Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-7257-2022
© Author(s) 2022. 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-15-7257-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
29 Sep 2022
Model description paper |
| 29 Sep 2022
| 29 Sep 2022
Atmospherically Relevant Chemistry and Aerosol box model – ARCA box (version 1.2)
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
Carlton Xavier
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
Lukas Pichelstorfer
Department of Chemistry and Physics of Materials, University of Salzburg, 5020, Salzburg, Austria
Putian Zhou
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
Tinja Olenius
Research Department, Unit of Meteorology/Environment and Climate,
Swedish Meteorological and Hydrological Institute (SMHI), 601 76 Norrköping, Sweden
Pontus Roldin
Division of Nuclear Physics, Department of Physics, Lund University, P.O. Box 118, 221 00 Lund, Sweden
Michael Boy
Institute for Atmospheric and Earth Systems Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
LUT School of Engineering Science, Lappeenranta-Lahti University of Technology, P.O. Box 20, 53851 Lappeenranta, Finland
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Petri Clusius, Metin Baykara, Carlton Xavier, Putian Zhou, Juniper Tyree, Benjamin Foreback, Mikko Äijälä, Frans Graeffe, Tuukka Petäjä, Markku Kulmala, Pauli Paasonen, Paul I. Palmer, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2025-39, https://doi.org/10.5194/egusphere-2025-39, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Cloud condensation nuclei are necessary to form clouds, and their size distribution affects cloud properties and therefore Earth’s energy budget. This study modelled the origins of cloud condensation nuclei at SMEAR II, Hyytiälä, Finland, and found that primary emissions and new particle formation separately contribute to more than half of the condensation nuclei, but they suppress each other, leading to current concentrations. Largest condensation nuclei originated mostly from emissions.
Lukas Pichelstorfer, Pontus Roldin, Matti Rissanen, Noora Hyttinen, Olga Garmash, Carlton Xavier, Putian Zhou, Petri Clusius, Benjamin Foreback, Thomas Golin Almeida, Chenjuan Deng, Metin Baykara, Theo Kurten, and Michael Boy
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Secondary organic aerosols (SOA) form effectively from gaseous precursors via a process called autoxidation. While key chemical reaction types seem to be known, no general description of autoxidation chemistry exists. In the present work, we present a method to create autoxidation chemistry schemes for any atmospherically relevant hydrocarbon. We exemplarily investigate benzene and its potential to form aerosols. We found that autoxidation, under some conditions, can dominate the SOA formation.
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
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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.
Carlton Xavier, Metin Baykara, Robin Wollesen de Jonge, Barbara Altstädter, Petri Clusius, Ville Vakkari, Roseline Thakur, Lisa Beck, Silvia Becagli, Mirko Severi, Rita Traversi, Radovan Krejci, Peter Tunved, Mauro Mazzola, Birgit Wehner, Mikko Sipilä, Markku Kulmala, Michael Boy, and Pontus Roldin
Atmos. Chem. Phys., 22, 10023–10043, https://doi.org/10.5194/acp-22-10023-2022, https://doi.org/10.5194/acp-22-10023-2022, 2022
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The focus of this work is to study and improve our understanding of processes involved in the formation and growth of new particles in a remote Arctic marine environment. We run the 1D model ADCHEM along air mass trajectories arriving at Ny-Ålesund in May 2018. The model finds that ion-mediated H2SO4–NH3 nucleation can explain the observed new particle formation at Ny-Ålesund. The growth of particles is driven via H2SO4 condensation and formation of methane sulfonic acid in the aqueous phase.
Dean Chen, Putian Zhou, Tuomo Nieminen, Pontus Roldin, Ximeng Qi, Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Markku Kulmala, Pekka Rantala, Juho Aalto, Nina Sarnela, Pasi Kolari, Petri Keronen, Matti P. Rissanen, Metin Baykara, and Michael Boy
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-128, https://doi.org/10.5194/acp-2020-128, 2020
Preprint withdrawn
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Atmospheric oxidants OH, O3 and NO3 dominate the atmospheric oxidation capacity, and sulfuric acid (H2SO4) is considered as a main driver for new particle formation events. We studied how the trends of these atmospheric oxidants and H2SO4 changed in southern Finland during the past 12 years and discussed how these trends related to decreasing emissions of air pollutants in Europe. Our results showed that OH increased by 1.56 % yr−1 at daytime and NO3 decreased by 3.92 % yr−1 at nighttime.
Yunfeng He, Xiang Ding, Quanfu He, Yuqing Zhang, Duohong Chen, Tao Zhang, Kong Yang, Junqi Wang, Qian Cheng, Hao Jiang, Zirui Wang, Ping Liu, Xinming Wang, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2025-2204, https://doi.org/10.5194/egusphere-2025-2204, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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The long-term field measurements in the Pearl River Delta revealed a significant decline in PM2.5 main components. As air quality improved, secondary species became more dominant. In addition, the proportion of nitrate had doubled. The changes in chemical composition led to the reductions in aerosol acidity, liquid water content and light extinction coefficient. Our results help to improve understanding of the secondary species formation under decreasing anthropogenic emissions.
Xinyang Li, Tuomo Nieminen, Rima Baalbaki, Putian Zhou, Pauli Paasonen, Risto Makkonen, Martha Arbayani Zaidan, Nina Sarnela, Chao Yan, Tuija Jokinen, Imre Salma, Máté Vörösmarty, Tuukka Petäjä, Veli-Matti Kerminen, Markku Kulmala, and Lubna Dada
Aerosol Research, 3, 271–291, https://doi.org/10.5194/ar-3-271-2025, https://doi.org/10.5194/ar-3-271-2025, 2025
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Particle formation rate is one of the key factors in studying the physical properties of aerosols. By developing powerful and simple semi-empirical particle formation rate models, we can predict particle formation rates and compare them with real-time measurements to aid in discovering hidden particle formation mechanisms as well as global simulations of particle population to fill the knowledge gap caused by the uncertainty in aerosol cooling effects on Earth's atmosphere.
Petri Clusius, Metin Baykara, Carlton Xavier, Putian Zhou, Juniper Tyree, Benjamin Foreback, Mikko Äijälä, Frans Graeffe, Tuukka Petäjä, Markku Kulmala, Pauli Paasonen, Paul I. Palmer, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2025-39, https://doi.org/10.5194/egusphere-2025-39, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Cloud condensation nuclei are necessary to form clouds, and their size distribution affects cloud properties and therefore Earth’s energy budget. This study modelled the origins of cloud condensation nuclei at SMEAR II, Hyytiälä, Finland, and found that primary emissions and new particle formation separately contribute to more than half of the condensation nuclei, but they suppress each other, leading to current concentrations. Largest condensation nuclei originated mostly from emissions.
Carl Svenhag, Pontus Roldin, Tinja Olenius, Robin Wollesen de Jonge, Sara Blichner, Daniel Yazgi, and Moa Sporre
EGUsphere, https://doi.org/10.5194/egusphere-2024-3626, https://doi.org/10.5194/egusphere-2024-3626, 2024
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This study investigates the model representation of how particles are formed and grow in the atmosphere. Using modeled and observed data from two boreal forest stations in 2018, we identify key factors for NPF to improve particle-climate predictions in the global EC-Earth3 model. Comparisons with the detailed ADCHEM model show that adding ammonia improves particle growth predictions, though EC-Earth3 still highly underestimates the number of particles during warmer months.
Steven Turnock, Dimitris Akritidis, Larry Horowitz, Mariano Mertens, Andrea Pozzer, Carly Reddington, Hantao Wang, Putian Zhou, and Fiona O'Connor
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We assess the drivers behind changes in peak season surface zone concentrations and risk to human health between 1850 and 2014. Substantial increases in surface ozone have occurred over this period resulting in a significant increase in the risk to human health, mainly driven by increases in anthropogenic NOx emissions and global CH4 concentrations. Fixing anthropogenic NOx emissions at 1850 values in the near present-day period can eliminate the risk to human health.
Zoé Brasseur, Julia Schneider, Janne Lampilahti, Ville Vakkari, Victoria A. Sinclair, Christina J. Williamson, Carlton Xavier, Dmitri Moisseev, Markus Hartmann, Pyry Poutanen, Markus Lampimäki, Markku Kulmala, Tuukka Petäjä, Katrianne Lehtipalo, Erik S. Thomson, Kristina Höhler, Ottmar Möhler, and Jonathan Duplissy
Atmos. Chem. Phys., 24, 11305–11332, https://doi.org/10.5194/acp-24-11305-2024, https://doi.org/10.5194/acp-24-11305-2024, 2024
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Ice-nucleating particles (INPs) strongly influence the formation of clouds by initiating the formation of ice crystals. However, very little is known about the vertical distribution of INPs in the atmosphere. Here, we present aircraft measurements of INP concentrations above the Finnish boreal forest. Results show that near-surface INPs are efficiently transported and mixed within the boundary layer and occasionally reach the free troposphere.
Yuanyuan Luo, Ditte Thomsen, Emil Mark Iversen, Pontus Roldin, Jane Tygesen Skønager, Linjie Li, Michael Priestley, Henrik B. Pedersen, Mattias Hallquist, Merete Bilde, Marianne Glasius, and Mikael Ehn
Atmos. Chem. Phys., 24, 9459–9473, https://doi.org/10.5194/acp-24-9459-2024, https://doi.org/10.5194/acp-24-9459-2024, 2024
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∆3-carene is abundantly emitted from vegetation, but its atmospheric oxidation chemistry has received limited attention. We explored highly oxygenated organic molecule (HOM) formation from ∆3-carene ozonolysis in chambers and investigated the impact of temperature and relative humidity on HOM formation. Our findings provide new insights into ∆3-carene oxidation pathways and their potential to impact atmospheric aerosols.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Fredrik Lagergren, Robert G. Björk, Camilla Andersson, Danijel Belušić, Mats P. Björkman, Erik Kjellström, Petter Lind, David Lindstedt, Tinja Olenius, Håkan Pleijel, Gunhild Rosqvist, and Paul A. Miller
Biogeosciences, 21, 1093–1116, https://doi.org/10.5194/bg-21-1093-2024, https://doi.org/10.5194/bg-21-1093-2024, 2024
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The Fennoscandian boreal and mountain regions harbour a wide range of ecosystems sensitive to climate change. A new, highly resolved high-emission climate scenario enabled modelling of the vegetation development in this region at high resolution for the 21st century. The results show dramatic south to north and low- to high-altitude shifts of vegetation zones, especially for the open tundra environments, which will have large implications for nature conservation, reindeer husbandry and forestry.
Putian Zhou, Zhengyao Lu, Jukka-Pekka Keskinen, Qiong Zhang, Juha Lento, Jianpu Bian, Twan van Noije, Philippe Le Sager, Veli-Matti Kerminen, Markku Kulmala, Michael Boy, and Risto Makkonen
Clim. Past, 19, 2445–2462, https://doi.org/10.5194/cp-19-2445-2023, https://doi.org/10.5194/cp-19-2445-2023, 2023
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A Green Sahara with enhanced rainfall and larger vegetation cover existed in northern Africa about 6000 years ago. Biosphere–atmosphere interactions are found to be critical to explaining this wet period. Based on modeled vegetation reconstruction data, we simulated dust emissions and aerosol formation, which are key factors in biosphere–atmosphere interactions. Our results also provide a benchmark of aerosol climatology for future paleo-climate simulation experiments.
Daniel Yazgi and Tinja Olenius
Geosci. Model Dev., 16, 5237–5249, https://doi.org/10.5194/gmd-16-5237-2023, https://doi.org/10.5194/gmd-16-5237-2023, 2023
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We present flexible tools to implement aerosol formation rate predictions in climate and chemical transport models. New-particle formation is a significant but uncertain factor affecting aerosol numbers and an active field within molecular modeling which provides data for assessing formation rates for different chemical species. We introduce tools to generate and interpolate formation rate lookup tables for user-defined data, thus enabling the easy inclusion and testing of formation schemes.
Lukas Pichelstorfer, Pontus Roldin, Matti Rissanen, Noora Hyttinen, Olga Garmash, Carlton Xavier, Putian Zhou, Petri Clusius, Benjamin Foreback, Thomas Golin Almeida, Chenjuan Deng, Metin Baykara, Theo Kurten, and Michael Boy
EGUsphere, https://doi.org/10.5194/egusphere-2023-1415, https://doi.org/10.5194/egusphere-2023-1415, 2023
Preprint archived
Short summary
Short summary
Secondary organic aerosols (SOA) form effectively from gaseous precursors via a process called autoxidation. While key chemical reaction types seem to be known, no general description of autoxidation chemistry exists. In the present work, we present a method to create autoxidation chemistry schemes for any atmospherically relevant hydrocarbon. We exemplarily investigate benzene and its potential to form aerosols. We found that autoxidation, under some conditions, can dominate the SOA formation.
Erik Ahlberg, Stina Ausmeel, Lovisa Nilsson, Mårten Spanne, Julija Pauraite, Jacob Klenø Nøjgaard, Michele Bertò, Henrik Skov, Pontus Roldin, Adam Kristensson, Erik Swietlicki, and Axel Eriksson
Atmos. Chem. Phys., 23, 3051–3064, https://doi.org/10.5194/acp-23-3051-2023, https://doi.org/10.5194/acp-23-3051-2023, 2023
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To investigate the properties and origin of black carbon particles in southern Sweden during late summer, we performed measurements both at a rural site and the nearby city of Malmö. We found that local traffic emissions of black carbon led to concentrations around twice as high as those at the rural site. Modeling show that these emissions are not clearly distinguishable at the rural site, unless meteorology was favourable, which shows the importance of long-range transport and processing.
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
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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.
Carlton Xavier, Metin Baykara, Robin Wollesen de Jonge, Barbara Altstädter, Petri Clusius, Ville Vakkari, Roseline Thakur, Lisa Beck, Silvia Becagli, Mirko Severi, Rita Traversi, Radovan Krejci, Peter Tunved, Mauro Mazzola, Birgit Wehner, Mikko Sipilä, Markku Kulmala, Michael Boy, and Pontus Roldin
Atmos. Chem. Phys., 22, 10023–10043, https://doi.org/10.5194/acp-22-10023-2022, https://doi.org/10.5194/acp-22-10023-2022, 2022
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The focus of this work is to study and improve our understanding of processes involved in the formation and growth of new particles in a remote Arctic marine environment. We run the 1D model ADCHEM along air mass trajectories arriving at Ny-Ålesund in May 2018. The model finds that ion-mediated H2SO4–NH3 nucleation can explain the observed new particle formation at Ny-Ålesund. The growth of particles is driven via H2SO4 condensation and formation of methane sulfonic acid in the aqueous phase.
Roseline C. Thakur, Lubna Dada, Lisa J. Beck, Lauriane L. J. Quéléver, Tommy Chan, Marjan Marbouti, Xu-Cheng He, Carlton Xavier, Juha Sulo, Janne Lampilahti, Markus Lampimäki, Yee Jun Tham, Nina Sarnela, Katrianne Lehtipalo, Alf Norkko, Markku Kulmala, Mikko Sipilä, and Tuija Jokinen
Atmos. Chem. Phys., 22, 6365–6391, https://doi.org/10.5194/acp-22-6365-2022, https://doi.org/10.5194/acp-22-6365-2022, 2022
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Every year intense cyanobacterial and macroalgal blooms occur in the Baltic Sea and in the coastal areas surrounding Helsinki, yet no studies have addressed the impact of biogenic emissions from these blooms on gas vapor concentrations, which in turn could influence new particle formation. This is the first study of its kind to address the chemistry driving new particle formation (NPF) during a bloom period in this region, highlighting the role of biogenic sulfuric acid and iodic acid.
Hanna K. Lappalainen, Tuukka Petäjä, Timo Vihma, Jouni Räisänen, Alexander Baklanov, Sergey Chalov, Igor Esau, Ekaterina Ezhova, Matti Leppäranta, Dmitry Pozdnyakov, Jukka Pumpanen, Meinrat O. Andreae, Mikhail Arshinov, Eija Asmi, Jianhui Bai, Igor Bashmachnikov, Boris Belan, Federico Bianchi, Boris Biskaborn, Michael Boy, Jaana Bäck, Bin Cheng, Natalia Chubarova, Jonathan Duplissy, Egor Dyukarev, Konstantinos Eleftheriadis, Martin Forsius, Martin Heimann, Sirkku Juhola, Vladimir Konovalov, Igor Konovalov, Pavel Konstantinov, Kajar Köster, Elena Lapshina, Anna Lintunen, Alexander Mahura, Risto Makkonen, Svetlana Malkhazova, Ivan Mammarella, Stefano Mammola, Stephany Buenrostro Mazon, Outi Meinander, Eugene Mikhailov, Victoria Miles, Stanislav Myslenkov, Dmitry Orlov, Jean-Daniel Paris, Roberta Pirazzini, Olga Popovicheva, Jouni Pulliainen, Kimmo Rautiainen, Torsten Sachs, Vladimir Shevchenko, Andrey Skorokhod, Andreas Stohl, Elli Suhonen, Erik S. Thomson, Marina Tsidilina, Veli-Pekka Tynkkynen, Petteri Uotila, Aki Virkkula, Nadezhda Voropay, Tobias Wolf, Sayaka Yasunaka, Jiahua Zhang, Yubao Qiu, Aijun Ding, Huadong Guo, Valery Bondur, Nikolay Kasimov, Sergej Zilitinkevich, Veli-Matti Kerminen, and Markku Kulmala
Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Zhuohui Lin, Yonghong Wang, Feixue Zheng, Ying Zhou, Yishuo Guo, Zemin Feng, Chang Li, Yusheng Zhang, Simo Hakala, Tommy Chan, Chao Yan, Kaspar R. Daellenbach, Biwu Chu, Lubna Dada, Juha Kangasluoma, Lei Yao, Xiaolong Fan, Wei Du, Jing Cai, Runlong Cai, Tom V. Kokkonen, Putian Zhou, Lili Wang, Tuukka Petäjä, Federico Bianchi, Veli-Matti Kerminen, Yongchun Liu, and Markku Kulmala
Atmos. Chem. Phys., 21, 12173–12187, https://doi.org/10.5194/acp-21-12173-2021, https://doi.org/10.5194/acp-21-12173-2021, 2021
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We find that ammonium nitrate and aerosol water content contributed most during low mixing layer height conditions; this may further trigger enhanced formation of sulfate and organic aerosol via heterogeneous reactions. The results of this study contribute towards a more detailed understanding of the aerosol–chemistry–radiation–boundary layer feedback that is likely to be responsible for explosive aerosol mass growth events in urban Beijing.
Robin Wollesen de Jonge, Jonas Elm, Bernadette Rosati, Sigurd Christiansen, Noora Hyttinen, Dana Lüdemann, Merete Bilde, and Pontus Roldin
Atmos. Chem. Phys., 21, 9955–9976, https://doi.org/10.5194/acp-21-9955-2021, https://doi.org/10.5194/acp-21-9955-2021, 2021
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This study presents a detailed analysis of the OH-initiated oxidation of dimethyl sulfide (DMS) based on experiments performed in the Aarhus University Research on Aerosol (AURA) smog chamber and the gas- and particle-phase chemistry kinetic multilayer model (ADCHAM). We capture the formation, growth and chemical composition of aerosols in the chamber setup by an improved multiphase oxidation mechanism and utilize our results to reproduce the important role of DMS in the marine boundary layer.
Anna Shcherbacheva, Tracey Balehowsky, Jakub Kubečka, Tinja Olenius, Tapio Helin, Heikki Haario, Marko Laine, Theo Kurtén, and Hanna Vehkamäki
Atmos. Chem. Phys., 20, 15867–15906, https://doi.org/10.5194/acp-20-15867-2020, https://doi.org/10.5194/acp-20-15867-2020, 2020
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Atmospheric new particle formation and cluster growth to aerosol particles is an important field of research, in particular due to the climate change phenomenon. Evaporation rates are very difficult to account for but they are important to explain the formation and growth of particles. Different quantum chemistry (QC) methods produce substantially different values for the evaporation rates. We propose a novel approach for inferring evaporation rates of clusters from available measurements.
Mona Kurppa, Pontus Roldin, Jani Strömberg, Anna Balling, Sasu Karttunen, Heino Kuuluvainen, Jarkko V. Niemi, Liisa Pirjola, Topi Rönkkö, Hilkka Timonen, Antti Hellsten, and Leena Järvi
Geosci. Model Dev., 13, 5663–5685, https://doi.org/10.5194/gmd-13-5663-2020, https://doi.org/10.5194/gmd-13-5663-2020, 2020
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High-resolution modelling is needed to solve the aerosol concentrations in a complex urban area. Here, the performance of an aerosol module within the PALM model to simulate the detailed horizontal and vertical distribution of aerosol particles is studied. Further, sensitivity to the meteorological and aerosol boundary conditions is assessed using both model and observation data. The horizontal distribution is sensitive to the wind speed and stability, and the vertical to the wind direction.
Yuan Yang, Yonghong Wang, Putian Zhou, Dan Yao, Dongsheng Ji, Jie Sun, Yinghong Wang, Shuman Zhao, Wei Huang, Shuanghong Yang, Dean Chen, Wenkang Gao, Zirui Liu, Bo Hu, Renjian Zhang, Limin Zeng, Maofa Ge, Tuukka Petäjä, Veli-Matti Kerminen, Markku Kulmala, and Yuesi Wang
Atmos. Chem. Phys., 20, 8181–8200, https://doi.org/10.5194/acp-20-8181-2020, https://doi.org/10.5194/acp-20-8181-2020, 2020
Dominik Stolzenburg, Mario Simon, Ananth Ranjithkumar, Andreas Kürten, Katrianne Lehtipalo, Hamish Gordon, Sebastian Ehrhart, Henning Finkenzeller, Lukas Pichelstorfer, Tuomo Nieminen, Xu-Cheng He, Sophia Brilke, Mao Xiao, António Amorim, Rima Baalbaki, Andrea Baccarini, Lisa Beck, Steffen Bräkling, Lucía Caudillo Murillo, Dexian Chen, Biwu Chu, Lubna Dada, António Dias, Josef Dommen, Jonathan Duplissy, Imad El Haddad, Lukas Fischer, Loic Gonzalez Carracedo, Martin Heinritzi, Changhyuk Kim, Theodore K. Koenig, Weimeng Kong, Houssni Lamkaddam, Chuan Ping Lee, Markus Leiminger, Zijun Li, Vladimir Makhmutov, Hanna E. Manninen, Guillaume Marie, Ruby Marten, Tatjana Müller, Wei Nie, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Maxim Philippov, Matti P. Rissanen, Birte Rörup, Siegfried Schobesberger, Simone Schuchmann, Jiali Shen, Mikko Sipilä, Gerhard Steiner, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Mingyi Wang, Yonghong Wang, Stefan K. Weber, Daniela Wimmer, Peter J. Wlasits, Yusheng Wu, Qing Ye, Marcel Zauner-Wieczorek, Urs Baltensperger, Kenneth S. Carslaw, Joachim Curtius, Neil M. Donahue, Richard C. Flagan, Armin Hansel, Markku Kulmala, Jos Lelieveld, Rainer Volkamer, Jasper Kirkby, and Paul M. Winkler
Atmos. Chem. Phys., 20, 7359–7372, https://doi.org/10.5194/acp-20-7359-2020, https://doi.org/10.5194/acp-20-7359-2020, 2020
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Sulfuric acid is a major atmospheric vapour for aerosol formation. If new particles grow fast enough, they can act as cloud droplet seeds or affect air quality. In a controlled laboratory set-up, we demonstrate that van der Waals forces enhance growth from sulfuric acid. We disentangle the effects of ammonia, ions and particle hydration, presenting a complete picture of sulfuric acid growth from molecular clusters onwards. In a climate model, we show its influence on the global aerosol budget.
Dean Chen, Putian Zhou, Tuomo Nieminen, Pontus Roldin, Ximeng Qi, Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Markku Kulmala, Pekka Rantala, Juho Aalto, Nina Sarnela, Pasi Kolari, Petri Keronen, Matti P. Rissanen, Metin Baykara, and Michael Boy
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-128, https://doi.org/10.5194/acp-2020-128, 2020
Preprint withdrawn
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Atmospheric oxidants OH, O3 and NO3 dominate the atmospheric oxidation capacity, and sulfuric acid (H2SO4) is considered as a main driver for new particle formation events. We studied how the trends of these atmospheric oxidants and H2SO4 changed in southern Finland during the past 12 years and discussed how these trends related to decreasing emissions of air pollutants in Europe. Our results showed that OH increased by 1.56 % yr−1 at daytime and NO3 decreased by 3.92 % yr−1 at nighttime.
Otso Peräkylä, Matthieu Riva, Liine Heikkinen, Lauriane Quéléver, Pontus Roldin, and Mikael Ehn
Atmos. Chem. Phys., 20, 649–669, https://doi.org/10.5194/acp-20-649-2020, https://doi.org/10.5194/acp-20-649-2020, 2020
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Highly oxygenated organic molecules have been suggested to form a large part of secondary organic aerosol. However, with their exotic structures, their volatilities are not well known, making their exact role in particle formation hard to assess. In laboratory experiments, we found the volatility of HOMs formed in the ozonolysis of the monoterpene alpha-pinene to be in the middle of earlier estimates. The volatilities of HOMs could be well explained in terms of their molecular formulae.
Yonghong Wang, Miao Yu, Yuesi Wang, Guiqian Tang, Tao Song, Putian Zhou, Zirui Liu, Bo Hu, Dongsheng Ji, Lili Wang, Xiaowan Zhu, Chao Yan, Mikael Ehn, Wenkang Gao, Yuepeng Pan, Jinyuan Xin, Yang Sun, Veli-Matti Kerminen, Markku Kulmala, and Tuukka Petäjä
Atmos. Chem. Phys., 20, 45–53, https://doi.org/10.5194/acp-20-45-2020, https://doi.org/10.5194/acp-20-45-2020, 2020
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We found a positive particle matter-mixing layer height feedback at three observation platforms at the 325 m Beijing meteorology tower, which is characterized by a shallower mixing layer height and a higher particle matter concentration. Measurements of solar radiation, aerosol chemical composition, meteorology parameters, trace gases and turbulent kinetic energy (TKE) could explain the feedback mechanism to some extent.
Arnaud P. Praplan, Toni Tykkä, Dean Chen, Michael Boy, Ditte Taipale, Ville Vakkari, Putian Zhou, Tuukka Petäjä, and Heidi Hellén
Atmos. Chem. Phys., 19, 14431–14453, https://doi.org/10.5194/acp-19-14431-2019, https://doi.org/10.5194/acp-19-14431-2019, 2019
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Our study shows that, despite our best efforts and recent progress, our knowledge of the chemical composition of the air under the canopy of a boreal forest still cannot be fully characterized. The discrepancy between the measured total reactivity of the air and the reactivity derived from the known chemical composition highlights the need to better understand the emissions from vegetation, but also other sources, such as the forest soil.
Carlton Xavier, Anton Rusanen, Putian Zhou, Chen Dean, Lukas Pichelstorfer, Pontus Roldin, and Michael Boy
Atmos. Chem. Phys., 19, 13741–13758, https://doi.org/10.5194/acp-19-13741-2019, https://doi.org/10.5194/acp-19-13741-2019, 2019
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Master Chemical Mechanism (MCM) coupled to peroxy radical autoxidation mechanism (PRAM) was used to simulate secondary organic aerosol mass loadings from oxidation of five selected biogenic volatile organic compounds. The simulations were designed to replicate idealized chamber and oxidative flow-tube setups. The mass yields using MCM + PRAM are in good agreement with the experimental yields, thereby allowing us to highlight a few important compounds which contribute to > 95 % of mass loadings.
Nanna Myllys, Jakub Kubečka, Vitus Besel, Dina Alfaouri, Tinja Olenius, James Norman Smith, and Monica Passananti
Atmos. Chem. Phys., 19, 9753–9768, https://doi.org/10.5194/acp-19-9753-2019, https://doi.org/10.5194/acp-19-9753-2019, 2019
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In atmospheric sulfuric-acid-driven particle formation, bases are able to stabilize the initial molecular clusters and thus enhance particle formation. We have investigated the enhancing potential of different bases in atmospheric particle formation. We show that strong bases with low abundance are likely to dominate electrically neutral particle formation, whereas weak bases with high abundance have a larger role in ion-mediated particle formation.
Lauriane L. J. Quéléver, Kasper Kristensen, Louise Normann Jensen, Bernadette Rosati, Ricky Teiwes, Kaspar R. Daellenbach, Otso Peräkylä, Pontus Roldin, Rossana Bossi, Henrik B. Pedersen, Marianne Glasius, Merete Bilde, and Mikael Ehn
Atmos. Chem. Phys., 19, 7609–7625, https://doi.org/10.5194/acp-19-7609-2019, https://doi.org/10.5194/acp-19-7609-2019, 2019
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Highly oxygenated organic molecules (HOMs) form rapidly in oxidation of monoterpenes and have been shown to be crucial for secondary organic aerosol formation. We studied the formation of HOMs under different temperatures, finding a strong dependence on their yields. As temperatures decrease, the isomerization reactions that allow rapid oxidation by molecular oxygen slow down, and competing reaction pathways can suppress the HOM formation almost completely, especially at high VOC loadings.
Mona Kurppa, Antti Hellsten, Pontus Roldin, Harri Kokkola, Juha Tonttila, Mikko Auvinen, Christoph Kent, Prashant Kumar, Björn Maronga, and Leena Järvi
Geosci. Model Dev., 12, 1403–1422, https://doi.org/10.5194/gmd-12-1403-2019, https://doi.org/10.5194/gmd-12-1403-2019, 2019
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This paper describes the implementation of a sectional aerosol module, SALSA, into the PALM model system 6.0. The first evaluation study shows excellent agreements with measurements. Furthermore, we show that ignoring the dry deposition of aerosol particles can overestimate aerosol number concentrations by 20 %, whereas condensation and dissolutional growth increase the total aerosol mass by over 10 % in this specific urban environment.
Nikos Kalivitis, Veli-Matti Kerminen, Giorgos Kouvarakis, Iasonas Stavroulas, Evaggelia Tzitzikalaki, Panayiotis Kalkavouras, Nikos Daskalakis, Stelios Myriokefalitakis, Aikaterini Bougiatioti, Hanna E. Manninen, Pontus Roldin, Tuukka Petäjä, Michael Boy, Markku Kulmala, Maria Kanakidou, and Nikolaos Mihalopoulos
Atmos. Chem. Phys., 19, 2671–2686, https://doi.org/10.5194/acp-19-2671-2019, https://doi.org/10.5194/acp-19-2671-2019, 2019
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New particle formation (NPF) is an important source of atmospheric aerosols. For the Mediterranean atmosphere, only few studies exist. In this study we present one of the longest series of NPF by analyzing 10 years of data from Crete, Greece. NPF took place on 27 % of the available days; it was more frequent in spring and less so in late summer. Model simulations showed that NPF in the subtropical environment may differ greatly from that in the boreal environment.
Erik Ahlberg, Axel Eriksson, William H. Brune, Pontus Roldin, and Birgitta Svenningsson
Atmos. Chem. Phys., 19, 2701–2712, https://doi.org/10.5194/acp-19-2701-2019, https://doi.org/10.5194/acp-19-2701-2019, 2019
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The effects of wet or dry salt seed particle concentration (ammonium nitrate and ammonium sulphate) on secondary organic aerosol mass yields from a mixture of m-xylene and α-pinene were examined in an oxidation flow reactor. The experiments confirmed that increasing the condensation sink significantly increases the particle mass yields in oxidation flow reactors. Further, wet seed particles increased the particle mass yield by 60 % more than dry particles.
Michael Boy, Erik S. Thomson, Juan-C. Acosta Navarro, Olafur Arnalds, Ekaterina Batchvarova, Jaana Bäck, Frank Berninger, Merete Bilde, Zoé Brasseur, Pavla Dagsson-Waldhauserova, Dimitri Castarède, Maryam Dalirian, Gerrit de Leeuw, Monika Dragosics, Ella-Maria Duplissy, Jonathan Duplissy, Annica M. L. Ekman, Keyan Fang, Jean-Charles Gallet, Marianne Glasius, Sven-Erik Gryning, Henrik Grythe, Hans-Christen Hansson, Margareta Hansson, Elisabeth Isaksson, Trond Iversen, Ingibjorg Jonsdottir, Ville Kasurinen, Alf Kirkevåg, Atte Korhola, Radovan Krejci, Jon Egill Kristjansson, Hanna K. Lappalainen, Antti Lauri, Matti Leppäranta, Heikki Lihavainen, Risto Makkonen, Andreas Massling, Outi Meinander, E. Douglas Nilsson, Haraldur Olafsson, Jan B. C. Pettersson, Nønne L. Prisle, Ilona Riipinen, Pontus Roldin, Meri Ruppel, Matthew Salter, Maria Sand, Øyvind Seland, Heikki Seppä, Henrik Skov, Joana Soares, Andreas Stohl, Johan Ström, Jonas Svensson, Erik Swietlicki, Ksenia Tabakova, Throstur Thorsteinsson, Aki Virkkula, Gesa A. Weyhenmeyer, Yusheng Wu, Paul Zieger, and Markku Kulmala
Atmos. Chem. Phys., 19, 2015–2061, https://doi.org/10.5194/acp-19-2015-2019, https://doi.org/10.5194/acp-19-2015-2019, 2019
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The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date and aimed to strengthen research and innovation regarding climate change issues in the Nordic region. The paper presents an overview of the main scientific topics investigated and provides a state-of-the-art comprehensive summary of what has been achieved in CRAICC.
Yuqin Liu, Jiahua Zhang, Putian Zhou, Tao Lin, Juan Hong, Lamei Shi, Fengmei Yao, Jun Wu, Huadong Guo, and Gerrit de Leeuw
Atmos. Chem. Phys., 18, 18187–18202, https://doi.org/10.5194/acp-18-18187-2018, https://doi.org/10.5194/acp-18-18187-2018, 2018
Liqing Hao, Olga Garmash, Mikael Ehn, Pasi Miettinen, Paola Massoli, Santtu Mikkonen, Tuija Jokinen, Pontus Roldin, Pasi Aalto, Taina Yli-Juuti, Jorma Joutsensaari, Tuukka Petäjä, Markku Kulmala, Kari E. J. Lehtinen, Douglas R. Worsnop, and Annele Virtanen
Atmos. Chem. Phys., 18, 17705–17716, https://doi.org/10.5194/acp-18-17705-2018, https://doi.org/10.5194/acp-18-17705-2018, 2018
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An aerosol mass spectrometer was used to characterize aerosol chemical composition during new particle formation periods. The time profiles of mass concentrations and chemical composition of observed aerosol particles are subjected to joint effects of boundary layer dilution, atmospheric chemistry and aerosol mixing in different boundary layers. During the nighttime, the increase in organic aerosol mass correlated well with the increase in condensed highly oxygenated organic molecules' mass.
Jenni Kontkanen, Tinja Olenius, Markku Kulmala, and Ilona Riipinen
Atmos. Chem. Phys., 18, 13733–13754, https://doi.org/10.5194/acp-18-13733-2018, https://doi.org/10.5194/acp-18-13733-2018, 2018
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New particle formation involving sulfuric acid, bases and organic compounds is an important source of atmospheric aerosol particles. We investigate the capability of nano-Köhler theory to describe this process by simulating the dynamics of atmospheric molecular clusters. We find that nano-Köhler-type behavior occurs in our simulations when the saturation ratio of the organic vapor and the ratio between organic and inorganic vapor concentrations are in a suitable range.
Ximeng Qi, Aijun Ding, Pontus Roldin, Zhengning Xu, Putian Zhou, Nina Sarnela, Wei Nie, Xin Huang, Anton Rusanen, Mikael Ehn, Matti P. Rissanen, Tuukka Petäjä, Markku Kulmala, and Michael Boy
Atmos. Chem. Phys., 18, 11779–11791, https://doi.org/10.5194/acp-18-11779-2018, https://doi.org/10.5194/acp-18-11779-2018, 2018
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In this study we simulate the HOM concentrations and discuss their roles in NPF at a remote boreal forest site in Finland and a suburban site in eastern China. We found that sulfuric acid and HOM organonitrate concentrations in the gas phase are significantly higher but other HOM monomers and dimers from monoterpene oxidation are lower in eastern China. This study highlights the need for molecular-scale measurements in improving the understanding of NPF mechanisms in polluted areas.
Ben H. Lee, Felipe D. Lopez-Hilfiker, Emma L. D'Ambro, Putian Zhou, Michael Boy, Tuukka Petäjä, Liqing Hao, Annele Virtanen, and Joel A. Thornton
Atmos. Chem. Phys., 18, 11547–11562, https://doi.org/10.5194/acp-18-11547-2018, https://doi.org/10.5194/acp-18-11547-2018, 2018
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Molecular identities and abundances of organic compounds residing in the gas and particle phases above a Finnish boreal forest are presented. We determined that in each phase, the organic components are categorized into three subgroups based on their behavior in time. Some are more enhanced at night, others during midday, and another around sunrise. Identifying such collective behavior can potentially connect the chemical processes that evolve in time to specific distributions of products.
Luciana Varanda Rizzo, Pontus Roldin, Joel Brito, John Backman, Erik Swietlicki, Radovan Krejci, Peter Tunved, Tukka Petäjä, Markku Kulmala, and Paulo Artaxo
Atmos. Chem. Phys., 18, 10255–10274, https://doi.org/10.5194/acp-18-10255-2018, https://doi.org/10.5194/acp-18-10255-2018, 2018
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Aerosols are tiny particles suspended in the air that can interact with sunlight and form clouds, which in turn affect the climate. They can also recycle nutrients in forest environments. Aerosols are naturally emitted at the surface in the Amazon forest, in addition to being brought down from above the boundary layer by intense air movements. In this work, we describe how the particle size number concentrations of aerosols change over hours, days and seasons in a multi-year study in Amazonia.
Putian Zhou, Laurens Ganzeveld, Ditte Taipale, Üllar Rannik, Pekka Rantala, Matti Petteri Rissanen, Dean Chen, and Michael Boy
Atmos. Chem. Phys., 17, 14309–14332, https://doi.org/10.5194/acp-17-14309-2017, https://doi.org/10.5194/acp-17-14309-2017, 2017
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In boreal forest, there is a large number of gaseous organic compounds called biogenic volatile organic compounds (BVOCs). Within the canopy, they can be emitted from vegetation and soil, react with each other and other gases, be transported in the air, and be removed from vegetation and soil surfaces. We applied a numerical model to simulate these processes and found that these BVOCs can be divided into five categories according to the significance of their sources and sinks.
Georgios Tsagkogeorgas, Pontus Roldin, Jonathan Duplissy, Linda Rondo, Jasmin Tröstl, Jay G. Slowik, Sebastian Ehrhart, Alessandro Franchin, Andreas Kürten, Antonio Amorim, Federico Bianchi, Jasper Kirkby, Tuukka Petäjä, Urs Baltensperger, Michael Boy, Joachim Curtius, Richard C. Flagan, Markku Kulmala, Neil M. Donahue, and Frank Stratmann
Atmos. Chem. Phys., 17, 8923–8938, https://doi.org/10.5194/acp-17-8923-2017, https://doi.org/10.5194/acp-17-8923-2017, 2017
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The H2SO4 vapour pressure plays key role in Earth's and Venus' atmospheres. In regions where RH is low and stabilising bases are scarce, H2SO4 can evaporate from particles; however the H2SO4 vapour pressure at low RH is uncertain. To address this, we measured H2SO4 evaporation versus T and RH in the CLOUD chamber and constrained the equilibrium constants for dissociation and dehydration of H2SO4. This study is important for nucleation, particle growth and H2SO4 formation occurring in atmosphere.
Emilie Öström, Zhou Putian, Guy Schurgers, Mikhail Mishurov, Niku Kivekäs, Heikki Lihavainen, Mikael Ehn, Matti P. Rissanen, Theo Kurtén, Michael Boy, Erik Swietlicki, and Pontus Roldin
Atmos. Chem. Phys., 17, 8887–8901, https://doi.org/10.5194/acp-17-8887-2017, https://doi.org/10.5194/acp-17-8887-2017, 2017
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We used a model to study how biogenic volatile organic compounds (BVOCs) emitted from the boreal forest contribute to the formation and growth of particles in the atmosphere. Some of these particles are important climate forcers, acting as seeds for cloud droplet fomation. We implemented a new gas chemistry mechanism that describes how the BVOCs are oxidized and form low-volatility highly oxidized organic molecules. With the new mechanism we are able to accurately predict the particle growth.
Eero Nikinmaa, Tuomo Kalliokoski, Kari Minkkinen, Jaana Bäck, Michael Boy, Yao Gao, Nina Janasik-Honkela, Janne I. Hukkinen, Maarit Kallio, Markku Kulmala, Nea Kuusinen, Annikki Mäkelä, Brent D. Matthies, Mikko Peltoniemi, Risto Sievänen, Ditte Taipale, Lauri Valsta, Anni Vanhatalo, Martin Welp, Luxi Zhou, Putian Zhou, and Frank Berninger
Biogeosciences Discuss., https://doi.org/10.5194/bg-2017-141, https://doi.org/10.5194/bg-2017-141, 2017
Manuscript not accepted for further review
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We estimated the impact of boreal forest management on climate, considering the effects of carbon, albedo, aerosols, and effects of industrial wood use. We made analyses both in current and warmer climate of 2050. The aerosol effect was comparable to that of carbon sequestration. Deciduous trees may have a large potential for mitigation due to their high albedo and aerosol effects. If the forests will be used more intensively and mainly for pulp and energy, the warming influence is clear.
Yuqin Liu, Gerrit de Leeuw, Veli-Matti Kerminen, Jiahua Zhang, Putian Zhou, Wei Nie, Ximeng Qi, Juan Hong, Yonghong Wang, Aijun Ding, Huadong Guo, Olaf Krüger, Markku Kulmala, and Tuukka Petäjä
Atmos. Chem. Phys., 17, 5623–5641, https://doi.org/10.5194/acp-17-5623-2017, https://doi.org/10.5194/acp-17-5623-2017, 2017
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The aerosol effects on warm cloud parameters over the Yangtze River Delta are systematically examined using multi-sensor retrievals. This study shows that the COT–CDR and CWP–CDR relationships are not unique, but are affected by atmospheric aerosol loading. CDR and cloud fraction show different behaviours for low and high AOD. Aerosol–cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust. Meteorological conditions play an important role in ACI.
Putian Zhou, Laurens Ganzeveld, Üllar Rannik, Luxi Zhou, Rosa Gierens, Ditte Taipale, Ivan Mammarella, and Michael Boy
Atmos. Chem. Phys., 17, 1361–1379, https://doi.org/10.5194/acp-17-1361-2017, https://doi.org/10.5194/acp-17-1361-2017, 2017
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We implemented a multi-layer O3 dry deposition model in a 1-D model SOSAA to simulate O3 flux and concentration within and above a boreal forest at SMEAR II in Hyytiälä, Finland, in August 2010. The results showed that when RH > 70 % the O3 uptake on leaf wet skin was ~ 51 % to the total deposition at night and ~ 19 % at daytime. The sub-canopy contribution below 4.2 m was ~ 38 % at daytime. The averaged daily chemical contribution to total O3 alteration inside the canopy was less than 10 %.
Natalia Babkovskaia, Ullar Rannik, Vaughan Phillips, Holger Siebert, Birgit Wehner, and Michael Boy
Atmos. Chem. Phys., 16, 7889–7898, https://doi.org/10.5194/acp-16-7889-2016, https://doi.org/10.5194/acp-16-7889-2016, 2016
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Turbulence, aerosol growth and microphysics of hydrometeors in clouds are intimately coupled. A new modelling approach was applied to quantify this linkage. We study the interaction in the cloud area under transient, high supersaturation conditions, using direct numerical simulations. Analysing the effect of aerosol dynamics on the turbulent kinetic energy and on vertical velocity, we conclude that the presence of aerosol has an effect on vertical motion and tends to reduce downward velocity.
David Brus, Lenka Skrabalova, Erik Herrmann, Tinja Olenius, Tereza Travnickova, and Joonas Merikanto
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-398, https://doi.org/10.5194/acp-2016-398, 2016
Revised manuscript not accepted
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We report laboratory measurements of the diffusion coefficient of sulfuric acid in humidified air. To our best knowledge, this is the first study, which investigates systematically the temperature dependency of the diffusion coefficient of H2SO4. We observed a rather strong power dependence with power of 5.4 when compared to 1.75 observed for other gases. We suggest that observed higher temperature dependence might be due to strong clustering of H2SO4 with base-impurities like amines.
Jenni Kontkanen, Tinja Olenius, Katrianne Lehtipalo, Hanna Vehkamäki, Markku Kulmala, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 16, 5545–5560, https://doi.org/10.5194/acp-16-5545-2016, https://doi.org/10.5194/acp-16-5545-2016, 2016
Üllar Rannik, Luxi Zhou, Putian Zhou, Rosa Gierens, Ivan Mammarella, Andrey Sogachev, and Michael Boy
Atmos. Chem. Phys., 16, 3145–3160, https://doi.org/10.5194/acp-16-3145-2016, https://doi.org/10.5194/acp-16-3145-2016, 2016
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Atmospheric boundary layer (ABL) model coupled with detailed atmospheric chemistry and aerosol dynamical model was used to quantify the role of aerosol and ABL dynamics in the vertical transport of aerosols at a pine forest site in southern Finland. Simulations showed that under dynamical conditions the particle fluxes above canopy can significantly deviate from the dry deposition into the canopy. The deviation can be systematic for certain particle sizes over a period of several days.
Xin Huang, Luxi Zhou, Aijun Ding, Ximeng Qi, Wei Nie, Minghuai Wang, Xuguang Chi, Tuukka Petäjä, Veli-Matti Kerminen, Pontus Roldin, Anton Rusanen, Markku Kulmala, and Michael Boy
Atmos. Chem. Phys., 16, 2477–2492, https://doi.org/10.5194/acp-16-2477-2016, https://doi.org/10.5194/acp-16-2477-2016, 2016
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By combining a regional model and a box model, this study simulates new particle formation in Nanjing, China, when the air masses were affected by anthropogenic activities, biogenic emissions, or mixed ocean and continental sources. The simulations reveal that biogenic organic compounds play a vital role in growth of newly formed clusters. This novel combination of two models makes it possible to accomplish new particle formation simulation without direct measurements of all chemical species.
X. M. Qi, A. J. Ding, W. Nie, T. Petäjä, V.-M. Kerminen, E. Herrmann, Y. N. Xie, L. F. Zheng, H. Manninen, P. Aalto, J. N. Sun, Z. N. Xu, X. G. Chi, X. Huang, M. Boy, A. Virkkula, X.-Q. Yang, C. B. Fu, and M. Kulmala
Atmos. Chem. Phys., 15, 12445–12464, https://doi.org/10.5194/acp-15-12445-2015, https://doi.org/10.5194/acp-15-12445-2015, 2015
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We report 2 years of measurements of submicron particles at the SORPES station and provide a comprehensive understanding of main factors controlling temporal variation of the aerosol size distribution and NPF in eastern China. The number concentrations of total particles at Nanjing were comparable to other Chinese megacities but the frequency of NPF was much higher. Year-to-year differences of meteorological conditions could significantly influence the seasonal cycle of NPF and growth.
P. Roldin, L. Liao, D. Mogensen, M. Dal Maso, A. Rusanen, V.-M. Kerminen, T. F. Mentel, J. Wildt, E. Kleist, A. Kiendler-Scharr, R. Tillmann, M. Ehn, M. Kulmala, and M. Boy
Atmos. Chem. Phys., 15, 10777–10798, https://doi.org/10.5194/acp-15-10777-2015, https://doi.org/10.5194/acp-15-10777-2015, 2015
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We used the ADCHAM model to study new particle formation events in the JPAC chamber. The model results show that the new particles may be formed by a kinetic type of nucleation involving both sulphuric acid and organic compounds formed from OH oxidation of volatile organic compounds (VOCs). The observed particle growth may either be controlled by the condensation of semi- and low-volatililty organic compounds or by the formation of low-volatility compounds (oligomers) at the particle surface.
L. Zhou, R. Gierens, A. Sogachev, D. Mogensen, J. Ortega, J. N. Smith, P. C. Harley, A. J. Prenni, E. J. T. Levin, A. Turnipseed, A. Rusanen, S. Smolander, A. B. Guenther, M. Kulmala, T. Karl, and M. Boy
Atmos. Chem. Phys., 15, 8643–8656, https://doi.org/10.5194/acp-15-8643-2015, https://doi.org/10.5194/acp-15-8643-2015, 2015
D. Mogensen, R. Gierens, J. N. Crowley, P. Keronen, S. Smolander, A. Sogachev, A. C. Nölscher, L. Zhou, M. Kulmala, M. J. Tang, J. Williams, and M. Boy
Atmos. Chem. Phys., 15, 3909–3932, https://doi.org/10.5194/acp-15-3909-2015, https://doi.org/10.5194/acp-15-3909-2015, 2015
D. Mogensen and M. Boy
Atmos. Chem. Phys., 15, 3109–3110, https://doi.org/10.5194/acp-15-3109-2015, https://doi.org/10.5194/acp-15-3109-2015, 2015
E. Hermansson, P. Roldin, A. Rusanen, D. Mogensen, N. Kivekäs, R. Väänänen, M. Boy, and E. Swietlicki
Atmos. Chem. Phys., 14, 11853–11869, https://doi.org/10.5194/acp-14-11853-2014, https://doi.org/10.5194/acp-14-11853-2014, 2014
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Secondary organic aerosols (SOA), produced through oxidation processes, constitute a large part of the global organic aerosol load and affect the climate. We found that the modeled mass of SOA was highly dependent on how the oxidation processes were explained in models. The results indicated that it was especially important to get the volatility distribution of the products from the first oxidation step right and that fragmentation during the oxidation process played an important role.
S. Smolander, Q. He, D. Mogensen, L. Zhou, J. Bäck, T. Ruuskanen, S. Noe, A. Guenther, H. Aaltonen, M. Kulmala, and M. Boy
Biogeosciences, 11, 5425–5443, https://doi.org/10.5194/bg-11-5425-2014, https://doi.org/10.5194/bg-11-5425-2014, 2014
C. Wittbom, A. C. Eriksson, J. Rissler, J. E. Carlsson, P. Roldin, E. Z. Nordin, P. T. Nilsson, E. Swietlicki, J. H. Pagels, and B. Svenningsson
Atmos. Chem. Phys., 14, 9831–9854, https://doi.org/10.5194/acp-14-9831-2014, https://doi.org/10.5194/acp-14-9831-2014, 2014
L. Liao, V.-M. Kerminen, M. Boy, M. Kulmala, and M. Dal Maso
Atmos. Chem. Phys., 14, 8295–8308, https://doi.org/10.5194/acp-14-8295-2014, https://doi.org/10.5194/acp-14-8295-2014, 2014
P. Roldin, A. C. Eriksson, E. Z. Nordin, E. Hermansson, D. Mogensen, A. Rusanen, M. Boy, E. Swietlicki, B. Svenningsson, A. Zelenyuk, and J. Pagels
Atmos. Chem. Phys., 14, 7953–7993, https://doi.org/10.5194/acp-14-7953-2014, https://doi.org/10.5194/acp-14-7953-2014, 2014
Z. B. Wang, M. Hu, D. Mogensen, D. L. Yue, J. Zheng, R. Y. Zhang, Y. Liu, B. Yuan, X. Li, M. Shao, L. Zhou, Z. J. Wu, A. Wiedensohler, and M. Boy
Atmos. Chem. Phys., 13, 11157–11167, https://doi.org/10.5194/acp-13-11157-2013, https://doi.org/10.5194/acp-13-11157-2013, 2013
E. Z. Nordin, A. C. Eriksson, P. Roldin, P. T. Nilsson, J. E. Carlsson, M. K. Kajos, H. Hellén, C. Wittbom, J. Rissler, J. Löndahl, E. Swietlicki, B. Svenningsson, M. Bohgard, M. Kulmala, M. Hallquist, and J. H. Pagels
Atmos. Chem. Phys., 13, 6101–6116, https://doi.org/10.5194/acp-13-6101-2013, https://doi.org/10.5194/acp-13-6101-2013, 2013
M. Boy, D. Mogensen, S. Smolander, L. Zhou, T. Nieminen, P. Paasonen, C. Plass-Dülmer, M. Sipilä, T. Petäjä, L. Mauldin, H. Berresheim, and M. Kulmala
Atmos. Chem. Phys., 13, 3865–3879, https://doi.org/10.5194/acp-13-3865-2013, https://doi.org/10.5194/acp-13-3865-2013, 2013
L. V. Rizzo, P. Artaxo, T. Müller, A. Wiedensohler, M. Paixão, G. G. Cirino, A. Arana, E. Swietlicki, P. Roldin, E. O. Fors, K. T. Wiedemann, L. S. M. Leal, and M. Kulmala
Atmos. Chem. Phys., 13, 2391–2413, https://doi.org/10.5194/acp-13-2391-2013, https://doi.org/10.5194/acp-13-2391-2013, 2013
Z. B. Wang, M. Hu, Z. J. Wu, D. L. Yue, J. Zheng, R. Y. Zhang, X. Y. Pei, P. Paasonen, M. Dal Maso, M. Boy, and A. Wiedensohler
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-3419-2013, https://doi.org/10.5194/acpd-13-3419-2013, 2013
Revised manuscript not accepted
Related subject area
Atmospheric sciences
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
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
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
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)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
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
Implementation of a dry deposition module (DEPAC v3.11) in a large eddy simulation code (DALES v4.4)
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
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
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the 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 between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
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
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, 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 individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this 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, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
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
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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
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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
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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
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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
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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
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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.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
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
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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
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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
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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
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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.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
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High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
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
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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
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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
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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
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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
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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.
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Jenkin, M. E., Young, J. C., and Rickard, A. R.: The MCM v3.3.1 degradation scheme for isoprene, Atmos. Chem. Phys., 15, 11433–11459, https://doi.org/10.5194/acp-15-11433-2015, 2015.
Karl, M., Pirjola, L., Grönholm, T., Kurppa, M., Anand, S., Zhang, X., Held, A., Sander, R., Dal Maso, M., Topping, D., Jiang, S., Kangas, L., and Kukkonen, J.: Description and evaluation of the community aerosol dynamics model MAFOR v2.0, Geosci. Model Dev., 15, 3969–4026, https://doi.org/10.5194/gmd-15-3969-2022, 2022.
Kokkola, H., Kühn, T., Laakso, A., Bergman, T., Lehtinen, K. E. J., Mielonen, T., Arola, A., Stadtler, S., Korhonen, H., Ferrachat, S., Lohmann, U., Neubauer, D., Tegen, I., Siegenthaler-Le Drian, C., Schultz, M. G., Bey, I., Stier, P., Daskalakis, N., Heald, C. L., and Romakkaniemi, S.: SALSA2.0: The sectional aerosol module of the aerosol–chemistry–climate model ECHAM6.3.0-HAM2.3-MOZ1.0, Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, 2018.
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Short summary
Atmospheric chemistry and aerosol processes form a dynamic and sensitively balanced system, and solving problems regarding air quality or climate requires detailed modelling and coupling of the processes. The models involved are often very complex to use. We have addressed this problem with the new ARCA box model. It puts much of the current knowledge of the nano- and microscale aerosol dynamics and chemistry into usable software and has the potential to become a valuable tool in the community.
Atmospheric chemistry and aerosol processes form a dynamic and sensitively balanced system, and...
