Articles | Volume 14, issue 11
https://doi.org/10.5194/gmd-14-7189-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-7189-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
26 Nov 2021
Model evaluation paper |
| 26 Nov 2021
| 26 Nov 2021
A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality
Kai Wang
Department of Civil and Environmental Engineering, Northeastern
University, Boston, MA 02115, USA
Yang Zhang
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Northeastern
University, Boston, MA 02115, USA
Key Laboratory of Environmental Remediation and Ecological Health,
Ministry of Education; Research Center for Air Pollution and Health, College
of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
David C. Wong
Center for Environmental Measurement and Modeling, U.S. EPA, Research Triangle Park, NC 27711, USA
Jonathan Pleim
Center for Environmental Measurement and Modeling, U.S. EPA, Research Triangle Park, NC 27711, USA
Rohit Mathur
Center for Environmental Measurement and Modeling, U.S. EPA, Research Triangle Park, NC 27711, USA
James T. Kelly
Office of Air Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC 27711, USA
Michelle Bell
School of Forestry & Environmental Studies, Yale University, New
Haven, CT 06511, USA
Related authors
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.
Junxi Zhang, Yang Gao, Kun Luo, L. Ruby Leung, Yang Zhang, Kai Wang, and Jianren Fan
Atmos. Chem. Phys., 18, 9861–9877, https://doi.org/10.5194/acp-18-9861-2018, https://doi.org/10.5194/acp-18-9861-2018, 2018
Short summary
Short summary
We used a regional model to investigate the impact of atmosphere with high temperature and low wind speed on ozone concentration. When these compound events (heat waves and stagnant weather) occur simultaneously, a striking ozone enhancement is revealed. This type of compound event is projected to increase more dominantly compared to single events in the future over the US, Europe, and China, implying the importance of reducing emissions in order to alleviate the impact from the compound events.
Khairunnisa Yahya, Timothy Glotfelty, Kai Wang, Yang Zhang, and Athanasios Nenes
Geosci. Model Dev., 10, 2333–2363, https://doi.org/10.5194/gmd-10-2333-2017, https://doi.org/10.5194/gmd-10-2333-2017, 2017
Khairunnisa Yahya, Kai Wang, Patrick Campbell, Timothy Glotfelty, Jian He, and Yang Zhang
Geosci. Model Dev., 9, 671–695, https://doi.org/10.5194/gmd-9-671-2016, https://doi.org/10.5194/gmd-9-671-2016, 2016
Short summary
Short summary
The Weather Research and Forecasting model with Chemistry (WRF/Chem) v3.6.1 is evaluated for its first decadal application during 2001 to 2010 using the Representative Concentration Pathway 8.5 emissions. The model evaluation shows acceptable performance for long-term climatological simulations of most meteorological variables and chemical concentrations. Larger biases exist for aerosol-cloud-radiation variables, which future model improvement should focus on.
K. Yahya, K. Wang, Y. Zhang, and T. E. Kleindienst
Geosci. Model Dev., 8, 2095–2117, https://doi.org/10.5194/gmd-8-2095-2015, https://doi.org/10.5194/gmd-8-2095-2015, 2015
Short summary
Short summary
The application of WRF/Chem to North America shows that it can reproduce most observations and their variation trends from 2006 to 2010. The inclusion of chemical feedbacks reduces biases in meteorological predictions in 2010 but increases errors in comparison to WRF. The net changes in meteorology from 2006 to 2010 are mostly influenced by changes in meteorology and those of ozone and fine particles are influenced by changes in emissions and chemical BCONs, and to a lesser extent meteorology.
B. Zheng, Q. Zhang, Y. Zhang, K. B. He, K. Wang, G. J. Zheng, F. K. Duan, Y. L. Ma, and T. Kimoto
Atmos. Chem. Phys., 15, 2031–2049, https://doi.org/10.5194/acp-15-2031-2015, https://doi.org/10.5194/acp-15-2031-2015, 2015
Y. Zhang, K. Sartelet, S. Zhu, W. Wang, S.-Y. Wu, X. Zhang, K. Wang, P. Tran, C. Seigneur, and Z.-F. Wang
Atmos. Chem. Phys., 13, 6845–6875, https://doi.org/10.5194/acp-13-6845-2013, https://doi.org/10.5194/acp-13-6845-2013, 2013
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.
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.
Yuzhi Jin, Jiandong Wang, Chao Liu, David C. Wong, Golam Sarwar, Kathleen M. Fahey, Shang Wu, Jiaping Wang, Jing Cai, Zeyuan Tian, Zhouyang Zhang, Jia Xing, Aijun Ding, and Shuxiao Wang
Atmos. Chem. Phys., 25, 2613–2630, https://doi.org/10.5194/acp-25-2613-2025, https://doi.org/10.5194/acp-25-2613-2025, 2025
Short summary
Short summary
Black carbon (BC) affects climate and the environment, and its aging process alters its properties. Current models, like WRF-CMAQ, lack full accounting for it. We developed the WRF-CMAQ-BCG model to better represent BC aging by introducing bare and coated BC species and their conversion. The WRF-CMAQ-BCG model introduces the capability to simulate BC mixing states and bare and coated BC wet deposition, and it improves the accuracy of BC mass concentration and aerosol optics.
Zhe Song, Shaocai Yu, Pengfei Li, Ningning Yao, Lang Chen, Yuhai Sun, Boqiong Jiang, and Daniel Rosenfeld
Atmos. Chem. Phys., 25, 2473–2494, https://doi.org/10.5194/acp-25-2473-2025, https://doi.org/10.5194/acp-25-2473-2025, 2025
Short summary
Short summary
Our results with injected sea salt aerosols for five open oceans show that sea salt aerosols with low injection amounts dominate shortwave radiation, mainly through indirect effects. As indirect aerosol effects saturate with increasing injection rates, direct effects exceed indirect effects. This implies that marine cloud brightening is best implemented in areas with extensive cloud cover, while aerosol direct scattering effects remain dominant when clouds are scarce.
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.
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.
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.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
Short summary
We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Xu Feng, Loretta J. Mickley, Michelle L. Bell, Tianjia Liu, Jenny A. Fisher, and Maria Val Martin
Atmos. Chem. Phys., 24, 2985–3007, https://doi.org/10.5194/acp-24-2985-2024, https://doi.org/10.5194/acp-24-2985-2024, 2024
Short summary
Short summary
During severe wildfire seasons, smoke can have a significant impact on air quality in Australia. Our study demonstrates that characterization of the smoke plume injection fractions greatly affects estimates of surface smoke PM2.5. Using the plume behavior predicted by the machine learning method leads to the best model agreement with observed surface PM2.5 in key cities across Australia, with smoke PM2.5 accounting for 5 %–52 % of total PM2.5 on average during fire seasons from 2009 to 2020.
Calvin Howes, Pablo E. Saide, Hugh Coe, Amie Dobracki, Steffen Freitag, Jim M. Haywood, Steven G. Howell, Siddhant Gupta, Janek Uin, Mary Kacarab, Chongai Kuang, L. Ruby Leung, Athanasios Nenes, Greg M. McFarquhar, James Podolske, Jens Redemann, Arthur J. Sedlacek, Kenneth L. Thornhill, Jenny P. S. Wong, Robert Wood, Huihui Wu, Yang Zhang, Jianhao Zhang, and Paquita Zuidema
Atmos. Chem. Phys., 23, 13911–13940, https://doi.org/10.5194/acp-23-13911-2023, https://doi.org/10.5194/acp-23-13911-2023, 2023
Short summary
Short summary
To better understand smoke properties and its interactions with clouds, we compare the WRF-CAM5 model with observations from ORACLES, CLARIFY, and LASIC field campaigns in the southeastern Atlantic in August 2017. The model transports and mixes smoke well but does not fully capture some important processes. These include smoke chemical and physical aging over 4–12 days, smoke removal by rain, sulfate particle formation, aerosol activation into cloud droplets, and boundary layer turbulence.
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.
Yuchen Wang, Xvli Guo, Yajie Huo, Mengying Li, Yuqing Pan, Shaocai Yu, Alexander Baklanov, Daniel Rosenfeld, John H. Seinfeld, and Pengfei Li
Atmos. Chem. Phys., 23, 5233–5249, https://doi.org/10.5194/acp-23-5233-2023, https://doi.org/10.5194/acp-23-5233-2023, 2023
Short summary
Short summary
Substantial advances have been made in recent years toward detecting and quantifying methane super-emitters from space. However, such advances have rarely been expanded to measure the global methane pledge because large-scale swaths and high-resolution sampling have not been coordinated. Here we present a versatile spaceborne architecture that can juggle planet-scale and plant-level methane retrievals, challenge official emission reports, and remain relevant for stereoscopic measurements.
Michael S. Walters and David C. Wong
Geosci. Model Dev., 16, 1179–1190, https://doi.org/10.5194/gmd-16-1179-2023, https://doi.org/10.5194/gmd-16-1179-2023, 2023
Short summary
Short summary
A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.
Chandan Sarangi, Yun Qian, L. Ruby Leung, Yang Zhang, Yufei Zou, and Yuhang Wang
Atmos. Chem. Phys., 23, 1769–1783, https://doi.org/10.5194/acp-23-1769-2023, https://doi.org/10.5194/acp-23-1769-2023, 2023
Short summary
Short summary
We show that for air quality, the densely populated eastern US may see even larger impacts of wildfires due to long-distance smoke transport and associated positive climatic impacts, partially compensating the improvements from regulations on anthropogenic emissions. This study highlights the tension between natural and anthropogenic contributions and the non-local nature of air pollution that complicate regulatory strategies for improving future regional air quality for human health.
Daiwen Kang, Nicholas K. Heath, Robert C. Gilliam, Tanya L. Spero, and Jonathan E. Pleim
Geosci. Model Dev., 15, 8561–8579, https://doi.org/10.5194/gmd-15-8561-2022, https://doi.org/10.5194/gmd-15-8561-2022, 2022
Short summary
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.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
Short summary
Short summary
This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
Short summary
Short summary
This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Fanlei Meng, Yibo Zhang, Jiahui Kang, Mathew R. Heal, Stefan Reis, Mengru Wang, Lei Liu, Kai Wang, Shaocai Yu, Pengfei Li, Jing Wei, Yong Hou, Ying Zhang, Xuejun Liu, Zhenling Cui, Wen Xu, and Fusuo Zhang
Atmos. Chem. Phys., 22, 6291–6308, https://doi.org/10.5194/acp-22-6291-2022, https://doi.org/10.5194/acp-22-6291-2022, 2022
Short summary
Short summary
PM2.5 pollution is a pressing environmental issue threatening human health and food security globally. We combined a meta-analysis of nationwide measurements and air quality modeling to identify efficiency gains by striking a balance between controlling NH3 and acid gas emissions. Persistent secondary inorganic aerosol pollution in China is limited by acid gas emissions, while an additional control on NH3 emissions would become more important as reductions in SO2 and NOx emissions progress.
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.
Sally S.-C. Wang, Yun Qian, L. Ruby Leung, and Yang Zhang
Atmos. Chem. Phys., 22, 3445–3468, https://doi.org/10.5194/acp-22-3445-2022, https://doi.org/10.5194/acp-22-3445-2022, 2022
Short summary
Short summary
This study develops an interpretable machine learning (ML) model predicting monthly PM2.5 fire emission over the contiguous US at 0.25° resolution and compares the prediction skills of the ML and process-based models. The comparison facilitates attributions of model biases and better understanding of the strengths and uncertainties in the two types of models at regional scales, for informing future model development and their applications in fire emission projection.
Amir H. Souri, Kelly Chance, Juseon Bak, Caroline R. Nowlan, Gonzalo González Abad, Yeonjin Jung, David C. Wong, Jingqiu Mao, and Xiong Liu
Atmos. Chem. Phys., 21, 18227–18245, https://doi.org/10.5194/acp-21-18227-2021, https://doi.org/10.5194/acp-21-18227-2021, 2021
Short summary
Short summary
The global pandemic is believed to have an impact on emissions of air pollutants such as nitrogen dioxide (NO2) and formaldehyde (HCHO). This study quantifies the changes in the amount of NOx and VOC emissions via state-of-the-art inverse modeling technique using satellite observations during the lockdown 2020 with respect to a baseline over Europe, which in turn, it permits unraveling atmospheric processes being responsible for ozone formation in a less cloudy month.
Ruili Wu, Christopher W. Tessum, Yang Zhang, Chaopeng Hong, Yixuan Zheng, Xinyin Qin, Shigan Liu, and Qiang Zhang
Geosci. Model Dev., 14, 7621–7638, https://doi.org/10.5194/gmd-14-7621-2021, https://doi.org/10.5194/gmd-14-7621-2021, 2021
Short summary
Short summary
Reduced-complexity air quality models are less computationally intensive and easier to use. We developed a reduced-complexity air quality Intervention Model for Air Pollution over China (InMAP-China) to rapidly predict the air quality and estimate the health impacts of emission sources in China. We believe that this work will be of great interest to a broad audience, including environmentalists in China and scientists in relevant fields at both national and local institutes.
Linhui Jiang, Yan Xia, Lu Wang, Xue Chen, Jianjie Ye, Tangyan Hou, Liqiang Wang, Yibo Zhang, Mengying Li, Zhen Li, Zhe Song, Yaping Jiang, Weiping Liu, Pengfei Li, Daniel Rosenfeld, John H. Seinfeld, and Shaocai Yu
Atmos. Chem. Phys., 21, 16985–17002, https://doi.org/10.5194/acp-21-16985-2021, https://doi.org/10.5194/acp-21-16985-2021, 2021
Short summary
Short summary
This paper establishes a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current inventories. The results show that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74 kg, 40 kg, 8 kg, and 2 kg, respectively. Integrating our traffic-monitoring-based approach with urban measurements, we could address major data gaps between urban air pollutant emissions and concentrations.
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.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Geosci. Model Dev., 14, 5751–5768, https://doi.org/10.5194/gmd-14-5751-2021, https://doi.org/10.5194/gmd-14-5751-2021, 2021
Short summary
Short summary
The Community Multiscale Air Quality (CMAQ) modeling system extended for hemispheric-scale applications (H-CMAQ) incorporated the satellite-constrained degassing SO2 emissions from 50 volcanos across the Northern Hemisphere. The impact on tropospheric sulfate aerosol (SO42−) is assessed for 2010. Although the considered volcanic emissions occurred at or below the middle of free troposphere (500 hPa), SO42− enhancements of more than 10 % were detected up to the top of free troposphere (250 hPa).
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.
Mario Eduardo Gavidia-Calderón, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade
Geosci. Model Dev., 14, 3251–3268, https://doi.org/10.5194/gmd-14-3251-2021, https://doi.org/10.5194/gmd-14-3251-2021, 2021
Short summary
Short summary
The MUNICH model was used to calculate pollutant concentrations inside the streets of São Paulo. The VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the street rooftops. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.
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.
Liqiang Wang, Shaocai Yu, Pengfei Li, Xue Chen, Zhen Li, Yibo Zhang, Mengying Li, Khalid Mehmood, Weiping Liu, Tianfeng Chai, Yannian Zhu, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 20, 14787–14800, https://doi.org/10.5194/acp-20-14787-2020, https://doi.org/10.5194/acp-20-14787-2020, 2020
Short summary
Short summary
The Chinese government has made major strides in curbing anthropogenic emissions. In this study, we constrain a state-of-the-art CTM by a reliable data assimilation method with extensive chemical and meteorological observations. This comprehensive technical design provides a crucial advance in isolating the influences of emission changes and meteorological perturbations over the Yangtze River Delta (YRD) from 2016 to 2019, thus establishing the first map of the PM2.5 mitigation across the YRD.
Huiying Luo, Marina Astitha, Christian Hogrefe, Rohit Mathur, and S. Trivikrama Rao
Atmos. Chem. Phys., 20, 13801–13815, https://doi.org/10.5194/acp-20-13801-2020, https://doi.org/10.5194/acp-20-13801-2020, 2020
Short summary
Short summary
A new method is introduced to evaluate nonlinear, nonstationary modeled PM2.5 time series by decomposing decadal PM2.5 concentrations and its species onto various timescales. It does not require preselection of temporal scales and assumptions of linearity and stationarity. It provides a unique opportunity to assess the influence of each species on total PM2.5. The results reveal a phase shift in modeled EC/OC concentrations, indicating the need for improved model treatment of organic aerosols.
Yohei Shinozuka, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon, Karla Longo, Marc Mallet, Yan Feng, Qiaoqiao Wang, Yafang Cheng, Amie Dobracki, Steffen Freitag, Steven G. Howell, Samuel LeBlanc, Connor Flynn, Michal Segal-Rosenhaimer, Kristina Pistone, James R. Podolske, Eric J. Stith, Joseph Ryan Bennett, Gregory R. Carmichael, Arlindo da Silva, Ravi Govindaraju, Ruby Leung, Yang Zhang, Leonhard Pfister, Ju-Mee Ryoo, Jens Redemann, Robert Wood, and Paquita Zuidema
Atmos. Chem. Phys., 20, 11491–11526, https://doi.org/10.5194/acp-20-11491-2020, https://doi.org/10.5194/acp-20-11491-2020, 2020
Short summary
Short summary
In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016.
Havala O. T. Pye, Athanasios Nenes, Becky Alexander, Andrew P. Ault, Mary C. Barth, Simon L. Clegg, Jeffrey L. Collett Jr., Kathleen M. Fahey, Christopher J. Hennigan, Hartmut Herrmann, Maria Kanakidou, James T. Kelly, I-Ting Ku, V. Faye McNeill, Nicole Riemer, Thomas Schaefer, Guoliang Shi, Andreas Tilgner, John T. Walker, Tao Wang, Rodney Weber, Jia Xing, Rahul A. Zaveri, and Andreas Zuend
Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, https://doi.org/10.5194/acp-20-4809-2020, 2020
Short summary
Short summary
Acid rain is recognized for its impacts on human health and ecosystems, and programs to mitigate these effects have had implications for atmospheric acidity. Historical measurements indicate that cloud and fog droplet acidity has changed in recent decades in response to controls on emissions from human activity, while the limited trend data for suspended particles indicate acidity may be relatively constant. This review synthesizes knowledge on the acidity of atmospheric particles and clouds.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, and Yang Zhang
Atmos. Chem. Phys., 20, 3373–3396, https://doi.org/10.5194/acp-20-3373-2020, https://doi.org/10.5194/acp-20-3373-2020, 2020
Short summary
Short summary
The state-of-the-science Community Multiscale Air Quality model extended for hemispheric applications (H-CMAQ) is used to model the trans-Pacific transport which has been recognized as a potential source of air pollutants over the US. In Part 1, modeled ozone is evaluated with observations at surface, by ozonesonde and airplane, and by satellite across the Northern Hemisphere. In addition, a newly developed air mass characterization method to estimate stratospheric intrusion is presented.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Atmos. Chem. Phys., 20, 3397–3413, https://doi.org/10.5194/acp-20-3397-2020, https://doi.org/10.5194/acp-20-3397-2020, 2020
Short summary
Short summary
The state-of-the-science Community Multiscale Air Quality model extended for hemispheric applications (H-CMAQ) is used to model the trans-Pacific transport which has been recognized as a potential source of air pollutants over the US. In Part 2, the higher-order decoupled direct method (HDDM) is applied to investigate the emission impacts from east Asia and the US during April 2010. Furthermore, changes in trans-Pacific transport caused by the recent emissions are examined.
Khalid Mehmood, Yujie Wu, Liqiang Wang, Shaocai Yu, Pengfei Li, Xue Chen, Zhen Li, Yibo Zhang, Mengying Li, Weiping Liu, Yuesi Wang, Zirui Liu, Yannian Zhu, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 20, 2419–2443, https://doi.org/10.5194/acp-20-2419-2020, https://doi.org/10.5194/acp-20-2419-2020, 2020
Short summary
Short summary
We selected June 2014 as our study period, which exhibited a complete evolution process of open biomass burning (OBB) dominated by open crop straw burning (OCSB) over central and eastern China (CEC). We established a constraining method that integrates ground-based PM2.5 measurements with the two-way coupled WRF-CMAQ model to derive optimal OBB emissions. It was found that these emissions could allow the model to reproduce meteorological and chemical fields over CEC during the study period.
S. Trivikrama Rao, Huiying Luo, Marina Astitha, Christian Hogrefe, Valerie Garcia, and Rohit Mathur
Atmos. Chem. Phys., 20, 1627–1639, https://doi.org/10.5194/acp-20-1627-2020, https://doi.org/10.5194/acp-20-1627-2020, 2020
Short summary
Short summary
Since numerical air quality models do not explicitly simulate stochastic variations in the atmosphere, there will always be differences between modeled and measured pollutant levels even when the model's physics, chemistry, numerical analysis, and its input data are perfect. This paper quantifies the inherent uncertainty in regional models due to the stochastic nature of the atmosphere. A knowledge of the expected error helps model developers in evaluating the real progress in improving models.
Jia Xing, Dian Ding, Shuxiao Wang, Zhaoxin Dong, James T. Kelly, Carey Jang, Yun Zhu, and Jiming Hao
Atmos. Chem. Phys., 19, 13627–13646, https://doi.org/10.5194/acp-19-13627-2019, https://doi.org/10.5194/acp-19-13627-2019, 2019
Short summary
Short summary
The study aims at addressing the challenge in efficient quantification of the nonlinear response of air pollution to precursor emission perturbations. The newly developed observable response indicators can be easily calculated by a combination of ambient concentrations of certain species. Their capability in representing the spatial and temporal variation in PM2.5 and O3 chemistry has also been well evaluated and applied in China.
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.
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.
Junxi Zhang, Yang Gao, Kun Luo, L. Ruby Leung, Yang Zhang, Kai Wang, and Jianren Fan
Atmos. Chem. Phys., 18, 9861–9877, https://doi.org/10.5194/acp-18-9861-2018, https://doi.org/10.5194/acp-18-9861-2018, 2018
Short summary
Short summary
We used a regional model to investigate the impact of atmosphere with high temperature and low wind speed on ozone concentration. When these compound events (heat waves and stagnant weather) occur simultaneously, a striking ozone enhancement is revealed. This type of compound event is projected to increase more dominantly compared to single events in the future over the US, Europe, and China, implying the importance of reducing emissions in order to alleviate the impact from the compound events.
Yuqiang Zhang, Rohit Mathur, Jesse O. Bash, Christian Hogrefe, Jia Xing, and Shawn J. Roselle
Atmos. Chem. Phys., 18, 9091–9106, https://doi.org/10.5194/acp-18-9091-2018, https://doi.org/10.5194/acp-18-9091-2018, 2018
Short summary
Short summary
For this study, we evaluated the WRF–CMAQ coupled model's ability to simulate the long-term trends of wet deposition of nitrogen and sulfur from 1990 to 2010 by comparing the model results with long-term observation datasets in the US. The model generally underestimates the wet deposition of both nitrogen and sulfur but captured well the decreasing trends for the deposition. Then we estimated the deposition budget in the US, including wet deposition and dry deposition from model simulations.
Stefano Galmarini, Ioannis Kioutsioukis, Efisio Solazzo, Ummugulsum Alyuz, Alessandra Balzarini, Roberto Bellasio, Anna M. K. Benedictow, Roberto Bianconi, Johannes Bieser, Joergen Brandt, Jesper H. Christensen, Augustin Colette, Gabriele Curci, Yanko Davila, Xinyi Dong, Johannes Flemming, Xavier Francis, Andrea Fraser, Joshua Fu, Daven K. Henze, Christian Hogrefe, Ulas Im, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Jan Eiof Jonson, Nutthida Kitwiroon, Astrid Manders, Rohit Mathur, Laura Palacios-Peña, Guido Pirovano, Luca Pozzoli, Marie Prank, Martin Schultz, Rajeet S. Sokhi, Kengo Sudo, Paolo Tuccella, Toshihiko Takemura, Takashi Sekiya, and Alper Unal
Atmos. Chem. Phys., 18, 8727–8744, https://doi.org/10.5194/acp-18-8727-2018, https://doi.org/10.5194/acp-18-8727-2018, 2018
Short summary
Short summary
An ensemble of model results relating to ozone concentrations in Europe in 2010 has been produced and studied. The novelty consists in the fact that the ensemble is made of results of models working at two different scales (regional and global), therefore contributing in detail two different parts of the atmospheric spectrum. The ensemble defined as a hybrid has been studied in detail and shown to bring additional value to the assessment of air quality.
Christian Hogrefe, Peng Liu, George Pouliot, Rohit Mathur, Shawn Roselle, Johannes Flemming, Meiyun Lin, and Rokjin J. Park
Atmos. Chem. Phys., 18, 3839–3864, https://doi.org/10.5194/acp-18-3839-2018, https://doi.org/10.5194/acp-18-3839-2018, 2018
Short summary
Short summary
This study quantifies the impacts of different representations of background ozone in state-of-the-science large-scale models on surface and aloft ozone burdens simulated by the CMAQ regional model over the United States. It also compares both the CMAQ simulations and the driving large-scale models to surface and upper air observations.
Jingqiu Mao, Annmarie Carlton, Ronald C. Cohen, William H. Brune, Steven S. Brown, Glenn M. Wolfe, Jose L. Jimenez, Havala O. T. Pye, Nga Lee Ng, Lu Xu, V. Faye McNeill, Kostas Tsigaridis, Brian C. McDonald, Carsten Warneke, Alex Guenther, Matthew J. Alvarado, Joost de Gouw, Loretta J. Mickley, Eric M. Leibensperger, Rohit Mathur, Christopher G. Nolte, Robert W. Portmann, Nadine Unger, Mika Tosca, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 2615–2651, https://doi.org/10.5194/acp-18-2615-2018, https://doi.org/10.5194/acp-18-2615-2018, 2018
Short summary
Short summary
This paper is aimed at discussing progress in evaluating, diagnosing, and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models.
Kai Duan, Ge Sun, Steven G. McNulty, Peter V. Caldwell, Erika C. Cohen, Shanlei Sun, Heather D. Aldridge, Decheng Zhou, Liangxia Zhang, and Yang Zhang
Hydrol. Earth Syst. Sci., 21, 5517–5529, https://doi.org/10.5194/hess-21-5517-2017, https://doi.org/10.5194/hess-21-5517-2017, 2017
Short summary
Short summary
We examined the potential roles of major climatic variables (including precipitation, air temperature, solar radiation, specific humidity, and wind speed) in altering annual runoff, which is an important indicator of freshwater supply, in the United States through the 21st century. Increasing temperature, precipitation, and humidity are recognized as three major climatic factors that drive runoff to change in different directions across the country.
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.
Chaopeng Hong, Qiang Zhang, Yang Zhang, Youhua Tang, Daniel Tong, and Kebin He
Geosci. Model Dev., 10, 2447–2470, https://doi.org/10.5194/gmd-10-2447-2017, https://doi.org/10.5194/gmd-10-2447-2017, 2017
Short summary
Short summary
A regional coupled climate–chemistry modeling system using the dynamical downscaling technique was established and evaluated. The modeling system performed well for both the climatological and the short-term air quality applications over east Asia. Regional models outperformed global models in regional climate and air quality predictions. The coupled modeling system improved the model performance, although some biases remained in the aerosol–cloud–radiation variables.
Khairunnisa Yahya, Timothy Glotfelty, Kai Wang, Yang Zhang, and Athanasios Nenes
Geosci. Model Dev., 10, 2333–2363, https://doi.org/10.5194/gmd-10-2333-2017, https://doi.org/10.5194/gmd-10-2333-2017, 2017
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.
Provat K. Saha, Andrey Khlystov, Khairunnisa Yahya, Yang Zhang, Lu Xu, Nga L. Ng, and Andrew P. Grieshop
Atmos. Chem. Phys., 17, 501–520, https://doi.org/10.5194/acp-17-501-2017, https://doi.org/10.5194/acp-17-501-2017, 2017
Kai Duan, Ge Sun, Steven G. McNulty, Peter V. Caldwell, Erika C. Cohen, Shanlei Sun, Heather D. Aldridge, Decheng Zhou, Liangxia Zhang, and Yang Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-493, https://doi.org/10.5194/hess-2016-493, 2016
Revised manuscript not accepted
Short summary
Short summary
This study examines the potential shift of the relative roles of changing precipitation and temperature in controlling freshwater availability in the USA. The influence of temperature is projected to outweigh that of precipitation in a continued warming future in the 21st century, although precipitation has been the primary control in recent decades. The vast croplands and grasslands across the central and forests in the northwestern regions might be particularly vulnerable to climate change.
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.
Shanlei Sun, Ge Sun, Erika Cohen, Steven G. McNulty, Peter V. Caldwell, Kai Duan, and Yang Zhang
Hydrol. Earth Syst. Sci., 20, 935–952, https://doi.org/10.5194/hess-20-935-2016, https://doi.org/10.5194/hess-20-935-2016, 2016
Short summary
Short summary
This study links an ecohydrological model with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. Water yield and ecosystem productivity response to climate change were highly variable with an increasing trend across the 82 773 watersheds. Results are useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources.
Khairunnisa Yahya, Kai Wang, Patrick Campbell, Timothy Glotfelty, Jian He, and Yang Zhang
Geosci. Model Dev., 9, 671–695, https://doi.org/10.5194/gmd-9-671-2016, https://doi.org/10.5194/gmd-9-671-2016, 2016
Short summary
Short summary
The Weather Research and Forecasting model with Chemistry (WRF/Chem) v3.6.1 is evaluated for its first decadal application during 2001 to 2010 using the Representative Concentration Pathway 8.5 emissions. The model evaluation shows acceptable performance for long-term climatological simulations of most meteorological variables and chemical concentrations. Larger biases exist for aerosol-cloud-radiation variables, which future model improvement should focus on.
J. He, Y. Zhang, S. Tilmes, L. Emmons, J.-F. Lamarque, T. Glotfelty, A. Hodzic, and F. Vitt
Geosci. Model Dev., 8, 3999–4025, https://doi.org/10.5194/gmd-8-3999-2015, https://doi.org/10.5194/gmd-8-3999-2015, 2015
Short summary
Short summary
The global simulations with CB05_GE and MOZART-4x predict similar chemical profiles for major gases compared to aircraft measurements, with better agreement for the NOy profile by CB05_GE. The SOA concentrations of SOA at four sites in CONUS and organic carbon over the IMPROVE sites are better predicted by MOZART-4x. The two simulations result in a global average difference of 0.5W m-2 in simulated shortwave cloud radiative forcing, with up to 13.6W m-2 over subtropical regions.
B. Gantt, J. T. Kelly, and J. O. Bash
Geosci. Model Dev., 8, 3733–3746, https://doi.org/10.5194/gmd-8-3733-2015, https://doi.org/10.5194/gmd-8-3733-2015, 2015
J. He, R. He, and Y. Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-8-9965-2015, https://doi.org/10.5194/gmdd-8-9965-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
WRF/Chem simulations are performed to understand the impacts of cumulus parameterizations and air-sea interactions on coastal air quality. The use of different cumulus parameterizations gives different vertical mixing and wet scavenging. The use of different air-sea interaction treatments also gives different predictions of O3 and PM2.5 by up to 17.3 ppb and 7.9 μg m-3, respectively. WRF/Chem-ROMS improves model predictions, illustrating the benefits and needs of using coupled atmospheric-ocean
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.
C. G. Nolte, K. W. Appel, J. T. Kelly, P. V. Bhave, K. M. Fahey, J. L. Collett Jr., L. Zhang, and J. O. Young
Geosci. Model Dev., 8, 2877–2892, https://doi.org/10.5194/gmd-8-2877-2015, https://doi.org/10.5194/gmd-8-2877-2015, 2015
Short summary
Short summary
This study is the most comprehensive evaluation of CMAQ inorganic
aerosol size-composition distributions conducted to date. We compare two
methods of inferring PM2.5 concentrations from the model: (1) based on
the sum of the masses in the fine aerosol modes, as is most commonly
done in CMAQ model evaluation; and (2) computed using the simulated size
distributions. Differences are generally less than 1 microgram/m3, and
are largest over the eastern USA during the summer.
J. Xing, R. Mathur, J. Pleim, C. Hogrefe, C.-M. Gan, D. C. Wong, and C. Wei
Atmos. Chem. Phys., 15, 9997–10018, https://doi.org/10.5194/acp-15-9997-2015, https://doi.org/10.5194/acp-15-9997-2015, 2015
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.
K. Yahya, K. Wang, Y. Zhang, and T. E. Kleindienst
Geosci. Model Dev., 8, 2095–2117, https://doi.org/10.5194/gmd-8-2095-2015, https://doi.org/10.5194/gmd-8-2095-2015, 2015
Short summary
Short summary
The application of WRF/Chem to North America shows that it can reproduce most observations and their variation trends from 2006 to 2010. The inclusion of chemical feedbacks reduces biases in meteorological predictions in 2010 but increases errors in comparison to WRF. The net changes in meteorology from 2006 to 2010 are mostly influenced by changes in meteorology and those of ozone and fine particles are influenced by changes in emissions and chemical BCONs, and to a lesser extent meteorology.
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.
K. R. Baker, A. G. Carlton, T. E. Kleindienst, J. H. Offenberg, M. R. Beaver, D. R. Gentner, A. H. Goldstein, P. L. Hayes, J. L. Jimenez, J. B. Gilman, J. A. de Gouw, M. C. Woody, H. O. T. Pye, J. T. Kelly, M. Lewandowski, M. Jaoui, P. S. Stevens, W. H. Brune, Y.-H. Lin, C. L. Rubitschun, and J. D. Surratt
Atmos. Chem. Phys., 15, 5243–5258, https://doi.org/10.5194/acp-15-5243-2015, https://doi.org/10.5194/acp-15-5243-2015, 2015
Short summary
Short summary
This work details the evaluation of PM2.5 carbon, VOC precursors, and OH estimated by the CMAQ photochemical transport model using routine and special measurements from the 2010 CalNex field study. Here, CMAQ and most recent emissions inventory (2011 NEI) are used to generate model PM2.5 OC estimates that are examined in novel ways including primary vs. secondary formation, fossil vs. contemporary carbon, OH and HO2 evaluation, and the relationship between key VOC precursors and SOC tracers.
D. C. Wong, C. E. Yang, J. S. Fu, K. Wong, and Y. Gao
Geosci. Model Dev., 8, 1033–1046, https://doi.org/10.5194/gmd-8-1033-2015, https://doi.org/10.5194/gmd-8-1033-2015, 2015
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.
B. Zheng, Q. Zhang, Y. Zhang, K. B. He, K. Wang, G. J. Zheng, F. K. Duan, Y. L. Ma, and T. Kimoto
Atmos. Chem. Phys., 15, 2031–2049, https://doi.org/10.5194/acp-15-2031-2015, https://doi.org/10.5194/acp-15-2031-2015, 2015
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
T. Glotfelty, Y. Zhang, P. Karamchandani, and D. G. Streets
Atmos. Chem. Phys., 14, 9379–9402, https://doi.org/10.5194/acp-14-9379-2014, https://doi.org/10.5194/acp-14-9379-2014, 2014
J. He and Y. Zhang
Atmos. Chem. Phys., 14, 9171–9200, https://doi.org/10.5194/acp-14-9171-2014, https://doi.org/10.5194/acp-14-9171-2014, 2014
B. Gantt, J. He, X. Zhang, Y. Zhang, and A. Nenes
Atmos. Chem. Phys., 14, 7485–7497, https://doi.org/10.5194/acp-14-7485-2014, https://doi.org/10.5194/acp-14-7485-2014, 2014
F. Yan, E. Winijkul, D. G. Streets, Z. Lu, T. C. Bond, and Y. Zhang
Atmos. Chem. Phys., 14, 5709–5733, https://doi.org/10.5194/acp-14-5709-2014, https://doi.org/10.5194/acp-14-5709-2014, 2014
M. Li, Q. Zhang, D. G. Streets, K. B. He, Y. F. Cheng, L. K. Emmons, H. Huo, S. C. Kang, Z. Lu, M. Shao, H. Su, X. Yu, and Y. Zhang
Atmos. Chem. Phys., 14, 5617–5638, https://doi.org/10.5194/acp-14-5617-2014, https://doi.org/10.5194/acp-14-5617-2014, 2014
L. T. Wang, Z. Wei, J. Yang, Y. Zhang, F. F. Zhang, J. Su, C. C. Meng, and Q. Zhang
Atmos. Chem. Phys., 14, 3151–3173, https://doi.org/10.5194/acp-14-3151-2014, https://doi.org/10.5194/acp-14-3151-2014, 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
A. Baklanov, K. Schlünzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. S. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang
Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, https://doi.org/10.5194/acp-14-317-2014, 2014
G. Sarwar, J. Godowitch, B. H. Henderson, K. Fahey, G. Pouliot, W. T. Hutzell, R. Mathur, D. Kang, W. S. Goliff, and W. R. Stockwell
Atmos. Chem. Phys., 13, 9695–9712, https://doi.org/10.5194/acp-13-9695-2013, https://doi.org/10.5194/acp-13-9695-2013, 2013
J. Xing, J. Pleim, R. Mathur, G. Pouliot, C. Hogrefe, C.-M. Gan, and C. Wei
Atmos. Chem. Phys., 13, 7531–7549, https://doi.org/10.5194/acp-13-7531-2013, https://doi.org/10.5194/acp-13-7531-2013, 2013
Y. Zhang, K. Sartelet, S.-Y. Wu, and C. Seigneur
Atmos. Chem. Phys., 13, 6807–6843, https://doi.org/10.5194/acp-13-6807-2013, https://doi.org/10.5194/acp-13-6807-2013, 2013
Y. Zhang, K. Sartelet, S. Zhu, W. Wang, S.-Y. Wu, X. Zhang, K. Wang, P. Tran, C. Seigneur, and Z.-F. Wang
Atmos. Chem. Phys., 13, 6845–6875, https://doi.org/10.5194/acp-13-6845-2013, https://doi.org/10.5194/acp-13-6845-2013, 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
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
Short summary
Short summary
This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
Short summary
Short summary
We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
Short summary
Short summary
Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
Short summary
We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Short summary
This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
Short summary
Short summary
Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
Short summary
Short summary
The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
Short summary
Short summary
The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
Short summary
Short summary
Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
Short summary
Short summary
We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation
2. Multiple aerosol types, J. Geophys. Res., 105, 6837–6844, 2000.
Alapaty, K., Herwehe, J. A., Otte, T. L., Nolte, C. G., Bullock, O. R.,
Mallard, M. S., Kain, J. S., and Dudhia, J.: Introducing subgrid-scale cloud
feedbacks to radiation for regional meteorological and climate modeling,
Geophys. Res. Lett., 39, L24809, https://doi.org/10.1029/2012GL054031, 2012.
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., Gilliland, A. B., Sarwar, G., and Gilliam, R. C.: Evaluation
of the Community Multiscale Air Quality (CMAQ) model version 4.5:
Sensitivities impacting model performance: Part I, Ozone, Atmos. Environ.,
41, 9603–9615, 2007.
Appel, K. W., Pouliot, G. A., Simon, H., Sarwar, G., Pye, H. O. T., Napelenok, S. L., Akhtar, F., and Roselle, S. J.: Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0, Geosci. Model Dev., 6, 883–899, https://doi.org/10.5194/gmd-6-883-2013, 2013.
Appel, K. W., Napelenok, S. L., Foley, K. M., Pye, H. O. T., Hogrefe, C., Luecken, D. J., Bash, J. O., Roselle, S. J., Pleim, J. E., Foroutan, H., Hutzell, W. T., Pouliot, G. A., Sarwar, G., Fahey, K. M., Gantt, B., Gilliam, R. C., Heath, N. K., Kang, D., Mathur, R., Schwede, D. B., Spero, T. L., Wong, D. C., and Young, J. O.: Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geosci. Model Dev., 10, 1703–1732, https://doi.org/10.5194/gmd-10-1703-2017, 2017.
Baklanov, A., Schlünzen, K., Suppan, P., Baldasano, J., Brunner, D., Aksoyoglu, S., Carmichael, G., Douros, J., Flemming, J., Forkel, R., Galmarini, S., Gauss, M., Grell, G., Hirtl, M., Joffre, S., Jorba, O., Kaas, E., Kaasik, M., Kallos, G., Kong, X., Korsholm, U., Kurganskiy, A., Kushta, J., Lohmann, U., Mahura, A., Manders-Groot, A., Maurizi, A., Moussiopoulos, N., Rao, S. T., Savage, N., Seigneur, C., Sokhi, R. S., Solazzo, E., Solomos, S., Sørensen, B., Tsegas, G., Vignati, E., Vogel, B., and Zhang, Y.: Online coupled regional meteorology chemistry models in Europe: current status and prospects, Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, 2014.
Bennartz, R.: Global assessment of marine boundary layer cloud droplet
number concentration from satellite, J. Geophys. Res., 112, D02201,
https://doi.org/10.1029/2006JD007547, 2007.
Boersma, K. F., Eskes, H. J., and Brinksma, E. J.: Error analysis for
tropospheric NO2 retrieval from space, J. Geophys. Res., 109, D04311,
https://doi.org/10.1029/2003JD003962, 2004.
Brunner, D., Savage, N., Jorba, O., Eder, B., Giordano, L., Badia, A.,
Balzarini, A., Baro, R., Bianconi, R., Chemel, C., Curci, G., Forkel, R.,
Jimenez-Guerrero, P., Hirtl, M., Hodzic, A., Hozak, L., Im, U., Knote, C.,
Makar, P., Manders-Groot, A., van Meijgaard, E., Neal, L., Perez, J. L.,
Pirovano, G., San Jose, R., Schroder, W., Sokhi, R. S., Syrakov, D., Torian,
A., Tuccella, P., Werhahn, J., Wolke, R., Yahya, K., Zabkar, R., Zhang, Y.,
Hogrefe, C., and Galmarini, S.: Comparative analysis of meteorological
performance of coupled chemistry-meteorology models in the context of AQMEII
phase 2, Atmos. Environ., 115, 470–498, https://doi.org/10.1016/j.atmosenv.2014.12.032, 2015.
Byun, D. W. and Schere K. L.: Review equations, computational algorithms,
and other components of the Models-3 Community Multi-Scale Air Quality
(CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77,
https://doi.org/10.1115/1.2128636, 2006.
Choi, M. W., Lee, J. H., Woo, J. W., Kim, C. H., and Lee, S. H.: Comparison
of PM2.5 chemical components over East Asia simulated by the WRF-Chem
and WRF/CMAQ models: On the models' prediction inconsistency, Atmosphere, 10,
618, https://doi.org/10.3390/atmos10100618, 2019.
CMAS (Community Modeling and Analysis System):
https://www.cmascenter.org/download/data.cfm#obs, last access: 3 November 2021.
Cohen, A. E., Cavallo, S. M., Coniglio, M. C., and Brooks, H. E.: A review
of planetary boundary layer parameterization schemes and their sensitivity
in simulating southeastern U.S. cold season severe weather environments,
Weather Forecast., 30, 591–612, https://doi.org/10.1175/WAF-D-14-00105.1, 2015.
Dong, X., Fu, J. S., Huang, K., Tong, D., and Zhuang, G.: Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia, Atmos. Chem. Phys., 16, 8157–8180, https://doi.org/10.5194/acp-16-8157-2016, 2016.
Eder, B. and Yu, S.: A performance evaluation of the 2004 release of
Models-3 CMAQ, Atmos. Environ., 40, 4811–4824, 2006.
Emery, C., Liu, Z., Russell, A. G., Odman, M. T., Yarwood, G., and Kumar,
N.: Recommendations on statistics and benchmarks to assess photochemical
model performance, J. Air Waste Manage. Assoc., 67, 582–598,
https://doi.org/10.1080/10962247.2016.1265027, 2017.
Emmons, L. K., Edwards, D. P., Deeter, M. N., Gille, J. C., Campos, T., Nédélec, P., Novelli, P., and Sachse, G.: Measurements of Pollution In The Troposphere (MOPITT) validation through 2006, Atmos. Chem. Phys., 9, 1795–1803, https://doi.org/10.5194/acp-9-1795-2009, 2009.
Gan, C.-M., Pleim, J., Mathur, R., Hogrefe, C., Long, C. N., Xing, J., Wong, D., Gilliam, R., and Wei, C.: Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation “brightening” in the United States, Atmos. Chem. Phys., 15, 12193–12209, https://doi.org/10.5194/acp-15-12193-2015, 2015a.
Gan, C.-M., Binkowski, F., Pleim, J., Xing, J., Wong, D., Mathur, R., and
Gilliam, R.: Assessment of the aerosol optics component of the coupled
WRF–CMAQ model using CARES field campaign data and a single column model,
Atmos. Environ., 115, 670–682, 2015b.
Gantt, B., He, J., Zhang, X., Zhang, Y., and Nenes, A.: Incorporation of advanced aerosol activation treatments into CESM/CAM5: model evaluation and impacts on aerosol indirect effects, Atmos. Chem. Phys., 14, 7485–7497, https://doi.org/10.5194/acp-14-7485-2014, 2014.
Gantt, B., Sarwar, G., Xing, J., Simon, H., Schwede, D., Hutzell, W. T.,
Mathur, R., and Saiz-Lopez, A.: The impact of iodide-mediated ozone
deposition and halogen chemistry on surface ozone concentrations across the
continental United States, Environ. Sci. Technol., 51, 1458–1466, 2017.
Ghan, S. J., Laulainen, N. S., Easter, R. C., Wagener, R., Nemesure, S.,
Chapman, E. G., Zhang, Y., and Leung, L. R.: Evaluation of aerosol direct
radiative forcing in MIRAGE, J. Geophys. Res., 106, 5295–5316, 2001.
Glotfelty, T., He, J., and Zhang, Y.: Impact of future climate policy
scenarios on air quality and aerosol-cloud interactions using an advanced
version of CESM/CAM5: Part I. model evaluation for the current decadal
simulations, Atmos. Environ., 152, 222–239, 2017.
Grell, G. A. and Baklanov, A.: Integrated modelling for forecasting weather
and air quality: A call for fully coupled approaches, Atmos. Environ., 45,
38, 6845–6851, 2011.
Grell, G. A., Peckham, S. E., Schmitz, R., McKenn, S. A., Frost, G.,
Skamarock, W. C., and Eder, B.: Fully Coupled “Online” chemistry within
the WRF Model, Atmos. Environ., 39, 6957–6975, 2005.
He, J. and Zhang, Y.: Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments, Atmos. Chem. Phys., 14, 9171–9200, https://doi.org/10.5194/acp-14-9171-2014, 2014.
Heald, C. L., Jacob, D. J., Fiore, A. M., Emmons, L. K., Gille, J. C.,
Deeter, M. N., Warner, J., Edwards, D. P., Crawford, J. H., Hamlin, A. J.,
Sachse, G. W., Browell, E. V., Avery, M. A., Vay, S. A., Westberg, D. J.,
Blake, D. R., Singh, H. B., Sandholm, S. T., Talbot, R. W., and Fuelberg, H.
E.: Asian outflow and trans-Pacific transport of carbon monoxide and ozone
pollution: An integrated satellite, aircraft, and model perspective, J.
Geophys. Res., 108, 4804, https://doi.org/10.1029/2003JD003507, 2003.
Herwehe, J. A., Otte, T. L., Mathur, R., and Rao, S. T.: Diagnostic analysis
of ozone concentrations simulated by two regional-scale air quality models,
Atmos. Environ., 45, 5957–5969, 2011.
Hogrefe, C., Pouliot, G., Wong, D., Torian, A., Roselle, S., Pleim, J., and
Mathur, R.: Annual application and evaluation of the online coupled
WRF–CMAQ system over North America under AQMEII phase 2, Atmos. Environ.,
115, 683–694, 2015.
Hong, C., Zhang, Q., Zhang, Y., Tang, Y., Tong, D., and He, K.: Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects, Geosci. Model Dev., 10, 2447–2470, https://doi.org/10.5194/gmd-10-2447-2017, 2017.
Hong, C.-P., Zhang, Q., Zhang, Y., Davis, S. J., Zhang, X., Tong, D., Guan,
D., Liu, Z., and He, K.-B.: Weakened aerosol radiative effects may mitigate
the climate penalty on Chinese air quality, Nat. Clim. Change, 10, 845–850, https://doi.org/10.1038/s41558-020-0840-y, 2020.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S.
A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases:
Calculations with the AER radiative transfer models, J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008.
IPCC: Global warming of 1.5 ∘C, An IPCC Special Report on the
impacts of global warming of 1.5 ∘C above pre-industrial levels
and related global greenhouse gas emission pathways, in the context of
strengthening the global response to the threat of climate change,
sustainable development, and efforts to eradicate poverty, edited by:
Masson-Delmotte, V., Zhai, P., Pörtner, H. O., Roberts, D., Skea, J.,
Shukla, P. R., Pirani, A., Moufouma-Okia, W., Péan, C., Pidcock, R.,
Connors, S., Matthews, J. B. R., Chen, Y., Zhou, X., Gomis, M. I., Lonnoy,
E., Maycock, T., Tignor, M., and Waterfield, T., World Meteorological Organization, Geneva, Switzerland, 32 pp., 2018.
Jacobson, M. Z.: GATOR-GCMM: A global- through urban-scale air pollution and
weather forecast model 1. Model design and treatment of subgrid soil,
vegetation, roads, rooftops, water, sea, ice, and snow, J. Geophys. Res.,
106, 5385–5401, 2001.
Jacobson, M. Z., Lu, R., Turco, R. P., and Toon, O. B.: Development and
application of a new air pollution modeling system. Part I: Gas-phase
simulations, Atmos. Environ., 30B, 1939–1963, 1996.
Jung, J., Souri, A. H., Wong, D. C., Lee, S., Jeon, W., Kim, J., and Choi,
Y.: The impact of the direct effect of aerosols on meteorology and air
quality using aerosol optical depth assimilation during the KORUS-AQ campaign, J. Geophys. Res.-Atmos., 124, 8303–8319,
https://doi.org/10.1029/2019JD030641, 2019.
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.
Karydis, V. A., Tsimpidi, A. P., and Pandis, S. N.: Evaluation of a
three-dimensional chemical transport model (PMCAMx) in the eastern United
States for all four seasons, J. Geophys. Res., 112, D14211,
https://doi.org/10.1029/2006JD007890, 2007.
Kaufman, Y. J., Smirnov, A., Holben, B., and Dubovik, O.: Baseline maritime
aerosol methodology to derive the optical thickness and scattering
properties, Geophys. Res. Lett., 28, 3251, https://doi.org/10.1029/2001GL013312, 2001.
Kelly, J., Koplitz, S., Baker, K., Holder, A., Pye, H., Murphy, B., Bash,
J., Henderson, B., Possiel, N., Simon, H., Eyth, A., Jang, C., Phillips, S.,
and Timin, B.: Assessing PM2.5 model performance for the conterminous
U.S. with comparison to model performance statistics from 2007–2015, Atmos.
Environ., 214, 116872, https://doi.org/10.1016/j.atmosenv.2019.116872, 2019.
Kukkonen, J., Olsson, T., Schultz, D. M., Baklanov, A., Klein, T., Miranda, A. I., Monteiro, A., Hirtl, M., Tarvainen, V., Boy, M., Peuch, V.-H., Poupkou, A., Kioutsioukis, I., Finardi, S., Sofiev, M., Sokhi, R., Lehtinen, K. E. J., Karatzas, K., San José, R., Astitha, M., Kallos, G., Schaap, M., Reimer, E., Jakobs, H., and Eben, K.: A review of operational, regional-scale, chemical weather forecasting models in Europe, Atmos. Chem. Phys., 12, 1–87, https://doi.org/10.5194/acp-12-1-2012, 2012.
Li, P, Wang, L., Guo, P., Yu, S., Mehmood, K., Wang, S., Liu, W., Seinfeld,
J. H., Zhang, Y., Wong, D., Alapaty, K., Pleim, J., and Mathur, R.: High
reduction of ozone and particulate matter during the 2016 G-20 summit in
Hangzhou by forced emission controls of industry and traffic, Environ. Chem.
Lett., 15, 709–715, https://doi.org/10.1007/s10311-017-0642-2, 2017.
Lin, M., Holloway, T., Carmichael, G. R., and Fiore, A. M.: Quantifying pollution inflow and outflow over East Asia in spring with regional and global models, Atmos. Chem. Phys., 10, 4221–4239, https://doi.org/10.5194/acp-10-4221-2010, 2010.
Liu, X.-H., Zhang, Y., Xing, J., Zhang, Q., Wang, K., Streets, D. G., Jang,
C. J., Wang, W.-X., and Hao, J. M.: Understanding of regional air pollution
over China using CMAQ: Part II. Process analysis and ozone sensitivity to
precursor emissions, Atmos. Environ., 44, 3719–3727, 2010.
Lorente, A., Folkert Boersma, K., Yu, H., Dörner, S., Hilboll, A., Richter, A., Liu, M., Lamsal, L. N., Barkley, M., De Smedt, I., Van Roozendael, M., Wang, Y., Wagner, T., Beirle, S., Lin, J.-T., Krotkov, N., Stammes, P., Wang, P., Eskes, H. J., and Krol, M.: Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals, Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, 2017.
Ma, P.-L., Rasch, P. J., Fast, J. D., Easter, R. C., Gustafson Jr., W. I., Liu, X., Ghan, S. J., and Singh, B.: Assessing the CAM5 physics suite in the WRF-Chem model: implementation, resolution sensitivity, and a first evaluation for a regional case study, Geosci. Model Dev., 7, 755–778, https://doi.org/10.5194/gmd-7-755-2014, 2014.
Makar, P. A., Gonga, W., Hogrefe, C., Zhang, Y., Curci, G., Žabkar, R.,
Milbrandt, J., Im, U., Balzarini, A., Baró, R., Bianconi, R., Cheung,
P., Forkel, R., Gravel, S., Hirtl, M., Honzak, L., Hou, A.,
Jiménez-Guerrero, P., Langer, M., Moran, M. B., Pabla, B., Pérez, J.
L., Pirovano, G., San José, R., Tuccella, P., Werhahn, J., Zhang, J.,
and Galmarini, S.: Feedbacks between air pollution and weather, Part 2:
Effects on chemistry, Atmos. Environ., 115, 499–526, 2015.
Mathur, R., Xiu, A., Coats, C., Alapaty, K., Shankar, U., and Hanna, A.:
Development of an air quality modeling system with integrated meteorology,
chemistry, and emissions, Proc. Measurement of Toxic and Related Air
Pollutants, AWMA, Cary, NC, 1–3 September 1998.
Mathur, R., Xing, J., Gilliam, R., Sarwar, G., Hogrefe, C., Pleim, J., Pouliot, G., Roselle, S., Spero, T. L., Wong, D. C., and Young, J.: Extending the Community Multiscale Air Quality (CMAQ) modeling system to hemispheric scales: overview of process considerations and initial applications, Atmos. Chem. Phys., 17, 12449–12474, https://doi.org/10.5194/acp-17-12449-2017, 2017.
Matsui, H., Koike, M., Kondo, Y., Takegawa, N., Kita,K., Miyazaki, Y., Hu,
M., Chang, S.-Y., Blake, D. R., Fast, J. D., Zaveri, R. A., Streets, D. G.,
Zhang, Q. and Zhu, T.: Spatial and temporal variations of aerosols around
Beijing in summer 2006: Model evaluation and source apportionment, J.
Geophys. Res., 114, D00G13, https://doi.org/10.1029/2008JD010906, 2009.
Mebust, M. R., Eder, B. K., Binkowski, F. S., and Roselle, S. J.: Models-3
Community Multiscale Air Quality (CMAQ) model aerosol component: 2. Model
evaluation, J. Geophys. Res., 108, 4184, https://doi.org/10.1029/2001JD001410, 2003.
Mehmood, K., Wu, Y., Wang, L., Yu, S., Li, P., Chen, X., Li, Z., Zhang, Y., Li, M., Liu, W., Wang, Y., Liu, Z., Zhu, Y., Rosenfeld, D., and Seinfeld, J. H.: Relative effects of open biomass burning and open crop straw burning on haze formation over central and eastern China: modeling study driven by constrained emissions, Atmos. Chem. Phys., 20, 2419–2443, https://doi.org/10.5194/acp-20-2419-2020, 2020.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics
on the development of trailing stratiform precipitation in a simulated
squall line: Comparison of one- and two-moment schemes, Mon. Weather Rev.,
137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009.
NASA CERES: CERES_EBAF_Ed4.1 Subsetting and Browsing, NASA [data set], available at: https://ceres-tool.larc.nasa.gov/ord-tool/jsp/EBAF41Selection.jsp, last access: 3 November 2021.
NASA/LARC/SD/ASDC: MOPITT CO gridded monthly means (Near and Thermal Infrared Radiances) V009, NASA Langley Atmospheric Science Data Center DAAC [data set], https://doi.org/10.5067/TERRA/MOPITT/MOP03JM.009, last access: 3 November 2021.
NCAR (National Center for Atmospheric Research): WRFv3.4, NCAR [code], available at: https://www2.mmm.ucar.edu/wrf/src/WRFV3.4.TAR.gz (last access: 3 November 2021), 2012.
NCEI (National Centers for Environmental Information): GPCP data, available at: https://www.ncei.noaa.gov/data/global-precipitation-climatology-project-gpcp-monthly, last access: 3 November 2021a.
NCEI (National Centers for Environmental Information): NCDC data, available at: https://www.ncei.noaa.gov/data/global-hourly/archive/csv, last access: 3 November 2021b.
Penrod, A., Zhang, Y., Wang, K., Wu, S.-Y., and Leung, R. L.: Impacts of
future climate and emission changes on US air quality, Atmos. Environ., 89,
533–547, https://doi.org/10.1016/j.atmosenv.2014.01.001, 2014.
Platnick, S., Hubanks, P., Meyer, K.. and King, M. D.: MODIS Atmosphere L3 Monthly Product (08_L3), NASA MODIS Adaptive Processing System, Goddard Space Flight Center [data set], https://doi.org/10.5067/MODIS/MOD08_M3.006 (Terra), 2015.
Pleim, J., Young, J., Wong, D., Gilliam, R., Otte, T., and Mathur, R.:
Two-way coupled meteorology and air quality modeling, in Air Pollution
Modeling and its Application, edited by: Borrego, C. and Miranda, A. I., XIX,
NATO Science for Peace and Security Series, Series C: Environmental
Security, Springer, Dordrecht, 2008.
Pleim, J. E.: A combined local and nonlocal closure model for the
atmospheric boundary layer. Part I: Model description and testing, J. Appl.
Meteorol. Clim., 46, 1383–1395, https://doi.org/10.1175/JAM2539.1, 2007.
Pleim, J. E. and Gilliam, R.: An indirect data assimilation scheme for deep
soil temperature in the Pleim–Xiu land surface model, J. Appl. Meteorol.
Clim., 48, 1362–1376, 2009.
Pye, H. O. T., Murphy, B. N., Xu, L., Ng, N. L., Carlton, A. G., Guo, H., Weber, R., Vasilakos, P., Appel, K. W., Budisulistiorini, S. H., Surratt, J. D., Nenes, A., Hu, W., Jimenez, J. L., Isaacman-VanWertz, G., Misztal, P. K., and Goldstein, A. H.: On the implications of aerosol liquid water and phase separation for organic aerosol mass, Atmos. Chem. Phys., 17, 343–369, https://doi.org/10.5194/acp-17-343-2017, 2017.
Pye, H. O. T., Nenes, A., Alexander, B., Ault, A. P., Barth, M. C., Clegg, S. L., Collett Jr., J. L., Fahey, K. M., Hennigan, C. J., Herrmann, H., Kanakidou, M., Kelly, J. T., Ku, I.-T., McNeill, V. F., Riemer, N., Schaefer, T., Shi, G., Tilgner, A., Walker, J. T., Wang, T., Weber, R., Xing, J., Zaveri, R. A., and Zuend, A.: The acidity of atmospheric particles and clouds, Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, 2020.
Remer, L. A., Kaufman, Y. J., Tanré, D., Mattoo, S., Chu, D. A.,
Martins, J. V., Li, R. R., Ichoku, C., Levy, R. C., and Kleidman, R. G.: The
MODIS aerosol algorithm, products, and validation, J. Atmos. Sci., 62,
947–973, 2005.
Roy, B., Pouliot, G. A., Gilliland, A., Pierce, T., Howard, S., Bhave, P.
V., and Benjey, W.: Refining fire emissions for air quality modeling with
remotely sensed fire counts: A wildfire case study, Atmos. Environ., 41,
655–665, https://doi.org/10.1016/j.atmosenv.2006.08.037, 2007.
San Joaquin Valley Air Pollution Control District: 2018 Plan for the 1997,
2006, and 2012 PM2.5 Standards, available at: https://www.valleyair.org/pmplans (last access: 3 November 2021), 15 November 2018.
Sarwar, G., Luecken, D., Yarwood, G., Whitten, G. Z., and Carter, W. P. L.:
Impact of an updated carbon bond mechanism on predictions from the CMAQ
modeling system: Preliminary assessment, J. Appl. Meteorol. Clim., 47, 3–14,
2008.
Sarwar, G., Gantt, B., Schwede, D., Foley, K., Mathur, R., and Saiz-Lopez,
A.: Impact of enhanced ozone deposition and halogen chemistry on
tropospheric ozone over the Northern Hemisphere, Environ. Sci. Technol., 49, 9203-9211, 2015.
Scheffe, R. D., Strum, M., Phillips, S. B., Thurman, J., Eyth, A., Fudge,
S., Morris, M., Palma, T., and Cook, R.: Hybrid modeling approach to
estimate exposures of hazardous air pollutants (HAPs) for the National Air
Toxics Assessment (NATA), Environ. Sci. Technol., 50,
12356–12364, https://doi.org/10.1021/acs.est.6b04752, 2016.
Schwede, D., Pouliot, G. A., and Pierce, T.: Changes to the biogenic
emissions inventory system version 3 (BEIS3), in: Proceedings of the 4th
CMAS Models-3 Users' Conference, Chapel Hill, NC, 26–28 September 2005.
Sekiguchi, A., Shimadera, H., and Kondo, A.: Impact of aerosol direct effect
on wintertime PM2.5 simulated by an online coupled meteorology-air
quality model over East Asia, Aerosol. Air Qual. Res., 18, 1068–1079, 2018.
Solazzo, E., Hogrefe, C., Colette, A., Garcia-Vivanco, M., and Galmarini, S.: Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework, Atmos. Chem. Phys., 17, 10435–10465, https://doi.org/10.5194/acp-17-10435-2017, 2017.
Stavrakou, T., Müller, J.-F., De Smedt, I., Van Roozendael, M., van der Werf, G. R., Giglio, L., and Guenther, A.: Global emissions of non-methane hydrocarbons deduced from SCIAMACHY formaldehyde columns through 2003–2006, Atmos. Chem. Phys., 9, 3663–3679, https://doi.org/10.5194/acp-9-3663-2009, 2009.
TEMIS (Tropospheric Emission Monitoring Internet Service): Tropospheric NO2 from satellites, available at: https://www.temis.nl/airpollution/no2.php, last access: 3 November 2021a.
TEMIS (Tropospheric Emission Monitoring Internet Service): Tropospheric ozone column, available at: https://www.temis.nl/protocols/tropo.php, last access: 3 November 2021b.
U.S. EPA: Our nation's air status and trends through 2010, EPA-454/R-12-001,
available at: https://www.epa.gov/sites/default/files/2017-11/documents/trends_brochure_2010.pdf (last access: 3 November 2021), 2012.
U.S. EPA: Policy assessment for the review of the National Ambient Air
Quality Standards for particulate matter, EPA-452/R-20-002, available at:
https://www.epa.gov/sites/production/files/2020-01/documents/final_policy_assessment_for_the_review_of_the_pm_naaqs_01-2020.pdf (last access: 3 November 2021), 2020.
U.S. EPA Office of Research and Development: CMAQv5.0.2, 5.0.2, Zenodo [code], https://doi.org/10.5281/zenodo.1079898, 2014.
Vasilakos, P., Russell, A., Weber, R., and Nenes, A.: Understanding nitrate formation in a world with less sulfate, Atmos. Chem. Phys., 18, 12765–12775, https://doi.org/10.5194/acp-18-12765-2018, 2018.
Wang, J., Wang, S., Jiang, J., Ding, A., Zheng, M., Zhao, B., Wong, C.-D.,
Zhou, W., Zheng, G., Wang, L., Pleim, J., and Hao, J.: Impact of
aerosol–meteorology interactions on fine particle pollution during China's
severe haze episode in January 2013, Environ. Res. Lett., 9, 094002,
https://doi.org/10.1088/1748-9326/9/9/094002, 2014.
Wang, K. and Zhang, Y.: Application, evaluation, and process analysis of
U.S. EPA's 2002 multiple-pollutant air quality modeling platform,
Atmospheric and Climate Sciences, 2, 254–289, 2012.
Wang, K. and Zhang, Y.: 3-D agricultural air quality modeling: Impacts of
Wang, K., Zhang, Y., Jang, C., Phillips, S., and Wang, B.: Modeling
intercontinental air pollution transport over the trans-Pacific region in
2001 using the Community Multiscale Air Quality modeling system, J. Geophys.
Res., 114, D04307, https://doi.org/10.1029/2008JD010807, 2009.
Wang, K., Zhang, Y., Nenes, A., and Fountoukis, C.: Implementation of dust
emission and chemistry into the Community Multiscale Air Quality modeling
system and initial application to an Asian dust storm episode, Atmos. Chem.
Phys., 12, 10209–10237, https://doi.org/10.5194/acp-12-10209-2012, 2012.
Wang, K., Zhang, Y., Yahya, K., Wu, S.-Y., and Grell, G.: Implementation and
initial application of new chemistry-aerosol options in WRF/Chem for
simulating secondary organic aerosols and aerosol indirect effects for
regional air quality, Atmos. Environ., 115, 716–732,
https://doi.org/10.1016/j.atmosenv.2014.12.007, 2015a.
Wang, K., Yahya, K., Zhang, Y., Hogrefe, C., Pouliot, G., Knote, C., Hodzic,
A., Jose, R. S., Perez, J. L., Jiménez-Guerrero, P., Baro, R., Makar,
P., and Bennartz, R.: A multi-model assessment for the 2006 and 2010
simulations under the Air Quality Model Evaluation International Initiative
(AQMEII) Phase 2 over North America: Part II. Evaluation of column variable
predictions using satellite data, Atmos. Environ., 115, 587–603, https://doi.org/10.1016/j.atmosenv.2014.07.044, 2015b.
Wang, K., Zhang, Y., and Yahya, K.: Decadal application of WRF/Chem over the
continental U.S.: Simulation design, sensitivity simulations, and
climatological model evaluation, Atmos. Environ., 253, 118331,
https://doi.org/10.1016/j.atmosenv.2021.118331, 2021.
West, J. J., Ansari, A. S., and Pandis, S. N.: Marginal PM2.5:
Nonlinear aerosol mass response to sulfate reductions in the Eastern United
States, J. Air Waste Manage. Assoc., 49, 1415–1424, https://doi.org/10.1080/10473289.1999.10463973, 1999.
Wiedinmyer, C., Quayle, B., Geron, C., Belote, A., McKenzie, D., Zhang, X.,
O'Neill, S., and Wynne, K. K.: Estimating emissions from fires in North
America for air quality modeling, Atmos. Environ., 40, 3419–3432,
https://doi.org/10.1016/j.atmosenv.2006.02.010, 2006.
Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Lee III, R. B., Smith,
G. L., and Cooper, J. E.: Clouds and the Earth's Radiant Energy System
(CERES): An earth observing system experiment, B. Am. Meteorol. Soc., 77,
853–868, 1996.
Wilczak, J. M., Djalalova, I., McKeen, S., Bianco, L., Bao, J.-W., Grell,
G., Peckham, S., Mathur, R., McQueen, J., and Lee, P: Analysis of regional
meteorology and surface ozone during the TexAQS II field program and an
evaluation of the NMM-CMAQ and WRF-Chem air quality models, J. Geophys.
Res., 114, D00F14, https://doi.org/10.1029/2008JD011675, 2009.
Wong, D. C., Pleim, J., Mathur, R., Binkowski, F., Otte, T., Gilliam, R., Pouliot, G., Xiu, A., Young, J. O., and Kang, D.: WRF-CMAQ two-way coupled system with aerosol feedback: software development and preliminary results, Geosci. Model Dev., 5, 299–312, https://doi.org/10.5194/gmd-5-299-2012, 2012.
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C.-M., Wong, D. C., Wei,
C., and Wang, J.: Air pollution and climate response to aerosol direct
radiative effects: A modeling study of decadal trends across the northern
hemisphere, J. Geophys. Res.-Atmos., 120, 12221–12236,
https://doi.org/10.1002/2015JD023933, 2015a.
Xing, J., Mathur, R., Pleim, J., Hogrefe, C., Gan, C.-M., Wong, D. C., and Wei, C.: Can a coupled meteorology–chemistry model reproduce the historical trend in aerosol direct radiative effects over the Northern Hemisphere?, Atmos. Chem. Phys., 15, 9997–10018, https://doi.org/10.5194/acp-15-9997-2015, 2015b.
Xing, J., Wang, J., Mathur, R., Pleim, J., Wang, S., Hogrefe, C., Gan,
C.-M., Wong, D., and Hao, J.: Unexpected benefits of reducing aerosol
cooling effects, Environ. Sci. Technol., 50, 7527–7534, https://doi.org/10.1021/acs.est.6b00767, 2016.
Xing, J., Wang, J., Mathur, R., Wang, S., Sarwar, G., Pleim, J., Hogrefe, C., Zhang, Y., Jiang, J., Wong, D. C., and Hao, J.: Impacts of aerosol direct effects on tropospheric ozone through changes in atmospheric dynamics and photolysis rates, Atmos. Chem. Phys., 17, 9869–9883, https://doi.org/10.5194/acp-17-9869-2017, 2017.
Xiu, A. and Pleim, J. E.: Development of a land surface model. Part I:
Application in a mesoscale meteorological model, J. Appl. Meteorol., 40,
192–209, https://doi.org/10.1175/1520-0450(2001)040<0192:DOALSM>2.0.CO;2, 2001.
Yahya, K., Wang, K., Gudoshava, M., Glotfelty, T., and Zhang, Y.:
Application of WRF/Chem over North America under the AQMEII Phase 2. Part I.
Comprehensive evaluation of 2006 simulation, Atmos. Environ., 115, 733–755,
https://doi.org/10.1016/j.atmosenv.2014.08.063, 2015a.
Yahya, K., Wang, K., Zhang, Y., and Kleindienst, T. E.: Application of WRF/Chem over North America under the AQMEII Phase 2 – Part 2: Evaluation of 2010 application and responses of air quality and meteorology–chemistry interactions to changes in emissions and meteorology from 2006 to 2010, Geosci. Model Dev., 8, 2095–2117, https://doi.org/10.5194/gmd-8-2095-2015, 2015b.
Yahya, K., Wang, K., Campbell, P., Glotfelty, T., He, J., and Zhang, Y.: Decadal evaluation of regional climate, air quality, and their interactions over the continental US and their interactions using WRF/Chem version 3.6.1, Geosci. Model Dev., 9, 671–695, https://doi.org/10.5194/gmd-9-671-2016, 2016.
Yarwood, G., Rao, S., Yocke, M., and Whitten, G. Z.: Final Report–Updates
to the Carbon Bond Chemical Mechanism: CB05, Rep. RT-04-00675, Yocke and Co.,
Novato, Calif., 246 pp., 2005.
Yoo, J.-W., Jeon, W., Park, S.-Y., Park, C., Jung, J., Lee, S.-H., and Lee,
H. W.: Investigating the regional difference of aerosol feedback effects
over South Korea using the WRF-CMAQ two-way coupled modeling system, Atmos.
Environ., 218, 116968, https://doi.org/10.1016/j.atmosenv.2019.116968, 2019.
Yu, S., Eder, B., Dennis, R., Chu, S., and Schwartz, S.: New unbiased
symmetric metrics for evaluation of air quality models, Atmos. Sci. Lett.,
7, 26–34, 2006.
Yu, S., Mathur, R., Pleim, J., Wong, D., Gilliam, R., Alapaty, K., Zhao, C., and Liu, X.: Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF–CMAQ: model description, development, evaluation and regional analysis, Atmos. Chem. Phys., 14, 11247–11285, https://doi.org/10.5194/acp-14-11247-2014, 2014 (data available at: https://person.zju.edu.cn/shaocaiyu#674502, last access: 3 November 2021).
Yu, S., Li, P., Wang, L., Wu, Y., Wang, S., Liu, W., Zhu, T., Zhang, Y., Hu,
M., Alapaty, K., Wong, D., Pleim, J., Mathur, R., Rosenfeld, D., and
Seinfeld, J.: Mitigation of severe urban haze pollution by a precision air
pollution control approach, Scientific Reports, 8, 8151,
https://doi.org/10.1038/s41598-018-26344-1, 2018.
Yu, S. C., Mathur, R., Schere, K., Kang, D., Pleim, J., and Otte, T. L.: A
detailed evaluation of the Eta-CMAQ forecast model performance for O3, its related precursors, and meteorological parameters during the 2004 ICARTT Study, J. Geophys. Res, 112, D12S14, https://doi.org/10.1029/2006JD007715, 2007.
Yu, S. C., Mathur, R., Pleim, J., Wong, D., Carlton, A. G., Roselle, S., and
Rao, S. T.: Simulation of the indirect radiative forcing of climate due to
aerosols by the two-way coupled WRF-CMAQ over the eastern United States, in
Air Pollution Modeling and its Applications, edited by: Steyn, D. G. and Castelli, S. T., XXI, Springer Netherlands, Netherlands, C(96), 579–583, 2011.
Yu, X.-Y., Lee, T., Ayres, B., Kreidenweis, S. M., Malm, W., and Collett, J.
L.: Loss of fine particle ammonium from denuded nylon filters, Atmos.
Environ., 40, 4797–4807, 2006.
Zender, C. S., Bian, H., and Newman, D.: Mineral Dust Entrainment and
Deposition (DEAD) model: Description and 1990s dust climatology, J. Geophys.
Res., 108, 4416, https://doi.org/10.1029/2002JD002775, 2003.
Zhang, Y.: Online-coupled meteorology and chemistry models: history, current status, and outlook, Atmos. Chem. Phys., 8, 2895–2932, https://doi.org/10.5194/acp-8-2895-2008, 2008.
Zhang, Y. and Wang, Y.: Climate-driven ground-level ozone extreme in the
fall over the Southeast United States, P. Natl. Acad. Sci. USA, 113,
10025–10030, https://doi.org/10.1073/pnas.1602563113, 2016.
Zhang, Y. and Wang, K.: Project 3 – Air quality and climate modeling:
Multi-model application, evaluation, intercomparison, and ensemble over the
U.S., poster presentation at the Air Climate Energy (ACE) Centers Meeting,
Pittsburgh, PA, 18–19 June 2019.
Zhang, K. M., Knipping, E. M., Wexler, A. S., Bhave, P. V., and Tonnesen, G.
S.: Size distribution of sea-salt emissions as a function of relative humidity, Atmos. Environ., 39, 3373–3379, 2005.
Zhang, Y., Liu, P., Pun, B., and Seigneur, C.: A comprehensive performance
evaluation of MM5-CMAQ for the summer 1999 Southern Oxidants Study episode,
Part-I. Evaluation protocols, databases and meteorological predictions,
Atmos. Environ., 40, 4825–4838, https://doi.org/10.1016/j.atmosenv.2005.12.043, 2006.
Zhang, Y., Vijayaraghavan, K., Wen, X.-Y., Snell, H. E., and Jacobson, M.
Z.: Probing into regional ozone and particulate matter pollution in the
United States: 1. A 1-year CMAQ simulation and evaluation using surface and
satellite data, J. Geophys. Res., 114, D22304, https://doi.org/10.1029/2009JD011898,
2009a.
Zhang, Y., Wen, X.-Y., Wang, K., Vijayaraghavan, K., and Jacobson, M. Z.:
Probing into regional ozone and particulate matter pollution in the United
States: 2. An examination of formation mechanisms through a process analysis
technique and sensitivity study, J. Geophys. Res., 114, D22305,
https://doi.org/10.1029/2009JD011900, 2009b.
Zhang, Y., Wen, X.-Y., and Jang, C. J.: Simulating
chemistry-aerosol-cloud-radiation-climate feedbacks over the continental US
using the online-coupled Weather Research Forecasting Model with chemistry
(WRF/Chem), Atmos. Environ., 44, 3568–3582,
https://doi.org/10.1016/j.atmosenv.2010.05.056, 2010.
Zhang, Y., Sartelet, K., Zhu, S., Wang, W., Wu, S.-Y., Zhang, X., Wang, K., Tran, P., Seigneur, C., and Wang, Z.-F.: Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 2: Evaluation of chemical concentrations and sensitivity simulations, Atmos. Chem. Phys., 13, 6845–6875, https://doi.org/10.5194/acp-13-6845-2013, 2013.
Zhang, Y., Chen, Y., Fan, J., and Leung, L. R.: Application of an
online-coupled regional climate model, WRF-CAM5, over East Asia for
examination of ice nucleation schemes: Part II. Sensitivity to ice
nucleation parameterizations and dust emissions, Climate, 3, 753–774,
https://doi.org/10.3390/cli3030753, 2015a.
Zhang, Y., Zhang, X., Wang, K., He, J., Leung, L. R., Fan, J.-W., and Nenes,
A.: Incorporating an advanced aerosol activation parameterization into
WRF-CAM5: Model evaluation and parameterization intercomparison, J. Geophys.
Res.-Atmos., 120, 6952–6979, https://doi.org/10.1002/2014JD023051, 2015b.
Zhang, Y., Zhang, X., Wang, L., Zhang, Q., Duan, F., and He, K.: Application
of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison
with MM5/CMAQ, Atmos. Environ., 124, 285–300, 2016a.
Zhang, Y., Hong, C.-P., Yahya, K., Li, Q., Zhang, Q., and He, K.-B.:
Comprehensive evaluation of multi-year real-time air quality forecasting
using an online-coupled meteorology-chemistry model over southeastern United
States, Atmos. Environ., 138, 162–182, https://doi.org/10.1016/j.atmosenv.2016.05.006,
2016b.
Zhang, Y., Wang, K., and He, J.: Multi-year application of WRF-CAM5 over East
Asia-Part II: Interannual variability, trend analysis, and aerosol indirect
effects, Atmos. Environ., 165, 222–239, 2017.
Zhang, Y., Jena, C., Wang, K., Paton-Walsh, C., Guérette, E.-A.,
Utembe, S., Silver, J. D., and Keywood, M.: Multiscale applications of two
online-coupled meteorology-chemistry models during recent field campaigns in
Australia, Part I: Model description and WRF/Chem-ROMS evaluation using
surface and satellite data and sensitivity to spatial grid resolutions,
Atmosphere, 10, 189, https://doi.org/10.3390/atmos10040189, 2019.
Zheng, B., Zhang, Q., Zhang, Y., He, K. B., Wang, K., Zheng, G. J., Duan, F. K., Ma, Y. L., and Kimoto, T.: Heterogeneous chemistry: a mechanism missing in current models to explain secondary inorganic aerosol formation during the January 2013 haze episode in North China, Atmos. Chem. Phys., 15, 2031–2049, https://doi.org/10.5194/acp-15-2031-2015, 2015.
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.
The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has...
