Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7459-2021
© 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-14-7459-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
07 Dec 2021
Model experiment description paper |
| 07 Dec 2021
| 07 Dec 2021
The effect of accounting for public holidays on the skills of the atmospheric composition model SILAM v.5.7
Finnish Meteorological Institute, Helsinki, Finland
Rostislav Kouznetsov
Finnish Meteorological Institute, Helsinki, Finland
A.M. Obukhov Institute for Atmospheric Physics, Moscow, Russia
Mikhail Sofiev
Finnish Meteorological Institute, Helsinki, Finland
Related authors
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frederik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Massimo D’Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
EGUsphere, https://doi.org/10.5194/egusphere-2024-3744, https://doi.org/10.5194/egusphere-2024-3744, 2024
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Rostislav Kouznetsov, Risto Hänninen, Andreas Uppstu, Evgeny Kadantsev, Yalda Fatahi, Marje Prank, Dmitrii Kouznetsov, Steffen Manfred Noe, Heikki Junninen, and Mikhail Sofiev
Atmos. Chem. Phys., 24, 4675–4691, https://doi.org/10.5194/acp-24-4675-2024, https://doi.org/10.5194/acp-24-4675-2024, 2024
Short summary
Short summary
By relying solely on publicly available media reports, we were able to infer the temporal evolution and the injection height for the Nord Stream gas leaks in September 2022. The inventory specifies locations, vertical distributions, and temporal evolution of the methane sources. The inventory can be used to simulate the event with atmospheric transport models. The inventory is supplemented with a set of observational data tailored to evaluate the results of the simulated atmospheric dispersion.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frederik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Massimo D’Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
EGUsphere, https://doi.org/10.5194/egusphere-2024-3744, https://doi.org/10.5194/egusphere-2024-3744, 2024
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
Branko Sikoparija, Predrag Matavulj, Isidora Simovic, Predrag Radisic, Sanja Brdar, Vladan Minic, Danijela Tesendic, Evgeny Kadantsev, Julia Palamarchuk, and Mikhail Sofiev
Atmos. Meas. Tech., 17, 5051–5070, https://doi.org/10.5194/amt-17-5051-2024, https://doi.org/10.5194/amt-17-5051-2024, 2024
Short summary
Short summary
We assess the suitability of a Rapid-E+ particle counter for use in pollen monitoring networks. The criterion was the ability of different devices to provide the same signal for the same pollen type, which would allow for unified reference libraries and recognition algorithms for Rapid-E+. We tested three devices and found notable differences between their fluorescence measurements. Each one showed potential for pollen identification, but the large variability between them needs to be addressed.
Rostislav Kouznetsov, Risto Hänninen, Andreas Uppstu, Evgeny Kadantsev, Yalda Fatahi, Marje Prank, Dmitrii Kouznetsov, Steffen Manfred Noe, Heikki Junninen, and Mikhail Sofiev
Atmos. Chem. Phys., 24, 4675–4691, https://doi.org/10.5194/acp-24-4675-2024, https://doi.org/10.5194/acp-24-4675-2024, 2024
Short summary
Short summary
By relying solely on publicly available media reports, we were able to infer the temporal evolution and the injection height for the Nord Stream gas leaks in September 2022. The inventory specifies locations, vertical distributions, and temporal evolution of the methane sources. The inventory can be used to simulate the event with atmospheric transport models. The inventory is supplemented with a set of observational data tailored to evaluate the results of the simulated atmospheric dispersion.
Heidi Hellén, Rostislav Kouznetsov, Kaisa Kraft, Jukka Seppälä, Mika Vestenius, Jukka-Pekka Jalkanen, Lauri Laakso, and Hannele Hakola
Atmos. Chem. Phys., 24, 4717–4731, https://doi.org/10.5194/acp-24-4717-2024, https://doi.org/10.5194/acp-24-4717-2024, 2024
Short summary
Short summary
Mixing ratios of C2-C5 NMHCs and methanethiol were measured on an island in the Baltic Sea using an in situ gas chromatograph. Shipping emissions were found to be an important source of ethene, ethyne, propene, and benzene. High summertime mixing ratios of methanethiol and dependence of mixing ratios on seawater temperature and height indicated the biogenic origin to possibly be phytoplankton or macroalgae. These emissions may have a strong impact on SO2 production and new particle formation.
Leena Kangas, Jaakko Kukkonen, Mari Kauhaniemi, Kari Riikonen, Mikhail Sofiev, Anu Kousa, Jarkko V. Niemi, and Ari Karppinen
Atmos. Chem. Phys., 24, 1489–1507, https://doi.org/10.5194/acp-24-1489-2024, https://doi.org/10.5194/acp-24-1489-2024, 2024
Short summary
Short summary
Residential wood combustion is a major source of fine particulate matter. This study has evaluated the contribution of residential wood combustion to fine particle concentrations and its year-to-year and seasonal variation in te Helsinki metropolitan area. The average concentrations attributed to wood combustion in winter were up to 10- or 15-fold compared to summer. Wood combustion caused 12 % to 14 % of annual fine particle concentrations. In winter, the contribution ranged from 16 % to 21 %.
Risto Matias Hänninen, Rostislav Kouznetsov, and Mikhail Sofiev
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-3, https://doi.org/10.5194/gmd-2023-3, 2023
Preprint withdrawn
Short summary
Short summary
Chemistry transport models describe the motion of particles and gases in atmosphere, containing chemistry equations that allow reaction between different species. The widely used carbon-bond chemistry schemes are originally written in a numerically problematic form that drives some concentrations to unphysical negative values. Here the chemistry equations are re-written in a form where this problem is absent, allowing an easier integration of the equations into any chemistry transport model.
Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, https://doi.org/10.5194/acp-23-3083-2023, 2023
Short summary
Short summary
Plume height is important in wildfire smoke dispersion and affects air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region, but higher pollution in downwind regions, due to the faster spread of the smoke once ejected, affects pollution exceedance forecasts and the early warning of extreme air pollution events.
Sanna Saarikoski, Heidi Hellén, Arnaud P. Praplan, Simon Schallhart, Petri Clusius, Jarkko V. Niemi, Anu Kousa, Toni Tykkä, Rostislav Kouznetsov, Minna Aurela, Laura Salo, Topi Rönkkö, Luis M. F. Barreira, Liisa Pirjola, and Hilkka Timonen
Atmos. Chem. Phys., 23, 2963–2982, https://doi.org/10.5194/acp-23-2963-2023, https://doi.org/10.5194/acp-23-2963-2023, 2023
Short summary
Short summary
This study elucidates properties and sources of volatile organic compounds (VOCs) and organic aerosol (OA) in a traffic environment. Anthropogenic VOCs (aVOCs) were clearly higher than biogenic VOCs (bVOCs), but bVOCs produced a larger portion of oxidation products. OA consisted mostly of oxygenated OA, representing secondary OA (SOA). SOA was partly associated with bVOCs, but it was also related to long-range transport. Primary OA originated mostly from traffic.
Svetlana Sofieva, Eija Asmi, Nina S. Atanasova, Aino E. Heikkinen, Emeline Vidal, Jonathan Duplissy, Martin Romantschuk, Rostislav Kouznetsov, Jaakko Kukkonen, Dennis H. Bamford, Antti-Pekka Hyvärinen, and Mikhail Sofiev
Atmos. Meas. Tech., 15, 6201–6219, https://doi.org/10.5194/amt-15-6201-2022, https://doi.org/10.5194/amt-15-6201-2022, 2022
Short summary
Short summary
A new bubble-generating glass chamber design with an extensive set of aerosol production experiments is presented to re-evaluate bubble-bursting-mediated aerosol production as a function of water parameters: bubbling air flow, water salinity, and temperature. Our main findings suggest modest dependence of aerosol production on the water salinity and a strong dependence on temperature below ~ 10 °C.
Outi Meinander, Pavla Dagsson-Waldhauserova, Pavel Amosov, Elena Aseyeva, Cliff Atkins, Alexander Baklanov, Clarissa Baldo, Sarah L. Barr, Barbara Barzycka, Liane G. Benning, Bojan Cvetkovic, Polina Enchilik, Denis Frolov, Santiago Gassó, Konrad Kandler, Nikolay Kasimov, Jan Kavan, James King, Tatyana Koroleva, Viktoria Krupskaya, Markku Kulmala, Monika Kusiak, Hanna K. Lappalainen, Michał Laska, Jerome Lasne, Marek Lewandowski, Bartłomiej Luks, James B. McQuaid, Beatrice Moroni, Benjamin Murray, Ottmar Möhler, Adam Nawrot, Slobodan Nickovic, Norman T. O’Neill, Goran Pejanovic, Olga Popovicheva, Keyvan Ranjbar, Manolis Romanias, Olga Samonova, Alberto Sanchez-Marroquin, Kerstin Schepanski, Ivan Semenkov, Anna Sharapova, Elena Shevnina, Zongbo Shi, Mikhail Sofiev, Frédéric Thevenet, Throstur Thorsteinsson, Mikhail Timofeev, Nsikanabasi Silas Umo, Andreas Uppstu, Darya Urupina, György Varga, Tomasz Werner, Olafur Arnalds, and Ana Vukovic Vimic
Atmos. Chem. Phys., 22, 11889–11930, https://doi.org/10.5194/acp-22-11889-2022, https://doi.org/10.5194/acp-22-11889-2022, 2022
Short summary
Short summary
High-latitude dust (HLD) is a short-lived climate forcer, air pollutant, and nutrient source. Our results suggest a northern HLD belt at 50–58° N in Eurasia and 50–55° N in Canada and at >60° N in Eurasia and >58° N in Canada. Our addition to the previously identified global dust belt (GDB) provides crucially needed information on the extent of active HLD sources with both direct and indirect impacts on climate and environment in remote regions, which are often poorly understood and predicted.
Viktoria F. Sofieva, Risto Hänninen, Mikhail Sofiev, Monika Szeląg, Hei Shing Lee, Johanna Tamminen, and Christian Retscher
Atmos. Meas. Tech., 15, 3193–3212, https://doi.org/10.5194/amt-15-3193-2022, https://doi.org/10.5194/amt-15-3193-2022, 2022
Short summary
Short summary
We present tropospheric ozone column datasets that have been created using combinations of total ozone column from OMI and TROPOMI with stratospheric ozone column datasets from several available limb-viewing instruments (MLS, OSIRIS, MIPAS, SCIAMACHY, OMPS-LP, GOMOS). The main results are (i) several methodological developments, (ii) new tropospheric ozone column datasets from OMI and TROPOMI, and (iii) a new high-resolution dataset of ozone profiles from limb satellite instruments.
Tero M. Partanen and Mikhail Sofiev
Nat. Hazards Earth Syst. Sci., 22, 1335–1346, https://doi.org/10.5194/nhess-22-1335-2022, https://doi.org/10.5194/nhess-22-1335-2022, 2022
Short summary
Short summary
The presented method aims to forecast regional wildfire-emitted radiative power in a time-dependent manner several days in advance. The temporal fire radiative power can be converted to an emission production rate, which can be implemented in air quality forecasting simulations. It is shown that in areas with a high incidence of wildfires, the fire radiative power is quite predictable, but otherwise it is not.
Karol Kuliński, Gregor Rehder, Eero Asmala, Alena Bartosova, Jacob Carstensen, Bo Gustafsson, Per O. J. Hall, Christoph Humborg, Tom Jilbert, Klaus Jürgens, H. E. Markus Meier, Bärbel Müller-Karulis, Michael Naumann, Jørgen E. Olesen, Oleg Savchuk, Andreas Schramm, Caroline P. Slomp, Mikhail Sofiev, Anna Sobek, Beata Szymczycha, and Emma Undeman
Earth Syst. Dynam., 13, 633–685, https://doi.org/10.5194/esd-13-633-2022, https://doi.org/10.5194/esd-13-633-2022, 2022
Short summary
Short summary
The paper covers the aspects related to changes in carbon, nitrogen, and phosphorus (C, N, P) external loads; their transformations in the coastal zone; changes in organic matter production (eutrophication) and remineralization (oxygen availability); and the role of sediments in burial and turnover of C, N, and P. Furthermore, this paper also focuses on changes in the marine CO2 system, the structure of the microbial community, and the role of contaminants for biogeochemical processes.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
Short summary
Short summary
The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986).
Jérôme Barré, Hervé Petetin, Augustin Colette, Marc Guevara, Vincent-Henri Peuch, Laurence Rouil, Richard Engelen, Antje Inness, Johannes Flemming, Carlos Pérez García-Pando, Dene Bowdalo, Frederik Meleux, Camilla Geels, Jesper H. Christensen, Michael Gauss, Anna Benedictow, Svetlana Tsyro, Elmar Friese, Joanna Struzewska, Jacek W. Kaminski, John Douros, Renske Timmermans, Lennart Robertson, Mario Adani, Oriol Jorba, Mathieu Joly, and Rostislav Kouznetsov
Atmos. Chem. Phys., 21, 7373–7394, https://doi.org/10.5194/acp-21-7373-2021, https://doi.org/10.5194/acp-21-7373-2021, 2021
Short summary
Short summary
This study provides a comprehensive assessment of air quality changes across the main European urban areas induced by the COVID-19 lockdown using satellite observations, surface site measurements, and the forecasting system from the Copernicus Atmospheric Monitoring Service (CAMS). We demonstrate the importance of accounting for weather and seasonal variability when calculating such estimates.
Rostislav Kouznetsov
Geosci. Model Dev., 14, 377–389, https://doi.org/10.5194/gmd-14-377-2021, https://doi.org/10.5194/gmd-14-377-2021, 2021
Short summary
Short summary
Resetting of non-significant figures (precision trimming) enables efficient data compression and helps to avoid excessive use of storage space and network bandwidth while having well-constrained distortion to the data. The paper analyses accuracy losses and artifacts caused by trimming methods and by the widely used linear packing method. The paper presents several methods with implementation, evaluation, and illustrations and includes subroutines directly usable in geoscientific models.
Jaakko Kukkonen, Mikko Savolahti, Yuliia Palamarchuk, Timo Lanki, Väinö Nurmi, Ville-Veikko Paunu, Leena Kangas, Mikhail Sofiev, Ari Karppinen, Androniki Maragkidou, Pekka Tiittanen, and Niko Karvosenoja
Atmos. Chem. Phys., 20, 9371–9391, https://doi.org/10.5194/acp-20-9371-2020, https://doi.org/10.5194/acp-20-9371-2020, 2020
Short summary
Short summary
We have developed a mathematical model that can be used to analyse the benefits that could be achieved by implementing alternative air quality abatement measures, policies or strategies. The model was applied to determine pollution sources in the whole of Finland in 2015. Clearly the most economically effective measures were the reduction in emissions from low-level sources in urban areas. Such sources include road transport, non-road vehicles and machinery, and residential wood combustion.
Marcus Hirtl, Delia Arnold, Rocio Baro, Hugues Brenot, Mauro Coltelli, Kurt Eschbacher, Helmut Hard-Stremayer, Florian Lipok, Christian Maurer, Dieter Meinhard, Lucia Mona, Marie D. Mulder, Nikolaos Papagiannopoulos, Michael Pernsteiner, Matthieu Plu, Lennart Robertson, Carl-Herbert Rokitansky, Barbara Scherllin-Pirscher, Klaus Sievers, Mikhail Sofiev, Wim Som de Cerff, Martin Steinheimer, Martin Stuefer, Nicolas Theys, Andreas Uppstu, Saskia Wagenaar, Roland Winkler, Gerhard Wotawa, Fritz Zobl, and Raimund Zopp
Nat. Hazards Earth Syst. Sci., 20, 1719–1739, https://doi.org/10.5194/nhess-20-1719-2020, https://doi.org/10.5194/nhess-20-1719-2020, 2020
Short summary
Short summary
The paper summarizes the set-up and outcome of a volcanic-hazard demonstration exercise, with the goals of assessing and mitigating the impacts of volcanic ash clouds on civil and military aviation. Experts in the field simulated the sequence of procedures for an artificial eruption of the Etna volcano in Italy. The scope of the exercise ranged from the detection of the assumed event to the issuance of early warnings and optimized rerouting of flights.
Rostislav Kouznetsov, Mikhail Sofiev, Julius Vira, and Gabriele Stiller
Atmos. Chem. Phys., 20, 5837–5859, https://doi.org/10.5194/acp-20-5837-2020, https://doi.org/10.5194/acp-20-5837-2020, 2020
Short summary
Short summary
Estimates of the age of stratospheric air (AoA), its distribution, and trends, obtained by different experimental methods, differ among each other. AoA derived form MIPAS satellite observations, the richest observational dataset on sulfur hexafluoride (SF6) in the stratosphere, are a clear outlier. With multi-decade simulations of AoA and SF6 in the stratosphere, we show that the origin of the discrepancy is in a methodology of deriving AoA from observations rather than in observational data.
Jaakko Kukkonen, Susana López-Aparicio, David Segersson, Camilla Geels, Leena Kangas, Mari Kauhaniemi, Androniki Maragkidou, Anne Jensen, Timo Assmuth, Ari Karppinen, Mikhail Sofiev, Heidi Hellén, Kari Riikonen, Juha Nikmo, Anu Kousa, Jarkko V. Niemi, Niko Karvosenoja, Gabriela Sousa Santos, Ingrid Sundvor, Ulas Im, Jesper H. Christensen, Ole-Kenneth Nielsen, Marlene S. Plejdrup, Jacob Klenø Nøjgaard, Gunnar Omstedt, Camilla Andersson, Bertil Forsberg, and Jørgen Brandt
Atmos. Chem. Phys., 20, 4333–4365, https://doi.org/10.5194/acp-20-4333-2020, https://doi.org/10.5194/acp-20-4333-2020, 2020
Short summary
Short summary
Residential wood combustion can cause substantial emissions of fine particulate matter and adverse health effects. This study has, for the first time, evaluated the impacts of residential wood combustion in a harmonised manner in four Nordic cities. Wood combustion caused major shares of fine particle concentrations in Oslo (up to 60 %) and Umeå (up to 30 %) and also notable shares in Copenhagen (up to 20 %) and Helsinki (up to 15 %).
Anne-Marlene Blechschmidt, Joaquim Arteta, Adriana Coman, Lyana Curier, Henk Eskes, Gilles Foret, Clio Gielen, Francois Hendrick, Virginie Marécal, Frédérik Meleux, Jonathan Parmentier, Enno Peters, Gaia Pinardi, Ankie J. M. Piters, Matthieu Plu, Andreas Richter, Arjo Segers, Mikhail Sofiev, Álvaro M. Valdebenito, Michel Van Roozendael, Julius Vira, Tim Vlemmix, and John P. Burrows
Atmos. Chem. Phys., 20, 2795–2823, https://doi.org/10.5194/acp-20-2795-2020, https://doi.org/10.5194/acp-20-2795-2020, 2020
Short summary
Short summary
MAX-DOAS tropospheric NO2 vertical column retrievals from a set of European measurement stations are compared to regional air quality models which contribute to the operational Copernicus Atmosphere Monitoring Service (CAMS). Correlations are on the order of 35 %–75 %; large differences occur for individual pollution plumes. The results demonstrate that future model development needs to concentrate on improving representation of diurnal cycles and associated temporal scalings.
Alexander Kurganskiy, Carsten Ambelas Skjøth, Alexander Baklanov, Mikhail Sofiev, Annika Saarto, Elena Severova, Sergei Smyshlyaev, and Eigil Kaas
Atmos. Chem. Phys., 20, 2099–2121, https://doi.org/10.5194/acp-20-2099-2020, https://doi.org/10.5194/acp-20-2099-2020, 2020
Short summary
Short summary
The aim of the study was to evaluate three birch pollen source maps using a state-of-the-art atmospheric model Enviro-HIRLAM. Enviro-HIRLAM is a so-called online model where both weather and air pollution are calculated at all time steps.
The evaluation has been performed for 12 pollen observation sites located in Denmark, Finland, and Russia.
Mikhail Sofiev, Rostislav Kouznetsov, Risto Hänninen, and Viktoria F. Sofieva
Atmos. Chem. Phys., 20, 1839–1847, https://doi.org/10.5194/acp-20-1839-2020, https://doi.org/10.5194/acp-20-1839-2020, 2020
Short summary
Short summary
An episode of anomalously low ozone concentrations in the stratosphere over northern Europe occurred on 3–5 November 2018. The 30 % reduction of the ozone layer was predicted by the global chemistry-transport model of the Finnish Meteorological Institute driven by weather forecasts of ECMWF. The reduction was subsequently observed by ozone monitoring satellites. The episode was caused by a storm in the northern Atlantic, which uplifted air from the troposphere to stratosphere.
Ingrida Šaulienė, Laura Šukienė, Gintautas Daunys, Gediminas Valiulis, Lukas Vaitkevičius, Predrag Matavulj, Sanja Brdar, Marko Panic, Branko Sikoparija, Bernard Clot, Benoît Crouzy, and Mikhail Sofiev
Atmos. Meas. Tech., 12, 3435–3452, https://doi.org/10.5194/amt-12-3435-2019, https://doi.org/10.5194/amt-12-3435-2019, 2019
Short summary
Short summary
The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct a first-level pollen recognition algorithm. The output data were treated with ANN aiming at classification of the injected pollen. Algorithms based on scattering and fluorescence data alone fall short of acceptable quality. The combinations of these exceeded 80 % accuracy for 5 out of 11 pollen species. Constructing multistep algorithms with sequential discrimination of pollen can be a possible way forward.
Matthias Karl, Jan Eiof Jonson, Andreas Uppstu, Armin Aulinger, Marje Prank, Mikhail Sofiev, Jukka-Pekka Jalkanen, Lasse Johansson, Markus Quante, and Volker Matthias
Atmos. Chem. Phys., 19, 7019–7053, https://doi.org/10.5194/acp-19-7019-2019, https://doi.org/10.5194/acp-19-7019-2019, 2019
Short summary
Short summary
The effect of ship emissions on the regional air quality in the Baltic Sea region was investigated with three regional chemistry transport model systems. The ship influence on air quality is shown to depend on the boundary conditions, meteorological data and aerosol formation and deposition schemes that are used in these models. The study provides a reliable approach for the evaluation of policy options regarding emission regulations for ship traffic in the Baltic Sea.
Anna Katinka Petersen, Guy P. Brasseur, Idir Bouarar, Johannes Flemming, Michael Gauss, Fei Jiang, Rostislav Kouznetsov, Richard Kranenburg, Bas Mijling, Vincent-Henri Peuch, Matthieu Pommier, Arjo Segers, Mikhail Sofiev, Renske Timmermans, Ronald van der A, Stacy Walters, Ying Xie, Jianming Xu, and Guangqiang Zhou
Geosci. Model Dev., 12, 1241–1266, https://doi.org/10.5194/gmd-12-1241-2019, https://doi.org/10.5194/gmd-12-1241-2019, 2019
Short summary
Short summary
An operational multi-model forecasting system for air quality is providing daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas of China. The paper presents the evaluation of the different forecasts performed during the first year of operation.
Guy P. Brasseur, Ying Xie, Anna Katinka Petersen, Idir Bouarar, Johannes Flemming, Michael Gauss, Fei Jiang, Rostislav Kouznetsov, Richard Kranenburg, Bas Mijling, Vincent-Henri Peuch, Matthieu Pommier, Arjo Segers, Mikhail Sofiev, Renske Timmermans, Ronald van der A, Stacy Walters, Jianming Xu, and Guangqiang Zhou
Geosci. Model Dev., 12, 33–67, https://doi.org/10.5194/gmd-12-33-2019, https://doi.org/10.5194/gmd-12-33-2019, 2019
Short summary
Short summary
An operational multi-model forecasting system for air quality provides daily forecasts of ozone, nitrogen oxides, and particulate matter for 37 urban areas in China. The paper presents an intercomparison of the different forecasts performed during a specific period of time and highlights recurrent differences between the model output. Pathways to improve the forecasts by the multi-model system are suggested.
Leena Järvi, Üllar Rannik, Tom V. Kokkonen, Mona Kurppa, Ari Karppinen, Rostislav D. Kouznetsov, Pekka Rantala, Timo Vesala, and Curtis R. Wood
Atmos. Meas. Tech., 11, 5421–5438, https://doi.org/10.5194/amt-11-5421-2018, https://doi.org/10.5194/amt-11-5421-2018, 2018
Short summary
Short summary
Identical EC systems on two sides of a building in central Helsinki were used to assess the uncertainty of the vertical fluxes on the single measurement point from July 2013 to September 2015. Sampling at only one point yielded up to 12% underestimation in the cumulative carbon fluxes; for sensible and latent heat the respective values were up to 5 and 8%. The commonly used statistics, kurtosis and skewness, are not necessarily suitable for filtering out data in a densely built urban area.
Jaakko Kukkonen, Leena Kangas, Mari Kauhaniemi, Mikhail Sofiev, Mia Aarnio, Jouni J. K. Jaakkola, Anu Kousa, and Ari Karppinen
Atmos. Chem. Phys., 18, 8041–8064, https://doi.org/10.5194/acp-18-8041-2018, https://doi.org/10.5194/acp-18-8041-2018, 2018
Short summary
Short summary
We have quantified the emissions and concentrations of fine particulate matter in the Helsinki area for an unprecedentedly extensive period, from 1980 to 2014. The modelled concentrations agree well with the measured data. The concentrations of fine particles have decreased drastically since the 1980s, to about a half of the highest values. The results make it possible to evaluate the long-term health impacts of air pollution substantially better.
Mikhail Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou
Atmos. Chem. Phys., 17, 12341–12360, https://doi.org/10.5194/acp-17-12341-2017, https://doi.org/10.5194/acp-17-12341-2017, 2017
Short summary
Short summary
This work presents the features and evaluates the quality of the Copernicus Atmospheric Monitoring Service forecasts of olive pollen distribution in Europe. It is shown that the models can predict the main features of the observed pollen distribution but have more difficulties in capturing the season start and end, which appeared shifted by a few days. We also demonstrated that the combined use of model predictions with up-to-date measurements (data fusion) can strongly improve the results.
Julius Vira, Elisa Carboni, Roy G. Grainger, and Mikhail Sofiev
Geosci. Model Dev., 10, 1985–2008, https://doi.org/10.5194/gmd-10-1985-2017, https://doi.org/10.5194/gmd-10-1985-2017, 2017
Short summary
Short summary
The vertical and temporal distributions of sulfur dioxide emissions during the 2010 eruption of Eyjafjallajökull were reconstructed by combining data from the IASI satellite instrument with a dispersion model. Unlike in previous studies, both column density (the total amount above a given point) and the plume height were derived from the satellite data. This resulted in more accurate simulated vertical distributions for the times when the emission was not constrained by the column densities.
Samuel Rémy, Andreas Veira, Ronan Paugam, Mikhail Sofiev, Johannes W. Kaiser, Franco Marenco, Sharon P. Burton, Angela Benedetti, Richard J. Engelen, Richard Ferrare, and Jonathan W. Hair
Atmos. Chem. Phys., 17, 2921–2942, https://doi.org/10.5194/acp-17-2921-2017, https://doi.org/10.5194/acp-17-2921-2017, 2017
Short summary
Short summary
Biomass burning emission injection heights are an important source of uncertainty in global climate and atmospheric composition modelling. This work provides a global daily data set of injection heights computed by two very different algorithms, which coherently complete a global biomass burning emissions database. The two data sets were compared and validated against observations, and their use was found to improve forecasts of carbonaceous aerosols in two case studies.
Joana Soares, Mikhail Sofiev, Camilla Geels, Jens H. Christensen, Camilla Andersson, Svetlana Tsyro, and Joakim Langner
Atmos. Chem. Phys., 16, 13081–13104, https://doi.org/10.5194/acp-16-13081-2016, https://doi.org/10.5194/acp-16-13081-2016, 2016
Short summary
Short summary
Multi-model comparison of four offline dispersion models driven by the global climate projection climate show that the major driver for the sea salt flux changes will be the seawater temperature, but there are substantial differences between the model predictions. The impact on regional radiative budget due to sea spray is considerable in the Mediterranean area, due to warmer temperatures and longer days during the winter.
Marje Prank, Mikhail Sofiev, Svetlana Tsyro, Carlijn Hendriks, Valiyaveetil Semeena, Xavier Vazhappilly Francis, Tim Butler, Hugo Denier van der Gon, Rainer Friedrich, Johannes Hendricks, Xin Kong, Mark Lawrence, Mattia Righi, Zissis Samaras, Robert Sausen, Jaakko Kukkonen, and Ranjeet Sokhi
Atmos. Chem. Phys., 16, 6041–6070, https://doi.org/10.5194/acp-16-6041-2016, https://doi.org/10.5194/acp-16-6041-2016, 2016
Short summary
Short summary
Aerosol composition in Europe was simulated by four chemistry transport models and compared to observations to identify the most prominent areas for model improvement. Notable differences were found between the models' predictions, attributable to different treatment or omission of aerosol sources and processes. All models underestimated the observed concentrations by 10–60 %, mostly due to under-predicting the carbonaceous and mineral particles and omitting the aerosol-bound water.
M. Sofiev, J. Vira, R. Kouznetsov, M. Prank, J. Soares, and E. Genikhovich
Geosci. Model Dev., 8, 3497–3522, https://doi.org/10.5194/gmd-8-3497-2015, https://doi.org/10.5194/gmd-8-3497-2015, 2015
Short summary
Short summary
The paper presents a transport mechanism of SILAM CTM based on an algorithm of M. Galperin. We describe the original scheme and its updates needed for applications to long-living species, complex atmospheric flows, etc. The scheme is connected to vertical diffusion, chemical transformation and deposition algorithms. Quality of the advection routine is evaluated with a large set of tests, which showed performance fully comparable with state-of-the-art algorithms at much lower computational costs.
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
Short summary
Short summary
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
Short summary
Short summary
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.
M. Bocquet, H. Elbern, H. Eskes, M. Hirtl, R. Žabkar, G. R. Carmichael, J. Flemming, A. Inness, M. Pagowski, J. L. Pérez Camaño, P. E. Saide, R. San Jose, M. Sofiev, J. Vira, A. Baklanov, C. Carnevale, G. Grell, and C. Seigneur
Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, https://doi.org/10.5194/acp-15-5325-2015, 2015
Short summary
Short summary
Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of concentrations, and perform inverse modeling. Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. We review here the current status of data assimilation in atmospheric chemistry models, with a particular focus on future prospects for data assimilation in CCMM.
J. Vira and M. Sofiev
Geosci. Model Dev., 8, 191–203, https://doi.org/10.5194/gmd-8-191-2015, https://doi.org/10.5194/gmd-8-191-2015, 2015
J. Kukkonen, J. Nikmo, M. Sofiev, K. Riikonen, T. Petäjä, A. Virkkula, J. Levula, S. Schobesberger, and D. M. Webber
Geosci. Model Dev., 7, 2663–2681, https://doi.org/10.5194/gmd-7-2663-2014, https://doi.org/10.5194/gmd-7-2663-2014, 2014
D. Simpson, C. Andersson, J.H. Christensen, M. Engardt, C. Geels, A. Nyiri, M. Posch, J. Soares, M. Sofiev, P. Wind, and J. Langner
Atmos. Chem. Phys., 14, 6995–7017, https://doi.org/10.5194/acp-14-6995-2014, https://doi.org/10.5194/acp-14-6995-2014, 2014
M. Sofiev, R. Vankevich, T. Ermakova, and J. Hakkarainen
Atmos. Chem. Phys., 13, 7039–7052, https://doi.org/10.5194/acp-13-7039-2013, https://doi.org/10.5194/acp-13-7039-2013, 2013
Related subject area
Atmospheric sciences
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Low-level jets in the North and Baltic Seas: Mesoscale Model Sensitivity and Climatology
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Estimation of aerosol and cloud radiative heating rate in tropical stratosphere using radiative kernel method
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
Short summary
Short summary
The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
Short summary
Short summary
Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
Short summary
Short summary
This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2815, https://doi.org/10.5194/egusphere-2024-2815, 2024
Short summary
Short summary
The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate that effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense and consists well with radiative model calculations and can be applied to atmospheric models with speed requirements.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary
Short summary
We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2024-2700, https://doi.org/10.5194/egusphere-2024-2700, 2024
Short summary
Short summary
Reducing methane emissions, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from regional to global scales and allow continuous emissions monitoring.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
Short summary
Short summary
Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
Short summary
Short summary
RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Cited articles
Beirle, S., Platt, U., Wenig, M., and Wagner, T.: Weekly cycle of NO2 by GOME measurements: a signature of anthropogenic sources, Atmos. Chem. Phys., 3, 2225–2232, https://doi.org/10.5194/acp-3-2225-2003, 2003.
Brasseur, G. P., Xie, Y., Petersen, A. K., Bouarar, I., Flemming, J., Gauss, M., Jiang, F., Kouznetsov, R., Kranenburg, R., Mijling, B., Peuch, V.-H., Pommier, M., Segers, A., Sofiev, M., Timmermans, R., van der A, R., Walters, S., Xu, J., and Zhou, G.: Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1, Geosci. Model Dev., 12, 33–67, https://doi.org/10.5194/gmd-12-33-2019, 2019.
Carslaw, K. S., Luo, B., and Peter, T.: An analytic expression for the composition of aqueous HNO3-H2SO4 stratospheric aerosols including gas phase removal of HNO3, Geophys. Res. Lett., 22, 1877–1880, https://doi.org/10.1029/95GL01668, 1995.
Chen, P.-Y., Tan, P.-H., Chou, C. C.-K., Lin, Y.-S., Chen, W.-N., and Shiu, C.-J.: Impacts of holiday characteristics and number of vacation days on “holiday effect” in Taipei: Implications on ozone control strategies, Atmos. Environ., 202, 357–369, https://doi.org/10.1016/j.atmosenv.2019.01.029, 2019.
Damski, J., Thölix, L., Backman, L., Taalas, P., and Kulmala, M.: FinROSE – middle atmospheric chemistry transport model, Boreal Environ. Res., 12, 535–550, 2007.
Dasari, H. P., Desamsetti, S., Langodan, S., Karumuri, R. K., Singh, S., and Hoteit, I.: Atmospheric conditions and air quality assessment over NEOM, Kingdom of Saudi Arabia, Atmos. Environ., 230, 117489, https://doi.org/10.1016/j.atmosenv.2020.117489, 2020.
de Foy, B., Lu, Z., and Streets, D. G.: Impacts of control strategies, the Great Recession and weekday variations on NO2 columns above North American cities, Atmos. Environ., 138, 74–86, https://doi.org/10.1016/j.atmosenv.2016.04.038, 2016.
de Foy, B., Brune, W. H., and Schauer, J. J.: Changes in ozone photochemical regime in Fresno, California from 1994 to 2018 deduced from changes in the weekend effect, Environ. Pollut., 263, 114380, https://doi.org/10.1016/j.envpol.2020.114380, 2020.
Derwent, R. and Hjellbrekke, A.-G.: Air Pollution by Ozone Across Europe: Handbook of Environmental Chemistry, Springer, Berlin, Heidelberg, 371 pp., 2012.
Ding, J., Miyazaki, K., van der A, R. J., Mijling, B., Kurokawa, J.-I., Cho, S., Janssens-Maenhout, G., Zhang, Q., Liu, F., and Levelt, P. F.: Intercomparison of NOx emission inventories over East Asia, Atmos. Chem. Phys., 17, 10125–10141, https://doi.org/10.5194/acp-17-10125-2017, 2017.
Elansky, N. F., Shilkin, A. V., Ponomarev, N. A., Semutnikova, E. G., and Zakharova, P. V.: Weekly patterns and weekend effects of air pollution in the Moscow megacity, Atmos. Environ., 224, 117303, https://doi.org/10.1016/j.atmosenv.2020.117303, 2020.
European Environment Agency: EMEP/EEA air pollutant emission inventory guidebook 2013: technical guidance to prepare national emission inventories, Publications Office, LU, Luxembourg, 2013.
Fan, C., Li, Z., Li, Y., Dong, J., van der A, R., and de Leeuw, G.: Variability of NO2 concentrations over China and effect on air quality derived from satellite and ground-based observations, Atmos. Chem. Phys., 21, 7723–7748, https://doi.org/10.5194/acp-21-7723-2021, 2021.
Forster, P. M. de F. and Solomon, S.: Observations of a “Weekend Effect” in Diurnal Temperature Range, P. Natl. Acad. Sci. USA, 100, 11225–11230, 2003.
Frost, G. J., Middleton, P., Tarrasón, L., Granier, C., Guenther, A., Cardenas, B., Denier van der Gon, H., Janssens-Maenhout, G., Kaiser, J. W., Keating, T., Klimont, Z., Lamarque, J.-F., Liousse, C., Nickovic, S., Ohara, T., Schultz, M. G., Skiba, U., van Aardenne, J., and Wang, Y.: New Directions: GEIA's 2020 vision for better air emissions information, Atmos. Environ., 81, 710–712, https://doi.org/10.1016/j.atmosenv.2013.08.063, 2013.
Fu, D., Song, Z., Zhang, X., Wu, Y., Duan, M., Pu, W., Ma, Z., Quan, W., Zhou, H., Che, H., and Xia, X.: Similarities and Differences in the Temporal Variability of PM2.5 and AOD Between Urban and Rural Stations in Beijing, Remote Sens., 12, 1193, https://doi.org/10.3390/rs12071193, 2020.
Fu, X., Wang, S., Zhao, B., Xing, J., Cheng, Z., Liu, H., and Hao, J.: Emission inventory of primary pollutants and chemical speciation in 2010 for the Yangtze River Delta region, China, Atmos. Environ., 70, 39–50, https://doi.org/10.1016/j.atmosenv.2012.12.034, 2013.
Galperin, M. V., Maslyaev, A. M., Pekar, M. I., and Sofiev, M.: The development of HM model in 1996, Meteorological Synthesising Centre East, Moscow, 1996.
Gery, M. W., Whitten, G. Z., Killus, J. P., and Dodge, M. C.: A photochemical kinetics mechanism for urban and regional scale computer modelling, J. Geophys. Res., 94, 12925–12956, https://doi.org/10.1029/JD094iD10p12925, 1989.
Gioli, B., Gualtieri, G., Busillo, C., Calastrini, F., Zaldei, A., and Toscano, P.: Improving high resolution emission inventories with local proxies and urban eddy covariance flux measurements, Atmos. Environ., 115, 246–256, https://doi.org/10.1016/j.atmosenv.2015.05.068, 2015.
Gour, A. A., Singh, S. K., Tyagi, S. K., and Mandal, A.: Weekday/weekend differences in air quality parameters in Delhi, India, International Journal of Research in Engineering and Technology, 1, 69–76, 2013.
Granier, C., Bessagnet, B., Bond, T., D'Angiola, A., Denier van der Gon, H., Frost, G. J., Heil, A., Kaiser, J. W., Kinne, S., Klimont, Z., Kloster, S., Lamarque, J.-F., Liousse, C., Masui, T., Meleux, F., Mieville, A., Ohara, T., Raut, J.-C., Riahi, K., Schultz, M. G., Smith, S. J., Thompson, A., van Aardenne, J., van der Werf, G. R., and van Vuuren, D. P.: Evolution of anthropogenic and biomass burning emissions of air pollutants at global and regional scales during the 1980–2010 period, Climatic Change, 109, 163–190, https://doi.org/10.1007/s10584-011-0154-1, 2011.
Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J., Elguindi, N., Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse, C., Quack, B., Simpson, D., and Sindelarova, K.: The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version), https://doi.org/10.24380/D0BN-KX16, 2019.
Grivas, G., Athanasopoulou, E., Kakouri, A., Bailey, J., Liakakou, E., Stavroulas, I., Kalkavouras, P., Bougiatioti, A., Kaskaoutis, D. G., Ramonet, M., Mihalopoulos, N., and Gerasopoulos, E.: Integrating In Situ Measurements and City Scale Modelling to Assess the COVID–19 Lockdown Effects on Emissions and Air Quality in Athens, Greece, Atmosphere, 11, 1174, https://doi.org/10.3390/atmos11111174, 2020.
Guevara, M., Lopez-Aparicio, S., Cuvelier, C., Tarrason, L., Clappier, A., and Thunis, P.: A benchmarking tool to screen and compare bottom-up and top-down atmospheric emission inventories, Air Qual. Atmos. Hlth., 10, 627–642, https://doi.org/10.1007/s11869-016-0456-6, 2017.
Guevara, M., Jorba, O., Tena, C., Denier van der Gon, H., Kuenen, J., Elguindi, N., Darras, S., Granier, C., and Pérez García-Pando, C.: Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling, Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, 2021.
Hassan, S. K., El-Abssawy, A. A., AbdEl-Maksoud, A. S., Abdou, M. H., and Khoder, M. I.: Seasonal Behaviours and Weekdays/Weekends Differences in Elemental Composition of Atmospheric Aerosols in Cairo, Egypt, Aerosol Air Qual. Res., 13, 1552–1562, https://doi.org/10.4209/aaqr.2012.12.0349, 2013.
Hoyos, C. D., Herrera-Mejía, L., Roldán-Henao, N., and Isaza, A.: Effects of fireworks on particulate matter concentration in a narrow valley: the case of the Medellín metropolitan area, Environ. Monit. Assess., 192, 6, https://doi.org/10.1007/s10661-019-7838-9, 2020.
Hua, J., Zhang, Y., de Foy, B., Mei, X., Shang, J., and Feng, C.: Competing PM2.5 and NO2 holiday effects in the Beijing area vary locally due to differences in residential coal burning and traffic patterns, Sci. Total Environ., 750, 141575, https://doi.org/10.1016/j.scitotenv.2020.141575, 2021.
Huang, X., Ding, A., Gao, J., Zheng, B., Zhou, D., Qi, X., Tang, R., Wang, J., Ren, C., Nie, W., Chi, X., Xu, Z., Chen, L., Li, Y., Che, F., Pang, N., Wang, H., Tong, D., Qin, W., Cheng, W., Liu, W., Fu, Q., Liu, B., Chai, F., Davis, S. J., Zhang, Q., and He, K.: Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China, Natl. Sci. Rev., 8, 137, https://doi.org/10.1093/nsr/nwaa137, 2020.
Iriti, M., Piscitelli, P., Missoni, E., and Miani, A.: Air Pollution and Health: The Need for a Medical Reading of Environmental Monitoring Data, Int. J. Env. Res. Pub. He., 17, 2174, https://doi.org/10.3390/ijerph17072174, 2020.
Jacob, D. J. and Winner, D. A.: Effect of climate change on air quality, Atmos. Environ., 43, 51–63, https://doi.org/10.1016/j.atmosenv.2008.09.051, 2009.
Jhun, I., Coull, B. A., Schwartz, J., Hubbell, B., and Koutrakis, P.: The impact of weather changes on air quality and health in the United States in 1994–2012, Environ. Res. Lett., 10, 084009, https://doi.org/10.1088/1748-9326/10/8/084009, 2015.
Jiang, Q., Sun, Y. L., Wang, Z., and Yin, Y.: Aerosol composition and sources during the Chinese Spring Festival: fireworks, secondary aerosol, and holiday effects, Atmos. Chem. Phys., 15, 6023–6034, https://doi.org/10.5194/acp-15-6023-2015, 2015.
Joly, M. and Peuch, V.-H.: Objective classification of air quality monitoring sites over Europe, Atmos. Environ., 47, 111–123, https://doi.org/10.1016/j.atmosenv.2011.11.025, 2012.
Karl, M., Bieser, J., Geyer, B., Matthias, V., Jalkanen, J.-P., Johansson, L., and Fridell, E.: Impact of a nitrogen emission control area (NECA) on the future air quality and nitrogen deposition to seawater in the Baltic Sea region, Atmos. Chem. Phys., 19, 1721–1752, https://doi.org/10.5194/acp-19-1721-2019, 2019.
Khalil, M. A. K., Butenhoff, C. L., Porter, W. C., Almazroui, M., Alkhalaf, A., and Al-Sahafi, M. S.: Air quality in Yanbu, Saudi Arabia, J. Air Waste Ma., 66, 341–355, https://doi.org/10.1080/10962247.2015.1129999, 2016.
Khezri, B., Chan, Y. Y., Tiong, L. Y. D., and Webster, R. D.: Annual air pollution caused by the Hungry Ghost Festival, Environ. Sci.-Proc. Imp., 17, 1578–1586, https://doi.org/10.1039/C5EM00312A, 2015.
Kouznetsov, R. and Sofiev, M.: A methodology for evaluation of vertical dispersion and dry deposition of atmospheric aerosols, J. Geophys. Res., 117, D01202, https://doi.org/10.1029/2011JD016366, 2012.
Kouznetsov, R., Sofiev, M., Vira, J., and Stiller, G.: Simulating age of air and the distribution of SF6 in the stratosphere with the SILAM model, Atmos. Chem. Phys., 20, 5837–5859, https://doi.org/10.5194/acp-20-5837-2020, 2020.
Kukkonen, J., López-Aparicio, S., Segersson, D., Geels, C., Kangas, L., Kauhaniemi, M., Maragkidou, A., Jensen, A., Assmuth, T., Karppinen, A., Sofiev, M., Hellén, H., Riikonen, K., Nikmo, J., Kousa, A., Niemi, J. V., Karvosenoja, N., Santos, G. S., Sundvor, I., Im, U., Christensen, J. H., Nielsen, O.-K., Plejdrup, M. S., Nøjgaard, J. K., Omstedt, G., Andersson, C., Forsberg, B., and Brandt, J.: The influence of residential wood combustion on the concentrations of PM2.5 in four Nordic cities, Atmos. Chem. Phys., 20, 4333–4365, https://doi.org/10.5194/acp-20-4333-2020, 2020.
Lai, Y. and Brimblecombe, P.: Regulatory effects on particulate pollution in the early hours of Chinese New Year, 2015, Environ. Monit. Assess., 189, 467, https://doi.org/10.1007/s10661-017-6167-0, 2017.
Lehtomäki, H., Korhonen, A., Asikainen, A., Karvosenoja, N., Kupiainen, K., Paunu, V.-V., Savolahti, M., Sofiev, M., Palamarchuk, Y., Karppinen, A., Kukkonen, J., and Hänninen, O.: Health impacts of ambient air pollution in Finland, Int. J. Env. Res. Pub. He., 15, 736, https://doi.org/10.3390/ijerph15040736, 2018.
Lonati, G., Giugliano, M., and Cernuschi, S.: The role of traffic emissions from weekends' and weekdays' fine PM data in Milan, Atmos. Environ., 40, 5998–6011, https://doi.org/10.1016/j.atmosenv.2005.12.033, 2006.
McGraw, J., Haas, P., Young, L., and Evens, A.: Greenhouse gas emissions in Chicago: Emissions inventories and reduction strategies for Chicago and its metropolitan region, J. Great Lakes Res., 36, 106–114, https://doi.org/10.1016/j.jglr.2009.11.010, 2010.
Menut, L., Goussebaile, A., Bessagnet, B., Khvorostiyanov, D., and Ung, A.: Impact of realistic hourly emissions profiles on air pollutants concentrations modelled with CHIMERE, Atmos. Environ., 49, 233–244, https://doi.org/10.1016/j.atmosenv.2011.11.057, 2012.
Menut, L., Bessagnet, B., Siour, G., Mailler, S., Pennel, R., and Cholakian, A.: Impact of lockdown measures to combat Covid-19 on air quality over western Europe, Sci. Total Environ., 741, 140426–140426, https://doi.org/10.1016/j.scitotenv.2020.140426, 2020.
Mues, A., Kuenen, J., Hendriks, C., Manders, A., Segers, A., Scholz, Y., Hueglin, C., Builtjes, P., and Schaap, M.: Sensitivity of air pollution simulations with LOTOS-EUROS to the temporal distribution of anthropogenic emissions, Atmos. Chem. Phys., 14, 939–955, https://doi.org/10.5194/acp-14-939-2014, 2014.
Nodehi, R. N., Hashemi, S. Y., and Azimi, F.: The effect of national events and holidays on ambient PM2.5 concentrations, Journal of Air Pollution and Health, 3, 109–118, 2018.
Parra, R. and Franco, E.: Identifying the Ozone Weekend Effect in the air quality of the northern Andean region of Ecuador, WIT Trans. Ecol. Environ., 207, 169–180, 2016.
Petersen, A. K., Brasseur, G. P., Bouarar, I., Flemming, J., Gauss, M., Jiang, F., Kouznetsov, R., Kranenburg, R., Mijling, B., Peuch, V.-H., Pommier, M., Segers, A., Sofiev, M., Timmermans, R., van der A, R., Walters, S., Xie, Y., Xu, J., and Zhou, G.: Ensemble forecasts of air quality in eastern China – Part 2: Evaluation of the MarcoPolo–Panda prediction system, version 1, Geosci. Model Dev., 12, 1241–1266, https://doi.org/10.5194/gmd-12-1241-2019, 2019.
Poupkou, A., Giannaros, T., Markakis, K., Kioutsioukis, I., Curci, G., Melas, D., and Zerefos, C.: A model for European Biogenic Volatile Organic Compound emissions: Software development and first validation, Environ. Modell. Softw., 25, 1845–1856, https://doi.org/10.1016/j.envsoft.2010.05.004, 2010.
Retama, A., Neria-Hernández, A., Jaimes-Palomera, M., Rivera-Hernández, O., Sánchez-Rodríguez, M., López-Medina, A., and Velasco, E.: Fireworks: A major source of inorganic and organic aerosols during Christmas and New Year in Mexico city, Atmospheric Environment: X, 2, 100013, https://doi.org/10.1016/j.aeaoa.2019.100013, 2019.
rkouznetsov: fmidev/silam-model: Release to get DOI, v5_7pub_1, Zenodo [code], https://doi.org/10.5281/zenodo.5713863, 2021 (data available at: https://github.com/fmidev/silam-model, last access: 22 November 2021).
Rozbicka, K. and Rozbicki, T.: The “Weekend Effect” on Ozone in the Warsaw Conurbation, Poland, Pol. J. Environ. Stud., 25, 1675–1683, https://doi.org/10.15244/pjoes/61815, 2016.
Sharma, S., Zhang, M., Anshika, Gao, J., Zhang, H., and Kota, S. H.: Effect of restricted emissions during COVID-19 on air quality in India, Sci. Total Environ., 728, 138878, https://doi.org/10.1016/j.scitotenv.2020.138878, 2020.
Shi, C., Wu, H., and Chiu, Y.-H.: The Dynamic Analysis of the Pollutant Emissions Impact on Human Health in China Industries Based on the Meta-Frontier DEA, Healthcare, 8, 5, https://doi.org/10.3390/healthcare8010005, 2019.
Singh, A., Pant, P., and Pope, F. D.: Air quality during and after festivals: Aerosol concentrations, composition and health effects, Atmos. Res., 227, 220–232, https://doi.org/10.1016/j.atmosres.2019.05.012, 2019.
Singh, K. P., Gupta, S., and Rai, P.: Identifying pollution sources and predicting urban air quality using ensemble learning methods, Atmos. Environ., 80, 426–437, https://doi.org/10.1016/j.atmosenv.2013.08.023, 2013.
Sofiev, M.: A model for the evaluation of long-term airborne pollution transport at regional and continental scales, Atmos. Environ., 34, 2481–2493, 2000.
Sofiev, M.: Extended resistance analogy for construction of the vertical diffusion scheme for dispersion models, J. Geophys. Res., 107, ACH 10-1–ACH 10-8, https://doi.org/10.1029/2001JD001233, 2002.
Sofiev, M.: On possibilities of assimilation of near-real-time pollen data by atmospheric composition models, Aerobiologia 35, 523–531, https://doi.org/10.1007/s10453-019-09583-1, 2019.
Sofiev, M., Siljamo, P., Valkama, I., Ilvonen, M., and Kukkonen, J.: A dispersion modelling system SILAM and its evaluation against ETEX data, Atmos. Environ., 40, 674–685, https://doi.org/10.1016/j.atmosenv.2005.09.069, 2006.
Sofiev, M., Genikhovich, E., Keronen, P., and Vesala, T.: Diagnosing the Surface Layer Parameters for Dispersion Models within the Meteorological-to-Dispersion Modeling Interface, J. Appl. Meteorol. Clim., 49, 221–233, https://doi.org/10.1175/2009JAMC2210.1, 2010.
Sofiev, M., Soares, J., Prank, M., de Leeuw, G., and Kukkonen, J.: A regional-to-global model of emission and transport of sea salt particles in the atmosphere, J. Geophys. Res., 116, D21302, https://doi.org/10.1029/2010JD014713, 2011.
Sofiev, M., Vira, J., Kouznetsov, R., Prank, M., Soares, J., and Genikhovich, E.: Construction of the SILAM Eulerian atmospheric dispersion model based on the advection algorithm of Michael Galperin, Geosci. Model Dev., 8, 3497–3522, https://doi.org/10.5194/gmd-8-3497-2015, 2015a.
Sofiev, M., Berger, U., Prank, M., Vira, J., Arteta, J., Belmonte, J., Bergmann, K.-C., Chéroux, F., Elbern, H., Friese, E., Galan, C., Gehrig, R., Khvorostyanov, D., Kranenburg, R., Kumar, U., Marécal, V., Meleux, F., Menut, L., Pessi, A.-M., Robertson, L., Ritenberga, O., Rodinkova, V., Saarto, A., Segers, A., Severova, E., Sauliene, I., Siljamo, P., Steensen, B. M., Teinemaa, E., Thibaudon, M., and Peuch, V.-H.: MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe, Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015, 2015b.
Sofiev, M., Kouznetsov, R., Hänninen, R., and Sofieva, V. F.: Technical note: Intermittent reduction of the stratospheric ozone over northern Europe caused by a storm in the Atlantic Ocean, Atmos. Chem. Phys., 20, 1839–1847, https://doi.org/10.5194/acp-20-1839-2020, 2020.
Vira, J. and Sofiev, M.: On variational data assimilation for estimating the model initial conditions and emission fluxes for short-term forecasting of SOx concentrations, Atmos. Environ., 46, 318–328, https://doi.org/10.1016/j.atmosenv.2011.09.066, 2012.
Wang, Q. and Su, M.: A preliminary assessment of the impact of COVID-19 on environment – A case study of China, Sci. Total Environ., 728, 138915, https://doi.org/10.1016/j.scitotenv.2020.138915, 2020.
Wesely, M. L.: Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models, Atmos. Environ., 23, 1293–1304, 1989.
Xian, P., Reid, J. S., Hyer, E. J., Sampson, C. R., Rubin, J. I., Ades, M., Asencio, N., Basart, S., Benedetti, A., Bhattacharjee, P. S., Brooks, M. E., Colarco, P. R., da Silva, A. M., Eck, T. F., Guth, J., Jorba, O., Kouznetsov, R., Kipling, Z., Sofiev, M., Perez Garcia-Pando, C., Pradhan, Y., Tanaka, T., Wang, J., Westphal, D. L., Yumimoto, K., and Zhang, J.: Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP), Q. J. Roy. Meteor. Soc., 145, 176–209, https://doi.org/10.1002/qj.3497, 2019.
Xu, Z., Huang, X., Nie, W., Chi, X., Xu, Z., Zheng, L., Sun, P., and Ding, A.: Influence of synoptic condition and holiday effects on VOCs and ozone production in the Yangtze River Delta region, China, Atmos. Environ., 168, 112–124, https://doi.org/10.1016/j.atmosenv.2017.08.035, 2017.
Yao, L., Wang, D., Fu, Q., Qiao, L., Wang, H., Li, L., Sun, W., Li, Q., Wang, L., Yang, X., Zhao, Z., Kan, H., Xian, A., Wang, G., Xiao, H., and Chen, J.: The effects of firework regulation on air quality and public health during the Chinese Spring Festival from 2013 to 2017 in a Chinese megacity, Environ. Int., 126, 96–106, https://doi.org/10.1016/j.envint.2019.01.037, 2019.
Yarwood, G., Rao, S., Yocke, M., and Whitten, G. Z.: Updates to the carbon bond chemical mechanism: CB05, Final report to the U.S. Environmental Protection Agency, RT-0400675, 2005.
Ye, C., Chen, R., and Chen, M.: The impacts of Chinese Nian culture on air pollution, J. Clean. Prod., 112, 1740–1745, https://doi.org/10.1016/j.jclepro.2015.04.113, 2016.
Zhao, Y., Qiu, L. P., Xu, R. Y., Xie, F. J., Zhang, Q., Yu, Y. Y., Nielsen, C. P., Qin, H. X., Wang, H. K., Wu, X. C., Li, W. Q., and Zhang, J.: Advantages of a city-scale emission inventory for urban air quality research and policy: the case of Nanjing, a typical industrial city in the Yangtze River Delta, China, Atmos. Chem. Phys., 15, 12623–12644, https://doi.org/10.5194/acp-15-12623-2015, 2015.
Zhou, M., Jiang, W., Gao, W., Zhou, B., and Liao, X.: A high spatiotemporal resolution anthropogenic VOC emission inventory for Qingdao City in 2016 and its ozone formation potential analysis, Process Saf. Environ., 139, 147–160, https://doi.org/10.1016/j.psep.2020.03.040, 2020.
Zou, Y., Charlesworth, E., Yin, C. Q., Yan, X. L., Deng, X. J., and Li, F.: The weekday/weekend ozone differences induced by the emissions change during summer and autumn in Guangzhou, China, Atmos. Environ., 199, 114–126, https://doi.org/10.1016/j.atmosenv.2018.11.019, 2019.
Short summary
Incorporating information on public holidays into anthropogenic sector emissions results in substantial short-term improvement of the chemistry transport model SILAM scores. The largest impact was found for NOx, which is controlled by the changes in the traffic intensity. Certain improvements were also found for other species, but the signal was weaker than that for NOx.
Incorporating information on public holidays into anthropogenic sector emissions results in...
