Articles | Volume 11, issue 8
https://doi.org/10.5194/gmd-11-3261-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-3261-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
13 Aug 2018
Model description paper |
| 13 Aug 2018
A parameterisation for the co-condensation of semi-volatile organics into multiple aerosol particle modes
Matthew Crooks
CORRESPONDING AUTHOR
The School of Earth, Atmospheric and Environmental Science, The
University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Paul Connolly
The School of Earth, Atmospheric and Environmental Science, The
University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Gordon McFiggans
The School of Earth, Atmospheric and Environmental Science, The
University of Manchester, Oxford Road, Manchester, M13 9PL, UK
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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
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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
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Simon Patrick O'Meara, Shuxuan Xu, David Topping, M. Rami Alfarra, Gerard Capes, Douglas Lowe, Yunqi Shao, and Gordon McFiggans
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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.
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.
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.
Jonathan W. Taylor, Sophie L. Haslett, Keith Bower, Michael Flynn, Ian Crawford, James Dorsey, Tom Choularton, Paul J. Connolly, Valerian Hahn, Christiane Voigt, Daniel Sauer, Régis Dupuy, Joel Brito, Alfons Schwarzenboeck, Thierry Bourriane, Cyrielle Denjean, Phil Rosenberg, Cyrille Flamant, James D. Lee, Adam R. Vaughan, Peter G. Hill, Barbara Brooks, Valéry Catoire, Peter Knippertz, and Hugh Coe
Atmos. Chem. Phys., 19, 8503–8522, https://doi.org/10.5194/acp-19-8503-2019, https://doi.org/10.5194/acp-19-8503-2019, 2019
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Low-level clouds cover a wide area of southern West Africa (SWA) and play an important role in the region's climate, reflecting sunlight away from the surface. We performed aircraft measurements of aerosols and clouds over SWA during the 2016 summer monsoon and found pollution, and polluted clouds, across the whole region. Smoke from biomass burning in Central Africa is transported to West Africa, causing a polluted background which limits the effect of local pollution on cloud properties.
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.
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.
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.
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.
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.
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.
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.
Gillian Young, Paul J. Connolly, Christopher Dearden, and Thomas W. Choularton
Atmos. Chem. Phys., 18, 1475–1494, https://doi.org/10.5194/acp-18-1475-2018, https://doi.org/10.5194/acp-18-1475-2018, 2018
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Large-scale subsidence, associated with high-pressure systems, is often used in cloud-resolving models to maintain the height of boundary layer clouds; however, its influence on the small-scale interactions in mixed-phase clouds has not been previously investigated. Using large-eddy simulations, we have identified a relationship between subsidence and convection development in such clouds, with implications for mixed-phase boundary layer clouds forming in the ocean-exposed Arctic regions.
Olivia Goulden, Matthew Crooks, and Paul Connolly
Atmos. Chem. Phys., 18, 275–287, https://doi.org/10.5194/acp-18-275-2018, https://doi.org/10.5194/acp-18-275-2018, 2018
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The formation of cloud from the condensation of water vapour in the atmosphere on aerosol particles is highly dependent of the chemical properties of the particles. The chemistry is further complicated by the presence of condensible gases in the atmosphere other than water. We provide several methods of including the complicated chemical properties of the aerosol particles and condensing gases into single parameter descriptions, which are suitable for inclusion in large-scale models.
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.
Leonid Nichman, Emma Järvinen, James Dorsey, Paul Connolly, Jonathan Duplissy, Claudia Fuchs, Karoliina Ignatius, Kamalika Sengupta, Frank Stratmann, Ottmar Möhler, Martin Schnaiter, and Martin Gallagher
Atmos. Meas. Tech., 10, 3231–3248, https://doi.org/10.5194/amt-10-3231-2017, https://doi.org/10.5194/amt-10-3231-2017, 2017
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Optical probes are frequently used for the detection of cloud particles. The detected microphysical properties may affect particle growth and accretion mechanisms and the light scattering properties of cirrus clouds. In the CLOUD chamber study at CERN, we compared four optical measurement techniques. We show that shape derivation alone is not sufficient to determine the phase of the small cloud particles. None of the instruments were able to unambiguously determine the phase of small particles.
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
Gillian Young, Paul J. Connolly, Hazel M. Jones, and Thomas W. Choularton
Atmos. Chem. Phys., 17, 4209–4227, https://doi.org/10.5194/acp-17-4209-2017, https://doi.org/10.5194/acp-17-4209-2017, 2017
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Arctic mixed-phase clouds are poorly represented in numerical models, due in part to an overpredicted ice phase. Here, we examine the sensitivity of cloud structure, evolution, and lifetime to modelled primary ice number concentrations over three different surfaces – sea ice, marginal ice, and ocean – to investigate the dependency on both the ice phase and dynamics induced from surface fluxes.
Gillian Young, Hazel M. Jones, Thomas W. Choularton, Jonathan Crosier, Keith N. Bower, Martin W. Gallagher, Rhiannon S. Davies, Ian A. Renfrew, Andrew D. Elvidge, Eoghan Darbyshire, Franco Marenco, Philip R. A. Brown, Hugo M. A. Ricketts, Paul J. Connolly, Gary Lloyd, Paul I. Williams, James D. Allan, Jonathan W. Taylor, Dantong Liu, and Michael J. Flynn
Atmos. Chem. Phys., 16, 13945–13967, https://doi.org/10.5194/acp-16-13945-2016, https://doi.org/10.5194/acp-16-13945-2016, 2016
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Clouds are intricately coupled to the Arctic sea ice. Our inability to accurately model cloud fractions causes large uncertainties in predicted radiative interactions in this region, therefore, affecting sea ice forecasts. Here, we present measurements of cloud microphysics, aerosol properties, and thermodynamic structure over the transition from sea ice to ocean to improve our understanding of the relationship between the Arctic atmosphere and clouds which develop in this region.
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.
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.
Robert J. Farrington, Paul J. Connolly, Gary Lloyd, Keith N. Bower, Michael J. Flynn, Martin W. Gallagher, Paul R. Field, Chris Dearden, and Thomas W. Choularton
Atmos. Chem. Phys., 16, 4945–4966, https://doi.org/10.5194/acp-16-4945-2016, https://doi.org/10.5194/acp-16-4945-2016, 2016
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This paper assesses the reasons for high ice number concentrations observed in orographic clouds by comparing observations with model simulations over Jungfraujoch, Switzerland. The results suggest that ice nuclei do not significantly contribute to the high concentrations and that a surface source of ice crystals is responsible for the witnessed ice number concentrations.
G. Young, H. M. Jones, E. Darbyshire, K. J. Baustian, J. B. McQuaid, K. N. Bower, P. J. Connolly, M. W. Gallagher, and T. W. Choularton
Atmos. Chem. Phys., 16, 4063–4079, https://doi.org/10.5194/acp-16-4063-2016, https://doi.org/10.5194/acp-16-4063-2016, 2016
Leonid Nichman, Claudia Fuchs, Emma Järvinen, Karoliina Ignatius, Niko Florian Höppel, Antonio Dias, Martin Heinritzi, Mario Simon, Jasmin Tröstl, Andrea Christine Wagner, Robert Wagner, Christina Williamson, Chao Yan, Paul James Connolly, James Robert Dorsey, Jonathan Duplissy, Sebastian Ehrhart, Carla Frege, Hamish Gordon, Christopher Robert Hoyle, Thomas Bjerring Kristensen, Gerhard Steiner, Neil McPherson Donahue, Richard Flagan, Martin William Gallagher, Jasper Kirkby, Ottmar Möhler, Harald Saathoff, Martin Schnaiter, Frank Stratmann, and António Tomé
Atmos. Chem. Phys., 16, 3651–3664, https://doi.org/10.5194/acp-16-3651-2016, https://doi.org/10.5194/acp-16-3651-2016, 2016
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Processes in the atmosphere are often governed by the physical and chemical properties of small cloud particles. Ice, water, and mixed clouds, as well as viscous aerosols, were formed under controlled conditions at the CLOUD-CERN facility. The experimental results show a link between cloud particle properties and their unique optical fingerprints. The classification map presented here allows easier discrimination between various particles such as viscous organic aerosol, salt, ice, and liquid.
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, G. Lloyd, E. Herrmann, C. R. Hoyle, K. N. Bower, P. J. Connolly, M. J. Flynn, P. H. Kaye, T. W. Choularton, and M. W. Gallagher
Atmos. Chem. Phys., 16, 2273–2284, https://doi.org/10.5194/acp-16-2273-2016, https://doi.org/10.5194/acp-16-2273-2016, 2016
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In this manuscript we discuss observations of fluorescent aerosol and their interactions with cloud at a high-alpine site in the wintertime under background conditions. We find the majority of the fluorescent aerosol to be consistent in nature to mineral dust and no apparent trend was observed between the fluorescent aerosol fraction and meteorological or cloud microphysical parameters, suggesting that particle fluorescence does not impact cloud evolution or formation at the site.
J. Grazioli, G. Lloyd, L. Panziera, C. R. Hoyle, P. J. Connolly, J. Henneberger, and A. Berne
Atmos. Chem. Phys., 15, 13787–13802, https://doi.org/10.5194/acp-15-13787-2015, https://doi.org/10.5194/acp-15-13787-2015, 2015
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This study investigates the microphysics of winter alpine snowfall occurring in mixed-phase clouds in an inner-Alpine valley during CLACE2014. From polarimetric radar and in situ observations, riming is shown to be an important process leading to more intense snowfall. Riming is usually associated with more intense turbulence providing supercooled liquid water. Distinct features are identified in the vertical structure of polarimetric radar variables.
G. Lloyd, T. W. Choularton, K. N. Bower, M. W. Gallagher, P. J. Connolly, M. Flynn, R. Farrington, J. Crosier, O. Schlenczek, J. Fugal, and J. Henneberger
Atmos. Chem. Phys., 15, 12953–12969, https://doi.org/10.5194/acp-15-12953-2015, https://doi.org/10.5194/acp-15-12953-2015, 2015
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The paper explores the microphysical structure of clouds at the high-alpine measurement site Jungfraujoch, Switzerland. High concentrations of ice crystals were measured by a range of instruments. The presence of these high concentrations could not be explained through conventional understanding of ice formation processes in clouds and the possibility that the surface provides a significant source of ice crystals is investigated.
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.
C. Emersic, P. J. Connolly, S. Boult, M. Campana, and Z. Li
Atmos. Chem. Phys., 15, 11311–11326, https://doi.org/10.5194/acp-15-11311-2015, https://doi.org/10.5194/acp-15-11311-2015, 2015
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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.
I. Steinke, C. Hoose, O. Möhler, P. Connolly, and T. Leisner
Atmos. Chem. Phys., 15, 3703–3717, https://doi.org/10.5194/acp-15-3703-2015, https://doi.org/10.5194/acp-15-3703-2015, 2015
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Ice nucleation in clouds has a significant influence on the global radiative budget and the hydrological cycle. Several studies have investigated the ice formation in droplets and parameterizations have been developed in order to include immersion freezing in climate models. In contrast, there are fewer studies regarding the conversion of water vapor into ice (so-called deposition nucleation) which is the topic of this paper which investigates deposition nucleation by Arizona Test dust in detail
G. Lloyd, T. W. Choularton, K. N. Bower, J. Crosier, H. Jones, J. R. Dorsey, M. W. Gallagher, P. Connolly, A. C. R. Kirchgaessner, and T. Lachlan-Cope
Atmos. Chem. Phys., 15, 3719–3737, https://doi.org/10.5194/acp-15-3719-2015, https://doi.org/10.5194/acp-15-3719-2015, 2015
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Measurements of cloud microphysics are reported from the Aerosol-Cloud Coupling And Climate Interactions (ACCACIA) campaign. Concentrations of ice particles from two spring and two summer cases are compared with particular attention to the role of secondary ice in these clouds. In addition aerosol measurements were used as input to a primary ice nucleation parameterisation which was compared with observed values of primary ice in these clouds. We found higher concentrations of ice during summer.
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
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
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
P. J. Connolly, G. Vaughan, P. Cook, G. Allen, H. Coe, T. W. Choularton, C. Dearden, and A. Hill
Atmos. Chem. Phys., 13, 7133–7152, https://doi.org/10.5194/acp-13-7133-2013, https://doi.org/10.5194/acp-13-7133-2013, 2013
J. Skrotzki, P. Connolly, M. Schnaiter, H. Saathoff, O. Möhler, R. Wagner, M. Niemand, V. Ebert, and T. Leisner
Atmos. Chem. Phys., 13, 4451–4466, https://doi.org/10.5194/acp-13-4451-2013, https://doi.org/10.5194/acp-13-4451-2013, 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
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Assessment of tropospheric ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Application of regional meteorology and air quality models based on MIPS CPU Platform
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
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Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
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Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
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This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
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Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
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Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
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Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Nathan Patrick Arnold
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-245, https://doi.org/10.5194/gmd-2023-245, 2024
Revised manuscript accepted for GMD
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Earth System Models often represent the land surface at smaller scales than the atmosphere, but surface-atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter Notebooks included in the library.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
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Short summary
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.
Clouds form when water condenses onto particles in the atmosphere and the size and chemical...
