Articles | Volume 15, issue 22
https://doi.org/10.5194/gmd-15-8561-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-8561-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
23 Nov 2022
Development and technical paper |
| 23 Nov 2022
| 23 Nov 2022
Lightning assimilation in the WRF model (Version 4.1.1): technique updates and assessment of the applications from regional to hemispheric scales
Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Nicholas K. Heath
Air Quality and Atmospheric Composition, Atmospheric and Environmental Research, Lexington, MA 02421, USA
currently working as an independent consultant
Robert C. Gilliam
Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Tanya L. Spero
Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Jonathan E. Pleim
Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Related authors
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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).
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
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.
Ioannis Kioutsioukis, Christian Hogrefe, Paul A. Makar, Ummugulsun Alyuz, Jessy O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Buttler, Olivia E. Clifton, Philippe Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camaño, John Pleim, Young-Hee Ryu, Robero San Jose, Donna Schwede, Ranjeet Sokhi, and Stefano Galmarini
EGUsphere, https://doi.org/10.5194/egusphere-2025-1091, https://doi.org/10.5194/egusphere-2025-1091, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Deposition is a key in air quality modelling. An evaluation of the AQMEII4 models is performed prior to analysing the different deposition schemes in relation to the LULC used. Such analysis is unprecedented. Among the results, LULC masks have to be harmonised and up-to-date information used in place of outdated and too course masks. Alternatively LULC masks should be evaluated and intercom pared when multiple model results are analysed.
Sara L. Farrell, Havala O. T. Pye, Robert Gilliam, George Pouliot, Deanna Huff, Golam Sarwar, William Vizuete, Nicole Briggs, Fengkui Duan, Tao Ma, Shuping Zhang, and Kathleen Fahey
Atmos. Chem. Phys., 25, 3287–3312, https://doi.org/10.5194/acp-25-3287-2025, https://doi.org/10.5194/acp-25-3287-2025, 2025
Short summary
Short summary
In this work we implement heterogeneous sulfur chemistry into the Community Multiscale Air Quality (CMAQ) model. This new chemistry accounts for the formation of sulfate via aqueous oxidation of SO2 in aerosol liquid water and the formation of hydroxymethanesulfonate (HMS) – often confused by measurement techniques as sulfate. Model performance in predicting sulfur PM2.5 in Fairbanks, Alaska, and other places that experience dark and cold winters is improved.
Paul A. Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz, Jesse O. Bash, Michael D. Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E. Clifton, Alma Hodzic, Ioannis Kioutsioukis, 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 W. Shephard, Ranjeet S. Sokhi, and Stefano Galmarini
Atmos. Chem. Phys., 25, 3049–3107, https://doi.org/10.5194/acp-25-3049-2025, https://doi.org/10.5194/acp-25-3049-2025, 2025
Short summary
Short summary
The large range of sulfur 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 sulfur and nitrogen deposition variability. Controlling factors included the uptake of gases and aerosols by hydrometeors, aerosol inorganic chemistry, particle dry deposition, ammonia bidirectional fluxes, gas deposition via plant cuticles and soil, and land use data.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
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
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.
Natalie Brett, Kathy S. Law, Steve R. Arnold, Javier G. Fochesatto, Jean-Christophe Raut, Tatsuo Onishi, Robert Gilliam, Kathleen Fahey, Deanna Huff, George Pouliot, Brice Barret, Elsa Dieudonné, Roman Pohorsky, Julia Schmale, Andrea Baccarini, Slimane Bekki, Gianluca Pappaccogli, Federico Scoto, Stefano Decesari, Antonio Donateo, Meeta Cesler-Maloney, William Simpson, Patrice Medina, Barbara D'Anna, Brice Temime-Roussel, Joel Savarino, Sarah Albertin, Jingqiu Mao, Becky Alexander, Allison Moon, Peter F. DeCarlo, Vanessa Selimovic, Robert Yokelson, and Ellis S. Robinson
Atmos. Chem. Phys., 25, 1063–1104, https://doi.org/10.5194/acp-25-1063-2025, https://doi.org/10.5194/acp-25-1063-2025, 2025
Short summary
Short summary
Processes influencing dispersion of local anthropogenic pollution in Arctic wintertime are investigated with Lagrangian dispersion modelling. Simulated power plant plume rise that considers temperature inversion layers improves results compared to observations (interior Alaska). Modelled surface concentrations are improved by representation of vertical mixing and emission estimates. Large increases in diesel vehicle emissions at temperatures reaching −35°C are required to reproduce observed NOx.
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
Short summary
Short summary
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.
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
Short summary
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.
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.
Bryan K. Place, William T. Hutzell, K. Wyat Appel, Sara Farrell, Lukas Valin, Benjamin N. Murphy, Karl M. Seltzer, Golam Sarwar, Christine Allen, Ivan R. Piletic, Emma L. D'Ambro, Emily Saunders, Heather Simon, Ana Torres-Vasquez, Jonathan Pleim, Rebecca H. Schwantes, Matthew M. Coggon, Lu Xu, William R. Stockwell, and Havala O. T. Pye
Atmos. Chem. Phys., 23, 9173–9190, https://doi.org/10.5194/acp-23-9173-2023, https://doi.org/10.5194/acp-23-9173-2023, 2023
Short summary
Short summary
Ground-level ozone is a pollutant with adverse human health and ecosystem effects. Air quality models allow scientists to understand the chemical production of ozone and demonstrate impacts of air quality management plans. In this work, the role of multiple systems in ozone production was investigated for the northeastern US in summer. Model updates to chemical reaction rates and monoterpene chemistry were most influential in decreasing predicted ozone and improving agreement with observations.
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
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Preprint withdrawn
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
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
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
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
Related subject area
Atmospheric sciences
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
A Novel Method for Quantifying the Contribution of Regional Transport to PM2.5 in Beijing (2013–2020): Combining Machine Learning with Concentration-Weighted Trajectory Analysis
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Low-level jets in the North and Baltic Seas: Mesoscale Model Sensitivity and Climatology
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
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
Short summary
Short summary
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.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-157, https://doi.org/10.5194/gmd-2024-157, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study combines Machine Learning with Concentration-Weighted Trajectory Analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
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
Short summary
Short summary
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.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
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
Short summary
Short summary
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.
Cited articles
Abarca, S. F., Corbosiero, K. L., and Galarneau Jr., T. J.: An evaluation of the Worldwide Lightning Location Network (WWLLN) using the National Lightning Detection Network (NLDN) as ground truth, J. Geophys. Res., 115, D18206, https://doi.org/10.1029/2009JD013411, 2010.
Allen, D. J., Pickering, K. E., Pinder, R. W., Henderson, B. H., Appel, K. W., and Prados, A.: Impact of lightning-NO on eastern United States photochemistry during the summer of 2006 as determined using the CMAQ model, Atmos. Chem. Phys., 12, 1737–1758, https://doi.org/10.5194/acp-12-1737-2012, 2012.
Appel, K. W., Gilliam, R. C., Davis, N., Zubrow, A., and Howard, S. C.: Overview of the Atmospheric Model Evaluation Tool (AMET) v1.1 for evaluating meteorological and air quality models, Environ. Modell. Softw., 26, 434–443, https://doi.org/10.1016/j.envsoft.2010.09.007, 2011.
Appel, K. W., Bash, J. O., Fahey, K. M., Foley, K. M., Gilliam, R. C., Hogrefe, C., Hutzell, W. T., Kang, D., Mathur, R., Murphy, B. N., Napelenok, S. L., Nolte, C. G., Pleim, J. E., Pouliot, G. A., Pye, H. O. T., Ran, L., Roselle, S. J., Sarwar, G., Schwede, D. B., Sidi, F. I., Spero, T. L., and Wong, D. C.: The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation, Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, 2021.
Asong, Z. E., Razavi, S., Wheater, H. S., and Wong, J. S.: Evaluation of Integrated Multisatellite Retrievals for GPM (IMERG)over Southern Canada against Ground Precipitation Observations: A Preliminary Assessment, J. Hydrometeorol., 18, 1033–1050, https://doi.org/10.1175/JHM-D-16-0187.1, 2017.
Bruning, E. C., Weiss, S. A., and Calhoun, K. M.: Continuous variability in thunderstorm primary electrification and an evaluation of inverted-polarity terminology, Atmos. Res., 135–136, 274–284, https://doi.org/10.1016/j.atmosres.2012.10.009, 2014.
Burgesser, R. E.: Assessment of the World Wide Lightning Location Network (WWLLN) detection efficiency by comparison to the Lightning Imaging Sensor (LIS), Q. J. Roy. Meteor. Soc., 143, 2809–2817, https://doi.org/10.1002/qj.3129, 2017.
Fierro, A. O., Mansell, E. R., Ziegler, C. L., and MacGorman, D. R.: Application of a lightning data assimilation technique in the WRFARW model at cloud-resolving scales for the tornado outbreak of 24 May 2011, Mon. Weather Rev., 140, 2609–2627, 2012.
Fierro, A. O., Clark, A., Mansell, E. R., MacGorman, D. R., Dembek, S. R., and Ziegler, C. L.: Impact of storm-scale lightning data assimilation on WRF-ARW precipitation forecasts during the 2013 warm season over the contiguous United States, Mon. Weather Rev., 143, 757–777, 2015.
Finney, D. L., Doherty, R. M., Wild, O., Huntrieser, H., Pumphrey, H. C., and Blyth, A. M.: Using cloud ice flux to parametrise large-scale lightning, Atmos. Chem. Phys., 14, 12665–12682, https://doi.org/10.5194/acp-14-12665-2014, 2014.
Gan, R., Yang, Y., Xie, Q., Lin, E., Wang, Y., and Liu, P.: Assimilation of Radar and Cloud-to-Ground Lightning Data Using WRF-3DVar Combined with the Physical Initialization Method – A Case Study of a Mesoscale Convective System, J. Meteorol. Res.-PRC, 35, 329–342, https://doi.org/10.1007/s13351-021-0092-4, 2021.
Giannaros, T. M., Kotroni, V., and Lagouvardos, K.: WRF-LTNGDA: A lightning data assimilation technique implemented in the WRF model for improving precipitation forecasts, Environ. Modell. Softw., 76, 54–68, 2016.
Gilliam, R. C., Herwehe, J. A., Bullock, Jr., O. R., Pleim, J. E., Ran, L., Campbell, P. C., and Foroutan, H.: Establishing the suitability of the model for prediction across scales for global retrospective air quality modeling, J. Geophys. Res.-Atmos., 126, e2020JD033588, https://doi.org/10.1029/2020JD033588, 2021.
Glotfelty, T., Alapaty, K., He, J., Hawbecker, P., Song, X., and Zhang, G.: The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI): Development, evaluation, and initial application, Mon. Weather Rev., 147, 1491–1511, https://doi.org/10.1175/MWR-D-18-0267.1, 2019.
Goodman, S. J., Blakeslee, R. J., Koshak, W. J., Mach, D., Baiely, J., Buechler, D., Carey, L., Schultz, C., Bateman, M., McCaul Jr., E., and Stano G.: The GOES-R Geostationary Lightning Mapper (GLM), Atmos. Res., 125–126, 34–49, https://doi.org/10.1016/j.atmosres.2013.01.006, 2013.
Heath, N. K., Pleim, J. E., Gilliam, R. C., and Kang, D.: A simple lightning assimilation technique for improving retrospective WRF simulations, J. Adv. Model. Earth Sy., 8, 1806–1824, https://doi.org/10.1002/2016MS000735, 2016.
Hogrefe, C., Gilliam, R., Mathur, R., Henderson, B., Sarwar, G., Appel, K. W., Pouliot, G., Willison, J., Miller, R., Vukovich, J., Eyth, A., Talgo, K., Allen, C., and Foley, K.: CMAQv5.3.2 ozone simulations over the Northern Hemisphere: model performance and sensitivity to model configuration, 20th Annual CMAS Conference, 1–5 November 2021, Virtual, https://www.cmascenter.org/conference/2021/slides/hogrefe-cmaq5-3-2-ozone-2021.pdf (last access: 7 November 2022), 2021.
Huffman, G. J., Adler, R. F., and Nelkin, E. J.: Integrated Multi-satellitE Retrievalsfor GPM (IMERG) technical documentation, NASA/GSFC Code612 Tech. Doc., 48 pp., http://pmm.nasa.gov/sites/default/files/document_files/IMERG_doc.pdf (last access: 7 November 2022), 2015.
Kain, J. S.: The Kain-Fritsch convective parameterization: An update, J. Appl. Meteorol., 43, 170–181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Kain, J. S. and Fritsch, J. M.: A one-dimensional entraining/detraining plume model and its application in convective parameterization, J. Atmos. Sci., 47, 2784–2802, 1990.
Kain, J. S. and Fritsch, J. M.: Convective parameterization for mesoscale models: the Kain–Fritsch scheme, The Representation of Cumulus Convection in Numerical Models, Meteor. Mon., 46, 165–170, 1993.
Kang, D., Foley, K. M., Mathur, R., Roselle, S. J., Pickering, K. E., and Allen, D. J.: Simulating lightning NO production in CMAQv5.2: performance evaluations, Geosci. Model Dev., 12, 4409–4424, https://doi.org/10.5194/gmd-12-4409-2019, 2019a.
Kang, D., Pickering, K. E., Allen, D. J., Foley, K. M., Wong, D. C., Mathur, R., and Roselle, S. J.: Simulating lightning NO production in CMAQv5.2: evolution of scientific updates, Geosci. Model Dev., 12, 3071–3083, https://doi.org/10.5194/gmd-12-3071-2019, 2019b.
Kang, D., Mathur, R., Pouliot, G. A., Gilliam, R. C., and Wong, D. C.: Significant ground-level ozone attributed to lightning-induced nitrogen oxides during summertime over the Mountain West States, npj Climate and Atmospheric Science, 3, 6, https://doi.org/10.1038/s41612-020-0108-2, 2020.
Kang, D., Heath, N., Gilliam, R., Spero, T., and Pleim, J.: Lightning Assimilation in the Weather Research and Forecasting (WRF) Model: Technique Updates and Assessment of the Applications from Regional to Hemispheric Scales (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.6493145, 2022.
Lagouvardos, K., Kotroni, V., Defer, E., and Bousquet, O.: Study of a heavy precipitation event over southern France, in the frame of HYMEX project: Observational analysis and model results using assimilation of lightning, Atmos. Res., 134, 45–55, 2013.
Liu, Y., Warner, T. T., Bowers, J. F., Carson, L. P., Chen, F., Clough, C. A., Davis, C. A., Egeland, C. H., Halvorson, S. F., Huck Jr., T. W., Lachapelle, L., Malone, R. E., Rife, D. L., Sheu, R.-S., Swerdlin, S. P., and Weingarten, D. S.: The operational mesogamma-scale analysis and forecast system of the U. S. Army Test and Evaluation Command. Part 1: Overview of the modeling system, the forecast products, J. Appl. Meteorol. Clim., 47, 1077–1092, 2008.
Lopez, P.: A lightning parameterization for the ECMWF Integrated Forecasting System, Mon. Weather Rev., 144, 30573075, https://doi.org/10.1175/mwr-d-16-0026.1, 2016.
Ma, L.-M. and Tan, Z. M.: Improving the Behavior of the Cumulus Parameterization for Tropical Cyclone Prediction: Convection Trigger, Atmos. Res., 92, 190–211, https://doi.org/10.1016/j.atmosres.2008.09.022, 2009.
Mach, D. M., Christian, H. J., Blakeslee, R. J., Boccipio, D. J., Goodman, S. J., and Boeck, W. L.: Performance assessment of the Optical Transient Detector and Lightning Imaging Sensor, J. Geophys. Res., 112, D09210, https://doi.org/10.1029/2006JD007787, 2007.
Mansell, E. R., Ziegler, C. L., and MacGorman, D. R.: A lightning data assimilation technique for mesoscale forecast models, Mon. Weather Rev., 135, 1732–1748, https://doi.org/10.1175/MWR3387.1, 2007.
Marchand, M. R. and Fuelberg, H. E.: Assimilation of lightning data using a nudging method involving low-level warming, Mon. Weather Rev., 142, 4850–4871, https://doi.org/10.1175/MWR-D-14-00076.1, 2015.
Murphy, M. J., Cramer, J. A., and Said, R. K.: Recent history of upgrades to the U. S. National Detection Network, J. Atmos. Ocean. Tech., 38, 573–581, https://doi.org/10.1175/JTECH-D-19-0215.1, 2021.
Murphy, M. S. and Konrad II, C. E.: Spatial and temporal patterns of thunderstorm events that produce cloud-to-ground lightning in the interior southeastern United States, Mon. Weather Rev., 133, 1417–1420, 2005.
National Oceanic and Atmospheric Administration: CPC Global Unified Gauge-Based Analysis of Daily Precipitation, NOAA [data set], https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html, last access: 10 November 2022.
Preston, A. D. and Fuelberg, H. E.: Improving lightning cessation guidance using polarimetric radar data, Weather Forecast., 30, 308–328, https://doi.org/10.1175/WAF-D-14-00031.1, 2015.
Price, C. and Rind, D.: A simple lightning parameterization for calculating global lightning distributions, J. Geophys. Res.-Atmos., 97, 99199933, https://doi.org/10.1029/92jd00719, 1992.
Rogers, R. F., Fritsch, J. M., and Lambert, W. C.: A simple technique for using radar data in the dynamic initialization of a mesoscale model, Mon. Weather Rev., 128, 2560–2574, 2000.
Romps, D. M., Seeley, J. T., Vollaro, D., and Molinari, J.: Projected increase in lightning strikes in the United States due to global warming, Science, 346, 851854, https://doi.org/10.1126/science.1259100, 2014.
Rudlosky, S. D. and Shea, D. T.: Evaluation WWLLN performance relative to TRMM/LIS, Geophys. Res. Lett., 40, 2344–2348, https://doi.org/10.1002/grl.50428, 2013.
Sims, A. P., Alapaty, K., and Raman, S.: Sensitivities of Summertime Mesoscale Circulations in the Coastal Carolinas to Modifications of the Kain-Fritsch Cumulus Parameterization, Mon. Weather Rev., 145, 4381–4399, https://doi.org/10.1175/MWR-D-16-0047.1, 2017.
Skamarock, W. C. and Klemp, J. B.: A time-split nonhydrostatic atmospheric model, J. Comput. Phys., 227, 3465–3485, https://doi.org/10.1016/j.jcp.2007.01.037, 2008.
Stolzenburg, M. and Marshall, T. C.: Electric field and charge structure in lightning-producing clouds, in: Lightning: Principles, Instruments and Applications, edited by: Betz, H.-D., Schumann, U., and Laroche, P., Springer, 641 pp., https://doi.org/10.1007/978-1-4020-9079-0_3, 2009.
University Corporation for Atmospheric Research: WRFv4.1.1 (Version 4.1.1), GitHub [data set], https://github.com/wrf-model/WRF/tree/v4.1.1, last access: 10 November 2022a.
University Corporation for Atmospheric Research: PRISM High-Resolution Spatial Climate Data for the United States, University Corporation for Atmospheric Research [data set], https://climatedataguide.ucar.edu/climate-data/prism-high-resolution-spatial-climate-data-united-states-maxmin-temp-dewpoint, last access: 10 November 2022b.
University of Washington: Lightning flash data from the World Lightning Location Network, University of Washington [data set], http://wwlln.net, last access: 10 November 2022.
U. S. EPA: Meteorological Model Performance for Annual 2016 Simulation WRF v3.8, EPA-454/R-19-010, https://www.epa.gov/sites/default/files/2020-10/documents/met_model_performance-2016_wrf.pdf (last access: 7 November 2022), 2019.
Vaisala Inc.: The lightning flashes data from National Lightning Detection Network, Vaisala Inc. [data set], https://www.vaisala.com/en/products/systems/lightning-detection, last access: 10 November 2022.
Zheng, Y., Alapaty, K., Herwehe, J. A., Del Genio, A. D., and Niyogi, D.: Improving high-resolution weather forecasts using the Weather Research and Forecasting (WRF) Model with an updated Kain–Fritsch scheme, Mon. Weather Rev., 144, 833–860, https://doi.org/10.1175/MWR-D-15-0005.1, 2016.
Short summary
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.
A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF)...
