Articles | Volume 9, issue 6
https://doi.org/10.5194/gmd-9-2191-2016
© Author(s) 2016. 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-9-2191-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
16 Jun 2016
Development and technical paper |
| 16 Jun 2016
Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California
US Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA
Kirk R. Baker
US Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, USA
Melinda R. Beaver
US Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, USA
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Christian Hogrefe, Stefano Galmarini, Paul A. Makar, Ioannis Kioutsioukis, Olivia E. Clifton, Ummugulsum Alyuz, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Butler, Philip Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camanyo, Jonathan E. Pleim, Young-Hee Ryu, Roberto San Jose, Martijn Schaap, Donna B. Schwede, and Ranjeet Sokhi
EGUsphere, https://doi.org/10.5194/egusphere-2025-225, https://doi.org/10.5194/egusphere-2025-225, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Performed under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in regional-scale models. The results also strongly suggest that improvement and harmonization of the representation of land use in these models would serve the community in their future development efforts.
T. Nash Skipper, Emma L. D'Ambro, Forwood C. Wiser, V. Faye McNeill, Rebecca H. Schwantes, Barron H. Henderson, Ivan R. Piletic, Colleen B. Baublitz, Jesse O. Bash, Andrew R. Whitehill, Lukas C. Valin, Asher P. Mouat, Jennifer Kaiser, Glenn M. Wolfe, Jason M. St. Clair, Thomas F. Hanisco, Alan Fried, Bryan K. Place, and Havala O.T. Pye
Atmos. Chem. Phys., 24, 12903–12924, https://doi.org/10.5194/acp-24-12903-2024, https://doi.org/10.5194/acp-24-12903-2024, 2024
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We develop the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 2 to improve predictions of formaldehyde in ambient air compared to satellite-, aircraft-, and ground-based observations. With the updated chemistry, we estimate the cancer risk from inhalation exposure to ambient formaldehyde across the contiguous USA and predict that 40 % of this risk is controllable through reductions in anthropogenic emissions of nitrogen oxides and reactive organic carbon.
Anam M. Khan, Olivia E. Clifton, Jesse O. Bash, Sam Bland, Nathan Booth, Philip Cheung, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christian Hogrefe, Christopher D. Holmes, Laszlo Horvath, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Perez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Donna Schwede, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamas Weidinger, Zhiyong Wu, Leiming Zhang, and Paul C. Stoy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3038, https://doi.org/10.5194/egusphere-2024-3038, 2024
Short summary
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Vegetation removes tropospheric ozone through stomatal uptake, and accurately modeling the stomatal uptake of ozone is important for modeling dry deposition and air quality. We evaluated the stomatal component of ozone dry deposition modeled by atmospheric chemistry models at six sites. We find that models and observation-based estimates agree at times during the growing season at all sites, but some models overestimated the stomatal component during the dry summers at a seasonally dry site.
Paul A. Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz-Ozdemir, Jesse O. Bash, Michael D. Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E. Clifton, Alma Hodzic, Iannis Koutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A. Lynch, Kester Momoh, Juan L. Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark Shephard, Ranjeet Sokhi, and Stefano Galmarini
EGUsphere, https://doi.org/10.5194/egusphere-2024-2226, https://doi.org/10.5194/egusphere-2024-2226, 2024
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The large range of sulphur and nitrogen deposition estimates from air-quality models results in a large range of predicted impacts. We used models and deposition diagnostics to identify the processes controlling atmospheric sulphur and nitrogen deposition variability. Controlling factors included the uptake of gases and aerosols by droplets, rain, snow, etc., aerosol inorganic chemistry, particle dry deposition, ammonia bidirectional fluxes, and gas deposition via plant cuticles and soil.
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
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A primary sink of air pollutants is dry deposition. Dry deposition estimates differ across the models used to simulate atmospheric chemistry. Here, we introduce an effort to examine dry deposition schemes from atmospheric chemistry models. We provide our approach’s rationale, document the schemes, and describe datasets used to drive and evaluate the schemes. We also launch the analysis of results by evaluating against observations and identifying the processes leading to model–model differences.
Christian Hogrefe, Jesse O. Bash, Jonathan E. Pleim, Donna B. Schwede, Robert C. Gilliam, Kristen M. Foley, K. Wyat Appel, and Rohit Mathur
Atmos. Chem. Phys., 23, 8119–8147, https://doi.org/10.5194/acp-23-8119-2023, https://doi.org/10.5194/acp-23-8119-2023, 2023
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Under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in the widely used CMAQ model. The results illustrate how these tools can provide insights into similarities and differences between the two CMAQ dry deposition options that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.
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
Atmos. Chem. Phys., 23, 5043–5099, https://doi.org/10.5194/acp-23-5043-2023, https://doi.org/10.5194/acp-23-5043-2023, 2023
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Chemical mechanisms describe how emissions from vehicles, vegetation, and other sources are chemically transformed in the atmosphere to secondary products including criteria and hazardous air pollutants. The Community Regional Atmospheric Chemistry Multiphase Mechanism integrates gas-phase radical chemistry with pathways to fine-particle mass. New species were implemented, resulting in a bottom-up representation of organic aerosol, which is required for accurate source attribution of pollutants.
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
Biogeosciences, 20, 971–995, https://doi.org/10.5194/bg-20-971-2023, https://doi.org/10.5194/bg-20-971-2023, 2023
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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.
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.
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.
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).
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.
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
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.
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.
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.
K. Wyat Appel, Sergey L. Napelenok, Kristen M. Foley, Havala O. T. Pye, Christian Hogrefe, Deborah J. Luecken, Jesse O. Bash, Shawn J. Roselle, Jonathan E. Pleim, Hosein Foroutan, William T. Hutzell, George A. Pouliot, Golam Sarwar, Kathleen M. Fahey, Brett Gantt, Robert C. Gilliam, Nicholas K. Heath, Daiwen Kang, Rohit Mathur, Donna B. Schwede, Tanya L. Spero, David C. Wong, and Jeffrey O. Young
Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, https://doi.org/10.5194/gmd-10-1703-2017, 2017
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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.
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.
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
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.
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
Christian Hogrefe, Stefano Galmarini, Paul A. Makar, Ioannis Kioutsioukis, Olivia E. Clifton, Ummugulsum Alyuz, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Butler, Philip Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camanyo, Jonathan E. Pleim, Young-Hee Ryu, Roberto San Jose, Martijn Schaap, Donna B. Schwede, and Ranjeet Sokhi
EGUsphere, https://doi.org/10.5194/egusphere-2025-225, https://doi.org/10.5194/egusphere-2025-225, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Performed under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in regional-scale models. The results also strongly suggest that improvement and harmonization of the representation of land use in these models would serve the community in their future development efforts.
T. Nash Skipper, Emma L. D'Ambro, Forwood C. Wiser, V. Faye McNeill, Rebecca H. Schwantes, Barron H. Henderson, Ivan R. Piletic, Colleen B. Baublitz, Jesse O. Bash, Andrew R. Whitehill, Lukas C. Valin, Asher P. Mouat, Jennifer Kaiser, Glenn M. Wolfe, Jason M. St. Clair, Thomas F. Hanisco, Alan Fried, Bryan K. Place, and Havala O.T. Pye
Atmos. Chem. Phys., 24, 12903–12924, https://doi.org/10.5194/acp-24-12903-2024, https://doi.org/10.5194/acp-24-12903-2024, 2024
Short summary
Short summary
We develop the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 2 to improve predictions of formaldehyde in ambient air compared to satellite-, aircraft-, and ground-based observations. With the updated chemistry, we estimate the cancer risk from inhalation exposure to ambient formaldehyde across the contiguous USA and predict that 40 % of this risk is controllable through reductions in anthropogenic emissions of nitrogen oxides and reactive organic carbon.
Anam M. Khan, Olivia E. Clifton, Jesse O. Bash, Sam Bland, Nathan Booth, Philip Cheung, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christian Hogrefe, Christopher D. Holmes, Laszlo Horvath, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Perez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Donna Schwede, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamas Weidinger, Zhiyong Wu, Leiming Zhang, and Paul C. Stoy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3038, https://doi.org/10.5194/egusphere-2024-3038, 2024
Short summary
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Vegetation removes tropospheric ozone through stomatal uptake, and accurately modeling the stomatal uptake of ozone is important for modeling dry deposition and air quality. We evaluated the stomatal component of ozone dry deposition modeled by atmospheric chemistry models at six sites. We find that models and observation-based estimates agree at times during the growing season at all sites, but some models overestimated the stomatal component during the dry summers at a seasonally dry site.
Paul A. Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz-Ozdemir, Jesse O. Bash, Michael D. Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E. Clifton, Alma Hodzic, Iannis Koutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A. Lynch, Kester Momoh, Juan L. Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark Shephard, Ranjeet Sokhi, and Stefano Galmarini
EGUsphere, https://doi.org/10.5194/egusphere-2024-2226, https://doi.org/10.5194/egusphere-2024-2226, 2024
Short summary
Short summary
The large range of sulphur and nitrogen deposition estimates from air-quality models results in a large range of predicted impacts. We used models and deposition diagnostics to identify the processes controlling atmospheric sulphur and nitrogen deposition variability. Controlling factors included the uptake of gases and aerosols by droplets, rain, snow, etc., aerosol inorganic chemistry, particle dry deposition, ammonia bidirectional fluxes, and gas deposition via plant cuticles and soil.
Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-48, https://doi.org/10.5194/gmd-2024-48, 2024
Preprint withdrawn
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We describe the Comprehensive Air quality Model with extensions (CAMx) and evaluate a model simulation during 2016 over nine U.S. climate zones. For ozone, the model statistically replicates measured concentrations better than most other past models and applications. For small inhalable particulates, the model replicates concentrations consistent with most other past models and applications subject to common uncertainties associated with sources, weather, and chemical interactions.
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
Short summary
Short summary
A primary sink of air pollutants is dry deposition. Dry deposition estimates differ across the models used to simulate atmospheric chemistry. Here, we introduce an effort to examine dry deposition schemes from atmospheric chemistry models. We provide our approach’s rationale, document the schemes, and describe datasets used to drive and evaluate the schemes. We also launch the analysis of results by evaluating against observations and identifying the processes leading to model–model differences.
Christian Hogrefe, Jesse O. Bash, Jonathan E. Pleim, Donna B. Schwede, Robert C. Gilliam, Kristen M. Foley, K. Wyat Appel, and Rohit Mathur
Atmos. Chem. Phys., 23, 8119–8147, https://doi.org/10.5194/acp-23-8119-2023, https://doi.org/10.5194/acp-23-8119-2023, 2023
Short summary
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Under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in the widely used CMAQ model. The results illustrate how these tools can provide insights into similarities and differences between the two CMAQ dry deposition options that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.
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
Atmos. Chem. Phys., 23, 5043–5099, https://doi.org/10.5194/acp-23-5043-2023, https://doi.org/10.5194/acp-23-5043-2023, 2023
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Chemical mechanisms describe how emissions from vehicles, vegetation, and other sources are chemically transformed in the atmosphere to secondary products including criteria and hazardous air pollutants. The Community Regional Atmospheric Chemistry Multiphase Mechanism integrates gas-phase radical chemistry with pathways to fine-particle mass. New species were implemented, resulting in a bottom-up representation of organic aerosol, which is required for accurate source attribution of pollutants.
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.
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
Biogeosciences, 20, 971–995, https://doi.org/10.5194/bg-20-971-2023, https://doi.org/10.5194/bg-20-971-2023, 2023
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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.
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.
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.
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).
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.
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
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.
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.
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.
K. Wyat Appel, Sergey L. Napelenok, Kristen M. Foley, Havala O. T. Pye, Christian Hogrefe, Deborah J. Luecken, Jesse O. Bash, Shawn J. Roselle, Jonathan E. Pleim, Hosein Foroutan, William T. Hutzell, George A. Pouliot, Golam Sarwar, Kathleen M. Fahey, Brett Gantt, Robert C. Gilliam, Nicholas K. Heath, Daiwen Kang, Rohit Mathur, Donna B. Schwede, Tanya L. Spero, David C. Wong, and Jeffrey O. Young
Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, https://doi.org/10.5194/gmd-10-1703-2017, 2017
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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.
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.
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.
Caroline R. Nowlan, Xiong Liu, James W. Leitch, Kelly Chance, Gonzalo González Abad, Cheng Liu, Peter Zoogman, Joshua Cole, Thomas Delker, William Good, Frank Murcray, Lyle Ruppert, Daniel Soo, Melanie B. Follette-Cook, Scott J. Janz, Matthew G. Kowalewski, Christopher P. Loughner, Kenneth E. Pickering, Jay R. Herman, Melinda R. Beaver, Russell W. Long, James J. Szykman, Laura M. Judd, Paul Kelley, Winston T. Luke, Xinrong Ren, and Jassim A. Al-Saadi
Atmos. Meas. Tech., 9, 2647–2668, https://doi.org/10.5194/amt-9-2647-2016, https://doi.org/10.5194/amt-9-2647-2016, 2016
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The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument is a remote sensing airborne instrument developed in support of future air quality satellite missions that will operate from geostationary orbit. GeoTASO flew in its first intensive field campaign during the DISCOVER-AQ 2013 Earth Venture Mission over Houston, Texas. This paper introduces the instrument and data analysis, and presents GeoTASO's first observations of NO2 at 250 m x 250 m spatial resolution.
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 ×.
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
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.
P. L. Hayes, A. G. Carlton, K. R. Baker, R. Ahmadov, R. A. Washenfelder, S. Alvarez, B. Rappenglück, J. B. Gilman, W. C. Kuster, J. A. de Gouw, P. Zotter, A. S. H. Prévôt, S. Szidat, T. E. Kleindienst, J. H. Offenberg, P. K. Ma, and J. L. Jimenez
Atmos. Chem. Phys., 15, 5773–5801, https://doi.org/10.5194/acp-15-5773-2015, https://doi.org/10.5194/acp-15-5773-2015, 2015
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(1) Four different parameterizations for the formation and chemical evolution of secondary organic aerosol (SOA) are evaluated using a box model representing the Los Angeles region during the CalNex campaign.
(2) The SOA formed only from the oxidation of VOCs is insufficient to explain the observed SOA concentrations.
(3) The amount of SOA mass formed from diesel vehicle emissions is estimated to be 16-27%.
(4) Modeled SOA depends strongly on the P-S/IVOC volatility distribution.
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.
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.
D. R. Gentner, T. B. Ford, A. Guha, K. Boulanger, J. Brioude, W. M. Angevine, J. A. de Gouw, C. Warneke, J. B. Gilman, T. B. Ryerson, J. Peischl, S. Meinardi, D. R. Blake, E. Atlas, W. A. Lonneman, T. E. Kleindienst, M. R. Beaver, J. M. St. Clair, P. O. Wennberg, T. C. VandenBoer, M. Z. Markovic, J. G. Murphy, R. A. Harley, and A. H. Goldstein
Atmos. Chem. Phys., 14, 4955–4978, https://doi.org/10.5194/acp-14-4955-2014, https://doi.org/10.5194/acp-14-4955-2014, 2014
S. E. Pusede, D. R. Gentner, P. J. Wooldridge, E. C. Browne, A. W. Rollins, K.-E. Min, A. R. Russell, J. Thomas, L. Zhang, W. H. Brune, S. B. Henry, J. P. DiGangi, F. N. Keutsch, S. A. Harrold, J. A. Thornton, M. R. Beaver, J. M. St. Clair, P. O. Wennberg, J. Sanders, X. Ren, T. C. VandenBoer, M. Z. Markovic, A. Guha, R. Weber, A. H. Goldstein, and R. C. Cohen
Atmos. Chem. Phys., 14, 3373–3395, https://doi.org/10.5194/acp-14-3373-2014, https://doi.org/10.5194/acp-14-3373-2014, 2014
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
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Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2815, https://doi.org/10.5194/egusphere-2024-2815, 2024
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate that effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense and consists well with radiative model calculations and can be applied to atmospheric models with speed requirements.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
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Short summary
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.
Biogenic volatile organic compounds (BVOCs) participate in reactions that can lead to...
