Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3969-2021
© 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-14-3969-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States
Xiaoyang Chen
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
Kai Wang
Department of Civil and Environmental Engineering, Northeastern
University, Boston, MA 02115, USA
Daniel Tong
Department of Atmospheric, Oceanic and Earth Sciences, George Mason
University, Fairfax, VA 22030, USA
IM Systems Group, Rockville, MD 20852, USA
Pius Lee
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Center for Spatial Information Science and System, George Mason
University, Fairfax, VA 22030, USA
Youhua Tang
Center for Spatial Information Science and System, George Mason
University, Fairfax, VA 22030, USA
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Jianping Huang
National Oceanic and Atmospheric Administration/National Centers for
Environmental Prediction/Environmental Modeling Center, College Park, MD
20740, USA
IM Systems Group, Rockville, MD 20852, USA
Patrick C. Campbell
Center for Spatial Information Science and System, George Mason
University, Fairfax, VA 22030, USA
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Jeff Mcqueen
National Oceanic and Atmospheric Administration/National Centers for
Environmental Prediction/Environmental Modeling Center, College Park, MD
20740, USA
Havala O. T. Pye
Office of Research and Development, U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711, USA
Benjamin N. Murphy
Office of Research and Development, U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711, USA
Daiwen Kang
Office of Research and Development, U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711, USA
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Peeyush Khare, Jordan E. Krechmer, Jo E. Machesky, Tori Hass-Mitchell, Cong Cao, Junqi Wang, Francesca Majluf, Felipe Lopez-Hilfiker, Sonja Malek, Will Wang, Karl Seltzer, Havala O. T. Pye, Roisin Commane, Brian C. McDonald, Ricardo Toledo-Crow, John E. Mak, and Drew R. Gentner
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Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
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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
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Li Zhang, Raffaele Montuoro, Stuart A. McKeen, Barry Baker, Partha S. Bhattacharjee, Georg A. Grell, Judy Henderson, Li Pan, Gregory J. Frost, Jeff McQueen, Rick Saylor, Haiqin Li, Ravan Ahmadov, Jun Wang, Ivanka Stajner, Shobha Kondragunta, Xiaoyang Zhang, and Fangjun Li
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Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022, https://doi.org/10.5194/gmd-15-3281-2022, 2022
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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
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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.
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
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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.
Elyse A. Pennington, Karl M. Seltzer, Benjamin N. Murphy, Momei Qin, John H. Seinfeld, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 18247–18261, https://doi.org/10.5194/acp-21-18247-2021, https://doi.org/10.5194/acp-21-18247-2021, 2021
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Volatile chemical products (VCPs) are commonly used consumer and industrial items that contribute to the formation of atmospheric aerosol. We implemented the emissions and chemistry of VCPs in a regional-scale model and compared predictions with measurements made in Los Angeles. Our results reduced model bias and suggest that VCPs may contribute up to half of anthropogenic secondary organic aerosol in Los Angeles and are an important source of human-influenced particular matter in urban areas.
Kai Wang, Yang Zhang, Shaocai Yu, David C. Wong, Jonathan Pleim, Rohit Mathur, James T. Kelly, and Michelle Bell
Geosci. Model Dev., 14, 7189–7221, https://doi.org/10.5194/gmd-14-7189-2021, https://doi.org/10.5194/gmd-14-7189-2021, 2021
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The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has been applied to the long-term predictions of regional meteorology and air quality over the US. The model results show superior performance and importance of chemistry–meteorology feedbacks when compared to the offline coupled WRF and CMAQ simulations, which suggests that feedbacks should be considered along with other factors in developing future model applications to inform policy making.
Siqi Ma, Daniel Tong, Lok Lamsal, Julian Wang, Xuelei Zhang, Youhua Tang, Rick Saylor, Tianfeng Chai, Pius Lee, Patrick Campbell, Barry Baker, Shobha Kondragunta, Laura Judd, Timothy A. Berkoff, Scott J. Janz, and Ivanka Stajner
Atmos. Chem. Phys., 21, 16531–16553, https://doi.org/10.5194/acp-21-16531-2021, https://doi.org/10.5194/acp-21-16531-2021, 2021
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Predicting high ozone gets more challenging as urban emissions decrease. How can different techniques be used to foretell the quality of air to better protect human health? We tested four techniques with the CMAQ model against observations during a field campaign over New York City. The new system proves to better predict the magnitude and timing of high ozone. These approaches can be extended to other regions to improve the predictability of high-O3 episodes in contemporary urban environments.
Adrian Chappell, Nicholas Webb, Mark Hennen, Charles Zender, Philippe Ciais, Kerstin Schepanski, Brandon Edwards, Nancy Ziegler, Sandra Jones, Yves Balkanski, Daniel Tong, John Leys, Stephan Heidenreich, Robert Hynes, David Fuchs, Zhenzhong Zeng, Marie Ekström, Matthew Baddock, Jeffrey Lee, and Tarek Kandakji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-337, https://doi.org/10.5194/gmd-2021-337, 2021
Revised manuscript not accepted
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Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Our results indicate that tuning dust emission models to dust in the atmosphere has hidden dust emission modelling weaknesses and its poor performance. Our new approach will reduce uncertainty and driven by prognostic albedo improve Earth System Models of aerosol effects on future environmental change.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Geosci. Model Dev., 14, 5751–5768, https://doi.org/10.5194/gmd-14-5751-2021, https://doi.org/10.5194/gmd-14-5751-2021, 2021
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The Community Multiscale Air Quality (CMAQ) modeling system extended for hemispheric-scale applications (H-CMAQ) incorporated the satellite-constrained degassing SO2 emissions from 50 volcanos across the Northern Hemisphere. The impact on tropospheric sulfate aerosol (SO42−) is assessed for 2010. Although the considered volcanic emissions occurred at or below the middle of free troposphere (500 hPa), SO42− enhancements of more than 10 % were detected up to the top of free troposphere (250 hPa).
Andreas Tilgner, Thomas Schaefer, Becky Alexander, Mary Barth, Jeffrey L. Collett Jr., Kathleen M. Fahey, Athanasios Nenes, Havala O. T. Pye, Hartmut Herrmann, and V. Faye McNeill
Atmos. Chem. Phys., 21, 13483–13536, https://doi.org/10.5194/acp-21-13483-2021, https://doi.org/10.5194/acp-21-13483-2021, 2021
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Feedbacks of acidity and atmospheric multiphase chemistry in deliquesced particles and clouds are crucial for the tropospheric composition, depositions, climate, and human health. This review synthesizes the current scientific knowledge on these feedbacks using both inorganic and organic aqueous-phase chemistry. Finally, this review outlines atmospheric implications and highlights the need for future investigations with respect to reducing emissions of key acid precursors in a changing world.
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, https://doi.org/10.5194/gmd-14-5487-2021, 2021
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Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
Benjamin N. Murphy, Christopher G. Nolte, Fahim Sidi, Jesse O. Bash, K. Wyat Appel, Carey Jang, Daiwen Kang, James Kelly, Rohit Mathur, Sergey Napelenok, George Pouliot, and Havala O. T. Pye
Geosci. Model Dev., 14, 3407–3420, https://doi.org/10.5194/gmd-14-3407-2021, https://doi.org/10.5194/gmd-14-3407-2021, 2021
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The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical aspect of atmospheric modeling.
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
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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
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This paper details the scientific updates in the recently released CMAQ version 5.3 (and v5.3.1) and also includes operational and diagnostic evaluations of CMAQv5.3.1 against observations and the previous version of the CMAQ (v5.2.1). This work was done to improve the underlying science in CMAQ. This article is used to inform the CMAQ modeling community of the updates to the modeling system and the expected change in model performance from these updates (versus the previous model version).
Qian Shu, Benjamin Murphy, Jonathan E. Pleim, Donna Schwede, Barron H. Henderson, Havala O.T. Pye, Keith Wyat Appel, Tanvir R. Khan, and Judith A. Perlinger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-129, https://doi.org/10.5194/gmd-2021-129, 2021
Preprint withdrawn
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We have bridged the gap between dry deposition measurement and modeling by rigorous use of box and regional transport models and field measurements, but more efforts are needed. This study highlights that deviation among deposition schemes is most pronounced for small and large particles. This study better links model predictions to available real-world observations and incrementally reduces uncertainties in the magnitude of loss processes important for the lifecycle of air pollutants.
Karl M. Seltzer, Elyse Pennington, Venkatesh Rao, Benjamin N. Murphy, Madeleine Strum, Kristin K. Isaacs, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 5079–5100, https://doi.org/10.5194/acp-21-5079-2021, https://doi.org/10.5194/acp-21-5079-2021, 2021
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Volatile chemical products (VCPs) are an increasingly important source of anthropogenic reactive organic carbon emissions. Here, we develop VCPy, a new framework to model organic emissions from VCPs throughout the United States. At the national-level, VCPy emissions are broadly consistent with the US EPA’s 2017 National Emission Inventory, however county-level and categorical estimates can differ substantially. An observational evaluation indicates high fidelity in the methods employed here.
Youhua Tang, Huisheng Bian, Zhining Tao, Luke D. Oman, Daniel Tong, Pius Lee, Patrick C. Campbell, Barry Baker, Cheng-Hsuan Lu, Li Pan, Jun Wang, Jeffery McQueen, and Ivanka Stajner
Atmos. Chem. Phys., 21, 2527–2550, https://doi.org/10.5194/acp-21-2527-2021, https://doi.org/10.5194/acp-21-2527-2021, 2021
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Chemical lateral boundary condition (CLBC) impact is essential for regional air quality prediction during intrusion events. We present a model mapping Goddard Earth Observing System (GEOS) to Community Multi-scale Air Quality (CMAQ) CB05–AERO6 (Carbon Bond 5; version 6 of the aerosol module) species. Influence depends on distance from the inflow boundary and species and their regional characteristics. We use aerosol optical thickness to derive CLBCs, achieving reasonable prediction.
Xiaodan Ma, Jianping Huang, Tianliang Zhao, Cheng Liu, Kaihui Zhao, Jia Xing, and Wei Xiao
Atmos. Chem. Phys., 21, 1–16, https://doi.org/10.5194/acp-21-1-2021, https://doi.org/10.5194/acp-21-1-2021, 2021
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The present work aims at identifying and quantifying the relative contributions of the key factors in driving a rapid increase in summertime surface O3 over the North China Plain during 2013–2019. In addition to anthropogenic emission reduction and meteorological variabilities, our study highlights the importance of inclusion of aerosol absorption and scattering properties rather than aerosol abundance only in accurate assessment of aerosol radiative effect on surface O3 formation and change.
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
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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.
Mingfu Cai, Baoling Liang, Qibin Sun, Shengzhen Zhou, Xiaoyang Chen, Bin Yuan, Min Shao, Haobo Tan, and Jun Zhao
Atmos. Chem. Phys., 20, 9153–9167, https://doi.org/10.5194/acp-20-9153-2020, https://doi.org/10.5194/acp-20-9153-2020, 2020
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Cloud condensation nuclei activity in marine atmosphere affects cloud formation and the solar radiation balance over ocean. We employed advanced instruments to measure aerosol hygroscopicity and chemical composition in the northern South China Sea. Our results show that marine aerosols can be affected by local emissions or pollutants from long-range transport. Our study highlights dynamical variations in particle properties and the impact of long-range transport on this region during summertime.
Ryan Schmedding, Quazi Z. Rasool, Yue Zhang, Havala O. T. Pye, Haofei Zhang, Yuzhi Chen, Jason D. Surratt, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Allen H. Goldstein, and William Vizuete
Atmos. Chem. Phys., 20, 8201–8225, https://doi.org/10.5194/acp-20-8201-2020, https://doi.org/10.5194/acp-20-8201-2020, 2020
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Accurate model prediction of aerosol concentrations is a known challenge. It is assumed in many modeling systems that aerosols are in a homogeneously mixed phase state. It has been observed that aerosols do phase separate and can form a highly viscous organic shell with an aqueous core impacting the formation processes of aerosols. This work is a model implementation to determine an aerosol's phase state using glass transition temperature and aerosol composition.
Li Pan, HyunCheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev., 13, 2169–2184, https://doi.org/10.5194/gmd-13-2169-2020, https://doi.org/10.5194/gmd-13-2169-2020, 2020
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Compared to anthropogenic emissions, emissions from wildfires are largely uncontrolled and unpredictable. Quantitatively describing wildfire emissions and their contributions to air pollution remains a substantial challenge for air quality forecasting efforts. In this study, we test the wildfire calculation algorithm used by the National Air Quality Forecasting Capability (NAQFC) by comparison with ground, satellite and flight measurements during the Southeast Nexus (SENEX) field experiment.
Havala O. T. Pye, Athanasios Nenes, Becky Alexander, Andrew P. Ault, Mary C. Barth, Simon L. Clegg, Jeffrey L. Collett Jr., Kathleen M. Fahey, Christopher J. Hennigan, Hartmut Herrmann, Maria Kanakidou, James T. Kelly, I-Ting Ku, V. Faye McNeill, Nicole Riemer, Thomas Schaefer, Guoliang Shi, Andreas Tilgner, John T. Walker, Tao Wang, Rodney Weber, Jia Xing, Rahul A. Zaveri, and Andreas Zuend
Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, https://doi.org/10.5194/acp-20-4809-2020, 2020
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Acid rain is recognized for its impacts on human health and ecosystems, and programs to mitigate these effects have had implications for atmospheric acidity. Historical measurements indicate that cloud and fog droplet acidity has changed in recent decades in response to controls on emissions from human activity, while the limited trend data for suspended particles indicate acidity may be relatively constant. This review synthesizes knowledge on the acidity of atmospheric particles and clouds.
Quanyang Lu, Benjamin N. Murphy, Momei Qin, Peter J. Adams, Yunliang Zhao, Havala O. T. Pye, Christos Efstathiou, Chris Allen, and Allen L. Robinson
Atmos. Chem. Phys., 20, 4313–4332, https://doi.org/10.5194/acp-20-4313-2020, https://doi.org/10.5194/acp-20-4313-2020, 2020
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This research work investigates organic aerosol formation in California during the CalNex study. We update the chemical transport model with the most recent mobile-source emission data and introduce a simple parameterization for secondary organic aerosol formed from intermediate-volatility organic compounds. Our results highlight the important contribution of IVOCs to SOA production in the Los Angeles region but underscore that other uncertainties must be addressed to close the SOA mass balance.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, and Yang Zhang
Atmos. Chem. Phys., 20, 3373–3396, https://doi.org/10.5194/acp-20-3373-2020, https://doi.org/10.5194/acp-20-3373-2020, 2020
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The state-of-the-science Community Multiscale Air Quality model extended for hemispheric applications (H-CMAQ) is used to model the trans-Pacific transport which has been recognized as a potential source of air pollutants over the US. In Part 1, modeled ozone is evaluated with observations at surface, by ozonesonde and airplane, and by satellite across the Northern Hemisphere. In addition, a newly developed air mass characterization method to estimate stratospheric intrusion is presented.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Atmos. Chem. Phys., 20, 3397–3413, https://doi.org/10.5194/acp-20-3397-2020, https://doi.org/10.5194/acp-20-3397-2020, 2020
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The state-of-the-science Community Multiscale Air Quality model extended for hemispheric applications (H-CMAQ) is used to model the trans-Pacific transport which has been recognized as a potential source of air pollutants over the US. In Part 2, the higher-order decoupled direct method (HDDM) is applied to investigate the emission impacts from east Asia and the US during April 2010. Furthermore, changes in trans-Pacific transport caused by the recent emissions are examined.
Hao He, Xin-Zhong Liang, Chao Sun, Zhining Tao, and Daniel Q. Tong
Atmos. Chem. Phys., 20, 3191–3208, https://doi.org/10.5194/acp-20-3191-2020, https://doi.org/10.5194/acp-20-3191-2020, 2020
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We studied the trend of US ozone pollution from 1990 to 2015 using EPA observations and computer simulations. Observations indicated a decrease in peak ozone at noon due to regulations and a slight increase in ozone in early morning and late afternoon possibly. Our modeling system confirmed these findings and provided detailed information about ozone photochemistry. These results revealed the success of previous control measures and provide scientific evidence for the future regulations.
Siqi Ma, Xuelei Zhang, Chao Gao, Daniel Q. Tong, Aijun Xiu, Guangjian Wu, Xinyuan Cao, Ling Huang, Hongmei Zhao, Shichun Zhang, Sergio Ibarra-Espinosa, Xin Wang, Xiaolan Li, and Mo Dan
Geosci. Model Dev., 12, 4603–4625, https://doi.org/10.5194/gmd-12-4603-2019, https://doi.org/10.5194/gmd-12-4603-2019, 2019
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Dust storms are thought to be a worldwide societal issue, and numerical modeling is an effective way to help us to predict dust events. Here we present the first comprehensive evaluation of dust emission modules in four commonly used air quality models for northeastern China. The results showed that most of these models were able to capture this dust event and indicated the dust source maps should be carefully selected or replaced with a new one that is constructed with local data.
Daiwen Kang, Kristen M. Foley, Rohit Mathur, Shawn J. Roselle, Kenneth E. Pickering, and Dale J. Allen
Geosci. Model Dev., 12, 4409–4424, https://doi.org/10.5194/gmd-12-4409-2019, https://doi.org/10.5194/gmd-12-4409-2019, 2019
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This paper provides a comprehensive evaluation of the lightning production schemes in CMAQ as described in https://www.geosci-model-dev.net/12/3071/2019/gmd-12-3071-2019.html on model performance. The impact of lightning NOx from different schemes is evaluated in time and space using both ground–level network measurements and aloft (ozonesonde and aircraft) observations. These results provide users the benchmark model performance when the lightning NOx production schemes are applied.
Daiwen Kang, Kenneth E. Pickering, Dale J. Allen, Kristen M. Foley, David C. Wong, Rohit Mathur, and Shawn J. Roselle
Geosci. Model Dev., 12, 3071–3083, https://doi.org/10.5194/gmd-12-3071-2019, https://doi.org/10.5194/gmd-12-3071-2019, 2019
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Lightning strikes produce significant amount of nitrogen oxides and the resulting atmospheric chemistry causes one of the primary air pollutants, ground-level ozone, to change. In this paper, we documented the evolution of scientific updates for lightning-induced nitrogen oxides schemes in the CMAQ model. The updated observation-based schemes are good for retrospective applications, while the parameterized scheme can estimate lightning nitrogen oxides for applications without observations.
Lu Xu, Havala O. T. Pye, Jia He, Yunle Chen, Benjamin N. Murphy, and Nga Lee Ng
Atmos. Chem. Phys., 18, 12613–12637, https://doi.org/10.5194/acp-18-12613-2018, https://doi.org/10.5194/acp-18-12613-2018, 2018
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In this study, we integrate lab-in-the-field experiments, extensive ambient ground measurements, and state-of-the-art modeling to constrain the concentration of organic aerosol from biogenic monoterpenes and sesquiterpenes. Further, we show that the organic aerosol from the investigated sources accounts for roughly 20 % of the World Health Organization PM2.5 standard in the southeastern US.
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
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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.
Jun Wang, Partha S. Bhattacharjee, Vijay Tallapragada, Cheng-Hsuan Lu, Shobha Kondragunta, Arlindo da Silva, Xiaoyang Zhang, Sheng-Po Chen, Shih-Wei Wei, Anton S. Darmenov, Jeff McQueen, Pius Lee, Prabhat Koner, and Andy Harris
Geosci. Model Dev., 11, 2315–2332, https://doi.org/10.5194/gmd-11-2315-2018, https://doi.org/10.5194/gmd-11-2315-2018, 2018
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The NEMS GFS Aerosol Component (NGAC) version 2.0 for global multispecies aerosol forecast was developed at NCEP. Additional sea salt, sulfate, organic carbon, and black carbon aerosol species were included. This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been provided to meet the stakeholder's needs.
Jingqiu Mao, Annmarie Carlton, Ronald C. Cohen, William H. Brune, Steven S. Brown, Glenn M. Wolfe, Jose L. Jimenez, Havala O. T. Pye, Nga Lee Ng, Lu Xu, V. Faye McNeill, Kostas Tsigaridis, Brian C. McDonald, Carsten Warneke, Alex Guenther, Matthew J. Alvarado, Joost de Gouw, Loretta J. Mickley, Eric M. Leibensperger, Rohit Mathur, Christopher G. Nolte, Robert W. Portmann, Nadine Unger, Mika Tosca, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 2615–2651, https://doi.org/10.5194/acp-18-2615-2018, https://doi.org/10.5194/acp-18-2615-2018, 2018
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This paper is aimed at discussing progress in evaluating, diagnosing, and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models.
Havala O. T. Pye, Andreas Zuend, Juliane L. Fry, Gabriel Isaacman-VanWertz, Shannon L. Capps, K. Wyat Appel, Hosein Foroutan, Lu Xu, Nga L. Ng, and Allen H. Goldstein
Atmos. Chem. Phys., 18, 357–370, https://doi.org/10.5194/acp-18-357-2018, https://doi.org/10.5194/acp-18-357-2018, 2018
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Thermodynamic modeling revealed that some but not all measurements of ammonium-to-sulfate ratios are consistent with theory. The measurement diversity likely explains the previously reported range of results regarding the suitability of thermodynamic modeling. Despite particles being predominantly phase separated, organic–inorganic interactions resulted in increased aerosol pH and partitioning towards the particle phase for highly oxygenated organic compounds compared to traditional methods.
Youhua Tang, Mariusz Pagowski, Tianfeng Chai, Li Pan, Pius Lee, Barry Baker, Rajesh Kumar, Luca Delle Monache, Daniel Tong, and Hyun-Cheol Kim
Geosci. Model Dev., 10, 4743–4758, https://doi.org/10.5194/gmd-10-4743-2017, https://doi.org/10.5194/gmd-10-4743-2017, 2017
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In order to evaluate the data assimilation tools for regional real-time PM2.5 forecasts, we applied a 3D-Var assimilation tool to adjust the aerosol initial condition by assimilating satellite-retrieved aerosol optical depth and surface PM2.5 observations for a regional air quality model, which is compared to another assimilation method, optimal interpolation. We discuss the pros and cons of these two assimilation methods based on the comparison of their 1-month four-cycles-per-day runs.
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
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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.
Li Pan, Hyun Cheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-207, https://doi.org/10.5194/gmd-2017-207, 2017
Revised manuscript not accepted
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In this study, a system accounting for fire emissions in a chemical transport model is described. The focus of this work is to qualitatively evaluate the system's capability to capture fire signals identified by multiple observation data sets. We discuss how to use observational data correctly to filter out fire signals and synergistic use of multiple data sets together. We also address the limitations of each of the observation data sets and of the evaluation methods.
Benjamin N. Murphy, Matthew C. Woody, Jose L. Jimenez, Ann Marie G. Carlton, Patrick L. Hayes, Shang Liu, Nga L. Ng, Lynn M. Russell, Ari Setyan, Lu Xu, Jeff Young, Rahul A. Zaveri, Qi Zhang, and Havala O. T. Pye
Atmos. Chem. Phys., 17, 11107–11133, https://doi.org/10.5194/acp-17-11107-2017, https://doi.org/10.5194/acp-17-11107-2017, 2017
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We incorporate recent findings about the behavior of organic pollutants in urban airsheds into the Community Multiscale Air Quality (CMAQ) model to refine predictions of organic particulate pollution in the United States. The new techniques, which account for the volatility and ongoing chemistry of airborne organic compounds, substantially reduce biases, particularly in the winter time and near emission sources.
Min Huang, Gregory R. Carmichael, James H. Crawford, Armin Wisthaler, Xiwu Zhan, Christopher R. Hain, Pius Lee, and Alex B. Guenther
Geosci. Model Dev., 10, 3085–3104, https://doi.org/10.5194/gmd-10-3085-2017, https://doi.org/10.5194/gmd-10-3085-2017, 2017
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Various sensitivity simulations during two airborne campaigns were performed to assess the impact of different initialization methods and model resolutions on NUWRF-modeled weather states, heat fluxes, and the follow-on MEGAN isoprene emission calculations. Proper land initialization is shown to be important to the coupled weather modeling and the follow-on emission modeling, which is also critical to accurately representing other processes in air quality modeling and data assimilation.
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
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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
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The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system. The CMAQ model is used extensively throughout the world to simulate air pollutants for many purposes, including regulatory and air quality forecasting applications. This work describes the scientific updates made to the latest version of the CMAQ modeling system (CMAQv5.1) and presents an evaluation of the new model against observations and results from the previous model version.
Kathleen M. Fahey, Annmarie G. Carlton, Havala O. T. Pye, Jaemeen Baek, William T. Hutzell, Charles O. Stanier, Kirk R. Baker, K. Wyat Appel, Mohammed Jaoui, and John H. Offenberg
Geosci. Model Dev., 10, 1587–1605, https://doi.org/10.5194/gmd-10-1587-2017, https://doi.org/10.5194/gmd-10-1587-2017, 2017
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Chemical transport models (CTMs) are a crucial tool in understanding links between emissions, air quality, and climate. Only a simple description of cloud chemistry has been implemented in many of these; however, clouds play a major role in the physicochemical processing of atmospheric species. In CMAQ, EPA’s widely used CTM, the cloud code is limited to the treatment of simple chemistry. We update CMAQ clouds to consider additional chemistry and then examine regional impacts of these updates.
Shantanu H. Jathar, Matthew Woody, Havala O. T. Pye, Kirk R. Baker, and Allen L. Robinson
Atmos. Chem. Phys., 17, 4305–4318, https://doi.org/10.5194/acp-17-4305-2017, https://doi.org/10.5194/acp-17-4305-2017, 2017
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Mobile sources such as cars and trucks are large sources of pollution in cities, but it is unclear what their relative contribution to organic particle pollution is. We used a numerical model along with recent data gathered from tests performed on cars and trucks to calculate organic particle levels in southern California. We found that model calculations agreed better with measurements and gasoline cars and trucks dominated the organic particle pollution.
Nga Lee Ng, Steven S. Brown, Alexander T. Archibald, Elliot Atlas, Ronald C. Cohen, John N. Crowley, Douglas A. Day, Neil M. Donahue, Juliane L. Fry, Hendrik Fuchs, Robert J. Griffin, Marcelo I. Guzman, Hartmut Herrmann, Alma Hodzic, Yoshiteru Iinuma, José L. Jimenez, Astrid Kiendler-Scharr, Ben H. Lee, Deborah J. Luecken, Jingqiu Mao, Robert McLaren, Anke Mutzel, Hans D. Osthoff, Bin Ouyang, Benedicte Picquet-Varrault, Ulrich Platt, Havala O. T. Pye, Yinon Rudich, Rebecca H. Schwantes, Manabu Shiraiwa, Jochen Stutz, Joel A. Thornton, Andreas Tilgner, Brent J. Williams, and Rahul A. Zaveri
Atmos. Chem. Phys., 17, 2103–2162, https://doi.org/10.5194/acp-17-2103-2017, https://doi.org/10.5194/acp-17-2103-2017, 2017
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Oxidation of biogenic volatile organic compounds by NO3 is an important interaction between anthropogenic
and natural emissions. This review results from a June 2015 workshop and includes the recent literature
on kinetics, mechanisms, organic aerosol yields, and heterogeneous chemistry; advances in analytical
instrumentation; the current state NO3-BVOC chemistry in atmospheric models; and critical needs for
future research in modeling, field observations, and laboratory studies.
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
Havala O. T. Pye, Benjamin N. Murphy, Lu Xu, Nga L. Ng, Annmarie G. Carlton, Hongyu Guo, Rodney Weber, Petros Vasilakos, K. Wyat Appel, Sri Hapsari Budisulistiorini, Jason D. Surratt, Athanasios Nenes, Weiwei Hu, Jose L. Jimenez, Gabriel Isaacman-VanWertz, Pawel K. Misztal, and Allen H. Goldstein
Atmos. Chem. Phys., 17, 343–369, https://doi.org/10.5194/acp-17-343-2017, https://doi.org/10.5194/acp-17-343-2017, 2017
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We use a chemical transport model to examine how organic compounds in the atmosphere interact with water present in particles. Organic compounds themselves lead to water uptake, and organic compounds interact with water associated with inorganic compounds in the rural southeast atmosphere. Including interactions of organic compounds with water requires a treatment of nonideality to more accurately represent aerosol observations during the Southern Oxidant and Aerosol Study (SOAS) 2013.
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
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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.
Hyun Cheol Kim, Soontae Kim, Seok-Woo Son, Pius Lee, Chun-Sil Jin, Eunhye Kim, Byeong-Uk Kim, Fong Ngan, Changhan Bae, Chang-Keun Song, and Ariel Stein
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-673, https://doi.org/10.5194/acp-2016-673, 2016
Revised manuscript not accepted
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In recent years, frequent occurrence of severe haze events in East Asia is one of the most serious public concerns in this region. We demonstrate that daily pollutant transport patterns in East Asia are visible from satellite images when inspected with corresponding synoptic weather analyses. Our manuscript focuses on the possible role of meteorology, especially by the routine passages of synoptic systems, on the production and removal of regional pollution in East Asia.
Xinyi Dong, Joshua S. Fu, Kan Huang, Daniel Tong, and Guoshun Zhuang
Atmos. Chem. Phys., 16, 8157–8180, https://doi.org/10.5194/acp-16-8157-2016, https://doi.org/10.5194/acp-16-8157-2016, 2016
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The Community Multiscale Air Quality (CMAQ) model has been further developed in terms of simulating natural wind-blown dust in this study, with a series of modifications aimed at improving the model's capability to predict the emission, transport, and chemical reactions of dust aerosols. Evaluation with observations suggested improved model performance by correcting the double counting of soil moisture impact, applying source-dependent speciation profile, and implementing heterogeneous chemitry.
Cheng-Hsuan Lu, Arlindo da Silva, Jun Wang, Shrinivas Moorthi, Mian Chin, Peter Colarco, Youhua Tang, Partha S. Bhattacharjee, Shen-Po Chen, Hui-Ya Chuang, Hann-Ming Henry Juang, Jeffery McQueen, and Mark Iredell
Geosci. Model Dev., 9, 1905–1919, https://doi.org/10.5194/gmd-9-1905-2016, https://doi.org/10.5194/gmd-9-1905-2016, 2016
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Aerosols have an important effect on the Earth's climate and implications for public health. NASA has partnered with NOAA to transfer GOCART aerosol model to NCEP, enabling the first global aerosol forecasting system at NOAA/NCEP. This collaboration reflects an effective research-to-operation transition, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders and to allow the effects of aerosols on weather and climate prediction to be considered.
Matthew C. Woody, Kirk R. Baker, Patrick L. Hayes, Jose L. Jimenez, Bonyoung Koo, and Havala O. T. Pye
Atmos. Chem. Phys., 16, 4081–4100, https://doi.org/10.5194/acp-16-4081-2016, https://doi.org/10.5194/acp-16-4081-2016, 2016
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In this work, organic aerosol (OA) predictions from the volatility basis set (VBS) module in the CMAQ photochemical transport model were evaluated against routine monitoring data and measurements collected during the 2010 CalNex field study. We found that the VBS module more accurately reproduced the observed primary/secondary OA split and secondary OA (SOA) mass at the CalNex Pasadena ground site compared to the traditional CMAQ OA module but still underpredicted observed SOA by ~ 5.2 ×.
Hyun Cheol Kim, Pius Lee, Laura Judd, Li Pan, and Barry Lefer
Geosci. Model Dev., 9, 1111–1123, https://doi.org/10.5194/gmd-9-1111-2016, https://doi.org/10.5194/gmd-9-1111-2016, 2016
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Fair comparison between satellite- and modeled urban NO2 column densities is important in emission inventory evaluation and regulation policy making. This study focuses on the impact of satellite footprint resolution geometry. Since OMI NO2 pixels are too coarse to resolve fine-scale urban plumes, it may cause 20–30 % bias over major cities. We introduce approaches to adjust spatial and vertical structure (downscaling & averaging kernel), and demonstrate improved agreement between sat. and model.
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
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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
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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.
E. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618, https://doi.org/10.5194/acp-16-1603-2016, https://doi.org/10.5194/acp-16-1603-2016, 2016
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Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
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
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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.
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
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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
M. Huang, D. Tong, P. Lee, L. Pan, Y. Tang, I. Stajner, R. B. Pierce, J. McQueen, and J. Wang
Atmos. Chem. Phys., 15, 12595–12610, https://doi.org/10.5194/acp-15-12595-2015, https://doi.org/10.5194/acp-15-12595-2015, 2015
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We developed Arizona dust records in 2005-2013 using multiple surface and remote sensing observation data sets. The inter-annual variability of dust events was anticorrelated with three drought indicators (PDSI, satellite NDVI and soil moisture), and stronger dust activity was found in the afternoon than in the morning due to stronger winds and drier soil. Impact of a recent dust event accompanied by a stratospheric ozone intrusion was evaluated with various observational and modeling data sets.
H. C. Kim, P. Lee, F. Ngan, Y. Tang, H. L. Yoo, and L. Pan
Geosci. Model Dev., 8, 2959–2965, https://doi.org/10.5194/gmd-8-2959-2015, https://doi.org/10.5194/gmd-8-2959-2015, 2015
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This study focuses on the evaluation of regional air quality model's performance based on the cloud information from satellites. While cloud information is crucial in photochemistry model, the definitions of cloud fraction from model and satellite are not physically consistent. We demonstrate that improper modeling of cloud fraction is correlated with surface ozone bias, and we also show that current model cloud field might be too bright, causing an overestimation of surface ozone level.
S. H. Budisulistiorini, X. Li, S. T. Bairai, J. Renfro, Y. Liu, Y. J. Liu, K. A. McKinney, S. T. Martin, V. F. McNeill, H. O. T. Pye, A. Nenes, M. E. Neff, E. A. Stone, S. Mueller, C. Knote, S. L. Shaw, Z. Zhang, A. Gold, and J. D. Surratt
Atmos. Chem. Phys., 15, 8871–8888, https://doi.org/10.5194/acp-15-8871-2015, https://doi.org/10.5194/acp-15-8871-2015, 2015
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Isoprene epoxydiols (IEPOX) are major gas-phase products from the atmospheric oxidation of isoprene that yield secondary organic aerosol (SOA) by reactive uptake onto acidic sulfate aerosol. We report a substantial contribution of IEPOX-derived SOA to the total fine aerosol collected during summer. IEPOX-derived SOA measured by online and offline mass spectrometry techniques is correlated with acidic sulfate aerosol, demonstrating the critical role of anthropogenic emissions in its formation.
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
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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.
K. R. Baker, A. G. Carlton, T. E. Kleindienst, J. H. Offenberg, M. R. Beaver, D. R. Gentner, A. H. Goldstein, P. L. Hayes, J. L. Jimenez, J. B. Gilman, J. A. de Gouw, M. C. Woody, H. O. T. Pye, J. T. Kelly, M. Lewandowski, M. Jaoui, P. S. Stevens, W. H. Brune, Y.-H. Lin, C. L. Rubitschun, and J. D. Surratt
Atmos. Chem. Phys., 15, 5243–5258, https://doi.org/10.5194/acp-15-5243-2015, https://doi.org/10.5194/acp-15-5243-2015, 2015
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This work details the evaluation of PM2.5 carbon, VOC precursors, and OH estimated by the CMAQ photochemical transport model using routine and special measurements from the 2010 CalNex field study. Here, CMAQ and most recent emissions inventory (2011 NEI) are used to generate model PM2.5 OC estimates that are examined in novel ways including primary vs. secondary formation, fossil vs. contemporary carbon, OH and HO2 evaluation, and the relationship between key VOC precursors and SOC tracers.
P. A. Cleary, N. Fuhrman, L. Schulz, J. Schafer, J. Fillingham, H. Bootsma, J. McQueen, Y. Tang, T. Langel, S. McKeen, E. J. Williams, and S. S. Brown
Atmos. Chem. Phys., 15, 5109–5122, https://doi.org/10.5194/acp-15-5109-2015, https://doi.org/10.5194/acp-15-5109-2015, 2015
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This study examines ozone mixing ratios over Lake Michigan as measured on the Lake Express ferry, by shoreline differential optical absorption spectroscopy (DOAS) observations in southeastern Wisconsin, and as predicted by the Community Multiscale Air Quality (CMAQ) model. Over water, ozone was determined to be an average of 3.8ppb higher than shoreline observations but overpredicted by the CMAQ model by as much as 11-16ppb midday.
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
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
K. Skyllakou, B. N. Murphy, A. G. Megaritis, C. Fountoukis, and S. N. Pandis
Atmos. Chem. Phys., 14, 2343–2352, https://doi.org/10.5194/acp-14-2343-2014, https://doi.org/10.5194/acp-14-2343-2014, 2014
B. H. Henderson, F. Akhtar, H. O. T. Pye, S. L. Napelenok, and W. T. Hutzell
Geosci. Model Dev., 7, 339–360, https://doi.org/10.5194/gmd-7-339-2014, https://doi.org/10.5194/gmd-7-339-2014, 2014
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
T. Chai, H.-C. Kim, P. Lee, D. Tong, L. Pan, Y. Tang, J. Huang, J. McQueen, M. Tsidulko, and I. Stajner
Geosci. Model Dev., 6, 1831–1850, https://doi.org/10.5194/gmd-6-1831-2013, https://doi.org/10.5194/gmd-6-1831-2013, 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
K. W. Appel, G. A. Pouliot, H. Simon, G. Sarwar, H. O. T. Pye, S. L. Napelenok, F. Akhtar, and S. J. Roselle
Geosci. Model Dev., 6, 883–899, https://doi.org/10.5194/gmd-6-883-2013, https://doi.org/10.5194/gmd-6-883-2013, 2013
Related subject area
Atmospheric sciences
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models
The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Balloon drift estimation and improved position estimates for radiosondes
Challenges of constructing and selecting the "perfect" initial and boundary conditions for the LES model PALM
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective
Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
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Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Hang, and Feijuan Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-201, https://doi.org/10.5194/gmd-2023-201, 2023
Revised manuscript accepted for GMD
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In this study, we have developed a model (RF-PWV) to characterize PWV variation with altitude in the study area. The RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-215, https://doi.org/10.5194/gmd-2023-215, 2023
Revised manuscript accepted for GMD
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The paper presents a method for calculating balloon drift from historical radiosonde ascent data. This drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes, but would also work for drop sondes, ozone sondes, or any other in-situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Jelena Radovic, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-197, https://doi.org/10.5194/gmd-2023-197, 2023
Revised manuscript accepted for GMD
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The initial and boundary conditions are of crucial importance for numerical model (e.g., PALM model) validation studies and have a large influence on the model results especially in the case of studying the atmosphere of a real, complex, and densely built urban environments. Our experiments with different driving conditions for the LES model PALM show its strong dependency on them which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-214, https://doi.org/10.5194/gmd-2023-214, 2023
Revised manuscript accepted for GMD
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS), is well suited for calculating transport, as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
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Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
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It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
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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.
The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality...