier Boucher, Ian M. Brooks, Laurent Menut, Lucia Mona, Paolo Laj, Gelsomina Pappalardo, Alfred Wiedensohler, Alexander Baklanov, Malcolm Brooks, Peter R. Colarco, Emilio Cuevas, Arlindo da Silva, Jeronimo Escribano, Johannes Flemming, Nicolas Huneeus, Oriol Jorba, Stelios Kazadzis, Stefan Kinne, Thomas Popp, Patricia K. Quinn, Thomas T. Sekiyama, Taichu Tanaka, and Enric Terradellas
Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, https://doi.org/10.5194/acp-18-10615-2018, 2018
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Alessandro Anav, Chiara Proietti, Laurent Menut, Stefano Carnicelli, Alessandra De Marco, and Elena Paoletti
Atmos. Chem. Phys., 18, 5747–5763, https://doi.org/10.5194/acp-18-5747-2018, https://doi.org/10.5194/acp-18-5747-2018, 2018
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Laurent Menut, Cyrille Flamant, Solène Turquety, Adrien Deroubaix, Patrick Chazette, and Rémi Meynadier
Atmos. Chem. Phys., 18, 2687–2707, https://doi.org/10.5194/acp-18-2687-2018, https://doi.org/10.5194/acp-18-2687-2018, 2018
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During the DACCIWA project, the tropospheric chemical composition in large cities along the Gulf of Guinea is modelled using WRF and CHIMERE, with and without biomass burning emissions. The difference shows the net impact of fires on air quality in Lagos and Abidjan.
Adrien Deroubaix, Cyrille Flamant, Laurent Menut, Guillaume Siour, Sylvain Mailler, Solène Turquety, Régis Briant, Dmitry Khvorostyanov, and Suzanne Crumeyrolle
Atmos. Chem. Phys., 18, 445–465, https://doi.org/10.5194/acp-18-445-2018, https://doi.org/10.5194/acp-18-445-2018, 2018
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CO and PM2.5 are analyzed over the Guinean Gulf coastal region during the beginning of the 2006 West African monsoon. A biomass burning plume from Central Africa is observed since June at the Guinean coast. In June, the modeled anthropogenic PM2.5 concentrations are higher than in May or July. An important part of the pollution emitted along the coastline is transported to the north at night within the surface layer and within the nocturnal low-level jet.
Florian Couvidat, Bertrand Bessagnet, Marta Garcia-Vivanco, Elsa Real, Laurent Menut, and Augustin Colette
Geosci. Model Dev., 11, 165–194, https://doi.org/10.5194/gmd-11-165-2018, https://doi.org/10.5194/gmd-11-165-2018, 2018
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Sylvain Mailler, Laurent Menut, Dmitry Khvorostyanov, Myrto Valari, Florian Couvidat, Guillaume Siour, Solène Turquety, Régis Briant, Paolo Tuccella, Bertrand Bessagnet, Augustin Colette, Laurent Létinois, Kostantinos Markakis, and Frédérik Meleux
Geosci. Model Dev., 10, 2397–2423, https://doi.org/10.5194/gmd-10-2397-2017, https://doi.org/10.5194/gmd-10-2397-2017, 2017
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Laurent Menut, Sylvain Mailler, Bertrand Bessagnet, Guillaume Siour, Augustin Colette, Florian Couvidat, and Frédérik Meleux
Geosci. Model Dev., 10, 1199–1208, https://doi.org/10.5194/gmd-10-1199-2017, https://doi.org/10.5194/gmd-10-1199-2017, 2017
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A simple and complementary model evaluation technique for regional chemistry transport is discussed. The methodology is based on the concept that we can learn about model performance by comparing the simulation results with observational data available for time periods other than the period originally targeted.
Régis Briant, Paolo Tuccella, Adrien Deroubaix, Dmitry Khvorostyanov, Laurent Menut, Sylvain Mailler, and Solène Turquety
Geosci. Model Dev., 10, 927–944, https://doi.org/10.5194/gmd-10-927-2017, https://doi.org/10.5194/gmd-10-927-2017, 2017
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This paper presents the coupling of the CHIMERE chemistry-transport model with the WRF meteorological model, using the OASIS3-MCT coupler. WRF meteorological fields along with CHIMERE aerosol optical properties are exchanged through the coupler at a high frequency in order to model the aerosol direct and semi-direct effects.
Laurent Menut, Guillaume Siour, Sylvain Mailler, Florian Couvidat, and Bertrand Bessagnet
Atmos. Chem. Phys., 16, 12961–12982, https://doi.org/10.5194/acp-16-12961-2016, https://doi.org/10.5194/acp-16-12961-2016, 2016
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The aerosol is modelled during the summer 2013 with the WRF and CHIMERE models and over a large area encompassing Africa, Mediterranean sea and west Europe. The modelled aerosol is compared to available measurements such as the AERONET and EMEP networks. The model ability to estimate the aerosol speciation and size distribution is quantified.
Bertrand Bessagnet, Guido Pirovano, Mihaela Mircea, Cornelius Cuvelier, Armin Aulinger, Giuseppe Calori, Giancarlo Ciarelli, Astrid Manders, Rainer Stern, Svetlana Tsyro, Marta García Vivanco, Philippe Thunis, Maria-Teresa Pay, Augustin Colette, Florian Couvidat, Frédérik Meleux, Laurence Rouïl, Anthony Ung, Sebnem Aksoyoglu, José María Baldasano, Johannes Bieser, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Sandro Finardi, Richard Kranenburg, Camillo Silibello, Claudio Carnevale, Wenche Aas, Jean-Charles Dupont, Hilde Fagerli, Lucia Gonzalez, Laurent Menut, André S. H. Prévôt, Pete Roberts, and Les White
Atmos. Chem. Phys., 16, 12667–12701, https://doi.org/10.5194/acp-16-12667-2016, https://doi.org/10.5194/acp-16-12667-2016, 2016
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The EURODELTA III exercise allows a very comprehensive intercomparison and evaluation of air quality models' performance. On average, the models provide a rather good picture of the particulate matter (PM) concentrations over Europe even if the highest concentrations are underestimated. The meteorology is responsible for model discrepancies, while the lack of emissions, particularly in winter, is mentioned as the main reason for the underestimations of PM.
Vincent E. P. Lemaire, Augustin Colette, and Laurent Menut
Atmos. Chem. Phys., 16, 2559–2574, https://doi.org/10.5194/acp-16-2559-2016, https://doi.org/10.5194/acp-16-2559-2016, 2016
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Because of its sensitivity to unfavorable weather patterns, air pollution is sensitive to climate change. Its impact is typically assessed using deterministic chemistry-transport models forced by an ensemble of climate projection. Because of the high computational cost of such initiative, elaborated techniques are required to optimize the exploration of ensemble of future projections. We develop such a technique, which also allows quantifying uncertainties in climate and air quality projections.
S. Mailler, L. Menut, A. G. di Sarra, S. Becagli, T. Di Iorio, B. Bessagnet, R. Briant, P. Formenti, J.-F. Doussin, J. L. Gómez-Amo, M. Mallet, G. Rea, G. Siour, D. M. Sferlazzo, R. Traversi, R. Udisti, and S. Turquety
Atmos. Chem. Phys., 16, 1219–1244, https://doi.org/10.5194/acp-16-1219-2016, https://doi.org/10.5194/acp-16-1219-2016, 2016
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We studied the impact of aerosols on tropospheric photolysis rates at Lampedusa during the CharMEx/ADRIMED campaign in June 2013. It is shown by using the CHIMERE chemistry-transport model (CTM) as well as in situ and remote-sensing measurements that taking into account the radiative effect of the tropospheric aerosols improves the ability of the model to reproduce the observed photolysis rates. It is hence important for CTMs to include the radiative effect of aerosols on photochemistry.
M. Mallet, F. Dulac, P. Formenti, P. Nabat, J. Sciare, G. Roberts, J. Pelon, G. Ancellet, D. Tanré, F. Parol, C. Denjean, G. Brogniez, A. di Sarra, L. Alados-Arboledas, J. Arndt, F. Auriol, L. Blarel, T. Bourrianne, P. Chazette, S. Chevaillier, M. Claeys, B. D'Anna, Y. Derimian, K. Desboeufs, T. Di Iorio, J.-F. Doussin, P. Durand, A. Féron, E. Freney, C. Gaimoz, P. Goloub, J. L. Gómez-Amo, M. J. Granados-Muñoz, N. Grand, E. Hamonou, I. Jankowiak, M. Jeannot, J.-F. Léon, M. Maillé, S. Mailler, D. Meloni, L. Menut, G. Momboisse, J. Nicolas, T. Podvin, V. Pont, G. Rea, J.-B. Renard, L. Roblou, K. Schepanski, A. Schwarzenboeck, K. Sellegri, M. Sicard, F. Solmon, S. Somot, B Torres, J. Totems, S. Triquet, N. Verdier, C. Verwaerde, F. Waquet, J. Wenger, and P. Zapf
Atmos. Chem. Phys., 16, 455–504, https://doi.org/10.5194/acp-16-455-2016, https://doi.org/10.5194/acp-16-455-2016, 2016
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The aim of this article is to present an experimental campaign over the Mediterranean focused on aerosol-radiation measurements and modeling. Results indicate an important atmospheric loading associated with a moderate absorbing ability of mineral dust. Observations suggest a complex vertical structure and size distributions characterized by large aerosols within dust plumes. The radiative effect is highly variable, with negative forcing over the Mediterranean and positive over northern Africa.
V. Marécal, V.-H. Peuch, C. Andersson, S. Andersson, J. Arteta, M. Beekmann, A. Benedictow, R. Bergström, B. Bessagnet, A. Cansado, F. Chéroux, A. Colette, A. Coman, R. L. Curier, H. A. C. Denier van der Gon, A. Drouin, H. Elbern, E. Emili, R. J. Engelen, H. J. Eskes, G. Foret, E. Friese, M. Gauss, C. Giannaros, J. Guth, M. Joly, E. Jaumouillé, B. Josse, N. Kadygrov, J. W. Kaiser, K. Krajsek, J. Kuenen, U. Kumar, N. Liora, E. Lopez, L. Malherbe, I. Martinez, D. Melas, F. Meleux, L. Menut, P. Moinat, T. Morales, J. Parmentier, A. Piacentini, M. Plu, A. Poupkou, S. Queguiner, L. Robertson, L. Rouïl, M. Schaap, A. Segers, M. Sofiev, L. Tarasson, M. Thomas, R. Timmermans, Á. Valdebenito, P. van Velthoven, R. van Versendaal, J. Vira, and A. Ung
Geosci. Model Dev., 8, 2777–2813, https://doi.org/10.5194/gmd-8-2777-2015, https://doi.org/10.5194/gmd-8-2777-2015, 2015
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This paper describes the air quality forecasting system over Europe put in place in the Monitoring Atmospheric Composition and Climate projects. It provides daily and 4-day forecasts and analyses for the previous day for major gas and particulate pollutants and their main precursors. These products are based on a multi-model approach using seven state-of-the-art models developed in Europe. An evaluation of the performance of the system is discussed in the paper.
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, https://doi.org/10.5194/acp-15-8115-2015, 2015
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The paper presents the first ensemble modelling experiment for forecasting the atmospheric dispersion of birch pollen in Europe. The study included 7 models of MACC-ENS tested over the season of 2010 and applied for 2013 in forecasting and reanalysis modes. The results were compared with observations in 11 countries, members of European Aeroallergen Network. The models successfully reproduced the timing of the unusually late season of 2013 but had more difficulties with absolute concentration.
G. Rea, S. Turquety, L. Menut, R. Briant, S. Mailler, and G. Siour
Atmos. Chem. Phys., 15, 8013–8036, https://doi.org/10.5194/acp-15-8013-2015, https://doi.org/10.5194/acp-15-8013-2015, 2015
L. Menut, G. Rea, S. Mailler, D. Khvorostyanov, and S. Turquety
Atmos. Chem. Phys., 15, 7897–7911, https://doi.org/10.5194/acp-15-7897-2015, https://doi.org/10.5194/acp-15-7897-2015, 2015
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The atmospheric composition was extensively studied in the European Mediterranean region and during summer 2013 within the framework of the ADRIMED project. During the campaign experiment, the WRF and CHIMERE models were used in forecast mode in order to help scientists to decide whether intensive observation periods should be triggered or not. This study quantifies the origin of the forecast error by comparing several forecast leads to the corresponding measurements.
F. Hourdin, M. Gueye, B. Diallo, J.-L. Dufresne, J. Escribano, L. Menut, B. Marticoréna, G. Siour, and F. Guichard
Atmos. Chem. Phys., 15, 6775–6788, https://doi.org/10.5194/acp-15-6775-2015, https://doi.org/10.5194/acp-15-6775-2015, 2015
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New parameterizations of the convective boundary layer are used to better represent the diurnal cycle of near-surface wind over Sahara and Sahel in a climate model and the associated emission of dust.
L. Menut, S. Mailler, G. Siour, B. Bessagnet, S. Turquety, G. Rea, R. Briant, M. Mallet, J. Sciare, P. Formenti, and F. Meleux
Atmos. Chem. Phys., 15, 6159–6182, https://doi.org/10.5194/acp-15-6159-2015, https://doi.org/10.5194/acp-15-6159-2015, 2015
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The ozone and aerosol concentration variability is studied over the Euro-Mediterranean area during the months of June and July 2013 and in the framework of the ADRIMED project. A first analysis is performed using meteorological variables, ozone and aerosol concentrations using routine network station, satellite and specific ADRIMED project airborne measurements. This analysis is complemented by modeling using the WRF and CHIMERE regional models.
K. Haustein, R. Washington, J. King, G. Wiggs, D. S. G. Thomas, F. D. Eckardt, R. G. Bryant, and L. Menut
Geosci. Model Dev., 8, 341–362, https://doi.org/10.5194/gmd-8-341-2015, https://doi.org/10.5194/gmd-8-341-2015, 2015
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In this paper, the performance of three commonly used dust emissions schemes is investigated using a box model environment and observational data obtained in Botswana (Sua Pan). The results suggest that all schemes fail to reproduce the observed horizontal dust flux properly. They overestimate its magnitude by several orders of magnitude. The key parameter for this mismatch is the surface crusting which limits the availability of erosive material, even at higher wind speeds.
E. Terrenoire, B. Bessagnet, L. Rouïl, F. Tognet, G. Pirovano, L. Létinois, M. Beauchamp, A. Colette, P. Thunis, M. Amann, and L. Menut
Geosci. Model Dev., 8, 21–42, https://doi.org/10.5194/gmd-8-21-2015, https://doi.org/10.5194/gmd-8-21-2015, 2015
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The model reproduces the temporal variability of NO2, O3, PM10, PM2.5 better at rural than urban background stations.
The fractional biases show that the model performs slightly better at RB sites than at UB sites for NO2, O3 and PM10.
At UB sites, CHIMERE reproduces PM2.5 better than PM10.
This is primarily the result of an underestimation of coarse particulate matter (PM) associated with uncertainties on SOA chemistry and their precursor emissions, dust and sea salt.
L. Menut, S. Mailler, G. Siour, B. Bessagnet, S. Turquety, G. Rea, R. Briant, M. Mallet, J. Sciare, and P. Formenti
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-23075-2014, https://doi.org/10.5194/acpd-14-23075-2014, 2014
Revised manuscript not accepted
R. Briant, L. Menut, G. Siour, and C. Prigent
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-3441-2014, https://doi.org/10.5194/gmdd-7-3441-2014, 2014
Revised manuscript not accepted
L. Menut, R. Vautard, A. Colette, D. Khvorostyanov, A. Potier, L. Hamaoui-Laguel, N. Viovy, and M. Thibaudon
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-10891-2014, https://doi.org/10.5194/acpd-14-10891-2014, 2014
Revised manuscript not accepted
P. Yiou, M. Boichu, R. Vautard, M. Vrac, S. Jourdain, E. Garnier, F. Fluteau, and L. Menut
Clim. Past, 10, 797–809, https://doi.org/10.5194/cp-10-797-2014, https://doi.org/10.5194/cp-10-797-2014, 2014
S. Turquety, L. Menut, B. Bessagnet, A. Anav, N. Viovy, F. Maignan, and M. Wooster
Geosci. Model Dev., 7, 587–612, https://doi.org/10.5194/gmd-7-587-2014, https://doi.org/10.5194/gmd-7-587-2014, 2014
J. C. Péré, B. Bessagnet, M. Mallet, F. Waquet, I. Chiapello, F. Minvielle, V. Pont, and L. Menut
Atmos. Chem. Phys., 14, 1999–2013, https://doi.org/10.5194/acp-14-1999-2014, https://doi.org/10.5194/acp-14-1999-2014, 2014
M. Boichu, L. Menut, D. Khvorostyanov, L. Clarisse, C. Clerbaux, S. Turquety, and P.-F. Coheur
Atmos. Chem. Phys., 13, 8569–8584, https://doi.org/10.5194/acp-13-8569-2013, https://doi.org/10.5194/acp-13-8569-2013, 2013
A. Colette, B. Bessagnet, R. Vautard, S. Szopa, S. Rao, S. Schucht, Z. Klimont, L. Menut, G. Clain, F. Meleux, G. Curci, and L. Rouïl
Atmos. Chem. Phys., 13, 7451–7471, https://doi.org/10.5194/acp-13-7451-2013, https://doi.org/10.5194/acp-13-7451-2013, 2013
L. Menut, B. Bessagnet, D. Khvorostyanov, M. Beekmann, N. Blond, A. Colette, I. Coll, G. Curci, G. Foret, A. Hodzic, S. Mailler, F. Meleux, J.-L. Monge, I. Pison, G. Siour, S. Turquety, M. Valari, R. Vautard, and M. G. Vivanco
Geosci. Model Dev., 6, 981–1028, https://doi.org/10.5194/gmd-6-981-2013, https://doi.org/10.5194/gmd-6-981-2013, 2013
S. Mailler, D. Khvorostyanov, and L. Menut
Atmos. Chem. Phys., 13, 5987–5998, https://doi.org/10.5194/acp-13-5987-2013, https://doi.org/10.5194/acp-13-5987-2013, 2013
S. Stromatas, S. Turquety, L. Menut, H. Chepfer, J. C. Péré, G. Cesana, and B. Bessagnet
Geosci. Model Dev., 5, 1543–1564, https://doi.org/10.5194/gmd-5-1543-2012, https://doi.org/10.5194/gmd-5-1543-2012, 2012
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Malena Sabaté Landman, Julianne Chung, Jiahua Jiang, Scot M. Miller, and Arvind K. Saibaba
Geosci. Model Dev., 17, 8853–8872, https://doi.org/10.5194/gmd-17-8853-2024, https://doi.org/10.5194/gmd-17-8853-2024, 2024
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Making an informed decision about what prior information to incorporate or discard in an inverse model is important yet very challenging, as it is often not straightforward to distinguish between informative and non-informative variables. In this study, we develop a new approach for incorporating prior information in an inverse model using predictor variables, while simultaneously selecting the relevant predictor variables for the estimation of the unknown quantity of interest.
Joonlee Lee, Myong-In Lee, Sunlae Tak, Eunkyo Seo, and Yong-Keun Lee
Geosci. Model Dev., 17, 8799–8816, https://doi.org/10.5194/gmd-17-8799-2024, https://doi.org/10.5194/gmd-17-8799-2024, 2024
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We developed an advanced snow water equivalent (SWE) data assimilation framework using satellite data based on a land surface model. The results of this study highlight the beneficial impact of data assimilation by effectively combining land surface model and satellite-derived data according to their relative uncertainty, thereby controlling not only transitional regions but also the regions with heavy snow accumulation that are difficult to detect by satellite.
Frédéric Parrenin, Marie Bouchet, Christo Buizert, Emilie Capron, Ellen Corrick, Russell Drysdale, Kenji Kawamura, Amaëlle Landais, Robert Mulvaney, Ikumi Oyabu, and Sune Olander Rasmussen
Geosci. Model Dev., 17, 8735–8750, https://doi.org/10.5194/gmd-17-8735-2024, https://doi.org/10.5194/gmd-17-8735-2024, 2024
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The Paleochrono-1.1 probabilistic dating model allows users to derive a common and optimized chronology for several paleoclimatic sites from various archives (ice cores, speleothems, marine cores, lake cores, etc.). It combines prior sedimentation scenarios with chronological information such as dated horizons, dated intervals, stratigraphic links and (for ice cores) Δdepth observations. Paleochrono-1.1 is available under an open-source license.
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 17, 8399–8420, https://doi.org/10.5194/gmd-17-8399-2024, https://doi.org/10.5194/gmd-17-8399-2024, 2024
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This paper introduces a numerical method for simulating particle-based aerosol transport in atmospheric models. We detail the various numerical properties of the advection order method and demonstrate its implementation in a 3D weather prediction model (WRF) for the first time. Particle-based techniques improve the accuracy of aerosol size and composition predictions, which are key for aerosol–cloud and aerosol–radiation interactions.
Matt J. Fischer
Geosci. Model Dev., 17, 6745–6760, https://doi.org/10.5194/gmd-17-6745-2024, https://doi.org/10.5194/gmd-17-6745-2024, 2024
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In paleoclimate research, proxy system models (PSMs) model chemical or biological systems which receive environmental input and output (e.g., geochemical signals). The environmental inputs are rarely noiseless, which causes problems when calibrating multi-input PSMs. Here a PSM is developed which includes generalized noise in both model inputs and outputs and prior information. A quasi-Bayesian method enhances the stability of the solution of the Measurement Error Proxy System Model.
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024, https://doi.org/10.5194/gmd-17-6227-2024, 2024
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We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Úa for solving level-set equations, specifically those related to the dynamic representation of moving ice fronts within numerical ice sheet models. Our results demonstrate that the streamline upwind Petrov–Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.
Hugo Dominguez, Nicolas Riel, and Pierre Lanari
Geosci. Model Dev., 17, 6105–6122, https://doi.org/10.5194/gmd-17-6105-2024, https://doi.org/10.5194/gmd-17-6105-2024, 2024
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Predicting the behaviour of magmatic systems is important for understanding Earth's matter and heat transport. Numerical modelling is a technique that can predict complex systems at different scales of space and time by solving equations using various techniques. This study tests four algorithms to find the best way to transport the melt composition. The "weighted essentially non-oscillatory" algorithm emerges as the best choice, minimising errors and preserving system mass well.
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Bödecker, Carsten F. Dormann, Florian Pappenberger, and Gianpaolo Balsamo
EGUsphere, https://doi.org/10.5194/egusphere-2024-2081, https://doi.org/10.5194/egusphere-2024-2081, 2024
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We compared spatio-temporal forecast performances of three popular machine learning approaches that learned processes of water and energy exchange on the earth surface from a large physical model. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the Globe. We found that all approaches deliver highly accurate predictions until long time horizons, implying their usefulness to advance land surface forecasting when data is available.
Maarten van Ormondt, Tim Leijnse, Roel de Goede, Kees Nederhoff, and Ap van Dongeren
EGUsphere, https://doi.org/10.5194/egusphere-2024-1839, https://doi.org/10.5194/egusphere-2024-1839, 2024
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Accurate flood risk assessments are crucial for storm protection. To achieve efficiency, computational costs must be minimized. This paper introduces a novel subgrid approach for Linear Inertial Equations (LIE) with bed level and friction variations, implemented in the SFINCS model. Pre-processed lookup tables enhance simulation precision with lower costs. Validations show significant accuracy improvement, even at coarser resolutions.
Reuben W. Nixon-Hill, Daniel Shapero, Colin J. Cotter, and David A. Ham
Geosci. Model Dev., 17, 5369–5386, https://doi.org/10.5194/gmd-17-5369-2024, https://doi.org/10.5194/gmd-17-5369-2024, 2024
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Scientists often use models to study complex processes, like the movement of ice sheets, and compare them to measurements for estimating quantities that are hard to measure. We highlight an approach that ensures accurate results from point data sources (e.g. height measurements) by evaluating the numerical solution at true point locations. This method improves accuracy, aids communication between scientists, and is well-suited for integration with specialised software that automates processes.
Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, and Johannes Flemming
Geosci. Model Dev., 17, 5009–5021, https://doi.org/10.5194/gmd-17-5009-2024, https://doi.org/10.5194/gmd-17-5009-2024, 2024
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EQSAM4Clim has recently been revised to provide an accurate and efficient method for calculating the acidity of atmospheric particles. It is based on an analytical concept that is sufficiently fast and free of numerical noise, which makes it attractive for air quality forecasting. Version 12 allows the calculation of aerosol composition based on the gas–liquid–solid and the reduced gas–liquid partitioning with the associated water uptake for both cases, including the acidity of the aerosols.
Niko Schmidt, Angelika Humbert, and Thomas Slawig
Geosci. Model Dev., 17, 4943–4959, https://doi.org/10.5194/gmd-17-4943-2024, https://doi.org/10.5194/gmd-17-4943-2024, 2024
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Future sea-level rise is of big significance for coastal regions. The melting and acceleration of glaciers plays a major role in sea-level change. Computer simulation of glaciers costs a lot of computational resources. In this publication, we test a new way of simulating glaciers. This approach produces the same results but has the advantage that it needs much less computation time. As simulations can be obtained with fewer computation resources, higher resolution and physics become affordable.
Jevgenijs Steinbuks, Yongyang Cai, Jonas Jaegermeyr, and Thomas W. Hertel
Geosci. Model Dev., 17, 4791–4819, https://doi.org/10.5194/gmd-17-4791-2024, https://doi.org/10.5194/gmd-17-4791-2024, 2024
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This paper applies a cutting-edge numerical method, SCEQ, to show how uncertain climate change and technological progress affect the future utilization of the world's scarce land resources. The paper's key insight is to illustrate how much global cropland will expand when future crop yields are unknown. The study finds the range of outcomes for land use change to be smaller when using this novel method compared to existing deterministic models.
Yuta Kawai and Hirofumi Tomita
EGUsphere, https://doi.org/10.5194/egusphere-2024-1477, https://doi.org/10.5194/egusphere-2024-1477, 2024
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When considering future high-resolution atmospheric simulations with O(10–100 m) grid spacing, such as global large-eddy simulations, numerical errors with the conventional low-order dynamical cores can contaminate the effects of turbulent parameterization. To achieve high-order discretization, we developed a global atmospheric dynamical core using the discontinuous Galerkin method (DGM). By conducting several validation tests, we discussed the impact of high-order DGM on the atmospheric flows.
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard
EGUsphere, https://doi.org/10.5194/egusphere-2024-1191, https://doi.org/10.5194/egusphere-2024-1191, 2024
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In geosciences, the reliance on numerical models necessitates the precise calibration of their parameters to effectively translate information from observed to unobserved settings. We introduce a generalizable framework for calibrating numerical models, with a case study of the geomorphological model CAESAR-Lisflood. This approach efficiently identifies the optimal set of parameters for a given numerical model, enabling retrospective and prospective analyses at various temporal resolutions.
Gianandrea Mannarini, Mario Leonardo Salinas, Lorenzo Carelli, Nicola Petacco, and Josip Orović
Geosci. Model Dev., 17, 4355–4382, https://doi.org/10.5194/gmd-17-4355-2024, https://doi.org/10.5194/gmd-17-4355-2024, 2024
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Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024, https://doi.org/10.5194/gmd-17-4199-2024, 2024
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To mitigate the imbalances in the initial conditions, this study introduces our recent implementation of the incremental analysis update (IAU) in the Model for Prediction Across Scales – Atmospheric (MPAS-A) component coupled with the Joint Effort for Data assimilation Integration (JEDI) through the cycling system. A month-long cycling run demonstrates the successful implementation of the IAU capability in the MPAS–JEDI cycling system.
Federica Castino, Feijia Yin, Volker Grewe, Hiroshi Yamashita, Sigrun Matthes, Simone Dietmüller, Sabine Baumann, Manuel Soler, Abolfazl Simorgh, Maximilian Mendiguchia Meuser, Florian Linke, and Benjamin Lührs
Geosci. Model Dev., 17, 4031–4052, https://doi.org/10.5194/gmd-17-4031-2024, https://doi.org/10.5194/gmd-17-4031-2024, 2024
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We introduce SolFinder 1.0, a decision-making tool to select trade-offs between different objective functions for optimal aircraft trajectories, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel and uses weather conditions simulated by the EMAC atmospheric model. This paper focuses on the ability of SolFinder to identify eco-efficient trajectories, reducing a flight's climate impact at limited cost penalties.
Ali Dashti, Jens C. Grimmer, Christophe Geuzaine, Florian Bauer, and Thomas Kohl
Geosci. Model Dev., 17, 3467–3485, https://doi.org/10.5194/gmd-17-3467-2024, https://doi.org/10.5194/gmd-17-3467-2024, 2024
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This study developed new meshing workflows to enable the automatic generation of meshes that follow geological models. The workflow allows for importing several geological models as input for Gmsh and later exporting the same number of high-quality meshes. This way, geological uncertainty is directly included in the numerical simulations. This study evaluates the impact of the geological uncertainty on thermohydraulic performance of two reservoirs for high-temperature heat storage applications.
Wangbin Shen, Zhaohui Lin, Zhengkun Qin, and Juan Li
Geosci. Model Dev., 17, 3447–3465, https://doi.org/10.5194/gmd-17-3447-2024, https://doi.org/10.5194/gmd-17-3447-2024, 2024
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In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The findings demonstrate that the assimilation of surface soil moisture observation images effectively and reasonably enhances the spatial structure of soil moisture analysis field.
Luan Carlos de Sena Monteiro Ozelim, Michéle Dal Toé Casagrande, and André Luís Brasil Cavalcante
Geosci. Model Dev., 17, 3175–3197, https://doi.org/10.5194/gmd-17-3175-2024, https://doi.org/10.5194/gmd-17-3175-2024, 2024
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The paper addresses synthetic dataset challenges in nonlinear constitutive modeling of soils, providing two datasets: one with 2000 soil types, 40 test conditions each (160 000 triaxial tests), and a second with 2048 soil types, 42 test conditions each (172 032 triaxial tests). Each dataset is a 4000×10 matrix applicable for multivariate forecasting and geotechnical simulations. In addition, a new Python code is introduced, empowering researchers to leverage Python packages for NorSand analyses.
Daniel Giles, Matthew M. Graham, Mosè Giordano, Tuomas Koskela, Alexandros Beskos, and Serge Guillas
Geosci. Model Dev., 17, 2427–2445, https://doi.org/10.5194/gmd-17-2427-2024, https://doi.org/10.5194/gmd-17-2427-2024, 2024
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Digital twins of physical and human systems informed by real-time data are becoming ubiquitous across a wide range of settings. Progress for researchers is currently limited by a lack of tools to run these models effectively and efficiently. A key challenge is the optimal use of high-performance computing environments. The work presented here focuses on a developed open-source software platform which aims to improve this usage, with an emphasis placed on flexibility, efficiency, and scalability.
Stefan J. Miller, Paul A. Makar, and Colin J. Lee
Geosci. Model Dev., 17, 2197–2219, https://doi.org/10.5194/gmd-17-2197-2024, https://doi.org/10.5194/gmd-17-2197-2024, 2024
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This work outlines a new solver written in Fortran to calculate the partitioning of metastable aerosols at thermodynamic equilibrium based on the forward algorithms of ISORROPIA II. The new code includes numerical improvements that decrease the computational speed (compared to ISORROPIA II) while improving the accuracy of the partitioning solution.
Fernanda Alvarado-Neves, Laurent Ailleres, Lachlan Grose, Alexander R. Cruden, and Robin Armit
Geosci. Model Dev., 17, 1975–1993, https://doi.org/10.5194/gmd-17-1975-2024, https://doi.org/10.5194/gmd-17-1975-2024, 2024
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Previous work has demonstrated that adding geological knowledge to modelling methods creates more accurate and reliable models. Following this reasoning, we added constraints from magma emplacement mechanisms into existing modelling frameworks to improve the 3D characterisation of igneous intrusions. We tested the method on synthetic and real-world case studies, and the results show that our method can reproduce intrusion morphologies with no manual processing and using realistic datasets.
André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum, and Nina Kristiansen
Geosci. Model Dev., 17, 1957–1974, https://doi.org/10.5194/gmd-17-1957-2024, https://doi.org/10.5194/gmd-17-1957-2024, 2024
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It is vital to know the extent and concentration of volcanic ash in the atmosphere during a volcanic eruption. Whilst satellite imagery may give an estimate of the ash right now (assuming no cloud coverage), we also need to know where it will be in the coming hours. This paper presents a method for estimating parameters for a volcanic eruption based on satellite observations of ash in the atmosphere. The software package is open source and applicable to similar inversion scenarios.
Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, José Antonio Álvarez Antolínez, Tim Leijnse, and Dano Roelvink
Geosci. Model Dev., 17, 1789–1811, https://doi.org/10.5194/gmd-17-1789-2024, https://doi.org/10.5194/gmd-17-1789-2024, 2024
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Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
Younghun Kang and Ethan J. Kubatko
Geosci. Model Dev., 17, 1603–1625, https://doi.org/10.5194/gmd-17-1603-2024, https://doi.org/10.5194/gmd-17-1603-2024, 2024
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Models used to simulate the flow of coastal and riverine waters, including flooding, require a geometric representation (or mesh) of geographic features that exhibit a range of disparate spatial scales from large, open waters to small, narrow channels. Representing these features in an accurate way without excessive computational overhead presents a challenge. Here, we develop an automatic mesh generation tool to help address this challenge. Our results demonstrate the efficacy of our approach.
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024, https://doi.org/10.5194/gmd-17-1387-2024, 2024
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Sophisticated numerical models of the Earth's atmosphere include representations of many physical and chemical processes. In numerical simulations, these processes need to be calculated in a certain sequence. This study reveals the weaknesses of the sequence of calculations used for aerosol processes in a global atmosphere model. A revision of the sequence is proposed and its impacts on the simulated global aerosol climatology are evaluated.
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024, https://doi.org/10.5194/gmd-17-1409-2024, 2024
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Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
Tom Keel, Chris Brierley, and Tamsin Edwards
Geosci. Model Dev., 17, 1229–1247, https://doi.org/10.5194/gmd-17-1229-2024, https://doi.org/10.5194/gmd-17-1229-2024, 2024
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Jet streams are an important control on surface weather as their speed and shape can modify the properties of weather systems. Establishing trends in the operation of jet streams may provide some indication of the future of weather in a warming world. Despite this, it has not been easy to establish trends, as many methods have been used to characterise them in data. We introduce a tool containing various implementations of jet stream statistics and algorithms that works in a standardised manner.
Amir Golparvar, Matthias Kästner, and Martin Thullner
Geosci. Model Dev., 17, 881–898, https://doi.org/10.5194/gmd-17-881-2024, https://doi.org/10.5194/gmd-17-881-2024, 2024
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Coupled reaction transport modelling is an established and beneficial method for studying natural and synthetic porous material, with applications ranging from industrial processes to natural decompositions in terrestrial environments. Up to now, a framework that explicitly considers the porous structure (e.g. from µ-CT images) for modelling the transport of reactive species is missing. We presented a model that overcomes this limitation and represents a novel numerical simulation toolbox.
Stefan Hergarten
Geosci. Model Dev., 17, 781–794, https://doi.org/10.5194/gmd-17-781-2024, https://doi.org/10.5194/gmd-17-781-2024, 2024
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The Voellmy rheology has been widely used for simulating snow and rock avalanches. Recently, a modified version of this rheology was proposed, which turned out to be able to predict the observed long runout of large rock avalanches theoretically. The software MinVoellmy presented here is the first numerical implementation of the modified rheology. It consists of MATLAB and Python classes, where simplicity and parsimony were the design goals.
Arjun Babu Nellikkattil, Danielle Lemmon, Travis Allen O'Brien, June-Yi Lee, and Jung-Eun Chu
Geosci. Model Dev., 17, 301–320, https://doi.org/10.5194/gmd-17-301-2024, https://doi.org/10.5194/gmd-17-301-2024, 2024
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This study introduces a new computational framework called Scalable Feature Extraction and Tracking (SCAFET), designed to extract and track features in climate data. SCAFET stands out by using innovative shape-based metrics to identify features without relying on preconceived assumptions about the climate model or mean state. This approach allows more accurate comparisons between different models and scenarios.
Mohammad Mortezazadeh, Jean-François Cossette, Ashu Dastoor, Jean de Grandpré, Irena Ivanova, and Abdessamad Qaddouri
Geosci. Model Dev., 17, 335–346, https://doi.org/10.5194/gmd-17-335-2024, https://doi.org/10.5194/gmd-17-335-2024, 2024
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The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach. In this paper we implement a new interpolation scheme into the semi-Lagrangian approach which has the same computational cost as a third-order polynomial scheme but with the accuracy of a fourth-order interpolation scheme. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps.
Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024, https://doi.org/10.5194/gmd-17-71-2024, 2024
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This contribution presents a new method to numerically explore the evolution of mountain ranges and surrounding areas. The method helps in monitoring with details on the timing and travel path of material eroded from the mountain ranges. It is particularly well suited to studies juxtaposing different domains – lakes or multiple rock types, for example – and enables the combination of different processes.
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023, https://doi.org/10.5194/gmd-16-7375-2023, 2023
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In geosciences, we often use simulations based on physical laws. These simulations can be computationally expensive, which is a problem if simulations must be performed many times (e.g., to add error bounds). We show how a novel machine learning method helps to reduce simulation time. In comparison to other approaches, which typically only look at the output of a simulation, the method considers physical laws in the simulation itself. The method provides reliable results faster than standard.
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023, https://doi.org/10.5194/gmd-16-7237-2023, 2023
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This paper develops a calibration methodology of all absorbing techniques typically used by Fourier pseudo-spectral time-domain (PSTD) methods for geoacoustic wave simulations. The main contributions of the paper are (a) an implementation and quantitative comparison of all absorbing techniques available for PSTD methods through a simple and robust numerical experiment, and (b) a validation of these absorbing techniques in several 3-D seismic scenarios with gradual heterogeneity complexities.
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023, https://doi.org/10.5194/gmd-16-6987-2023, 2023
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Neural networks can be used effectively to model three-dimensional geological structures from point data, sampling geological interfaces, units, and structural orientations. Existing neural network approaches for this type of modelling are advanced by the efficient incorporation of unconformities, new knowledge inputs, and improved data fitting techniques. These advances permit the modelling of more complex geology in diverse geological settings, different-sized areas, and various data regimes.
Ane Lopez de Gamiz-Zearra, Cecilie Hansen, Xavier Corrales, Iñaki Quincoces, Izaskun Preciado, and Eider Andonegi
EGUsphere, https://doi.org/10.5194/egusphere-2023-1368, https://doi.org/10.5194/egusphere-2023-1368, 2023
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This paper describes the development of the first calibrated end-to-end Atlantis model for the Bay of Biscay that will help us improve the comprehension of the spatial functioning of the Bay of Biscay ecosystem and help establishing management measures of human activities. Our results highlighted the importance of lower trophic levels to the pelagic system and demonstrate the importance of having accurate and precise data for biological processes.
Tor Nordam, Ruben Kristiansen, Raymond Nepstad, Erik van Sebille, and Andy M. Booth
Geosci. Model Dev., 16, 5339–5363, https://doi.org/10.5194/gmd-16-5339-2023, https://doi.org/10.5194/gmd-16-5339-2023, 2023
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We describe and compare two common methods, Eulerian and Lagrangian models, used to simulate the vertical transport of material in the ocean. They both solve the same transport problems but use different approaches for representing the underlying equations on the computer. The main focus of our study is on the numerical accuracy of the two approaches. Our results should be useful for other researchers creating or using these types of transport models.
Mathieu Gravey and Grégoire Mariethoz
Geosci. Model Dev., 16, 5265–5279, https://doi.org/10.5194/gmd-16-5265-2023, https://doi.org/10.5194/gmd-16-5265-2023, 2023
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Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Siting Li, Ping Wang, Hong Wang, Yue Peng, Zhaodong Liu, Wenjie Zhang, Hongli Liu, Yaqiang Wang, Huizheng Che, and Xiaoye Zhang
Geosci. Model Dev., 16, 4171–4191, https://doi.org/10.5194/gmd-16-4171-2023, https://doi.org/10.5194/gmd-16-4171-2023, 2023
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Optimizing the initial state of atmospheric chemistry model input is one of the most essential methods to improve forecast accuracy. Considering the large computational load of the model, we introduce an ensemble optimal interpolation scheme (EnOI) for operational use and efficient updating of the initial fields of chemical components. The results suggest that EnOI provides a practical and cost-effective technique for improving the accuracy of chemical weather numerical forecasts.
Thomas Richter, Véronique Dansereau, Christian Lessig, and Piotr Minakowski
Geosci. Model Dev., 16, 3907–3926, https://doi.org/10.5194/gmd-16-3907-2023, https://doi.org/10.5194/gmd-16-3907-2023, 2023
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Sea ice covers not only the pole regions but affects the weather and climate globally. For example, its white surface reflects more sunlight than land. The oceans around the poles are therefore kept cool, which affects the circulation in the oceans worldwide. Simulating the behavior and changes in sea ice on a computer is, however, very difficult. We propose a new computer simulation that better models how cracks in the ice change over time and show this by comparing to other simulations.
Emma J. MacKie, Michael Field, Lijing Wang, Zhen Yin, Nathan Schoedl, Matthew Hibbs, and Allan Zhang
Geosci. Model Dev., 16, 3765–3783, https://doi.org/10.5194/gmd-16-3765-2023, https://doi.org/10.5194/gmd-16-3765-2023, 2023
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Earth scientists often have to fill in spatial gaps in measurements. This gap-filling or interpolation can be accomplished with geostatistical methods, where the statistical relationships between measurements are used to inform how these gaps should be filled. Despite the broad utility of these methods, there are few freely available geostatistical software applications. We present GStatSim, a Python package for performing different geostatistical interpolation methods.
Ian Madden, Simone Marras, and Jenny Suckale
Geosci. Model Dev., 16, 3479–3500, https://doi.org/10.5194/gmd-16-3479-2023, https://doi.org/10.5194/gmd-16-3479-2023, 2023
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To aid risk managers who may wish to rapidly assess tsunami risk but may lack high-performance computing infrastructure, we provide an accessible software package able to rapidly model tsunami inundation over real topography by leveraging Google's Tensor Processing Unit, a high-performance hardware. Minimally trained users can take advantage of the rapid modeling abilities provided by this package via a web browser thanks to the ease of use of Google Cloud Platform.
Youtong Rong, Paul Bates, and Jeffrey Neal
Geosci. Model Dev., 16, 3291–3311, https://doi.org/10.5194/gmd-16-3291-2023, https://doi.org/10.5194/gmd-16-3291-2023, 2023
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A novel subgrid channel (SGC) model is developed for river–floodplain modelling, allowing utilization of subgrid-scale bathymetric information while performing computations on relatively coarse grids. By including adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low-friction regions such as urban areas is addressed. Evaluation of the new SGC model through structured tests confirmed that the accuracy and stability have improved.
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.
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Short summary
This paper presents a new interpolator useful for geophysics applications. It can explore N-dimensional meshes, grids or look-up tables. The code accepts irregular but structured grids. Written in Fortran, it is easy to implement in existing codes and very fast and portable. We have compared it with a Python library. Python is convenient but suffers from portability and is sometimes not optimized enough. As an application case, this method is applied to atmospheric sciences.
This paper presents a new interpolator useful for geophysics applications. It can explore...
