Articles | Volume 16, issue 20
https://doi.org/10.5194/gmd-16-5931-2023
© Author(s) 2023. 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-16-5931-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
20 Oct 2023
Model evaluation paper |
| 20 Oct 2023
| 20 Oct 2023
Evaluation of vertically resolved longwave radiation in SPARTACUS-Urban 0.7.3 and the sensitivity to urban surface temperatures
Megan A. Stretton
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
William Morrison
Department of Meteorology, University of Reading, Reading, UK
Chair of Environmental Meteorology, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
Robin J. Hogan
Department of Meteorology, University of Reading, Reading, UK
European Centre for Medium-Range Weather Forecasts, Reading, UK
Sue Grimmond
Department of Meteorology, University of Reading, Reading, UK
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Russell H. Glazer, Sue Grimmond, Lewis Blunn, Daniel Fenner, Humphrey Lean, Andreas Christen, Will Morrison, and Dana Looschelders
EGUsphere, https://doi.org/10.5194/egusphere-2025-2064, https://doi.org/10.5194/egusphere-2025-2064, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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In this study we use very high resolution numerical weather prediction model simulations of the Berlin, Germany region along with assessment of field campaign observations to understand better the impact of urban areas on the near-surface boundary layer. We find that there a clear affect of urban areas up to 15 kilometers downwind of the city centre in both the field campaign observations and the high resolution model.
William Morrison, Dana Looschelders, Jonnathan Céspedes, Bernie Claxton, Marc-Antoine Drouin, Jean-Charles Dupont, Aurélien Faucheux, Martial Haeffelin, Christopher C. Holst, Simone Kotthaus, Valéry Masson, James McGregor, Jeremy Price, Matthias Zeeman, Sue Grimmond, and Andreas Christen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-167, https://doi.org/10.5194/essd-2025-167, 2025
Preprint under review for ESSD
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We conducted research using sophisticated wind sensors to better understand wind patterns in Paris. By installing these sensors across the city, we gathered detailed data on wind speeds and directions from 2022 to 2024. This information helps improve weather and climate models, making them more accurate for city environments. Our findings offer valuable insights for scientists studying urban air and weather, improving predictions and understanding of city-scale atmospheric processes.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Matthias Zeeman, Andreas Christen, Sue Grimmond, Daniel Fenner, William Morrison, Gregor Feigel, Markus Sulzer, and Nektarios Chrysoulakis
Geosci. Instrum. Method. Data Syst., 13, 393–424, https://doi.org/10.5194/gi-13-393-2024, https://doi.org/10.5194/gi-13-393-2024, 2024
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This study presents an overview of a data system for documenting, processing, managing, and publishing data streams from research networks of atmospheric and environmental sensors of varying complexity in urban environments. Our solutions aim to deliver resilient, near-time data using freely available software.
Kaah P. Menang, Stefan A. Buehler, Lukas Kluft, Robin J. Hogan, and Florian E. Roemer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3051, https://doi.org/10.5194/egusphere-2024-3051, 2024
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We investigated how the uncertainty in representing water vapour continuum absorption in the shortwave affects clear-sky shortwave radiative feedback. For current surface temperature, the impact is modest (<2 %). In a warmer world, continuum induced error in estimated shortwave feedback is up to ~5 %. Using the MT_CKD model in radiative transfer calculations may lead to an underestimation of the shortwave feedback. Constraining shortwave continuum will contribute to reducing these discrepancies.
Howard W. Barker, Jason N. S. Cole, Najda Villefranque, Zhipeng Qu, Almudena Velázquez Blázquez, Carlos Domenech, Shannon L. Mason, and Robin J. Hogan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1651, https://doi.org/10.5194/egusphere-2024-1651, 2024
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Measurements made by three instruments aboard EarthCARE are used to retrieve estimates of cloud and aerosol properties. A radiative closure assessment of these retrievals is performed by the ACMB-DF processor. Radiative transfer models acting on retrieved information produce broadband radiances commensurate with measurements made by EarthCARE’s broadband radiometer. Measured and modelled radiances for small domains are compared and the likelihood of them differing by 10 W/m2 defines the closure.
Johannes Röttenbacher, André Ehrlich, Hanno Müller, Florian Ewald, Anna E. Luebke, Benjamin Kirbus, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 8085–8104, https://doi.org/10.5194/acp-24-8085-2024, https://doi.org/10.5194/acp-24-8085-2024, 2024
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Weather prediction models simplify the physical processes related to light scattering by clouds consisting of complex ice crystals. Whether these simplifications are the cause for uncertainties in their prediction can be evaluated by comparing them with measurement data. Here we do this for Arctic ice clouds over sea ice using airborne measurements from two case studies. The model performs well for thick ice clouds but not so well for thin ones. This work can be used to improve the model.
Nimra Iqbal, Marvin Ravan, Zina Mitraka, Joern Birkmann, Sue Grimmond, Denise Hertwig, Nektarios Chrysoulakis, Giorgos Somarakis, and Angela Wendnagel-Beck
EGUsphere, https://doi.org/10.5194/egusphere-2024-1907, https://doi.org/10.5194/egusphere-2024-1907, 2024
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This work deepens the understanding of how perceived heat stress, human vulnerability (e.g. age, income) and adaptive capacities (e.g. green, shaded spaces) are coupled with urban structures. The results show that perceived heat stress decreases with distance from urban center, however, human vulnerability and adaptive capacities depend stronger on inner-variations and differences between urban structures. Planning policies and adaptation strategies should account for these differences.
Robin J. Hogan, Anthony J. Illingworth, Pavlos Kollias, Hajime Okamoto, and Ulla Wandinger
Atmos. Meas. Tech., 17, 3081–3083, https://doi.org/10.5194/amt-17-3081-2024, https://doi.org/10.5194/amt-17-3081-2024, 2024
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024, https://doi.org/10.5194/acp-24-4157-2024, 2024
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A weather model is used to compare solar radiation with measurements from an aircraft campaign in the Arctic. Model and observations agree on the downward radiation but show differences in the radiation reflected by the surface and the clouds, which in the model is too low above sea ice and too high above open ocean. The model–observation bias is reduced above open ocean by a realistic fraction of clouds and less cloud liquid water and above sea ice by less dark sea ice and more cloud droplets.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Junxia Dou, Sue Grimmond, Shiguang Miao, Bei Huang, Huimin Lei, and Mingshui Liao
Atmos. Chem. Phys., 23, 13143–13166, https://doi.org/10.5194/acp-23-13143-2023, https://doi.org/10.5194/acp-23-13143-2023, 2023
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Multi-timescale variations in surface energy fluxes in a suburb of Beijing are analyzed using 16-month observations. Compared to previous suburban areas, this study site has larger seasonal variability in energy partitioning, and summer and winter Bowen ratios are at the lower and higher end of those at other suburban sites, respectively. Our analysis indicates that precipitation, irrigation, crop/vegetation growth activity, and land use/cover all play critical roles in energy partitioning.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Peter Ukkonen and Robin J. Hogan
Geosci. Model Dev., 16, 3241–3261, https://doi.org/10.5194/gmd-16-3241-2023, https://doi.org/10.5194/gmd-16-3241-2023, 2023
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Climate and weather models suffer from uncertainties resulting from approximated processes. Solar and thermal radiation is one example, as it is computationally too costly to simulate precisely. This has led to attempts to replace radiation codes based on physical equations with neural networks (NNs) that are faster but uncertain. In this paper we use global weather simulations to demonstrate that a middle-ground approach of using NNs only to predict optical properties is accurate and reliable.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Joanna E. Dyson, Lisa K. Whalley, Eloise J. Slater, Robert Woodward-Massey, Chunxiang Ye, James D. Lee, Freya Squires, James R. Hopkins, Rachel E. Dunmore, Marvin Shaw, Jacqueline F. Hamilton, Alastair C. Lewis, Stephen D. Worrall, Asan Bacak, Archit Mehra, Thomas J. Bannan, Hugh Coe, Carl J. Percival, Bin Ouyang, C. Nicholas Hewitt, Roderic L. Jones, Leigh R. Crilley, Louisa J. Kramer, W. Joe F. Acton, William J. Bloss, Supattarachai Saksakulkrai, Jingsha Xu, Zongbo Shi, Roy M. Harrison, Simone Kotthaus, Sue Grimmond, Yele Sun, Weiqi Xu, Siyao Yue, Lianfang Wei, Pingqing Fu, Xinming Wang, Stephen R. Arnold, and Dwayne E. Heard
Atmos. Chem. Phys., 23, 5679–5697, https://doi.org/10.5194/acp-23-5679-2023, https://doi.org/10.5194/acp-23-5679-2023, 2023
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The hydroxyl (OH) and closely coupled hydroperoxyl (HO2) radicals are vital for their role in the removal of atmospheric pollutants. In less polluted regions, atmospheric models over-predict HO2 concentrations. In this modelling study, the impact of heterogeneous uptake of HO2 onto aerosol surfaces on radical concentrations and the ozone production regime in Beijing in the summertime is investigated, and the implications for emissions policies across China are considered.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
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We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Will S. Drysdale, Adam R. Vaughan, Freya A. Squires, Sam J. Cliff, Stefan Metzger, David Durden, Natchaya Pingintha-Durden, Carole Helfter, Eiko Nemitz, C. Sue B. Grimmond, Janet Barlow, Sean Beevers, Gregor Stewart, David Dajnak, Ruth M. Purvis, and James D. Lee
Atmos. Chem. Phys., 22, 9413–9433, https://doi.org/10.5194/acp-22-9413-2022, https://doi.org/10.5194/acp-22-9413-2022, 2022
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Measurements of NOx emissions are important for a good understanding of air quality. While there are many direct measurements of NOx concentration, there are very few measurements of its emission. Measurements of emissions provide constraints on emissions inventories and air quality models. This article presents measurements of NOx emission from the BT Tower in central London in 2017 and compares them with inventories, finding that they underestimate by a factor of ∼1.48.
Yiqing Liu, Zhiwen Luo, and Sue Grimmond
Atmos. Chem. Phys., 22, 4721–4735, https://doi.org/10.5194/acp-22-4721-2022, https://doi.org/10.5194/acp-22-4721-2022, 2022
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Anthropogenic heat emission from buildings is important for atmospheric modelling in cities. The current building anthropogenic heat flux is simplified by building energy consumption. Our research proposes a novel approach to determine ‘real’ building anthropogenic heat emission from the changes in energy balance fluxes between occupied and unoccupied buildings. We hope to provide new insights into future parameterisations of building anthropogenic heat flux in urban climate models.
Hamidreza Omidvar, Ting Sun, Sue Grimmond, Dave Bilesbach, Andrew Black, Jiquan Chen, Zexia Duan, Zhiqiu Gao, Hiroki Iwata, and Joseph P. McFadden
Geosci. Model Dev., 15, 3041–3078, https://doi.org/10.5194/gmd-15-3041-2022, https://doi.org/10.5194/gmd-15-3041-2022, 2022
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This paper extends the applicability of the SUEWS to extensive pervious areas outside cities. We derived various parameters such as leaf area index, albedo, roughness parameters and surface conductance for non-urban areas. The relation between LAI and albedo is also explored. The methods and parameters discussed can be used for both online and offline simulations. Using appropriate parameters related to non-urban areas is essential for assessing urban–rural differences.
Beatriz M. Monge-Sanz, Alessio Bozzo, Nicholas Byrne, Martyn P. Chipperfield, Michail Diamantakis, Johannes Flemming, Lesley J. Gray, Robin J. Hogan, Luke Jones, Linus Magnusson, Inna Polichtchouk, Theodore G. Shepherd, Nils Wedi, and Antje Weisheimer
Atmos. Chem. Phys., 22, 4277–4302, https://doi.org/10.5194/acp-22-4277-2022, https://doi.org/10.5194/acp-22-4277-2022, 2022
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The stratosphere is emerging as one of the keys to improve tropospheric weather and climate predictions. This study provides evidence of the role the stratospheric ozone layer plays in improving weather predictions at different timescales. Using a new ozone modelling approach suitable for high-resolution global models that provide operational forecasts from days to seasons, we find significant improvements in stratospheric meteorological fields and stratosphere–troposphere coupling.
Michael Biggart, Jenny Stocker, Ruth M. Doherty, Oliver Wild, David Carruthers, Sue Grimmond, Yiqun Han, Pingqing Fu, and Simone Kotthaus
Atmos. Chem. Phys., 21, 13687–13711, https://doi.org/10.5194/acp-21-13687-2021, https://doi.org/10.5194/acp-21-13687-2021, 2021
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Heat-related illnesses are of increasing concern in China given its rapid urbanisation and our ever-warming climate. We examine the relative impacts that land surface properties and anthropogenic heat have on the urban heat island (UHI) in Beijing using ADMS-Urban. Air temperature measurements and satellite-derived land surface temperatures provide valuable means of evaluating modelled spatiotemporal variations. This work provides critical information for urban planners and UHI mitigation.
David Meyer, Thomas Nagler, and Robin J. Hogan
Geosci. Model Dev., 14, 5205–5215, https://doi.org/10.5194/gmd-14-5205-2021, https://doi.org/10.5194/gmd-14-5205-2021, 2021
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A major limitation in training machine-learning emulators is often caused by the lack of data. This paper presents a cheap way to increase the size of training datasets using statistical techniques and thereby improve the performance of machine-learning emulators.
Claire E. Reeves, Graham P. Mills, Lisa K. Whalley, W. Joe F. Acton, William J. Bloss, Leigh R. Crilley, Sue Grimmond, Dwayne E. Heard, C. Nicholas Hewitt, James R. Hopkins, Simone Kotthaus, Louisa J. Kramer, Roderic L. Jones, James D. Lee, Yanhui Liu, Bin Ouyang, Eloise Slater, Freya Squires, Xinming Wang, Robert Woodward-Massey, and Chunxiang Ye
Atmos. Chem. Phys., 21, 6315–6330, https://doi.org/10.5194/acp-21-6315-2021, https://doi.org/10.5194/acp-21-6315-2021, 2021
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The impact of isoprene on atmospheric chemistry is dependent on how its oxidation products interact with other pollutants, specifically nitrogen oxides. Such interactions can lead to isoprene nitrates. We made measurements of the concentrations of individual isoprene nitrate isomers in Beijing and used a model to test current understanding of their chemistry. We highlight areas of uncertainty in understanding, in particular the chemistry following oxidation of isoprene by the nitrate radical.
Wenhua Wang, Longyi Shao, Claudio Mazzoleni, Yaowei Li, Simone Kotthaus, Sue Grimmond, Janarjan Bhandari, Jiaoping Xing, Xiaolei Feng, Mengyuan Zhang, and Zongbo Shi
Atmos. Chem. Phys., 21, 5301–5314, https://doi.org/10.5194/acp-21-5301-2021, https://doi.org/10.5194/acp-21-5301-2021, 2021
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We compared the characteristics of individual particles at ground level and above the mixed-layer height. We found that the particles above the mixed-layer height during haze periods are more aged compared to ground level. More coal-combustion-related primary organic particles were found above the mixed-layer height. We suggest that the particles above the mixed-layer height are affected by the surrounding areas, and once mixed down to the ground, they might contribute to ground air pollution.
Lisa K. Whalley, Eloise J. Slater, Robert Woodward-Massey, Chunxiang Ye, James D. Lee, Freya Squires, James R. Hopkins, Rachel E. Dunmore, Marvin Shaw, Jacqueline F. Hamilton, Alastair C. Lewis, Archit Mehra, Stephen D. Worrall, Asan Bacak, Thomas J. Bannan, Hugh Coe, Carl J. Percival, Bin Ouyang, Roderic L. Jones, Leigh R. Crilley, Louisa J. Kramer, William J. Bloss, Tuan Vu, Simone Kotthaus, Sue Grimmond, Yele Sun, Weiqi Xu, Siyao Yue, Lujie Ren, W. Joe F. Acton, C. Nicholas Hewitt, Xinming Wang, Pingqing Fu, and Dwayne E. Heard
Atmos. Chem. Phys., 21, 2125–2147, https://doi.org/10.5194/acp-21-2125-2021, https://doi.org/10.5194/acp-21-2125-2021, 2021
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To understand how emission controls will impact ozone, an understanding of the sources and sinks of OH and the chemical cycling between peroxy radicals is needed. This paper presents measurements of OH, HO2 and total RO2 taken in central Beijing. The radical observations are compared to a detailed chemistry model, which shows that under low NO conditions, there is a missing OH source. Under high NOx conditions, the model under-predicts RO2 and impacts our ability to model ozone.
Rutambhara Joshi, Dantong Liu, Eiko Nemitz, Ben Langford, Neil Mullinger, Freya Squires, James Lee, Yunfei Wu, Xiaole Pan, Pingqing Fu, Simone Kotthaus, Sue Grimmond, Qiang Zhang, Ruili Wu, Oliver Wild, Michael Flynn, Hugh Coe, and James Allan
Atmos. Chem. Phys., 21, 147–162, https://doi.org/10.5194/acp-21-147-2021, https://doi.org/10.5194/acp-21-147-2021, 2021
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Black carbon (BC) is a component of particulate matter which has significant effects on climate and human health. Sources of BC include biomass burning, transport, industry and domestic cooking and heating. In this study, we measured BC emissions in Beijing, finding a dominance of traffic emissions over all other sources. The quantitative method presented here has benefits for revising widely used emissions inventories and for understanding BC sources with impacts on air quality and climate.
Robin J. Hogan and Marco Matricardi
Geosci. Model Dev., 13, 6501–6521, https://doi.org/10.5194/gmd-13-6501-2020, https://doi.org/10.5194/gmd-13-6501-2020, 2020
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A key component of computer models used to predict weather and climate is the radiation scheme, which calculates how solar and infrared radiation heats and cools the atmosphere and surface, including the important role of greenhouse gases. This paper describes the experimental protocol and large datasets for a new project, CKDMIP, to evaluate and improve the accuracy of the treatment of atmospheric gases in the radiation schemes used worldwide, as well as their computational speed.
Isabella Capel-Timms, Stefán Thor Smith, Ting Sun, and Sue Grimmond
Geosci. Model Dev., 13, 4891–4924, https://doi.org/10.5194/gmd-13-4891-2020, https://doi.org/10.5194/gmd-13-4891-2020, 2020
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Thermal emissions or anthropogenic heat fluxes (QF) from human activities impact the local- and larger-scale urban climate. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, and socio-economic factors and in response to environmental conditions.
Freya A. Squires, Eiko Nemitz, Ben Langford, Oliver Wild, Will S. Drysdale, W. Joe F. Acton, Pingqing Fu, C. Sue B. Grimmond, Jacqueline F. Hamilton, C. Nicholas Hewitt, Michael Hollaway, Simone Kotthaus, James Lee, Stefan Metzger, Natchaya Pingintha-Durden, Marvin Shaw, Adam R. Vaughan, Xinming Wang, Ruili Wu, Qiang Zhang, and Yanli Zhang
Atmos. Chem. Phys., 20, 8737–8761, https://doi.org/10.5194/acp-20-8737-2020, https://doi.org/10.5194/acp-20-8737-2020, 2020
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Significant air quality problems exist in megacities like Beijing, China. To manage air pollution, legislators need a clear understanding of pollutant emissions. However, emissions inventories have large uncertainties, and reliable field measurements of pollutant emissions are required to constrain them. This work presents the first measurements of traffic-dominated emissions in Beijing which suggest that inventories overestimate these emissions in the region during both winter and summer.
Michael Biggart, Jenny Stocker, Ruth M. Doherty, Oliver Wild, Michael Hollaway, David Carruthers, Jie Li, Qiang Zhang, Ruili Wu, Simone Kotthaus, Sue Grimmond, Freya A. Squires, James Lee, and Zongbo Shi
Atmos. Chem. Phys., 20, 2755–2780, https://doi.org/10.5194/acp-20-2755-2020, https://doi.org/10.5194/acp-20-2755-2020, 2020
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Ambient air pollution is a major cause of premature death in China. We examine the street-scale variation of pollutant levels in Beijing using air pollution dispersion and chemistry model ADMS-Urban. Campaign measurements are compared with simulated pollutant levels, providing a valuable means of evaluating the impact of key processes on urban air quality. Air quality modelling at such fine scales is essential for human exposure studies and for informing choices on future emission controls.
Shannon L. Mason, Robin J. Hogan, Christopher D. Westbrook, Stefan Kneifel, Dmitri Moisseev, and Leonie von Terzi
Atmos. Meas. Tech., 12, 4993–5018, https://doi.org/10.5194/amt-12-4993-2019, https://doi.org/10.5194/amt-12-4993-2019, 2019
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The mass contents of snowflakes are critical to remotely sensed estimates of snowfall. The signatures of snow measured at three radar frequencies can distinguish fluffy, fractal snowflakes from dense and more homogeneous rimed snow. However, we show that the shape of the particle size spectrum also has a significant impact on triple-frequency radar signatures and must be accounted for when making triple-frequency radar estimates of snow that include variations in particle structure and density.
Ting Sun and Sue Grimmond
Geosci. Model Dev., 12, 2781–2795, https://doi.org/10.5194/gmd-12-2781-2019, https://doi.org/10.5194/gmd-12-2781-2019, 2019
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A Python-enhanced urban land surface model, SuPy (SUEWS in Python), is presented with its development (the SUEWS interface modification, F2PY configuration and Python frontend implementation), cross-platform deployment (PyPI, Python Package Index) and demonstration (online tutorials in Jupyter notebooks for users of different levels). SuPy represents a significant enhancement that supports existing and new model applications, reproducibility and enhanced functionality.
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.
Tom V. Kokkonen, Sue Grimmond, Sonja Murto, Huizhi Liu, Anu-Maija Sundström, and Leena Järvi
Atmos. Chem. Phys., 19, 7001–7017, https://doi.org/10.5194/acp-19-7001-2019, https://doi.org/10.5194/acp-19-7001-2019, 2019
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This is the first study to evaluate and correct the WATCH WFDEI reanalysis product in a highly polluted urban environment. It gives an important understanding of the uncertainties in reanalysis products in local-scale urban modelling in polluted environments and identifies and corrects the most important variables in hydrological modelling. This is also the first study to examine the effects of haze on the local-scale urban hydrological cycle.
Dantong Liu, Rutambhara Joshi, Junfeng Wang, Chenjie Yu, James D. Allan, Hugh Coe, Michael J. Flynn, Conghui Xie, James Lee, Freya Squires, Simone Kotthaus, Sue Grimmond, Xinlei Ge, Yele Sun, and Pingqing Fu
Atmos. Chem. Phys., 19, 6749–6769, https://doi.org/10.5194/acp-19-6749-2019, https://doi.org/10.5194/acp-19-6749-2019, 2019
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This study provides source attribution and characterization of BC in the Beijing urban environment in both winter and summer. For the first time, the physically and chemically based source apportionments are compared to evaluate the primary source contribution and secondary processing of BC-containing particles. A method is proposed to isolate the BC from the transportation sector and coal combustion sources.
Jeronimo Escribano, Alessio Bozzo, Philippe Dubuisson, Johannes Flemming, Robin J. Hogan, Laurent C.-Labonnote, and Olivier Boucher
Geosci. Model Dev., 12, 805–827, https://doi.org/10.5194/gmd-12-805-2019, https://doi.org/10.5194/gmd-12-805-2019, 2019
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Accurate shortwave radiance computations are becoming increasingly important for some applications in atmospheric composition. In this work we propose a benchmark protocol and dataset to asses the accuracy and computing runtime of radiance calculations of radiative transfer models. It is applied to four models, showing the potential of this benchmark to evaluate the model performance under a variety of atmospheric conditions, viewing geometries, aerosol loading, and optical properties.
Roy M. Harrison, David C. S. Beddows, Mohammed S. Alam, Ajit Singh, James Brean, Ruixin Xu, Simone Kotthaus, and Sue Grimmond
Atmos. Chem. Phys., 19, 39–55, https://doi.org/10.5194/acp-19-39-2019, https://doi.org/10.5194/acp-19-39-2019, 2019
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Particle number size distributions were measured simultaneously at five sites in London during a campaign. Observations are interpreted in terms of both evaporative shrinkage of traffic-generated particles and condensational growth, probably of traffic-generated particles under cool nocturnal conditions, as well as the influence of particles emitted from Heathrow Airport at a distance of about 22 km. The work highlights the highly dynamic behaviour of nanoparticles within the urban atmosphere.
Robin J. Hogan, Tristan Quaife, and Renato Braghiere
Geosci. Model Dev., 11, 339–350, https://doi.org/10.5194/gmd-11-339-2018, https://doi.org/10.5194/gmd-11-339-2018, 2018
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This paper describes a fast new method for calculating how much sunlight is absorbed and reflected by forests and other types of vegetation, rigorously taking account of the complex 3-D structure. Careful evaluation shows it to perform well even in difficult scenes with snow on the ground. The method is suitable for use within the computer models used to make weather and climate forecasts, where it has the potential to improve predictions of near-surface temperature and photosynthesis rates.
Shannon L. Mason, J. Christine Chiu, Robin J. Hogan, and Lin Tian
Atmos. Chem. Phys., 17, 11567–11589, https://doi.org/10.5194/acp-17-11567-2017, https://doi.org/10.5194/acp-17-11567-2017, 2017
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Airborne Doppler radar measurements are used to estimate the properties of tropical stratiform rain. Doppler velocity measurements provide sufficient information to estimate the rain rate over land and also to retrieve the raindrop size distribution over ocean, addressing major uncertainties in current satellite measurements of rain. These results suggest that EarthCARE, with the first space-borne Doppler radar, will facilitate improved global measurements of rain.
Ting Sun, Zhi-Hua Wang, Walter C. Oechel, and Sue Grimmond
Geosci. Model Dev., 10, 2875–2890, https://doi.org/10.5194/gmd-10-2875-2017, https://doi.org/10.5194/gmd-10-2875-2017, 2017
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The diurnal hysteresis behaviour found between the net storage heat flux and net all-wave radiation has been captured in the Objective Hysteresis Model (OHM). To facilitate use, and enhance physical interpretations of the OHM coefficients, we develop the Analytical Objective Hysteresis Model (AnOHM) using an analytical solution of the one-dimensional advection–diffusion equation of coupled heat and liquid water transport in conjunction with the surface energy balance relationship.
Carole Helfter, Anja H. Tremper, Christoforos H. Halios, Simone Kotthaus, Alex Bjorkegren, C. Sue B. Grimmond, Janet F. Barlow, and Eiko Nemitz
Atmos. Chem. Phys., 16, 10543–10557, https://doi.org/10.5194/acp-16-10543-2016, https://doi.org/10.5194/acp-16-10543-2016, 2016
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There are relatively few long-term, direct measurements of pollutant emissions in urban settings. We present over 3 years of measurements of fluxes of CO, CO2 and CH4, study their respective temporal and spatial dynamics and offer an independent verification of the London Atmospheric Emissions Inventory. CO and CO2 were strongly controlled by traffic and well characterised by the inventory whilst measured CH4 was two-fold larger and linked to natural gas usage and perhaps biogenic sources.
Simone Kotthaus, Ewan O'Connor, Christoph Münkel, Cristina Charlton-Perez, Martial Haeffelin, Andrew M. Gabey, and C. Sue B. Grimmond
Atmos. Meas. Tech., 9, 3769–3791, https://doi.org/10.5194/amt-9-3769-2016, https://doi.org/10.5194/amt-9-3769-2016, 2016
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Ceilometers lidars are useful to study clouds, aerosol layers and atmospheric boundary layer structures. As sensor optics and acquisition algorithms can strongly influence the observations, sensor specifics need to be incorporated into the physical interpretation. Here, recommendations are made for the operation and processing of profile observations from the widely deployed Vaisala CL31 ceilometer. Proposed corrections are shown to increase data quality and even data availability at times.
J. Lindén, C.S.B. Grimmond, and J. Esper
Adv. Sci. Res., 12, 157–162, https://doi.org/10.5194/asr-12-157-2015, https://doi.org/10.5194/asr-12-157-2015, 2015
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Long term meteorological records from stations associated with villages are generally classified as rural and assumed to have no urban influence. Using temperature sensor networks installed around two such stations, spatial variations of the same order magnitude as the long-term temperature trend from these stations were found. The potential bias in the long term series therefore warrants careful consideration in temperature trend evaluation also in village stations.
M. D. Fielding, J. C. Chiu, R. J. Hogan, G. Feingold, E. Eloranta, E. J. O'Connor, and M. P. Cadeddu
Atmos. Meas. Tech., 8, 2663–2683, https://doi.org/10.5194/amt-8-2663-2015, https://doi.org/10.5194/amt-8-2663-2015, 2015
H. C. Ward, J. G. Evans, C. S. B. Grimmond, and J. Bradford
Atmos. Meas. Tech., 8, 1385–1405, https://doi.org/10.5194/amt-8-1385-2015, https://doi.org/10.5194/amt-8-1385-2015, 2015
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Two-wavelength scintillometry, a ground-based remote sensing technique for deriving large-area heat fluxes, has been used over an urban area for the first time. The long data set enables investigation of the performance of the technique and characteristics of turbulent transport processes at sub-daily to inter-annual timescales. In this first paper, the structure parameters of temperature and humidity, and the correlation between temperature and humidity, are presented and analysed.
H. C. Ward, J. G. Evans, and C. S. B. Grimmond
Atmos. Meas. Tech., 8, 1407–1424, https://doi.org/10.5194/amt-8-1407-2015, https://doi.org/10.5194/amt-8-1407-2015, 2015
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Two-wavelength scintillometry, a ground-based remote sensing technique for deriving large-area heat fluxes, has been used over an urban area for the first time. The long data set enables investigation of the performance of the technique and characteristics of turbulent transport processes at sub-daily to inter-annual timescales. In this second paper, sensible and latent heat fluxes representative of an area of 5--10 km2 are presented and analysed.
J. C. Chiu, J. A. Holmes, R. J. Hogan, and E. J. O'Connor
Atmos. Chem. Phys., 14, 8389–8401, https://doi.org/10.5194/acp-14-8389-2014, https://doi.org/10.5194/acp-14-8389-2014, 2014
L. Järvi, C. S. B. Grimmond, M. Taka, A. Nordbo, H. Setälä, and I. B. Strachan
Geosci. Model Dev., 7, 1691–1711, https://doi.org/10.5194/gmd-7-1691-2014, https://doi.org/10.5194/gmd-7-1691-2014, 2014
A. Font, C. S. B. Grimmond, J.-A. Morguí, S. Kotthaus, M. Priestman, and B. Barratt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-13465-2013, https://doi.org/10.5194/acpd-13-13465-2013, 2013
Revised manuscript not accepted
H. C. Ward, J. G. Evans, and C. S. B. Grimmond
Atmos. Chem. Phys., 13, 4645–4666, https://doi.org/10.5194/acp-13-4645-2013, https://doi.org/10.5194/acp-13-4645-2013, 2013
Related subject area
Atmospheric sciences
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
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The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
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Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
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Short summary
Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer...
