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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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
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Atmospheric sciences
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
Mixed-Precision Computing in the GRIST Dynamical Core for Weather and Climate Modelling
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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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.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
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Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
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The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 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.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
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The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
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We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
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This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
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The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
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The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and 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.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
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This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
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We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
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This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
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In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 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 for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
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Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
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HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
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This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
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An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
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This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
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Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
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.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
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Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
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.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-68, https://doi.org/10.5194/gmd-2024-68, 2024
Revised manuscript accepted for GMD
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The equation terms in the governing equations that are sensitive (insensitive) to the precision level have been identified. The performance of mixed-precision computing for weather and climate simulations was analyzed.
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.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-195, https://doi.org/10.5194/gmd-2023-195, 2024
Revised manuscript accepted for GMD
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The satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator highlighting its added value through a case study and diagnostics.
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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...
