Articles | Volume 12, issue 4
https://doi.org/10.5194/gmd-12-1403-2019
© Author(s) 2019. 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-12-1403-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
11 Apr 2019
Model description paper |
| 11 Apr 2019
| 11 Apr 2019
Implementation of the sectional aerosol module SALSA2.0 into the PALM model system 6.0: model development and first evaluation
Institute for Atmospheric and Earth System Research/Physics,
Faculty of Science, University of Helsinki,
P.O. Box 68, 00014 Helsinki, Finland
Antti Hellsten
Finnish Meteorological Institute, 00101 Helsinki, Finland
Pontus Roldin
Institute for Atmospheric and Earth System Research/Physics,
Faculty of Science, University of Helsinki,
P.O. Box 68, 00014 Helsinki, Finland
Division of Nuclear Physics, Lund University, 22100 Lund, Sweden
Harri Kokkola
Finnish Meteorological Institute, 70211 Kuopio, Finland
Juha Tonttila
Finnish Meteorological Institute, 70211 Kuopio, Finland
Mikko Auvinen
Institute for Atmospheric and Earth System Research/Physics,
Faculty of Science, University of Helsinki,
P.O. Box 68, 00014 Helsinki, Finland
Finnish Meteorological Institute, 00101 Helsinki, Finland
Christoph Kent
Department of Meteorology, University of Reading, Reading RG6 6BB, UK
Prashant Kumar
Global Centre for Clean Air Research (GCARE), Department of
Civil & Environmental Engineering, University of Surrey, Guildford GU2 7XH, UK
Björn Maronga
Leibniz University Hanover, Institute of Meteorology and Climatology, 30419 Hanover, Germany
Geophysical Institute, University of Bergen, 5020 Bergen, Norway
Leena Järvi
Institute for Atmospheric and Earth System Research/Physics,
Faculty of Science, University of Helsinki,
P.O. Box 68, 00014 Helsinki, Finland
Helsinki Institute of Sustainability Science, University of Helsinki, 00014 Helsinki, Finland
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We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Petri Clusius, Carlton Xavier, Lukas Pichelstorfer, Putian Zhou, Tinja Olenius, Pontus Roldin, and Michael Boy
Geosci. Model Dev., 15, 7257–7286, https://doi.org/10.5194/gmd-15-7257-2022, https://doi.org/10.5194/gmd-15-7257-2022, 2022
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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.
Silvia M. Calderón, Juha Tonttila, Angela Buchholz, Jorma Joutsensaari, Mika Komppula, Ari Leskinen, Liqing Hao, Dmitri Moisseev, Iida Pullinen, Petri Tiitta, Jian Xu, Annele Virtanen, Harri Kokkola, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 12417–12441, https://doi.org/10.5194/acp-22-12417-2022, https://doi.org/10.5194/acp-22-12417-2022, 2022
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The spatial and temporal restrictions of observations and oversimplified aerosol representation in large eddy simulations (LES) limit our understanding of aerosol–stratocumulus interactions. In this closure study of in situ and remote sensing observations and outputs from UCLALES–SALSA, we have assessed the role of convective overturning and aerosol effects in two cloud events observed at the Puijo SMEAR IV station, Finland, a diurnal-high aerosol case and a nocturnal-low aerosol case.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom V. Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
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Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
Sini Isokääntä, Paul Kim, Santtu Mikkonen, Thomas Kühn, Harri Kokkola, Taina Yli-Juuti, Liine Heikkinen, Krista Luoma, Tuukka Petäjä, Zak Kipling, Daniel Partridge, and Annele Virtanen
Atmos. Chem. Phys., 22, 11823–11843, https://doi.org/10.5194/acp-22-11823-2022, https://doi.org/10.5194/acp-22-11823-2022, 2022
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This research employs air mass history analysis and observations to study how clouds and precipitation affect atmospheric aerosols during transport to a boreal forest site. The mass concentrations of studied chemical species showed exponential decrease as a function of accumulated rain along the air mass route. Our analysis revealed in-cloud sulfate formation, while no major changes in organic mass were seen. Most of the in-cloud-formed sulfate could be assigned to particle sizes above 200 nm.
Benjamin Foreback, Lubna Dada, Kaspar R. Daellenbach, Chao Yan, Lili Wang, Biwu Chu, Ying Zhou, Tom V. Kokkonen, Mona Kurppa, Rosaria E. Pileci, Yonghong Wang, Tommy Chan, Juha Kangasluoma, Lin Zhuohui, Yishou Guo, Chang Li, Rima Baalbaki, Joni Kujansuu, Xiaolong Fan, Zemin Feng, Pekka Rantala, Shahzad Gani, Federico Bianchi, Veli-Matti Kerminen, Tuukka Petäjä, Markku Kulmala, Yongchun Liu, and Pauli Paasonen
Atmos. Chem. Phys., 22, 11089–11104, https://doi.org/10.5194/acp-22-11089-2022, https://doi.org/10.5194/acp-22-11089-2022, 2022
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This study analyzed air quality in Beijing during the Chinese New Year over 7 years, including data from a new in-depth measurement station. This is one of few studies to look at long-term impacts, including the outcome of firework restrictions starting in 2018. Results show that firework pollution has gone down since 2016, indicating a positive result from the restrictions. Results of this study may be useful in making future decisions about the use of fireworks to improve air quality.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Marje Prank, Juha Tonttila, Jaakko Ahola, Harri Kokkola, Thomas Kühn, Sami Romakkaniemi, and Tomi Raatikainen
Atmos. Chem. Phys., 22, 10971–10992, https://doi.org/10.5194/acp-22-10971-2022, https://doi.org/10.5194/acp-22-10971-2022, 2022
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Aerosols and clouds persist as the dominant sources of uncertainty in climate projections. In this modelling study, we investigate the role of marine aerosols in influencing the lifetime of low-level clouds. Our high resolution simulations show that sea spray can both extend and shorten the lifetime of the cloud layer depending on the model setup. The impact of the primary marine organics is relatively limited while secondary aerosol from monoterpenes can have larger impact.
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.
Minttu Havu, Liisa Kulmala, Pasi Kolari, Timo Vesala, Anu Riikonen, and Leena Järvi
Biogeosciences, 19, 2121–2143, https://doi.org/10.5194/bg-19-2121-2022, https://doi.org/10.5194/bg-19-2121-2022, 2022
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The carbon sequestration potential of two street tree species and the soil beneath them was quantified with the urban land surface model SUEWS and the soil carbon model Yasso. The street tree plantings turned into a modest sink of carbon from the atmosphere after 14 years. Overall, the results indicate the importance of soil in urban carbon sequestration estimations, as soil respiration exceeded the carbon uptake in the early phase, due to the high initial carbon loss from the soil.
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432, https://doi.org/10.5194/amt-15-2417-2022, https://doi.org/10.5194/amt-15-2417-2022, 2022
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To study the complex structure of the lowest tens of metres of atmosphere in urban areas, measurement methods with great spatial and temporal coverage are needed. In our study, we analyse measurements with a promising and relatively new method, distributed temperature sensing, capable of providing detailed information on the near-surface atmosphere. We present multiple ways to utilise these kinds of measurements, as well as important considerations for planning new studies using the method.
Jaakko Ahola, Tomi Raatikainen, Muzaffer Ege Alper, Jukka-Pekka Keskinen, Harri Kokkola, Antti Kukkurainen, Antti Lipponen, Jia Liu, Kalle Nordling, Antti-Ilari Partanen, Sami Romakkaniemi, Petri Räisänen, Juha Tonttila, and Hannele Korhonen
Atmos. Chem. Phys., 22, 4523–4537, https://doi.org/10.5194/acp-22-4523-2022, https://doi.org/10.5194/acp-22-4523-2022, 2022
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Clouds are important for the climate, and cloud droplets have a significant role in cloud properties. Cloud droplets form when air rises and cools and water vapour condenses on small particles that can be natural or of anthropogenic origin. Currently, the updraft velocity, meaning how fast the air rises, is poorly represented in global climate models. In our study, we show three methods that will improve the depiction of updraft velocity and which properties are vital to updrafts.
Tomi Raatikainen, Marje Prank, Jaakko Ahola, Harri Kokkola, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 3763–3778, https://doi.org/10.5194/acp-22-3763-2022, https://doi.org/10.5194/acp-22-3763-2022, 2022
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Mineral dust or similar ice-nucleating particles (INPs) are needed to initiate cloud droplet freezing at temperatures common in shallow clouds. In this work we examine how INPs that are released from the sea surface impact marine clouds. Our high-resolution simulations show that turbulent updraughts carry these particles effectively up to the clouds, where they initiate cloud droplet freezing. Sea surface INP emissions become more important with decreasing background dust INP concentrations.
Jessica Slater, Hugh Coe, Gordon McFiggans, Juha Tonttila, and Sami Romakkaniemi
Atmos. Chem. Phys., 22, 2937–2953, https://doi.org/10.5194/acp-22-2937-2022, https://doi.org/10.5194/acp-22-2937-2022, 2022
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This paper shows the specific impact of black carbon (BC) on the aerosol–planetary boundary layer (PBL) feedback and its influence on a Beijing haze episode. Overall, this paper shows that strong temperature inversions prevent BC heating within the PBL from significantly increasing PBL height, while BC above the PBL suppresses PBL development significantly through the day. From this we suggest a method by which both locally and regionally emitted BC may impact urban pollution episodes.
Shang Gao, Mona Kurppa, Chak K. Chan, and Keith Ngan
Atmos. Chem. Phys., 22, 2703–2726, https://doi.org/10.5194/acp-22-2703-2022, https://doi.org/10.5194/acp-22-2703-2022, 2022
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The contribution of cooking emissions to organic aerosols may exceed that of motor vehicles. However, little is known about how cooking-generated aerosols evolve in the outdoor environment. In this paper, we present a numerical study of the dispersion of cooking emissions. For plausible choices of the emission strength, cooking can yield much higher concentrations than traffic. This has important implications for public health and city planning.
Mohamed H. Salim, Sebastian Schubert, Jaroslav Resler, Pavel Krč, Björn Maronga, Farah Kanani-Sühring, Matthias Sühring, and Christoph Schneider
Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
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Radiative transfer processes are the main energy transport mechanism in urban areas which influence the surface energy budget and drive local convection. We show here the importance of each process to help modellers decide on how much detail they should include in their models to parameterize radiative transfer in urban areas. We showed how the flow field may change in response to these processes and the essential processes needed to assure acceptable quality of the numerical simulations.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Anton Laakso, Ulrike Niemeier, Daniele Visioni, Simone Tilmes, and Harri Kokkola
Atmos. Chem. Phys., 22, 93–118, https://doi.org/10.5194/acp-22-93-2022, https://doi.org/10.5194/acp-22-93-2022, 2022
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The use of different spatio-temporal sulfur injection strategies with different magnitudes to create an artificial reflective aerosol layer to cool the climate is studied using sectional and modal aerosol schemes in a climate model. There are significant differences in the results depending on the aerosol microphysical module used. Different spatio-temporal injection strategies have a significant impact on the magnitude and zonal distribution of radiative forcing and atmospheric dynamics.
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev., 14, 7411–7424, https://doi.org/10.5194/gmd-14-7411-2021, https://doi.org/10.5194/gmd-14-7411-2021, 2021
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This study aims to replicate computationally expensive high-resolution large-eddy simulations (LESs) with regression models to simulate urban air quality and pollutant dispersion. The model development, including feature selection, model training and cross-validation, and detection of concept drift, has been described in detail. Of the models applied, log-linear regression shows the best performance. A regression model can replace LES unless high accuracy is needed.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
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Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Katrin Frieda Gehrke, Matthias Sühring, and Björn Maronga
Geosci. Model Dev., 14, 5307–5329, https://doi.org/10.5194/gmd-14-5307-2021, https://doi.org/10.5194/gmd-14-5307-2021, 2021
Michal Belda, Jaroslav Resler, Jan Geletič, Pavel Krč, Björn Maronga, Matthias Sühring, Mona Kurppa, Farah Kanani-Sühring, Vladimír Fuka, Kryštof Eben, Nina Benešová, and Mikko Auvinen
Geosci. Model Dev., 14, 4443–4464, https://doi.org/10.5194/gmd-14-4443-2021, https://doi.org/10.5194/gmd-14-4443-2021, 2021
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The analysis summarizes how sensitive the modelling of urban environment is to changes in physical parameters describing the city (e.g. reflectivity of surfaces) and to several heat island mitigation scenarios in a city quarter in Prague, Czech Republic. We used the large-eddy simulation modelling system PALM 6.0. Surface parameters connected to radiation show the highest sensitivity in this configuration. For heat island mitigation, urban vegetation is shown to be the most effective measure.
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.
Jens Pfafferott, Sascha Rißmann, Matthias Sühring, Farah Kanani-Sühring, and Björn Maronga
Geosci. Model Dev., 14, 3511–3519, https://doi.org/10.5194/gmd-14-3511-2021, https://doi.org/10.5194/gmd-14-3511-2021, 2021
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The building model is integrated via an urban surface model into the urban climate model.
There is a strong interaction between the built environment and the urban climate.
According to the building energy concept, the energy demand results in a waste heat; this is directly transferred to the urban environment.
The impact of buildings on the urban climate is defined by different physical building parameters with different technical facilities for ventilation, heating and cooling.
Tobias Gronemeier, Kerstin Surm, Frank Harms, Bernd Leitl, Björn Maronga, and Siegfried Raasch
Geosci. Model Dev., 14, 3317–3333, https://doi.org/10.5194/gmd-14-3317-2021, https://doi.org/10.5194/gmd-14-3317-2021, 2021
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We demonstrate the capability of the PALM model system version 6.0 to simulate urban boundary layers. The studied situation includes a real-world building setup of the HafenCity area in Hamburg, Germany. We evaluate the simulation results against wind-tunnel measurements utilizing PALM's virtual measurement module. The comparison reveals an overall high agreement between simulation results and wind-tunnel measurements including mean wind speed and direction as well as turbulence statistics.
Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch
Geosci. Model Dev., 14, 3185–3214, https://doi.org/10.5194/gmd-14-3185-2021, https://doi.org/10.5194/gmd-14-3185-2021, 2021
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Large-eddy simulation (LES) of the urban atmospheric boundary layer involves a large separation of turbulent scales, leading to prohibitive computational costs. An online LES–LES nesting scheme is implemented into the PALM model system 6.0 to overcome this problem. Test results show that the accuracy within the high-resolution nest domains approach the non-nested high-resolution reference results. The nesting can reduce the CPU by time up to 80 % compared to the fine-resolution reference runs.
Basit Khan, Sabine Banzhaf, Edward C. Chan, Renate Forkel, Farah Kanani-Sühring, Klaus Ketelsen, Mona Kurppa, Björn Maronga, Matthias Mauder, Siegfried Raasch, Emmanuele Russo, Martijn Schaap, and Matthias Sühring
Geosci. Model Dev., 14, 1171–1193, https://doi.org/10.5194/gmd-14-1171-2021, https://doi.org/10.5194/gmd-14-1171-2021, 2021
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An atmospheric chemistry model has been implemented in the microscale PALM model system 6.0. This article provides a detailed description of the model, its structure, input requirements, various features and limitations. Several pre-compiled ready-to-use chemical mechanisms are included in the chemistry model code; however, users can also easily implement other mechanisms. A case study is presented to demonstrate the application of the new chemistry model in the urban environment.
Antti Ruuskanen, Sami Romakkaniemi, Harri Kokkola, Antti Arola, Santtu Mikkonen, Harri Portin, Annele Virtanen, Kari E. J. Lehtinen, Mika Komppula, and Ari Leskinen
Atmos. Chem. Phys., 21, 1683–1695, https://doi.org/10.5194/acp-21-1683-2021, https://doi.org/10.5194/acp-21-1683-2021, 2021
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The study focuses mainly on cloud-scavenging efficiency of absorbing particulate matter (mainly black carbon) but additionally covers cloud-scavenging efficiency of scattering particles and statistics of cloud condensation nuclei. The main findings give insight into how black carbon is distributed in different particle sizes and the sensitivity to cloud scavenged. The main findings are useful for large-scale modelling for evaluating cloud scavenging.
Juha Tonttila, Ali Afzalifar, Harri Kokkola, Tomi Raatikainen, Hannele Korhonen, and Sami Romakkaniemi
Atmos. Chem. Phys., 21, 1035–1048, https://doi.org/10.5194/acp-21-1035-2021, https://doi.org/10.5194/acp-21-1035-2021, 2021
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The focus of this study is on rain enhancement by deliberate injection of small particles into clouds (
cloud seeding). The particles, usually released from an aircraft, are expected to enhance cloud droplet growth, but its practical feasibility is somewhat uncertain. To improve upon this, we simulate the seeding effects with a numerical model. The model reproduces the main features seen in field observations, with a strong sensitivity to the total mass of the injected particle material.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
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Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Eemeli Holopainen, Harri Kokkola, Anton Laakso, and Thomas Kühn
Geosci. Model Dev., 13, 6215–6235, https://doi.org/10.5194/gmd-13-6215-2020, https://doi.org/10.5194/gmd-13-6215-2020, 2020
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This paper introduces an in-cloud wet deposition scheme for liquid and ice phase clouds for global aerosol–climate models. With the default setup, our wet deposition scheme behaves spuriously and better representation can be achieved with this scheme when black carbon is mixed with soluble compounds at emission time. This work is done as many of the global models fail to reproduce the transport of black carbon to the Arctic, which may be due to the poor representation of wet removal in models.
Wieke Heldens, Cornelia Burmeister, Farah Kanani-Sühring, Björn Maronga, Dirk Pavlik, Matthias Sühring, Julian Zeidler, and Thomas Esch
Geosci. Model Dev., 13, 5833–5873, https://doi.org/10.5194/gmd-13-5833-2020, https://doi.org/10.5194/gmd-13-5833-2020, 2020
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For realistic microclimate simulations in urban areas with PALM 6.0, detailed description of surface types, buildings and vegetation is required. This paper shows how such input data sets can be derived with the example of three German cities. Various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. The collection and preparation of input data sets is tedious. Future research aims therefore at semi-automated tools to support users.
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.
Jessica Slater, Juha Tonttila, Gordon McFiggans, Paul Connolly, Sami Romakkaniemi, Thomas Kühn, and Hugh Coe
Atmos. Chem. Phys., 20, 11893–11906, https://doi.org/10.5194/acp-20-11893-2020, https://doi.org/10.5194/acp-20-11893-2020, 2020
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The feedback effect between aerosol particles, radiation and meteorology reduces turbulent motion and results in increased surface aerosol concentrations during Beijing haze. Observational analysis and regional modelling studies have examined the feedback effect but these studies are limited. In this work, we set up a high-resolution model for the Beijing environment to examine the sensitivity of the aerosol feedback effect to initial meteorological conditions and aerosol loading.
Jaakko Ahola, Hannele Korhonen, Juha Tonttila, Sami Romakkaniemi, Harri Kokkola, and Tomi Raatikainen
Atmos. Chem. Phys., 20, 11639–11654, https://doi.org/10.5194/acp-20-11639-2020, https://doi.org/10.5194/acp-20-11639-2020, 2020
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In this study, we present an improved cloud model that reproduces the behaviour of mixed-phase clouds containing liquid droplets and ice crystals in more detail than before. This model is a convenient computational tool that enables the study of phenomena that cannot fit into a laboratory. These clouds have a significant role in climate, but they are not yet properly understood. Here, we show the advantages of the new model in a case study focusing on Arctic mixed-phase clouds.
Innocent Kudzotsa, Harri Kokkola, Juha Tonttila, Tomi Raatikainen, and Sami Romakkaniemi
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-851, https://doi.org/10.5194/acp-2020-851, 2020
Publication in ACP not foreseen
María A. Burgos, Elisabeth Andrews, Gloria Titos, Angela Benedetti, Huisheng Bian, Virginie Buchard, Gabriele Curci, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Anton Laakso, Julie Letertre-Danczak, Marianne T. Lund, Hitoshi Matsui, Gunnar Myhre, Cynthia Randles, Michael Schulz, Twan van Noije, Kai Zhang, Lucas Alados-Arboledas, Urs Baltensperger, Anne Jefferson, James Sherman, Junying Sun, Ernest Weingartner, and Paul Zieger
Atmos. Chem. Phys., 20, 10231–10258, https://doi.org/10.5194/acp-20-10231-2020, https://doi.org/10.5194/acp-20-10231-2020, 2020
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We investigate how well models represent the enhancement in scattering coefficients due to particle water uptake, and perform an evaluation of several implementation schemes used in ten Earth system models. Our results show the importance of the parameterization of hygroscopicity and model chemistry as drivers of some of the observed diversity amongst model estimates. The definition of dry conditions and the phenomena taking place in this relative humidity range also impact the model evaluation.
Goran Gašparac, Amela Jeričević, Prashant Kumar, and Branko Grisogono
Atmos. Chem. Phys., 20, 6395–6415, https://doi.org/10.5194/acp-20-6395-2020, https://doi.org/10.5194/acp-20-6395-2020, 2020
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Two different available air quality modelling systems were used to investigate physical and chemical processes that contributed to increased daily background PM10 in all of Europe (focusing on eastern and central Europe). Differentiation of modelling performance in respect to the terrain height was found. A strong influence of meteorological conditions on increased background PM10 and statically stable atmospheric conditions were recognized as a key factor in the build-up of background PM10.
Thomas Kühn, Kaarle Kupiainen, Tuuli Miinalainen, Harri Kokkola, Ville-Veikko Paunu, Anton Laakso, Juha Tonttila, Rita Van Dingenen, Kati Kulovesi, Niko Karvosenoja, and Kari E. J. Lehtinen
Atmos. Chem. Phys., 20, 5527–5546, https://doi.org/10.5194/acp-20-5527-2020, https://doi.org/10.5194/acp-20-5527-2020, 2020
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We investigate the effects of black carbon (BC) mitigation on Arctic climate and human health, accounting for the concurrent reduction of other aerosol species. While BC is attributed a net warming effect on climate, most other aerosol species cool the planet. We find that the direct radiative effect of mitigating BC induces cooling, while aerosol–cloud effects offset this cooling and introduce large uncertainties. Furthermore, the reduced aerosol emissions reduce human mortality considerably.
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.
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, https://doi.org/10.5194/gmd-13-1335-2020, 2020
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In this paper, we describe the PALM model system 6.0. PALM is a Fortran-based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
Giulia Saponaro, Moa K. Sporre, David Neubauer, Harri Kokkola, Pekka Kolmonen, Larisa Sogacheva, Antti Arola, Gerrit de Leeuw, Inger H. H. Karset, Ari Laaksonen, and Ulrike Lohmann
Atmos. Chem. Phys., 20, 1607–1626, https://doi.org/10.5194/acp-20-1607-2020, https://doi.org/10.5194/acp-20-1607-2020, 2020
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The understanding of cloud processes is based on the quality of the representation of cloud properties. We compared cloud parameters from three models with satellite observations. We report on the performance of each data source, highlighting strengths and deficiencies, which should be considered when deriving the effect of aerosols on cloud properties.
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.
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.
David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Philip Stier, Daniel G. Partridge, Ina Tegen, Isabelle Bey, Tanja Stanelle, Harri Kokkola, and Ulrike Lohmann
Geosci. Model Dev., 12, 3609–3639, https://doi.org/10.5194/gmd-12-3609-2019, https://doi.org/10.5194/gmd-12-3609-2019, 2019
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The global aerosol–climate model ECHAM6.3–HAM2.3 as well as the previous model versions ECHAM5.5–HAM2.0 and ECHAM6.1–HAM2.2 are evaluated. The simulation of clouds has improved in ECHAM6.3–HAM2.3. This has an impact on effective radiative forcing due to aerosol–radiation and aerosol–cloud interactions and equilibrium climate sensitivity, which are weaker in ECHAM6.3–HAM2.3 than in the previous model versions.
Helge Knoop, Felix Ament, and Björn Maronga
Adv. Sci. Res., 16, 143–148, https://doi.org/10.5194/asr-16-143-2019, https://doi.org/10.5194/asr-16-143-2019, 2019
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This paper proposes a new generic method to define and detect wind gusts from high-resolution wind velocity data. The method describes any specific gust by an amplitude and period and allows the detection of individual gusts in time using wavelet-analysis. The result of a full gust analysis using this method yields a so-called characteristic gust distribution for the respective wind velocity data, which can serve as a direct link to the physical impact a particular gust has on e.g. an aircraft.
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.
Johannes Schwenkel and Björn Maronga
Atmos. Chem. Phys., 19, 7165–7181, https://doi.org/10.5194/acp-19-7165-2019, https://doi.org/10.5194/acp-19-7165-2019, 2019
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In this paper we study the influence of the cloud microphysical treatments in high-resolution numerical simulation models on radiation fog events, which are still unsatisfactorily predicted in weather forecasts. Our results showed that the choice of which scheme is used can have a significant impact on the strength and life cycle of the fog.
Tom V. Kokkonen, Sue Grimmond, Sonja Murto, Huizhi Liu, Anu-Maija Sundström, and Leena Järvi
Atmos. Chem. Phys., 19, 7001–7017, https://doi.org/10.5194/acp-19-7001-2019, https://doi.org/10.5194/acp-19-7001-2019, 2019
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This is the first study to evaluate and correct the WATCH WFDEI reanalysis product in a highly polluted urban environment. It gives an important understanding of the uncertainties in reanalysis products in local-scale urban modelling in polluted environments and identifies and corrects the most important variables in hydrological modelling. This is also the first study to examine the effects of haze on the local-scale urban hydrological cycle.
Ina Tegen, David Neubauer, Sylvaine Ferrachat, Colombe Siegenthaler-Le Drian, Isabelle Bey, Nick Schutgens, Philip Stier, Duncan Watson-Parris, Tanja Stanelle, Hauke Schmidt, Sebastian Rast, Harri Kokkola, Martin Schultz, Sabine Schroeder, Nikos Daskalakis, Stefan Barthel, Bernd Heinold, and Ulrike Lohmann
Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019, https://doi.org/10.5194/gmd-12-1643-2019, 2019
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We describe a new version of the aerosol–climate model ECHAM–HAM and show tests of the model performance by comparing different aspects of the aerosol distribution with different datasets. The updated version of HAM contains improved descriptions of aerosol processes, including updated emission fields and cloud processes. While there are regional deviations between the model and observations, the model performs well overall.
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.
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.
Leena Järvi, Üllar Rannik, Tom V. Kokkonen, Mona Kurppa, Ari Karppinen, Rostislav D. Kouznetsov, Pekka Rantala, Timo Vesala, and Curtis R. Wood
Atmos. Meas. Tech., 11, 5421–5438, https://doi.org/10.5194/amt-11-5421-2018, https://doi.org/10.5194/amt-11-5421-2018, 2018
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Identical EC systems on two sides of a building in central Helsinki were used to assess the uncertainty of the vertical fluxes on the single measurement point from July 2013 to September 2015. Sampling at only one point yielded up to 12% underestimation in the cumulative carbon fluxes; for sensible and latent heat the respective values were up to 5 and 8%. The commonly used statistics, kurtosis and skewness, are not necessarily suitable for filtering out data in a densely built urban area.
Harri Kokkola, Thomas Kühn, Anton Laakso, Tommi Bergman, Kari E. J. Lehtinen, Tero Mielonen, Antti Arola, Scarlet Stadtler, Hannele Korhonen, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Ina Tegen, Colombe Siegenthaler-Le Drian, Martin G. Schultz, Isabelle Bey, Philip Stier, Nikos Daskalakis, Colette L. Heald, and Sami Romakkaniemi
Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, https://doi.org/10.5194/gmd-11-3833-2018, 2018
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In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.
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.
Scarlet Stadtler, Thomas Kühn, Sabine Schröder, Domenico Taraborrelli, Martin G. Schultz, and Harri Kokkola
Geosci. Model Dev., 11, 3235–3260, https://doi.org/10.5194/gmd-11-3235-2018, https://doi.org/10.5194/gmd-11-3235-2018, 2018
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Atmospheric aerosols interact with our climate system and have adverse health effects. Nevertheless, these particles are a source of uncertainty in climate projections and the formation process of secondary aerosols formed by organic gas-phase precursors is particularly not fully understood. In order to gain a deeper understanding of secondary organic aerosol formation, this model system explicitly represents gas-phase and aerosol formation processes. Finally, this allows for process discussion.
Robin G. Stevens, Katharina Loewe, Christopher Dearden, Antonios Dimitrelos, Anna Possner, Gesa K. Eirund, Tomi Raatikainen, Adrian A. Hill, Benjamin J. Shipway, Jonathan Wilkinson, Sami Romakkaniemi, Juha Tonttila, Ari Laaksonen, Hannele Korhonen, Paul Connolly, Ulrike Lohmann, Corinna Hoose, Annica M. L. Ekman, Ken S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, https://doi.org/10.5194/acp-18-11041-2018, 2018
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We perform a model intercomparison of summertime high Arctic clouds. Observed concentrations of aerosol particles necessary for cloud formation fell to extremely low values, coincident with a transition from cloudy to nearly cloud-free conditions. Previous analyses have suggested that at these low concentrations, the radiative properties of the clouds are determined primarily by these particle concentrations. The model results strongly support this hypothesis.
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.
Ian Boutle, Jeremy Price, Innocent Kudzotsa, Harri Kokkola, and Sami Romakkaniemi
Atmos. Chem. Phys., 18, 7827–7840, https://doi.org/10.5194/acp-18-7827-2018, https://doi.org/10.5194/acp-18-7827-2018, 2018
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Aerosol processes are a key mechanism in the development of fog. Poor representation of aerosol–fog interaction can result in large biases in fog forecasts, such as surface temperatures which are too high and fog which is too deep and long lived. A relatively simple representation of aerosol–fog interaction can actually lead to significant improvements in forecasting. Aerosol–fog interaction can have a large effect on the climate system but is poorly represented in climate models.
Martin G. Schultz, Scarlet Stadtler, Sabine Schröder, Domenico Taraborrelli, Bruno Franco, Jonathan Krefting, Alexandra Henrot, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Colombe Siegenthaler-Le Drian, Sebastian Wahl, Harri Kokkola, Thomas Kühn, Sebastian Rast, Hauke Schmidt, Philip Stier, Doug Kinnison, Geoffrey S. Tyndall, John J. Orlando, and Catherine Wespes
Geosci. Model Dev., 11, 1695–1723, https://doi.org/10.5194/gmd-11-1695-2018, https://doi.org/10.5194/gmd-11-1695-2018, 2018
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The chemistry–climate model ECHAM-HAMMOZ contains a detailed representation of tropospheric and stratospheric reactive chemistry and state-of-the-art parameterizations of aerosols. It thus allows for detailed investigations of chemical processes in the climate system. Evaluation of the model with various observational data yields good results, but the model has a tendency to produce too much OH in the tropics. This highlights the important interplay between atmospheric chemistry and dynamics.
Lukas Pichelstorfer, Dominik Stolzenburg, John Ortega, Thomas Karl, Harri Kokkola, Anton Laakso, Kari E. J. Lehtinen, James N. Smith, Peter H. McMurry, and Paul M. Winkler
Atmos. Chem. Phys., 18, 1307–1323, https://doi.org/10.5194/acp-18-1307-2018, https://doi.org/10.5194/acp-18-1307-2018, 2018
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Quantification of new particle formation as a source of atmospheric aerosol is clearly of importance for climate and health aspects. In our new study we developed two analysis methods that allow retrieval of nanoparticle growth dynamics at much higher precision than it was possible so far. Our results clearly demonstrate that growth rates show much more variation than is currently known and suggest that the Kelvin effect governs growth in the sub-10 nm size range.
Mikko Auvinen, Leena Järvi, Antti Hellsten, Üllar Rannik, and Timo Vesala
Geosci. Model Dev., 10, 4187–4205, https://doi.org/10.5194/gmd-10-4187-2017, https://doi.org/10.5194/gmd-10-4187-2017, 2017
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Correct spatial interpretation of a micrometeorological measurement requires the determination of its effective source area, or footprint. In urban areas the use of analytical models becomes highly questionable. This work introduces a computational methodology that enables the generation of footprints for complex urban sites. The methodology is based on conducting high-resolution flow and particle analysis on a model that features a detailed topographic description of a real city environment.
John Backman, Curtis R. Wood, Mikko Auvinen, Leena Kangas, Hanna Hannuniemi, Ari Karppinen, and Jaakko Kukkonen
Geosci. Model Dev., 10, 3793–3803, https://doi.org/10.5194/gmd-10-3793-2017, https://doi.org/10.5194/gmd-10-3793-2017, 2017
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Meteorological input parameters for urban- and local-scale dispersion models can be derived from meteorological observations. This study presents a sensitivity analysis of a meteorological model that utilises readily available meteorological data to derive specific parameters required to model the atmospheric dispersion of pollutants. The study shows that wind speed is the most fundamental meteorological input parameter followed by solar radiation.
Jaroslav Resler, Pavel Krč, Michal Belda, Pavel Juruš, Nina Benešová, Jan Lopata, Ondřej Vlček, Daša Damašková, Kryštof Eben, Přemysl Derbek, Björn Maronga, and Farah Kanani-Sühring
Geosci. Model Dev., 10, 3635–3659, https://doi.org/10.5194/gmd-10-3635-2017, https://doi.org/10.5194/gmd-10-3635-2017, 2017
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A realistic numerical modelling of urban climate still poses a serious challenge. The paper describes a new urban surface model (USM), integrated into large-eddy simulation model PALM. The USM covers the most important urban canopy processes (e.g. radiation, energy balance on surfaces, thermal diffusion). The model was tested in the real conditions of a city and shows good agreement with observations. The USM is optimized for high-performance computing systems and is freely available.
Guilherme Martins Pereira, Kimmo Teinilä, Danilo Custódio, Aldenor Gomes Santos, Huang Xian, Risto Hillamo, Célia A. Alves, Jailson Bittencourt de Andrade, Gisele Olímpio da Rocha, Prashant Kumar, Rajasekhar Balasubramanian, Maria de Fátima Andrade, and Pérola de Castro Vasconcellos
Atmos. Chem. Phys., 17, 11943–11969, https://doi.org/10.5194/acp-17-11943-2017, https://doi.org/10.5194/acp-17-11943-2017, 2017
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São Paulo, Brazil, has relatively relaxed regulations for ambient air pollution standards and often presents high air pollution levels due to emissions of airborne particles from local sources and long-range transport of biomass burning smoke. High risks associated with particulate matter exposure were observed in most samples. The results highlighted the contribution of vehicular emissions and the significant input from biomass combustion in the dry season.
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.
Sami Romakkaniemi, Zubair Maalick, Antti Hellsten, Antti Ruuskanen, Olli Väisänen, Irshad Ahmad, Juha Tonttila, Santtu Mikkonen, Mika Komppula, and Thomas Kühn
Atmos. Chem. Phys., 17, 7955–7964, https://doi.org/10.5194/acp-17-7955-2017, https://doi.org/10.5194/acp-17-7955-2017, 2017
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Surface topography affects aerosol–cloud interactions in boundary layer clouds. Local topography effects should be screened out from in situ observations before results can be generalised into a larger scale. Here we present modelling and observational results from a measurement station residing in a 75 m tower on top of a 150 m hill, and analyse how landscape affects the cloud formation, and which factors should be taken into account when aerosol effect on cloud droplet formation is studied.
Anton Laakso, Hannele Korhonen, Sami Romakkaniemi, and Harri Kokkola
Atmos. Chem. Phys., 17, 6957–6974, https://doi.org/10.5194/acp-17-6957-2017, https://doi.org/10.5194/acp-17-6957-2017, 2017
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Based on simulations, equatorial stratospheric sulfur injections have shown to be an efficient strategy to counteract ongoing global warming. However, equatorial injections would result in relatively larger cooling in low latitudes than in high latitudes. This together with greenhouse-gas-induced warming would lead to cooling in the Equator and warming in the high latitudes. Results of this study show that a more optimal cooling effect is achieved by varying the injection area seasonally.
S. Wittke, K. Karila, E. Puttonen, A. Hellsten, M. Auvinen, and M. Karjalainen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 425–431, https://doi.org/10.5194/isprs-archives-XLII-1-W1-425-2017, https://doi.org/10.5194/isprs-archives-XLII-1-W1-425-2017, 2017
Antti Arola, Thomas F. Eck, Harri Kokkola, Mikko R. A. Pitkänen, and Sami Romakkaniemi
Atmos. Chem. Phys., 17, 5991–6001, https://doi.org/10.5194/acp-17-5991-2017, https://doi.org/10.5194/acp-17-5991-2017, 2017
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One of the issues that hinder the measurement-based assessment of aerosol–cloud interactions by remote sensing methods is that typically aerosols and clouds cannot be measured simultaneously by passive remote sensing methods. AERONET includes the SDA product that provides the fine-mode AOD also in mixed cloud–aerosol observations. These measurements have not yet been fully exploited in studies of aerosol–cloud interactions. We applied SDA for this kind of analysis.
Juha Tonttila, Zubair Maalick, Tomi Raatikainen, Harri Kokkola, Thomas Kühn, and Sami Romakkaniemi
Geosci. Model Dev., 10, 169–188, https://doi.org/10.5194/gmd-10-169-2017, https://doi.org/10.5194/gmd-10-169-2017, 2017
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Novel techniques for modelling the aerosol–cloud interactions are implemented in a cloud-resolving model. The new methods improve the representation of the poorly constrained effects of cloud processing, precipitation and the wet removal of particles on the aerosol population and the associated feedbacks. The detailed representation of these processes yields more realistic simulation of the evolution of boundary layer clouds and fogs, as compared to results obtained using more simple methods.
Carlos Eduardo Souto-Oliveira, Maria de Fátima Andrade, Prashant Kumar, Fábio Juliano da Silva Lopes, Marly Babinski, and Eduardo Landulfo
Atmos. Chem. Phys., 16, 14635–14656, https://doi.org/10.5194/acp-16-14635-2016, https://doi.org/10.5194/acp-16-14635-2016, 2016
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The Metropolitan Area of São Paulo is the biggest megacity of South America, with over 20 million inhabitants. In recent years, the region has been facing a modification in rain patterns. In this study, we evaluated the effects of local and remote sources of air pollution on cloud-condensation nuclei activation properties. Our results showed that the local vehicular traffic emission products presented more negative effects on cloud-condensation nuclei activation than the remote sources.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Ivan Mammarella, Olli Peltola, Annika Nordbo, Leena Järvi, and Üllar Rannik
Atmos. Meas. Tech., 9, 4915–4933, https://doi.org/10.5194/amt-9-4915-2016, https://doi.org/10.5194/amt-9-4915-2016, 2016
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In this study we have performed an inter-comparison between EddyUH and EddyPro, two public and commonly used software packages for eddy covariance data processing and calculation. The aims are to estimate the flux uncertainty due to the use of different software packages, and to assess the most critical processing steps, determining the largest deviations in the calculated fluxes. We focus not only on water vapour and carbon dioxide fluxes, but also on the methane flux.
Andrey Glazunov, Üllar Rannik, Victor Stepanenko, Vasily Lykosov, Mikko Auvinen, Timo Vesala, and Ivan Mammarella
Geosci. Model Dev., 9, 2925–2949, https://doi.org/10.5194/gmd-9-2925-2016, https://doi.org/10.5194/gmd-9-2925-2016, 2016
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Large-eddy simulation (LES) and Lagrangian stochastic modeling of passive particle dispersion were applied to the scalar flux footprint determination in the stable atmospheric boundary layer. The footprint functions obtained in LES were compared with the functions calculated with the use of first-order single-particle Lagrangian stochastic models (LSMs) and zeroth-order Lagrangian stochastic models - the random displacement models (RDMs).
Tero Mielonen, Anca Hienola, Thomas Kühn, Joonas Merikanto, Antti Lipponen, Tommi Bergman, Hannele Korhonen, Pekka Kolmonen, Larisa Sogacheva, Darren Ghent, Antti Arola, Gerrit de Leeuw, and Harri Kokkola
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-625, https://doi.org/10.5194/acp-2016-625, 2016
Revised manuscript not accepted
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We studied the temperature dependence of AOD and its radiative effects over the southeastern US. We used spaceborne observations of AOD, LST and tropospheric NO2 with simulations of ECHAM-HAMMOZ. The level of AOD in this region is governed by anthropogenic emissions but the temperature dependency is most likely caused by BVOC emissions. According to the observations and simulations, the regional clear-sky DRE for biogenic aerosols is −0.43 ± 0.88 W/m2/K and −0.86 ± 0.06 W/m2/K, respectively.
Jani Huttunen, Harri Kokkola, Tero Mielonen, Mika Esa Juhani Mononen, Antti Lipponen, Juha Reunanen, Anders Vilhelm Lindfors, Santtu Mikkonen, Kari Erkki Juhani Lehtinen, Natalia Kouremeti, Alkiviadis Bais, Harri Niska, and Antti Arola
Atmos. Chem. Phys., 16, 8181–8191, https://doi.org/10.5194/acp-16-8181-2016, https://doi.org/10.5194/acp-16-8181-2016, 2016
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For a good estimate of the current forcing by anthropogenic aerosols, knowledge in past is needed. One option to lengthen time series is to retrieve aerosol optical depth from solar radiation measurements. We have evaluated several methods for this task. Most of the methods produce aerosol optical depth estimates with a good accuracy. However, machine learning methods seem to be the most applicable not to produce any systematic biases, since they do not need constrain the aerosol properties.
Pekka Rantala, Leena Järvi, Risto Taipale, Terhi K. Laurila, Johanna Patokoski, Maija K. Kajos, Mona Kurppa, Sami Haapanala, Erkki Siivola, Tuukka Petäjä, Taina M. Ruuskanen, and Janne Rinne
Atmos. Chem. Phys., 16, 7981–8007, https://doi.org/10.5194/acp-16-7981-2016, https://doi.org/10.5194/acp-16-7981-2016, 2016
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Fluxes of volatile organic compounds (VOCs) were measured above an urban landscape in Helsinki, northern Europe. We found that traffic was a major source for many oxygenated and aromatic VOCs, whereas isoprene originated mostly from the urban vegetation. Overall, the VOC fluxes were quite small in comparison with the earlier urban VOC flux measurements.
N. I. Kristiansen, A. Stohl, D. J. L. Olivié, B. Croft, O. A. Søvde, H. Klein, T. Christoudias, D. Kunkel, S. J. Leadbetter, Y. H. Lee, K. Zhang, K. Tsigaridis, T. Bergman, N. Evangeliou, H. Wang, P.-L. Ma, R. C. Easter, P. J. Rasch, X. Liu, G. Pitari, G. Di Genova, S. Y. Zhao, Y. Balkanski, S. E. Bauer, G. S. Faluvegi, H. Kokkola, R. V. Martin, J. R. Pierce, M. Schulz, D. Shindell, H. Tost, and H. Zhang
Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, https://doi.org/10.5194/acp-16-3525-2016, 2016
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Processes affecting aerosol removal from the atmosphere are not fully understood. In this study we investigate to what extent atmospheric transport models can reproduce observed loss of aerosols. We compare measurements of radioactive isotopes, that attached to ambient sulfate aerosols during the 2011 Fukushima nuclear accident, to 19 models using identical emissions. Results indicate aerosol removal that is too fast in most models, and apply to aerosols that have undergone long-range transport.
Zak Kipling, Philip Stier, Colin E. Johnson, Graham W. Mann, Nicolas Bellouin, Susanne E. Bauer, Tommi Bergman, Mian Chin, Thomas Diehl, Steven J. Ghan, Trond Iversen, Alf Kirkevåg, Harri Kokkola, Xiaohong Liu, Gan Luo, Twan van Noije, Kirsty J. Pringle, Knut von Salzen, Michael Schulz, Øyvind Seland, Ragnhild B. Skeie, Toshihiko Takemura, Kostas Tsigaridis, and Kai Zhang
Atmos. Chem. Phys., 16, 2221–2241, https://doi.org/10.5194/acp-16-2221-2016, https://doi.org/10.5194/acp-16-2221-2016, 2016
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The vertical distribution of atmospheric aerosol is an important factor in its effects on climate. In this study we use a sophisticated model of the many interacting processes affecting aerosol in the atmosphere to show that the vertical distribution is typically dominated by only a few of these processes. Constraining these physical processes may help to reduce the large differences between models. However, the important processes are not always the same for different types of aerosol.
A Vara-Vela, M. F. Andrade, P. Kumar, R. Y. Ynoue, and A. G. Muñoz
Atmos. Chem. Phys., 16, 777–797, https://doi.org/10.5194/acp-16-777-2016, https://doi.org/10.5194/acp-16-777-2016, 2016
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This study provides a first step to understand the impact of vehicular emissions on the formation of secondary particles as well as the feedback between these particles and meteorology in the Sao Paulo Metropolitan Area (SPMA). Among the main research findings are:
- The emissions of primary gases from vehicles led to a production between 20 and 30 % due to new particles formation in relation to the total mass concentration PM2.5 in the downtown SPMA.
A. Laakso, H. Kokkola, A.-I. Partanen, U. Niemeier, C. Timmreck, K. E. J. Lehtinen, H. Hakkarainen, and H. Korhonen
Atmos. Chem. Phys., 16, 305–323, https://doi.org/10.5194/acp-16-305-2016, https://doi.org/10.5194/acp-16-305-2016, 2016
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We have studied the impacts of a volcanic eruption during solar radiation management (SRM) using an aerosol-climate model ECHAM5-HAM-SALSA and an Earth system model MPI-ESM. A volcanic eruption during stratospheric sulfur geoengineering would lead to larger particles and smaller amount of new particles than if an volcano erupts in normal atmospheric conditions. Thus, volcanic eruption during SRM would lead to only a small additional cooling which would last for a significantly shorter period.
A. Arola, G. L. Schuster, M. R. A. Pitkänen, O. Dubovik, H. Kokkola, A. V. Lindfors, T. Mielonen, T. Raatikainen, S. Romakkaniemi, S. N. Tripathi, and H. Lihavainen
Atmos. Chem. Phys., 15, 12731–12740, https://doi.org/10.5194/acp-15-12731-2015, https://doi.org/10.5194/acp-15-12731-2015, 2015
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There have been relatively few measurement-based estimates for the direct radiative effect of brown carbon so far. This is first time that the direct radiative effect of brown carbon is estimated by exploiting the AERONET-retrieved imaginary indices. We estimated it for four sites in the Indo-Gangetic Plain: Karachi, Lahore,
Kanpur and Gandhi College.
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.
B. Maronga, M. Gryschka, R. Heinze, F. Hoffmann, F. Kanani-Sühring, M. Keck, K. Ketelsen, M. O. Letzel, M. Sühring, and S. Raasch
Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, https://doi.org/10.5194/gmd-8-2515-2015, 2015
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The paper gives a detailed description of the PArallelized Large-eddy simulation Model (PALM) version 4.0 for the simulation of turbulent atmospheric and oceanic boundary layer flows. The model is optimized for use on massively parallel computer architectures and has been applied for various boundary-layer research studies over the last 15 years by various work groups all over the world. Besides the model description, we outline past PALM applications and also discuss future perspectives.
M. A. Thomas, M. Kahnert, C. Andersson, H. Kokkola, U. Hansson, C. Jones, J. Langner, and A. Devasthale
Geosci. Model Dev., 8, 1885–1898, https://doi.org/10.5194/gmd-8-1885-2015, https://doi.org/10.5194/gmd-8-1885-2015, 2015
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We have showed that a coupled modelling system is beneficial in the sense that more complex processes can be included to better represent the aerosol processes starting from their formation, their interactions with clouds and provide better estimate of radiative forcing. Using this model set up, we estimated an annual mean 'indirect' radiative forcing of -0.64W/m2. This means that aerosols, solely by their capability of altering the microphysical properties of clouds can cool the Earth system.
J. Tonttila, E. J. O'Connor, A. Hellsten, A. Hirsikko, C. O'Dowd, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 5873–5885, https://doi.org/10.5194/acp-15-5873-2015, https://doi.org/10.5194/acp-15-5873-2015, 2015
C. Andersson, R. Bergström, C. Bennet, L. Robertson, M. Thomas, H. Korhonen, K. E. J. Lehtinen, and H. Kokkola
Geosci. Model Dev., 8, 171–189, https://doi.org/10.5194/gmd-8-171-2015, https://doi.org/10.5194/gmd-8-171-2015, 2015
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We have integrated the sectional aerosol dynamics model SALSA into the European scale chemistry-transport model MATCH. The combined model reproduces observed higher particle number concentration (PNCs) in central Europe and lower concentrations in remote regions; however, the total PNC is underestimated. The low nucleation rate coefficient used in this study is an important reason for the underestimation.
J. Tonttila, H. Järvinen, and P. Räisänen
Atmos. Chem. Phys., 15, 703–714, https://doi.org/10.5194/acp-15-703-2015, https://doi.org/10.5194/acp-15-703-2015, 2015
E. M. Dunne, S. Mikkonen, H. Kokkola, and H. Korhonen
Atmos. Chem. Phys., 14, 13631–13642, https://doi.org/10.5194/acp-14-13631-2014, https://doi.org/10.5194/acp-14-13631-2014, 2014
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Marine clouds have a strong effect on the Earth's radiative balance. One proposed climate feedback is that, in a warming climate, marine aerosol emissions will change due to changing wind speeds. We have examined the processes that affect aerosol emissions and removal over 15 years, and high-temporal-resolution output over 2 months. We conclude that wind trends are unlikely to cause a strong feedback in marine regions, but changes in removal processes or transport from continental regions may.
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.
A.-I. Partanen, E. M. Dunne, T. Bergman, A. Laakso, H. Kokkola, J. Ovadnevaite, L. Sogacheva, D. Baisnée, J. Sciare, A. Manders, C. O'Dowd, G. de Leeuw, and H. Korhonen
Atmos. Chem. Phys., 14, 11731–11752, https://doi.org/10.5194/acp-14-11731-2014, https://doi.org/10.5194/acp-14-11731-2014, 2014
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New parameterizations for the sea spray aerosol source flux and its organic fraction were incorporated into a global aerosol-climate model. The emissions of sea salt were considerably less than previous estimates. This study demonstrates that sea spray aerosol may actually decrease the number of cloud droplets, which has a warming effect on climate. Overall, sea spray aerosol was predicted to have a global cooling effect due to the scattering of solar radiation from sea spray aerosol particles.
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
J. F. Peng, M. Hu, Z. B. Wang, X. F. Huang, P. Kumar, Z. J. Wu, S. Guo, D. L. Yue, D. J. Shang, Z. Zheng, and L. Y. He
Atmos. Chem. Phys., 14, 10249–10265, https://doi.org/10.5194/acp-14-10249-2014, https://doi.org/10.5194/acp-14-10249-2014, 2014
S. V. Henriksson, J.-P. Pietikäinen, A.-P. Hyvärinen, P. Räisänen, K. Kupiainen, J. Tonttila, R. Hooda, H. Lihavainen, D. O'Donnell, L. Backman, Z. Klimont, and A. Laaksonen
Atmos. Chem. Phys., 14, 10177–10192, https://doi.org/10.5194/acp-14-10177-2014, https://doi.org/10.5194/acp-14-10177-2014, 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. Järvi, C. S. B. Grimmond, M. Taka, A. Nordbo, H. Setälä, and I. B. Strachan
Geosci. Model Dev., 7, 1691–1711, https://doi.org/10.5194/gmd-7-1691-2014, https://doi.org/10.5194/gmd-7-1691-2014, 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
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 2014
H. Kokkola, P. Yli-Pirilä, M. Vesterinen, H. Korhonen, H. Keskinen, S. Romakkaniemi, L. Hao, A. Kortelainen, J. Joutsensaari, D. R. Worsnop, A. Virtanen, and K. E. J. Lehtinen
Atmos. Chem. Phys., 14, 1689–1700, https://doi.org/10.5194/acp-14-1689-2014, https://doi.org/10.5194/acp-14-1689-2014, 2014
T. Korhola, H. Kokkola, H. Korhonen, A.-I. Partanen, A. Laaksonen, K. E. J. Lehtinen, and S. Romakkaniemi
Geosci. Model Dev., 7, 161–174, https://doi.org/10.5194/gmd-7-161-2014, https://doi.org/10.5194/gmd-7-161-2014, 2014
A. Lipponen, V. Kolehmainen, S. Romakkaniemi, and H. Kokkola
Geosci. Model Dev., 6, 2087–2098, https://doi.org/10.5194/gmd-6-2087-2013, https://doi.org/10.5194/gmd-6-2087-2013, 2013
A. I. Partanen, A. Laakso, A. Schmidt, H. Kokkola, T. Kuokkanen, J.-P. Pietikäinen, V.-M. Kerminen, K. E. J. Lehtinen, L. Laakso, and H. Korhonen
Atmos. Chem. Phys., 13, 12059–12071, https://doi.org/10.5194/acp-13-12059-2013, https://doi.org/10.5194/acp-13-12059-2013, 2013
J. Tonttila, P. Räisänen, and H. Järvinen
Atmos. Chem. Phys., 13, 7551–7565, https://doi.org/10.5194/acp-13-7551-2013, https://doi.org/10.5194/acp-13-7551-2013, 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
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
Related subject area
Atmospheric sciences
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
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
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
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.
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.
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229, https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
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This study presents the first comprehensive evaluation of unstructured meshes using the iAMAS model over Antarctica, encompassing both surface and upper-level meteorological fields. Comparison with ERA5 and observational data reveals that the iAMAS model performs well in simulating the Antarctic atmosphere; iAMAS demonstrates comparable, and in some cases superior, performance in simulating temperature and wind speed in East Antarctica when compared to ERA5.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
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Short summary
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.
This paper describes the implementation of a sectional aerosol module, SALSA, into the PALM...
