Articles | Volume 14, issue 20
https://doi.org/10.5194/acp-14-11247-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-14-11247-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Oct 2014
Research article |
| 24 Oct 2014
Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF–CMAQ: model description, development, evaluation and regional analysis
Research Center for Air Pollution and Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P.R. China
R. Mathur
Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
J. Pleim
Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
D. Wong
Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
R. Gilliam
Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
K. Alapaty
Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
C. Zhao
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
now at: Department of Atmospheric Science, University of Wyoming, Laramie, WY 82071, USA
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Johannes Mülmenstädt, Edward Gryspeerdt, Sudhakar Dipu, Johannes Quaas, Andrew S. Ackerman, Ann M. Fridlind, Florian Tornow, Susanne E. Bauer, Andrew Gettelman, Yi Ming, Youtong Zheng, Po-Lun Ma, Hailong Wang, Kai Zhang, Matthew W. Christensen, Adam C. Varble, L. Ruby Leung, Xiaohong Liu, David Neubauer, Daniel G. Partridge, Philip Stier, and Toshihiko Takemura
Atmos. Chem. Phys., 24, 7331–7345, https://doi.org/10.5194/acp-24-7331-2024, https://doi.org/10.5194/acp-24-7331-2024, 2024
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Human activities release copious amounts of small particles called aerosols into the atmosphere. These particles change how much sunlight clouds reflect to space, an important human perturbation of the climate, whose magnitude is highly uncertain. We found that the latest climate models show a negative correlation but a positive causal relationship between aerosols and cloud water. This means we need to be very careful when we interpret observational studies that can only see correlation.
Hao Wang, Xiaohong Liu, Chenglai Wu, and Guangxing Lin
Atmos. Chem. Phys., 24, 3309–3328, https://doi.org/10.5194/acp-24-3309-2024, https://doi.org/10.5194/acp-24-3309-2024, 2024
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We quantified different global- and regional-scale drivers of biogenic volatile organic compound (BVOC) emission trends over the past 20 years. The results show that global greening trends significantly boost BVOC emissions and deforestation reduces BVOC emissions in South America and Southeast Asia. Elevated temperature in Europe and increased soil moisture in East and South Asia enhance BVOC emissions. The results deepen our understanding of long-term BVOC emission trends in hotspots.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
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Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev., 16, 6087–6125, https://doi.org/10.5194/gmd-16-6087-2023, https://doi.org/10.5194/gmd-16-6087-2023, 2023
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We implemented an alternative aerosol scheme in the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. This development enables the comparison of different aerosol schemes with different complexity in the same model framework. It identifies improvements compared to a range of observations in both the troposphere and stratosphere.
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
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A primary sink of air pollutants is dry deposition. Dry deposition estimates differ across the models used to simulate atmospheric chemistry. Here, we introduce an effort to examine dry deposition schemes from atmospheric chemistry models. We provide our approach’s rationale, document the schemes, and describe datasets used to drive and evaluate the schemes. We also launch the analysis of results by evaluating against observations and identifying the processes leading to model–model differences.
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
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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
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Under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in the widely used CMAQ model. The results illustrate how these tools can provide insights into similarities and differences between the two CMAQ dry deposition options that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
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
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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.
Hongxia Zhu, Rui Li, Shuping Yang, Chun Zhao, Zhe Jiang, and Chen Huang
Atmos. Chem. Phys., 23, 2421–2437, https://doi.org/10.5194/acp-23-2421-2023, https://doi.org/10.5194/acp-23-2421-2023, 2023
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The impacts of atmospheric dust aerosols and cloud dynamic conditions on precipitation vertical development in southeastern China were studied using multiple satellite observations. It was found that the precipitating drops under dusty conditions grow faster in the middle layer but slower in the upper and lower layers compared with their pristine counterparts. Quantitative estimation of the sensitivity of the precipitation top temperature to the dust aerosol optical depth is also provided.
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
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A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.
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
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A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF) convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the KF scheme on simulations with and without LTA are assessed. The model's performance is improved significantly by LTA, but it is sensitive to various factors.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
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This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Xueyin Ruan, Chun Zhao, Rahul A. Zaveri, Pengzhen He, Xinming Wang, Jingyuan Shao, and Lei Geng
Geosci. Model Dev., 15, 6143–6164, https://doi.org/10.5194/gmd-15-6143-2022, https://doi.org/10.5194/gmd-15-6143-2022, 2022
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Accurate prediction of aerosol pH in chemical transport models is essential to aerosol modeling. This study examines the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) on aerosol pH predictions and the sensitivities to emissions of nonvolatile cations and NH3, aerosol-phase state assumption, and heterogeneous sulfate production. Temporal evolution of aerosol pH during haze cycles in Beijing and the driving factors are also presented and discussed.
Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
Atmos. Chem. Phys., 22, 9129–9160, https://doi.org/10.5194/acp-22-9129-2022, https://doi.org/10.5194/acp-22-9129-2022, 2022
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Here we analyze the effective aerosol forcing simulated by E3SM version 1 using both century-long free-running and short nudged simulations. The aerosol forcing in E3SMv1 is relatively large compared to other models, mainly due to the large indirect aerosol effect. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 have a strong correlation. The aerosol forcing estimates in E3SMv1 are sensitive to the parameterization changes in both liquid and ice cloud processes.
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
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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.
Susannah M. Burrows, Richard C. Easter, Xiaohong Liu, Po-Lun Ma, Hailong Wang, Scott M. Elliott, Balwinder Singh, Kai Zhang, and Philip J. Rasch
Atmos. Chem. Phys., 22, 5223–5251, https://doi.org/10.5194/acp-22-5223-2022, https://doi.org/10.5194/acp-22-5223-2022, 2022
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Sea spray particles are composed of a mixture of salts and organic substances from oceanic microorganisms. In prior work, our team developed an approach connecting sea spray chemistry to ocean biology, called OCEANFILMS. Here we describe its implementation within an Earth system model, E3SM. We show that simulated sea spray chemistry is consistent with observed seasonal cycles and that sunlight reflected by simulated Southern Ocean clouds increases, consistent with analysis of satellite data.
Jiandong Wang, Jia Xing, Shuxiao Wang, Rohit Mathur, Jiaping Wang, Yuqiang Zhang, Chao Liu, Jonathan Pleim, Dian Ding, Xing Chang, Jingkun Jiang, Peng Zhao, Shovan Kumar Sahu, Yuzhi Jin, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 22, 5147–5156, https://doi.org/10.5194/acp-22-5147-2022, https://doi.org/10.5194/acp-22-5147-2022, 2022
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Aerosols reduce surface solar radiation and change the photolysis rate and planetary boundary layer stability. In this study, the online coupled meteorological and chemistry model was used to explore the detailed pathway of how aerosol direct effects affect secondary inorganic aerosol. The effects through the dynamics pathway act as an equally or even more important route compared with the photolysis pathway in affecting secondary aerosol concentration in both summer and winter.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Yang Shi, Xiaohong Liu, Mingxuan Wu, Xi Zhao, Ziming Ke, and Hunter Brown
Atmos. Chem. Phys., 22, 2909–2935, https://doi.org/10.5194/acp-22-2909-2022, https://doi.org/10.5194/acp-22-2909-2022, 2022
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We perform a modeling study to evaluate the contribution to Arctic dust loading and ice-nucleating particle (INP) population from high-latitude local and low-latitude dust. High-latitude dust has a large contribution in the lower troposphere, while low-latitude dust dominates the upper troposphere. The high-latitude dust INPs result in a net cooling effect on the Arctic surface by glaciating mixed-phase clouds. Our results highlight the contribution of high-latitude dust to the Arctic climate.
Xi Zhao and Xiaohong Liu
Atmos. Chem. Phys., 22, 2585–2600, https://doi.org/10.5194/acp-22-2585-2022, https://doi.org/10.5194/acp-22-2585-2022, 2022
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The goal of this study is to investigate the relative importance and interactions of primary and secondary ice production in the Arctic mixed-phase clouds. Our results show that the SIP is not only a result of ice crystals produced from ice nucleation, but also competes with the ice production; conversely, strong ice nucleation also suppresses SIP.
Ka Ming Fung, Colette L. Heald, Jesse H. Kroll, Siyuan Wang, Duseong S. Jo, Andrew Gettelman, Zheng Lu, Xiaohong Liu, Rahul A. Zaveri, Eric C. Apel, Donald R. Blake, Jose-Luis Jimenez, Pedro Campuzano-Jost, Patrick R. Veres, Timothy S. Bates, John E. Shilling, and Maria Zawadowicz
Atmos. Chem. Phys., 22, 1549–1573, https://doi.org/10.5194/acp-22-1549-2022, https://doi.org/10.5194/acp-22-1549-2022, 2022
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Understanding the natural aerosol burden in the preindustrial era is crucial for us to assess how atmospheric aerosols affect the Earth's radiative budgets. Our study explores how a detailed description of dimethyl sulfide (DMS) oxidation (implemented in the Community Atmospheric Model version 6 with chemistry, CAM6-chem) could help us better estimate the present-day and preindustrial concentrations of sulfate and other relevant chemicals, as well as the resulting aerosol radiative impacts.
Xiaodong Wang, Chun Zhao, Mingyue Xu, Qiuyan Du, Jianqiu Zheng, Yun Bi, Shengfu Lin, and Yali Luo
Geosci. Model Dev., 15, 199–218, https://doi.org/10.5194/gmd-15-199-2022, https://doi.org/10.5194/gmd-15-199-2022, 2022
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Regional models are widely used to investigate aerosol climatic impacts. However, there are few studies examining the sensitivities of modeling results to regional domain size. In this study, the regional model is used to study the aerosol impacts on the East Asian summer monsoon system and focus on the modeling sensitivities to domain size. This study highlights the important impacts of domain size on regional modeling results of aerosol climatic impacts, which may not be limited to East Asia.
Amir H. Souri, Kelly Chance, Juseon Bak, Caroline R. Nowlan, Gonzalo González Abad, Yeonjin Jung, David C. Wong, Jingqiu Mao, and Xiong Liu
Atmos. Chem. Phys., 21, 18227–18245, https://doi.org/10.5194/acp-21-18227-2021, https://doi.org/10.5194/acp-21-18227-2021, 2021
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The global pandemic is believed to have an impact on emissions of air pollutants such as nitrogen dioxide (NO2) and formaldehyde (HCHO). This study quantifies the changes in the amount of NOx and VOC emissions via state-of-the-art inverse modeling technique using satellite observations during the lockdown 2020 with respect to a baseline over Europe, which in turn, it permits unraveling atmospheric processes being responsible for ozone formation in a less cloudy month.
Zhonghua Zheng, Matthew West, Lei Zhao, Po-Lun Ma, Xiaohong Liu, and Nicole Riemer
Atmos. Chem. Phys., 21, 17727–17741, https://doi.org/10.5194/acp-21-17727-2021, https://doi.org/10.5194/acp-21-17727-2021, 2021
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Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
Kai Wang, Yang Zhang, Shaocai Yu, David C. Wong, Jonathan Pleim, Rohit Mathur, James T. Kelly, and Michelle Bell
Geosci. Model Dev., 14, 7189–7221, https://doi.org/10.5194/gmd-14-7189-2021, https://doi.org/10.5194/gmd-14-7189-2021, 2021
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The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has been applied to the long-term predictions of regional meteorology and air quality over the US. The model results show superior performance and importance of chemistry–meteorology feedbacks when compared to the offline coupled WRF and CMAQ simulations, which suggests that feedbacks should be considered along with other factors in developing future model applications to inform policy making.
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
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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
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This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Mingshuai Zhang, Chun Zhao, Yuhan Yang, Qiuyan Du, Yonglin Shen, Shengfu Lin, Dasa Gu, Wenjing Su, and Cheng Liu
Geosci. Model Dev., 14, 6155–6175, https://doi.org/10.5194/gmd-14-6155-2021, https://doi.org/10.5194/gmd-14-6155-2021, 2021
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Biogenic volatile organic compounds (BVOCs) can influence atmospheric chemistry and secondary pollutant formation. This study examines the performance of different versions of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in modeling BVOCs and ozone and their sensitivities to vegetation distributions over eastern China. The results suggest more accurate vegetation distribution and measurements of BVOC emission fluxes are needed to reduce the uncertainties.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation. Part 2: Multiple aerosol types, J. Geophys. Res., 105, 6837–6844, 2000.
Abdul-Razzak, H. and Ghan, S. J.: A Parameterization of Aerosol Activation. 3. Sectional Representation, J. Geophys. Res., 107, 4026, https://doi.org/10.1029/2001JD000483, 2002.
Abdul-Razzak, H., Ghan, S. J., and Rivera-Carpio, C.: A parameterization of aerosol activation. Part I: Single aerosol type, J. Geophys. Res., 103, 6123–6132, 1998.
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.
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, 1989.
Barnes, W. L., Pagano, T. S., and Salomonson, V. V.: Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1, IEEE T. Geosci. Remote, 36, 1088–1100, 1998.
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res., 106, 23073–23096, 2001.
Bhave, P. V., Roselle, S. J., Binkowski, F. S., Nolte, C. G., Yu, S. C., Gipson, G. L., and Schere, K. L.: CMAQ aerosol module development: Recent enhancements and future plans, paper presented at 3rd Annual CMAS Models-3 Users' Conference, Commun. Model. and Anal. Syst. Cent., Chapel Hill, N. C., 18–20 October, 2004.
Binkowski, F. S. and Roselle, S. J.: Models-3 Community Multiscale Air Quality (CMAQ) model aerosol component: 1. Model description, J. Geophys. Res., 108, 4183, https://doi.org/10.1029/2001JD001409, 2003.
Carlton, A. G., Bhave, P. V., Napelenok, S. L., Edney, E. O., Sarwar, G., Pinder, R. W., Pouliot, G. A., and Houyoux, M.: Model representation of secondary organic aerosol in CMAQv4.7., Environ. Sci. Technol., 44, 8553–8560, 2010.
Cerveny, R. S. and Bailing Jr., R. C.: 1998.Weekly cycles of air pollutants, precipitation and tropical cyclones in the coastal NW Atlantic region, Nature, 394, 561–563, 1998.
Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley, Jr., J. A., Hansen, J. E., and Hofmann, D. J.: Climate Forcing by Anthropogenic Aerosols, Science, 255, 5043, https://doi.org/10.1126/science.255.5043.423, 1992.
Chapman, E. G., Gustafson Jr., W. I., Easter, R. C., Barnard, J. C., Ghan, S. J., Pekour, M. S., and Fast, J. D.: Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources, Atmos. Chem. Phys., 9, 945–964, https://doi.org/10.5194/acp-9-945-2009, 2009.
Collins, W. D., Rasch, P. J., Boville, B. A., Hack, J. J., Mccaa, J. R., Williamson, D. L., Kiehl, J. T., Briegleb, B., Bitz, C., Lin, S.-J., Zhang, M., and Dai Y.: Description of the NCAR Community Atmosphere Model (CAM3.0), NCAR Technical Note, NCAR/TN-464+STR, 226 pp., 2004.
Daly, C.: Variable influence of terrain on precipitation patterns: Delineation and use of effective terrain height in PRISM, available at: http://www.ocs.orst.edu/pub/prism/docs/effectiveterrain-daly.pdf (14 October 2014), 2002.
Daly, C., Neilson, R. P., and Phillips, D. L.: A statistical-topographic model for mapping climatological precipitation over mountainous terrain, J. Appl. Meteorol., 33, 140–158, 1994.
DeFelice, T. P., Saxena, V. K., and Yu, S. C.:.On the measurements of cloud condensation nuclei (CCN) at Palmer Station, Antarctica, Atmos. Environ., 31, 4039–4044, 1997.
Eagen, R. C., Hobbs, P. V., and Radke, L. F.: Particle emissions from a large Kraft paper mill and their effects on the microstructure of warm clouds, J. App. Meteorol., 13, 535–552, 1974.
Eder, B. and Yu, S. C.: An evaluation of model performance of EPA models-3/CMAQ, Atmos. Environ., 40, 4811–4824, 2006.
Eder, B., Kang, D., Mathur, R., Pleim, J., Yu, S. C., Otte, T., and Pouliot, G.:. A performance evaluation of the national air quality forecast capability for the summer of 2007, Atmos. Environ., 43, 2312–2320, 2009.
Eder, B., Kang, D., Rao, S. T., Mathur, R., Yu, S. C., Otte, T., Schere, K., Wayland, R., Jackson, S., Davidson, P., and McQueen, J.: A demonstration of the use of national air quality forecast guidance for developing local air quality index forecasts, B. Am. Meteorol. Soc., 91, 313–326, https://doi.org/10.1175/2009BAMS2734.1, 2010.
Fu, Q.: An accurate parameterization of the solar radiative properties of cirrus clouds for climate models, J. Climate, 9, 2058–2082, 1996.
Foley, K. M., Roselle, S. J., Appel, K. W., Bhave, P. V., Pleim, J. E., Otte, T. L., Mathur, R., Sarwar, G., Young, J. O., Gilliam, R. C., Nolte, C. G., Kelly, J. T., Gilliland, A. B., and Bash, J. O.: Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7, Geosci. Model Dev., 3, 205–226, https://doi.org/10.5194/gmd-3-205-2010, 2010.
Ghan, S. J. and Easter, R. C.: Impact of cloud-borne aerosol representation on aerosol direct and indirect effects, Atmos. Chem. Phys., 6, 4163–4174, https://doi.org/10.5194/acp-6-4163-2006, 2006.
Ghan, S. J., Leung, L. R., Easter, R. C., and Abdul-Razzak, H.: Prediction of Droplet Number in a General Circulation Model, J. Geophys. Res., 102, 21777–21794, 1997.
Ghan, S. J., Easter, R. C., Chapman, E. G., Abdul-Razzak, H., Zhang, Y., and Leung, L. R., Laulainen, N. S., Saylor, R. D., and Zaveri, R. A.: A Physically Based Estimate of Radiative Forcing by Anthropogenic Sulfate Aerosol, J. Geophys. Res-Atmos., 106, 5279–5293, 2001a.
Ghan, S., Laulainen, N., Easter, R., Wagener, R., Nemesure, S., Chapman, E., Zhang, Y., and Leung, R.: Evaluation of Aerosol Direct Radiative Forcing in MIRAGE, J. Geophys. Res.-Atmos., 106, 5295–5316, 2001b.
Ghan, S. J., Easter, R. C., Hudson, J., and Breon, F.-M.: Evaluation of Aerosol Indirect Radiative Forcing in MIRAGE, J. Geophys. Res.-Atmos., 106, 5317–5334, 2001c.
Grabowski, W. W.: Indirect impact of atmospheric aerosols in idealized simulations of convective-radiative quasi equilibrium, J. Climate, 19, 4664–4682, 2006.
Granier, C. and Brasseur, G.: Ozone and other trace gases in the Arctic and Antarctic regions: Three-dimensional model simulations, J. Geophys. Res., 96, 2995–3011, https://doi.org/10.1029/90JD01779, 1991.
Grell, G. and Devenyi, D.: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques, Geophys. Res. Lett., 29, 1693–1697, https://doi.org/10.1029/2002GL015311, 2002.
Grell, G. A., Emeis, S., Stockwell, W. R., Schoenemeyer, T., Forkel, R., Michalakes, J., Knoche, R., and Seidl, W.: Application of a multiscale, coupled MM5/chemistry model to the complex terrain of the VOTALP valley campaign, Atmos. Environ. 34, 1435–1453, 2000.
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.
Gustafson Jr., W. I., Chapman, E. G., Ghan, S. J., Easter, R. C., and Fast, J. D.: Impact on Modeled Cloud Characteristics Due to Simplified Treatment of Uniform Cloud Condensation Nuclei During NEAQS 2004, Geophys. Res. Lett., 34, L19809, https://doi.org/10.1029/2007GL030021, 2007.
Gustafson Jr., W. I. and Yu, S. C.: Generalized approach for using unbiased symmetric metrics with negative values: normalized mean bias factor and normalized mean absolute error factor, Atmos. Sci. Lett., 13, 262–267, https://doi.org/10.1002/asl.393, 2012.
Han, Q., Rossow, W. B., and Lacis, A. A.: Near-global survey of effective droplet radii in liquid water clouds using ISCCP data, J. Climate, 7, 465–497, https://doi.org/10.1175/1520-0442(1994)0072.0.CO;2, 1994.
Hanel, G.: The properties of atmospheric aerosol particles as functions of the Relative humidityat thermodynamic equilibrium with the surrounding moist air, Adv. Geophys., 19, 73–188, 1976.
Hansen, J., Sato, M., and Ruedy, R.: Radiative Forcing and Climate Response, J. Geophys. Res., 102, 6831–6864, 1997.
Harrison, E. F., Minnis, P., Barkstrom, B. R., Ramanathan, V., Cess, R. D., and Gibson, G. G.: Seasonal Variation of Cloud Radiative Forcing Derived From the Earth Radiation Budget Experiment. J. Geophys. Res., 95, 18687–18703, https://doi.org/10.1029/JD095iD11p18687, 1990.
Hartmann, D. L. and Doelling, D.: On the net radiative effectiveness of clouds, J. Geophys. Res., 96, 869–891, 1991.
Haywood, J. and Boucher, O.: Estimates of the Direct and Indirect Radiative Forcing Due to Tropospheric Aerosols: A Review., Rev. Geophys., 38, 513–543, 2000.
Henderson, B. H., Akhtar, F., Pye, H. O. T., Napelenok, S. L., and Hutzell, W. T.: A database and tool for boundary conditions for regional air quality modeling: description and evaluation, Geosci. Model Dev., 7, 339–360, https://doi.org/10.5194/gmd-7-339-2014, 2014.
Hong, S.-Y., Juang, H.-M., and Zhao, Q.: Implementation of Prognostic Cloud Scheme for a Regional Spectral Model, Mon. Weather Rev., 126, 2621–2639, 1998.
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.
Intergovernmental Panel on Climate Change (IPCC), Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press, New York, 2007.
Isaksen, I. S. A., Granier, C., Myhre, G., Berntsen, T. K., Dalsøren, S. B., Gauss, M., Klimont, Z., Benestad, R., Bousquet, P., Collins, W., Cox, T., Eyring, V., Fowler, D., Fuzzi, S., Jöckel, P., Laj, P., Lohmann, U., Maione, M., Monks, P., Prevot, A. S. H., Raes, F., Richter, A., Rognerud, B., Schulz, M., Shindell, D., Stevenson, D. S., Storelvmo, T., Wang, W.-C., van Weele, M., Wild, M., and Wuebbles, D.: Atmospheric composition change: Climate–Chemistry interactions, Atmos. Environ., 43, 5138–5192, 2009.
Jacobson, M. Z.: Developing, coupling, and applying a gas, aerosol, transport, and radiation model to study urban and regional air pollution, Ph. D. Thesis, Department of Atmospheric Sciences, University of California, Los Angeles, 436 pp., 1994.
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, 2001a.
Jacobson, M. Z.: GATOR-GCMM: 2. A study of day- and nighttime ozone layers aloft, ozone in national parks, and weather during the SARMAP Field Campaign, J. Geophys. Res., 106, 5403–5420, 2001b.
Jacobson, M. Z.: Effects of absorption by soot inclusions within clouds and precipitation on global climate, J. Phys. Chem., 110, 6860–6873, 2006
Jauregui, E. and Romales, E.: Urban effects on convective precipitation in Mexico city, Atmos. Environ., 30, 3383–3389, 1996.
Kain, J. S.: The Kain-Fritsch convective parameterization: An update, J. Appl. Meteorol., 43, 170–181, 2004.
Kain, J. S. and Fritsch, J. M.: A one-dimensional entraining/detraining plume model and its application in convective parameterization, J. Atmos. Sci., 47, 2784–2802, 1990.
Kain, J. S. and Fritsch, J. M.: Convective parameterization for mesoscale models: The Kain-Fritcsh scheme, The representation of cumulus convection in numerical models, edited by: Emanuel, K. A. and Raymond, D. J., Amer. Meteor. Soc., 246 pp., 1993.
Khvorostyanov, V. I. and Curry, J. A.: A simple analytical model of aerosol properties with account for hygroscopic growth, Part 1, Equilibrium size spectra and CCN activity spectra, J. Geophys. Res., 104, 2163–2174, 1999.
Kiehl, J. T.: On the observed near cancellation between longwave and shortwave cloud forcing in tropical regions, J. Climate, 7, 559–656, 1994a.
Kiehl, J. T.: Sensitivity of a GCM climate simulation to differences in continental versus maritime cloud drop size, J. Geophys. Res., 99, 23107–23115, 1994b.
Kiehl, J. T. and Ramanathan, V.: Comparison of cloud forcing derived from the earth radiation budget experiment with that simulated by the NCAR community climate model, J. Geophys. Res., 95, 11679–11698, 1990.
King, S. M., Rosenoern, T., Shilling, J. E., Chen, Q., Wang, Z., Biskos, G., McKinney, K. A., Pöschl, U., and Martin, S. T.: Cloud droplet activation of mixed organic-sulfate particles produced by the photooxidation of isoprene, Atmos. Chem. Phys., 10, 3953–3964, https://doi.org/10.5194/acp-10-3953-2010, 2010.
Koehler, K. A., Kreidenweis, S. M., DeMott, P. J., Petters, M. D., Prenni, A. J., and Carrico, C. M.: Hygroscopicity and cloud droplet activation of mineral dust aerosol, Geophys. Res. Lett., 36, L08805, https://doi.org/10.1029/2009GL037348, 2009.
Kummerow, C., Barnes, W., Kozu, T., Shine, J., and Simpson, J.: The Tropical Rainfall Measuring Mission System (TRMM) sensor package, J. Atmos. Ocean. Technol., 15, 809–827, 1998.
Lauer, A., Wang, Y., Phillips, V. T. J., McNaughton, C. S., Bennartz, R., and Clarke, A. D.: Simulation marine boundary layer clouds over the eastern Pacific in a regional climate model with double-moment cloud microphysics, J. Geophys. Res., 114, D21205, https://doi.org/10.1029/2009JD012201, 2009.
Leaitch, W. R., Strapp, J. W., Wiebe, H. A., Anlauf, K. G., and Isaac, G. A.: Chemical and microphysical studies of nonprecipitating summer cloud in Ontario, Canada, J. Geophys. Res., 91, 11821–11831, 1986.
Li, Z., Niu, F., Fan, J., Liu, Y., Rosenfeld, D., and Ding Y.: The long-term impacts of aerosols on the vertical development of clouds and precipitation, Nat. Geosci., 4, 888–894, https://doi.org/10.1038/ngeo1313, 2011.
Lin, J. C., Matsui, T., Pielke Sr., R. A., and Kummerow, C.: Effects of biomass-burning-derived aerosols on precipitation and clouds in the Amazon Basin: a satellite-based empirical study, J. Geophys. Res., 111, D19204, https://doi.org/10.1029/2005JD006884, 2006.
Liu, P., Zhang, Y., Yu, S. C., and Schere, K. L.: Use of a Process Analysis Tool for Diagnostic Study on Fine Particulate Matter Predictions in the U.S. Part II: Process Analysis and Sensitivity Simulations, Atmos. Pollut. Res., 2, 61–71, 2011.
Liu, X. and Penner, J. E.: Ice nucleation parameterization for global models, Meteorol. Z., 14, 499–514, 2005.
Liu, X. and Wang, J.: How Important Is Organic Aerosol Hygroscopicity to Aerosol Indirect Forcing?, Environ. Res. Lett., 5, 044010, https://doi.org/10.1088/1748-9326/5/4/044010, 2010.
Liu, X., Penner, J. E., Ghan, S. J., and Wang, M.: Inclusion of ice microphysics in the NCAR community atmospheric model version 3 (CAM3), J. Climate, 20, 4526–4547, 2007.
Lohmann, U.: A glaciation indirect aerosol effect caused by soot aerosols, Geophys. Res. Lett., 29, 1052, https://doi.org/10.1029/2001GL014357, 2002.
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005.
Lu, M.-L. and Seinfeld, J.H.: Study of the aerosol indirect effect by large-eddy simulation of marine stratocumulus, J. Atmos. Sci., 62, 3909–3932, 2005.
Martin, G. M., Johnson, D. W., and Spice, A.: The measurement and parameterization of effective radius of droplets in warm stratiform clouds, J. Atmos. Sci., 51, 1823–1842, 1994.
Mathur, R., Yu, S. C., Kang, D., and Schere, K. L.: Assessment of the Winter-time Performance of Developmental Particulate Matter Forecasts with the Eta-CMAQ Modeling System, J. Geophys. Res., 113, D02303, https://doi.org/10.1029/2007JD008580, 2008.
Mathur, R., Pleim, J., Wong, D., Otte, T., Gilliam, R., Roselle, S., Young, J., Binkowski, F., and Xiu, A.: The WRF-CMAQ integrated on-line modeling system: development, testing and initial application, Air Pollution Modeling and Its Application XX, edited by: Steyn, D. G. and Rao, S. T., 155–159, https://doi.org/10.1007/978-90-481-3812-8, Springer, the Netherlands, 2010.
McKeen, S., Chung, S. H., Wilczak, J., Grell, G., Djalalova, I., Peckham, S., Gong, W., Bouchet, V., Moffet, R., Tang, Y., Carmichael, G. R., Mathur, R., and Yu, S. C: The evaluation of several PM2.5 forecast models using data collected during the ICARTT/NEAQS 2004 field study, J. Geophys. Res., 112, D10S20, https://doi.org/10.1029/2006JD007608, 2007.
Menon, S., Hansen, J. E., Nazarenko, L., and Luo, Y.: Climate effects of black carbon aerosols in China and India, Science, 297, 2250–2253, 2002.
Menon, S., Del Genio, A. D., Kaufman, Y. J., Koch, D., Bennartz, R., Loeb, N., and Orlikowski, D.: Analyzing signatures of aerosol-cloud interactions with satellite retrievals and the GISS GCM to constrain the aerosol indirect effect. J. Geophys. Res., 113, D14S22, https://doi.org/10.1029/2007JD009442, 2008.
Meyers, M. P., DeMott, P. J., and Cotton, W. R.: New primary ice nucleation parameterization in an explicit model, J. Appl. Meteorol., 31, 708–721, 1992.
Morrison, H. and Grabwski, W. W.: Comparison of bulk and bin warm-rain microphysics models using a kinematic framework, J. Atmos. Sci., 64, 2839–2861, 2007.
Morrison, H. and Pinto, J. O.: Intercomparison of bulk microphysics schemes in mesoscale simulations of springtime Arctic mixed-phase stratiform clouds, Mon. Weather Rev., 134, 1880–1900, 2006.
Morrison, H., Curry, J. A., and Khvorostyanov, V. I.: A new double-moment microphysics parameterization for application in cloud and climate models, Part I: Description, J. Atmos. Sci., 62, 1665–1677, 2005.
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, 2009.
Petters, M. D. and Kreidenweis, S. M.: A single parameter representation of hygroscopic growth and cloud condensation nucleus activity, Atmos. Chem. Phys., 7, 1961–1971, https://doi.org/10.5194/acp-7-1961-2007, 2007.
Phillips, V. T. J., DeMott, P. J., and Andronache, C.: An Empirical Parameterization of Heterogeneous Ice Nucleation for Multiple Chemical Species of Aerosol, J. Atmos. Sci., 65, 2757–2783, https://doi.org/10.1175/2007JAS2546.1, 2008.
Pleim, J. E.: A combined local and non-local closure model for the atmospheric boundary layer. Part 1: Model description and testing, J. Appl. Meteorol. Clim., 46, 1383–1395, 2007a.
Pleim, J. E.: A combined local and nonlocal closure model for the atmospheric boundary layer. Part II: application and evaluation in a mesoscale meteorological model, J. Appl. Meteorol. Clim., 46, 1396–1409, 2007b.
Pleim, J. E. and Xiu, A.: Development and testing of a surface flux and planetary boundary layer model for application in mesoscale models, J. Appl. Meteorol., 34, 16–32, 1995.
Pleim, J. E. and Xiu, A.: Development of a land surface model. Part II: Data Assimilation, J. Appl. Meteorol., 42, 1811–1822, 2003.
Pleim, J., Young, J., Wong, D., Gilliam, R., Otte, T., and Mathur, R.: Two-Way Coupled Meteorology and Air Quality Modeling, Air Pollution Modeling and Its Application XIX, edited by: Borrego, C. and Miranda, A. I., 496–504, ISBN 978-1-4020-8452-2, Springer, the Netherlands, 2008.
Prenni, A. J., Petters, M. D., Kreidenweis, S. M., DeMott, P. J., and Ziemann, P. J.: Cloud droplet activation of secondary organic aerosol, J. Geophys. Res., 112, D10223, https://doi.org/10.1029/2006JD007963, 2007.
Pruppacher, H. R. and Klett, J. D.: Microphysics of Clouds and Precipitation, 2 Edn., Kluwer Academic Publishers, Dordrecht, the Netherlands, 954 pp., 1997.
Ramanathan, V., Crutzen, P. J., Kiehl, J. T., and Rosenfeld, D.: Aerosols, Climate and the Hydrological Cycle, Science, 294, 2119–2124, 2001.
Randall, D. A.: Parameterizing fractional cloudiness produced by cumulus entrainment. Preprints, Workshop on Cloud Microphysics Parameterizations in Global Atmospheric Circulation Models, Kananaskis, AB, Canada, WMO, 1–16, 1995.
Rasch, P. J., Barth, M. C., Kiehl, J. T., Schwartz, S. E., and Benkovitz, C. M.: A description of the global sulfur cycle and its controlling processes in the National Center for Atmospheric Research Community Climate Model Version 3, J. Geophys. Res., 105, 1367–1385, 2000.
Rotstayn, L.: Indirect forcing by anthropogenic aerosols: A global climate model calculation of the effective-radius and cloud-lifetime effects, J. Geophys. Res, 104, 9369–9380, 1999.
Rosenfeld, D.: TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall, Geophys. Res. Lett., 26, 3105–3108, 1999.
Rosenfeld, D.: Suppression of rain and snow by urban and industrial air pollution, Science, 287, 1793–1796, https://doi.org/10.1126/science.287.5459.1793, 2000.
Rosenfeld, D., Dai, J., Yu, X., Yao, Z., Xu, X., Yang, X., and Du, C.: Inverse relations between amounts of air pollution and orographic precipitation, Science, 315, 1396–1398, https://doi.org/10.1126/science.1137949, 2007.
Rosenfeld, D., Lohmann, U., Raga, G. B., O'Dowd, C. D., Kulmala, M., Fuzzi, S., Reissell, A., and Andreae, M. O.: Flood or drought: how do aerosols affect precipitation?, Science, 321, 1309–1313, 2008.
Saide, P. E., Spak, S. N., Carmichael, G. R., Mena-Carrasco, M. A., Yang, Q., Howell, S., Leon, D. C., Snider, J. R., Bandy, A. R., Collett, J. L., Benedict, K. B., de Szoeke, S. P., Hawkins, L. N., Allen, G., Crawford, I., Crosier, J., and Springston, S. R.: Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx, Atmos. Chem. Phys., 12, 3045–3064, https://doi.org/10.5194/acp-12-3045-2012, 2012.
Saxena, V. K. and Yu, S. C.: Searching for a regional fingerprint of aerosol forcing in the southeastern US, Geophys. Res. Lett., 25, 2833–2836, 1998.
Saxena, V. K., Yu, S. C., and Anderson, J.: Impact of stratospheric volcanic aerosols on climate: Evidence of aerosol radiative forcing in the southeastern US, Atmos. Environ., 31, 4211–4221, 1997.
Seifert, A., Köhler, C., and Beheng, K. D.: Aerosol-cloud-precipitation effects over Germany as simulated by a convective-scale numerical weather prediction model, Atmos. Chem. Phys., 12, 709–725, https://doi.org/10.5194/acp-12-709-2012, 2012.
Seinfeld, J. and Pandis, S.: Atmospheric Chemistry and Physics, John Wiley & Sons, New York, NY, USA, 408–448, 1998.
Simon, H., Bhave, P. V., Swall, J. L., Frank, N. H., and Malm, W. C.: Determining the spatial and seasonal variability in OM / OC ratios across the US using multiple regression, Atmos. Chem. Phys., 11, 2933–2949, https://doi.org/10.5194/acp-11-2933-2011, 2011.
Sisler, J. F. and Malm, W. C.: Interpretation of trends of PM2.5 and reconstructed visibility from the IMPROVE Network, J. Air Waste Manage. Assoc., 50, 775–789, 2000.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A description of the advanced research WRF version 3, Technical Note TN-475+STR, NCAR, 2008.
Slingo, A.: Sensitivity of the earth's radiation budget to changes in low clouds, Nature, 343, 49–51, 1990.
Stephen, G. L.: Cloud feedbacks in the climate system: a critical review, J. Climate, 18, 237–273, 2005.
Su, W., Bodas-Salcedo, A., Xu, K.-M., and Charlock, T. P.: Comparison of the tropical radiative flux and cloud radiative effect profiles in a climate model with Clouds and the Earth's Radiant Energy System (CERES) data, J. Geophys. Res., 115, D01105, https://doi.org/10.1029/2009JD012490, 2010.
Tao, W.-K., Chen, J.-P., Li, Z., Wang, C. and Zhang, C.: Impact of aerosols on convective clouds and precipitation, Rev. Geophys., 50, RG2001, https://doi.org/10.1029/2011RG000369, 2012.
Taylor, K. E. and Penner, J. E.: Response of the climate system to atmospheric aerosols and greenhouse gases, Nature, 369, 734–737, https://doi.org/10.1038/369734a0, 1994.
Taylor, P. C.: The role of clouds: an introduction and rapporteur, Surv. Geophys., 33, 609–617, 2012.
Twomey, S.: Pollution and the Planetary Albedo, Atmos. Environ., 8, 1251–1256, 1974.
Twomey, S.: Aerosols, Clouds and Radiation, Atmos. Environ., 25, 2435–2442, 1991.
Wang, Y., Wang, M., Zhang, R., Ghan, S. J., Lin, Y., Hu, J., Pan, B., Levy, M., Jiang, J. H., and Molina, M. J.: Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model, P. Natl. Acad. Sci. USA, 111, 6894–6899, https://doi.org/10.1073/pnas.1403364111, 2014.
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.
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.
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, 2001.
Yang, Q., W. I. Gustafson Jr., Fast, J. D., Wang, H., Easter, R. C., Morrison, H., Lee, Y.-N., Chapman, E. G., Spak, S. N., and Mena-Carrasco, M. A.: Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem, Atmos. Chem. Phys., 11, 11951–11975, https://doi.org/10.5194/acp-11-11951-2011, 2011.
Yarwood, G., Rao, S., Yocke, M. and Whitten, G. Z.: Final Report – Updates to the Carbon Bond Chemical Mechanism: CB05, Rep. RT-04-00675, 246 pp., Yocke and Co., Novato, California, available at: http://www.camx.com/publ/pdfs/CB05_Final_Report_120805.pdf (last access: 15 October 2014), 2005.
Young, K. C.: Numerical-simulation of wintertime, orographic precipitation – 1. Description of model microphysics and numerical techniques, J. Atmos. Sci., 31, 1735–1748, 1974.
Yu, F., Luo, G., Liu, X., Easter, R. C., Ma, X., and Ghan, S. J.: Indirect radiative forcing by ion-mediated nucleation of aerosol, Atmos. Chem. Phys., 12, 11451–11463, https://doi.org/10.5194/acp-12-11451-2012, 2012a.
Yu, F., Luo, G., and Ma, X.: Regional and global modeling of aerosol optical properties with a size, composition, and mixing state resolved particle microphysics model, Atmos. Chem. Phys., 12, 5719–5736, https://doi.org/10.5194/acp-12-5719-2012, 2012b.
Yu, H., Kaufman, Y. J., Chin, M., Feingold, G., Remer, L. A., Anderson, T. L., Balkanski, Y., Bellouin, N., Boucher, O., Christopher, S., DeCola, P., Kahn, R., Koch, D., Loeb, N., Reddy, M. S., Schulz, M., Takemura, T., and Zhou, M.: A review of measurement-based assessments of the aerosol direct radiative effect and forcing, Atmos. Chem. Phys., 6, 613–666, https://doi.org/10.5194/acp-6-613-2006, 2006.
Yu, S. C.: The role of organic acids (formic, acetic, pyruvic and oxalic) in the formation of cloud condensation nuclei (CCN): a review, Atmos. Res., 53, 185–217, 2000.
Yu, S. C. and Zhang, Y.: An Examination of the Effects of Aerosol Chemical Composition and Size on Radiative Properties of Multi-Component Aerosols, Atmos. Clim. Sci., 1, 19–32, https://doi.org/10.4236/acs.2011.12003, 2011.
Yu, S. C., Saxena, V. K., Wenny, B. N., DeLuisi, J. J., Yue, G. K. and Petropavlovskikh, I. V.: A study of the aerosol radiative properties needed to compute direct aerosol forcing in the southeastern US, J. Geophys. Res., 105, 24739–24749, 2000.
Yu, S. C., Saxena, V. K. and Zhao, Z.: A comparison of signals of regional aerosol-induced forcing in eastern China and the southeastern United States, Geophys. Res. Lett., 28, 713–716, 2001a.
Yu, S. C., Zender, C. S. and Saxena, V. K.: Direct radiative forcing and atmospheric absorption by boundary layer aerosols in the southeastern US: model estimates on the basis of new observations, Atmos. Environ.,, 35, 3967–3977, 2001b.
Yu, S. C., Kasibhatla, P. S., Wright, D. L., Schwartz, S. E., McGraw, R., and Deng, A.: Moment-based simulation of microphysical properties of sulfate aerosols in the eastern United States: Model description, evaluation and regional analysis, J. Geophys. Res., 108, 4353, https://doi.org/10.1029/2002JD002890, 2003.
Yu, S. C., Dennis, R., Bhave, P., and Eder, B.: Primary and secondary organic aerosols over the United States: Estimates on the basis of observed organic carbon (OC) and elemental carbon (EC), and air quality modeled primary OC / EC ratios, Atmos. Environ., 38, 5257–5268, 2004.
Yu, S. C., Dennis, R., Roselle, S., Nenes, A., Walker, J., Eder, B., Schere, K., Swall, J., and Robarge, W.: An assessment of the ability of 3-D air quality models with current thermodynamic equilibrium models to predict aerosol NO3-, J. Geophys. Res., 110, D07S13, https://doi.org/10.1029/2004JD004718, 2005.
Yu, S. C., Eder, B., Dennis, R., Chu, S.-H., and Schwartz, S.: New unbiased symmetric metrics for evaluation of air quality models, Atmos. Sci. Lett., 7, 26–34, 2006.
Yu, S. C., Bhave, P. V., Dennis, R. L., and Mathur, R.: Seasonal and regional variations of primary and secondary organic aerosols over the continental United States: Semi-empirical estimates and model evaluation, Environ. Sci. Technol., 41, 4690–4697, 2007a.
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, 2007b.
Yu, S. C., Mathur, R., Schere, K., Kang, D., Pleim, J., Young, J., Tong, D., McKeen, S., and Rao, S. T.: Evaluation of real-time PM2.5 forecasts and process analysis for PM2.5 formation over the eastern U.S. using the Eta-CMAQ forecast model during the 2004 ICARTT Study, J. Geophys. Res., 113, D06204, https://doi.org/10.1029/2007JD009226, 2008.
Yu, S., Mathur, R., Pleim, J., Pouliot, G., Wong, D., Eder, B., Schere, K., Gilliam, R., and Rao, S. T.: Comparative evaluation of the impact of WRF/NMM and WRF/ARW meteorology on CMAQ simulations for PM2.5 and its related precursors during the 2006 TexAQS/GoMACCS study, Atmos. Chem. Phys., 12, 4091–4106, https://doi.org/10.5194/acp-12-4091-2012, 2012a.
Yu, S. C., Mathur, R., Pleim, J., Pouliot, G., Eder, B., Schere, K., Wong, D., Gilliam, R., and Rao, S. T.: Comparative evaluation of the impact of WRF-NMM and WRF-ARW meteorology on CMAQ simulations for O3 and related species during the 2006 TexAQS/GoMACCS campaign. Atmos. Pollut. Res., 3, 149–162, https://doi.org/10.5094/APR.2012.015, 2012b.
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., Easter, R. C., Ghan, S. J., and Abdul-Razzak, H.: Impact of Aerosol Size Representation on Modeling Aerosol-Cloud Interactions, J. Geophys. Res., 107, 4558, https://doi.org/10.1029/2001JD001549, 2002.
Zhang, Y., Wen, X.-Y., and Jang, C. J.: Simulating Climate-Chemistry-Aerosol-Cloud-Radiation Feedbacks in Continental U.S. using Online-Coupled WRF/Chem, Atmos. Environ., 44, 3568–3582, 2010a.
Zhang, Y., Liu, P., Liu, X.-H., Jacobson, M. Z., McMurry, P. H., Yu, F., Yu, S. C., and Schere, K. L.:. A comparative study of homogeneous nucleation parameterizations, part II. 3-D model simulations and evaluation, J. Geophys. Res., 115, D20213, https://doi.org/10.1029/2010JD014151, 2010b.
Zhang, Y., Chen, Y.-C., Sarwar, G., and Schere, K.: Impact of Gas-Phase Mechanisms on WRF/Chem Predictions: Mechanism Implementation and Comparative Evaluation, J. Geophys. Res., 117, D01301, https://doi.org/10.1029/2011JD015775, 2012.
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