Articles | Volume 10, issue 4
https://doi.org/10.5194/gmd-10-1703-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-1703-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
21 Apr 2017
Model evaluation paper |
| 21 Apr 2017
Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1
K. Wyat Appel
CORRESPONDING AUTHOR
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Sergey L. Napelenok
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Kristen M. Foley
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Havala O. T. Pye
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Christian Hogrefe
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Deborah J. Luecken
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Jesse O. Bash
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Shawn J. Roselle
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Jonathan E. Pleim
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Hosein Foroutan
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
William T. Hutzell
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
George A. Pouliot
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Golam Sarwar
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Kathleen M. Fahey
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Brett Gantt
Air Quality Analysis Division, Office of Air Quality Planning and
Standards, Office of Air and Radiation, US Environmental Protection Agency, Research Triangle Park, NC, USA
Robert C. Gilliam
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Nicholas K. Heath
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Daiwen Kang
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Rohit Mathur
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Donna B. Schwede
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Tanya L. Spero
Systems Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
David C. Wong
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
Jeffrey O. Young
Computational Exposure Division, National Exposure Research Laboratory,
Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, USA
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Benjamin N. Murphy, Darrell Sonntag, Karl M. Seltzer, Havala O. T. Pye, Christine Allen, Evan Murray, Claudia Toro, Drew R. Gentner, Cheng Huang, Shantanu H. Jathar, Li Li, Andrew A. May, and Allen L. Robinson
EGUsphere, https://doi.org/10.5194/egusphere-2023-855, https://doi.org/10.5194/egusphere-2023-855, 2023
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We update methods for calculating organic particle and vapor emissions from mobile sources in the U.S. Conventionally, particulate matter (PM) and volatile organic carbon (VOC) are speciated without consideration of primary semivolatile emissions. Our methods integrate state-of-the-science speciation profiles and correct for common artifacts when sampling emissions in a laboratory. We quantify impacts of the emission updates on ambient pollution with the Community Multiscale Air Quality model.
Havala O. T. Pye, Bryan K. Place, Benjamin N. Murphy, Karl M. Seltzer, Emma L. D'Ambro, Christine Allen, Ivan R. Piletic, Sara Farrell, Rebecca H. Schwantes, Matthew M. Coggon, Emily Saunders, Lu Xu, Golam Sarwar, William T. Hutzell, Kristen M. Foley, George Pouliot, Jesse Bash, and William R. Stockwell
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Elyse A. Pennington, Yuan Wang, Benjamin C. Schulze, Karl M. Seltzer, Jiani Yang, Bin Zhao, Zhe Jiang, Hongru Shi, Melissa Venecek, Daniel Chau, Benjamin N. Murphy, Christopher M. Kenseth, Ryan X. Ward, Havala O. T. Pye, and John H. Seinfeld
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Qian Shu, Sergey L. Napelenok, William T. Hutzell, Kirk R. Baker, Barron H. Henderson, Benjamin N. Murphy, and Christian Hogrefe
Geosci. Model Dev., 16, 2303–2322, https://doi.org/10.5194/gmd-16-2303-2023, https://doi.org/10.5194/gmd-16-2303-2023, 2023
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Source attribution methods are generally used to determine culpability of precursor emission sources to ambient pollutant concentrations. However, source attribution of secondarily formed pollutants such as ozone and its precursors cannot be explicitly measured, making evaluation of source apportionment methods challenging. In this study, multiple apportionment approach comparisons show common features but still reveal wide variations in predicted sector contribution and species dependency.
Forwood Wiser, Bryan K. Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
Geosci. Model Dev., 16, 1801–1821, https://doi.org/10.5194/gmd-16-1801-2023, https://doi.org/10.5194/gmd-16-1801-2023, 2023
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We developed a reduced model of atmospheric isoprene oxidation, AMORE-Isoprene 1.0. It was created using a new Automated Model Reduction (AMORE) method designed to simplify complex chemical mechanisms with minimal manual adjustments to the output. AMORE-Isoprene 1.0 has improved accuracy and similar size to other reduced isoprene mechanisms. When included in the CRACMM mechanism, it improved the accuracy of EPA’s CMAQ model predictions for the northeastern USA compared to observations.
John T. Walker, Xi Chen, Zhiyong Wu, Donna Schwede, Ryan Daly, Aleksandra Djurkovic, A. Christopher Oishi, Eric Edgerton, Jesse Bash, Jennifer Knoepp, Melissa Puchalski, John Iiames, and Chelcy F. Miniat
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Better estimates of atmospheric nitrogen (N) deposition are needed to accurately assess ecosystem risk and impacts from deposition of nutrients and acidity. Using measurements and modeling, we estimate total N deposition of 6.7 kg N ha−1 yr−1 at a forest site in the southern Appalachian Mountains, a region sensitive to atmospheric deposition. Reductions in deposition of reduced forms of N (ammonia and ammonium) will be needed to meet the lowest estimates of N critical loads for the region.
Michael S. Walters and David C. Wong
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A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.
James D. East, Barron H. Henderson, Sergey L. Napelenok, Shannon N. Koplitz, Golam Sarwar, Robert Gilliam, Allen Lenzen, Daniel Q. Tong, R. Bradley Pierce, and Fernando Garcia-Menendez
Atmos. Chem. Phys., 22, 15981–16001, https://doi.org/10.5194/acp-22-15981-2022, https://doi.org/10.5194/acp-22-15981-2022, 2022
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We present a framework that uses a computer model of air quality, along with air pollution data from satellite instruments, to estimate emissions of nitrogen oxides (NOx) across the Northern Hemisphere. The framework, which advances current methods to infer emissions from satellite observations, provides observationally constrained NOx estimates, including in regions of the world where emissions are highly uncertain, and can improve simulations of air pollutants relevant for health and policy.
Daiwen Kang, Nicholas K. Heath, Robert C. Gilliam, Tanya L. Spero, and Jonathan E. Pleim
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A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF) convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the KF scheme on simulations with and without LTA are assessed. The model's performance is improved significantly by LTA, but it is sensitive to various factors.
Peeyush Khare, Jordan E. Krechmer, Jo E. Machesky, Tori Hass-Mitchell, Cong Cao, Junqi Wang, Francesca Majluf, Felipe Lopez-Hilfiker, Sonja Malek, Will Wang, Karl Seltzer, Havala O. T. Pye, Roisin Commane, Brian C. McDonald, Ricardo Toledo-Crow, John E. Mak, and Drew R. Gentner
Atmos. Chem. Phys., 22, 14377–14399, https://doi.org/10.5194/acp-22-14377-2022, https://doi.org/10.5194/acp-22-14377-2022, 2022
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Ammonium adduct chemical ionization is used to examine the atmospheric abundances of oxygenated volatile organic compounds associated with emissions from volatile chemical products, which are now key contributors of reactive precursors to ozone and secondary organic aerosols in urban areas. The application of this valuable measurement approach in densely populated New York City enables the evaluation of emissions inventories and thus the role these oxygenated compounds play in urban air quality.
Sarah E. Benish, Jesse O. Bash, Kristen M. Foley, K. Wyat Appel, Christian Hogrefe, Robert Gilliam, and George Pouliot
Atmos. Chem. Phys., 22, 12749–12767, https://doi.org/10.5194/acp-22-12749-2022, https://doi.org/10.5194/acp-22-12749-2022, 2022
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We assess Community Multiscale Air Quality (CMAQ) model simulations of nitrogen and sulfur deposition over US climate regions to evaluate the model ability to reproduce long-term deposition trends and total deposition budgets. A measurement–model fusion technique is found to improve estimates of wet deposition. Emission controls set by the Clean Air Act successfully decreased oxidized nitrogen deposition across the US; we find increasing amounts of reduced nitrogen to the total nitrogen budget.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
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This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Charbel Harb and Hosein Foroutan
Atmos. Chem. Phys., 22, 11759–11779, https://doi.org/10.5194/acp-22-11759-2022, https://doi.org/10.5194/acp-22-11759-2022, 2022
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A model representation of lake spray aerosol (LSA) ejection from freshwater breaking waves is crucial for understanding their climatic and public health impacts. We develop an LSA emission parameterization and implement it in an atmospheric model to investigate Great Lakes surface emissions. We find that the same breaking wave is likely to produce fewer aerosols in freshwater than in saltwater and that Great Lakes emissions influence the regional aerosol burden and can reach the cloud layer.
Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022, https://doi.org/10.5194/gmd-15-3281-2022, 2022
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NOAA's National Air Quality Forecast Capability (NAQFC) continues to protect Americans from the harmful effects of air pollution, while saving billions of dollars per year. Here we describe and evaluate the development of the most advanced version of the NAQFC to date, which became operational at NOAA on 20 July 2021. The new NAQFC is based on a coupling of NOAA's operational Global Forecast System (GFS) version 16 with the Community Multiscale Air Quality (CMAQ) model version 5.3.1.
Jiandong Wang, Jia Xing, Shuxiao Wang, Rohit Mathur, Jiaping Wang, Yuqiang Zhang, Chao Liu, Jonathan Pleim, Dian Ding, Xing Chang, Jingkun Jiang, Peng Zhao, Shovan Kumar Sahu, Yuzhi Jin, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 22, 5147–5156, https://doi.org/10.5194/acp-22-5147-2022, https://doi.org/10.5194/acp-22-5147-2022, 2022
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Aerosols reduce surface solar radiation and change the photolysis rate and planetary boundary layer stability. In this study, the online coupled meteorological and chemistry model was used to explore the detailed pathway of how aerosol direct effects affect secondary inorganic aerosol. The effects through the dynamics pathway act as an equally or even more important route compared with the photolysis pathway in affecting secondary aerosol concentration in both summer and winter.
Amir H. Souri, Kelly Chance, Juseon Bak, Caroline R. Nowlan, Gonzalo González Abad, Yeonjin Jung, David C. Wong, Jingqiu Mao, and Xiong Liu
Atmos. Chem. Phys., 21, 18227–18245, https://doi.org/10.5194/acp-21-18227-2021, https://doi.org/10.5194/acp-21-18227-2021, 2021
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The global pandemic is believed to have an impact on emissions of air pollutants such as nitrogen dioxide (NO2) and formaldehyde (HCHO). This study quantifies the changes in the amount of NOx and VOC emissions via state-of-the-art inverse modeling technique using satellite observations during the lockdown 2020 with respect to a baseline over Europe, which in turn, it permits unraveling atmospheric processes being responsible for ozone formation in a less cloudy month.
Elyse A. Pennington, Karl M. Seltzer, Benjamin N. Murphy, Momei Qin, John H. Seinfeld, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 18247–18261, https://doi.org/10.5194/acp-21-18247-2021, https://doi.org/10.5194/acp-21-18247-2021, 2021
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Volatile chemical products (VCPs) are commonly used consumer and industrial items that contribute to the formation of atmospheric aerosol. We implemented the emissions and chemistry of VCPs in a regional-scale model and compared predictions with measurements made in Los Angeles. Our results reduced model bias and suggest that VCPs may contribute up to half of anthropogenic secondary organic aerosol in Los Angeles and are an important source of human-influenced particular matter in urban areas.
Kai Wang, Yang Zhang, Shaocai Yu, David C. Wong, Jonathan Pleim, Rohit Mathur, James T. Kelly, and Michelle Bell
Geosci. Model Dev., 14, 7189–7221, https://doi.org/10.5194/gmd-14-7189-2021, https://doi.org/10.5194/gmd-14-7189-2021, 2021
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The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has been applied to the long-term predictions of regional meteorology and air quality over the US. The model results show superior performance and importance of chemistry–meteorology feedbacks when compared to the offline coupled WRF and CMAQ simulations, which suggests that feedbacks should be considered along with other factors in developing future model applications to inform policy making.
Shuping Zhang, Golam Sarwar, Jia Xing, Biwu Chu, Chaoyang Xue, Arunachalam Sarav, Dian Ding, Haotian Zheng, Yujing Mu, Fengkui Duan, Tao Ma, and Hong He
Atmos. Chem. Phys., 21, 15809–15826, https://doi.org/10.5194/acp-21-15809-2021, https://doi.org/10.5194/acp-21-15809-2021, 2021
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Six heterogeneous HONO chemistry updates in CMAQ significantly improve HONO concentration. HONO production is primarily controlled by the heterogeneous reactions on ground and aerosol surfaces during haze. Additional HONO chemistry updates increase OH and production of secondary aerosols: sulfate, nitrate, and SOA.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697, https://doi.org/10.5194/acp-21-15663-2021, https://doi.org/10.5194/acp-21-15663-2021, 2021
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This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Geosci. Model Dev., 14, 5751–5768, https://doi.org/10.5194/gmd-14-5751-2021, https://doi.org/10.5194/gmd-14-5751-2021, 2021
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The Community Multiscale Air Quality (CMAQ) modeling system extended for hemispheric-scale applications (H-CMAQ) incorporated the satellite-constrained degassing SO2 emissions from 50 volcanos across the Northern Hemisphere. The impact on tropospheric sulfate aerosol (SO42−) is assessed for 2010. Although the considered volcanic emissions occurred at or below the middle of free troposphere (500 hPa), SO42− enhancements of more than 10 % were detected up to the top of free troposphere (250 hPa).
Andreas Tilgner, Thomas Schaefer, Becky Alexander, Mary Barth, Jeffrey L. Collett Jr., Kathleen M. Fahey, Athanasios Nenes, Havala O. T. Pye, Hartmut Herrmann, and V. Faye McNeill
Atmos. Chem. Phys., 21, 13483–13536, https://doi.org/10.5194/acp-21-13483-2021, https://doi.org/10.5194/acp-21-13483-2021, 2021
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Feedbacks of acidity and atmospheric multiphase chemistry in deliquesced particles and clouds are crucial for the tropospheric composition, depositions, climate, and human health. This review synthesizes the current scientific knowledge on these feedbacks using both inorganic and organic aqueous-phase chemistry. Finally, this review outlines atmospheric implications and highlights the need for future investigations with respect to reducing emissions of key acid precursors in a changing world.
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021, https://doi.org/10.5194/gmd-14-3969-2021, 2021
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The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
Karoline K. Barkjohn, Brett Gantt, and Andrea L. Clements
Atmos. Meas. Tech., 14, 4617–4637, https://doi.org/10.5194/amt-14-4617-2021, https://doi.org/10.5194/amt-14-4617-2021, 2021
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Although widely used, air sensor measurements are often biased. In this work we develop a correction with a relative humidity term that reduces the bias and improves consistency between different United States regions. This correction equation, along with proposed data cleaning criteria, has been applied to PurpleAir PM2.5 measurements across the US on the AirNow Fire and Smoke Map and has the potential to be successfully used in other air quality and public health applications.
Benjamin N. Murphy, Christopher G. Nolte, Fahim Sidi, Jesse O. Bash, K. Wyat Appel, Carey Jang, Daiwen Kang, James Kelly, Rohit Mathur, Sergey Napelenok, George Pouliot, and Havala O. T. Pye
Geosci. Model Dev., 14, 3407–3420, https://doi.org/10.5194/gmd-14-3407-2021, https://doi.org/10.5194/gmd-14-3407-2021, 2021
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The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical aspect of atmospheric modeling.
K. Wyat Appel, Jesse O. Bash, Kathleen M. Fahey, Kristen M. Foley, Robert C. Gilliam, Christian Hogrefe, William T. Hutzell, Daiwen Kang, Rohit Mathur, Benjamin N. Murphy, Sergey L. Napelenok, Christopher G. Nolte, Jonathan E. Pleim, George A. Pouliot, Havala O. T. Pye, Limei Ran, Shawn J. Roselle, Golam Sarwar, Donna B. Schwede, Fahim I. Sidi, Tanya L. Spero, and David C. Wong
Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, https://doi.org/10.5194/gmd-14-2867-2021, 2021
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This paper details the scientific updates in the recently released CMAQ version 5.3 (and v5.3.1) and also includes operational and diagnostic evaluations of CMAQv5.3.1 against observations and the previous version of the CMAQ (v5.2.1). This work was done to improve the underlying science in CMAQ. This article is used to inform the CMAQ modeling community of the updates to the modeling system and the expected change in model performance from these updates (versus the previous model version).
Qian Shu, Benjamin Murphy, Jonathan E. Pleim, Donna Schwede, Barron H. Henderson, Havala O.T. Pye, Keith Wyat Appel, Tanvir R. Khan, and Judith A. Perlinger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-129, https://doi.org/10.5194/gmd-2021-129, 2021
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We have bridged the gap between dry deposition measurement and modeling by rigorous use of box and regional transport models and field measurements, but more efforts are needed. This study highlights that deviation among deposition schemes is most pronounced for small and large particles. This study better links model predictions to available real-world observations and incrementally reduces uncertainties in the magnitude of loss processes important for the lifecycle of air pollutants.
Karl M. Seltzer, Elyse Pennington, Venkatesh Rao, Benjamin N. Murphy, Madeleine Strum, Kristin K. Isaacs, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 5079–5100, https://doi.org/10.5194/acp-21-5079-2021, https://doi.org/10.5194/acp-21-5079-2021, 2021
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Volatile chemical products (VCPs) are an increasingly important source of anthropogenic reactive organic carbon emissions. Here, we develop VCPy, a new framework to model organic emissions from VCPs throughout the United States. At the national-level, VCPy emissions are broadly consistent with the US EPA’s 2017 National Emission Inventory, however county-level and categorical estimates can differ substantially. An observational evaluation indicates high fidelity in the methods employed here.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
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Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Huiying Luo, Marina Astitha, Christian Hogrefe, Rohit Mathur, and S. Trivikrama Rao
Atmos. Chem. Phys., 20, 13801–13815, https://doi.org/10.5194/acp-20-13801-2020, https://doi.org/10.5194/acp-20-13801-2020, 2020
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A new method is introduced to evaluate nonlinear, nonstationary modeled PM2.5 time series by decomposing decadal PM2.5 concentrations and its species onto various timescales. It does not require preselection of temporal scales and assumptions of linearity and stationarity. It provides a unique opportunity to assess the influence of each species on total PM2.5. The results reveal a phase shift in modeled EC/OC concentrations, indicating the need for improved model treatment of organic aerosols.
Ryan Schmedding, Quazi Z. Rasool, Yue Zhang, Havala O. T. Pye, Haofei Zhang, Yuzhi Chen, Jason D. Surratt, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Allen H. Goldstein, and William Vizuete
Atmos. Chem. Phys., 20, 8201–8225, https://doi.org/10.5194/acp-20-8201-2020, https://doi.org/10.5194/acp-20-8201-2020, 2020
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Accurate model prediction of aerosol concentrations is a known challenge. It is assumed in many modeling systems that aerosols are in a homogeneously mixed phase state. It has been observed that aerosols do phase separate and can form a highly viscous organic shell with an aqueous core impacting the formation processes of aerosols. This work is a model implementation to determine an aerosol's phase state using glass transition temperature and aerosol composition.
Shunliu Zhao, Matthew G. Russell, Amir Hakami, Shannon L. Capps, Matthew D. Turner, Daven K. Henze, Peter B. Percell, Jaroslav Resler, Huizhong Shen, Armistead G. Russell, Athanasios Nenes, Amanda J. Pappin, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Charles O. Stanier, and Tianfeng Chai
Geosci. Model Dev., 13, 2925–2944, https://doi.org/10.5194/gmd-13-2925-2020, https://doi.org/10.5194/gmd-13-2925-2020, 2020
Sungyeon Choi, Lok N. Lamsal, Melanie Follette-Cook, Joanna Joiner, Nickolay A. Krotkov, William H. Swartz, Kenneth E. Pickering, Christopher P. Loughner, Wyat Appel, Gabriele Pfister, Pablo E. Saide, Ronald C. Cohen, Andrew J. Weinheimer, and Jay R. Herman
Atmos. Meas. Tech., 13, 2523–2546, https://doi.org/10.5194/amt-13-2523-2020, https://doi.org/10.5194/amt-13-2523-2020, 2020
Havala O. T. Pye, Athanasios Nenes, Becky Alexander, Andrew P. Ault, Mary C. Barth, Simon L. Clegg, Jeffrey L. Collett Jr., Kathleen M. Fahey, Christopher J. Hennigan, Hartmut Herrmann, Maria Kanakidou, James T. Kelly, I-Ting Ku, V. Faye McNeill, Nicole Riemer, Thomas Schaefer, Guoliang Shi, Andreas Tilgner, John T. Walker, Tao Wang, Rodney Weber, Jia Xing, Rahul A. Zaveri, and Andreas Zuend
Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, https://doi.org/10.5194/acp-20-4809-2020, 2020
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Acid rain is recognized for its impacts on human health and ecosystems, and programs to mitigate these effects have had implications for atmospheric acidity. Historical measurements indicate that cloud and fog droplet acidity has changed in recent decades in response to controls on emissions from human activity, while the limited trend data for suspended particles indicate acidity may be relatively constant. This review synthesizes knowledge on the acidity of atmospheric particles and clouds.
Quanyang Lu, Benjamin N. Murphy, Momei Qin, Peter J. Adams, Yunliang Zhao, Havala O. T. Pye, Christos Efstathiou, Chris Allen, and Allen L. Robinson
Atmos. Chem. Phys., 20, 4313–4332, https://doi.org/10.5194/acp-20-4313-2020, https://doi.org/10.5194/acp-20-4313-2020, 2020
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This research work investigates organic aerosol formation in California during the CalNex study. We update the chemical transport model with the most recent mobile-source emission data and introduce a simple parameterization for secondary organic aerosol formed from intermediate-volatility organic compounds. Our results highlight the important contribution of IVOCs to SOA production in the Los Angeles region but underscore that other uncertainties must be addressed to close the SOA mass balance.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, and Yang Zhang
Atmos. Chem. Phys., 20, 3373–3396, https://doi.org/10.5194/acp-20-3373-2020, https://doi.org/10.5194/acp-20-3373-2020, 2020
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The state-of-the-science Community Multiscale Air Quality model extended for hemispheric applications (H-CMAQ) is used to model the trans-Pacific transport which has been recognized as a potential source of air pollutants over the US. In Part 1, modeled ozone is evaluated with observations at surface, by ozonesonde and airplane, and by satellite across the Northern Hemisphere. In addition, a newly developed air mass characterization method to estimate stratospheric intrusion is presented.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Atmos. Chem. Phys., 20, 3397–3413, https://doi.org/10.5194/acp-20-3397-2020, https://doi.org/10.5194/acp-20-3397-2020, 2020
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The state-of-the-science Community Multiscale Air Quality model extended for hemispheric applications (H-CMAQ) is used to model the trans-Pacific transport which has been recognized as a potential source of air pollutants over the US. In Part 2, the higher-order decoupled direct method (HDDM) is applied to investigate the emission impacts from east Asia and the US during April 2010. Furthermore, changes in trans-Pacific transport caused by the recent emissions are examined.
S. Trivikrama Rao, Huiying Luo, Marina Astitha, Christian Hogrefe, Valerie Garcia, and Rohit Mathur
Atmos. Chem. Phys., 20, 1627–1639, https://doi.org/10.5194/acp-20-1627-2020, https://doi.org/10.5194/acp-20-1627-2020, 2020
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Since numerical air quality models do not explicitly simulate stochastic variations in the atmosphere, there will always be differences between modeled and measured pollutant levels even when the model's physics, chemistry, numerical analysis, and its input data are perfect. This paper quantifies the inherent uncertainty in regional models due to the stochastic nature of the atmosphere. A knowledge of the expected error helps model developers in evaluating the real progress in improving models.
Qinyi Li, Rafael Borge, Golam Sarwar, David de la Paz, Brett Gantt, Jessica Domingo, Carlos A. Cuevas, and Alfonso Saiz-Lopez
Atmos. Chem. Phys., 19, 15321–15337, https://doi.org/10.5194/acp-19-15321-2019, https://doi.org/10.5194/acp-19-15321-2019, 2019
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The abundance and distribution of reactive halogen species and their impact on air quality in Europe are poorly understood. We adopt a state-of-the-art regional model (CMAQ) to evaluate such effects, and the results demonstrate the significant influence of halogen chemistry on the capacity of atmospheric oxidation and the formation of air pollutants in Europe. Our study highlights the necessity of including halogen chemistry in the formulation of air pollution control policy.
Daiwen Kang, Kristen M. Foley, Rohit Mathur, Shawn J. Roselle, Kenneth E. Pickering, and Dale J. Allen
Geosci. Model Dev., 12, 4409–4424, https://doi.org/10.5194/gmd-12-4409-2019, https://doi.org/10.5194/gmd-12-4409-2019, 2019
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This paper provides a comprehensive evaluation of the lightning production schemes in CMAQ as described in https://www.geosci-model-dev.net/12/3071/2019/gmd-12-3071-2019.html on model performance. The impact of lightning NOx from different schemes is evaluated in time and space using both ground–level network measurements and aloft (ozonesonde and aircraft) observations. These results provide users the benchmark model performance when the lightning NOx production schemes are applied.
Daiwen Kang, Kenneth E. Pickering, Dale J. Allen, Kristen M. Foley, David C. Wong, Rohit Mathur, and Shawn J. Roselle
Geosci. Model Dev., 12, 3071–3083, https://doi.org/10.5194/gmd-12-3071-2019, https://doi.org/10.5194/gmd-12-3071-2019, 2019
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Lightning strikes produce significant amount of nitrogen oxides and the resulting atmospheric chemistry causes one of the primary air pollutants, ground-level ozone, to change. In this paper, we documented the evolution of scientific updates for lightning-induced nitrogen oxides schemes in the CMAQ model. The updated observation-based schemes are good for retrospective applications, while the parameterized scheme can estimate lightning nitrogen oxides for applications without observations.
María Teresa Pay, Gotzon Gangoiti, Marc Guevara, Sergey Napelenok, Xavier Querol, Oriol Jorba, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 19, 5467–5494, https://doi.org/10.5194/acp-19-5467-2019, https://doi.org/10.5194/acp-19-5467-2019, 2019
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The poor diagnostic of the O3 issue over southwestern Europe prevents authorities from implementing effective mitigation plans. This work is a pioneer in identifying that imported O3 is the largest input to the ground-level O3 concentration in the Iberian Peninsula, which is largely explained by vertical mixing. This study also proves that anthropogenic emissions control the severe O3 peaks during stagnant conditions. Ad hoc local actions should complement national/European strategies.
Quazi Z. Rasool, Jesse O. Bash, and Daniel S. Cohan
Geosci. Model Dev., 12, 849–878, https://doi.org/10.5194/gmd-12-849-2019, https://doi.org/10.5194/gmd-12-849-2019, 2019
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Soils have been overlooked as a source of reactive nitrogen (N) emissions that are pronounced in the summer ozone season (growing season) and increasingly important as fertilizer use grows, while fossil fuel combustion sources of N decline. Mechanistic process models of soil N emissions are used in Earth science and soil biogeochemical modeling on a site scale. This work mechanistically models soil N emissions for the first time on a regional scale to better understand their air quality impacts.
Gabriele Curci, Ummugulsum Alyuz, Rocio Barò, Roberto Bianconi, Johannes Bieser, Jesper H. Christensen, Augustin Colette, Aidan Farrow, Xavier Francis, Pedro Jiménez-Guerrero, Ulas Im, Peng Liu, Astrid Manders, Laura Palacios-Peña, Marje Prank, Luca Pozzoli, Ranjeet Sokhi, Efisio Solazzo, Paolo Tuccella, Alper Unal, Marta G. Vivanco, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 19, 181–204, https://doi.org/10.5194/acp-19-181-2019, https://doi.org/10.5194/acp-19-181-2019, 2019
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Atmospheric carbonaceous aerosols are able to absorb solar radiation and they continue to contribute some of the largest uncertainties in projected climate change. One important detail is how the chemical species are arranged inside each particle, i.e. the knowledge of their mixing state. We use an ensemble of regional model simulations to test different mixing state assumptions and found that a combination of internal and external mixing may better reproduce sunphotometer observations.
Peng Liu, Christian Hogrefe, Ulas Im, Jesper H. Christensen, Johannes Bieser, Uarporn Nopmongcol, Greg Yarwood, Rohit Mathur, Shawn Roselle, and Tanya Spero
Atmos. Chem. Phys., 18, 17157–17175, https://doi.org/10.5194/acp-18-17157-2018, https://doi.org/10.5194/acp-18-17157-2018, 2018
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This study represents an intercomparison of four regional-scale air quality simulations in order to understand the model similarities and differences in estimating the impact of ozone imported from outside of the US on the surface ozone within the US at process level. Vertical turbulent mixing stands out as a primary contributor to the model differences in inert tracers.
Christopher G. Nolte, Tanya L. Spero, Jared H. Bowden, Megan S. Mallard, and Patrick D. Dolwick
Atmos. Chem. Phys., 18, 15471–15489, https://doi.org/10.5194/acp-18-15471-2018, https://doi.org/10.5194/acp-18-15471-2018, 2018
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Changes in air pollution in the United States are simulated under three near-future climate scenarios. Widespread increases in average ozone levels are projected, with the largest increases during summer under the highest warming scenario. Increases are driven by higher temperatures and emissions from vegetation and are magnified at the upper end of the ozone distribution. The increases in ozone have potentially important implications for efforts to protect human health.
Yuqiang Zhang, J. Jason West, Rohit Mathur, Jia Xing, Christian Hogrefe, Shawn J. Roselle, Jesse O. Bash, Jonathan E. Pleim, Chuen-Meei Gan, and David C. Wong
Atmos. Chem. Phys., 18, 15003–15016, https://doi.org/10.5194/acp-18-15003-2018, https://doi.org/10.5194/acp-18-15003-2018, 2018
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Here we use a fine-resolution (36 km) self-consistent 21-year air quality simulation from 1990 to 2010, a health impact function, and annual county-level population and baseline mortality rate estimates to estimate annual mortality burdens from PM2.5 and O3 in the US, and also the contributions to the trends. We found that the PM2.5-related mortality burden has steadily decreased by 53 %, while the O3-related mortality burden has increased by 13 %, with larger inter-annual variabilities.
Marina Astitha, Ioannis Kioutsioukis, Ghezae Araya Fisseha, Roberto Bianconi, Johannes Bieser, Jesper H. Christensen, Owen R. Cooper, Stefano Galmarini, Christian Hogrefe, Ulas Im, Bryan Johnson, Peng Liu, Uarporn Nopmongcol, Irina Petropavlovskikh, Efisio Solazzo, David W. Tarasick, and Greg Yarwood
Atmos. Chem. Phys., 18, 13925–13945, https://doi.org/10.5194/acp-18-13925-2018, https://doi.org/10.5194/acp-18-13925-2018, 2018
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This work is unique in the detailed analyses of modeled ozone vertical profiles from sites in North America through the collaboration of four research groups from the US and EU. We assess the air quality models' performance and model inter-comparison for ozone vertical profiles and stratospheric ozone intrusions. Lastly, we designate the important role of lateral boundary conditions in the ozone vertical profiles using chemically inert tracers.
Mariel D. Friberg, Ralph A. Kahn, James A. Limbacher, K. Wyat Appel, and James A. Mulholland
Atmos. Chem. Phys., 18, 12891–12913, https://doi.org/10.5194/acp-18-12891-2018, https://doi.org/10.5194/acp-18-12891-2018, 2018
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Advances in satellite retrieval of aerosol type can improve ambient air quality concentration estimates by providing regional context where surface monitors are scarce or absent. This work focuses on the degree to which regional-scale satellite and model data can be combined to improve surface estimates of fine particles and their major speciated components. The physically based method applies satellite-derived column observations directly to total and speciated surface particle concentrations.
Lu Xu, Havala O. T. Pye, Jia He, Yunle Chen, Benjamin N. Murphy, and Nga Lee Ng
Atmos. Chem. Phys., 18, 12613–12637, https://doi.org/10.5194/acp-18-12613-2018, https://doi.org/10.5194/acp-18-12613-2018, 2018
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In this study, we integrate lab-in-the-field experiments, extensive ambient ground measurements, and state-of-the-art modeling to constrain the concentration of organic aerosol from biogenic monoterpenes and sesquiterpenes. Further, we show that the organic aerosol from the investigated sources accounts for roughly 20 % of the World Health Organization PM2.5 standard in the southeastern US.
Marta G. Vivanco, Mark R. Theobald, Héctor García-Gómez, Juan Luis Garrido, Marje Prank, Wenche Aas, Mario Adani, Ummugulsum Alyuz, Camilla Andersson, Roberto Bellasio, Bertrand Bessagnet, Roberto Bianconi, Johannes Bieser, Jørgen Brandt, Gino Briganti, Andrea Cappelletti, Gabriele Curci, Jesper H. Christensen, Augustin Colette, Florian Couvidat, Cornelis Cuvelier, Massimo D'Isidoro, Johannes Flemming, Andrea Fraser, Camilla Geels, Kaj M. Hansen, Christian Hogrefe, Ulas Im, Oriol Jorba, Nutthida Kitwiroon, Astrid Manders, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Luca Pozzoli, Efisio Solazzo, Svetlana Tsyro, Alper Unal, Peter Wind, and Stefano Galmarini
Atmos. Chem. Phys., 18, 10199–10218, https://doi.org/10.5194/acp-18-10199-2018, https://doi.org/10.5194/acp-18-10199-2018, 2018
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European wet and dry atmospheric deposition of N and S estimated by 14 air quality models was found to vary substantially. An ensemble of models meeting acceptability criteria was used to estimate the exceedances of the critical loads for N in habitats within the Natura 2000 network, as well as their lower and upper limits. Scenarios with 20 % emission reductions in different regions of the world showed that European emissions are responsible for most of the N and S deposition in Europe.
Orren Russell Bullock Jr., Hosein Foroutan, Robert C. Gilliam, and Jerold A. Herwehe
Geosci. Model Dev., 11, 2897–2922, https://doi.org/10.5194/gmd-11-2897-2018, https://doi.org/10.5194/gmd-11-2897-2018, 2018
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The U.S. Environmental Protection Agency is developing a new modeling system to investigate air pollution pathways on a global scale. We plan to use the Model for Prediction Across Scales – Atmosphere (MPAS-A) to define the meteorology that affects air pollution transport and fate. In order to do so, MPAS-A must accurately reproduce historical weather conditions. This work demonstrates that our implementation of four-dimensional data assimilation by analysis nudging provides that capability.
Ulas Im, Jesper Heile Christensen, Camilla Geels, Kaj Mantzius Hansen, Jørgen Brandt, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Peng Liu, Uarporn Nopmongcol, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta G. Vivanco, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 8929–8952, https://doi.org/10.5194/acp-18-8929-2018, https://doi.org/10.5194/acp-18-8929-2018, 2018
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We evaluate the impact of global and regional anthropogenic emission reductions on major air pollutant levels over Europe and North America, using a multi-model ensemble of regional chemistry and transport models. Results show that ozone levels are largely driven by long-range transport over both continents while other pollutants such as carbon monoxide or aerosols are mainly controlled by domestic sources. Use of multi-model ensembles can help to reduce the uncertainties in individual models.
Yuqiang Zhang, Rohit Mathur, Jesse O. Bash, Christian Hogrefe, Jia Xing, and Shawn J. Roselle
Atmos. Chem. Phys., 18, 9091–9106, https://doi.org/10.5194/acp-18-9091-2018, https://doi.org/10.5194/acp-18-9091-2018, 2018
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For this study, we evaluated the WRF–CMAQ coupled model's ability to simulate the long-term trends of wet deposition of nitrogen and sulfur from 1990 to 2010 by comparing the model results with long-term observation datasets in the US. The model generally underestimates the wet deposition of both nitrogen and sulfur but captured well the decreasing trends for the deposition. Then we estimated the deposition budget in the US, including wet deposition and dry deposition from model simulations.
Stefano Galmarini, Ioannis Kioutsioukis, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Roberto Bellasio, Anna M. K. Benedictow, Roberto Bianconi, Johannes Bieser, Joergen Brandt, Jesper H. Christensen, Augustin Colette, Gabriele Curci, Yanko Davila, Xinyi Dong, Johannes Flemming, Xavier Francis, Andrea Fraser, Joshua Fu, Daven K. Henze, Christian Hogrefe, Ulas Im, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Jan Eiof Jonson, Nutthida Kitwiroon, Astrid Manders, Rohit Mathur, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marie Prank, Martin Schultz, Rajeet S. Sokhi, Kengo Sudo, Paolo Tuccella, Toshihiko Takemura, Takashi Sekiya, and Alper Unal
Atmos. Chem. Phys., 18, 8727–8744, https://doi.org/10.5194/acp-18-8727-2018, https://doi.org/10.5194/acp-18-8727-2018, 2018
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An ensemble of model results relating to ozone concentrations in Europe in 2010 has been produced and studied. The novelty consists in the fact that the ensemble is made of results of models working at two different scales (regional and global), therefore contributing in detail two different parts of the atmospheric spectrum. The ensemble defined as a hybrid has been studied in detail and shown to bring additional value to the assessment of air quality.
Xi Chen, Mingjie Xie, Michael D. Hays, Eric Edgerton, Donna Schwede, and John T. Walker
Atmos. Chem. Phys., 18, 6829–6846, https://doi.org/10.5194/acp-18-6829-2018, https://doi.org/10.5194/acp-18-6829-2018, 2018
Ulas Im, Jørgen Brandt, Camilla Geels, Kaj Mantzius Hansen, Jesper Heile Christensen, Mikael Skou Andersen, Efisio Solazzo, Ioannis Kioutsioukis, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Ciao-Kai Liang, Uarporn Nopmongcol, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta Garcia Vivanco, Jason West, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 5967–5989, https://doi.org/10.5194/acp-18-5967-2018, https://doi.org/10.5194/acp-18-5967-2018, 2018
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The impacts of air pollution on human health and their costs in Europe and the United States for the year 2010 ared modeled by a multi-model ensemble. In Europe, the number of premature deaths is calculated to be 414 000, while in the US it is estimated to be 160 000. Health impacts estimated by individual models can vary up to a factor of 3. Results show that the domestic emissions have the largest impact on premature deaths, compared to foreign sources.
Christian Hogrefe, Peng Liu, George Pouliot, Rohit Mathur, Shawn Roselle, Johannes Flemming, Meiyun Lin, and Rokjin J. Park
Atmos. Chem. Phys., 18, 3839–3864, https://doi.org/10.5194/acp-18-3839-2018, https://doi.org/10.5194/acp-18-3839-2018, 2018
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This study quantifies the impacts of different representations of background ozone in state-of-the-science large-scale models on surface and aloft ozone burdens simulated by the CMAQ regional model over the United States. It also compares both the CMAQ simulations and the driving large-scale models to surface and upper air observations.
Jingqiu Mao, Annmarie Carlton, Ronald C. Cohen, William H. Brune, Steven S. Brown, Glenn M. Wolfe, Jose L. Jimenez, Havala O. T. Pye, Nga Lee Ng, Lu Xu, V. Faye McNeill, Kostas Tsigaridis, Brian C. McDonald, Carsten Warneke, Alex Guenther, Matthew J. Alvarado, Joost de Gouw, Loretta J. Mickley, Eric M. Leibensperger, Rohit Mathur, Christopher G. Nolte, Robert W. Portmann, Nadine Unger, Mika Tosca, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 2615–2651, https://doi.org/10.5194/acp-18-2615-2018, https://doi.org/10.5194/acp-18-2615-2018, 2018
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This paper is aimed at discussing progress in evaluating, diagnosing, and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models.
Havala O. T. Pye, Andreas Zuend, Juliane L. Fry, Gabriel Isaacman-VanWertz, Shannon L. Capps, K. Wyat Appel, Hosein Foroutan, Lu Xu, Nga L. Ng, and Allen H. Goldstein
Atmos. Chem. Phys., 18, 357–370, https://doi.org/10.5194/acp-18-357-2018, https://doi.org/10.5194/acp-18-357-2018, 2018
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Thermodynamic modeling revealed that some but not all measurements of ammonium-to-sulfate ratios are consistent with theory. The measurement diversity likely explains the previously reported range of results regarding the suitability of thermodynamic modeling. Despite particles being predominantly phase separated, organic–inorganic interactions resulted in increased aerosol pH and partitioning towards the particle phase for highly oxygenated organic compounds compared to traditional methods.
Rohit Mathur, Jia Xing, Robert Gilliam, Golam Sarwar, Christian Hogrefe, Jonathan Pleim, George Pouliot, Shawn Roselle, Tanya L. Spero, David C. Wong, and Jeffrey Young
Atmos. Chem. Phys., 17, 12449–12474, https://doi.org/10.5194/acp-17-12449-2017, https://doi.org/10.5194/acp-17-12449-2017, 2017
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We extend CMAQ's applicability to the entire Northern Hemisphere to enable consistent examination of interactions between atmospheric processes occurring on various spatial and temporal scales. Improvements were made in model process representation, structure, and input data sets that enable a range of model applications including episodic intercontinental pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution–climate interactions.
Benjamin N. Murphy, Matthew C. Woody, Jose L. Jimenez, Ann Marie G. Carlton, Patrick L. Hayes, Shang Liu, Nga L. Ng, Lynn M. Russell, Ari Setyan, Lu Xu, Jeff Young, Rahul A. Zaveri, Qi Zhang, and Havala O. T. Pye
Atmos. Chem. Phys., 17, 11107–11133, https://doi.org/10.5194/acp-17-11107-2017, https://doi.org/10.5194/acp-17-11107-2017, 2017
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We incorporate recent findings about the behavior of organic pollutants in urban airsheds into the Community Multiscale Air Quality (CMAQ) model to refine predictions of organic particulate pollution in the United States. The new techniques, which account for the volatility and ongoing chemistry of airborne organic compounds, substantially reduce biases, particularly in the winter time and near emission sources.
Efisio Solazzo, Christian Hogrefe, Augustin Colette, Marta Garcia-Vivanco, and Stefano Galmarini
Atmos. Chem. Phys., 17, 10435–10465, https://doi.org/10.5194/acp-17-10435-2017, https://doi.org/10.5194/acp-17-10435-2017, 2017
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The work here is conducted within the frame of AQMEII3 and promotes the use of diagnostic methods for the evaluation of air quality models. We highlight the need to move away from aggregated error metrics and to focus on the quality of the information that can be extracted from the model and the observation. This aids the understanding of the causes of model error, providing more useful information to model developers and users than can be gained from common evaluations.
Jia Xing, Jiandong Wang, Rohit Mathur, Shuxiao Wang, Golam Sarwar, Jonathan Pleim, Christian Hogrefe, Yuqiang Zhang, Jingkun Jiang, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 17, 9869–9883, https://doi.org/10.5194/acp-17-9869-2017, https://doi.org/10.5194/acp-17-9869-2017, 2017
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The assessment of the impacts of aerosol direct effects (ADE) is important for understanding emission reduction strategies that seek co-benefits associated with reductions in both particulate matter and ozone. This study quantifies the ADE impacts on tropospheric ozone by using a two-way coupled meteorology and atmospheric chemistry model. Results suggest that reducing ADE may have the potential risk of increasing ozone in winter, but it will benefit the reduction of maxima ozone in summer.
Kathleen M. Fahey, Annmarie G. Carlton, Havala O. T. Pye, Jaemeen Baek, William T. Hutzell, Charles O. Stanier, Kirk R. Baker, K. Wyat Appel, Mohammed Jaoui, and John H. Offenberg
Geosci. Model Dev., 10, 1587–1605, https://doi.org/10.5194/gmd-10-1587-2017, https://doi.org/10.5194/gmd-10-1587-2017, 2017
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Chemical transport models (CTMs) are a crucial tool in understanding links between emissions, air quality, and climate. Only a simple description of cloud chemistry has been implemented in many of these; however, clouds play a major role in the physicochemical processing of atmospheric species. In CMAQ, EPA’s widely used CTM, the cloud code is limited to the treatment of simple chemistry. We update CMAQ clouds to consider additional chemistry and then examine regional impacts of these updates.
Shantanu H. Jathar, Matthew Woody, Havala O. T. Pye, Kirk R. Baker, and Allen L. Robinson
Atmos. Chem. Phys., 17, 4305–4318, https://doi.org/10.5194/acp-17-4305-2017, https://doi.org/10.5194/acp-17-4305-2017, 2017
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Mobile sources such as cars and trucks are large sources of pollution in cities, but it is unclear what their relative contribution to organic particle pollution is. We used a numerical model along with recent data gathered from tests performed on cars and trucks to calculate organic particle levels in southern California. We found that model calculations agreed better with measurements and gasoline cars and trucks dominated the organic particle pollution.
Efisio Solazzo, Roberto Bianconi, Christian Hogrefe, Gabriele Curci, Paolo Tuccella, Ummugulsum Alyuz, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Johannes Bieser, Jørgen Brandt, Jesper H. Christensen, Augistin Colette, Xavier Francis, Andrea Fraser, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Ulas Im, Astrid Manders, Uarporn Nopmongcol, Nutthida Kitwiroon, Guido Pirovano, Luca Pozzoli, Marje Prank, Ranjeet S. Sokhi, Alper Unal, Greg Yarwood, and Stefano Galmarini
Atmos. Chem. Phys., 17, 3001–3054, https://doi.org/10.5194/acp-17-3001-2017, https://doi.org/10.5194/acp-17-3001-2017, 2017
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As part of the third phase of AQMEII, this study uses timescale analysis to apportion error to the responsible processes, detect causes of model error, and identify the processes and scales that require dedicated investigations. The analysis tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of model biases for ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature over Europe and North America.
Nga Lee Ng, Steven S. Brown, Alexander T. Archibald, Elliot Atlas, Ronald C. Cohen, John N. Crowley, Douglas A. Day, Neil M. Donahue, Juliane L. Fry, Hendrik Fuchs, Robert J. Griffin, Marcelo I. Guzman, Hartmut Herrmann, Alma Hodzic, Yoshiteru Iinuma, José L. Jimenez, Astrid Kiendler-Scharr, Ben H. Lee, Deborah J. Luecken, Jingqiu Mao, Robert McLaren, Anke Mutzel, Hans D. Osthoff, Bin Ouyang, Benedicte Picquet-Varrault, Ulrich Platt, Havala O. T. Pye, Yinon Rudich, Rebecca H. Schwantes, Manabu Shiraiwa, Jochen Stutz, Joel A. Thornton, Andreas Tilgner, Brent J. Williams, and Rahul A. Zaveri
Atmos. Chem. Phys., 17, 2103–2162, https://doi.org/10.5194/acp-17-2103-2017, https://doi.org/10.5194/acp-17-2103-2017, 2017
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Oxidation of biogenic volatile organic compounds by NO3 is an important interaction between anthropogenic
and natural emissions. This review results from a June 2015 workshop and includes the recent literature
on kinetics, mechanisms, organic aerosol yields, and heterogeneous chemistry; advances in analytical
instrumentation; the current state NO3-BVOC chemistry in atmospheric models; and critical needs for
future research in modeling, field observations, and laboratory studies.
Stefano Galmarini, Brigitte Koffi, Efisio Solazzo, Terry Keating, Christian Hogrefe, Michael Schulz, Anna Benedictow, Jan Jurgen Griesfeller, Greet Janssens-Maenhout, Greg Carmichael, Joshua Fu, and Frank Dentener
Atmos. Chem. Phys., 17, 1543–1555, https://doi.org/10.5194/acp-17-1543-2017, https://doi.org/10.5194/acp-17-1543-2017, 2017
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We present an overview of the coordinated global numerical modelling experiments performed during 2012–2016 by the Task Force on Hemispheric Transport of Air Pollution (TF HTAP), the regional experiments by the Air Quality Model Evaluation International Initiative (AQMEII) over Europe and North America, and the Model Intercomparison Study for Asia (MICS-Asia). Given the organizational complexity of bringing together these three initiatives, the experiment organization is presented.
Havala O. T. Pye, Benjamin N. Murphy, Lu Xu, Nga L. Ng, Annmarie G. Carlton, Hongyu Guo, Rodney Weber, Petros Vasilakos, K. Wyat Appel, Sri Hapsari Budisulistiorini, Jason D. Surratt, Athanasios Nenes, Weiwei Hu, Jose L. Jimenez, Gabriel Isaacman-VanWertz, Pawel K. Misztal, and Allen H. Goldstein
Atmos. Chem. Phys., 17, 343–369, https://doi.org/10.5194/acp-17-343-2017, https://doi.org/10.5194/acp-17-343-2017, 2017
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We use a chemical transport model to examine how organic compounds in the atmosphere interact with water present in particles. Organic compounds themselves lead to water uptake, and organic compounds interact with water associated with inorganic compounds in the rural southeast atmosphere. Including interactions of organic compounds with water requires a treatment of nonideality to more accurately represent aerosol observations during the Southern Oxidant and Aerosol Study (SOAS) 2013.
Ioannis Kioutsioukis, Ulas Im, Efisio Solazzo, Roberto Bianconi, Alba Badia, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Dominik Brunner, Charles Chemel, Gabriele Curci, Hugo Denier van der Gon, Johannes Flemming, Renate Forkel, Lea Giordano, Pedro Jiménez-Guerrero, Marcus Hirtl, Oriol Jorba, Astrid Manders-Groot, Lucy Neal, Juan L. Pérez, Guidio Pirovano, Roberto San Jose, Nicholas Savage, Wolfram Schroder, Ranjeet S. Sokhi, Dimiter Syrakov, Paolo Tuccella, Johannes Werhahn, Ralf Wolke, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 16, 15629–15652, https://doi.org/10.5194/acp-16-15629-2016, https://doi.org/10.5194/acp-16-15629-2016, 2016
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Four ensemble methods are applied to two annual AQMEII datasets and their performance is compared for O3, NO2 and PM10. The goal of the study is to quantify to what extent we can extract predictable signals from an ensemble with superior skill at each station over the single models and the ensemble mean. The promotion of the right amount of accuracy and diversity within the ensemble results in an average additional skill of up to 31 % compared to using the full ensemble in an unconditional way.
Quazi Z. Rasool, Rui Zhang, Benjamin Lash, Daniel S. Cohan, Ellen J. Cooter, Jesse O. Bash, and Lok N. Lamsal
Geosci. Model Dev., 9, 3177–3197, https://doi.org/10.5194/gmd-9-3177-2016, https://doi.org/10.5194/gmd-9-3177-2016, 2016
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This study updates the representation of soil NO emissions in a regional air quality model. The implementation enhances the representation of biome types and dynamic fertilizer use. Previous modeling of soil NO in CMAQ had tended to under-estimate emissions and misrepresent their response to soil conditions and meteorology. We evaluate results against satellite observations of NO2, and quantify the impacts of the new parameterization on simulations of ozone and particulate matter.
Jia Xing, Rohit Mathur, Jonathan Pleim, Christian Hogrefe, Jiandong Wang, Chuen-Meei Gan, Golam Sarwar, David C. Wong, and Stuart McKeen
Atmos. Chem. Phys., 16, 10865–10877, https://doi.org/10.5194/acp-16-10865-2016, https://doi.org/10.5194/acp-16-10865-2016, 2016
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Downward transport of ozone from the stratosphere has large impacts on surface concentration and needs to be properly represented in regional models. This study developed a seasonally and spatially varying PV-based function from an investigation of the relationship between PV and O3. The implementation of the new function significantly improves the model's performance in O3 simulation, which enables a more accurate simulation of the vertical distribution of O3 across the Northern Hemisphere.
Jesse O. Bash, Kirk R. Baker, and Melinda R. Beaver
Geosci. Model Dev., 9, 2191–2207, https://doi.org/10.5194/gmd-9-2191-2016, https://doi.org/10.5194/gmd-9-2191-2016, 2016
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Biogenic volatile organic compounds (BVOCs) participate in reactions that can lead to secondarily formed ozone and particulate matter impacting air quality and climate and are important inputs for atmospheric models. BVOC emissions are sensitive to the vegetation species and leaf temperature. Here, we have improved the vegetation data and modeled leaf temperature of the Biogenic Emission Inventory System model. Updated algorithms improved model evaluation against observations in California.
Matthew C. Woody, Kirk R. Baker, Patrick L. Hayes, Jose L. Jimenez, Bonyoung Koo, and Havala O. T. Pye
Atmos. Chem. Phys., 16, 4081–4100, https://doi.org/10.5194/acp-16-4081-2016, https://doi.org/10.5194/acp-16-4081-2016, 2016
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In this work, organic aerosol (OA) predictions from the volatility basis set (VBS) module in the CMAQ photochemical transport model were evaluated against routine monitoring data and measurements collected during the 2010 CalNex field study. We found that the VBS module more accurately reproduced the observed primary/secondary OA split and secondary OA (SOA) mass at the CalNex Pasadena ground site compared to the traditional CMAQ OA module but still underpredicted observed SOA by ~ 5.2 ×.
E. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618, https://doi.org/10.5194/acp-16-1603-2016, https://doi.org/10.5194/acp-16-1603-2016, 2016
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Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
M. W. Shephard, C. A. McLinden, K. E. Cady-Pereira, M. Luo, S. G. Moussa, A. Leithead, J. Liggio, R. M. Staebler, A. Akingunola, P. Makar, P. Lehr, J. Zhang, D. K. Henze, D. B. Millet, J. O. Bash, L. Zhu, K. C. Wells, S. L. Capps, S. Chaliyakunnel, M. Gordon, K. Hayden, J. R. Brook, M. Wolde, and S.-M. Li
Atmos. Meas. Tech., 8, 5189–5211, https://doi.org/10.5194/amt-8-5189-2015, https://doi.org/10.5194/amt-8-5189-2015, 2015
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This study provides direct validations of Tropospheric Emission Spectrometer (TES) satellite retrieved profiles against coincident aircraft profiles of carbon monoxide, ammonia, methanol, and formic acid, all of which are of interest for air quality. The comparisons are performed over the Canadian oil sands region during an intensive field campaign in support of the Joint Canada-Alberta Implementation Plan for the Oil Sands Monitoring (JOSM). Initial model evaluations are also provided.
L. Zhu, D. Henze, J. Bash, G.-R. Jeong, K. Cady-Pereira, M. Shephard, M. Luo, F. Paulot, and S. Capps
Atmos. Chem. Phys., 15, 12823–12843, https://doi.org/10.5194/acp-15-12823-2015, https://doi.org/10.5194/acp-15-12823-2015, 2015
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We implement new diurnal variation scheme for ammonia livestock emissions and bidirectional exchange scheme and its adjoint in the GEOS-Chem global chemical transport model. Updated diurnal variability improves modeled-to-hourly in situ measurements comparison. The ammonium soil pool in the bidirectional exchange model largely extends the ammonia lifetime in the atmosphere. Large model biases remain as livestock emissions are still underestimated.
B. Gantt, J. T. Kelly, and J. O. Bash
Geosci. Model Dev., 8, 3733–3746, https://doi.org/10.5194/gmd-8-3733-2015, https://doi.org/10.5194/gmd-8-3733-2015, 2015
C.-M. Gan, J. Pleim, R. Mathur, C. Hogrefe, C. N. Long, J. Xing, D. Wong, R. Gilliam, and C. Wei
Atmos. Chem. Phys., 15, 12193–12209, https://doi.org/10.5194/acp-15-12193-2015, https://doi.org/10.5194/acp-15-12193-2015, 2015
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This study attempts to determine the consequences of the changes in tropospheric aerosol burden arising from substantial reductions in emissions of SO2 and NOx associated with control measures under the Clean Air Act especially on trends in solar radiation. Comparisons of model results with observations of aerosol optical depth, aerosol concentration, and radiation demonstrate that the coupled WRF-CMAQ model is capable of replicating the trends well even though it tends to underestimate the AOD.
G. Janssens-Maenhout, M. Crippa, D. Guizzardi, F. Dentener, M. Muntean, G. Pouliot, T. Keating, Q. Zhang, J. Kurokawa, R. Wankmüller, H. Denier van der Gon, J. J. P. Kuenen, Z. Klimont, G. Frost, S. Darras, B. Koffi, and M. Li
Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, https://doi.org/10.5194/acp-15-11411-2015, 2015
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This paper provides monthly emission grid maps at 0.1deg x 0.1deg resolution with global coverage for air pollutants and aerosols anthropogenic emissions in 2008 and 2010.
Countries are consistently inter-compared with sector-specific implied emission factors, per capita emissions and emissions per unit of GDP.
The emission grid maps compose the reference emissions data set for the community modelling hemispheric transport of air pollution (HTAP).
Y. Zhou, H. Mao, K. Demerjian, C. Hogrefe, and J. Liu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-27253-2015, https://doi.org/10.5194/acpd-15-27253-2015, 2015
Revised manuscript not accepted
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Baseline carbon monoxide (CO) and ozone (O3) were studied at seven rural sites in the Northeast U.S. during varying periods over 2001 – 2010. Baseline CO at all sites decreased significantly at a rate between -4.3 – -2.3 ppbv yr-1, while baseline O3 was relatively constant. Interannual and seasonal variations of baseline CO and O3 were related to increasing Asian emissions, NOx emissions reduction in urban areas, global biomass burning emissions, and meteorological conditions.
C. G. Nolte, K. W. Appel, J. T. Kelly, P. V. Bhave, K. M. Fahey, J. L. Collett Jr., L. Zhang, and J. O. Young
Geosci. Model Dev., 8, 2877–2892, https://doi.org/10.5194/gmd-8-2877-2015, https://doi.org/10.5194/gmd-8-2877-2015, 2015
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This study is the most comprehensive evaluation of CMAQ inorganic
aerosol size-composition distributions conducted to date. We compare two
methods of inferring PM2.5 concentrations from the model: (1) based on
the sum of the masses in the fine aerosol modes, as is most commonly
done in CMAQ model evaluation; and (2) computed using the simulated size
distributions. Differences are generally less than 1 microgram/m3, and
are largest over the eastern USA during the summer.
J. Xing, R. Mathur, J. Pleim, C. Hogrefe, C.-M. Gan, D. C. Wong, and C. Wei
Atmos. Chem. Phys., 15, 9997–10018, https://doi.org/10.5194/acp-15-9997-2015, https://doi.org/10.5194/acp-15-9997-2015, 2015
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The ability of a coupled meteorology-chemistry model (WRF-CMAQ) to reproduce the historical trend in AOD and clear-sky SWR over the N. Hemisphere has been evaluated through a comparison of 21-year simulated results with observation-derived records from 1990 to 2010. Questions of how well the model represents the regional and temporal variability of aerosol burden and DRE, and whether the model is able to capture past trends in aerosol loading and associated radiation effects, will be addressed.
S. H. Budisulistiorini, X. Li, S. T. Bairai, J. Renfro, Y. Liu, Y. J. Liu, K. A. McKinney, S. T. Martin, V. F. McNeill, H. O. T. Pye, A. Nenes, M. E. Neff, E. A. Stone, S. Mueller, C. Knote, S. L. Shaw, Z. Zhang, A. Gold, and J. D. Surratt
Atmos. Chem. Phys., 15, 8871–8888, https://doi.org/10.5194/acp-15-8871-2015, https://doi.org/10.5194/acp-15-8871-2015, 2015
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Isoprene epoxydiols (IEPOX) are major gas-phase products from the atmospheric oxidation of isoprene that yield secondary organic aerosol (SOA) by reactive uptake onto acidic sulfate aerosol. We report a substantial contribution of IEPOX-derived SOA to the total fine aerosol collected during summer. IEPOX-derived SOA measured by online and offline mass spectrometry techniques is correlated with acidic sulfate aerosol, demonstrating the critical role of anthropogenic emissions in its formation.
X. Fu, S. X. Wang, L. M. Ran, J. E. Pleim, E. Cooter, J. O. Bash, V. Benson, and J. M. Hao
Atmos. Chem. Phys., 15, 6637–6649, https://doi.org/10.5194/acp-15-6637-2015, https://doi.org/10.5194/acp-15-6637-2015, 2015
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In this study, we estimate, for the first time, the NH3 emission from the agricultural fertilizer application in China online using the bi-directional CMAQ model coupled to an agro-ecosystem model. Compared with previous researches, this method considers more influencing factors, such as meteorological fields, soil and the fertilizer application, and provides improved NH3 emission with higher spatial and temporal resolution.
K. R. Baker, A. G. Carlton, T. E. Kleindienst, J. H. Offenberg, M. R. Beaver, D. R. Gentner, A. H. Goldstein, P. L. Hayes, J. L. Jimenez, J. B. Gilman, J. A. de Gouw, M. C. Woody, H. O. T. Pye, J. T. Kelly, M. Lewandowski, M. Jaoui, P. S. Stevens, W. H. Brune, Y.-H. Lin, C. L. Rubitschun, and J. D. Surratt
Atmos. Chem. Phys., 15, 5243–5258, https://doi.org/10.5194/acp-15-5243-2015, https://doi.org/10.5194/acp-15-5243-2015, 2015
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This work details the evaluation of PM2.5 carbon, VOC precursors, and OH estimated by the CMAQ photochemical transport model using routine and special measurements from the 2010 CalNex field study. Here, CMAQ and most recent emissions inventory (2011 NEI) are used to generate model PM2.5 OC estimates that are examined in novel ways including primary vs. secondary formation, fossil vs. contemporary carbon, OH and HO2 evaluation, and the relationship between key VOC precursors and SOC tracers.
M. S. Mallard, C. G. Nolte, T. L. Spero, O. R. Bullock, K. Alapaty, J. A. Herwehe, J. Gula, and J. H. Bowden
Geosci. Model Dev., 8, 1085–1096, https://doi.org/10.5194/gmd-8-1085-2015, https://doi.org/10.5194/gmd-8-1085-2015, 2015
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Because global climate models (GCMs) are typically run at coarse spatial resolution, lakes are often poorly resolved in their global fields. When downscaling such GCMs using the Weather Research & Forecasting (WRF) model, use of WRF’s default interpolation methods can result in unrealistic lake temperatures and ice cover, which can impact simulated air temperatures and precipitation. Here, alternative methods for setting lake variables in WRF downscaling applications are presented and compared.
D. C. Wong, C. E. Yang, J. S. Fu, K. Wong, and Y. Gao
Geosci. Model Dev., 8, 1033–1046, https://doi.org/10.5194/gmd-8-1033-2015, https://doi.org/10.5194/gmd-8-1033-2015, 2015
B. Gantt, M. S. Johnson, M. Crippa, A. S. H. Prévôt, and N. Meskhidze
Geosci. Model Dev., 8, 619–629, https://doi.org/10.5194/gmd-8-619-2015, https://doi.org/10.5194/gmd-8-619-2015, 2015
J. Xing, R. Mathur, J. Pleim, C. Hogrefe, C.-M. Gan, D. C. Wong, C. Wei, R. Gilliam, and G. Pouliot
Atmos. Chem. Phys., 15, 2723–2747, https://doi.org/10.5194/acp-15-2723-2015, https://doi.org/10.5194/acp-15-2723-2015, 2015
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Model-simulated air quality trends over the past 2 decades largely agree with those derived from observations. In the relative amounts of VOC and NOx emission controls in different regions across the northern hemisphere have led to significantly different trends in tropospheric O3. Differences in the historical changes in the relative amounts of NH3, NOx and SO2 emissions also impact the trends in inorganic particulate matter amounts and composition in China, the U.S. and Europe.
R. H. F. Kwok, K. R. Baker, S. L. Napelenok, and G. S. Tonnesen
Geosci. Model Dev., 8, 99–114, https://doi.org/10.5194/gmd-8-99-2015, https://doi.org/10.5194/gmd-8-99-2015, 2015
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The implementation and application of the Integrated Source Apportionment Method (ISAM) for O3 and its precursors for the Community Multiscale Air Quality (CMAQ) model are described. CMAQ-ISAM is a hybrid of source apportionment and source sensitivity in that O3 production is attributed to precursor sources based on the O3 formation regime. CMAQ-ISAM offers a source attribution tool for the purposes of quantifying and understanding sources and impacts of regional air pollution.
S. Yu, R. Mathur, J. Pleim, D. Wong, R. Gilliam, K. Alapaty, C. Zhao, and X. Liu
Atmos. Chem. Phys., 14, 11247–11285, https://doi.org/10.5194/acp-14-11247-2014, https://doi.org/10.5194/acp-14-11247-2014, 2014
B. Gantt, J. He, X. Zhang, Y. Zhang, and A. Nenes
Atmos. Chem. Phys., 14, 7485–7497, https://doi.org/10.5194/acp-14-7485-2014, https://doi.org/10.5194/acp-14-7485-2014, 2014
B. H. Henderson, F. Akhtar, H. O. T. Pye, S. L. Napelenok, and W. T. Hutzell
Geosci. Model Dev., 7, 339–360, https://doi.org/10.5194/gmd-7-339-2014, https://doi.org/10.5194/gmd-7-339-2014, 2014
C.-M. Gan, J. Pleim, R. Mathur, C. Hogrefe, C. N. Long, J. Xing, S. Roselle, and C. Wei
Atmos. Chem. Phys., 14, 1701–1715, https://doi.org/10.5194/acp-14-1701-2014, https://doi.org/10.5194/acp-14-1701-2014, 2014
G. Sarwar, J. Godowitch, B. H. Henderson, K. Fahey, G. Pouliot, W. T. Hutzell, R. Mathur, D. Kang, W. S. Goliff, and W. R. Stockwell
Atmos. Chem. Phys., 13, 9695–9712, https://doi.org/10.5194/acp-13-9695-2013, https://doi.org/10.5194/acp-13-9695-2013, 2013
J. Xing, J. Pleim, R. Mathur, G. Pouliot, C. Hogrefe, C.-M. Gan, and C. Wei
Atmos. Chem. Phys., 13, 7531–7549, https://doi.org/10.5194/acp-13-7531-2013, https://doi.org/10.5194/acp-13-7531-2013, 2013
K. W. Appel, G. A. Pouliot, H. Simon, G. Sarwar, H. O. T. Pye, S. L. Napelenok, F. Akhtar, and S. J. Roselle
Geosci. Model Dev., 6, 883–899, https://doi.org/10.5194/gmd-6-883-2013, https://doi.org/10.5194/gmd-6-883-2013, 2013
B. Gantt and N. Meskhidze
Atmos. Chem. Phys., 13, 3979–3996, https://doi.org/10.5194/acp-13-3979-2013, https://doi.org/10.5194/acp-13-3979-2013, 2013
J. O. Bash, E. J. Cooter, R. L. Dennis, J. T. Walker, and J. E. Pleim
Biogeosciences, 10, 1635–1645, https://doi.org/10.5194/bg-10-1635-2013, https://doi.org/10.5194/bg-10-1635-2013, 2013
J. T. Walker, M. R. Jones, J. O. Bash, L. Myles, T. Meyers, D. Schwede, J. Herrick, E. Nemitz, and W. Robarge
Biogeosciences, 10, 981–998, https://doi.org/10.5194/bg-10-981-2013, https://doi.org/10.5194/bg-10-981-2013, 2013
Related subject area
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Use of threshold parameter variation for tropical cyclone tracking
Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes
The High-resolution Intermediate Complexity Atmospheric Research (HICAR v1.1) model enables fast dynamic downscaling to the hectometer scale
A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter
Plume detection and emission estimate for biomass burning plumes from TROPOMI carbon monoxide observations using APE v1.1
CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model
A method to derive Fourier–wavelet spectra for the characterization of global-scale waves in the mesosphere and lower thermosphere and its MATLAB and Python software (fourierwavelet v1.1)
Dynamic Meteorology-induced Emissions Coupler (MetEmis) development in the Community Multiscale Air Quality (CMAQ): CMAQ-MetEmis
Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
Simulating heat and CO2 fluxes in Beijing using SUEWS V2020b: sensitivity to vegetation phenology and maximum conductance
A Python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0
The three-dimensional structure of fronts in mid-latitude weather systems in numerical weather prediction models
The development and validation of the Inhomogeneous Wind Scheme for Urban Street (IWSUS-v1)
GPU-HADVPPM V1.0: a high-efficiency parallel GPU design of the piecewise parabolic method (PPM) for horizontal advection in an air quality model (CAMx V6.10)
Variability and combination as an ensemble of mineral dust forecasts during the 2021 CADDIWA experiment using the WRF 3.7.1 and CHIMERE v2020r3 models
Breakups are complicated: an efficient representation of collisional breakup in the superdroplet method
An optimized semi-empirical physical approach for satellite-based PM2.5 retrieval: embedding machine learning to simulate complex physical parameters
Sensitivity of tropospheric ozone to halogen chemistry in the chemistry–climate model LMDZ-INCA vNMHC
Segmentation of XCO2 images with deep learning: application to synthetic plumes from cities and power plants
Evaluating precipitation distributions at regional scales: a benchmarking framework and application to CMIP5 and 6 models
The Fire Inventory from NCAR version 2.5: an updated global fire emissions model for climate and chemistry applications
An approach to refining the ground meteorological observation stations for improving PM2.5 forecasts in the Beijing–Tianjin–Hebei region
Assessment of WRF (v 4.2.1) dynamically downscaled precipitation on subdaily and daily timescales over CONUS
Convective-gust nowcasting based on radar reflectivity and a deep learning algorithm
Self-nested large-eddy simulations in PALM model system v21.10 for offshore wind prediction under different atmospheric stability conditions
How does cloud-radiative heating over the North Atlantic change with grid spacing, convective parameterization, and microphysics scheme in ICON version 2.1.00?
Simulations of idealised 3D atmospheric flows on terrestrial planets using LFRic-Atmosphere
Updated isoprene and terpene emission factors for the Interactive BVOC (iBVOC) emission scheme in the United Kingdom Earth System Model (UKESM1.0)
Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model
Evaluating WRF-GC v2.0 predictions of boundary layer and vertical ozone profiles during the 2021 TRACER-AQ campaign in Houston, Texas
Intercomparison of the weather and climate physics suites of a unified forecast–climate model system (GRIST-A22.7.28) based on single-column modeling
Halogen chemistry in volcanic plumes: a 1D framework based on MOCAGE 1D (version R1.18.1) preparing 3D global chemistry modelling
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Long-term evaluation of surface air pollution in CAMSRA and MERRA-2 global reanalyses over Europe (2003–2020)
A simplified non-linear chemistry-transport model for analyzing NO2 column observations
Evaluating Three Decades of Precipitation in the Upper Colorado River Basin from a High-Resolution Regional Climate Model
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Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality in Africa
Comparison of ozone formation attribution techniques in the northeastern United States
Description and performance of the CARMA sectional aerosol microphysical model in CESM2
Improving trajectory calculations by FLEXPART 10.4+ using single-image super-resolution
Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0
Forecasting tropical cyclone tracks in the northwestern Pacific based on a deep-learning model
Emulating lateral gravity wave propagation in a global chemistry-climate model (EMAC v2.55.2) through horizontal flux redistribution
Modelling concentration heterogeneities in streets using the street-network model MUNICH
Accelerating models for multiphase chemical kinetics through machine learning with polynomial chaos expansion and neural networks
A machine learning emulator for Lagrangian particle dispersion model footprints: a case study using NAME
An optimisation method to improve modelling of wet deposition in atmospheric transport models: applied to FLEXPART v10.4
Bernhard M. Enz, Jan P. Engelmann, and Ulrike Lohmann
Geosci. Model Dev., 16, 5093–5112, https://doi.org/10.5194/gmd-16-5093-2023, https://doi.org/10.5194/gmd-16-5093-2023, 2023
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An algorithm to track tropical cyclones in model simulation data has been developed. The algorithm uses many combinations of varying parameter thresholds to detect weaker phases of tropical cyclones while still being resilient to false positives. It is shown that the algorithm performs well and adequately represents the tropical cyclone activity of the underlying simulation data. The impact of false positives on overall tropical cyclone activity is shown to be insignificant.
Sepehr Fathi, Mark Gordon, and Yongsheng Chen
Geosci. Model Dev., 16, 5069–5091, https://doi.org/10.5194/gmd-16-5069-2023, https://doi.org/10.5194/gmd-16-5069-2023, 2023
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We have combined various capabilities within a WRF model to generate simulations of atmospheric pollutant dispersion at 50 m resolution. The study objective was to resolve transport processes at the scale of measurements to assess and optimize aircraft-based emission rate retrievals. Model performance evaluation resulted in agreement within 5 % of observed meteorological and within 1–2 standard deviations of observed wind fields. Mass was conserved in the model within 5 % of input emissions.
Dylan Reynolds, Ethan Gutmann, Bert Kruyt, Michael Haugeneder, Tobias Jonas, Franziska Gerber, Michael Lehning, and Rebecca Mott
Geosci. Model Dev., 16, 5049–5068, https://doi.org/10.5194/gmd-16-5049-2023, https://doi.org/10.5194/gmd-16-5049-2023, 2023
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The challenge of running geophysical models is often compounded by the question of where to obtain appropriate data to give as input to a model. Here we present the HICAR model, a simplified atmospheric model capable of running at spatial resolutions of hectometers for long time series or over large domains. This makes physically consistent atmospheric data available at the spatial and temporal scales needed for some terrestrial modeling applications, for example seasonal snow forecasting.
Li Fang, Jianbing Jin, Arjo Segers, Hong Liao, Ke Li, Bufan Xu, Wei Han, Mijie Pang, and Hai Xiang Lin
Geosci. Model Dev., 16, 4867–4882, https://doi.org/10.5194/gmd-16-4867-2023, https://doi.org/10.5194/gmd-16-4867-2023, 2023
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Machine learning models have gained great popularity in air quality prediction. However, they are only available at air quality monitoring stations. In contrast, chemical transport models (CTM) provide predictions that are continuous in the 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional feature selection machine learning prediction (RFSML v1.0) and a CTM prediction.
Manu Goudar, Juliëtte C. S. Anema, Rajesh Kumar, Tobias Borsdorff, and Jochen Landgraf
Geosci. Model Dev., 16, 4835–4852, https://doi.org/10.5194/gmd-16-4835-2023, https://doi.org/10.5194/gmd-16-4835-2023, 2023
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A framework was developed to automatically detect plumes and compute emission estimates with cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using Visible Infrared Imaging Radiometer Suite active fire data. The emissions were more reliable when changing plume height in downwind direction was used instead of constant injection height. The CFM had uncertainty even when the meteorological conditions were accurate; thus there is a need for better inversion models.
Drew C. Pendergrass, Daniel J. Jacob, Hannah Nesser, Daniel J. Varon, Melissa Sulprizio, Kazuyuki Miyazaki, and Kevin W. Bowman
Geosci. Model Dev., 16, 4793–4810, https://doi.org/10.5194/gmd-16-4793-2023, https://doi.org/10.5194/gmd-16-4793-2023, 2023
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We have built a tool called CHEEREIO that allows scientists to use observations of pollutants or gases in the atmosphere, such as from satellites or surface stations, to update supercomputer models that simulate the Earth. CHEEREIO uses the difference between the model simulations of the atmosphere and real-world observations to come up with a good guess for the actual composition of our atmosphere, the true emissions of various pollutants, and whatever else they may want to study.
Yosuke Yamazaki
Geosci. Model Dev., 16, 4749–4766, https://doi.org/10.5194/gmd-16-4749-2023, https://doi.org/10.5194/gmd-16-4749-2023, 2023
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The Earth's atmosphere can support various types of global-scale waves. Some waves propagate eastward and others westward, and they can have different zonal wavenumbers. The Fourier–wavelet analysis is a useful technique for identifying different components of global-scale waves and their temporal variability. This paper introduces an easy-to-implement method to derive Fourier–wavelet spectra from 2-D space–time data. Application examples are presented using atmospheric models.
Bok H. Baek, Carlie Coats, Siqi Ma, Chi-Tsan Wang, Yunyao Li, Jia Xing, Daniel Tong, Soontae Kim, and Jung-Hun Woo
Geosci. Model Dev., 16, 4659–4676, https://doi.org/10.5194/gmd-16-4659-2023, https://doi.org/10.5194/gmd-16-4659-2023, 2023
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To enable the direct feedback effects of aerosols and local meteorology in an air quality modeling system without any computational bottleneck, we have developed an inline meteorology-induced emissions coupler module within the U.S. Environmental Protection Agency’s Community Multiscale Air Quality modeling system to dynamically model the complex MOtor Vehicle Emission Simulator (MOVES) on-road mobile emissions inline without a separate dedicated emissions processing model like SMOKE.
Christoph Neuhauser, Maicon Hieronymus, Michael Kern, Marc Rautenhaus, Annika Oertel, and Rüdiger Westermann
Geosci. Model Dev., 16, 4617–4638, https://doi.org/10.5194/gmd-16-4617-2023, https://doi.org/10.5194/gmd-16-4617-2023, 2023
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Numerical weather prediction models rely on parameterizations for sub-grid-scale processes, which are a source of uncertainty. We present novel visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along trajectories regarding similarities in temporal development and spatiotemporal relationships. The proposed workflow is applied to cloud microphysical sensitivities along coherent strongly ascending trajectories.
Yingqi Zheng, Minttu Havu, Huizhi Liu, Xueling Cheng, Yifan Wen, Hei Shing Lee, Joyson Ahongshangbam, and Leena Järvi
Geosci. Model Dev., 16, 4551–4579, https://doi.org/10.5194/gmd-16-4551-2023, https://doi.org/10.5194/gmd-16-4551-2023, 2023
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The performance of the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated against the observed surface exchanges (fluxes) of heat and carbon dioxide in a densely built neighborhood in Beijing. The heat flux modeling is noticeably improved by using the observed maximum conductance and by optimizing the vegetation phenology modeling. SUEWS also performs well in simulating carbon dioxide flux.
Simone Dietmüller, Sigrun Matthes, Katrin Dahlmann, Hiroshi Yamashita, Abolfazl Simorgh, Manuel Soler, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Christian Weder, Volker Grewe, Feijia Yin, and Federica Castino
Geosci. Model Dev., 16, 4405–4425, https://doi.org/10.5194/gmd-16-4405-2023, https://doi.org/10.5194/gmd-16-4405-2023, 2023
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Climate-optimized aircraft trajectories avoid atmospheric regions with a large climate impact due to aviation emissions. This requires spatially and temporally resolved information on aviation's climate impact. We propose using algorithmic climate change functions (aCCFs) for CO2 and non-CO2 effects (ozone, methane, water vapor, contrail cirrus). Merged aCCFs combine individual aCCFs by assuming aircraft-specific parameters and climate metrics. Technically this is done with a Python library.
Andreas A. Beckert, Lea Eisenstein, Annika Oertel, Tim Hewson, George C. Craig, and Marc Rautenhaus
Geosci. Model Dev., 16, 4427–4450, https://doi.org/10.5194/gmd-16-4427-2023, https://doi.org/10.5194/gmd-16-4427-2023, 2023
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We investigate the benefit of objective 3-D front detection with modern interactive visual analysis techniques for case studies of extra-tropical cyclones and comparisons of frontal structures between different numerical weather prediction models. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment them in the vertical dimension. We see great potential for more complex studies of atmospheric dynamics and for operational weather forecasting.
Zhenxin Liu, Yuanhao Chen, Yuhang Wang, Cheng Liu, Shuhua Liu, and Hong Liao
Geosci. Model Dev., 16, 4385–4403, https://doi.org/10.5194/gmd-16-4385-2023, https://doi.org/10.5194/gmd-16-4385-2023, 2023
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The heterogeneous layout of urban buildings leads to the complex wind field in and over the urban canopy. Large discrepancies between the observations and the current simulations result from misunderstanding the character of the wind field. The Inhomogeneous Wind Scheme in Urban Street (IWSUS) was developed to simulate the heterogeneity of the wind speed in a typical street and then improve the simulated energy budget in the lower atmospheric layer over the urban canopy.
Kai Cao, Qizhong Wu, Lingling Wang, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongqing Li, and Lanning Wang
Geosci. Model Dev., 16, 4367–4383, https://doi.org/10.5194/gmd-16-4367-2023, https://doi.org/10.5194/gmd-16-4367-2023, 2023
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Offline performance experiment results show that the GPU-HADVPPM on a V100 GPU can achieve up to 1113.6 × speedups to its original version on an E5-2682 v4 CPU. A series of optimization measures are taken, and the CAMx-CUDA model improves the computing efficiency by 128.4 × on a single V100 GPU card. A parallel architecture with an MPI plus CUDA hybrid paradigm is presented, and it can achieve up to 4.5 × speedup when launching eight CPU cores and eight GPU cards.
Laurent Menut
Geosci. Model Dev., 16, 4265–4281, https://doi.org/10.5194/gmd-16-4265-2023, https://doi.org/10.5194/gmd-16-4265-2023, 2023
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This study analyzes forecasts that were made in 2021 to help trigger measurements during the CADDIWA experiment. The WRF and CHIMERE models were run each day, and the first goal is to quantify the variability of the forecast as a function of forecast leads and forecast location. The possibility of using the different leads as an ensemble is also tested. For some locations, the correlation scores are better with this approach. This could be tested on operational forecast chains in the future.
Emily de Jong, John Ben Mackay, Oleksii Bulenok, Anna Jaruga, and Sylwester Arabas
Geosci. Model Dev., 16, 4193–4211, https://doi.org/10.5194/gmd-16-4193-2023, https://doi.org/10.5194/gmd-16-4193-2023, 2023
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In clouds, collisional breakup occurs when two colliding droplets splinter into new, smaller fragments. Particle-based modeling approaches often do not represent breakup because of the computational demands of creating new droplets. We present a particle-based breakup method that preserves the computational efficiency of these methods. In a series of simple demonstrations, we show that this representation alters cloud processes in reasonable and expected ways.
Caiyi Jin, Qiangqiang Yuan, Tongwen Li, Yuan Wang, and Liangpei Zhang
Geosci. Model Dev., 16, 4137–4154, https://doi.org/10.5194/gmd-16-4137-2023, https://doi.org/10.5194/gmd-16-4137-2023, 2023
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The semi-empirical physical approach derives PM2.5 with strong physical significance. However, due to the complex optical characteristic, the physical parameters are difficult to express accurately. Thus, combining the atmospheric physical mechanism and machine learning, we propose an optimized model. It creatively embeds the random forest model into the physical PM2.5 remote sensing approach to simulate a physical parameter. Our method shows great optimized performance in the validations.
Cyril Caram, Sophie Szopa, Anne Cozic, Slimane Bekki, Carlos A. Cuevas, and Alfonso Saiz-Lopez
Geosci. Model Dev., 16, 4041–4062, https://doi.org/10.5194/gmd-16-4041-2023, https://doi.org/10.5194/gmd-16-4041-2023, 2023
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We studied the role of halogenated compounds (containing chlorine, bromine and iodine), emitted by natural processes (mainly above the oceans), in the chemistry of the lower layers of the atmosphere. We introduced this relatively new chemistry in a three-dimensional climate–chemistry model and looked at how this chemistry will disrupt the ozone. We showed that the concentration of ozone decreases by 22 % worldwide and that of the atmospheric detergent, OH, by 8 %.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
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Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Min-Seop Ahn, Paul A. Ullrich, Peter J. Gleckler, Jiwoo Lee, Ana C. Ordonez, and Angeline G. Pendergrass
Geosci. Model Dev., 16, 3927–3951, https://doi.org/10.5194/gmd-16-3927-2023, https://doi.org/10.5194/gmd-16-3927-2023, 2023
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We introduce a framework for regional-scale evaluation of simulated precipitation distributions with 62 climate reference regions and 10 metrics and apply it to evaluate CMIP5 and CMIP6 models against multiple satellite-based precipitation products. The common model biases identified in this study are mainly associated with the overestimated light precipitation and underestimated heavy precipitation. These biases persist from earlier-generation models and have been slightly improved in CMIP6.
Christine Wiedinmyer, Yosuke Kimura, Elena C. McDonald-Buller, Louisa K. Emmons, Rebecca R. Buchholz, Wenfu Tang, Keenan Seto, Maxwell B. Joseph, Kelley C. Barsanti, Annmarie G. Carlton, and Robert Yokelson
Geosci. Model Dev., 16, 3873–3891, https://doi.org/10.5194/gmd-16-3873-2023, https://doi.org/10.5194/gmd-16-3873-2023, 2023
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The Fire INventory from NCAR (FINN) provides daily global estimates of emissions from open fires based on satellite detections of hot spots. This version has been updated to apply MODIS and VIIRS satellite fire detection and better represents both large and small fires. FINNv2.5 generates more emissions than FINNv1 and is in general agreement with other fire emissions inventories. The new estimates are consistent with satellite observations, but uncertainties remain regionally and by pollutant.
Lichao Yang, Wansuo Duan, and Zifa Wang
Geosci. Model Dev., 16, 3827–3848, https://doi.org/10.5194/gmd-16-3827-2023, https://doi.org/10.5194/gmd-16-3827-2023, 2023
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An approach is proposed to refine a ground meteorological observation network to improve the PM2.5 forecasts in the Beijing–Tianjin–Hebei region. A cost-effective observation network is obtained and makes the relevant PM2.5 forecasts assimilate fewer observations but achieve the forecasting skill comparable to or higher than that obtained by assimilating all ground station observations, suggesting that many of the current ground stations can be greatly scattered to avoid much unnecessary work.
Abhishekh Kumar Srivastava, Paul Aaron Ullrich, Deeksha Rastogi, Pouya Vahmani, Andrew Jones, and Richard Grotjahn
Geosci. Model Dev., 16, 3699–3722, https://doi.org/10.5194/gmd-16-3699-2023, https://doi.org/10.5194/gmd-16-3699-2023, 2023
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Stakeholders need high-resolution regional climate data for applications such as assessing water availability and mountain snowpack. This study examines 3 h and 24 h historical precipitation over the contiguous United States in the 12 km WRF version 4.2.1-based dynamical downscaling of the ERA5 reanalysis. WRF improves precipitation characteristics such as the annual cycle and distribution of the precipitation maxima, but it also displays regionally and seasonally varying precipitation biases.
Haixia Xiao, Yaqiang Wang, Yu Zheng, Yuanyuan Zheng, Xiaoran Zhuang, Hongyan Wang, and Mei Gao
Geosci. Model Dev., 16, 3611–3628, https://doi.org/10.5194/gmd-16-3611-2023, https://doi.org/10.5194/gmd-16-3611-2023, 2023
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Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CG nowcasting has remained unattainable. Here, we developed a deep learning model — namely CGsNet — for 0—2 h of quantitative CG nowcasting, first achieving minute—kilometer-level forecasts. Based on the CGsNet model, the average surface wind speed (ASWS) and peak wind gust speed (PWGS) predictions are obtained. Experiments indicate that CGsNet exhibits higher accuracy than the traditional method.
Maria Krutova, Mostafa Bakhoday-Paskyabi, Joachim Reuder, and Finn Gunnar Nielsen
Geosci. Model Dev., 16, 3553–3564, https://doi.org/10.5194/gmd-16-3553-2023, https://doi.org/10.5194/gmd-16-3553-2023, 2023
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Local refinement of the grid is a powerful method allowing us to reduce the computational time while preserving the accuracy in the area of interest. Depending on the implementation, the local refinement may introduce unwanted numerical effects into the results. We study the wind speed common to the wind turbine operational speeds and confirm strong alteration of the result when the heat fluxes are present, except for the specific refinement scheme used.
Sylvia Sullivan, Behrooz Keshtgar, Nicole Albern, Elzina Bala, Christoph Braun, Anubhav Choudhary, Johannes Hörner, Hilke Lentink, Georgios Papavasileiou, and Aiko Voigt
Geosci. Model Dev., 16, 3535–3551, https://doi.org/10.5194/gmd-16-3535-2023, https://doi.org/10.5194/gmd-16-3535-2023, 2023
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Clouds absorb and re-emit infrared radiation from Earth's surface and absorb and reflect incoming solar radiation. As a result, they change atmospheric temperature gradients that drive large-scale circulation. To better simulate this circulation, we study how the radiative heating and cooling from clouds depends on model settings like grid spacing; whether we describe convection approximately or exactly; and the level of detail used to describe small-scale processes, or microphysics, in clouds.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavcic, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben J. Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
EGUsphere, https://doi.org/10.5194/egusphere-2023-647, https://doi.org/10.5194/egusphere-2023-647, 2023
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3D climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
James Weber, James A. King, Katerina Sindelarova, and Maria Val Martin
Geosci. Model Dev., 16, 3083–3101, https://doi.org/10.5194/gmd-16-3083-2023, https://doi.org/10.5194/gmd-16-3083-2023, 2023
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The emissions of volatile organic compounds from vegetation (BVOCs) influence atmospheric composition and contribute to certain gases and aerosols (tiny airborne particles) which play a role in climate change. BVOC emissions are likely to change in the future due to changes in climate and land use. Therefore, accurate simulation of BVOC emission is important, and this study describes an update to the simulation of BVOC emissions in the United Kingdom Earth System Model (UKESM).
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
Xueying Liu, Yuxuan Wang, Shailaja Wasti, Wei Li, Ehsan Soleimanian, James Flynn, Travis Griggs, Sergio Alvarez, John T. Sullivan, Maurice Roots, Laurence Twigg, Guillaume Gronoff, Timothy Berkoff, Paul Walter, Mark Estes, Johnathan W. Hair, Taylor Shingler, Amy Jo Scarino, Marta Fenn, and Laura Judd
EGUsphere, https://doi.org/10.5194/egusphere-2023-892, https://doi.org/10.5194/egusphere-2023-892, 2023
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With a comprehensive suite of ground-based and airborne remote sensing measurements during the 2021 Tracking Aerosol Convection Experiment Air Quality (TRACER-AQ) campaign in Houston, this study evaluates the simulation of the planetary boundary layer (PBL) height and the ozone vertical profile by a high-resolution (1.33 km) 3-D photochemical model Weather Research and Forecasting-driven GEOS-Chem (WRF-GC).
Xiaohan Li, Yi Zhang, Xindong Peng, Baiquan Zhou, Jian Li, and Yiming Wang
Geosci. Model Dev., 16, 2975–2993, https://doi.org/10.5194/gmd-16-2975-2023, https://doi.org/10.5194/gmd-16-2975-2023, 2023
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The weather and climate physics suites used in GRIST-A22.7.28 are compared using single-column modeling. The source of their discrepancies in terms of modeling cloud and precipitation is explored. Convective parameterization is found to be a key factor responsible for the differences. The two suites also have intrinsic differences in the interaction between microphysics and other processes, resulting in different cloud features and time step sensitivities.
Virginie Marécal, Ronan Voisin-Plessis, Tjarda Jane Roberts, Alessandro Aiuppa, Herizo Narivelo, Paul David Hamer, Béatrice Josse, Jonathan Guth, Luke Surl, and Lisa Grellier
Geosci. Model Dev., 16, 2873–2898, https://doi.org/10.5194/gmd-16-2873-2023, https://doi.org/10.5194/gmd-16-2873-2023, 2023
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We implemented a halogen volcanic chemistry scheme in a one-dimensional modelling framework preparing for further use in a three-dimensional global chemistry-transport model. The results of the simulations for an eruption of Mt Etna in 2008, including various sensitivity tests, show a good consistency with previous modelling studies.
Zhe Feng, Joseph Hardin, Hannah C. Barnes, Jianfeng Li, L. Ruby Leung, Adam Varble, and Zhixiao Zhang
Geosci. Model Dev., 16, 2753–2776, https://doi.org/10.5194/gmd-16-2753-2023, https://doi.org/10.5194/gmd-16-2753-2023, 2023
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PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to track convective clouds from a variety of observations and model simulations. The package has a collection of multi-object identification algorithms and has been optimized for large datasets. This paper describes the algorithms and demonstrates applications for tracking deep convective cells and mesoscale convective systems from observations and model simulations at a wide range of scales.
Yan Ji, Bing Gong, Michael Langguth, Amirpasha Mozaffari, and Xiefei Zhi
Geosci. Model Dev., 16, 2737–2752, https://doi.org/10.5194/gmd-16-2737-2023, https://doi.org/10.5194/gmd-16-2737-2023, 2023
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Formulating short-term precipitation forecasting as a video prediction task, a novel deep learning architecture (convolutional long short-term memory generative adversarial network, CLGAN) is proposed. A benchmark dataset is built on minute-level precipitation measurements. Results show that with the GAN component the model generates predictions sharing statistical properties with observations, resulting in it outperforming the baseline in dichotomous and spatial scores for heavy precipitation.
Aleksander Lacima, Hervé Petetin, Albert Soret, Dene Bowdalo, Oriol Jorba, Zhaoyue Chen, Raúl F. Méndez Turrubiates, Hicham Achebak, Joan Ballester, and Carlos Pérez García-Pando
Geosci. Model Dev., 16, 2689–2718, https://doi.org/10.5194/gmd-16-2689-2023, https://doi.org/10.5194/gmd-16-2689-2023, 2023
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Understanding how air pollution varies across space and time is of key importance for the safeguarding of human health. This work arose in the context of the project EARLY-ADAPT, for which the Barcelona Supercomputing Center developed an air pollution database covering all of Europe. Through different statistical methods, we compared two global pollution models against measurements from ground stations and found significant discrepancies between the observed and the modeled surface pollution.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-876, https://doi.org/10.5194/egusphere-2023-876, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and evaluate modeled results against TROPOMI v2 over multiple power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind direction and prior emissions.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-69, https://doi.org/10.5194/gmd-2023-69, 2023
Preprint under review for GMD
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It's important to know how well atmospheric models do in the mountains, but there aren't very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado river basin against the data that's available. The model works pretty well but, there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we couldn't before.
Andrew Geiss, Po-Lun Ma, Balwinder Singh, and Joseph C. Hardin
Geosci. Model Dev., 16, 2355–2370, https://doi.org/10.5194/gmd-16-2355-2023, https://doi.org/10.5194/gmd-16-2355-2023, 2023
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Atmospheric aerosols play a critical role in Earth's climate, but it is too computationally expensive to directly model their interaction with radiation in climate simulations. This work develops a new neural-network-based parameterization of aerosol optical properties for use in the Energy Exascale Earth System Model that is much more accurate than the current one; it also introduces a unique model optimization method that involves randomly generating neural network architectures.
Joey C. Y. Lam, Amos P. K. Tai, Jason A. Ducker, and Christopher D. Holmes
Geosci. Model Dev., 16, 2323–2342, https://doi.org/10.5194/gmd-16-2323-2023, https://doi.org/10.5194/gmd-16-2323-2023, 2023
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We developed a new component within an atmospheric chemistry model to better simulate plant ecophysiological processes relevant for ozone air quality. We showed that it reduces simulated biases in plant uptake of ozone in prior models. The new model enables us to explore how future climatic changes affect air quality via affecting plants, examine ozone–vegetation interactions and feedbacks, and evaluate the impacts of changing atmospheric chemistry and climate on vegetation productivity.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-50, https://doi.org/10.5194/gmd-2023-50, 2023
Revised manuscript accepted for GMD
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The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations, and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model-satellite discrepancies, we find that future field campaigns in an East African region (30° E – 45° E, 5° S – 5° N) could substantially improve the predictive skill of air quality models.
Qian Shu, Sergey L. Napelenok, William T. Hutzell, Kirk R. Baker, Barron H. Henderson, Benjamin N. Murphy, and Christian Hogrefe
Geosci. Model Dev., 16, 2303–2322, https://doi.org/10.5194/gmd-16-2303-2023, https://doi.org/10.5194/gmd-16-2303-2023, 2023
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Source attribution methods are generally used to determine culpability of precursor emission sources to ambient pollutant concentrations. However, source attribution of secondarily formed pollutants such as ozone and its precursors cannot be explicitly measured, making evaluation of source apportionment methods challenging. In this study, multiple apportionment approach comparisons show common features but still reveal wide variations in predicted sector contribution and species dependency.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-79, https://doi.org/10.5194/gmd-2023-79, 2023
Revised manuscript accepted for GMD
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We implemented an alternative aerosol scheme in the high and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. The development enables the comparison of different aerosol schemes with different complexity in the same model framework and identifies improvements in comparison to a range of observations in both the troposphere and stratosphere.
Rüdiger Brecht, Lucie Bakels, Alex Bihlo, and Andreas Stohl
Geosci. Model Dev., 16, 2181–2192, https://doi.org/10.5194/gmd-16-2181-2023, https://doi.org/10.5194/gmd-16-2181-2023, 2023
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We use neural-network-based single-image super-resolution to improve the upscaling of meteorological wind fields to be used for particle dispersion models. This deep-learning-based methodology improves the standard linear interpolation typically used in particle dispersion models. The improvement of wind fields leads to substantial improvement in the computed trajectories of the particles.
Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodriguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
Geosci. Model Dev., 16, 2193–2213, https://doi.org/10.5194/gmd-16-2193-2023, https://doi.org/10.5194/gmd-16-2193-2023, 2023
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This work aims to derive and evaluate a general statistical post-processing tool specifically designed for the street scale that can be applied to any urban air quality system. Our data fusion methodology corrects NO2 fields based on continuous hourly observations and experimental campaigns. This study enables us to obtain exceedance probability maps of air quality standards. In 2019, 13 % of the Barcelona area had a 70 % or higher probability of exceeding the annual legal NO2 limit of 40 µg/m3.
Liang Wang, Bingcheng Wan, Shaohui Zhou, Haofei Sun, and Zhiqiu Gao
Geosci. Model Dev., 16, 2167–2179, https://doi.org/10.5194/gmd-16-2167-2023, https://doi.org/10.5194/gmd-16-2167-2023, 2023
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The past 24 h TC trajectories and meteorological field data were used to forecast TC tracks in the northwestern Pacific from hours 6–72 based on GRU_CNN, which we proposed in this paper and which has better prediction results than traditional single deep-learning methods. The historical steering flow of cyclones has a significant effect on improving the accuracy of short-term forecasting, while, in long-term forecasting, the SST and geopotential height will have a particular impact.
Roland Eichinger, Sebastian Rhode, Hella Garny, Peter Preusse, Petr Pisoft, Aleš Kuchar, Patrick Jöckel, Astrid Kerkweg, and Bastian Kern
EGUsphere, https://doi.org/10.5194/egusphere-2023-270, https://doi.org/10.5194/egusphere-2023-270, 2023
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Dynamical model biases result from the columnar approach of gravity wave (GW) schemes, but parallel decomposition makes horizontal GW propagation computationally unfeasible. In the global model EMAC, we approximate it by GW redistribution at one altitude using tailor-made redistribution maps generated with a ray-tracer. More spread-out GW drag helps reconciling the model with observations and closing the 60S GW gap. Polar vortex dynamics are improved, enhancing climate model credibility.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-70, https://doi.org/10.5194/gmd-2023-70, 2023
Revised manuscript accepted for GMD
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A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
Geosci. Model Dev., 16, 2037–2054, https://doi.org/10.5194/gmd-16-2037-2023, https://doi.org/10.5194/gmd-16-2037-2023, 2023
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Kinetic multi-layer models (KMs) successfully describe heterogeneous and multiphase atmospheric chemistry. In applications requiring repeated execution, however, these models can be too expensive. We trained machine learning surrogate models on output of the model KM-SUB and achieved high correlations. The surrogate models run orders of magnitude faster, which suggests potential applicability in global optimization tasks and as sub-modules in large-scale atmospheric models.
Elena Fillola, Raul Santos-Rodriguez, Alistair Manning, Simon O'Doherty, and Matt Rigby
Geosci. Model Dev., 16, 1997–2009, https://doi.org/10.5194/gmd-16-1997-2023, https://doi.org/10.5194/gmd-16-1997-2023, 2023
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Lagrangian particle dispersion models are used extensively for the estimation of greenhouse gas (GHG) fluxes using atmospheric observations. However, these models do not scale well as data volumes increase. Here, we develop a proof-of-concept machine learning emulator that can produce outputs similar to those of the dispersion model, but 50 000 times faster, using only meteorological inputs. This works demonstrates the potential of machine learning to accelerate GHG estimations across the globe.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
EGUsphere, https://doi.org/10.5194/egusphere-2023-357, https://doi.org/10.5194/egusphere-2023-357, 2023
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Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidental) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011), and show that it improves the simulation of wet deposition.
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Short summary
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system. The CMAQ model is used extensively throughout the world to simulate air pollutants for many purposes, including regulatory and air quality forecasting applications. This work describes the scientific updates made to the latest version of the CMAQ modeling system (CMAQv5.1) and presents an evaluation of the new model against observations and results from the previous model version.
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality...
