Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-675-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-675-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
02 Feb 2021
Model description paper |
| 02 Feb 2021
| 02 Feb 2021
PyCHAM (v2.1.1): a Python box model for simulating aerosol chambers
Simon Patrick O'Meara
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, University of Manchester, Manchester, M13 9PL, UK
Shuxuan Xu
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
David Topping
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
M. Rami Alfarra
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
National Centre for Atmospheric Science, University of Manchester, Manchester, M13 9PL, UK
Gerard Capes
Research Computing Services, University of Manchester, Manchester, M13 9PL, UK
Douglas Lowe
Research Computing Services, University of Manchester, Manchester, M13 9PL, UK
Yunqi Shao
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
Gordon McFiggans
CORRESPONDING AUTHOR
Department for Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
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Yunqi Shao, Yu Wang, Mao Du, Aristeidis Voliotis, M. Rami Alfarra, Simon P. O'Meara, S. Fiona Turner, and Gordon McFiggans
Atmos. Meas. Tech., 15, 539–559, https://doi.org/10.5194/amt-15-539-2022, https://doi.org/10.5194/amt-15-539-2022, 2022
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Dawei Hu, M. Rami Alfarra, Kate Szpek, Justin M. Langridge, Michael I. Cotterell, Claire Belcher, Ian Rule, Zixia Liu, Chenjie Yu, Yunqi Shao, Aristeidis Voliotis, Mao Du, Brett Smith, Greg Smallwood, Prem Lobo, Dantong Liu, Jim M. Haywood, Hugh Coe, and James D. Allan
Atmos. Chem. Phys., 21, 16161–16182, https://doi.org/10.5194/acp-21-16161-2021, https://doi.org/10.5194/acp-21-16161-2021, 2021
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Here, we developed new techniques for investigating these properties in the laboratory and applied these to BC and BrC from different sources, including diesel exhaust, inverted propane flame and wood combustion. These have allowed us to quantify the changes in shape and chemical composition of different soots according to source and variables such as the moisture content of wood.
Aristeidis Voliotis, Yu Wang, Yunqi Shao, Mao Du, Thomas J. Bannan, Carl J. Percival, Spyros N. Pandis, M. Rami Alfarra, and Gordon McFiggans
Atmos. Chem. Phys., 21, 14251–14273, https://doi.org/10.5194/acp-21-14251-2021, https://doi.org/10.5194/acp-21-14251-2021, 2021
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Secondary organic aerosol (SOA) formation from mixtures of volatile precursors can be affected by the molecular interactions of the products. Composition and volatility measurements of SOA formed from mixtures of anthropogenic and biogenic precursors reveal processes that can increase or decrease the SOA volatility. The unique products of the mixture were more oxygenated and less volatile than those from either precursor. Analytical context is provided to explore the SOA volatility in mixtures.
Ernesto Reyes-Villegas, Upasana Panda, Eoghan Darbyshire, James M. Cash, Rutambhara Joshi, Ben Langford, Chiara F. Di Marco, Neil J. Mullinger, Mohammed S. Alam, Leigh R. Crilley, Daniel J. Rooney, W. Joe F. Acton, Will Drysdale, Eiko Nemitz, Michael Flynn, Aristeidis Voliotis, Gordon McFiggans, Hugh Coe, James Lee, C. Nicholas Hewitt, Mathew R. Heal, Sachin S. Gunthe, Tuhin K. Mandal, Bhola R. Gurjar, Shivani, Ranu Gadi, Siddhartha Singh, Vijay Soni, and James D. Allan
Atmos. Chem. Phys., 21, 11655–11667, https://doi.org/10.5194/acp-21-11655-2021, https://doi.org/10.5194/acp-21-11655-2021, 2021
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Yu Wang, Aristeidis Voliotis, Yunqi Shao, Taomou Zong, Xiangxinyue Meng, Mao Du, Dawei Hu, Ying Chen, Zhijun Wu, M. Rami Alfarra, and Gordon McFiggans
Atmos. Chem. Phys., 21, 11303–11316, https://doi.org/10.5194/acp-21-11303-2021, https://doi.org/10.5194/acp-21-11303-2021, 2021
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Langwen Huang and David Topping
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Michael Priestley, Thomas J. Bannan, Michael Le Breton, Stephen D. Worrall, Sungah Kang, Iida Pullinen, Sebastian Schmitt, Ralf Tillmann, Einhard Kleist, Defeng Zhao, Jürgen Wildt, Olga Garmash, Archit Mehra, Asan Bacak, Dudley E. Shallcross, Astrid Kiendler-Scharr, Åsa M. Hallquist, Mikael Ehn, Hugh Coe, Carl J. Percival, Mattias Hallquist, Thomas F. Mentel, and Gordon McFiggans
Atmos. Chem. Phys., 21, 3473–3490, https://doi.org/10.5194/acp-21-3473-2021, https://doi.org/10.5194/acp-21-3473-2021, 2021
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Douglas Morrison, Ian Crawford, Nicholas Marsden, Michael Flynn, Katie Read, Luis Neves, Virginia Foot, Paul Kaye, Warren Stanley, Hugh Coe, David Topping, and Martin Gallagher
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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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David Topping, David Watts, Hugh Coe, James Evans, Thomas J. Bannan, Douglas Lowe, Caroline Jay, and Jonathan W. Taylor
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Publication in GMD not foreseen
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Petroc D. Shelley, Thomas J. Bannan, Stephen D. Worrall, M. Rami Alfarra, Ulrich K. Krieger, Carl J. Percival, Arthur Garforth, and David Topping
Atmos. Chem. Phys., 20, 8293–8314, https://doi.org/10.5194/acp-20-8293-2020, https://doi.org/10.5194/acp-20-8293-2020, 2020
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Natalie R. Gervasi, David O. Topping, and Andreas Zuend
Atmos. Chem. Phys., 20, 2987–3008, https://doi.org/10.5194/acp-20-2987-2020, https://doi.org/10.5194/acp-20-2987-2020, 2020
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Organic aerosols have been shown to exist often in a semi-solid or amorphous, glassy state. Highly viscous particles behave differently than their well-mixed liquid analogues with consequences for a variety of aerosol processes. Here, we introduce a new predictive mixture viscosity model called AIOMFAC-VISC. It enables us to predict the viscosity of aqueous organic mixtures as a function of temperature and chemical composition, covering the full range of liquid, semi-solid, and glassy states.
Parya Broomandi, Xueyu Geng, Weisi Guo, Jong Ryeol Kim, Alessio Pagani, and David Topping
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-342, https://doi.org/10.5194/gmd-2019-342, 2020
Revised manuscript not accepted
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As a result of our novel graph-based reduced modeling, we are able to represent high-dimensional knowledge into a causal inference and stability framework.
Yu Wang, Ying Chen, Zhijun Wu, Dongjie Shang, Yuxuan Bian, Zhuofei Du, Sebastian H. Schmitt, Rong Su, Georgios I. Gkatzelis, Patrick Schlag, Thorsten Hohaus, Aristeidis Voliotis, Keding Lu, Limin Zeng, Chunsheng Zhao, M. Rami Alfarra, Gordon McFiggans, Alfred Wiedensohler, Astrid Kiendler-Scharr, Yuanhang Zhang, and Min Hu
Atmos. Chem. Phys., 20, 2161–2175, https://doi.org/10.5194/acp-20-2161-2020, https://doi.org/10.5194/acp-20-2161-2020, 2020
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Severe haze events, with high particulate nitrate (pNO3−) burden, frequently prevail in Beijing. In this study, we demonstrate a mutual-promotion effect between aerosol water uptake and pNO3− formation backed up by theoretical calculations and field observations throughout a typical pNO3−-dominated haze event in Beijing wintertime. This self-amplified mutual-promotion effect between aerosol water content and particulate nitrate can rapidly deteriorate air quality and degrade visibility.
Kathryn Fowler, Paul Connolly, and David Topping
Atmos. Chem. Phys., 20, 683–698, https://doi.org/10.5194/acp-20-683-2020, https://doi.org/10.5194/acp-20-683-2020, 2020
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Observations of low–temperature cirrus clouds have found unexpectedly low ice crystal numbers and high supersaturations, suggesting an incomplete understanding of the freezing mechanisms under these conditions. The existence of viscous organic aerosol has offered alternative ice nucleation pathways, which have been observed in laboratory studies. We have developed the first cloud parcel model to investigate the effect of viscosity on ice nucleation.
Olga Garmash, Matti P. Rissanen, Iida Pullinen, Sebastian Schmitt, Oskari Kausiala, Ralf Tillmann, Defeng Zhao, Carl Percival, Thomas J. Bannan, Michael Priestley, Åsa M. Hallquist, Einhard Kleist, Astrid Kiendler-Scharr, Mattias Hallquist, Torsten Berndt, Gordon McFiggans, Jürgen Wildt, Thomas F. Mentel, and Mikael Ehn
Atmos. Chem. Phys., 20, 515–537, https://doi.org/10.5194/acp-20-515-2020, https://doi.org/10.5194/acp-20-515-2020, 2020
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Highly oxygenated organic molecules (HOMs) facilitate aerosol formation in the atmosphere. Using NO3− chemical ionization mass spectrometry we investigated HOM composition and yield in oxidation of aromatic compounds at different reactant concentrations, in the presence of NOx and seed aerosol. Higher OH concentrations increased HOM yield, suggesting multiple oxidation steps, and affected HOM composition, potentially explaining in part discrepancies in published secondary organic aerosol yields.
Ying Chen, Oliver Wild, Edmund Ryan, Saroj Kumar Sahu, Douglas Lowe, Scott Archer-Nicholls, Yu Wang, Gordon McFiggans, Tabish Ansari, Vikas Singh, Ranjeet S. Sokhi, Alex Archibald, and Gufran Beig
Atmos. Chem. Phys., 20, 499–514, https://doi.org/10.5194/acp-20-499-2020, https://doi.org/10.5194/acp-20-499-2020, 2020
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PM2.5 and O3 are two major air pollutants. Some mitigation strategies focusing on reducing PM2.5 may lead to substantial increase in O3. We use statistical emulation combined with atmospheric transport model to perform thousands of sensitivity numerical studies to identify the major sources of PM2.5 and O3 and to develop strategies targeted at both pollutants. Our scientific evidence suggests that regional coordinated emission control is required to mitigate PM2.5 whilst preventing O3 increase.
Laura Kiely, Dominick V. Spracklen, Christine Wiedinmyer, Luke Conibear, Carly L. Reddington, Scott Archer-Nicholls, Douglas Lowe, Stephen R. Arnold, Christoph Knote, Md Firoz Khan, Mohd Talib Latif, Mikinori Kuwata, Sri Hapsari Budisulistiorini, and Lailan Syaufina
Atmos. Chem. Phys., 19, 11105–11121, https://doi.org/10.5194/acp-19-11105-2019, https://doi.org/10.5194/acp-19-11105-2019, 2019
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In 2015, a large fire episode occurred in Indonesia, reducing air quality. Fires occurred predominantly on peatland, where large uncertainties are associated with emissions. Current fire emissions datasets underestimate peat fire emissions. We created new fire emissions data, with data specific to Indonesian peat fires. Using these emissions in simulations of particulate matter and aerosol optical depth shows an improvement over simulations using current data, when compared with observations.
Zongbo Shi, Tuan Vu, Simone Kotthaus, Roy M. Harrison, Sue Grimmond, Siyao Yue, Tong Zhu, James Lee, Yiqun Han, Matthias Demuzere, Rachel E. Dunmore, Lujie Ren, Di Liu, Yuanlin Wang, Oliver Wild, James Allan, W. Joe Acton, Janet Barlow, Benjamin Barratt, David Beddows, William J. Bloss, Giulia Calzolai, David Carruthers, David C. Carslaw, Queenie Chan, Lia Chatzidiakou, Yang Chen, Leigh Crilley, Hugh Coe, Tie Dai, Ruth Doherty, Fengkui Duan, Pingqing Fu, Baozhu Ge, Maofa Ge, Daobo Guan, Jacqueline F. Hamilton, Kebin He, Mathew Heal, Dwayne Heard, C. Nicholas Hewitt, Michael Hollaway, Min Hu, Dongsheng Ji, Xujiang Jiang, Rod Jones, Markus Kalberer, Frank J. Kelly, Louisa Kramer, Ben Langford, Chun Lin, Alastair C. Lewis, Jie Li, Weijun Li, Huan Liu, Junfeng Liu, Miranda Loh, Keding Lu, Franco Lucarelli, Graham Mann, Gordon McFiggans, Mark R. Miller, Graham Mills, Paul Monk, Eiko Nemitz, Fionna O'Connor, Bin Ouyang, Paul I. Palmer, Carl Percival, Olalekan Popoola, Claire Reeves, Andrew R. Rickard, Longyi Shao, Guangyu Shi, Dominick Spracklen, David Stevenson, Yele Sun, Zhiwei Sun, Shu Tao, Shengrui Tong, Qingqing Wang, Wenhua Wang, Xinming Wang, Xuejun Wang, Zifang Wang, Lianfang Wei, Lisa Whalley, Xuefang Wu, Zhijun Wu, Pinhua Xie, Fumo Yang, Qiang Zhang, Yanli Zhang, Yuanhang Zhang, and Mei Zheng
Atmos. Chem. Phys., 19, 7519–7546, https://doi.org/10.5194/acp-19-7519-2019, https://doi.org/10.5194/acp-19-7519-2019, 2019
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APHH-Beijing is a collaborative international research programme to study the sources, processes and health effects of air pollution in Beijing. This introduction to the special issue provides an overview of (i) the APHH-Beijing programme, (ii) the measurement and modelling activities performed as part of it and (iii) the air quality and meteorological conditions during joint intensive field campaigns as a core activity within APHH-Beijing.
Eoghan Darbyshire, William T. Morgan, James D. Allan, Dantong Liu, Michael J. Flynn, James R. Dorsey, Sebastian J. O'Shea, Douglas Lowe, Kate Szpek, Franco Marenco, Ben T. Johnson, Stephane Bauguitte, Jim M. Haywood, Joel F. Brito, Paulo Artaxo, Karla M. Longo, and Hugh Coe
Atmos. Chem. Phys., 19, 5771–5790, https://doi.org/10.5194/acp-19-5771-2019, https://doi.org/10.5194/acp-19-5771-2019, 2019
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A novel analysis of aerosol and gas-phase vertical profiles shows a marked regional pollution contrast: composition is driven by the fire regime and vertical distribution is driven by thermodynamics. These drivers ought to be well represented in simulations to ensure realistic prediction of climate and air quality impacts. The BC : CO ratio in haze and plumes increases with altitude – long-range transport or fire stage coupled to plume dynamics may be responsible. Further enquiry is advocated.
Thomas J. Bannan, Michael Le Breton, Michael Priestley, Stephen D. Worrall, Asan Bacak, Nicholas A. Marsden, Archit Mehra, Julia Hammes, Mattias Hallquist, M. Rami Alfarra, Ulrich K. Krieger, Jonathan P. Reid, John Jayne, Wade Robinson, Gordon McFiggans, Hugh Coe, Carl J. Percival, and Dave Topping
Atmos. Meas. Tech., 12, 1429–1439, https://doi.org/10.5194/amt-12-1429-2019, https://doi.org/10.5194/amt-12-1429-2019, 2019
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The Filter Inlet for Gases and AEROsols (FIGAERO) is an inlet designed to be coupled with a high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) and provides simultaneous molecular information relating to both the gas- and particle-phase samples. This method has been used to extract vapour pressures of compounds whilst giving quantitative concentrations in the particle phase. Here we detail an ideal set of benchmark compounds for characterization of the FIGAERO.
Elizabeth Forde, Martin Gallagher, Virginia Foot, Roland Sarda-Esteve, Ian Crawford, Paul Kaye, Warren Stanley, and David Topping
Atmos. Chem. Phys., 19, 1665–1684, https://doi.org/10.5194/acp-19-1665-2019, https://doi.org/10.5194/acp-19-1665-2019, 2019
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The abundance and diversity of airborne biological particles in different environments remains poorly constrained. Measurements of such particles were conducted at four sites in the United Kingdom, using real-time fluorescence instrumentation. Using local land cover types, sources of suspected particle types were identified and compared. Most sites exhibited a wet-discharged fungal spore dominance, with the exception of one site, which was inferred to be influenced by a local dairy farm.
Simon Ruske, David O. Topping, Virginia E. Foot, Andrew P. Morse, and Martin W. Gallagher
Atmos. Meas. Tech., 11, 6203–6230, https://doi.org/10.5194/amt-11-6203-2018, https://doi.org/10.5194/amt-11-6203-2018, 2018
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Pollen, bacteria and fungal spores are common in the environment, can have very important implications for public health and may influence the weather. Biological sensors potentially could be used to monitor quantities of these types of particles. However, it is important to transform the measurements from these instruments into counts of these biological particles. The paper tests a variety of approaches for achieving this aim on data collected in a laboratory.
Dawei Hu, David Topping, and Gordon McFiggans
Atmos. Chem. Phys., 18, 14925–14937, https://doi.org/10.5194/acp-18-14925-2018, https://doi.org/10.5194/acp-18-14925-2018, 2018
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Co-condensation of inorganic or organic vapours on growing droplets could significantly enhance both CCN and cloud droplet number concentration, thereby influencing climate. Until now, there has been very few direct observational evidence of this process. We exposed involatile inorganic particles to a moist atmosphere containing a controlled amount of an organic semi-volatile vapour. We measured a much greater growth of the particles than if they had only been exposed to water vapour.
Matthew Crooks, Paul Connolly, and Gordon McFiggans
Geosci. Model Dev., 11, 3261–3278, https://doi.org/10.5194/gmd-11-3261-2018, https://doi.org/10.5194/gmd-11-3261-2018, 2018
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Clouds form when water condenses onto particles in the atmosphere and the size and chemical composition of these particles can have a large influence over how much water condenses and the subsequent formation of cloud. Additional gases exist in the atmosphere that can condense onto the aerosol particles and change their composition. We present a fast and efficient method of calculating the effect of atmospheric gases on the formation of cloud that can be used in climate and weather models.
Kelly L. Pereira, Rachel Dunmore, James Whitehead, M. Rami Alfarra, James D. Allan, Mohammed S. Alam, Roy M. Harrison, Gordon McFiggans, and Jacqueline F. Hamilton
Atmos. Chem. Phys., 18, 11073–11096, https://doi.org/10.5194/acp-18-11073-2018, https://doi.org/10.5194/acp-18-11073-2018, 2018
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Exhaust emissions from a light-duty diesel engine were introduced into an atmospheric simulation chamber which was used as a holding-cell for sampling, allowing instruments capable of providing detailed chemical speciation of exhaust gas emissions to be used. The effect of different engine conditions on the exhaust gas composition was investigated. The exhaust composition changed considerably due to two influencing factors, engine combustion and diesel oxidative catalyst efficiency.
Michael Le Breton, Yujue Wang, Åsa M. Hallquist, Ravi Kant Pathak, Jing Zheng, Yudong Yang, Dongjie Shang, Marianne Glasius, Thomas J. Bannan, Qianyun Liu, Chak K. Chan, Carl J. Percival, Wenfei Zhu, Shengrong Lou, David Topping, Yuchen Wang, Jianzhen Yu, Keding Lu, Song Guo, Min Hu, and Mattias Hallquist
Atmos. Chem. Phys., 18, 10355–10371, https://doi.org/10.5194/acp-18-10355-2018, https://doi.org/10.5194/acp-18-10355-2018, 2018
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This paper utilizes a chemical ionisation mass spectrometer measuring gas and particle-phase organosulfates (OS) simultaneously during a field campaign in Beijing, China, and highlights how high time frequency online measurements enable a detailed analysis of dominant production mechanisms. We find that high aerosol acidity, organic precursor concentration and relative humidity promote the production of OS. The thermogram desorption reveals the potential for semi-volatile gas-phase OS.
Wiebke Frey, Dawei Hu, James Dorsey, M. Rami Alfarra, Aki Pajunoja, Annele Virtanen, Paul Connolly, and Gordon McFiggans
Atmos. Chem. Phys., 18, 9393–9409, https://doi.org/10.5194/acp-18-9393-2018, https://doi.org/10.5194/acp-18-9393-2018, 2018
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The coupled system of the Manchester Aerosol Chamber and Manchester Ice Cloud Chamber was used to study the ice-forming abilities of secondary
organic aerosol particles under mixed-phase cloud conditions. Given the vast abundance of secondary organic particles in the atmosphere, they
might present an important contribution to ice-nucleating particles. However, we find that in the studied temperature range (20 to 28 °C)
the secondary organic particles do not nucleate ice particles.
Emma L. Simpson, Paul J. Connolly, and Gordon McFiggans
Atmos. Chem. Phys., 18, 7237–7250, https://doi.org/10.5194/acp-18-7237-2018, https://doi.org/10.5194/acp-18-7237-2018, 2018
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This study explores the process of ice formation in clouds by conducting computer model simulations and laboratory experiments in a cloud chamber. We show that the formation of ice in clouds can be limited by the presence of atmospheric aerosol particles and that further research is required to identify the requirements for freezing, e.g. minimum mass of water, in order to accurately calculate ice formation and thus improve climate and weather prediction.
Stefano Decesari, Simona Kovarich, Manuela Pavan, Arianna Bassan, Andrea Ciacci, and David Topping
Atmos. Chem. Phys., 18, 2329–2340, https://doi.org/10.5194/acp-18-2329-2018, https://doi.org/10.5194/acp-18-2329-2018, 2018
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Particulate matter (PM) chemical composition includes thousands of individual organic compounds that have never been tested for their toxicological potential. Computational (in silico) screenings represent a promising approach to identify new target compounds for more in-depth toxicological analyses. We provide here a proof-of-concept evaluation based on ca. 100 aerosol organic compounds. Reliable toxicological predictions were obtained for more than 80 % of them.
Kathryn Fowler, Paul J. Connolly, David O. Topping, and Simon O'Meara
Atmos. Chem. Phys., 18, 1629–1642, https://doi.org/10.5194/acp-18-1629-2018, https://doi.org/10.5194/acp-18-1629-2018, 2018
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This is the first time the Maxwell–Stefan framework has been applied to an atmospheric aerosol core–shell model and shows that there is a complex interplay between the viscous and solubility effects on aerosol composition. Understanding aerosol composition is essential to accurately model their interactions within atmospheric systems. We use simple binary systems to demonstrate how viscosity and solubility both play a role in affecting the rate of diffusion through aerosol particles.
Ulrich K. Krieger, Franziska Siegrist, Claudia Marcolli, Eva U. Emanuelsson, Freya M. Gøbel, Merete Bilde, Aleksandra Marsh, Jonathan P. Reid, Andrew J. Huisman, Ilona Riipinen, Noora Hyttinen, Nanna Myllys, Theo Kurtén, Thomas Bannan, Carl J. Percival, and David Topping
Atmos. Meas. Tech., 11, 49–63, https://doi.org/10.5194/amt-11-49-2018, https://doi.org/10.5194/amt-11-49-2018, 2018
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Vapor pressures of low-volatility organic molecules at atmospheric temperatures reported in the literature often differ by several orders of magnitude between measurement techniques. These discrepancies exceed the stated uncertainty of each technique, which is generally reported to be smaller than a factor of 2. We determined saturation vapor pressures for the homologous series of polyethylene glycols ranging in vapor pressure at 298 K from 1E−7 Pa to 5E−2 Pa as a reference set.
Simon O'Meara, David O. Topping, Rahul A. Zaveri, and Gordon McFiggans
Atmos. Chem. Phys., 17, 10477–10494, https://doi.org/10.5194/acp-17-10477-2017, https://doi.org/10.5194/acp-17-10477-2017, 2017
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To simulate particle-phase diffusion, an analytical expression is desired because it takes less calculation time than a differential equation. Here a correction is found for the analytical solution for when diffusivity is dependent on composition, thereby making it more widely applicable than before. Consequently, we are able to more realistically evaluate the rate limitation (if any) imposed by particle-phase diffusion on component partitioning between the gas and particle phase.
David O. Topping, James Allan, M. Rami Alfarra, and Bernard Aumont
Geosci. Model Dev., 10, 2365–2377, https://doi.org/10.5194/gmd-10-2365-2017, https://doi.org/10.5194/gmd-10-2365-2017, 2017
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Our ability to model the chemical and thermodynamic processes that lead to secondary organic aerosol (SOA) formation is thought to be hampered by the complexity of the system. In this proof of concept study, the ability to train supervised methods to predict electron impact ionisation (EI) mass spectra for the AMS is evaluated to facilitate improved model evaluation. The study demonstrates the use of a methodology that would be improved with more training data and data from simple mixed systems.
Huan Yao, Yu Song, Mingxu Liu, Scott Archer-Nicholls, Douglas Lowe, Gordon McFiggans, Tingting Xu, Pin Du, Jianfeng Li, Yusheng Wu, Min Hu, Chun Zhao, and Tong Zhu
Atmos. Chem. Phys., 17, 5205–5219, https://doi.org/10.5194/acp-17-5205-2017, https://doi.org/10.5194/acp-17-5205-2017, 2017
Simon Ruske, David O. Topping, Virginia E. Foot, Paul H. Kaye, Warren R. Stanley, Ian Crawford, Andrew P. Morse, and Martin W. Gallagher
Atmos. Meas. Tech., 10, 695–708, https://doi.org/10.5194/amt-10-695-2017, https://doi.org/10.5194/amt-10-695-2017, 2017
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Particles such as bacteria, pollen and fungal spores have important implications within the environment and public health sectors. Here we evaluate the performance of various different methods for distinguishing between these different types of particles using a new instrument. We demonstrate that there may be better alternatives to the currently used methods which can be further investigated in future research.
François Benduhn, Graham W. Mann, Kirsty J. Pringle, David O. Topping, Gordon McFiggans, and Kenneth S. Carslaw
Geosci. Model Dev., 9, 3875–3906, https://doi.org/10.5194/gmd-9-3875-2016, https://doi.org/10.5194/gmd-9-3875-2016, 2016
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We present a new mathematical formalism that serves to represent exchanges of inorganic matter between the atmosphere gas phase and the aerosol aqueous phase. In a global modelling framework, taking into account these processes may help represent many important features more accurately, such as the formation of cloud droplets or the radiative properties of the atmosphere. The formalism strives to keep an appropriate balance between accuracy and computation efficiency requirements.
Matthew Crooks, Paul Connolly, David Topping, and Gordon McFiggans
Geosci. Model Dev., 9, 3617–3637, https://doi.org/10.5194/gmd-9-3617-2016, https://doi.org/10.5194/gmd-9-3617-2016, 2016
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Semi-volatile compounds, like water, can exist in both vapour phases and condensed phases within a system. This paper presents a method of calculating the condensed and vapour phases of semi-volatile compounds at equilibrium, in particular, when the condensed mass occurs within particles of different sizes and chemical composition. The applications of interest to the authors are those of atmospheric importance such as cloud droplet formation and reflection or absorption of solar radiation.
Samuel Lowe, Daniel G. Partridge, David Topping, and Philip Stier
Atmos. Chem. Phys., 16, 10941–10963, https://doi.org/10.5194/acp-16-10941-2016, https://doi.org/10.5194/acp-16-10941-2016, 2016
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A novel inverse modelling framework is developed for analysing the sensitivity of cloud condensation nuclei (CCN) concentrations to simultaneous perturbations in multiple model parameters at atmospherically relevant humidities. Many parameter interactions are identified and CCN concentrations are found to be relatively insensitive to bulk–surface partitioning, while aerosol concentration, surface tension, composition and solution ideality exhibit a higher degree of sensitivity.
James D. Whitehead, Eoghan Darbyshire, Joel Brito, Henrique M. J. Barbosa, Ian Crawford, Rafael Stern, Martin W. Gallagher, Paul H. Kaye, James D. Allan, Hugh Coe, Paulo Artaxo, and Gordon McFiggans
Atmos. Chem. Phys., 16, 9727–9743, https://doi.org/10.5194/acp-16-9727-2016, https://doi.org/10.5194/acp-16-9727-2016, 2016
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We present measurements of aerosols during the transition from wet to dry seasons at a pristine rainforest site in central Amazonia. By excluding pollution episodes, we focus on natural biogenic aerosols. Submicron aerosols are dominated by organic material, similar to previous wet season measurements. Larger particles are dominated by biological material, mostly fungal spores, with higher concentrations at night. This study provides important data on the nature of particles above the Amazon.
Scott Archer-Nicholls, Douglas Lowe, David M. Schultz, and Gordon McFiggans
Atmos. Chem. Phys., 16, 5573–5594, https://doi.org/10.5194/acp-16-5573-2016, https://doi.org/10.5194/acp-16-5573-2016, 2016
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The response of the Weather Research and Forecasting model with Chemistry to forcings by biomass burning aerosol were investigated in high-resolution nested domains over Brazil. The aerosol-layer was found to have a negative direct effect at the top of the atmosphere, but this was largely cancelled by a semi-direct effect which inhibited afternoon cloud formation. The cloud response to the aerosol was found to be highly sensitive to model resolution and the use of convective parameterisation.
Simon O'Meara, David O. Topping, and Gordon McFiggans
Atmos. Chem. Phys., 16, 5299–5313, https://doi.org/10.5194/acp-16-5299-2016, https://doi.org/10.5194/acp-16-5299-2016, 2016
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To understand the effect of atmospheric particulate matter on climate and human health we need to know how it evolves. We investigate how best to estimate diffusion of components through particles by comparing diffusion times from three approaches to solving Fick's Law and find that they agree. This means that scientists can simulate Fickian diffusion through atmospheric particles using the approach best suited to their requirements and have confidence that their model is mathematically sound.
David Topping, Mark Barley, Michael K. Bane, Nicholas Higham, Bernard Aumont, Nicholas Dingle, and Gordon McFiggans
Geosci. Model Dev., 9, 899–914, https://doi.org/10.5194/gmd-9-899-2016, https://doi.org/10.5194/gmd-9-899-2016, 2016
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In this paper we describe the development and application of a new web-based and open-source facility, UManSysProp (http://umansysprop .seaes.manchester.ac.uk), for automating predictions of molecular and atmospheric aerosol properties. Current facilities include pure component vapour pressures, critical properties, and sub-cooled densities of organic molecules; activity coefficient predictions for mixed inorganic-organic liquid systems; hygroscopic growth factors and CCN activation potential.
I. Crawford, S. Ruske, D. O. Topping, and M. W. Gallagher
Atmos. Meas. Tech., 8, 4979–4991, https://doi.org/10.5194/amt-8-4979-2015, https://doi.org/10.5194/amt-8-4979-2015, 2015
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HCA analysis methods were evaluated for the purpose of identifying primary biological aerosol sampled with a WIBS. The ward linkage with z-score normalisation could discriminate between five test particles with 98% accuracy. We applied these methods to a previously studied ambient data set, where both methods produced similar results with some minor differences in cluster partitioning. Finally we compared to previous approaches and found our new method offered improved quantification of PBA.
M. Paramonov, V.-M. Kerminen, M. Gysel, P. P. Aalto, M. O. Andreae, E. Asmi, U. Baltensperger, A. Bougiatioti, D. Brus, G. P. Frank, N. Good, S. S. Gunthe, L. Hao, M. Irwin, A. Jaatinen, Z. Jurányi, S. M. King, A. Kortelainen, A. Kristensson, H. Lihavainen, M. Kulmala, U. Lohmann, S. T. Martin, G. McFiggans, N. Mihalopoulos, A. Nenes, C. D. O'Dowd, J. Ovadnevaite, T. Petäjä, U. Pöschl, G. C. Roberts, D. Rose, B. Svenningsson, E. Swietlicki, E. Weingartner, J. Whitehead, A. Wiedensohler, C. Wittbom, and B. Sierau
Atmos. Chem. Phys., 15, 12211–12229, https://doi.org/10.5194/acp-15-12211-2015, https://doi.org/10.5194/acp-15-12211-2015, 2015
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The research paper presents the first comprehensive overview of field measurements with the CCN Counter performed at a large number of locations around the world within the EUCAARI framework. The paper sheds light on the CCN number concentrations and activated fractions around the world and their dependence on the water vapour supersaturation ratio, the dependence of aerosol hygroscopicity on particle size, and seasonal and diurnal variation of CCN activation and hygroscopic properties.
K. P. Wyche, P. S. Monks, K. L. Smallbone, J. F. Hamilton, M. R. Alfarra, A. R. Rickard, G. B. McFiggans, M. E. Jenkin, W. J. Bloss, A. C. Ryan, C. N. Hewitt, and A. R. MacKenzie
Atmos. Chem. Phys., 15, 8077–8100, https://doi.org/10.5194/acp-15-8077-2015, https://doi.org/10.5194/acp-15-8077-2015, 2015
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This paper describes a new ensemble methodology for the statistical analysis of atmospheric gas- & particle-phase composition data sets. The methodology reduces the huge amount of data derived from many chamber experiments to show that organic reactivity & resultant particle formation can be mapped into unique clusters in statistical space. The model generated is used to map more realistic plant mesocosm oxidation data, the projection of which gives insight into reactive pathways & precursors.
J. D. Allan, P. I. Williams, J. Najera, J. D. Whitehead, M. J. Flynn, J. W. Taylor, D. Liu, E. Darbyshire, L. J. Carpenter, R. Chance, S. J. Andrews, S. C. Hackenberg, and G. McFiggans
Atmos. Chem. Phys., 15, 5599–5609, https://doi.org/10.5194/acp-15-5599-2015, https://doi.org/10.5194/acp-15-5599-2015, 2015
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New particle formation (NPF) is an important contributor to aerosol number concentrations in the Arctic and thus has a major role in dictating cloud properties and climate in this region. Here we present direct evidence that the oxidation of iodine in the atmosphere causes NPF in the Greenland Sea. This is important because this is a NPF mechanism that has not previously been considered in modelling studies at these latitudes.
M. D. Jolleys, H. Coe, G. McFiggans, J. W. Taylor, S. J. O'Shea, M. Le Breton, S. J.-B. Bauguitte, S. Moller, P. Di Carlo, E. Aruffo, P. I. Palmer, J. D. Lee, C. J. Percival, and M. W. Gallagher
Atmos. Chem. Phys., 15, 3077–3095, https://doi.org/10.5194/acp-15-3077-2015, https://doi.org/10.5194/acp-15-3077-2015, 2015
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Particulate emissions in the form of organic aerosol from boreal forest fires in Canada have been measured during an aircraft measurement campaign. Ratios of the amount of aerosol emitted relative to gas species such as CO were calculated and show high levels of variability throughout the campaign. This variability is affected by both changes in fire conditions, as fires tended to die down later in the measurement period, and by changes to the aerosol due to chemical reactions in the atmosphere.
S. Archer-Nicholls, D. Lowe, E. Darbyshire, W. T. Morgan, M. M. Bela, G. Pereira, J. Trembath, J. W. Kaiser, K. M. Longo, S. R. Freitas, H. Coe, and G. McFiggans
Geosci. Model Dev., 8, 549–577, https://doi.org/10.5194/gmd-8-549-2015, https://doi.org/10.5194/gmd-8-549-2015, 2015
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The regional WRF-Chem model was used to study aerosol particles from biomass burning in South America. The modelled estimates of fire plume injection heights were found to be too high, with serious implications for modelled aerosol vertical distribution, transport and impacts on local climate. A modified emission scenario was developed which improved the predicted injection height. Model results were compared and evaluated against in situ measurements from the 2012 SAMBBA flight campaign.
D. Lowe, S. Archer-Nicholls, W. Morgan, J. Allan, S. Utembe, B. Ouyang, E. Aruffo, M. Le Breton, R. A. Zaveri, P. Di Carlo, C. Percival, H. Coe, R. Jones, and G. McFiggans
Atmos. Chem. Phys., 15, 1385–1409, https://doi.org/10.5194/acp-15-1385-2015, https://doi.org/10.5194/acp-15-1385-2015, 2015
W. T. Morgan, B. Ouyang, J. D. Allan, E. Aruffo, P. Di Carlo, O. J. Kennedy, D. Lowe, M. J. Flynn, P. D. Rosenberg, P. I. Williams, R. Jones, G. B. McFiggans, and H. Coe
Atmos. Chem. Phys., 15, 973–990, https://doi.org/10.5194/acp-15-973-2015, https://doi.org/10.5194/acp-15-973-2015, 2015
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This paper used observations from a research aircraft flying around the UK to investigate how air pollution in north-western Europe can alter nighttime chemical reactions in the atmosphere. These chemical reactions can worsen air quality in the region, as well as influence regional climate change. Ammonium nitrate aerosol appears to play an important role. The paper indicates that representation of these chemical reactions is poorly represented in models used for air quality and climate.
K. P. Wyche, A. C. Ryan, C. N. Hewitt, M. R. Alfarra, G. McFiggans, T. Carr, P. S. Monks, K. L. Smallbone, G. Capes, J. F. Hamilton, T. A. M. Pugh, and A. R. MacKenzie
Atmos. Chem. Phys., 14, 12781–12801, https://doi.org/10.5194/acp-14-12781-2014, https://doi.org/10.5194/acp-14-12781-2014, 2014
J. D. Whitehead, M. Irwin, J. D. Allan, N. Good, and G. McFiggans
Atmos. Chem. Phys., 14, 11833–11841, https://doi.org/10.5194/acp-14-11833-2014, https://doi.org/10.5194/acp-14-11833-2014, 2014
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Water uptake of ambient particles was measured by 2 independent techniques at a wide range of locations between 2007 and 2013. The agreement between the techniques was mixed and hence the number of potential cloud seeds calculated from the measurements frequently showed discrepancies. Whilst there is sensitivity to how well we measure the size of the particles, much of the difference depends on how the particles behave when exposed to moisture in the different techniques (and in the atmosphere).
S. Archer-Nicholls, D. Lowe, S. Utembe, J. Allan, R. A. Zaveri, J. D. Fast, Ø. Hodnebrog, H. Denier van der Gon, and G. McFiggans
Geosci. Model Dev., 7, 2557–2579, https://doi.org/10.5194/gmd-7-2557-2014, https://doi.org/10.5194/gmd-7-2557-2014, 2014
M. J. Lawler, J. Whitehead, C. O'Dowd, C. Monahan, G. McFiggans, and J. N. Smith
Atmos. Chem. Phys., 14, 11557–11569, https://doi.org/10.5194/acp-14-11557-2014, https://doi.org/10.5194/acp-14-11557-2014, 2014
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This work describes the chemical and physical characterization of very small (< 100 nm diameter) particles in the marine atmosphere. We show that sea salt is present even at very small sizes and present evidence that organic species are important contributors to apparent new particle formation events over the ocean.
E. Simpson, P. Connolly, and G. McFiggans
Geosci. Model Dev., 7, 1535–1542, https://doi.org/10.5194/gmd-7-1535-2014, https://doi.org/10.5194/gmd-7-1535-2014, 2014
M. Crippa, F. Canonaco, V. A. Lanz, M. Äijälä, J. D. Allan, S. Carbone, G. Capes, D. Ceburnis, M. Dall'Osto, D. A. Day, P. F. DeCarlo, M. Ehn, A. Eriksson, E. Freney, L. Hildebrandt Ruiz, R. Hillamo, J. L. Jimenez, H. Junninen, A. Kiendler-Scharr, A.-M. Kortelainen, M. Kulmala, A. Laaksonen, A. A. Mensah, C. Mohr, E. Nemitz, C. O'Dowd, J. Ovadnevaite, S. N. Pandis, T. Petäjä, L. Poulain, S. Saarikoski, K. Sellegri, E. Swietlicki, P. Tiitta, D. R. Worsnop, U. Baltensperger, and A. S. H. Prévôt
Atmos. Chem. Phys., 14, 6159–6176, https://doi.org/10.5194/acp-14-6159-2014, https://doi.org/10.5194/acp-14-6159-2014, 2014
P. J. Connolly, D. O. Topping, F. Malavelle, and G. McFiggans
Atmos. Chem. Phys., 14, 2289–2302, https://doi.org/10.5194/acp-14-2289-2014, https://doi.org/10.5194/acp-14-2289-2014, 2014
M. R. Alfarra, N. Good, K. P. Wyche, J. F. Hamilton, P. S. Monks, A. C. Lewis, and G. McFiggans
Atmos. Chem. Phys., 13, 11769–11789, https://doi.org/10.5194/acp-13-11769-2013, https://doi.org/10.5194/acp-13-11769-2013, 2013
J. F. Hamilton, M. R. Alfarra, N. Robinson, M. W. Ward, A. C. Lewis, G. B. McFiggans, H. Coe, and J. D. Allan
Atmos. Chem. Phys., 13, 11295–11305, https://doi.org/10.5194/acp-13-11295-2013, https://doi.org/10.5194/acp-13-11295-2013, 2013
D. Liu, J. Allan, J. Whitehead, D. Young, M. Flynn, H. Coe, G. McFiggans, Z. L. Fleming, and B. Bandy
Atmos. Chem. Phys., 13, 2015–2029, https://doi.org/10.5194/acp-13-2015-2013, https://doi.org/10.5194/acp-13-2015-2013, 2013
Related subject area
Atmospheric sciences
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Low-level jets in the North and Baltic Seas: Mesoscale Model Sensitivity and Climatology
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Estimation of aerosol and cloud radiative heating rate in tropical stratosphere using radiative kernel method
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
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
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
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.
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.
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.
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.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
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Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2815, https://doi.org/10.5194/egusphere-2024-2815, 2024
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate that effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense and consists well with radiative model calculations and can be applied to atmospheric models with speed requirements.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
EGUsphere, https://doi.org/10.5194/egusphere-2024-2879, https://doi.org/10.5194/egusphere-2024-2879, 2024
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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 successful results , positioning the code for future use on exascale supercomputers.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
EGUsphere, https://doi.org/10.5194/egusphere-2024-1898, https://doi.org/10.5194/egusphere-2024-1898, 2024
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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.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
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Short summary
User-friendly and open-source software for simulating aerosol chambers is a valuable tool for research scientists in designing and analysing their experiments. This paper describes a new version of such software and will therefore provide a useful reference for those applying it. Central to the paper is an assessment of the software's accuracy through comparison against previously published simulations.
User-friendly and open-source software for simulating aerosol chambers is a valuable tool for...
