Articles | Volume 12, issue 3
https://doi.org/10.5194/gmd-12-1209-2019
© Author(s) 2019. 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-12-1209-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Application of random forest regression to the calculation of gas-phase chemistry within the GEOS-Chem chemistry model v10
Christoph A. Keller
CORRESPONDING AUTHOR
NASA Global Modeling and Assimilation Office, Goddard Space Flight Center, Greenbelt, MD, USA
Universities Space Research Association, Columbia, MD, USA
Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
National Centre for Atmospheric Sciences, University of York, York, YO10 5DD, UK
Related authors
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-77, https://doi.org/10.5194/gmd-2024-77, 2024
Preprint under review for GMD
Short summary
Short summary
We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity and produces uncertainty quantification metrics. It is ideal for forecasting of atmospheric chemistry in a computationally tractable manner.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Jason L. Tackett, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1127, https://doi.org/10.5194/egusphere-2024-1127, 2024
Short summary
Short summary
We use the GEOS-Chem model to simulate aerosols over the western North Atlantic Ocean (WNAO) during the winter and summer campaigns of ACTIVATE 2020. Model results are evaluated against in situ and remote sensing measurements from two aircraft as well as ground-based and satellite observations. The improved understanding of the aerosol life cycle, composition, transport pathways, and distribution has important implications for characterizing aerosol-cloud-meteorology interactions over the WNAO.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
Short summary
Short summary
Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, William M. Putman, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, https://doi.org/10.5194/gmd-14-5977-2021, 2021
Short summary
Short summary
Atmospheric chemistry models like GEOS-Chem are versatile tools widely used in air pollution and climate studies. The simulations used in such studies can be very computationally demanding, and thus it is useful if the model can simulate a specific geographic region at a higher resolution than the rest of the globe. Here, we implement, test, and demonstrate a new variable-resolution capability in GEOS-Chem that is suitable for simulations conducted on supercomputers.
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
Short summary
Short summary
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.
Christoph A. Keller, Mathew J. Evans, K. Emma Knowland, Christa A. Hasenkopf, Sruti Modekurty, Robert A. Lucchesi, Tomohiro Oda, Bruno B. Franca, Felipe C. Mandarino, M. Valeria Díaz Suárez, Robert G. Ryan, Luke H. Fakes, and Steven Pawson
Atmos. Chem. Phys., 21, 3555–3592, https://doi.org/10.5194/acp-21-3555-2021, https://doi.org/10.5194/acp-21-3555-2021, 2021
Short summary
Short summary
This study combines surface observations and model simulations to quantify the impact of COVID-19 restrictions on air quality across the world. The presented methodology removes the confounding impacts of meteorology on air pollution. Our results indicate that surface concentrations of nitrogen dioxide, an important air pollutant emitted during the combustion of fossil fuels, declined by up to 60 % following the implementation of COVID-19 containment measures.
Sarah A. Strode, James S. Wang, Michael Manyin, Bryan Duncan, Ryan Hossaini, Christoph A. Keller, Sylvia E. Michel, and James W. C. White
Atmos. Chem. Phys., 20, 8405–8419, https://doi.org/10.5194/acp-20-8405-2020, https://doi.org/10.5194/acp-20-8405-2020, 2020
Short summary
Short summary
The 13C : 12C isotopic ratio in methane (CH4) provides information about CH4 sources, but loss of CH4 by reaction with OH and chlorine (Cl) also affects this ratio. Tropospheric Cl provides a small and uncertain sink for CH4 but has a large effect on its isotopic ratio. We use the GEOS model with several different Cl fields to test the sensitivity of methane's isotopic composition to tropospheric Cl. Cl affects the global mean, hemispheric gradient, and seasonal cycle of the isotopic ratio.
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020, https://doi.org/10.5194/gmd-13-3241-2020, 2020
Short summary
Short summary
Online coupling of meteorology and chemistry models often presents maintenance issues with hard-wired coding. We present WRF-GC, an one-way online coupling of the WRF meteorological model and GEOS-Chem atmospheric chemistry model for regional atmospheric chemistry and air quality modeling. Our coupling structure allows future versions of either parent model to be immediately integrated into WRF-GC. The WRF-GC model was able to well reproduce regional PM2.5 with greater computational efficiency.
Meghana Velegar, N. Benjamin Erichson, Christoph A. Keller, and J. Nathan Kutz
Geosci. Model Dev., 12, 1525–1539, https://doi.org/10.5194/gmd-12-1525-2019, https://doi.org/10.5194/gmd-12-1525-2019, 2019
Short summary
Short summary
We introduce a new set of algorithmic tools capable of producing scalable, low-rank decompositions of global spatiotemporal atmospheric chemistry data. By exploiting emerging randomized linear algebra algorithms, a suite of decompositions are proposed that efficiently extract the dominant features from global atmospheric chemistry at longitude, latitude, and elevation with improved interpretability. The algorithms provide a strategy for the global monitoring of atmospheric chemistry.
Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
Short summary
Short summary
We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Lu Hu, Christoph A. Keller, Michael S. Long, Tomás Sherwen, Benjamin Auer, Arlindo Da Silva, Jon E. Nielsen, Steven Pawson, Matthew A. Thompson, Atanas L. Trayanov, Katherine R. Travis, Stuart K. Grange, Mat J. Evans, and Daniel J. Jacob
Geosci. Model Dev., 11, 4603–4620, https://doi.org/10.5194/gmd-11-4603-2018, https://doi.org/10.5194/gmd-11-4603-2018, 2018
Short summary
Short summary
We present a full-year online global simulation of tropospheric chemistry at 12.5 km resolution. To the best of our knowledge, such a resolution in a state-of-the-science global simulation of tropospheric chemistry is unprecedented. This simulation will serve as the Nature Run for observing system simulation experiments to support the future geostationary satellite constellation for tropospheric chemistry, and can also be used for various air quality applications.
Sebastian D. Eastham, Michael S. Long, Christoph A. Keller, Elizabeth Lundgren, Robert M. Yantosca, Jiawei Zhuang, Chi Li, Colin J. Lee, Matthew Yannetti, Benjamin M. Auer, Thomas L. Clune, Jules Kouatchou, William M. Putman, Matthew A. Thompson, Atanas L. Trayanov, Andrea M. Molod, Randall V. Martin, and Daniel J. Jacob
Geosci. Model Dev., 11, 2941–2953, https://doi.org/10.5194/gmd-11-2941-2018, https://doi.org/10.5194/gmd-11-2941-2018, 2018
Short summary
Short summary
Global atmospheric chemical transport models are crucial tools in atmospheric science, used to address problems ranging from climate change to acid rain. GEOS-Chem High Performance (GCHP) is a new implementation of the widely used GEOS-Chem model, designed for massively parallel architectures. GCHP v11-02c is shown to be highly scalable from 6 to over 500 cores, enabling the routine simulation of global atmospheric chemistry from the surface to the stratopause at resolutions of ~50 km or finer.
Karen Yu, Christoph A. Keller, Daniel J. Jacob, Andrea M. Molod, Sebastian D. Eastham, and Michael S. Long
Geosci. Model Dev., 11, 305–319, https://doi.org/10.5194/gmd-11-305-2018, https://doi.org/10.5194/gmd-11-305-2018, 2018
Short summary
Short summary
Global simulations of atmospheric chemistry are generally conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it is unable to reproduce the GCM transport exactly. We investigate the cascade of errors associated with the off-line approach using the GEOS-5 GCM and GEOS-Chem CTM and discuss improvements in the use of archived meteorology.
Katherine R. Travis, Daniel J. Jacob, Christoph A. Keller, Shi Kuang, Jintai Lin, Michael J. Newchurch, and Anne M. Thompson
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-596, https://doi.org/10.5194/acp-2017-596, 2017
Preprint retracted
Short summary
Short summary
Models severely overestimate surface ozone in the Southeast US during summertime which has implications for the design of air quality regulations. We use a model (GEOS-Chem) to interpret ozone observations from a suite of observations taken during August–September 2013. The model is unbiased relative to observations below 1 km but is biased high at the surface. We attribute this bias to model representation error, an underestimate in low-cloud, and insufficient treatment of vertical mixing.
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-77, https://doi.org/10.5194/gmd-2024-77, 2024
Preprint under review for GMD
Short summary
Short summary
We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity and produces uncertainty quantification metrics. It is ideal for forecasting of atmospheric chemistry in a computationally tractable manner.
Ryan J. Pound, Lucy V. Brown, Mat J. Evans, and Lucy J. Carpenter
Atmos. Chem. Phys., 24, 9899–9921, https://doi.org/10.5194/acp-24-9899-2024, https://doi.org/10.5194/acp-24-9899-2024, 2024
Short summary
Short summary
Iodine-mediated loss of ozone to the ocean surface and the subsequent emission of iodine species has a large effect on the troposphere. Here we combine recent experimental insights to develop a box model of the process, which we then parameterize and incorporate into the GEOS-Chem transport model. We find that these new insights have a small impact on the total emission of iodine but significantly change its distribution.
Matthew J. Rowlinson, Mat J. Evans, Lucy J. Carpenter, Katie A. Read, Shalini Punjabi, Adedayo Adedeji, Luke Fakes, Ally Lewis, Ben Richmond, Neil Passant, Tim Murrells, Barron Henderson, Kelvin H. Bates, and Detlev Helmig
Atmos. Chem. Phys., 24, 8317–8342, https://doi.org/10.5194/acp-24-8317-2024, https://doi.org/10.5194/acp-24-8317-2024, 2024
Short summary
Short summary
Ethane and propane are volatile organic compounds emitted from human activities which help to form ozone, a pollutant and greenhouse gas, and also affect the chemistry of the lower atmosphere. Atmospheric models tend to do a poor job of reproducing the abundance of these compounds in the atmosphere. By using regional estimates of their emissions, rather than globally consistent estimates, we can significantly improve the simulation of ethane in the model and make some improvement for propane.
Gregory P. Schill, Karl D. Froyd, Daniel M. Murphy, Christina J. Williamson, Charles Brock, Tomás Sherwen, Mat J. Evans, Eric A. Ray, Eric C. Apel, Rebecca S. Hornbrook, Alan J. Hills, Jeff Peischl, Tomas B. Ryerson, Chelsea R. Thompson, Ilann Bourgeois, Donald R. Blake, Joshua P. DiGangi, and Glenn S. Diskin
EGUsphere, https://doi.org/10.5194/egusphere-2024-1399, https://doi.org/10.5194/egusphere-2024-1399, 2024
Short summary
Short summary
Using single-particle mass spectrometry, we show that trace concentrations of bromine and iodine are ubiquitous in remote tropospheric aerosol, and suggest that aerosols are an important part of the global reactive iodine budget. Comparisons to a global climate model with detailed iodine chemistry are favorable in the background atmosphere; however, the model cannot replicate our measurements near the ocean surface, in biomass burning plumes, and in the stratosphere.
Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Jason L. Tackett, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1127, https://doi.org/10.5194/egusphere-2024-1127, 2024
Short summary
Short summary
We use the GEOS-Chem model to simulate aerosols over the western North Atlantic Ocean (WNAO) during the winter and summer campaigns of ACTIVATE 2020. Model results are evaluated against in situ and remote sensing measurements from two aircraft as well as ground-based and satellite observations. The improved understanding of the aerosol life cycle, composition, transport pathways, and distribution has important implications for characterizing aerosol-cloud-meteorology interactions over the WNAO.
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
Short summary
Short summary
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.
Adedayo R. Adedeji, Stephen J. Andrews, Matthew J. Rowlinson, Mathew J. Evans, Alastair C. Lewis, Shigeru Hashimoto, Hitoshi Mukai, Hiroshi Tanimoto, Yasunori Tohjima, and Takuya Saito
Atmos. Chem. Phys., 23, 9229–9244, https://doi.org/10.5194/acp-23-9229-2023, https://doi.org/10.5194/acp-23-9229-2023, 2023
Short summary
Short summary
We use the GEOS-Chem model to interpret observations of CO, C2H6, C3H8, NOx, NOy and O3 made from Hateruma Island in 2018. The model captures many synoptic-scale events and the seasonality of most pollutants at the site but underestimates C2H6 and C3H8 during the winter. These underestimates are unlikely to be reconciled by increases in biomass burning emissions but could be reconciled by increasing the Asian anthropogenic source of C2H6 and C3H8 by factors of around 2 and 3, respectively.
Viral Shah, Daniel J. Jacob, Ruijun Dang, Lok N. Lamsal, Sarah A. Strode, Stephen D. Steenrod, K. Folkert Boersma, Sebastian D. Eastham, Thibaud M. Fritz, Chelsea Thompson, Jeff Peischl, Ilann Bourgeois, Ilana B. Pollack, Benjamin A. Nault, Ronald C. Cohen, Pedro Campuzano-Jost, Jose L. Jimenez, Simone T. Andersen, Lucy J. Carpenter, Tomás Sherwen, and Mat J. Evans
Atmos. Chem. Phys., 23, 1227–1257, https://doi.org/10.5194/acp-23-1227-2023, https://doi.org/10.5194/acp-23-1227-2023, 2023
Short summary
Short summary
NOx in the free troposphere (above 2 km) affects global tropospheric chemistry and the retrieval and interpretation of satellite NO2 measurements. We evaluate free tropospheric NOx in global atmospheric chemistry models and find that recycling NOx from its reservoirs over the oceans is faster than that simulated in the models, resulting in increases in simulated tropospheric ozone and OH. Over the U.S., free tropospheric NO2 contributes the majority of the tropospheric NO2 column in summer.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
Short summary
Short summary
Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Kelvin H. Bates, Daniel J. Jacob, Ke Li, Peter D. Ivatt, Mat J. Evans, Yingying Yan, and Jintai Lin
Atmos. Chem. Phys., 21, 18351–18374, https://doi.org/10.5194/acp-21-18351-2021, https://doi.org/10.5194/acp-21-18351-2021, 2021
Short summary
Short summary
Simple aromatic compounds (benzene, toluene, xylene) have complex gas-phase chemistry that is inconsistently represented in atmospheric models. We compile recent experimental and theoretical insights to develop a new mechanism for gas-phase aromatic oxidation that is sufficiently compact for use in multiscale models. We compare our new mechanism to chamber experiments and other mechanisms, and implement it in a global model to quantify the impacts of aromatic oxidation on tropospheric chemistry.
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, William M. Putman, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, https://doi.org/10.5194/gmd-14-5977-2021, 2021
Short summary
Short summary
Atmospheric chemistry models like GEOS-Chem are versatile tools widely used in air pollution and climate studies. The simulations used in such studies can be very computationally demanding, and thus it is useful if the model can simulate a specific geographic region at a higher resolution than the rest of the globe. Here, we implement, test, and demonstrate a new variable-resolution capability in GEOS-Chem that is suitable for simulations conducted on supercomputers.
Xuan Wang, Daniel J. Jacob, William Downs, Shuting Zhai, Lei Zhu, Viral Shah, Christopher D. Holmes, Tomás Sherwen, Becky Alexander, Mathew J. Evans, Sebastian D. Eastham, J. Andrew Neuman, Patrick R. Veres, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Thomas J. Bannan, Carl J. Percival, Ben H. Lee, and Joel A. Thornton
Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, https://doi.org/10.5194/acp-21-13973-2021, 2021
Short summary
Short summary
Halogen radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a new mechanistic description and comprehensive simulation of tropospheric halogens in a global 3-D model and compare the model results with surface and aircraft measurements. We find that halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %.
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
Short summary
Short summary
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.
Christoph A. Keller, Mathew J. Evans, K. Emma Knowland, Christa A. Hasenkopf, Sruti Modekurty, Robert A. Lucchesi, Tomohiro Oda, Bruno B. Franca, Felipe C. Mandarino, M. Valeria Díaz Suárez, Robert G. Ryan, Luke H. Fakes, and Steven Pawson
Atmos. Chem. Phys., 21, 3555–3592, https://doi.org/10.5194/acp-21-3555-2021, https://doi.org/10.5194/acp-21-3555-2021, 2021
Short summary
Short summary
This study combines surface observations and model simulations to quantify the impact of COVID-19 restrictions on air quality across the world. The presented methodology removes the confounding impacts of meteorology on air pollution. Our results indicate that surface concentrations of nitrogen dioxide, an important air pollutant emitted during the combustion of fossil fuels, declined by up to 60 % following the implementation of COVID-19 containment measures.
Mike J. Newland, Daniel J. Bryant, Rachel E. Dunmore, Thomas J. Bannan, W. Joe F. Acton, Ben Langford, James R. Hopkins, Freya A. Squires, William Dixon, William S. Drysdale, Peter D. Ivatt, Mathew J. Evans, Peter M. Edwards, Lisa K. Whalley, Dwayne E. Heard, Eloise J. Slater, Robert Woodward-Massey, Chunxiang Ye, Archit Mehra, Stephen D. Worrall, Asan Bacak, Hugh Coe, Carl J. Percival, C. Nicholas Hewitt, James D. Lee, Tianqu Cui, Jason D. Surratt, Xinming Wang, Alastair C. Lewis, Andrew R. Rickard, and Jacqueline F. Hamilton
Atmos. Chem. Phys., 21, 1613–1625, https://doi.org/10.5194/acp-21-1613-2021, https://doi.org/10.5194/acp-21-1613-2021, 2021
Short summary
Short summary
We report the formation of secondary pollutants in the urban megacity of Beijing that are typically associated with remote regions such as rainforests. This is caused by extremely low levels of nitric oxide (NO), typically expected to be high in urban areas, observed in the afternoon. This work has significant implications for how we understand atmospheric chemistry in the urban environment and thus for how to implement effective policies to improve urban air quality.
Sarah A. Strode, James S. Wang, Michael Manyin, Bryan Duncan, Ryan Hossaini, Christoph A. Keller, Sylvia E. Michel, and James W. C. White
Atmos. Chem. Phys., 20, 8405–8419, https://doi.org/10.5194/acp-20-8405-2020, https://doi.org/10.5194/acp-20-8405-2020, 2020
Short summary
Short summary
The 13C : 12C isotopic ratio in methane (CH4) provides information about CH4 sources, but loss of CH4 by reaction with OH and chlorine (Cl) also affects this ratio. Tropospheric Cl provides a small and uncertain sink for CH4 but has a large effect on its isotopic ratio. We use the GEOS model with several different Cl fields to test the sensitivity of methane's isotopic composition to tropospheric Cl. Cl affects the global mean, hemispheric gradient, and seasonal cycle of the isotopic ratio.
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020, https://doi.org/10.5194/gmd-13-3241-2020, 2020
Short summary
Short summary
Online coupling of meteorology and chemistry models often presents maintenance issues with hard-wired coding. We present WRF-GC, an one-way online coupling of the WRF meteorological model and GEOS-Chem atmospheric chemistry model for regional atmospheric chemistry and air quality modeling. Our coupling structure allows future versions of either parent model to be immediately integrated into WRF-GC. The WRF-GC model was able to well reproduce regional PM2.5 with greater computational efficiency.
Peter D. Ivatt and Mathew J. Evans
Atmos. Chem. Phys., 20, 8063–8082, https://doi.org/10.5194/acp-20-8063-2020, https://doi.org/10.5194/acp-20-8063-2020, 2020
Short summary
Short summary
We investigate the potential of using a decision tree algorithm to identify and correct the tropospheric ozone bias in a chemical transport model. We train the algorithm on 2010–2015 ground and column observation data and test the algorithm on the 2016–2017 data using the ground data as well as independent flight data. We find the algorithm is successfully able to identify and correct the bias, improving the model performance.
Katherine R. Travis, Colette L. Heald, Hannah M. Allen, Eric C. Apel, Stephen R. Arnold, Donald R. Blake, William H. Brune, Xin Chen, Róisín Commane, John D. Crounse, Bruce C. Daube, Glenn S. Diskin, James W. Elkins, Mathew J. Evans, Samuel R. Hall, Eric J. Hintsa, Rebecca S. Hornbrook, Prasad S. Kasibhatla, Michelle J. Kim, Gan Luo, Kathryn McKain, Dylan B. Millet, Fred L. Moore, Jeffrey Peischl, Thomas B. Ryerson, Tomás Sherwen, Alexander B. Thames, Kirk Ullmann, Xuan Wang, Paul O. Wennberg, Glenn M. Wolfe, and Fangqun Yu
Atmos. Chem. Phys., 20, 7753–7781, https://doi.org/10.5194/acp-20-7753-2020, https://doi.org/10.5194/acp-20-7753-2020, 2020
Short summary
Short summary
Atmospheric models overestimate the rate of removal of trace gases by the hydroxyl radical (OH). This is a concern for studies of the climate and air quality impacts of human activities. Here, we evaluate the performance of a commonly used model of atmospheric chemistry against data from the NASA Atmospheric Tomography Mission (ATom) over the remote oceans where models have received little validation. The model is generally successful, suggesting that biases in OH may be a concern over land.
Jiayue Huang, Lyatt Jaeglé, Qianjie Chen, Becky Alexander, Tomás Sherwen, Mat J. Evans, Nicolas Theys, and Sungyeon Choi
Atmos. Chem. Phys., 20, 7335–7358, https://doi.org/10.5194/acp-20-7335-2020, https://doi.org/10.5194/acp-20-7335-2020, 2020
Short summary
Short summary
Large-scale enhancements of tropospheric BrO and the depletion of surface ozone are often observed in the springtime Arctic. Here, we use a chemical transport model to examine the role of sea salt aerosol from blowing snow in explaining these phenomena. We find that our simulation can account for the spatiotemporal variability of satellite observations of BrO. However, the model has difficulty in producing the magnitude of observed ozone depletion events.
Ryan J. Pound, Tomás Sherwen, Detlev Helmig, Lucy J. Carpenter, and Mat J. Evans
Atmos. Chem. Phys., 20, 4227–4239, https://doi.org/10.5194/acp-20-4227-2020, https://doi.org/10.5194/acp-20-4227-2020, 2020
Short summary
Short summary
Ozone is an important pollutant with impacts on health and the environment. Ozone is lost to plants, land and the oceans. Loss to the ocean is slow compared to all other types of land cover and has not received as much attention. We build on previous work to more accurately model ozone loss to the ocean. We find changes in the concentration of ozone over the oceans, notably the Southern Ocean, which improves model performance.
Becky Alexander, Tomás Sherwen, Christopher D. Holmes, Jenny A. Fisher, Qianjie Chen, Mat J. Evans, and Prasad Kasibhatla
Atmos. Chem. Phys., 20, 3859–3877, https://doi.org/10.5194/acp-20-3859-2020, https://doi.org/10.5194/acp-20-3859-2020, 2020
Short summary
Short summary
Nitrogen oxides are important for the formation of tropospheric oxidants and are removed from the atmosphere mainly through the formation of nitrate. We compare observations of the oxygen isotopes of nitrate with a global model to test our understanding of the chemistry nitrate formation. We use the model to quantify nitrate formation pathways in the atmosphere and identify key uncertainties and their relevance for the oxidation capacity of the atmosphere.
Sophie L. Haslett, Jonathan W. Taylor, Mathew Evans, Eleanor Morris, Bernhard Vogel, Alima Dajuma, Joel Brito, Anneke M. Batenburg, Stephan Borrmann, Johannes Schneider, Christiane Schulz, Cyrielle Denjean, Thierry Bourrianne, Peter Knippertz, Régis Dupuy, Alfons Schwarzenböck, Daniel Sauer, Cyrille Flamant, James Dorsey, Ian Crawford, and Hugh Coe
Atmos. Chem. Phys., 19, 15217–15234, https://doi.org/10.5194/acp-19-15217-2019, https://doi.org/10.5194/acp-19-15217-2019, 2019
Short summary
Short summary
Three aircraft datasets from the DACCIWA campaign in summer 2016 are used here to show there is a background mass of pollution present in the lower atmosphere in southern West Africa. We suggest that this likely comes from biomass burning in central and southern Africa, which has been carried into the region over the Atlantic Ocean. This would have a negative health impact on populations living near the coast and may alter the impact of growing city emissions on cloud formation and the monsoon.
Tomás Sherwen, Rosie J. Chance, Liselotte Tinel, Daniel Ellis, Mat J. Evans, and Lucy J. Carpenter
Earth Syst. Sci. Data, 11, 1239–1262, https://doi.org/10.5194/essd-11-1239-2019, https://doi.org/10.5194/essd-11-1239-2019, 2019
Short summary
Short summary
Iodine plays an important role in the Earth system, as a nutrient to the biosphere and by changing the concentrations of climate and air-quality species. However, there are uncertainties on the magnitude of iodine’s role, and a key uncertainty is our understanding of iodide in the global sea-surface. Here we take a data-driven approach using a machine learning algorithm to convert a sparse set of sea-surface iodide observations into a spatially and temporally resolved dataset for use in models.
Lei Zhu, Daniel J. Jacob, Sebastian D. Eastham, Melissa P. Sulprizio, Xuan Wang, Tomás Sherwen, Mat J. Evans, Qianjie Chen, Becky Alexander, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Michael Le Breton, Thomas J. Bannan, and Carl J. Percival
Atmos. Chem. Phys., 19, 6497–6507, https://doi.org/10.5194/acp-19-6497-2019, https://doi.org/10.5194/acp-19-6497-2019, 2019
Short summary
Short summary
We quantify the effect of sea salt aerosol on tropospheric bromine chemistry with a new mechanistic description of the halogen chemistry in a global atmospheric chemistry model. For the first time, we are able to reproduce the observed levels of bromide activation from the sea salt aerosol in a manner consistent with bromine oxide radical measured from various platforms. Sea salt aerosol plays a far more complex role in global tropospheric chemistry than previously recognized.
Meghana Velegar, N. Benjamin Erichson, Christoph A. Keller, and J. Nathan Kutz
Geosci. Model Dev., 12, 1525–1539, https://doi.org/10.5194/gmd-12-1525-2019, https://doi.org/10.5194/gmd-12-1525-2019, 2019
Short summary
Short summary
We introduce a new set of algorithmic tools capable of producing scalable, low-rank decompositions of global spatiotemporal atmospheric chemistry data. By exploiting emerging randomized linear algebra algorithms, a suite of decompositions are proposed that efficiently extract the dominant features from global atmospheric chemistry at longitude, latitude, and elevation with improved interpretability. The algorithms provide a strategy for the global monitoring of atmospheric chemistry.
Xuan Wang, Daniel J. Jacob, Sebastian D. Eastham, Melissa P. Sulprizio, Lei Zhu, Qianjie Chen, Becky Alexander, Tomás Sherwen, Mathew J. Evans, Ben H. Lee, Jessica D. Haskins, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Gregory L. Huey, and Hong Liao
Atmos. Chem. Phys., 19, 3981–4003, https://doi.org/10.5194/acp-19-3981-2019, https://doi.org/10.5194/acp-19-3981-2019, 2019
Short summary
Short summary
Chlorine radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a comprehensive simulation of tropospheric chlorine in a global 3-D model, which includes explicit accounting of chloride mobilization from sea salt aerosol. We find the chlorine chemistry contributes 1.0 % of the global oxidation of methane and decreases global burdens of tropospheric ozone by 7 % and OH by 3 % through the associated bromine radical chemistry.
Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
Short summary
Short summary
We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Kate R. Smith, Peter M. Edwards, Peter D. Ivatt, James D. Lee, Freya Squires, Chengliang Dai, Richard E. Peltier, Mat J. Evans, Yele Sun, and Alastair C. Lewis
Atmos. Meas. Tech., 12, 1325–1336, https://doi.org/10.5194/amt-12-1325-2019, https://doi.org/10.5194/amt-12-1325-2019, 2019
Short summary
Short summary
Clusters of low-cost, low-power atmospheric gas sensors were built into a sensor instrument to monitor NO2 and O3 in Beijing, alongside reference instruments, aiming to improve the reliability of sensor measurements. Clustering identical sensors and using the median sensor signal was used to minimize drift over short and medium timescales. Three different machine learning techniques were used for all the sensor data in an attempt to correct for cross-interferences, which worked to some degree.
Federica Pacifico, Claire Delon, Corinne Jambert, Pierre Durand, Eleanor Morris, Mat J. Evans, Fabienne Lohou, Solène Derrien, Venance H. E. Donnou, Arnaud V. Houeto, Irene Reinares Martínez, and Pierre-Etienne Brilouet
Atmos. Chem. Phys., 19, 2299–2325, https://doi.org/10.5194/acp-19-2299-2019, https://doi.org/10.5194/acp-19-2299-2019, 2019
Short summary
Short summary
Biogenic fluxes from soil at a local and regional scale are crucial to study air pollution and climate. Here we present field measurements of soil fluxes of nitric oxide (NO) and ammonia (NH3) observed over four different land cover types, i.e. bare soil, grassland, maize field, and forest, at an inland rural site in Benin, West Africa, during the DACCIWA field campaign in
June and July 2016.
Lu Hu, Christoph A. Keller, Michael S. Long, Tomás Sherwen, Benjamin Auer, Arlindo Da Silva, Jon E. Nielsen, Steven Pawson, Matthew A. Thompson, Atanas L. Trayanov, Katherine R. Travis, Stuart K. Grange, Mat J. Evans, and Daniel J. Jacob
Geosci. Model Dev., 11, 4603–4620, https://doi.org/10.5194/gmd-11-4603-2018, https://doi.org/10.5194/gmd-11-4603-2018, 2018
Short summary
Short summary
We present a full-year online global simulation of tropospheric chemistry at 12.5 km resolution. To the best of our knowledge, such a resolution in a state-of-the-science global simulation of tropospheric chemistry is unprecedented. This simulation will serve as the Nature Run for observing system simulation experiments to support the future geostationary satellite constellation for tropospheric chemistry, and can also be used for various air quality applications.
Qianjie Chen, Tomás Sherwen, Mathew Evans, and Becky Alexander
Atmos. Chem. Phys., 18, 13617–13637, https://doi.org/10.5194/acp-18-13617-2018, https://doi.org/10.5194/acp-18-13617-2018, 2018
Short summary
Short summary
Uncertainty in the natural tropospheric sulfur cycle represents the largest source of uncertainty in radiative forcing estimates of sulfate aerosol. This study investigates the natural sulfur cycle in the marine troposphere using the GEOS-Chem model. We found that BrO is important for DMS oxidation and multiphase chemistry is important for MSA production and loss, which have implications for the yield of SO2 and MSA from DMS oxidation and the radiative effect of DMS-derived sulfate aerosol.
Prasad Kasibhatla, Tomás Sherwen, Mathew J. Evans, Lucy J. Carpenter, Chris Reed, Becky Alexander, Qianjie Chen, Melissa P. Sulprizio, James D. Lee, Katie A. Read, William Bloss, Leigh R. Crilley, William C. Keene, Alexander A. P. Pszenny, and Alma Hodzic
Atmos. Chem. Phys., 18, 11185–11203, https://doi.org/10.5194/acp-18-11185-2018, https://doi.org/10.5194/acp-18-11185-2018, 2018
Short summary
Short summary
Recent measurements of NOx and HONO suggest that photolysis of particulate nitrate in sea-salt aerosols is important in terms of marine boundary layer oxidant chemistry. We present the first global-scale assessment of the significance of this new chemical pathway for NOx, O3, and OH in the marine boundary layer. We also present a preliminary assessment of the potential impact of photolysis of particulate nitrate associated with other aerosol types on continental boundary layer chemistry.
Sebastian D. Eastham, Michael S. Long, Christoph A. Keller, Elizabeth Lundgren, Robert M. Yantosca, Jiawei Zhuang, Chi Li, Colin J. Lee, Matthew Yannetti, Benjamin M. Auer, Thomas L. Clune, Jules Kouatchou, William M. Putman, Matthew A. Thompson, Atanas L. Trayanov, Andrea M. Molod, Randall V. Martin, and Daniel J. Jacob
Geosci. Model Dev., 11, 2941–2953, https://doi.org/10.5194/gmd-11-2941-2018, https://doi.org/10.5194/gmd-11-2941-2018, 2018
Short summary
Short summary
Global atmospheric chemical transport models are crucial tools in atmospheric science, used to address problems ranging from climate change to acid rain. GEOS-Chem High Performance (GCHP) is a new implementation of the widely used GEOS-Chem model, designed for massively parallel architectures. GCHP v11-02c is shown to be highly scalable from 6 to over 500 cores, enabling the routine simulation of global atmospheric chemistry from the surface to the stratopause at resolutions of ~50 km or finer.
Mike J. Newland, Andrew R. Rickard, Tomás Sherwen, Mathew J. Evans, Luc Vereecken, Amalia Muñoz, Milagros Ródenas, and William J. Bloss
Atmos. Chem. Phys., 18, 6095–6120, https://doi.org/10.5194/acp-18-6095-2018, https://doi.org/10.5194/acp-18-6095-2018, 2018
Short summary
Short summary
Stabilised Criegee intermediates (SCIs) are formed in the reaction of alkenes with ozone, both of which are ubiquitous throughout the troposphere. We determine the fate and global distribution of SCI from monoterpene ozonolysis. One major fate of SCI is reaction with H2O, but for a fraction of SCIs, unimolecular reactions dominate. Concentrations of SCIs are high enough regionally to play a key role in the conversion of sulfur dioxide to aerosol, affecting air quality and climate.
Daniel Stone, Tomás Sherwen, Mathew J. Evans, Stewart Vaughan, Trevor Ingham, Lisa K. Whalley, Peter M. Edwards, Katie A. Read, James D. Lee, Sarah J. Moller, Lucy J. Carpenter, Alastair C. Lewis, and Dwayne E. Heard
Atmos. Chem. Phys., 18, 3541–3561, https://doi.org/10.5194/acp-18-3541-2018, https://doi.org/10.5194/acp-18-3541-2018, 2018
Short summary
Short summary
Halogen chemistry in the troposphere impacts oxidising capacity, but model studies assessing the nature of these impacts can vary according to the model framework used. In this work we present simulations of OH and HO2 radicals using both box and global model frameworks, and compare to observations made at the Cape Verde Atmospheric Observatory. We highlight, and rationalise, differences between the model frameworks.
Karen Yu, Christoph A. Keller, Daniel J. Jacob, Andrea M. Molod, Sebastian D. Eastham, and Michael S. Long
Geosci. Model Dev., 11, 305–319, https://doi.org/10.5194/gmd-11-305-2018, https://doi.org/10.5194/gmd-11-305-2018, 2018
Short summary
Short summary
Global simulations of atmospheric chemistry are generally conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it is unable to reproduce the GCM transport exactly. We investigate the cascade of errors associated with the off-line approach using the GEOS-5 GCM and GEOS-Chem CTM and discuss improvements in the use of archived meteorology.
Theodore K. Koenig, Rainer Volkamer, Sunil Baidar, Barbara Dix, Siyuan Wang, Daniel C. Anderson, Ross J. Salawitch, Pamela A. Wales, Carlos A. Cuevas, Rafael P. Fernandez, Alfonso Saiz-Lopez, Mathew J. Evans, Tomás Sherwen, Daniel J. Jacob, Johan Schmidt, Douglas Kinnison, Jean-François Lamarque, Eric C. Apel, James C. Bresch, Teresa Campos, Frank M. Flocke, Samuel R. Hall, Shawn B. Honomichl, Rebecca Hornbrook, Jørgen B. Jensen, Richard Lueb, Denise D. Montzka, Laura L. Pan, J. Michael Reeves, Sue M. Schauffler, Kirk Ullmann, Andrew J. Weinheimer, Elliot L. Atlas, Valeria Donets, Maria A. Navarro, Daniel Riemer, Nicola J. Blake, Dexian Chen, L. Gregory Huey, David J. Tanner, Thomas F. Hanisco, and Glenn M. Wolfe
Atmos. Chem. Phys., 17, 15245–15270, https://doi.org/10.5194/acp-17-15245-2017, https://doi.org/10.5194/acp-17-15245-2017, 2017
Short summary
Short summary
Tropospheric inorganic bromine (BrO and Bry) shows a C-shaped profile over the tropical western Pacific Ocean, and supports previous speculation that marine convection is a source for inorganic bromine from sea salt to the upper troposphere. The Bry profile in the tropical tropopause layer (TTL) is complex, suggesting that the total Bry budget in the TTL is not closed without considering aerosol bromide. The implications for atmospheric composition and bromine sources are discussed.
Ben Newsome and Mat Evans
Atmos. Chem. Phys., 17, 14333–14352, https://doi.org/10.5194/acp-17-14333-2017, https://doi.org/10.5194/acp-17-14333-2017, 2017
Short summary
Short summary
We explore the uncertainty in the predictions of a chemical transport model (GEOS-Chem) from uncertainty in 60 inorganic rate constants and photolysis rates. We find uncertainty in the global mean ozone burden of 10 %, in global mean OH of 16 %, methane lifetimes of 16 %, and tropospheric ozone radiative forcings of 13 %. Reductions in the uncertainty of rate constants of these simple reactions would reduce uncertainty in our understanding of atmospheric composition.
Peter M. Edwards and Mathew J. Evans
Atmos. Chem. Phys., 17, 13669–13680, https://doi.org/10.5194/acp-17-13669-2017, https://doi.org/10.5194/acp-17-13669-2017, 2017
Short summary
Short summary
Understanding tropospheric ozone chemistry has been at the centre of the field of atmospheric chemistry for the last 30 years. However, our conceptual approach to diagnosing ozone production in global models has not advanced in this time. Our work presents a new and powerful approach for diagnosing tropospheric ozone production, providing a significant enhancement in our ability to understand the processes controlling ozone and how we can validate our assessment of these processes.
Peter Knippertz, Andreas H. Fink, Adrien Deroubaix, Eleanor Morris, Flore Tocquer, Mat J. Evans, Cyrille Flamant, Marco Gaetani, Christophe Lavaysse, Celine Mari, John H. Marsham, Rémi Meynadier, Abalo Affo-Dogo, Titike Bahaga, Fabien Brosse, Konrad Deetz, Ridha Guebsi, Issaou Latifou, Marlon Maranan, Philip D. Rosenberg, and Andreas Schlueter
Atmos. Chem. Phys., 17, 10893–10918, https://doi.org/10.5194/acp-17-10893-2017, https://doi.org/10.5194/acp-17-10893-2017, 2017
Short summary
Short summary
In June–July 2016 DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa), a large, EU-funded European–African project, organised an international field campaign in densely populated southern West Africa, including measurements from ground sites, research aircraft, weather balloons and urban sites. This paper gives an overview of the atmospheric evolution during this period focusing on meteorological (precipitation, cloudiness, winds) and composition (gases, particles) aspects.
Katherine R. Travis, Daniel J. Jacob, Christoph A. Keller, Shi Kuang, Jintai Lin, Michael J. Newchurch, and Anne M. Thompson
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-596, https://doi.org/10.5194/acp-2017-596, 2017
Preprint retracted
Short summary
Short summary
Models severely overestimate surface ozone in the Southeast US during summertime which has implications for the design of air quality regulations. We use a model (GEOS-Chem) to interpret ozone observations from a suite of observations taken during August–September 2013. The model is unbiased relative to observations below 1 km but is biased high at the surface. We attribute this bias to model representation error, an underestimate in low-cloud, and insufficient treatment of vertical mixing.
Chris Reed, Mathew J. Evans, Leigh R. Crilley, William J. Bloss, Tomás Sherwen, Katie A. Read, James D. Lee, and Lucy J. Carpenter
Atmos. Chem. Phys., 17, 4081–4092, https://doi.org/10.5194/acp-17-4081-2017, https://doi.org/10.5194/acp-17-4081-2017, 2017
Short summary
Short summary
The source of ozone-depleting compounds in the remote troposphere has been thought to be long-range transport of secondary pollutants such as organic nitrates. Processing of organic nitrates to nitric acid and subsequent deposition on surfaces in the atmosphere was thought to remove these nitrates from the ozone–NOx–HOx cycle. We found through observation of NOx in the remote tropical troposphere at the Cape Verde Observatory that surface nitrates can be released back into the atmosphere.
Tomás Sherwen, Mat J. Evans, Lucy J. Carpenter, Johan A. Schmidt, and Loretta J. Mickley
Atmos. Chem. Phys., 17, 1557–1569, https://doi.org/10.5194/acp-17-1557-2017, https://doi.org/10.5194/acp-17-1557-2017, 2017
Short summary
Short summary
We model pre-industrial to present day changes using the GEOS-Chem global chemical transport model with halogens (Cl, Br, I). The model better captures pre-industrial O3 observations with halogens included. Halogens buffer the tropospheric forcing of O3 (RFTO3) from pre-industrial to present day, reducing RFTO3 by 0.087 Wm−2. This reduction is greater than that from halogens on stratospheric O3 (−0.05 Wm−2). This suggests that models that do not include halogens will overestimate RFTO3by ~ 25%.
Tomás Sherwen, Johan A. Schmidt, Mat J. Evans, Lucy J. Carpenter, Katja Großmann, Sebastian D. Eastham, Daniel J. Jacob, Barbara Dix, Theodore K. Koenig, Roman Sinreich, Ivan Ortega, Rainer Volkamer, Alfonso Saiz-Lopez, Cristina Prados-Roman, Anoop S. Mahajan, and Carlos Ordóñez
Atmos. Chem. Phys., 16, 12239–12271, https://doi.org/10.5194/acp-16-12239-2016, https://doi.org/10.5194/acp-16-12239-2016, 2016
Short summary
Short summary
We present a simulation of tropospheric Cl, Br, I chemistry within the GEOS-Chem CTM. We find a decrease in tropospheric ozone burden of 18.6 % and a 8.2 % decrease in global mean OH concentrations. Cl oxidation of some VOCs range from 15 to 27 % of the total loss. Bromine plays a small role in oxidising oVOCs. Surface ozone, ozone sondes, and methane lifetime are in general improved by the inclusion of halogens. We argue that simulated bromine and chlorine represent a lower limit.
Dene R. Bowdalo, Mathew J. Evans, and Eric D. Sofen
Atmos. Chem. Phys., 16, 8295–8308, https://doi.org/10.5194/acp-16-8295-2016, https://doi.org/10.5194/acp-16-8295-2016, 2016
Short summary
Short summary
We introduce a new methodology for the assessment of atmospheric models with observations. We apply a spectral analysis methodology to hourly ozone observations and the equivalent model output. The spectrally transformed observational data show significant peaks on daily and annual timescales. Comparison between the amplitude and phase of these peaks introduces a new comparison methodology between model and measurements. We find the model shows significant biases on an annual timescale.
Alicia Gressent, Bastien Sauvage, Daniel Cariolle, Mathew Evans, Maud Leriche, Céline Mari, and Valérie Thouret
Atmos. Chem. Phys., 16, 5867–5889, https://doi.org/10.5194/acp-16-5867-2016, https://doi.org/10.5194/acp-16-5867-2016, 2016
Short summary
Short summary
In chemical transport models, NOx emitted by lightning (LNOx) is instantaneously diluted into the grid. A plume-in-grid parameterization to account for the sub-grid chemistry of LNOx is presented. This approach was implemented into the GEOS-Chem model and leads to a relative increase of NOx and O3 (18 % and 2 %, respectively, in July) on a large scale downwind of lightning emissions and a relative decrease (25 % and 8 %, respectively, over central Africa in July) over the regions of emissions.
Chris Reed, Mathew J. Evans, Piero Di Carlo, James D. Lee, and Lucy J. Carpenter
Atmos. Chem. Phys., 16, 4707–4724, https://doi.org/10.5194/acp-16-4707-2016, https://doi.org/10.5194/acp-16-4707-2016, 2016
Short summary
Short summary
The self-cleaning capacity of the atmosphere in places like Antarctica can be measured by quantifying very low amounts of combustion products that exist in a well-known ratio. When this ratio deviates from 1 it points to the existence of unknown compounds. Several unknown compounds have been theorized to exist but never measured. We have found the method for measuring the ratio of combustion products suffers a bias in remote places, which when taken into account disproves any unknown compounds.
Frank A. F. Winiberg, Terry J. Dillon, Stephanie C. Orr, Christoph B. M Groß, Iustinian Bejan, Charlotte A. Brumby, Matthew J. Evans, Shona C. Smith, Dwayne E. Heard, and Paul W. Seakins
Atmos. Chem. Phys., 16, 4023–4042, https://doi.org/10.5194/acp-16-4023-2016, https://doi.org/10.5194/acp-16-4023-2016, 2016
Short summary
Short summary
OH radicals are important intermediates in the atmosphere, and the high concentrations observed in tropical regions are yet to be fully explained. Radical-radical reactions such as the title reaction can contribute to OH formation. This is the most fully comprehensive study of the CH3C(O)O2 + HO2 reaction with direct observation of products in all reaction channels. The implications of the new measurements on OH, PAN and NOx concentrations are considered via global models.
E. D. Sofen, D. Bowdalo, M. J. Evans, F. Apadula, P. Bonasoni, M. Cupeiro, R. Ellul, I. E. Galbally, R. Girgzdiene, S. Luppo, M. Mimouni, A. C. Nahas, M. Saliba, and K. Tørseth
Earth Syst. Sci. Data, 8, 41–59, https://doi.org/10.5194/essd-8-41-2016, https://doi.org/10.5194/essd-8-41-2016, 2016
Short summary
Short summary
We have brought together all publicly available surface ozone observations from online databases from 1971–2015, with 2200 sites representing regional background conditions appropriate for the evaluation of chemical transport and chemistry-climate models for projects such as the Chemistry-Climate Model Initiative. Gridded data sets of ozone metrics (mean, percentiles, MDA8, SOMO35, etc.) are available from the British Atmospheric Data Centre.
E. D. Sofen, D. Bowdalo, and M. J. Evans
Atmos. Chem. Phys., 16, 1445–1457, https://doi.org/10.5194/acp-16-1445-2016, https://doi.org/10.5194/acp-16-1445-2016, 2016
Short summary
Short summary
We explore the global representativeness of a global surface ozone data set from a range of perspectives (area, biomes, chemical regimes, model uncertainty, model trends). We conclude that the current network fails to provide sufficient constraints for important regions/regimes, leading to uncertainty for a range of atmospheric composition challenges. We suggest 20 new locations for making surface ozone observations, which would significantly enhance our observational capability.
T. Sherwen, M. J. Evans, L. J. Carpenter, S. J. Andrews, R. T. Lidster, B. Dix, T. K. Koenig, R. Sinreich, I. Ortega, R. Volkamer, A. Saiz-Lopez, C. Prados-Roman, A. S. Mahajan, and C. Ordóñez
Atmos. Chem. Phys., 16, 1161–1186, https://doi.org/10.5194/acp-16-1161-2016, https://doi.org/10.5194/acp-16-1161-2016, 2016
Short summary
Short summary
Using a global chemical transport model (GEOS-Chem) with additional iodine emissions, chemistry, and deposition we show that iodine is responsible for ~ 9 % of global ozone loss but has negligible impacts on global OH. Uncertainties are large in the chemistry and emissions and future research is needed in both. Measurements of iodine species (especially HOI) would be useful. We believe iodine chemistry should be considered in future chemistry-climate and in air quality modelling.
E. D. Sofen, M. J. Evans, and A. C. Lewis
Atmos. Chem. Phys., 15, 13627–13632, https://doi.org/10.5194/acp-15-13627-2015, https://doi.org/10.5194/acp-15-13627-2015, 2015
Short summary
Short summary
As an air pollutant, O3 is monitored photometrically to assess compliance with air quality legislation. A recent study found a 1.8% reduction in its absorption cross section, which would lead to an equivalent increase in observed O3 concentrations. We estimate this would increase the number of sites out of compliance with air quality regulations in the EU and US by 20%. We draw attention to how small changes in gas metrology impacts attainment and compliance with legal air quality standards.
R. E. Dunmore, J. R. Hopkins, R. T. Lidster, J. D. Lee, M. J. Evans, A. R. Rickard, A. C. Lewis, and J. F. Hamilton
Atmos. Chem. Phys., 15, 9983–9996, https://doi.org/10.5194/acp-15-9983-2015, https://doi.org/10.5194/acp-15-9983-2015, 2015
Short summary
Short summary
Technological shifts between fuel sources have had unexpected impacts on atmospheric composition and these significant changes can go undetected if source-specific monitoring infrastructure is not in place. We present chemically comprehensive, continuous measurements of organic compounds in a developed megacity (London), that show diesel-related hydrocarbons can dominate reactive carbon and ozone formation potential, highlighting a serious underestimation of this source in emission inventories.
H. M. Walker, D. Stone, T. Ingham, S. Vaughan, M. Cain, R. L. Jones, O. J. Kennedy, M. McLeod, B. Ouyang, J. Pyle, S. Bauguitte, B. Bandy, G. Forster, M. J. Evans, J. F. Hamilton, J. R. Hopkins, J. D. Lee, A. C. Lewis, R. T. Lidster, S. Punjabi, W. T. Morgan, and D. E. Heard
Atmos. Chem. Phys., 15, 8179–8200, https://doi.org/10.5194/acp-15-8179-2015, https://doi.org/10.5194/acp-15-8179-2015, 2015
L. K. Whalley, D. Stone, I. J. George, S. Mertes, D. van Pinxteren, A. Tilgner, H. Herrmann, M. J. Evans, and D. E. Heard
Atmos. Chem. Phys., 15, 3289–3301, https://doi.org/10.5194/acp-15-3289-2015, https://doi.org/10.5194/acp-15-3289-2015, 2015
D. Stone, M. J. Evans, H. Walker, T. Ingham, S. Vaughan, B. Ouyang, O. J. Kennedy, M. W. McLeod, R. L. Jones, J. Hopkins, S. Punjabi, R. Lidster, J. F. Hamilton, J. D. Lee, A. C. Lewis, L. J. Carpenter, G. Forster, D. E. Oram, C. E. Reeves, S. Bauguitte, W. Morgan, H. Coe, E. Aruffo, C. Dari-Salisburgo, F. Giammaria, P. Di Carlo, and D. E. Heard
Atmos. Chem. Phys., 14, 1299–1321, https://doi.org/10.5194/acp-14-1299-2014, https://doi.org/10.5194/acp-14-1299-2014, 2014
P. M. Edwards, M. J. Evans, K. L. Furneaux, J. Hopkins, T. Ingham, C. Jones, J. D. Lee, A. C. Lewis, S. J. Moller, D. Stone, L. K. Whalley, and D. E. Heard
Atmos. Chem. Phys., 13, 9497–9514, https://doi.org/10.5194/acp-13-9497-2013, https://doi.org/10.5194/acp-13-9497-2013, 2013
J. R. Pierce, M. J. Evans, C. E. Scott, S. D. D'Andrea, D. K. Farmer, E. Swietlicki, and D. V. Spracklen
Atmos. Chem. Phys., 13, 3163–3176, https://doi.org/10.5194/acp-13-3163-2013, https://doi.org/10.5194/acp-13-3163-2013, 2013
A. C. Lewis, M. J. Evans, J. R. Hopkins, S. Punjabi, K. A. Read, R. M. Purvis, S. J. Andrews, S. J. Moller, L. J. Carpenter, J. D. Lee, A. R. Rickard, P. I. Palmer, and M. Parrington
Atmos. Chem. Phys., 13, 851–867, https://doi.org/10.5194/acp-13-851-2013, https://doi.org/10.5194/acp-13-851-2013, 2013
Related subject area
Atmospheric sciences
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Orbital-Radar v1.0.0: A tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
New explicit formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations
Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3
The CHIMERE chemistry-transport model v2023r1
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1
Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary
Short summary
We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
Short summary
Short summary
Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
Short summary
Short summary
RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
Short summary
Short summary
We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
Short summary
We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
Short summary
Short summary
Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
Short summary
Short summary
Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
Short summary
Short summary
AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
Short summary
Short summary
Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
Short summary
Short summary
Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
Short summary
Short summary
The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
Short summary
Short summary
A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
Short summary
Short summary
The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
Short summary
Short summary
Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
Short summary
Short summary
This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
Short summary
Short summary
Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
Short summary
Short summary
This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
Short summary
Short summary
Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
Short summary
Short summary
TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
Short summary
Short summary
Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
Short summary
Short summary
We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
Short summary
Short summary
A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
Short summary
Short summary
In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
Short summary
Short summary
A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
Short summary
Short summary
Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
Short summary
Short summary
We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1437, https://doi.org/10.5194/egusphere-2024-1437, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can well reproduce the distribution of PAHs. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change of BaP is less than PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although "the Action Plan" has been implemented.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
Short summary
Short summary
Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
Short summary
Short summary
Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
Short summary
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Cited articles
Aumont, B., Szopa, S., and Madronich, S.: Modelling the evolution of organic
carbon during its gas-phase tropospheric oxidation: development of an
explicit model based on a self generating approach, Atmos. Chem. Phys., 5,
2497–2517, https://doi.org/10.5194/acp-5-2497-2005, 2005. a
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore,
A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global
modeling of tropospheric chemistry with assimilated meteorology: Model
description and evaluation, J. Geophys. Res.-Atmos.,
106, 23073–23095, https://doi.org/10.1029/2001JD000807,
2001. a
Bian, H. and Prather, M. J.: Fast-J2: Accurate Simulation of Stratospheric
Photolysis in Global Chemical Models, J. Atmos. Chem., 41,
281–296, https://doi.org/10.1023/A:1014980619462,
2002. a
Blasco, J., Fueyo, N., Dopazo, C., and Ballester, J.: Modelling the Temporal
Evolution of a Reduced Combustion Chemical System With an Artificial Neural
Network, Combust. Flame, 113, 38–52,
https://doi.org/10.1016/S0010-2180(97)00211-3,
1998. a
Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., Žabkar, R., Carmichael, G.
R., Flemming, J., Inness, A., Pagowski, M., Pérez Camaño, J. L., Saide,
P. E., San Jose, R., Sofiev, M., Vira, J., Baklanov, A., Carnevale, C.,
Grell, G., and Seigneur, C.: Data assimilation in atmospheric chemistry
models: current status and future prospects for coupled chemistry meteorology
models, Atmos. Chem. Phys., 15, 5325–5358,
https://doi.org/10.5194/acp-15-5325-2015, 2015. a
Brasseur, G. P., Xie, Y., Petersen, A. K., Bouarar, I., Flemming, J., Gauss,
M., Jiang, F., Kouznetsov, R., Kranenburg, R., Mijling, B., Peuch, V.-H.,
Pommier, M., Segers, A., Sofiev, M., Timmermans, R., van der A, R., Walters,
S., Xu, J., and Zhou, G.: Ensemble forecasts of air quality in eastern China
– Part 1: Model description and implementation of the MarcoPolo–Panda
prediction system, version 1, Geosci. Model Dev., 12, 33–67,
https://doi.org/10.5194/gmd-12-33-2019, 2019. a
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32,
https://doi.org/10.1023/A:1010933404324,
2001. a, b
Brenowitz, N. D. and Bretherton, C. S.: Prognostic Validation of a Neural
Network Unified Physics Parameterization, Geophys. Res. Lett., 45,
6289–6298, https://doi.org/10.1029/2018GL078510,
2018. a, b, c
Cariolle, D., Moinat, P., Teyssèdre, H., Giraud, L., Josse, B., and
Lefèvre, F.: ASIS v1.0: an adaptive solver for the simulation of
atmospheric chemistry, Geosci. Model Dev., 10, 1467–1485,
https://doi.org/10.5194/gmd-10-1467-2017, 2017. a
Carmichael, G. R., Sandu, A., Chai, T., Daescu, D. N., Constantinescu, E. M.,
and Tang, Y.: Predicting air quality: Improvements through advanced methods
to integrate models and measurements, J. Comput. Phys., 227,
3540–3571, https://doi.org/10.1016/j.jcp.2007.02.024,
2008. a
Chen, T. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System,
ArXiv e-prints, 1603.02754, available at: http://arxiv.org/abs/1603.02754 (last access: 18 March 2019),
2016. a
Cooper, O. R., Parrish, D. D., Ziemke, J., Balashov, N. V., Cupeiro, M.,
Galbally, I. E., Gilge, S., Horowitz, L., Jensen, N. R., Lamarque, J.-F.,
Naik, V., Oltmans, S. J., Schwab, J., Shindell, D. T., Thompson, A. M.,
Thouret, V., Wang, Y., and Zbinden, R. M.: Global distribution and trends of
tropospheric ozone: An observation-based review, Elementa,
2, 000 029, https://doi.org/10.12952/journal.elementa.000029, 2014. a
Eastham, S. D., Weisenstein, D. K., and Barrett, S. R.: Development and
evaluation of the unified tropospheric–stratospheric chemistry extension
(UCX) for the global chemistry-transport model GEOS-Chem, Atmos.
Environ., 89, 52–63, https://doi.org/10.1016/j.atmosenv.2014.02.001,
2014. a
Eastham, S. D., Long, M. S., Keller, C. A., Lundgren, E., Yantosca, R. M.,
Zhuang, J., Li, C., Lee, C. J., Yannetti, M., Auer, B. M., Clune, T. L.,
Kouatchou, J., Putman, W. M., Thompson, M. A., Trayanov, A. L., Molod, A. M.,
Martin, R. V., and Jacob, D. J.: GEOS-Chem High Performance (GCHP v11-02c): a
next-generation implementation of the GEOS-Chem chemical transport model for
massively parallel applications, Geosci. Model Dev., 11, 2941–2953,
https://doi.org/10.5194/gmd-11-2941-2018, 2018. a
Evans, M. J. and Keller, C. A.: Dataset associated with Keller and Evans,
GMD, 2019, University or York, 28 February 2019,
https://doi.org/10.15124/e291fdb4-f035-419c-948e-c8c7c978f8d6, made available under a
Creative Commons Attribution (CC BY 4.0) licence at
https://pure.york.ac.uk/portal/en/datasets/dataset-associated-with-keller-and-evans-gmd-2019(e291fdb4-f035-419c-948e-c8c7c978f8d6).html
last access: 18 March 2019. a
Gentine, P., Pritchard, M., Rasp, S., Reinaudi, G., and Yacalis, G.: Could
Machine Learning Break the Convection Parameterization Deadlock?, Geophys.
Res. Lett., 45, 5742–5751, https://doi.org/10.1029/2018GL078202,
2018. a
Hu, L., Keller, C. A., Long, M. S., Sherwen, T., Auer, B., Da Silva, A.,
Nielsen, J. E., Pawson, S., Thompson, M. A., Trayanov, A. L., Travis, K. R.,
Grange, S. K., Evans, M. J., and Jacob, D. J.: Global simulation of
tropospheric chemistry at 12.5 km resolution: performance and evaluation of
the GEOS-Chem chemical module (v10-1) within the NASA GEOS Earth system model
(GEOS-5 ESM), Geosci. Model Dev., 11, 4603–4620,
https://doi.org/10.5194/gmd-11-4603-2018, 2018. a, b
Inness, A., Blechschmidt, A.-M., Bouarar, I., Chabrillat, S., Crepulja, M.,
Engelen, R. J., Eskes, H., Flemming, J., Gaudel, A., Hendrick, F., Huijnen,
V., Jones, L., Kapsomenakis, J., Katragkou, E., Keppens, A., Langerock, B.,
de Mazière, M., Melas, D., Parrington, M., Peuch, V. H., Razinger, M.,
Richter, A., Schultz, M. G., Suttie, M., Thouret, V., Vrekoussis, M., Wagner,
A., and Zerefos, C.: Data assimilation of satellite-retrieved ozone, carbon
monoxide and nitrogen dioxide with ECMWF's Composition-IFS, Atmos. Chem.
Phys., 15, 5275–5303, https://doi.org/10.5194/acp-15-5275-2015, 2015. a
Jenkin, M., Watson, L., Utembe, S., and Shallcross, D.: A Common
Representative
Intermediates (CRI) mechanism for VOC degradation. Part 1: Gas phase
mechanism development, Atmos. Environ., 42, 7185–7195,
https://doi.org/10.1016/j.atmosenv.2008.07.028, 2008. a
Jenkin, M. E., Saunders, S. M., and Pilling, M. J.: The tropospheric
degradation of volatile organic compounds: a protocol for mechanism
development, Atmos. Environ., 31, 81–104,
https://doi.org/10.1016/S1352-2310(96)00105-7,
1997. a
Jiang, G., Xu, J., and Wei, J.: A Deep Learning Algorithm of Neural Network
for
the Parameterization of Typhoon–Ocean Feedback in Typhoon Forecast Models,
Geophys. Res. Lett., 45, 3706–3716, https://doi.org/10.1002/2018GL077004,
2018. a
Kelp, M. M., Tessum, C. W., and Marshall, J. D.: Orders-of-magnitude
speedup in atmospheric chemistry modeling through neural network-based
emulation, ArXiv e-prints, 1808.03874, available at: https://arxiv.org/abs/1808.03874 (last access: 18 March 2019), 2018. a
Krasnopolsky, V. M.: Neural network emulations for complex multidimensional
geophysical mappings: Applications of neural network techniques to
atmospheric and oceanic satellite retrievals and numerical modeling, Rev.
Geophys., 45, RG3009, https://doi.org/10.1029/2006RG000200, 2007. a
Krasnopolsky, V. M., Fox-Rabinovitz, M. S., and Chalikov, D. V.: New Approach
to Calculation of Atmospheric Model Physics: Accurate and Fast Neural Network
Emulation of Longwave Radiation in a Climate Model, Mon. Weather Rev.,
133, 1370–1383, https://doi.org/10.1175/MWR2923.1, 2005. a
Krasnopolsky, V. M., Fox-Rabinovitz, M. S., Hou, Y. T., Lord, S. J., and
Belochitski, A. A.: Accurate and Fast Neural Network Emulations of Model
Radiation for the NCEP Coupled Climate Forecast System: Climate Simulations
and Seasonal Predictions, Mon. Weather Rev., 138, 1822–1842,
https://doi.org/10.1175/2009MWR3149.1, 2010. a, b
Leighton, P.: Photochemistry of Air Pollution, Academic Press, New York,
ISBN 9780323156455, 1961. a
Long, M. S., Yantosca, R., Nielsen, J. E., Keller, C. A., da Silva, A.,
Sulprizio, M. P., Pawson, S., and Jacob, D. J.: Development of a
grid-independent GEOS-Chem chemical transport model (v9-02) as an atmospheric
chemistry module for Earth system models, Geosci. Model Dev., 8, 595–602,
https://doi.org/10.5194/gmd-8-595-2015, 2015. a, b
Mallet, V., Stoltz, G., and Mauricette, B.: Ozone ensemble forecast with
machine learning algorithms, J. Geophys. Res.-Atmos.,
114, D05307, https://doi.org/10.1029/2008JD009978,
2009. a
Mao, J., Jacob, D. J., Evans, M. J., Olson, J. R., Ren, X., Brune, W. H.,
Clair, J. M. St., Crounse, J. D., Spencer, K. M., Beaver, M. R., Wennberg, P.
O., Cubison, M. J., Jimenez, J. L., Fried, A., Weibring, P., Walega, J. G.,
Hall, S. R., Weinheimer, A. J., Cohen, R. C., Chen, G., Crawford, J. H.,
McNaughton, C., Clarke, A. D., Jaeglé, L., Fisher, J. A., Yantosca, R. M.,
Le Sager, P., and Carouge, C.: Chemistry of hydrogen oxide radicals
(HOx) in the Arctic troposphere in spring, Atmos. Chem.
Phys., 10, 5823–5838, https://doi.org/10.5194/acp-10-5823-2010, 2010. a
Mao, J., Paulot, F., Jacob, D. J., Cohen, R. C., Crounse, J. D., Wennberg,
P. O., Keller, C. A., Hudman, R. C., Barkley, M. P., and Horowitz, L. W.:
Ozone and organic nitrates over the eastern United States: Sensitivity to
isoprene chemistry, J. Geophys. Res.-Atmos., 118,
11256–11268, https://doi.org/10.1002/jgrd.50817,
2013. a
Mjolsness, E. and DeCoste, D.: Machine Learning for Science: State of the Art
and Future Prospects, Science, 293, 2051–2055,
https://doi.org/10.1126/science.293.5537.2051,
2001. a
Molteni, F., Buizza, R., Palmer, T. N., and Petroliagis, T.: The ECMWF
Ensemble
Prediction System: Methodology and validation, Q. J. Roy.
Meteor. Soc., 122, 73–119, https://doi.org/10.1002/qj.49712252905,
1996. a
Murray, L. T., Jacob, D. J., Logan, J. A., Hudman, R. C., and Koshak, W. J.:
Optimized regional and interannual variability of lightning in a global
chemical transport model constrained by LIS/OTD satellite data, J.
Geophys. Res.-Atmos., 117, d20307, https://doi.org/10.1029/2012JD017934,
2012. a
Nicely, J. M., Salawitch, R. J., Canty, T., Anderson, D. C., Arnold, S. R.,
Chipperfield, M. P., Emmons, L. K., Flemming, J., Huijnen, V., Kinnison,
D. E., Lamarque, J.-F., Mao, J., Monks, S. A., Steenrod, S. D., Tilmes, S.,
and Turquety, S.: Quantifying the causes of differences in tropospheric OH
within global models, J. Geophys. Res.-Atmos., 122,
1983–2007, https://doi.org/10.1002/2016JD026239,
2017. a, b
Nielsen, J. E., Pawson, S., Molod, A., Auer, B., da Silva, A. M., Douglass,
A. R., Duncan, B., Liang, Q., Manyin, M., Oman, L. D., Putman, W., Strahan,
S. E., and Wargan, K.: Chemical Mechanisms and Their Applications in the
Goddard Earth Observing System (GEOS) Earth System Model, J. Adv.
Model. Earth Sy., 9, 3019–3044, https://doi.org/10.1002/2017MS001011,
2017. a
Nowack, P., Braesicke, P., Haigh, J., Abraham, N. L., Pyle, J., and
Voulgarakis, A.: Using machine learning to build temperature-based ozone
parameterizations for climate sensitivity simulations, Environ. Res.
Lett., 13, 104016, https://doi.org/10.1088/1748-9326/aae2be,
2018. a, b
Parrella, J. P., Jacob, D. J., Liang, Q., Zhang, Y., Mickley, L. J., Miller,
B., Evans, M. J., Yang, X., Pyle, J. A., Theys, N., and Van Roozendael, M.:
Tropospheric bromine chemistry: implications for present and pre-industrial
ozone and mercury, Atmos. Chem. Phys., 12, 6723–6740,
https://doi.org/10.5194/acp-12-6723-2012, 2012. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J.,
Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.:
Scikit-learn: Machine Learning in Python, J. Mach. Learn.
Res., 12, 2825–2830, 2011. a
Porumbel, I., Petcu, A. C., Florean, F. G., and Hritcu, C. E.: Artificial
Neural Networks for Modeling of Chemical Source Terms in CFD Simulations of
Turbulent Reactive Flows, in: Modeling and Optimization of the Aerospace,
Robotics, Mechatronics, Machines-Tools, Mechanical Engineering and Human
Motricity Fields, Vol. 555, Applied Mechanics and Materials, Trans Tech Publications,
395–400, 2014. a
Sandu, A. and Chai, T.: Chemical Data Assimilation – An Overview,
Atmosphere,
2, 426–463, https://doi.org/10.3390/atmos2030426,
2011. a
Sandu, A. and Sander, R.: Technical note: Simulating chemical systems in
Fortran90 and Matlab with the Kinetic PreProcessor KPP-2.1, Atmos. Chem.
Phys., 6, 187–195, https://doi.org/10.5194/acp-6-187-2006, 2006. a
Sandu, A., Verwer, J., Blom, J., Spee, E., Carmichael, G., and Potra, F.:
Benchmarking stiff ode solvers for atmospheric chemistry problems II:
Rosenbrock solvers, Atmos. Environ., 31, 3459–3472,
https://doi.org/10.1016/S1352-2310(97)83212-8,
1997a. a
Sandu, A., Verwer, J., Loon, M. V., Carmichael, G., Potra, F., Dabdub, D.,
and
Seinfeld, J.: Benchmarking stiff ode solvers for atmospheric chemistry
problems-I. implicit vs explicit, Atmos. Environ., 31, 3151–3166,
https://doi.org/10.1016/S1352-2310(97)00059-9,
1997b. a
Santillana, M., Sager, P. L., Jacob, D. J., and Brenner, M. P.: An adaptive
reduction algorithm for efficient chemical calculations in global atmospheric
chemistry models, Atmos. Environ., 44, 4426–4431,
https://doi.org/10.1016/j.atmosenv.2010.07.044,
2010. a
Silva, S. J. and Heald, C. L.: Investigating Dry Deposition of Ozone to
Vegetation, J. Geophys. Res.-Atmos., 123, 559–573,
https://doi.org/10.1002/2017JD027278,
2018. a
Stevenson, D. S., Dentener, F. J., Schultz, M. G., Ellingsen, K., van Noije,
T.
P. C., Wild, O., Zeng, G., Amann, M., Atherton, C. S., Bell, N., Bergmann,
D. J., Bey, I., Butler, T., Cofala, J., Collins, W. J., Derwent, R. G.,
Doherty, R. M., Drevet, J., Eskes, H. J., Fiore, A. M., Gauss, M.,
Hauglustaine, D. A., Horowitz, L. W., Isaksen, I. S. A., Krol, M. C.,
Lamarque, J.-F., Lawrence, M. G., Montanaro, V., Müller, J.-F., Pitari, G.,
Prather, M. J., Pyle, J. A., Rast, S., Rodriguez, J. M., Sanderson, M. G.,
Savage, N. H., Shindell, D. T., Strahan, S. E., Sudo, K., and Szopa, S.:
Multimodel ensemble simulations of present-day and near-future tropospheric
ozone, J. Geophys. Res.-Atmos., 111, D08301,
https://doi.org/10.1029/2005JD006338,
2006.
a
Turányi, T.: Parameterization of reaction mechanisms using orthonormal
polynomials, Comput. Chem., 18, 45–54,
https://doi.org/10.1016/0097-8485(94)80022-7,
1994. a
Whitehouse, L. E., Tomlin, A. S., and Pilling, M. J.: Systematic reduction of
complex tropospheric chemical mechanisms, Part I: sensitivity and time-scale
analyses, Atmos. Chem. Phys., 4, 2025–2056, https://doi.org/10.5194/acp-4-2025-2004,
2004a. a
Whitehouse, L. E., Tomlin, A. S., and Pilling, M. J.: Systematic reduction of
complex tropospheric chemical mechanisms, Part II: Lumping using a time-scale
based approach, Atmos. Chem. Phys., 4, 2057–2081,
https://doi.org/10.5194/acp-4-2057-2004, 2004b. a
Young, P. J., Naik, V., Fiore, A. M., Gaudel, A., Guo, J., Lin, M. Y., Neu,
J. L., Parrish, D. D., Rieder, H. E., Schnell, J. L., Tilmes, S., Wild, O.,
Zhang, L., Ziemke, J. R., Brandt, J., Delcloo, A., Doherty, R. M., Geels, C.,
Hegglin, M. I., Hu, L., Im, U., Kumar, R., Luhar, A., Murray, L., Plummer,
D., Rodriguez, J., Saiz-Lopez, A., Schultz, M. G., Woodhouse, M. T., and
Zeng, G.: Tropospheric Ozone Assessment Report: Assessment of global-scale
model performance for global and regional ozone distributions, variability,
and trends, Elementa, 6, 10, https://doi.org/10.1525/elementa.265,
2018. a
Young, T. R. and Boris, J. P.: A numerical technique for solving stiff
ordinary
differential equations associated with the chemical kinetics of reactive-flow
problems, J. Phys. Chem., 81, 2424–2427,
https://doi.org/10.1021/j100540a018,
1977. a
Short summary
Computer simulations of atmospheric chemistry are a central tool to study the impact of air pollutants on the environment. These models are highly complex and require a lot of computing resources. In this study we show that machine learning can be used to predict air pollution with an accuracy that is comparable to the traditional, computationally expensive method. Such a machine-learning-based model has the potential to be orders of magnitude faster.
Computer simulations of atmospheric chemistry are a central tool to study the impact of air...