Articles | Volume 11, issue 11
https://doi.org/10.5194/gmd-11-4603-2018
© Author(s) 2018. 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-11-4603-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
16 Nov 2018
Model evaluation paper |
| 16 Nov 2018
| 16 Nov 2018
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)
Department of Chemistry and Biochemistry, University of Montana, Missoula, MT, USA
John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Christoph A. Keller
John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Universities Space Research Association, Columbia, MD, USA
Michael S. Long
John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Tomás Sherwen
National Centre for Atmospheric Science, University of York, York, UK
Wolfson Atmospheric Chemistry Laboratory, University of York, York, UK
Benjamin Auer
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Lanham, MD, USA
Arlindo Da Silva
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Jon E. Nielsen
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Lanham, MD, USA
Steven Pawson
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Matthew A. Thompson
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Lanham, MD, USA
Atanas L. Trayanov
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Science Systems and Applications, Inc., Lanham, MD, USA
Katherine R. Travis
John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
Stuart K. Grange
Wolfson Atmospheric Chemistry Laboratory, University of York, York, UK
Mat J. Evans
National Centre for Atmospheric Science, University of York, York, UK
Wolfson Atmospheric Chemistry Laboratory, University of York, York, UK
Daniel J. Jacob
John A. Paulson School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
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Joseph O. Palmo, Colette L. Heald, Donald R. Blake, Ilann Bourgeois, Matthew Coggon, Jeff Collett, Frank Flocke, Alan Fried, Georgios Gkatzelis, Samuel Hall, Lu Hu, Jose L. Jimenez, Pedro Campuzano-Jost, I-Ting Ku, Benjamin Nault, Brett Palm, Jeff Peischl, Ilana Pollack, Amy Sullivan, Joel Thornton, Carsten Warneke, Armin Wisthaler, and Lu Xu
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Huanxin Zhang, Jun Wang, Nathan Janechek, Cui Ge, Meng Zhou, Lorena Castro García, Tong Sha, Yanyu Wang, Weizhi Deng, Zhixin Xue, Chengzhe Li, Lakhima Chutia, Yi Wang, Sebastian Val, James L. McDuffie, Sina Hasheminassab, Scott E. Gluck, David J. Diner, Peter R. Colarco, and Arlindo M. da Silva
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Drew C. Pendergrass, Daniel J. Jacob, Nicholas Balasus, Lucas Estrada, Daniel J. Varon, James D. East, Megan He, Todd A. Mooring, Elise Penn, Hannah Nesser, and John R. Worden
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Elise Penn, Daniel J. Jacob, Zichong Chen, James D. East, Melissa P. Sulprizio, Lori Bruhwiler, Joannes D. Maasakkers, Hannah Nesser, Zhen Qu, Yuzhong Zhang, and John Worden
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Abdullah A. Fahad, Andrea Molod, Krzysztof Wargan, Dimitris Menemenlis, Patrick Heimbach, Atanas Trayanov, Ehud Strobach, and Lawrence Coy
EGUsphere, https://doi.org/10.21203/rs.3.rs-1892797/v2, https://doi.org/10.21203/rs.3.rs-1892797/v2, 2025
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Stuart K. Grange, Pascal Rubli, Andrea Fischer, Dominik Brunner, Christoph Hueglin, and Lukas Emmenegger
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Matthew James Rowlinson, Lucy J. Carpenter, Mat J. Evans, James D. Lee, Simone Andersen, Tomas Sherwen, Anna B. Callaghan, Roberto Sommariva, William Bloss, Siqi Hou, Leigh R. Crilley, Klaus Pfeilsticker, Benjamin Weyland, Thomas B. Ryerson, Patrick R. Veres, Pedro Campuzano-Jost, Hongyu Guo, Benjamin A. Nault, Jose L. Jimenez, and Khanneh Wadinga Fomba
EGUsphere, https://doi.org/10.5194/egusphere-2025-830, https://doi.org/10.5194/egusphere-2025-830, 2025
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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, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2087–2121, https://doi.org/10.5194/acp-25-2087-2025, https://doi.org/10.5194/acp-25-2087-2025, 2025
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We use the GEOS-Chem model to simulate aerosol distributions and properties over the western North Atlantic Ocean (WNAO) during the winter and summer deployments in 2020 of the NASA ACTIVATE mission. Model results are evaluated against aircraft, ground-based, and satellite observations. The improved understanding of life cycle, composition, transport pathways, and distribution of aerosols has important implications for characterizing aerosol–cloud–meteorology interactions over WNAO.
Tia R. Scarpelli, Elfie Roy, Daniel J. Jacob, Melissa P. Sulprizio, Ryan D. Tate, and Daniel H. Cusworth
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-552, https://doi.org/10.5194/essd-2024-552, 2025
Revised manuscript under review for ESSD
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We present an update of the Global Fuel Exploitation Inventory (GFEI), a global inventory of methane emissions from oil, gas, and coal exploitation. GFEI v3 uses emissions as reported by countries in national inventories for 2020, and new infrastructure information, including a new dataset on coal mine locations. The goal of updating GFEI is to provide a more accurate spatial representation of the country-reported national inventories, allowing comparison with methane monitoring data.
Sarah E. Hancock, Daniel J. Jacob, Zichong Chen, Hannah Nesser, Aaron Davitt, Daniel J. Varon, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, María Cazorla, Laura Dawidowski, Sebastián Diez, James D. East, Elise Penn, Cynthia A. Randles, John Worden, Ilse Aben, Robert J. Parker, and Joannes D. Maasakkers
Atmos. Chem. Phys., 25, 797–817, https://doi.org/10.5194/acp-25-797-2025, https://doi.org/10.5194/acp-25-797-2025, 2025
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We quantify 2021 methane emissions in South America at up to 25 km × 25 km resolution using satellite methane observations. We find a 55 % upward adjustment to anthropogenic emission inventories, including those reported to the UN Framework Convention on Climate Change under the Paris Agreement. Our estimates match inventories for Brazil, Bolivia, and Paraguay but are much higher for other countries. Livestock emissions (65 % of anthropogenic emissions) show the largest discrepancies.
Gregory P. Schill, Karl D. Froyd, Daniel M. Murphy, Christina J. Williamson, Charles A. Brock, Tomás Sherwen, Mat J. Evans, Eric A. Ray, Eric C. Apel, Rebecca S. Hornbrook, Alan J. Hills, Jeff Peischl, Thomas B. Ryerson, Chelsea R. Thompson, Ilann Bourgeois, Donald R. Blake, Joshua P. DiGangi, and Glenn S. Diskin
Atmos. Chem. Phys., 25, 45–71, https://doi.org/10.5194/acp-25-45-2025, https://doi.org/10.5194/acp-25-45-2025, 2025
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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.
Yingjie Shen, Rudra P. Pokhrel, Amy P. Sullivan, Ezra J. T. Levin, Lauren A. Garofalo, Delphine K. Farmer, Wade Permar, Lu Hu, Darin W. Toohey, Teresa Campos, Emily V. Fischer, and Shane M. Murphy
Atmos. Chem. Phys., 24, 12881–12901, https://doi.org/10.5194/acp-24-12881-2024, https://doi.org/10.5194/acp-24-12881-2024, 2024
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The magnitude and evolution of brown carbon (BrC) absorption remain unclear, with uncertainty in climate models. Data from the WE-CAN airborne experiment show that model parameterizations overestimate the mass absorption cross section (MAC) of BrC. Observed decreases in BrC absorption with chemical markers are due to decreasing organic aerosol (OA) mass rather than a decreasing BrC MAC, which is currently implemented in models. Water-soluble BrC contributes 23 % of total absorption at 660 nm.
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
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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.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Benjamin A. Nault, Katherine R. Travis, James H. Crawford, Donald R. Blake, Pedro Campuzano-Jost, Ronald C. Cohen, Joshua P. DiGangi, Glenn S. Diskin, Samuel R. Hall, L. Gregory Huey, Jose L. Jimenez, Kyung-Eun Min, Young Ro Lee, Isobel J. Simpson, Kirk Ullmann, and Armin Wisthaler
Atmos. Chem. Phys., 24, 9573–9595, https://doi.org/10.5194/acp-24-9573-2024, https://doi.org/10.5194/acp-24-9573-2024, 2024
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Ozone (O3) is a pollutant formed from the reactions of gases emitted from various sources. In urban areas, the density of human activities can increase the O3 formation rate (P(O3)), thus impacting air quality and health. Observations collected over Seoul, South Korea, are used to constrain P(O3). A high local P(O3) was found; however, local P(O3) was partly reduced due to compounds typically ignored. These observations also provide constraints for unmeasured compounds that will impact P(O3).
Katherine R. Travis, Benjamin A. Nault, James H. Crawford, Kelvin H. Bates, Donald R. Blake, Ronald C. Cohen, Alan Fried, Samuel R. Hall, L. Gregory Huey, Young Ro Lee, Simone Meinardi, Kyung-Eun Min, Isobel J. Simpson, and Kirk Ullman
Atmos. Chem. Phys., 24, 9555–9572, https://doi.org/10.5194/acp-24-9555-2024, https://doi.org/10.5194/acp-24-9555-2024, 2024
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Human activities result in the emission of volatile organic compounds (VOCs) that contribute to air pollution. Detailed VOC measurements were taken during a field study in South Korea. When compared to VOC inventories, large discrepancies showed underestimates from chemical products, liquefied petroleum gas, and long-range transport. Improved emissions and chemistry of these VOCs better described urban pollution. The new chemical scheme is relevant to urban areas and other VOC sources.
Haipeng Lin, Louisa K. Emmons, Elizabeth W. Lundgren, Laura Hyesung Yang, Xu Feng, Ruijun Dang, Shixian Zhai, Yunxiao Tang, Makoto M. Kelp, Nadia K. Colombi, Sebastian D. Eastham, Thibaud M. Fritz, and Daniel J. Jacob
Atmos. Chem. Phys., 24, 8607–8624, https://doi.org/10.5194/acp-24-8607-2024, https://doi.org/10.5194/acp-24-8607-2024, 2024
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Tropospheric ozone is a major air pollutant, a greenhouse gas, and a major indicator of model skill. Global atmospheric chemistry models show large differences in simulations of tropospheric ozone, but isolating sources of differences is complicated by different model environments. By implementing the GEOS-Chem model side by side to CAM-chem within a common Earth system model, we identify and evaluate specific differences between the two models and their impacts on key chemical species.
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
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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.
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, and Hong Liao
Atmos. Chem. Phys., 24, 7027–7039, https://doi.org/10.5194/acp-24-7027-2024, https://doi.org/10.5194/acp-24-7027-2024, 2024
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The Geostationary Environment Monitoring Spectrometer (GEMS) provides hourly measurements of NO2. We use the chemical transport model to find how emissions, chemistry, and transport drive the changes in NO2 observed by GEMS at different times of the day. In winter, the chemistry plays a minor role, and high daytime emissions dominate the diurnal variation in NO2, balanced by transport. In summer, emissions, chemistry, and transport play an important role in shaping the diurnal variation in NO2.
Peng Xian, Jeffrey S. Reid, Melanie Ades, Angela Benedetti, Peter R. Colarco, Arlindo da Silva, Tom F. Eck, Johannes Flemming, Edward J. Hyer, Zak Kipling, Samuel Rémy, Tsuyoshi Thomas Sekiyama, Taichu Tanaka, Keiya Yumimoto, and Jianglong Zhang
Atmos. Chem. Phys., 24, 6385–6411, https://doi.org/10.5194/acp-24-6385-2024, https://doi.org/10.5194/acp-24-6385-2024, 2024
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The study compares and evaluates monthly AOD of four reanalyses (RA) and their consensus (i.e., ensemble mean). The basic verification characteristics of these RA versus both AERONET and MODIS retrievals are presented. The study discusses the strength of each RA and identifies regions where divergence and challenges are prominent. The RA consensus usually performs very well on a global scale in terms of how well it matches the observational data, making it a good choice for various applications.
Drew C. Pendergrass, Daniel J. Jacob, Yujin J. Oak, Jeewoo Lee, Minseok Kim, Jhoon Kim, Seoyoung Lee, Shixian Zhai, Hitoshi Irie, and Hong Liao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-172, https://doi.org/10.5194/essd-2024-172, 2024
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Fine particles suspended in the atmosphere are a major form of air pollution and an important public health burden. However, measurements of particulate matter are sparse in space and in places like East Asia monitors are established after regulatory policies to improve pollution have changed. In this paper, we use machine learning to fill in the gaps. We train an algorithm to predict pollution at the surface from the atmosphere’s opacity, then produce high resolution maps of data without gaps.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Alba Lorente, Zichong Chen, Xiao Lu, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Margaux Winter, Shuang Ma, A. Anthony Bloom, John R. Worden, Robert N. Stavins, and Cynthia A. Randles
Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, https://doi.org/10.5194/acp-24-5069-2024, 2024
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We quantify 2019 methane emissions in the contiguous US (CONUS) at a ≈ 25 km × 25 km resolution using satellite methane observations. We find a 13 % upward correction to the 2023 US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) for 2019, with large corrections to individual states, urban areas, and landfills. This may present a challenge for US climate policies and goals, many of which target significant reductions in methane emissions.
Amy Christiansen, Loretta J. Mickley, and Lu Hu
Atmos. Chem. Phys., 24, 4569–4589, https://doi.org/10.5194/acp-24-4569-2024, https://doi.org/10.5194/acp-24-4569-2024, 2024
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In this work, we provide an additional constraint on emissions and trends of nitrogen oxides using nitrate wet deposition (NWD) fluxes over the United States and Europe from 1980–2020. We find that NWD measurements constrain total NOx emissions well. We also find evidence of NOx emission overestimates in both domains, but especially over Europe, where NOx emissions are overestimated by a factor of 2. Reducing NOx emissions over Europe improves model representation of ozone at the surface.
Sebastian D. Eastham, Guillaume P. Chossière, Raymond L. Speth, Daniel J. Jacob, and Steven R. H. Barrett
Atmos. Chem. Phys., 24, 2687–2703, https://doi.org/10.5194/acp-24-2687-2024, https://doi.org/10.5194/acp-24-2687-2024, 2024
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Emissions from aircraft are known to cause air quality impacts worldwide, but the scale and mechanisms of this impact are not well understood. This work uses high-resolution computational modeling of the atmosphere to show that air pollution changes from aviation are mostly the result of emissions during cruise (high-altitude) operations, that these impacts are related to how much non-aviation pollution is present, and that prior regional assessments have underestimated these impacts.
Adriana Rocha-Lima, Peter R. Colarco, Anton S. Darmenov, Edward P. Nowottnick, Arlindo M. da Silva, and Luke D. Oman
Atmos. Chem. Phys., 24, 2443–2464, https://doi.org/10.5194/acp-24-2443-2024, https://doi.org/10.5194/acp-24-2443-2024, 2024
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Observations show an increasing aerosol optical depth trend in the Middle East between 2003–2012. We evaluate the NASA Goddard Earth Observing System (GEOS) model's ability to capture these trends and examine the meteorological and surface parameters driving dust emissions. Our results highlight the importance of data assimilation for long-term trends of atmospheric aerosols and support the hypothesis that vegetation cover loss may have contributed to increasing dust emissions in the period.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Drew C. Pendergrass, Daniel J. Jacob, Hannah Nesser, Daniel J. Varon, Melissa Sulprizio, Kazuyuki Miyazaki, and Kevin W. Bowman
Geosci. Model Dev., 16, 4793–4810, https://doi.org/10.5194/gmd-16-4793-2023, https://doi.org/10.5194/gmd-16-4793-2023, 2023
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We have built a tool called CHEEREIO that allows scientists to use observations of pollutants or gases in the atmosphere, such as from satellites or surface stations, to update supercomputer models that simulate the Earth. CHEEREIO uses the difference between the model simulations of the atmosphere and real-world observations to come up with a good guess for the actual composition of our atmosphere, the true emissions of various pollutants, and whatever else they may want to study.
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
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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.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
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We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
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We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
Ruijun Dang, Daniel J. Jacob, Viral Shah, Sebastian D. Eastham, Thibaud M. Fritz, Loretta J. Mickley, Tianjia Liu, Yi Wang, and Jun Wang
Atmos. Chem. Phys., 23, 6271–6284, https://doi.org/10.5194/acp-23-6271-2023, https://doi.org/10.5194/acp-23-6271-2023, 2023
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We use the GEOS-Chem model to better understand the magnitude and trend in free tropospheric NO2 over the contiguous US. Model underestimate of background NO2 is largely corrected by considering aerosol nitrate photolysis. Increase in aircraft emissions affects satellite retrievals by altering the NO2 shape factor, and this effect is expected to increase in future. We show the importance of properly accounting for the free tropospheric background in interpreting NO2 observations from space.
Lixu Jin, Wade Permar, Vanessa Selimovic, Damien Ketcherside, Robert J. Yokelson, Rebecca S. Hornbrook, Eric C. Apel, I-Ting Ku, Jeffrey L. Collett Jr., Amy P. Sullivan, Daniel A. Jaffe, Jeffrey R. Pierce, Alan Fried, Matthew M. Coggon, Georgios I. Gkatzelis, Carsten Warneke, Emily V. Fischer, and Lu Hu
Atmos. Chem. Phys., 23, 5969–5991, https://doi.org/10.5194/acp-23-5969-2023, https://doi.org/10.5194/acp-23-5969-2023, 2023
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Air quality in the USA has been improving since 1970 due to anthropogenic emission reduction. Those gains have been partly offset by increased wildfire pollution in the western USA in the past 20 years. Still, we do not understand wildfire emissions well due to limited measurements. Here, we used a global transport model to evaluate and constrain current knowledge of wildfire emissions with recent observational constraints, showing the underestimation of wildfire emissions in the western USA.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
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We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Ian Chang, Lan Gao, Connor J. Flynn, Yohei Shinozuka, Sarah J. Doherty, Michael S. Diamond, Karla M. Longo, Gonzalo A. Ferrada, Gregory R. Carmichael, Patricia Castellanos, Arlindo M. da Silva, Pablo E. Saide, Calvin Howes, Zhixin Xue, Marc Mallet, Ravi Govindaraju, Qiaoqiao Wang, Yafang Cheng, Yan Feng, Sharon P. Burton, Richard A. Ferrare, Samuel E. LeBlanc, Meloë S. Kacenelenbogen, Kristina Pistone, Michal Segal-Rozenhaimer, Kerry G. Meyer, Ju-Mee Ryoo, Leonhard Pfister, Adeyemi A. Adebiyi, Robert Wood, Paquita Zuidema, Sundar A. Christopher, and Jens Redemann
Atmos. Chem. Phys., 23, 4283–4309, https://doi.org/10.5194/acp-23-4283-2023, https://doi.org/10.5194/acp-23-4283-2023, 2023
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Abundant aerosols are present above low-level liquid clouds over the southeastern Atlantic during late austral spring. The model simulation differences in the proportion of aerosol residing in the planetary boundary layer and in the free troposphere can greatly affect the regional aerosol radiative effects. This study examines the aerosol loading and fractional aerosol loading in the free troposphere among various models and evaluates them against measurements from the NASA ORACLES campaign.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
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Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Nadia K. Colombi, Daniel J. Jacob, Laura Hyesung Yang, Shixian Zhai, Viral Shah, Stuart K. Grange, Robert M. Yantosca, Soontae Kim, and Hong Liao
Atmos. Chem. Phys., 23, 4031–4044, https://doi.org/10.5194/acp-23-4031-2023, https://doi.org/10.5194/acp-23-4031-2023, 2023
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Surface ozone, detrimental to human and ecosystem health, is very high and increasing in South Korea. Using a global model of the atmosphere, we found that emissions from South Korea and China contribute equally to the high ozone observed. We found that in the absence of all anthropogenic emissions over East Asia, ozone is still very high, implying that the air quality standard in South Korea is not practically achievable unless this background external to East Asia can be decreased.
Laura Hyesung Yang, Daniel J. Jacob, Nadia K. Colombi, Shixian Zhai, Kelvin H. Bates, Viral Shah, Ellie Beaudry, Robert M. Yantosca, Haipeng Lin, Jared F. Brewer, Heesung Chong, Katherine R. Travis, James H. Crawford, Lok N. Lamsal, Ja-Ho Koo, and Jhoon Kim
Atmos. Chem. Phys., 23, 2465–2481, https://doi.org/10.5194/acp-23-2465-2023, https://doi.org/10.5194/acp-23-2465-2023, 2023
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A geostationary satellite can now provide hourly NO2 vertical columns, and obtaining the NO2 vertical columns from space relies on NO2 vertical distribution from the chemical transport model (CTM). In this work, we update the CTM to better represent the chemistry environment so that the CTM can accurately provide NO2 vertical distribution. We also find that the changes in NO2 vertical distribution driven by a change in mixing depth play an important role in the NO2 column's diurnal variation.
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
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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.
Allison B. Marquardt Collow, Virginie Buchard, Peter R. Colarco, Arlindo M. da Silva, Ravi Govindaraju, Edward P. Nowottnick, Sharon Burton, Richard Ferrare, Chris Hostetler, and Luke Ziemba
Atmos. Chem. Phys., 22, 16091–16109, https://doi.org/10.5194/acp-22-16091-2022, https://doi.org/10.5194/acp-22-16091-2022, 2022
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Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in models. Field campaign observations from CAMP2Ex are used to evaluate the mass and extinction of aerosols in the GEOS model. Notable biases in the model illuminate areas of future development with GEOS and the underlying GOCART aerosol module.
Simone T. Andersen, Beth S. Nelson, Katie A. Read, Shalini Punjabi, Luis Neves, Matthew J. Rowlinson, James Hopkins, Tomás Sherwen, Lisa K. Whalley, James D. Lee, and Lucy J. Carpenter
Atmos. Chem. Phys., 22, 15747–15765, https://doi.org/10.5194/acp-22-15747-2022, https://doi.org/10.5194/acp-22-15747-2022, 2022
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The cycling of NO and NO2 is important to understand to be able to predict O3 concentrations in the atmosphere. We have used long-term measurements from the Cape Verde Atmospheric Observatory together with model outputs to investigate the cycling of nitrogen oxide (NO) and nitrogen dioxide (NO2) in very clean marine air. This study shows that we understand the processes occurring in very clean air, but with small amounts of pollution in the air, known chemistry cannot explain what is observed.
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
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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.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Amy Christiansen, Loretta J. Mickley, Junhua Liu, Luke D. Oman, and Lu Hu
Atmos. Chem. Phys., 22, 14751–14782, https://doi.org/10.5194/acp-22-14751-2022, https://doi.org/10.5194/acp-22-14751-2022, 2022
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Understanding tropospheric ozone trends is crucial for accurate predictions of future air quality and climate, but drivers of trends are not well understood. We analyze global tropospheric ozone trends since 1980 using ozonesonde and surface measurements, and we evaluate two models for their ability to reproduce trends. We find observational evidence of increasing tropospheric ozone, but models underestimate these increases. This hinders our ability to estimate ozone radiative forcing.
William F. Swanson, Chris D. Holmes, William R. Simpson, Kaitlyn Confer, Louis Marelle, Jennie L. Thomas, Lyatt Jaeglé, Becky Alexander, Shuting Zhai, Qianjie Chen, Xuan Wang, and Tomás Sherwen
Atmos. Chem. Phys., 22, 14467–14488, https://doi.org/10.5194/acp-22-14467-2022, https://doi.org/10.5194/acp-22-14467-2022, 2022
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Radical bromine molecules are seen at higher concentrations during the Arctic spring. We use the global model GEOS-Chem to test whether snowpack and wind-blown snow sources can explain high bromine concentrations. We run this model for the entire year of 2015 and compare results to observations of bromine from floating platforms on the Arctic Ocean and at Utqiaġvik. We find that the model performs best when both sources are enabled but may overestimate bromine production in summer and fall.
Vanessa Selimovic, Damien Ketcherside, Sreelekha Chaliyakunnel, Catherine Wielgasz, Wade Permar, Hélène Angot, Dylan B. Millet, Alan Fried, Detlev Helmig, and Lu Hu
Atmos. Chem. Phys., 22, 14037–14058, https://doi.org/10.5194/acp-22-14037-2022, https://doi.org/10.5194/acp-22-14037-2022, 2022
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Arctic warming has led to an increase in plants that emit gases in response to stress, but how these gases affect regional chemistry is largely unknown due to lack of observational data. Here we present the most comprehensive gas-phase measurements for this area to date and compare them to predictions from a global transport model. We report 78 gas-phase species and investigate their importance to atmospheric chemistry in the area, with broader implications for similar plant types.
Haolin Wang, Xiao Lu, Daniel J. Jacob, Owen R. Cooper, Kai-Lan Chang, Ke Li, Meng Gao, Yiming Liu, Bosi Sheng, Kai Wu, Tongwen Wu, Jie Zhang, Bastien Sauvage, Philippe Nédélec, Romain Blot, and Shaojia Fan
Atmos. Chem. Phys., 22, 13753–13782, https://doi.org/10.5194/acp-22-13753-2022, https://doi.org/10.5194/acp-22-13753-2022, 2022
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We report significant global tropospheric ozone increases in 1995–2017 based on extensive aircraft and ozonesonde observations. Using GEOS-Chem (Goddard Earth Observing System chemistry model) multi-decadal global simulations, we find that changes in global anthropogenic emissions, in particular the rapid increases in aircraft emissions, contribute significantly to the increases in tropospheric ozone and resulting radiative impact.
Samuel E. LeBlanc, Michal Segal-Rozenhaimer, Jens Redemann, Connor Flynn, Roy R. Johnson, Stephen E. Dunagan, Robert Dahlgren, Jhoon Kim, Myungje Choi, Arlindo da Silva, Patricia Castellanos, Qian Tan, Luke Ziemba, Kenneth Lee Thornhill, and Meloë Kacenelenbogen
Atmos. Chem. Phys., 22, 11275–11304, https://doi.org/10.5194/acp-22-11275-2022, https://doi.org/10.5194/acp-22-11275-2022, 2022
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Airborne observations of atmospheric particles and pollution over Korea during a field campaign in May–June 2016 showed that the smallest atmospheric particles are present in the lowest 2 km of the atmosphere. The aerosol size is more spatially variable than optical thickness. We show this with remote sensing (4STAR), in situ (LARGE) observations, satellite measurements (GOCI), and modeled properties (MERRA-2), and it is contrary to the current understanding.
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala-Araiza, Joannes D. Maasakkers, Tia R. Scarpelli, Alba Lorente, David Lyon, Jianxiong Sheng, Daniel J. Varon, Hannah Nesser, Zhen Qu, Xiao Lu, Melissa P. Sulprizio, Steven P. Hamburg, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 11203–11215, https://doi.org/10.5194/acp-22-11203-2022, https://doi.org/10.5194/acp-22-11203-2022, 2022
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We use 22 months of TROPOMI satellite observations to quantity methane emissions from the oil (O) and natural gas (G) sector in the US and Canada at the scale of both individual basins as well as country-wide aggregates. We find that O/G-related methane emissions are underestimated in these inventories by 80 % for the US and 40 % for Canada, and 70 % of the underestimate in the US is from five O/G basins, including Permian, Haynesville, Anadarko, Eagle Ford, and Barnett.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
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Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Sudip Chakraborty, Bin Guan, Duane E. Waliser, and Arlindo M. da Silva
Atmos. Chem. Phys., 22, 8175–8195, https://doi.org/10.5194/acp-22-8175-2022, https://doi.org/10.5194/acp-22-8175-2022, 2022
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This study explores extreme aerosol transport events by aerosol atmospheric rivers (AARs) and shows the characteristics of individual AARs such as length, width, length-to-width ratio, transport strength, and dominant transport direction, the seasonal variations, the relationship to the spatial distribution of surface emissions, the vertical profiles of wind, aerosol mixing ratio, and aerosol mass fluxes, and the major planetary-scale aerosol transport pathways.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
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The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
Joseph S. Schlosser, Connor Stahl, Armin Sorooshian, Yen Thi-Hoang Le, Ki-Joon Jeon, Peng Xian, Carolyn E. Jordan, Katherine R. Travis, James H. Crawford, Sung Yong Gong, Hye-Jung Shin, In-Ho Song, and Jong-sang Youn
Atmos. Chem. Phys., 22, 7505–7522, https://doi.org/10.5194/acp-22-7505-2022, https://doi.org/10.5194/acp-22-7505-2022, 2022
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During a major haze pollution episode in March 2019, anthropogenic emissions were dominant in the boundary layer over Incheon and Seoul, South Korea. Using supermicrometer and submicrometer size- and chemistry-resolved aerosol particle measurements taken during this haze pollution period, this work shows that local emissions and a shallow boundary layer, enhanced humidity, and low temperature promoted local heterogeneous formation of secondary inorganic and organic aerosol species.
Stuart K. Grange, Gaëlle Uzu, Samuël Weber, Jean-Luc Jaffrezo, and Christoph Hueglin
Atmos. Chem. Phys., 22, 7029–7050, https://doi.org/10.5194/acp-22-7029-2022, https://doi.org/10.5194/acp-22-7029-2022, 2022
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Oxidative potential (OP), a biologically relevant metric for particulate matter (PM), was linked to PM10 and PM2.5 sources and constituents across Switzerland between 2018 and 2019. Wood burning and non-exhaust traffic emissions were identified as key processes that led to enhanced OP. Therefore, the make-up of the PM mix was very important for OP. The results highlight the importance of the management of wood burning and non-exhaust emissions to reduce OP, and presumably biological harm.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
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This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Adam Brighty, Véronique Jacob, Gaëlle Uzu, Lucille Borlaza, Sébastien Conil, Christoph Hueglin, Stuart K. Grange, Olivier Favez, Cécile Trébuchon, and Jean-Luc Jaffrezo
Atmos. Chem. Phys., 22, 6021–6043, https://doi.org/10.5194/acp-22-6021-2022, https://doi.org/10.5194/acp-22-6021-2022, 2022
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With an revised analytical method and long-term sampling strategy, we have been able to elucidate much more information about atmospheric plant debris, a poorly understood class of particulate matter. We found weaker seasonal patterns at urban locations compared to rural locations and significant interannual variability in concentrations between previous years and 2020, during the COVID-19 pandemic. This suggests a possible man-made influence on plant debris concentration and source strength.
Ehud Strobach, Andrea Molod, Donifan Barahona, Atanas Trayanov, Dimitris Menemenlis, and Gael Forget
Geosci. Model Dev., 15, 2309–2324, https://doi.org/10.5194/gmd-15-2309-2022, https://doi.org/10.5194/gmd-15-2309-2022, 2022
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The Green's functions methodology offers a systematic, easy-to-implement, computationally cheap, scalable, and extendable method to tune uncertain parameters in models accounting for the dependent response of the model to a change in various parameters. Herein, we successfully show for the first time that long-term errors in earth system models can be considerably reduced using Green's functions methodology. The method can be easily applied to any model containing uncertain parameters.
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
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We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Kelvin Bates, Jiawei Zhuang, and Wei Chen
Geosci. Model Dev., 15, 1677–1687, https://doi.org/10.5194/gmd-15-1677-2022, https://doi.org/10.5194/gmd-15-1677-2022, 2022
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The high computational cost of chemical integration is a long-standing limitation in global atmospheric chemistry models. Here we present an adaptive and efficient algorithm that can reduce the computational time of atmospheric chemistry by 50 % and maintain the error below 2 % for important species, inspired by machine learning clustering techniques and traditional asymptotic analysis ideas.
Sujung Go, Alexei Lyapustin, Gregory L. Schuster, Myungje Choi, Paul Ginoux, Mian Chin, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, Arlindo da Silva, Brent Holben, and Jeffrey S. Reid
Atmos. Chem. Phys., 22, 1395–1423, https://doi.org/10.5194/acp-22-1395-2022, https://doi.org/10.5194/acp-22-1395-2022, 2022
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This paper presents a retrieval algorithm of iron-oxide species (hematite, goethite) content in the atmosphere from DSCOVR EPIC observations. Our results display variations within the published range of hematite and goethite over the main dust-source regions but show significant seasonal and spatial variability. This implies a single-viewing satellite instrument with UV–visible channels may provide essential information on shortwave dust direct radiative effects for climate modeling.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Galina Wind, Arlindo M. da Silva, Kerry G. Meyer, Steven Platnick, and Peter M. Norris
Geosci. Model Dev., 15, 1–14, https://doi.org/10.5194/gmd-15-1-2022, https://doi.org/10.5194/gmd-15-1-2022, 2022
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This is the third paper in series about the Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In this paper we use MCARS to create a set of constraints that might be used to assimilate a new above-cloud aerosol retrieval product developed for the MODIS instrument into a general circulation model. We executed the above-cloud aerosol retrieval over a series of synthetic MODIS granules and found the product to be of excellent quality.
Sarah J. Doherty, Pablo E. Saide, Paquita Zuidema, Yohei Shinozuka, Gonzalo A. Ferrada, Hamish Gordon, Marc Mallet, Kerry Meyer, David Painemal, Steven G. Howell, Steffen Freitag, Amie Dobracki, James R. Podolske, Sharon P. Burton, Richard A. Ferrare, Calvin Howes, Pierre Nabat, Gregory R. Carmichael, Arlindo da Silva, Kristina Pistone, Ian Chang, Lan Gao, Robert Wood, and Jens Redemann
Atmos. Chem. Phys., 22, 1–46, https://doi.org/10.5194/acp-22-1-2022, https://doi.org/10.5194/acp-22-1-2022, 2022
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Between July and October, biomass burning smoke is advected over the southeastern Atlantic Ocean, leading to climate forcing. Model calculations of forcing by this plume vary significantly in both magnitude and sign. This paper compares aerosol and cloud properties observed during three NASA ORACLES field campaigns to the same in four models. It quantifies modeled biases in properties key to aerosol direct radiative forcing and evaluates how these biases propagate to biases in forcing.
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
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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.
Sabour Baray, Daniel J. Jacob, Joannes D. Maasakkers, Jian-Xiong Sheng, Melissa P. Sulprizio, Dylan B. A. Jones, A. Anthony Bloom, and Robert McLaren
Atmos. Chem. Phys., 21, 18101–18121, https://doi.org/10.5194/acp-21-18101-2021, https://doi.org/10.5194/acp-21-18101-2021, 2021
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We use 2010–2015 surface and satellite observations to disentangle methane from anthropogenic and natural sources in Canada. Using a chemical transport model (GEOS-Chem), the mismatch between modelled and observed methane concentrations can be used to infer emissions according to Bayesian statistics. Compared to prior knowledge, we show higher anthropogenic emissions attributed to energy and/or agriculture in Western Canada and lower natural emissions from Boreal wetlands.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Arseniy Karagodin-Doyennel, Eugene Rozanov, Timofei Sukhodolov, Tatiana Egorova, Alfonso Saiz-Lopez, Carlos A. Cuevas, Rafael P. Fernandez, Tomás Sherwen, Rainer Volkamer, Theodore K. Koenig, Tanguy Giroud, and Thomas Peter
Geosci. Model Dev., 14, 6623–6645, https://doi.org/10.5194/gmd-14-6623-2021, https://doi.org/10.5194/gmd-14-6623-2021, 2021
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Here, we present the iodine chemistry module in the SOCOL-AERv2 model. The obtained iodine distribution demonstrated a good agreement when validated against other simulations and available observations. We also estimated the iodine influence on ozone in the case of present-day iodine emissions, the sensitivity of ozone to doubled iodine emissions, and when considering only organic or inorganic iodine sources. The new model can be used as a tool for further studies of iodine effects on ozone.
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
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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.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
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
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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
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Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Tia R. Scarpelli, Melissa P. Sulprizio, Yuzhong Zhang, and Chris H. Rycroft
Atmos. Meas. Tech., 14, 5521–5534, https://doi.org/10.5194/amt-14-5521-2021, https://doi.org/10.5194/amt-14-5521-2021, 2021
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Analytical inversions of satellite observations of atmospheric composition can improve emissions estimates and quantify errors but are computationally expensive at high resolutions. We propose two methods to decrease this cost. The methods reproduce a high-resolution inversion at a quarter of the cost. The reduced-dimension method creates a multiscale grid. The reduced-rank method solves the inversion where information content is highest.
Kristina Pistone, Paquita Zuidema, Robert Wood, Michael Diamond, Arlindo M. da Silva, Gonzalo Ferrada, Pablo E. Saide, Rei Ueyama, Ju-Mee Ryoo, Leonhard Pfister, James Podolske, David Noone, Ryan Bennett, Eric Stith, Gregory Carmichael, Jens Redemann, Connor Flynn, Samuel LeBlanc, Michal Segal-Rozenhaimer, and Yohei Shinozuka
Atmos. Chem. Phys., 21, 9643–9668, https://doi.org/10.5194/acp-21-9643-2021, https://doi.org/10.5194/acp-21-9643-2021, 2021
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Using aircraft-based measurements off the Atlantic coast of Africa, we found the springtime smoke plume was strongly correlated with the amount of water vapor in the atmosphere (more smoke indicated more humidity). We see the same general feature in satellite-assimilated and free-running models. Our analysis suggests this relationship is not caused by the burning but originates due to coincident continental meteorology plus fires. This air is transported over the ocean without further mixing.
Brad Weir, Lesley E. Ott, George J. Collatz, Stephan R. Kawa, Benjamin Poulter, Abhishek Chatterjee, Tomohiro Oda, and Steven Pawson
Atmos. Chem. Phys., 21, 9609–9628, https://doi.org/10.5194/acp-21-9609-2021, https://doi.org/10.5194/acp-21-9609-2021, 2021
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We present a collection of carbon surface fluxes, the Low-order Flux Inversion (LoFI), derived from satellite observations of the Earth's surface and calibrated to match long-term inventories and atmospheric and oceanic records. Simulations using LoFI reproduce background atmospheric carbon dioxide measurements with comparable skill to the leading surface flux products. Available both retrospectively and as a forecast, LoFI enables the study of the carbon cycle as it occurs.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, Qi Chen, and Zhiwei Han
Geosci. Model Dev., 14, 3741–3768, https://doi.org/10.5194/gmd-14-3741-2021, https://doi.org/10.5194/gmd-14-3741-2021, 2021
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WRF-GC is an online coupling of the WRF meteorological model and GEOS-Chem chemical transport model for regional atmospheric chemistry and air quality modeling. In WRF-GC v2.0, we implemented the aerosol–radiation interactions and aerosol–cloud interactions, as well as the capability to nest multiple domains for high-resolution simulations based on the modular framework of WRF-GC v1.0. This allows the GEOS-Chem users to investigate the meteorology–atmospheric chemistry interactions.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
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The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Daniel J. Varon, Dylan Jervis, Jason McKeever, Ian Spence, David Gains, and Daniel J. Jacob
Atmos. Meas. Tech., 14, 2771–2785, https://doi.org/10.5194/amt-14-2771-2021, https://doi.org/10.5194/amt-14-2771-2021, 2021
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Satellites can detect methane emissions by measuring sunlight reflected from the Earth's surface and atmosphere. Here we show that the European Space Agency's Sentinel-2 twin satellites can be used to monitor anomalously large methane point sources around the world, with global coverage every 2–5 days and 20 m spatial resolution. We demonstrate this previously unreported capability through high-frequency Sentinel-2 monitoring of two strong methane point sources in Algeria and Turkmenistan.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
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We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
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We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Stuart K. Grange, James D. Lee, Will S. Drysdale, Alastair C. Lewis, Christoph Hueglin, Lukas Emmenegger, and David C. Carslaw
Atmos. Chem. Phys., 21, 4169–4185, https://doi.org/10.5194/acp-21-4169-2021, https://doi.org/10.5194/acp-21-4169-2021, 2021
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The changes in mobility across Europe due to the COVID-19 lockdowns had consequences for air quality. We compare what was experienced to estimates of "what would have been" without the lockdowns. Nitrogen dioxide (NO2), an important vehicle-sourced pollutant, decreased by a third. However, ozone (O3) increased in response to lower NO2. Because NO2 is decreasing over time, increases in O3 can be expected in European urban areas and will require management to avoid future negative outcomes.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
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
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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.
Angharad C. Stell, Luke M. Western, Tomás Sherwen, and Matthew Rigby
Atmos. Chem. Phys., 21, 1717–1736, https://doi.org/10.5194/acp-21-1717-2021, https://doi.org/10.5194/acp-21-1717-2021, 2021
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Although it is the second-most important greenhouse gas, our understanding of the atmospheric-methane budget is limited. The uncertainty highlights the need for new tools to investigate sources and sinks. Here, we use a Gaussian process emulator to efficiently approximate the response of atmospheric-methane observations to changes in the most uncertain emission or loss processes. With this new method, we rigorously quantify the sensitivity of atmospheric observations to budget uncertainties.
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
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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.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
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Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Susan S. Kulawik, John R. Worden, Vivienne H. Payne, Dejian Fu, Steven C. Wofsy, Kathryn McKain, Colm Sweeney, Bruce C. Daube Jr., Alan Lipton, Igor Polonsky, Yuguang He, Karen E. Cady-Pereira, Edward J. Dlugokencky, Daniel J. Jacob, and Yi Yin
Atmos. Meas. Tech., 14, 335–354, https://doi.org/10.5194/amt-14-335-2021, https://doi.org/10.5194/amt-14-335-2021, 2021
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This paper shows comparisons of a new single-footprint methane product from the AIRS satellite to aircraft-based observations. We show that this AIRS methane product provides useful information to study seasonal and global methane trends of this important greenhouse gas.
Hélène Angot, Katelyn McErlean, Lu Hu, Dylan B. Millet, Jacques Hueber, Kaixin Cui, Jacob Moss, Catherine Wielgasz, Tyler Milligan, Damien Ketcherside, M. Syndonia Bret-Harte, and Detlev Helmig
Biogeosciences, 17, 6219–6236, https://doi.org/10.5194/bg-17-6219-2020, https://doi.org/10.5194/bg-17-6219-2020, 2020
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We report biogenic volatile organic compounds (BVOCs) ambient levels and emission rates from key vegetation species in the Alaskan arctic tundra, providing a new data set to further constrain isoprene chemistry under low NOx conditions in models. We add to the growing body of evidence that climate-induced changes in the vegetation composition will significantly affect the BVOC emission potential of the tundra, with implications for atmospheric oxidation processes and climate feedbacks.
Junfeng Wang, Jianhuai Ye, Dantong Liu, Yangzhou Wu, Jian Zhao, Weiqi Xu, Conghui Xie, Fuzhen Shen, Jie Zhang, Paul E. Ohno, Yiming Qin, Xiuyong Zhao, Scot T. Martin, Alex K. Y. Lee, Pingqing Fu, Daniel J. Jacob, Qi Zhang, Yele Sun, Mindong Chen, and Xinlei Ge
Atmos. Chem. Phys., 20, 14091–14102, https://doi.org/10.5194/acp-20-14091-2020, https://doi.org/10.5194/acp-20-14091-2020, 2020
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We compared the organics in total submicron matter and those coated on BC cores during summertime in Beijing and found large differences between them. Traffic-related OA was associated significantly with BC, while cooking-related OA did not coat BC. In addition, a factor likely originated from primary biomass burning OA was only identified in BC-containing particles. Such a unique BBOA requires further field and laboratory studies to verify its presence and elucidate its properties and impacts.
Lei Zhu, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Kelly Chance, Eric C. Apel, Joshua P. DiGangi, Alan Fried, Thomas F. Hanisco, Rebecca S. Hornbrook, Lu Hu, Jennifer Kaiser, Frank N. Keutsch, Wade Permar, Jason M. St. Clair, and Glenn M. Wolfe
Atmos. Chem. Phys., 20, 12329–12345, https://doi.org/10.5194/acp-20-12329-2020, https://doi.org/10.5194/acp-20-12329-2020, 2020
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We develop a validation platform for satellite HCHO retrievals using in situ observations from 12 aircraft campaigns. The platform offers an alternative way to quickly assess systematic biases in HCHO satellite products over large domains and long periods, facilitating optimization of retrieval settings and the minimization of retrieval biases. Application to the NASA operational HCHO product indicates that relative biases range from −44.5 % to +112.1 % depending on locations and seasons.
Viral Shah, Daniel J. Jacob, Jonathan M. Moch, Xuan Wang, and Shixian Zhai
Atmos. Chem. Phys., 20, 12223–12245, https://doi.org/10.5194/acp-20-12223-2020, https://doi.org/10.5194/acp-20-12223-2020, 2020
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Cloud water pH affects atmospheric chemistry, and acid rain damages ecosystems. We use model simulations along with observations to present a global view of cloud water and precipitation pH. Sulfuric acid, nitric acid, and ammonia control the pH in the northern midlatitudes, but carboxylic acids and dust cations are important in the tropics and subtropics. The acid inputs to many nitrogen-saturated ecosystems are high enough to cause acidification, with ammonium as the main acidifying species.
Swaleha Inamdar, Liselotte Tinel, Rosie Chance, Lucy J. Carpenter, Prabhakaran Sabu, Racheal Chacko, Sarat C. Tripathy, Anvita U. Kerkar, Alok K. Sinha, Parli Venkateswaran Bhaskar, Amit Sarkar, Rajdeep Roy, Tomás Sherwen, Carlos Cuevas, Alfonso Saiz-Lopez, Kirpa Ram, and Anoop S. Mahajan
Atmos. Chem. Phys., 20, 12093–12114, https://doi.org/10.5194/acp-20-12093-2020, https://doi.org/10.5194/acp-20-12093-2020, 2020
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Iodine chemistry is generating a lot of interest because of its impacts on the oxidising capacity of the marine boundary and depletion of ozone. However, one of the challenges has been predicting the right levels of iodine in the models, which depend on parameterisations for emissions from the sea surface. This paper discusses the different parameterisations available and compares them with observations, showing that our current knowledge is still insufficient, especially on a regional scale.
Yohei Shinozuka, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon, Karla Longo, Marc Mallet, Yan Feng, Qiaoqiao Wang, Yafang Cheng, Amie Dobracki, Steffen Freitag, Steven G. Howell, Samuel LeBlanc, Connor Flynn, Michal Segal-Rosenhaimer, Kristina Pistone, James R. Podolske, Eric J. Stith, Joseph Ryan Bennett, Gregory R. Carmichael, Arlindo da Silva, Ravi Govindaraju, Ruby Leung, Yang Zhang, Leonhard Pfister, Ju-Mee Ryoo, Jens Redemann, Robert Wood, and Paquita Zuidema
Atmos. Chem. Phys., 20, 11491–11526, https://doi.org/10.5194/acp-20-11491-2020, https://doi.org/10.5194/acp-20-11491-2020, 2020
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In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016.
Ke Li, Daniel J. Jacob, Lu Shen, Xiao Lu, Isabelle De Smedt, and Hong Liao
Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, https://doi.org/10.5194/acp-20-11423-2020, 2020
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Surface summer ozone increased in China from 2013 to 2019 despite new governmental efforts targeting ozone pollution. We find that the ozone increase is mostly due to anthropogenic drivers, although meteorology also plays a role. Further analysis for the North China Plain shows that PM2.5 continued to decrease through 2019, while emissions of volatile organic compounds (VOCs) stayed flat. This could explain the anthropogenic increase in ozone, as PM2.5 scavenges the radical precursors of ozone.
Kirk Knobelspiesse, Henrique M. J. Barbosa, Christine Bradley, Carol Bruegge, Brian Cairns, Gao Chen, Jacek Chowdhary, Anthony Cook, Antonio Di Noia, Bastiaan van Diedenhoven, David J. Diner, Richard Ferrare, Guangliang Fu, Meng Gao, Michael Garay, Johnathan Hair, David Harper, Gerard van Harten, Otto Hasekamp, Mark Helmlinger, Chris Hostetler, Olga Kalashnikova, Andrew Kupchock, Karla Longo De Freitas, Hal Maring, J. Vanderlei Martins, Brent McBride, Matthew McGill, Ken Norlin, Anin Puthukkudy, Brian Rheingans, Jeroen Rietjens, Felix C. Seidel, Arlindo da Silva, Martijn Smit, Snorre Stamnes, Qian Tan, Sebastian Val, Andrzej Wasilewski, Feng Xu, Xiaoguang Xu, and John Yorks
Earth Syst. Sci. Data, 12, 2183–2208, https://doi.org/10.5194/essd-12-2183-2020, https://doi.org/10.5194/essd-12-2183-2020, 2020
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The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign is a resource for the next generation of spaceborne multi-angle polarimeter (MAP) and lidar missions. Conducted in the fall of 2017 from the Armstrong Flight Research Center in Palmdale, California, four MAP instruments and two lidars were flown on the high-altitude ER-2 aircraft over a variety of scene types and ground assets. Data are freely available to the public and useful for algorithm development and testing.
Xiao Lu, Lin Zhang, Tongwen Wu, Michael S. Long, Jun Wang, Daniel J. Jacob, Fang Zhang, Jie Zhang, Sebastian D. Eastham, Lu Hu, Lei Zhu, Xiong Liu, and Min Wei
Geosci. Model Dev., 13, 3817–3838, https://doi.org/10.5194/gmd-13-3817-2020, https://doi.org/10.5194/gmd-13-3817-2020, 2020
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This study presents the development and evaluation of a new climate chemistry model, BCC-GEOS-Chem v1.0, which couples the GEOS-Chem chemical transport model as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model. A 3-year (2012–2014) simulation of BCC-GEOS-Chem v1.0 shows that the model captures well the spatiotemporal distributions of tropospheric ozone, other gaseous pollutants, and aerosols.
Alexander Ukhov, Suleiman Mostamandi, Arlindo da Silva, Johannes Flemming, Yasser Alshehri, Illia Shevchenko, and Georgiy Stenchikov
Atmos. Chem. Phys., 20, 9281–9310, https://doi.org/10.5194/acp-20-9281-2020, https://doi.org/10.5194/acp-20-9281-2020, 2020
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The data assimilation products MERRA2 and CAMS are tested over the Middle East (ME) against in situ and satellite observations. For the first time, we compared the new MODIS aerosol optical depth (AOD) retrieval, MAIAC, with the Deep Blue and Dark Target MODIS AOD. We conducted 2-year high-resolution WRF-Chem simulations with the most accurate OMI-HTAP SO2 emissions to estimate the contribution of natural and anthropogenic aerosols to the PM pollution in the ME.
Eirini Boleti, Christoph Hueglin, Stuart K. Grange, André S. H. Prévôt, and Satoshi Takahama
Atmos. Chem. Phys., 20, 9051–9066, https://doi.org/10.5194/acp-20-9051-2020, https://doi.org/10.5194/acp-20-9051-2020, 2020
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Long-term temporal evolution of ozone concentrations between 2000 and 2015 in Europe was estimated using a signal decomposition technique. The seasonal cycles are correlated with local climate conditions and vary according to geographic region, while ozone levels are indicative of distance to emission sources. The site's environment plays a key role in ozone trends, with the most polluted environments showing the least reduction in ozone, while in less polluted areas ozone has decreased.
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
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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
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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
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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
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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
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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.
Junhua Liu, Jose M. Rodriguez, Luke D. Oman, Anne R. Douglass, Mark A. Olsen, and Lu Hu
Atmos. Chem. Phys., 20, 6417–6433, https://doi.org/10.5194/acp-20-6417-2020, https://doi.org/10.5194/acp-20-6417-2020, 2020
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Our paper quantifies and identifies the importance of stratospheric ozone influence on the tropospheric ozone IAV in Northern Hemisphere mid-high latitudes. Our analysis provides an in-depth understanding of how 3-D dynamics influences the O3 redistribution in the troposphere. These findings are particularly important considering the potential changes in these dynamical conditions in the future as a result of climate change
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Xuan Wang, and Wei Chen
Geosci. Model Dev., 13, 2475–2486, https://doi.org/10.5194/gmd-13-2475-2020, https://doi.org/10.5194/gmd-13-2475-2020, 2020
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Chemical mechanisms in air quality models tend to get more complicated with time, reflecting both increasing knowledge and the need for greater scope. This objectively improves the models but increases the computational burden. In this work, we present an approach that can reduce the computational cost of chemical integration by 30–40 % while maintaining an accuracy better than 1 %. It retains the complexity of the full mechanism where it is needed and preserves full diagnostic information.
Stuart K. Grange, Hanspeter Lötscher, Andrea Fischer, Lukas Emmenegger, and Christoph Hueglin
Atmos. Meas. Tech., 13, 1867–1885, https://doi.org/10.5194/amt-13-1867-2020, https://doi.org/10.5194/amt-13-1867-2020, 2020
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Black carbon (BC) is an important atmospheric pollutant and can be monitored by instruments called aethalometers. A pragmatic data processing technique called the
aethalometer modelcan be used to apportion aethalometer observations into traffic and woodburning components. We present an exploratory data analysis evaluating the aethalometer model and use the outputs for BC trend analysis across Switzerland. The aethalometer model's robustness and utility for such analyses is discussed.
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
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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
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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.
Tia R. Scarpelli, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Kelly Rose, Lucy Romeo, John R. Worden, and Greet Janssens-Maenhout
Earth Syst. Sci. Data, 12, 563–575, https://doi.org/10.5194/essd-12-563-2020, https://doi.org/10.5194/essd-12-563-2020, 2020
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Methane, a potent greenhouse gas, is emitted through the exploitation of oil, gas, and coal resources, and many efforts to reduce emissions have targeted these sources. We have created a global inventory of oil, gas, and coal methane emissions based on country reporting to the United Nations. The inventory can be used along with satellite observations of methane to better understand the contribution of these sources to global emissions and to identify potential biases in emissions reporting.
Therese S. Carter, Colette L. Heald, Jose L. Jimenez, Pedro Campuzano-Jost, Yutaka Kondo, Nobuhiro Moteki, Joshua P. Schwarz, Christine Wiedinmyer, Anton S. Darmenov, Arlindo M. da Silva, and Johannes W. Kaiser
Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, https://doi.org/10.5194/acp-20-2073-2020, 2020
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Fires and the smoke they emit impact air quality, health, and climate, but the abundance and properties of smoke remain uncertain and poorly constrained. To explore this, we compare model simulations driven by four commonly-used fire emission inventories with surface, aloft, and satellite observations. We show that across inventories smoke emissions differ by factors of 4 to 7 over North America, challenging our ability to accurately characterize the impact of smoke on air quality and climate.
Guangliang Fu, Otto Hasekamp, Jeroen Rietjens, Martijn Smit, Antonio Di Noia, Brian Cairns, Andrzej Wasilewski, David Diner, Felix Seidel, Feng Xu, Kirk Knobelspiesse, Meng Gao, Arlindo da Silva, Sharon Burton, Chris Hostetler, John Hair, and Richard Ferrare
Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, https://doi.org/10.5194/amt-13-553-2020, 2020
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In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (the Netherlands Institute for Space Research). We perform aerosol retrievals from different multi-angle polarimeters employed during the ACEPOL campaign and evaluate them against ground-based AERONET measurements and High Spectral Resolution Lidar-2 (HSRL-2) measurements.
Viral Shah, Daniel J. Jacob, Ke Li, Rachel F. Silvern, Shixian Zhai, Mengyao Liu, Jintai Lin, and Qiang Zhang
Atmos. Chem. Phys., 20, 1483–1495, https://doi.org/10.5194/acp-20-1483-2020, https://doi.org/10.5194/acp-20-1483-2020, 2020
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We analyze 15 years of satellite observations of nitrogen dioxide (NO2) and use an atmospheric chemistry model to understand the seasonal changes and trends in nitrogen oxides (NOx) over China. We show that the seasonal changes in NO2 occur due to changes in the NOx oxidation lifetime. We find that Chinese NOx emissions peaked in 2011 and had decreased by about 25 % by 2018. But the decrease in NO2 in winter was larger, likely because of a simultaneous decrease in the NOx oxidation lifetime.
Xiaohua Pan, Charles Ichoku, Mian Chin, Huisheng Bian, Anton Darmenov, Peter Colarco, Luke Ellison, Tom Kucsera, Arlindo da Silva, Jun Wang, Tomohiro Oda, and Ge Cui
Atmos. Chem. Phys., 20, 969–994, https://doi.org/10.5194/acp-20-969-2020, https://doi.org/10.5194/acp-20-969-2020, 2020
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The differences between these six BB emission datasets are large. Our study found that (1) most current biomass burning (BB) aerosol emission datasets derived from satellite observations lead to the underestimation of aerosol optical depth (AOD) in this model in the biomass-burning-dominated regions and (2) it is important to accurately estimate both the magnitudes and spatial patterns of regional BB emissions in order for a model using these emissions to reproduce observed AOD levels.
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
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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.
Daniel H. Cusworth, Daniel J. Jacob, Daniel J. Varon, Christopher Chan Miller, Xiong Liu, Kelly Chance, Andrew K. Thorpe, Riley M. Duren, Charles E. Miller, David R. Thompson, Christian Frankenberg, Luis Guanter, and Cynthia A. Randles
Atmos. Meas. Tech., 12, 5655–5668, https://doi.org/10.5194/amt-12-5655-2019, https://doi.org/10.5194/amt-12-5655-2019, 2019
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We examine the potential for global detection of methane plumes from individual point sources with the new generation of spaceborne imaging spectrometers scheduled for launch in 2019–2025. We perform methane retrievals on simulated scenes with varying surfaces and atmospheric methane concentrations. Our results suggest that imaging spectrometers in space could play a transformative role in the future for quantifying methane emissions from point sources on a global scale.
Shixian Zhai, Daniel J. Jacob, Xuan Wang, Lu Shen, Ke Li, Yuzhong Zhang, Ke Gui, Tianliang Zhao, and Hong Liao
Atmos. Chem. Phys., 19, 11031–11041, https://doi.org/10.5194/acp-19-11031-2019, https://doi.org/10.5194/acp-19-11031-2019, 2019
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Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However, meteorologically PM2.5 variability complicates trend attribution. We used a stepwise multiple linear regression model to quantitatively separate contributions from anthropogenic emissions and meteorology. Results show that 88 % of the PM2.5 decrease across China is attributable to anthropogenic emission changes, and 12 % is attributable to meteorology.
Huisheng Bian, Karl Froyd, Daniel M. Murphy, Jack Dibb, Anton Darmenov, Mian Chin, Peter R. Colarco, Arlindo da Silva, Tom L. Kucsera, Gregory Schill, Hongbin Yu, Paul Bui, Maximilian Dollner, Bernadett Weinzierl, and Alexander Smirnov
Atmos. Chem. Phys., 19, 10773–10785, https://doi.org/10.5194/acp-19-10773-2019, https://doi.org/10.5194/acp-19-10773-2019, 2019
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We address the GEOS-GOCART sea salt simulations constrained by NASA EVS ATom measurements, as well as those by MODIS and the AERONET MAN. The study covers remote regions over the Pacific, Atlantic, and Southern oceans from near the surface to ~ 12 km altitude and covers both summer and winter seasons. Important sea salt fields, e.g., mass mixing ratio, vertical distribution, size distribution, and marine aerosol AOD, as well as their relationship to relative humidity and emissions, are examined.
Katherine R. Travis and Daniel J. Jacob
Geosci. Model Dev., 12, 3641–3648, https://doi.org/10.5194/gmd-12-3641-2019, https://doi.org/10.5194/gmd-12-3641-2019, 2019
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Models of ozone air pollution are often evaluated with the policy metric set by the EPA of the maximum daily 8 h average ozone concentration. These models may be used in policy settings to evaluate air quality regulations. However, most models have difficulty simulating how ozone varies over the course of the day, and thus the use of this metric in model evaluation is problematic. Improved representation of mixed layer dynamics and ozone loss to the surface is needed to resolve this issue.
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
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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.
Kelvin H. Bates and Daniel J. Jacob
Atmos. Chem. Phys., 19, 9613–9640, https://doi.org/10.5194/acp-19-9613-2019, https://doi.org/10.5194/acp-19-9613-2019, 2019
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Isoprene is a highly reactive chemical released to the atmosphere by plants. Its gas-phase reactions and interactions with chemicals released by human activity have far-reaching atmospheric consequences, contributing to ozone and particulate pollution and prolonging the lifetime of methane, a potent greenhouse gas. We use global simulations with a new isoprene reaction scheme to quantify those effects and to show how recently discovered aspects of isoprene chemistry play out on a global scale.
Rachel F. Silvern, Daniel J. Jacob, Loretta J. Mickley, Melissa P. Sulprizio, Katherine R. Travis, Eloise A. Marais, Ronald C. Cohen, Joshua L. Laughner, Sungyeon Choi, Joanna Joiner, and Lok N. Lamsal
Atmos. Chem. Phys., 19, 8863–8878, https://doi.org/10.5194/acp-19-8863-2019, https://doi.org/10.5194/acp-19-8863-2019, 2019
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The US EPA reports a steady decrease in nitrogen oxide (NOx) emissions from fuel combustion over the 2005–2017 period, while satellite observations show a leveling off after 2009, suggesting emission reductions and related air quality gains have halted. We show the sustained decrease in NOx emissions is in fact consistent with observed trends in surface NO2 and ozone concentrations and that the flattening of the satellite trend reflects a growing influence from the non-anthropogenic background.
Ilana B. Pollack, Jakob Lindaas, J. Robert Roscioli, Michael Agnese, Wade Permar, Lu Hu, and Emily V. Fischer
Atmos. Meas. Tech., 12, 3717–3742, https://doi.org/10.5194/amt-12-3717-2019, https://doi.org/10.5194/amt-12-3717-2019, 2019
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A closed-path infrared absorption spectrometer was outfitted with the option for active continuous passivation for measuring large, rapid gradients in atmospheric NH3 from a research aircraft. In-flight and ground observations show utility in passivant addition for recovering instrument time response when sampling surfaces are contaminated and cannot be cleaned in a timely manner and for maintaining rapid time response in an NH3-rich and humid environment over a several-week-long field campaign.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jian-Xiong Sheng, Yuzhong Zhang, Monica Hersher, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, Greet Janssens-Maenhout, and Robert J. Parker
Atmos. Chem. Phys., 19, 7859–7881, https://doi.org/10.5194/acp-19-7859-2019, https://doi.org/10.5194/acp-19-7859-2019, 2019
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We use 2010–2015 satellite observations of atmospheric methane to improve estimates of methane emissions and their trends, as well as the concentration and trend of tropospheric OH (hydroxyl radical, methane's main sink). We find overestimates of Chinese coal and Middle East oil/gas emissions in the prior estimate. The 2010–2015 growth in methane is attributed to an increase in emissions from India, China, and areas with large tropical wetlands. The contribution from OH is small in comparison.
Lu Shen, Daniel J. Jacob, Xiong Liu, Guanyu Huang, Ke Li, Hong Liao, and Tao Wang
Atmos. Chem. Phys., 19, 6551–6560, https://doi.org/10.5194/acp-19-6551-2019, https://doi.org/10.5194/acp-19-6551-2019, 2019
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
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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
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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.
Christoph A. Keller and Mat J. Evans
Geosci. Model Dev., 12, 1209–1225, https://doi.org/10.5194/gmd-12-1209-2019, https://doi.org/10.5194/gmd-12-1209-2019, 2019
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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.
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
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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.
Alba Badia, Claire E. Reeves, Alex R. Baker, Alfonso Saiz-Lopez, Rainer Volkamer, Theodore K. Koenig, Eric C. Apel, Rebecca S. Hornbrook, Lucy J. Carpenter, Stephen J. Andrews, Tomás Sherwen, and Roland von Glasow
Atmos. Chem. Phys., 19, 3161–3189, https://doi.org/10.5194/acp-19-3161-2019, https://doi.org/10.5194/acp-19-3161-2019, 2019
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The oceans have an impact on the composition and reactivity of the troposphere through the emission of gases and particles. Thus, a quantitative understanding of the marine atmosphere is crucial to examine the oxidative capacity and climate forcing. This study investigates the impact of halogens in the tropical troposphere and explores the sensitivity of this to uncertainties in the fluxes and their chemical processing. Our modelled tropospheric Ox loss due to halogens ranges from 20 % to 60 %.
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
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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
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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
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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.
Shaojie Song, Meng Gao, Weiqi Xu, Yele Sun, Douglas R. Worsnop, John T. Jayne, Yuzhong Zhang, Lei Zhu, Mei Li, Zhen Zhou, Chunlei Cheng, Yibing Lv, Ying Wang, Wei Peng, Xiaobin Xu, Nan Lin, Yuxuan Wang, Shuxiao Wang, J. William Munger, Daniel J. Jacob, and Michael B. McElroy
Atmos. Chem. Phys., 19, 1357–1371, https://doi.org/10.5194/acp-19-1357-2019, https://doi.org/10.5194/acp-19-1357-2019, 2019
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Chemistry responsible for sulfate production in northern China winter haze remains mysterious. We propose a potentially key pathway through the reaction of formaldehyde and sulfur dioxide that has not been accounted for in previous studies. The special atmospheric conditions favor the formation and existence of their complex, hydroxymethanesulfonate (HMS).
Lu Shen, Daniel J. Jacob, Loretta J. Mickley, Yuxuan Wang, and Qiang Zhang
Atmos. Chem. Phys., 18, 17489–17496, https://doi.org/10.5194/acp-18-17489-2018, https://doi.org/10.5194/acp-18-17489-2018, 2018
Eloise A. Marais, Daniel J. Jacob, Sungyeon Choi, Joanna Joiner, Maria Belmonte-Rivas, Ronald C. Cohen, Steffen Beirle, Lee T. Murray, Luke D. Schiferl, Viral Shah, and Lyatt Jaeglé
Atmos. Chem. Phys., 18, 17017–17027, https://doi.org/10.5194/acp-18-17017-2018, https://doi.org/10.5194/acp-18-17017-2018, 2018
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We intercompare two new products of global upper tropospheric nitrogen dioxide (NO2) retrieved from the Ozone Monitoring Instrument (OMI). We evaluate these products with aircraft observations from NASA DC8 aircraft campaigns and interpret the useful information these products can provide about nitrogen oxides (NOx) in the global upper troposphere using the GEOS-Chem chemical transport model.
Jian-Xiong Sheng, Daniel J. Jacob, Joannes D. Maasakkers, Yuzhong Zhang, and Melissa P. Sulprizio
Atmos. Meas. Tech., 11, 6379–6388, https://doi.org/10.5194/amt-11-6379-2018, https://doi.org/10.5194/amt-11-6379-2018, 2018
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We conduct Observing System Simulation Experiments to compare the ability of future satellite measurements of atmospheric methane columns for constraining methane emissions at the 25 km scale. We find that the geostationary instruments can do much better than TROPOMI and are less sensitive to cloud cover. GeoCARB observing twice a day would provide 70 % of the information from the nominal GEO-CAPE mission considered by NASA in response to the Decadal Survey of the US National Research Council.
Daniel H. Cusworth, Daniel J. Jacob, Jian-Xiong Sheng, Joshua Benmergui, Alexander J. Turner, Jeremy Brandman, Laurent White, and Cynthia A. Randles
Atmos. Chem. Phys., 18, 16885–16896, https://doi.org/10.5194/acp-18-16885-2018, https://doi.org/10.5194/acp-18-16885-2018, 2018
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Methane emissions from oil/gas fields originate from a large number of small and densely clustered point sources. We examine the potential of recently launched or planned satellites to locate these high-mode emitters through measurements of atmospheric methane. We find that the recently launched TROPOMI and the planned GeoCARB instruments are successful at locating high-emitting sources for fields of 20-50 emitters within the 50 × 50 km2 geographic domain but are unsuccessful for denser fields.
Fei Liu, Sungyeon Choi, Can Li, Vitali E. Fioletov, Chris A. McLinden, Joanna Joiner, Nickolay A. Krotkov, Huisheng Bian, Greet Janssens-Maenhout, Anton S. Darmenov, and Arlindo M. da Silva
Atmos. Chem. Phys., 18, 16571–16586, https://doi.org/10.5194/acp-18-16571-2018, https://doi.org/10.5194/acp-18-16571-2018, 2018
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Sulfur dioxide measurements from space have been used to detect emissions from large sources. We developed a new emission inventory by combining the satellite-based emission estimates and the conventional bottom-up inventory for smaller sources. The new inventory improves the model agreement with in situ observations and offers the possibility of rapid updates to emissions.
Yuzhong Zhang, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Ritesh Gautam, and John Worden
Atmos. Chem. Phys., 18, 15959–15973, https://doi.org/10.5194/acp-18-15959-2018, https://doi.org/10.5194/acp-18-15959-2018, 2018
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We assess the potential of using satellite observations of atmospheric methane to monitor global mean tropospheric OH concentration, a key parameter for the oxidizing power of the atmosphere.
Daniel J. Varon, Daniel J. Jacob, Jason McKeever, Dylan Jervis, Berke O. A. Durak, Yan Xia, and Yi Huang
Atmos. Meas. Tech., 11, 5673–5686, https://doi.org/10.5194/amt-11-5673-2018, https://doi.org/10.5194/amt-11-5673-2018, 2018
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Methane is a powerful greenhouse gas emitted from numerous human activities. Space-based observation of point sources would be a cost-effective monitoring solution, but the resolution of most current and planned methane-observing satellites is too coarse to resolve individual emitters. We simulate fine-resolution (50 m) satellite observations of methane plumes as would be measured by GHGSat (to be launched in 2019) and show that such data can usefully quantify large methane point sources.
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
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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.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Joshua Benmergui, A. Anthony Bloom, Claudia Arndt, Ritesh Gautam, Daniel Zavala-Araiza, Hartmut Boesch, and Robert J. Parker
Atmos. Chem. Phys., 18, 12257–12267, https://doi.org/10.5194/acp-18-12257-2018, https://doi.org/10.5194/acp-18-12257-2018, 2018
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Analysis of 7 years (2010–2016) of GOSAT methane trends over Canada, the contiguous US, and Mexico suggests that US methane emissions increased by 2.5 ± 1.4 % a−1 over the 7-year period, with contributions from both oil–gas systems and livestock in the Midwest. Mexican emissions show a decrease that can be attributed to a decreasing cattle population. Canadian emissions show year-to-year variability driven by wetland emissions and correlated with wetland areal extent.
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
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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.
Angela Benedetti, Jeffrey S. Reid, Peter Knippertz, John H. Marsham, Francesca Di Giuseppe, Samuel Rémy, Sara Basart, Olivier Boucher, Ian M. Brooks, Laurent Menut, Lucia Mona, Paolo Laj, Gelsomina Pappalardo, Alfred Wiedensohler, Alexander Baklanov, Malcolm Brooks, Peter R. Colarco, Emilio Cuevas, Arlindo da Silva, Jeronimo Escribano, Johannes Flemming, Nicolas Huneeus, Oriol Jorba, Stelios Kazadzis, Stefan Kinne, Thomas Popp, Patricia K. Quinn, Thomas T. Sekiyama, Taichu Tanaka, and Enric Terradellas
Atmos. Chem. Phys., 18, 10615–10643, https://doi.org/10.5194/acp-18-10615-2018, https://doi.org/10.5194/acp-18-10615-2018, 2018
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Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation authorities, solar energy plant managers, climate service providers, and health professionals. This paper describes the advances in the field and sets out requirements for observations for the sustainability of these activities.
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
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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.
Jun Wang, Partha S. Bhattacharjee, Vijay Tallapragada, Cheng-Hsuan Lu, Shobha Kondragunta, Arlindo da Silva, Xiaoyang Zhang, Sheng-Po Chen, Shih-Wei Wei, Anton S. Darmenov, Jeff McQueen, Pius Lee, Prabhat Koner, and Andy Harris
Geosci. Model Dev., 11, 2315–2332, https://doi.org/10.5194/gmd-11-2315-2018, https://doi.org/10.5194/gmd-11-2315-2018, 2018
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The NEMS GFS Aerosol Component (NGAC) version 2.0 for global multispecies aerosol forecast was developed at NCEP. Additional sea salt, sulfate, organic carbon, and black carbon aerosol species were included. This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been provided to meet the stakeholder's needs.
Alexander J. Turner, Daniel J. Jacob, Joshua Benmergui, Jeremy Brandman, Laurent White, and Cynthia A. Randles
Atmos. Chem. Phys., 18, 8265–8278, https://doi.org/10.5194/acp-18-8265-2018, https://doi.org/10.5194/acp-18-8265-2018, 2018
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We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 km spatial resolution and hourly temporal resolution over the Barnett Shale. We find that a week of TROPOMI observations should provide regional (~30 km) information on temporally invariant sources and GeoCARB should provide information on temporally invariant sources at 2–7 km spatial resolution. An instrument precision better than 6 ppb is an important threshold for achieving fine resolution of emissions.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Melissa P. Sulprizio, A. Anthony Bloom, Arlyn E. Andrews, and Debra Wunch
Atmos. Chem. Phys., 18, 6483–6491, https://doi.org/10.5194/acp-18-6483-2018, https://doi.org/10.5194/acp-18-6483-2018, 2018
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We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US to estimate methane emissions in that region. Our results suggest that the EPA inventory is regionally unbiased but there are large local biases, suggesting variable emission factors. Our results also suggest that the choice of landcover map is the dominant source of error for wetland emission estimates.
Stuart K. Grange, David C. Carslaw, Alastair C. Lewis, Eirini Boleti, and Christoph Hueglin
Atmos. Chem. Phys., 18, 6223–6239, https://doi.org/10.5194/acp-18-6223-2018, https://doi.org/10.5194/acp-18-6223-2018, 2018
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Weather (meteorology) has a strong effect on air quality; if not accounted for, there is uncertainty surrounding what drives features in air quality time series. We present a machine learning approach to account for meteorology using PM10 data in Switzerland. With the exception of one site, all Swiss normalised PM10 trends were found to significantly decrease, which validates air quality management efforts. The machine learning models were interpreted to investigate interesting processes.
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
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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.
Jiawei Zhuang, Daniel J. Jacob, and Sebastian D. Eastham
Atmos. Chem. Phys., 18, 6039–6055, https://doi.org/10.5194/acp-18-6039-2018, https://doi.org/10.5194/acp-18-6039-2018, 2018
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Our work explains why current model simulations are unable to capture the intercontinental influences of pollution plumes that are often observed over some regions like California. Due to inadequate vertical grid resolution in these models, the plumes get diffused too rapidly during intercontinental transport. Increasing the vertical grid resolution greatly improves the simulation of plumes and considerably increases the estimate of local surface pollution influence.
Jennifer Kaiser, Daniel J. Jacob, Lei Zhu, Katherine R. Travis, Jenny A. Fisher, Gonzalo González Abad, Lin Zhang, Xuesong Zhang, Alan Fried, John D. Crounse, Jason M. St. Clair, and Armin Wisthaler
Atmos. Chem. Phys., 18, 5483–5497, https://doi.org/10.5194/acp-18-5483-2018, https://doi.org/10.5194/acp-18-5483-2018, 2018
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Isoprene emissions from vegetation have a large effect on atmospheric chemistry and air quality. Here we use the adjoint of GEOS-Chem in an inversion of OMI formaldehyde observations to produce top-down estimates of isoprene emissions in the southeast US during the summer of 2013. We find that MEGAN v2.1 is biased high on average by 40 %. Our downward correction of isoprene emissions leads to a small reduction in modeled surface O3 and decreases the contribution of isoprene to organic aerosol.
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
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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.
Igor Veselovskii, Philippe Goloub, Thierry Podvin, Didier Tanre, Arlindo da Silva, Peter Colarco, Patricia Castellanos, Mikhail Korenskiy, Qiaoyun Hu, David N. Whiteman, Daniel Pérez-Ramírez, Patrick Augustin, Marc Fourmentin, and Alexei Kolgotin
Atmos. Meas. Tech., 11, 949–969, https://doi.org/10.5194/amt-11-949-2018, https://doi.org/10.5194/amt-11-949-2018, 2018
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Observations of multiwavelength Mie–Raman lidar during smoke episode over West Africa are compared with the vertical distribution of aerosol parameters provided by the MERRA-2 model. The values of modeled and observed extinctions at both 355 nm and 532 nm are also rather close. The model predicts significant concentration of dust particles inside the smoke layer. This is supported by a high depolarization ratio of 15 % observed in the center of this layer.
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
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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
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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
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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
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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 R. Colarco, Santiago Gassó, Changwoo Ahn, Virginie Buchard, Arlindo M. da Silva, and Omar Torres
Atmos. Meas. Tech., 10, 4121–4134, https://doi.org/10.5194/amt-10-4121-2017, https://doi.org/10.5194/amt-10-4121-2017, 2017
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We need satellite observations to characterize the properties of atmospheric aerosols. Those observations have uncertainties associated with them because of assumptions made in their algorithms. We test the assumptions on a part of the aerosol algorithms used with the Ozone Monitoring Instrument (OMI) flying on the NASA Aura spacecraft. We simulate the OMI observations using a global aerosol model, and then compare what OMI tells us about the simulated aerosols with the model results directly.
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
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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
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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.
Christopher Chan Miller, Daniel J. Jacob, Eloise A. Marais, Karen Yu, Katherine R. Travis, Patrick S. Kim, Jenny A. Fisher, Lei Zhu, Glenn M. Wolfe, Thomas F. Hanisco, Frank N. Keutsch, Jennifer Kaiser, Kyung-Eun Min, Steven S. Brown, Rebecca A. Washenfelder, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 17, 8725–8738, https://doi.org/10.5194/acp-17-8725-2017, https://doi.org/10.5194/acp-17-8725-2017, 2017
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The use of satellite glyoxal observations for estimating isoprene emissions has been limited by knowledge of the glyoxal yield from isoprene. We use SENEX aircraft observations over the southeast US to evaluate glyoxal yields from isoprene in a 3-D atmospheric model. The SENEX observations support a pathway for glyoxal formation in pristine regions that we propose here, which may have implications for improving isoprene emissions estimates from upcoming high-resolution geostationary satellites.
A. Anthony Bloom, Kevin W. Bowman, Meemong Lee, Alexander J. Turner, Ronny Schroeder, John R. Worden, Richard Weidner, Kyle C. McDonald, and Daniel J. Jacob
Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, https://doi.org/10.5194/gmd-10-2141-2017, 2017
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Wetland emissions are a principal source of uncertainty in the global atmospheric methane budget due to poor knowledge of wetland processes. We construct a wetland methane emission and uncertainty dataset for use in global atmospheric methane models. Our wetland model ensemble is based on static wetland maps, satellite-derived inundation and carbon cycle models. The ensemble performs favourably against regional flux estimates and atmospheric methane measurements relative to previous studies.
Hannah M. Horowitz, Daniel J. Jacob, Yanxu Zhang, Theodore S. Dibble, Franz Slemr, Helen M. Amos, Johan A. Schmidt, Elizabeth S. Corbitt, Eloïse A. Marais, and Elsie M. Sunderland
Atmos. Chem. Phys., 17, 6353–6371, https://doi.org/10.5194/acp-17-6353-2017, https://doi.org/10.5194/acp-17-6353-2017, 2017
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Mercury is a toxic, global pollutant released to the air from human activities like coal burning. Chemical reactions in air determine how far mercury is transported before it is deposited to the environment, where it may be converted to a form that accumulates in fish. We use a 3-D atmospheric model to evaluate a new set of chemical reactions and its effects on mercury deposition. We find it is consistent with observations and leads to increased deposition to oceans, especially in the tropics.
Rachel F. Silvern, Daniel J. Jacob, Patrick S. Kim, Eloise A. Marais, Jay R. Turner, Pedro Campuzano-Jost, and Jose L. Jimenez
Atmos. Chem. Phys., 17, 5107–5118, https://doi.org/10.5194/acp-17-5107-2017, https://doi.org/10.5194/acp-17-5107-2017, 2017
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We identify a fundamental discrepancy between thermodynamic equilibrium theory and observations of inorganic aerosol composition in the eastern US in summer that shows low ammonium sulfate aerosol ratios. In addition, from 2003 to 2013, while SO2 emissions have declined due to US emission controls, aerosols have become more acidic in the southeastern US. To explain these observations, we suggest that the large and increasing source of organic aerosol may be affecting thermodynamic equilibrium.
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
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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.
Sebastian D. Eastham and Daniel J. Jacob
Atmos. Chem. Phys., 17, 2543–2553, https://doi.org/10.5194/acp-17-2543-2017, https://doi.org/10.5194/acp-17-2543-2017, 2017
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Intercontinental atmospheric transport can disrupt local chemistry and cause air quality issues thousands of kilometers from the source, complicating correct attribution of air quality exceedances. This transport occurs in long, thin plumes which current-generation models consistently fail to reproduce. Our study investigates the cause of this failure, finding that greater vertical resolution than is currently available is required to reliably resolve the plumes and their effects.
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
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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%.
Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Jianxiong Sheng, Kang Sun, Xiong Liu, Kelly Chance, Ilse Aben, Jason McKeever, and Christian Frankenberg
Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, https://doi.org/10.5194/acp-16-14371-2016, 2016
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Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned to launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify methane emissions from the global scale down to the scale of point sources.
Katherine R. Travis, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Lei Zhu, Karen Yu, Christopher C. Miller, Robert M. Yantosca, Melissa P. Sulprizio, Anne M. Thompson, Paul O. Wennberg, John D. Crounse, Jason M. St. Clair, Ronald C. Cohen, Joshua L. Laughner, Jack E. Dibb, Samuel R. Hall, Kirk Ullmann, Glenn M. Wolfe, Illana B. Pollack, Jeff Peischl, Jonathan A. Neuman, and Xianliang Zhou
Atmos. Chem. Phys., 16, 13561–13577, https://doi.org/10.5194/acp-16-13561-2016, https://doi.org/10.5194/acp-16-13561-2016, 2016
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Ground-level ozone pollution in the Southeast US involves complex chemistry driven by anthropogenic emissions of nitrogen oxides (NOx) and biogenic emissions of isoprene. We find that US NOx emissions are overestimated nationally by as much as 50 % and that reducing model emissions by this amount results in good agreement with SEAC4RS aircraft measurements in August and September 2013. Observations of nitrate wet deposition fluxes and satellite NO2 columns further support this result.
Lei Zhu, Daniel J. Jacob, Patrick S. Kim, Jenny A. Fisher, Karen Yu, Katherine R. Travis, Loretta J. Mickley, Robert M. Yantosca, Melissa P. Sulprizio, Isabelle De Smedt, Gonzalo González Abad, Kelly Chance, Can Li, Richard Ferrare, Alan Fried, Johnathan W. Hair, Thomas F. Hanisco, Dirk Richter, Amy Jo Scarino, James Walega, Petter Weibring, and Glenn M. Wolfe
Atmos. Chem. Phys., 16, 13477–13490, https://doi.org/10.5194/acp-16-13477-2016, https://doi.org/10.5194/acp-16-13477-2016, 2016
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HCHO column data are widely used as a proxy for VOCs emissions, but validation of the data has been extremely limited. We use accurate aircraft observations to validate and intercompare 6 HCHO retrievals with GEOS-Chem as the intercomparison platform. Retrievals are interconsistent in spatial variability over the SE US and in daily variability, but are biased low by 20–51 %. Our work supports the use of HCHO column as a quantitative proxy for isoprene emission after correction of the low bias.
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
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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.
Glenn M. Wolfe, Margaret R. Marvin, Sandra J. Roberts, Katherine R. Travis, and Jin Liao
Geosci. Model Dev., 9, 3309–3319, https://doi.org/10.5194/gmd-9-3309-2016, https://doi.org/10.5194/gmd-9-3309-2016, 2016
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The Framework for 0-D Atmospheric Modeling (F0AM) is a new, user-friendly platform for simulation of atmospheric chemistry systems. It incorporates a suite of commonly used mechanisms and is adaptable to photochemical chambers, Lagrangian plumes, and steady-state or time-varying diurnal cycles. We provide a detailed model description, demonstrate several common applications, and highlight some of the advantages and challenges of the 0-D box modeling approach.
Galina Wind, Arlindo M. da Silva, Peter M. Norris, Steven Platnick, Shana Mattoo, and Robert C. Levy
Geosci. Model Dev., 9, 2377–2389, https://doi.org/10.5194/gmd-9-2377-2016, https://doi.org/10.5194/gmd-9-2377-2016, 2016
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The MCARS code creates sensor radiances using model-generated atmospheric columns and actual sensor and solar geometry. MCARS output looks like real data, so it is usable by any code that reads MODIS data. MCARS output can be used to test remote-sensing retrieval algorithms. Users know what went into creating the radiance: atmosphere, surface, clouds, and aerosols. Models can use MCARS output to create new parameterizations of relations of atmospheric physical quantities and measured radiances.
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
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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.
Cheng-Hsuan Lu, Arlindo da Silva, Jun Wang, Shrinivas Moorthi, Mian Chin, Peter Colarco, Youhua Tang, Partha S. Bhattacharjee, Shen-Po Chen, Hui-Ya Chuang, Hann-Ming Henry Juang, Jeffery McQueen, and Mark Iredell
Geosci. Model Dev., 9, 1905–1919, https://doi.org/10.5194/gmd-9-1905-2016, https://doi.org/10.5194/gmd-9-1905-2016, 2016
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Aerosols have an important effect on the Earth's climate and implications for public health. NASA has partnered with NOAA to transfer GOCART aerosol model to NCEP, enabling the first global aerosol forecasting system at NOAA/NCEP. This collaboration reflects an effective research-to-operation transition, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders and to allow the effects of aerosols on weather and climate prediction to be considered.
Jenny A. Fisher, Daniel J. Jacob, Katherine R. Travis, Patrick S. Kim, Eloise A. Marais, Christopher Chan Miller, Karen Yu, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Jingqiu Mao, Paul O. Wennberg, John D. Crounse, Alex P. Teng, Tran B. Nguyen, Jason M. St. Clair, Ronald C. Cohen, Paul Romer, Benjamin A. Nault, Paul J. Wooldridge, Jose L. Jimenez, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Paul B. Shepson, Fulizi Xiong, Donald R. Blake, Allen H. Goldstein, Pawel K. Misztal, Thomas F. Hanisco, Glenn M. Wolfe, Thomas B. Ryerson, Armin Wisthaler, and Tomas Mikoviny
Atmos. Chem. Phys., 16, 5969–5991, https://doi.org/10.5194/acp-16-5969-2016, https://doi.org/10.5194/acp-16-5969-2016, 2016
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We use new airborne and ground-based observations from two summer 2013 campaigns in the southeastern US, interpreted with a chemical transport model, to understand the impact of isoprene and monoterpene chemistry on the atmospheric NOx budget via production of organic nitrates (RONO2). We find that a diversity of species contribute to observed RONO2. Our work implies that the NOx sink to RONO2 production is only sensitive to NOx emissions in regions where they are already low.
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
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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
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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.
Christopher Chan Miller, Daniel J. Jacob, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 16, 4631–4639, https://doi.org/10.5194/acp-16-4631-2016, https://doi.org/10.5194/acp-16-4631-2016, 2016
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Volatile organic compounds (VOCs) are important precursors for photochemical smog.
Glyoxal is an organic compound produced in the atmosphere from reactions of larger VOCs. OMI satellite observations of glyoxal show a large hotspot over the Pearl River delta. The hotspot can be explained by industrial paint and solvent emissions of aromatic VOCs. Our work shows OMI observations are consistent with current VOC emissions estimates, whereas previous work has suggested large underestimates.
Karen Yu, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Christopher C. Miller, Katherine R. Travis, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Ron C. Cohen, Jack E. Dibb, Alan Fried, Tomas Mikoviny, Thomas B. Ryerson, Paul O. Wennberg, and Armin Wisthaler
Atmos. Chem. Phys., 16, 4369–4378, https://doi.org/10.5194/acp-16-4369-2016, https://doi.org/10.5194/acp-16-4369-2016, 2016
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Increasing the spatial resolution of a chemical transport model may improve simulations but can be computationally expensive. Using observations from the SEAC4RS aircraft campaign, we find that at higher spatial resolutions, models are better able to simulate the chemical pathways of ozone precursors, but the overall effect on regional mean concentrations is small. This implies that for continental boundary layer applications, coarse resolution models are adequate.
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
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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
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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. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618, https://doi.org/10.5194/acp-16-1603-2016, https://doi.org/10.5194/acp-16-1603-2016, 2016
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Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
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
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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
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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.
H.-M. Lee, F. Paulot, D. K. Henze, K. Travis, D. J. Jacob, L. H. Pardo, and B. A. Schichtel
Atmos. Chem. Phys., 16, 525–540, https://doi.org/10.5194/acp-16-525-2016, https://doi.org/10.5194/acp-16-525-2016, 2016
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Sources of nitrogen deposition (Ndep) in Federal Class I areas in the US are investigated, identifying unique features in contributions from different species, sectors and locations. Ndep in many parks is impacted by emissions several hundred km away; the role of oxidized vs reduced sources varies regionally. Emissions reductions in the western US most effectively reduce the extent of areas in critical load exceedance, while reductions in the east most effectively reduce exceedance magnitudes.
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
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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.
P. S. Kim, D. J. Jacob, J. A. Fisher, K. Travis, K. Yu, L. Zhu, R. M. Yantosca, M. P. Sulprizio, J. L. Jimenez, P. Campuzano-Jost, K. D. Froyd, J. Liao, J. W. Hair, M. A. Fenn, C. F. Butler, N. L. Wagner, T. D. Gordon, A. Welti, P. O. Wennberg, J. D. Crounse, J. M. St. Clair, A. P. Teng, D. B. Millet, J. P. Schwarz, M. Z. Markovic, and A. E. Perring
Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, https://doi.org/10.5194/acp-15-10411-2015, 2015
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
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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
J. Kaiser, G. M. Wolfe, K. E. Min, S. S. Brown, C. C. Miller, D. J. Jacob, J. A. deGouw, M. Graus, T. F. Hanisco, J. Holloway, J. Peischl, I. B. Pollack, T. B. Ryerson, C. Warneke, R. A. Washenfelder, and F. N. Keutsch
Atmos. Chem. Phys., 15, 7571–7583, https://doi.org/10.5194/acp-15-7571-2015, https://doi.org/10.5194/acp-15-7571-2015, 2015
A. J. Turner and D. J. Jacob
Atmos. Chem. Phys., 15, 7039–7048, https://doi.org/10.5194/acp-15-7039-2015, https://doi.org/10.5194/acp-15-7039-2015, 2015
A. J. Turner, D. J. Jacob, K. J. Wecht, J. D. Maasakkers, E. Lundgren, A. E. Andrews, S. C. Biraud, H. Boesch, K. W. Bowman, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, A. Kuze, J. Notholt, H. Ohyama, R. Parker, V. H. Payne, R. Sussmann, C. Sweeney, V. A. Velazco, T. Warneke, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 15, 7049–7069, https://doi.org/10.5194/acp-15-7049-2015, https://doi.org/10.5194/acp-15-7049-2015, 2015
V. Buchard, A. M. da Silva, P. R. Colarco, A. Darmenov, C. A. Randles, R. Govindaraju, O. Torres, J. Campbell, and R. Spurr
Atmos. Chem. Phys., 15, 5743–5760, https://doi.org/10.5194/acp-15-5743-2015, https://doi.org/10.5194/acp-15-5743-2015, 2015
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MERRAero is an aerosol reanalysis based on the GEOS-5 earth system model that incorporates an online aerosol module and assimilation of AOD from MODIS sensors. This study assesses the quality of MERRAero absorption using independent OMI observations. In addition to comparisons to OMI absorption AOD, we have developed a radiative transfer interface to simulate the UV aerosol index from assimilated aerosol fields at OMI footprint. Also, we fully diagnose the model using MISR, AERONET and CALIPSO.
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
M. Baasandorj, D. B. Millet, L. Hu, D. Mitroo, and B. J. Williams
Atmos. Meas. Tech., 8, 1303–1321, https://doi.org/10.5194/amt-8-1303-2015, https://doi.org/10.5194/amt-8-1303-2015, 2015
M. S. Long, R. Yantosca, J. E. Nielsen, C. A. Keller, A. da Silva, M. P. Sulprizio, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 8, 595–602, https://doi.org/10.5194/gmd-8-595-2015, https://doi.org/10.5194/gmd-8-595-2015, 2015
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This paper presents results from the modularization of the GEOS-Chem chemical transport model, and its coupling as the chemical operator within the NASA-GMAO GEOS-5 Earth system model (ESM). The key findings are that chemistry within the modular GEOS-Chem system shows consistent, high strong-scaling properties across the range of distributed processors, transport is the limiting component prohibiting efficient scalability, and GEOS-Chem is able to generate suitable chemical results in an ESM.
W. R. Sessions, J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama, T. Y. Tanaka, J. M. Baldasano, S. Basart, M. E. Brooks, T. F. Eck, M. Iredell, J. A. Hansen, O. C. Jorba, H.-M. H. Juang, P. Lynch, J.-J. Morcrette, S. Moorthi, J. Mulcahy, Y. Pradhan, M. Razinger, C. B. Sampson, J. Wang, and D. L. Westphal
Atmos. Chem. Phys., 15, 335–362, https://doi.org/10.5194/acp-15-335-2015, https://doi.org/10.5194/acp-15-335-2015, 2015
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C. Chan Miller, G. Gonzalez Abad, H. Wang, X. Liu, T. Kurosu, D. J. Jacob, and K. Chance
Atmos. Meas. Tech., 7, 3891–3907, https://doi.org/10.5194/amt-7-3891-2014, https://doi.org/10.5194/amt-7-3891-2014, 2014
P. Kishcha, A. M. da Silva, B. Starobinets, C. N. Long, O. Kalashnikova, and P. Alpert
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-23309-2014, https://doi.org/10.5194/acpd-14-23309-2014, 2014
Revised manuscript not accepted
K. J. Wecht, D. J. Jacob, M. P. Sulprizio, G. W. Santoni, S. C. Wofsy, R. Parker, H. Bösch, and J. Worden
Atmos. Chem. Phys., 14, 8173–8184, https://doi.org/10.5194/acp-14-8173-2014, https://doi.org/10.5194/acp-14-8173-2014, 2014
C. A. Keller, M. S. Long, R. M. Yantosca, A. M. Da Silva, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 7, 1409–1417, https://doi.org/10.5194/gmd-7-1409-2014, https://doi.org/10.5194/gmd-7-1409-2014, 2014
P. Zoogman, D. J. Jacob, K. Chance, X. Liu, M. Lin, A. Fiore, and K. Travis
Atmos. Chem. Phys., 14, 6261–6271, https://doi.org/10.5194/acp-14-6261-2014, https://doi.org/10.5194/acp-14-6261-2014, 2014
L. Zhang, D. J. Jacob, X. Yue, N. V. Downey, D. A. Wood, and D. Blewitt
Atmos. Chem. Phys., 14, 5295–5309, https://doi.org/10.5194/acp-14-5295-2014, https://doi.org/10.5194/acp-14-5295-2014, 2014
M. S. Long, W. C. Keene, R. C. Easter, R. Sander, X. Liu, A. Kerkweg, and D. Erickson
Atmos. Chem. Phys., 14, 3397–3425, https://doi.org/10.5194/acp-14-3397-2014, https://doi.org/10.5194/acp-14-3397-2014, 2014
E. V. Fischer, D. J. Jacob, R. M. Yantosca, M. P. Sulprizio, D. B. Millet, J. Mao, F. Paulot, H. B. Singh, A. Roiger, L. Ries, R.W. Talbot, K. Dzepina, and S. Pandey Deolal
Atmos. Chem. Phys., 14, 2679–2698, https://doi.org/10.5194/acp-14-2679-2014, https://doi.org/10.5194/acp-14-2679-2014, 2014
V. Buchard, A. M. da Silva, P. Colarco, N. Krotkov, R. R. Dickerson, J. W. Stehr, G. Mount, E. Spinei, H. L. Arkinson, and H. He
Atmos. Chem. Phys., 14, 1929–1941, https://doi.org/10.5194/acp-14-1929-2014, https://doi.org/10.5194/acp-14-1929-2014, 2014
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
R. Sander, A. A. P. Pszenny, W. C. Keene, E. Crete, B. Deegan, M. S. Long, J. R. Maben, and A. H. Young
Earth Syst. Sci. Data, 5, 385–392, https://doi.org/10.5194/essd-5-385-2013, https://doi.org/10.5194/essd-5-385-2013, 2013
G. Wind, A. M. da Silva, P. M. Norris, and S. Platnick
Geosci. Model Dev., 6, 2049–2062, https://doi.org/10.5194/gmd-6-2049-2013, https://doi.org/10.5194/gmd-6-2049-2013, 2013
P. E. Saide, G. R. Carmichael, Z. Liu, C. S. Schwartz, H. C. Lin, A. M. da Silva, and E. Hyer
Atmos. Chem. Phys., 13, 10425–10444, https://doi.org/10.5194/acp-13-10425-2013, https://doi.org/10.5194/acp-13-10425-2013, 2013
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
P. S. Kim, D. J. Jacob, X. Liu, J. X. Warner, K. Yang, K. Chance, V. Thouret, and P. Nedelec
Atmos. Chem. Phys., 13, 9321–9335, https://doi.org/10.5194/acp-13-9321-2013, https://doi.org/10.5194/acp-13-9321-2013, 2013
L. Hu, D. B. Millet, S. Y. Kim, K. C. Wells, T. J. Griffis, E. V. Fischer, D. Helmig, J. Hueber, and A. J. Curtis
Atmos. Chem. Phys., 13, 3379–3392, https://doi.org/10.5194/acp-13-3379-2013, https://doi.org/10.5194/acp-13-3379-2013, 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
M. S. Long, W. C. Keene, R. Easter, R. Sander, A. Kerkweg, D. Erickson, X. Liu, and S. Ghan
Geosci. Model Dev., 6, 255–262, https://doi.org/10.5194/gmd-6-255-2013, https://doi.org/10.5194/gmd-6-255-2013, 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
J. Mao, S. Fan, D. J. Jacob, and K. R. Travis
Atmos. Chem. Phys., 13, 509–519, https://doi.org/10.5194/acp-13-509-2013, https://doi.org/10.5194/acp-13-509-2013, 2013
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Optimized dynamic mode decomposition for reconstruction and forecasting of atmospheric chemistry data
Interpolating turbulent heat fluxes missing from a prairie observation on the Tibetan Plateau using artificial intelligence models
Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
The Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP1): Evaluating simulated atmospheric transport of air-sea gas exchange tracers and APO flux products
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Development of a High-Resolution Coupled SHiELD-MOM6 Model. Part I – Model Overview, Coupling Technique, and Validation in a Regional Setup
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
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A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev., 18, 4667–4684, https://doi.org/10.5194/gmd-18-4667-2025, https://doi.org/10.5194/gmd-18-4667-2025, 2025
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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 the forecasting of atmospheric chemistry in a computationally tractable manner.
Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025, https://doi.org/10.5194/gmd-18-4625-2025, 2025
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This study evaluates various machine learning and statistical methods for interpolating turbulent heat flux data over the Tibetan Plateau. The Transformer model showed the best performance, leading to the development of the Transformer_CNN model, which combines global and local attention mechanisms. Results show that Transformer_CNN outperforms the other models and was successfully applied to interpolate heat flux data from 2007 to 2016.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
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We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
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A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
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Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
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We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
EGUsphere, https://doi.org/10.5194/egusphere-2025-1736, https://doi.org/10.5194/egusphere-2025-1736, 2025
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We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 exchange products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
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We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
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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.
We present a full-year online global simulation of tropospheric chemistry at 12.5 km resolution....
