Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4579-2020
© Author(s) 2020. 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-13-4579-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
28 Sep 2020
Model description paper |
| 28 Sep 2020
| 28 Sep 2020
Simulating the forest fire plume dispersion, chemistry, and aerosol formation using SAM-ASP version 1.0
Chantelle R. Lonsdale
Atmospheric and Environmental Research (AER), Lexington, MA 02421,
USA
Matthew J. Alvarado
CORRESPONDING AUTHOR
Atmospheric and Environmental Research (AER), Lexington, MA 02421,
USA
Anna L. Hodshire
Department of Atmospheric Science, Colorado State University, Fort
Collins, CO 80523, USA
Emily Ramnarine
Department of Atmospheric Science, Colorado State University, Fort
Collins, CO 80523, USA
Jeffrey R. Pierce
Department of Atmospheric Science, Colorado State University, Fort
Collins, CO 80523, USA
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Biomass burning emits particles and vapors that can impact both health and climate. Here, we investigate the role of dilution in the evolution of aerosol size and composition in observed US wildfire smoke plumes. Centers of plumes dilute more slowly than edges. We see differences in concentrations and composition between the centers and edges both in the first measurement and in subsequent measurements. Our findings support the hypothesis that plume dilution influences smoke aging.
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Atmos. Chem. Phys., 19, 6561–6577, https://doi.org/10.5194/acp-19-6561-2019, https://doi.org/10.5194/acp-19-6561-2019, 2019
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Biomass burning aerosols have important global radiative effects that depend on particle size. However, model estimates of these effects do not explicitly account for the coagulation of particles in biomass burning plumes. In this work, we present the first use of a sub-grid coagulation scheme in a global aerosol model to account for in-plume coagulation. We find that this in-plume coagulation leads to important changes in the biomass burning aerosol radiative effects.
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Linia Tashmim, William C. Porter, Qianjie Chen, Becky Alexander, Charles H. Fite, Christopher D. Holmes, Jeffrey R. Pierce, Betty Croft, and Sakiko Ishino
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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
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Haihui Zhu, Randall V. Martin, Betty Croft, Shixian Zhai, Chi Li, Liam Bindle, Jeffrey R. Pierce, Rachel Y.-W. Chang, Bruce E. Anderson, Luke D. Ziemba, Johnathan W. Hair, Richard A. Ferrare, Chris A. Hostetler, Inderjeet Singh, Deepangsu Chatterjee, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jack E. Dibb, Joshua S. Schwarz, and Andrew Weinheimer
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Anna L. Hodshire, Ezra J. T. Levin, A. Gannet Hallar, Christopher N. Rapp, Dan R. Gilchrist, Ian McCubbin, and Gavin R. McMeeking
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The new Continuous Flow Diffusion Chamber-Ice Activation Spectrometer collected 4 months of ice nucleating particle (INP) measurements at a 5-minute resolution at the mountainside Storm Peak Laboratory. Most long-term INP measurements are at a time resolution of a day or longer: our instrument is a promising advance towards high-resolution long-term INP measurements. We observe higher peak INP concentrations than previous mountain studies, possibly due to the higher time resolution of our data.
Mathew Sebastian, Sobhan Kumar Kompalli, Vasudevan Anil Kumar, Sandhya Jose, S. Suresh Babu, Govindan Pandithurai, Sachchidanand Singh, Rakesh K. Hooda, Vijay K. Soni, Jeffrey R. Pierce, Ville Vakkari, Eija Asmi, Daniel M. Westervelt, Antti-Pekka Hyvärinen, and Vijay P. Kanawade
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Anna L. Hodshire, Ezra J. T. Levin, A. Gannet Hallar, Christopher N. Rapp, Dan R. Gilchrist, Ian McCubbin, and Gavin R. McMeeking
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-29, https://doi.org/10.5194/acp-2022-29, 2022
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The new Continuous Flow Diffusion Chamber-Ice Activation Spectrometer collected 4 months of ice nucleating particle (INP) measurements at a 5-minute resolution at the mountainside Storm Peak Laboratory. Most long-term INP measurements are at a time resolution of a day or longer: our instrument is a promising advance towards high-resolution long-term INP measurements. We observe higher peak INP concentrations than previous mountain studies, possibly due to the higher time resolution of our data.
Michael Cheeseman, Bonne Ford, Zoey Rosen, Eric Wendt, Alex DesRosiers, Aaron J. Hill, Christian L'Orange, Casey Quinn, Marilee Long, Shantanu H. Jathar, John Volckens, and Jeffrey R. Pierce
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-751, https://doi.org/10.5194/acp-2021-751, 2021
Revised manuscript not accepted
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Eric A. Wendt, Casey Quinn, Christian L'Orange, Daniel D. Miller-Lionberg, Bonne Ford, Jeffrey R. Pierce, John Mehaffy, Michael Cheeseman, Shantanu H. Jathar, David H. Hagan, Zoey Rosen, Marilee Long, and John Volckens
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Anna L. Hodshire, Emily Ramnarine, Ali Akherati, Matthew L. Alvarado, Delphine K. Farmer, Shantanu H. Jathar, Sonia M. Kreidenweis, Chantelle R. Lonsdale, Timothy B. Onasch, Stephen R. Springston, Jian Wang, Yang Wang, Lawrence I. Kleinman, Arthur J. Sedlacek III, and Jeffrey R. Pierce
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Betty Croft, Randall V. Martin, Richard H. Moore, Luke D. Ziemba, Ewan C. Crosbie, Hongyu Liu, Lynn M. Russell, Georges Saliba, Armin Wisthaler, Markus Müller, Arne Schiller, Martí Galí, Rachel Y.-W. Chang, Erin E. McDuffie, Kelsey R. Bilsback, and Jeffrey R. Pierce
Atmos. Chem. Phys., 21, 1889–1916, https://doi.org/10.5194/acp-21-1889-2021, https://doi.org/10.5194/acp-21-1889-2021, 2021
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Agnieszka Kupc, Christina J. Williamson, Anna L. Hodshire, Jan Kazil, Eric Ray, T. Paul Bui, Maximilian Dollner, Karl D. Froyd, Kathryn McKain, Andrew Rollins, Gregory P. Schill, Alexander Thames, Bernadett B. Weinzierl, Jeffrey R. Pierce, and Charles A. Brock
Atmos. Chem. Phys., 20, 15037–15060, https://doi.org/10.5194/acp-20-15037-2020, https://doi.org/10.5194/acp-20-15037-2020, 2020
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Tropical upper troposphere over the Atlantic and Pacific oceans is a major source region of new particles. These particles are associated with the outflow from deep convection. We investigate the processes that govern the formation of these particles and their initial growth and show that none of the formation schemes commonly used in global models are consistent with observations. Using newer schemes indicates that organic compounds are likely important as nucleating and initial growth agents.
Lawrence I. Kleinman, Arthur J. Sedlacek III, Kouji Adachi, Peter R. Buseck, Sonya Collier, Manvendra K. Dubey, Anna L. Hodshire, Ernie Lewis, Timothy B. Onasch, Jeffery R. Pierce, John Shilling, Stephen R. Springston, Jian Wang, Qi Zhang, Shan Zhou, and Robert J. Yokelson
Atmos. Chem. Phys., 20, 13319–13341, https://doi.org/10.5194/acp-20-13319-2020, https://doi.org/10.5194/acp-20-13319-2020, 2020
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Aerosols from wildfires affect the Earth's temperature by absorbing light or reflecting it back into space. This study investigates time-dependent chemical, microphysical, and optical properties of aerosols generated by wildfires in the Pacific Northwest, USA. Wildfire smoke plumes were traversed by an instrumented aircraft at locations near the fire and up to 3.5 h travel time downwind. Although there was no net aerosol production, aerosol particles grew and became more efficient scatters.
W. Richard Leaitch, John K. Kodros, Megan D. Willis, Sarah Hanna, Hannes Schulz, Elisabeth Andrews, Heiko Bozem, Julia Burkart, Peter Hoor, Felicia Kolonjari, John A. Ogren, Sangeeta Sharma, Meng Si, Knut von Salzen, Allan K. Bertram, Andreas Herber, Jonathan P. D. Abbatt, and Jeffrey R. Pierce
Atmos. Chem. Phys., 20, 10545–10563, https://doi.org/10.5194/acp-20-10545-2020, https://doi.org/10.5194/acp-20-10545-2020, 2020
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Black carbon is a factor in the warming of the Arctic atmosphere due to its ability to absorb light, but the uncertainty is high and few observations have been made in the high Arctic above 80° N. We combine airborne and ground-based observations in the springtime Arctic, at and above 80° N, with simulations from a global model to show that light absorption by black carbon may be much larger than modelled. However, the uncertainty remains high.
Alma Hodzic, Pedro Campuzano-Jost, Huisheng Bian, Mian Chin, Peter R. Colarco, Douglas A. Day, Karl D. Froyd, Bernd Heinold, Duseong S. Jo, Joseph M. Katich, John K. Kodros, Benjamin A. Nault, Jeffrey R. Pierce, Eric Ray, Jacob Schacht, Gregory P. Schill, Jason C. Schroder, Joshua P. Schwarz, Donna T. Sueper, Ina Tegen, Simone Tilmes, Kostas Tsigaridis, Pengfei Yu, and Jose L. Jimenez
Atmos. Chem. Phys., 20, 4607–4635, https://doi.org/10.5194/acp-20-4607-2020, https://doi.org/10.5194/acp-20-4607-2020, 2020
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Organic aerosol (OA) is a key source of uncertainty in aerosol climate effects. We present the first pole-to-pole OA characterization during the NASA Atmospheric Tomography aircraft mission. OA has a strong seasonal and zonal variability, with the highest levels in summer and over fire-influenced regions and the lowest ones in the southern high latitudes. We show that global models predict the OA distribution well but not the relative contribution of OA emissions vs. chemical production.
Sidhant J. Pai, Colette L. Heald, Jeffrey R. Pierce, Salvatore C. Farina, Eloise A. Marais, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Ann M. Middlebrook, Hugh Coe, John E. Shilling, Roya Bahreini, Justin H. Dingle, and Kennedy Vu
Atmos. Chem. Phys., 20, 2637–2665, https://doi.org/10.5194/acp-20-2637-2020, https://doi.org/10.5194/acp-20-2637-2020, 2020
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Aerosols in the atmosphere have significant health and climate impacts. Organic aerosol (OA) accounts for a large fraction of the total aerosol burden, but models have historically struggled to accurately simulate it. This study compares two very different OA model schemes and evaluates them against a suite of globally distributed airborne measurements with the goal of providing insight into the strengths and weaknesses of each approach across different environments.
Mark W. Shephard, Enrico Dammers, Karen E. Cady-Pereira, Shailesh K. Kharol, Jesse Thompson, Yonatan Gainariu-Matz, Junhua Zhang, Chris A. McLinden, Andrew Kovachik, Michael Moran, Shabtai Bittman, Christopher E. Sioris, Debora Griffin, Matthew J. Alvarado, Chantelle Lonsdale, Verica Savic-Jovcic, and Qiong Zheng
Atmos. Chem. Phys., 20, 2277–2302, https://doi.org/10.5194/acp-20-2277-2020, https://doi.org/10.5194/acp-20-2277-2020, 2020
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Presented is a description and survey demonstrating the capabilities of the CrIS ammonia product for monitoring, air quality forecast model evaluation, dry deposition estimates, and emission estimates of an agricultural hotspot.
Bonne Ford, Jeffrey R. Pierce, Eric Wendt, Marilee Long, Shantanu Jathar, John Mehaffy, Jessica Tryner, Casey Quinn, Lizette van Zyl, Christian L'Orange, Daniel Miller-Lionberg, and John Volckens
Atmos. Meas. Tech., 12, 6385–6399, https://doi.org/10.5194/amt-12-6385-2019, https://doi.org/10.5194/amt-12-6385-2019, 2019
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This study demonstrates the use of a low-cost sensor in a citizen-science network, Citizen-Enabled Aerosol Measurements for Satellites (CEAMS), to measure air quality in participants’ backyards. The pilot network was conducted in the fall and winter of 2017 in northern Colorado. Measurements of aerosols taken by the citizens are also compared to standard air quality instruments.
Eric A. Wendt, Casey W. Quinn, Daniel D. Miller-Lionberg, Jessica Tryner, Christian L'Orange, Bonne Ford, Azer P. Yalin, Jeffrey R. Pierce, Shantanu Jathar, and John Volckens
Atmos. Meas. Tech., 12, 5431–5441, https://doi.org/10.5194/amt-12-5431-2019, https://doi.org/10.5194/amt-12-5431-2019, 2019
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We introduce a low-cost, compact device (aerosol mass and optical depth (AMOD) sampler) that can be used by citizen scientists to measure air quality. Our paper discusses the development and different components for measuring aerosols. It also shows that measurements made by the AMOD next to reference-grade monitors agreed within 10 %. Coupled with the cost of these instruments, this agreement demonstrates that the AMOD can be widely deployed to monitor air quality by citizen scientists.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617, https://doi.org/10.5194/acp-19-8591-2019, https://doi.org/10.5194/acp-19-8591-2019, 2019
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Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Emily Ramnarine, John K. Kodros, Anna L. Hodshire, Chantelle R. Lonsdale, Matthew J. Alvarado, and Jeffrey R. Pierce
Atmos. Chem. Phys., 19, 6561–6577, https://doi.org/10.5194/acp-19-6561-2019, https://doi.org/10.5194/acp-19-6561-2019, 2019
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Biomass burning aerosols have important global radiative effects that depend on particle size. However, model estimates of these effects do not explicitly account for the coagulation of particles in biomass burning plumes. In this work, we present the first use of a sub-grid coagulation scheme in a global aerosol model to account for in-plume coagulation. We find that this in-plume coagulation leads to important changes in the biomass burning aerosol radiative effects.
Anna L. Hodshire, Pedro Campuzano-Jost, John K. Kodros, Betty Croft, Benjamin A. Nault, Jason C. Schroder, Jose L. Jimenez, and Jeffrey R. Pierce
Atmos. Chem. Phys., 19, 3137–3160, https://doi.org/10.5194/acp-19-3137-2019, https://doi.org/10.5194/acp-19-3137-2019, 2019
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A global chemical-transport model is used to determine the impact of methanesulfonic acid (MSA) on the aerosol size distribution and associated radiative effects, testing varying assumptions of MSA’s effective volatility and nucleating ability. We find that MSA mass best matches the ATom airborne measurements when volatility varies as a function of temperature, relative humidity, and available gas-phase bases, and the MSA radiative forcing is on the order of -50 mW m-2 over the Southern Ocean.
Betty Croft, Randall V. Martin, W. Richard Leaitch, Julia Burkart, Rachel Y.-W. Chang, Douglas B. Collins, Patrick L. Hayes, Anna L. Hodshire, Lin Huang, John K. Kodros, Alexander Moravek, Emma L. Mungall, Jennifer G. Murphy, Sangeeta Sharma, Samantha Tremblay, Gregory R. Wentworth, Megan D. Willis, Jonathan P. D. Abbatt, and Jeffrey R. Pierce
Atmos. Chem. Phys., 19, 2787–2812, https://doi.org/10.5194/acp-19-2787-2019, https://doi.org/10.5194/acp-19-2787-2019, 2019
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Summertime Arctic atmospheric aerosols are strongly controlled by processes related to natural regional sources. We use a chemical transport model with size-resolved aerosol microphysics to interpret measurements made during summertime 2016 in the Canadian Arctic Archipelago. Our results explore the processes that control summertime aerosol size distributions and support a climate-relevant role for Arctic marine secondary organic aerosol formed from precursor vapors with Arctic marine sources.
Jonathan P. D. Abbatt, W. Richard Leaitch, Amir A. Aliabadi, Allan K. Bertram, Jean-Pierre Blanchet, Aude Boivin-Rioux, Heiko Bozem, Julia Burkart, Rachel Y. W. Chang, Joannie Charette, Jai P. Chaubey, Robert J. Christensen, Ana Cirisan, Douglas B. Collins, Betty Croft, Joelle Dionne, Greg J. Evans, Christopher G. Fletcher, Martí Galí, Roya Ghahreman, Eric Girard, Wanmin Gong, Michel Gosselin, Margaux Gourdal, Sarah J. Hanna, Hakase Hayashida, Andreas B. Herber, Sareh Hesaraki, Peter Hoor, Lin Huang, Rachel Hussherr, Victoria E. Irish, Setigui A. Keita, John K. Kodros, Franziska Köllner, Felicia Kolonjari, Daniel Kunkel, Luis A. Ladino, Kathy Law, Maurice Levasseur, Quentin Libois, John Liggio, Martine Lizotte, Katrina M. Macdonald, Rashed Mahmood, Randall V. Martin, Ryan H. Mason, Lisa A. Miller, Alexander Moravek, Eric Mortenson, Emma L. Mungall, Jennifer G. Murphy, Maryam Namazi, Ann-Lise Norman, Norman T. O'Neill, Jeffrey R. Pierce, Lynn M. Russell, Johannes Schneider, Hannes Schulz, Sangeeta Sharma, Meng Si, Ralf M. Staebler, Nadja S. Steiner, Jennie L. Thomas, Knut von Salzen, Jeremy J. B. Wentzell, Megan D. Willis, Gregory R. Wentworth, Jun-Wei Xu, and Jacqueline D. Yakobi-Hancock
Atmos. Chem. Phys., 19, 2527–2560, https://doi.org/10.5194/acp-19-2527-2019, https://doi.org/10.5194/acp-19-2527-2019, 2019
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The Arctic is experiencing considerable environmental change with climate warming, illustrated by the dramatic decrease in sea-ice extent. It is important to understand both the natural and perturbed Arctic systems to gain a better understanding of how they will change in the future. This paper summarizes new insights into the relationships between Arctic aerosol particles and climate, as learned over the past five or so years by a large Canadian research consortium, NETCARE.
Ningxin Wang, Spiro D. Jorga, Jeffery R. Pierce, Neil M. Donahue, and Spyros N. Pandis
Atmos. Meas. Tech., 11, 6577–6588, https://doi.org/10.5194/amt-11-6577-2018, https://doi.org/10.5194/amt-11-6577-2018, 2018
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The interaction of particles with the chamber walls has been a significant source of uncertainty when analyzing results of secondary organic aerosol formation experiments performed in Teflon chambers. We evaluated the performance of several particle wall-loss correction methods for aging experiments of α-pinene ozonolysis products. Experimental procedures are proposed for the characterization of particle losses during different stages of these experiments.
Anna L. Hodshire, Brett B. Palm, M. Lizabeth Alexander, Qijing Bian, Pedro Campuzano-Jost, Eben S. Cross, Douglas A. Day, Suzane S. de Sá, Alex B. Guenther, Armin Hansel, James F. Hunter, Werner Jud, Thomas Karl, Saewung Kim, Jesse H. Kroll, Jeong-Hoo Park, Zhe Peng, Roger Seco, James N. Smith, Jose L. Jimenez, and Jeffrey R. Pierce
Atmos. Chem. Phys., 18, 12433–12460, https://doi.org/10.5194/acp-18-12433-2018, https://doi.org/10.5194/acp-18-12433-2018, 2018
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We investigate the nucleation and growth processes that shape the aerosol size distribution inside oxidation flow reactors (OFRs) that sampled ambient air from Colorado and the Amazon rainforest. Results indicate that organics are important for both nucleation and growth, vapor uptake was limited to accumulation-mode particles, fragmentation reactions were important to limit particle growth at higher OH exposures, and an H2SO4-organics nucleation mechanism captured new particle formation well.
John K. Kodros, Sarah J. Hanna, Allan K. Bertram, W. Richard Leaitch, Hannes Schulz, Andreas B. Herber, Marco Zanatta, Julia Burkart, Megan D. Willis, Jonathan P. D. Abbatt, and Jeffrey R. Pierce
Atmos. Chem. Phys., 18, 11345–11361, https://doi.org/10.5194/acp-18-11345-2018, https://doi.org/10.5194/acp-18-11345-2018, 2018
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The mixing state of black carbon is one of the key uncertainties limiting the ability of models to estimate the direct radiative effect. In this work, we present aircraft measurements from the Canadian Arctic of coating thickness as a function of black carbon core diameter and black-carbon-containing particle number fractions. We use these measurements to inform estimates of the direct radiative effect in Arctic aerosol simulations.
Jingqiu Mao, Annmarie Carlton, Ronald C. Cohen, William H. Brune, Steven S. Brown, Glenn M. Wolfe, Jose L. Jimenez, Havala O. T. Pye, Nga Lee Ng, Lu Xu, V. Faye McNeill, Kostas Tsigaridis, Brian C. McDonald, Carsten Warneke, Alex Guenther, Matthew J. Alvarado, Joost de Gouw, Loretta J. Mickley, Eric M. Leibensperger, Rohit Mathur, Christopher G. Nolte, Robert W. Portmann, Nadine Unger, Mika Tosca, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 2615–2651, https://doi.org/10.5194/acp-18-2615-2018, https://doi.org/10.5194/acp-18-2615-2018, 2018
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This paper is aimed at discussing progress in evaluating, diagnosing, and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models.
Haihan Chen, Anna L. Hodshire, John Ortega, James Greenberg, Peter H. McMurry, Annmarie G. Carlton, Jeffrey R. Pierce, Dave R. Hanson, and James N. Smith
Atmos. Chem. Phys., 18, 311–326, https://doi.org/10.5194/acp-18-311-2018, https://doi.org/10.5194/acp-18-311-2018, 2018
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Much of what we know about atmospheric new particle formation (NPF) is based on ground-level measurements. We used tethered balloon measurements and remote sensing to study the location in the boundary layer in which NPF events are initiated, the degree to which the boundary layer is well-mixed during NPF, and the potential role that water may play in aerosol particle chemical evolution. This information will improve the representativeness of process level models and laboratory experiments.
Roya Ghahreman, Ann-Lise Norman, Betty Croft, Randall V. Martin, Jeffrey R. Pierce, Julia Burkart, Ofelia Rempillo, Heiko Bozem, Daniel Kunkel, Jennie L. Thomas, Amir A. Aliabadi, Gregory R. Wentworth, Maurice Levasseur, Ralf M. Staebler, Sangeeta Sharma, and W. Richard Leaitch
Atmos. Chem. Phys., 17, 8757–8770, https://doi.org/10.5194/acp-17-8757-2017, https://doi.org/10.5194/acp-17-8757-2017, 2017
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We present spring and summertime vertical profile measurements of Arctic dimethyl sulfide (DMS), together with model simulations to consider what these profiles indicate about DMS sources and lifetimes in the Arctic. Our results highlight the role of local open water as the source of DMS(g) during July 2014 and the influence of long-range transport of DMS(g) from further afield in the Arctic during April 2015.
Bonne Ford, Moira Burke, William Lassman, Gabriele Pfister, and Jeffrey R. Pierce
Atmos. Chem. Phys., 17, 7541–7554, https://doi.org/10.5194/acp-17-7541-2017, https://doi.org/10.5194/acp-17-7541-2017, 2017
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We explore using the percent of Facebook posters mentioning
smokeor
air qualityto assess exposure to wildfire smoke in the western US during summer 2015. We compare this de-identified, aggregated Facebook dataset to satellite observations, surface measurements, and model-simulated concentrations, and we find good agreement in smoke-impacted regions. Our results suggest that aggregate social media data can be used to supplement traditional datasets to estimate smoke exposure.
Petros Vasilakos, Yong-Ηa Kim, Jeffrey R. Pierce, Sotira Yiacoumi, Costas Tsouris, and Athanasios Nenes
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-96, https://doi.org/10.5194/gmd-2017-96, 2017
Revised manuscript not accepted
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Radioactive charging can significantly impact the way radioactive aerosols behave, and as a result their lifetime, but such effects are neglected in predictive model studies of radioactive plumes. We extend a well-established model that simulates the evolution of atmospheric particulate matter to account for radioactive charging effects in an accurate and computationally efficient way. It is shown that radioactivity can strongly impact the deposition patterns of aerosol.
Qijing Bian, Shantanu H. Jathar, John K. Kodros, Kelley C. Barsanti, Lindsay E. Hatch, Andrew A. May, Sonia M. Kreidenweis, and Jeffrey R. Pierce
Atmos. Chem. Phys., 17, 5459–5475, https://doi.org/10.5194/acp-17-5459-2017, https://doi.org/10.5194/acp-17-5459-2017, 2017
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In this paper, we perform simulations of the evolution of biomass-burning organic aerosol in laboratory smog-chamber experiments and ambient plumes. We find that in smog-chamber experiments, vapor wall losses lead to a large reduction in the apparent secondary organic aerosol formation. In ambient plumes, fire size and meteorology regulate the plume dilution rate, primary organic aerosol evaporation rate, and secondary organic aerosol formation rate.
Chantelle R. Lonsdale, Jennifer D. Hegarty, Karen E. Cady-Pereira, Matthew J. Alvarado, Daven K. Henze, Matthew D. Turner, Shannon L. Capps, John B. Nowak, J. Andy Neuman, Ann M. Middlebrook, Roya Bahreini, Jennifer G. Murphy, Milos Z. Markovic, Trevor C. VandenBoer, Lynn M. Russell, and Amy Jo Scarino
Atmos. Chem. Phys., 17, 2721–2739, https://doi.org/10.5194/acp-17-2721-2017, https://doi.org/10.5194/acp-17-2721-2017, 2017
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This study takes advantage of the high-resolution observations of NH3(g) made by the TES satellite instrument over Bakersfield during the CalNex campaign, along with campaign measurements, to compare CMAQ model results in the San Joaquin Valley, California. Additionally we evaluate the CMAQ bi-directional ammonia flux results using the CARB emissions inventory against these satellite and campaign measurements, not previously explored in combination.
Theodora Nah, Renee C. McVay, Jeffrey R. Pierce, John H. Seinfeld, and Nga L. Ng
Atmos. Chem. Phys., 17, 2297–2310, https://doi.org/10.5194/acp-17-2297-2017, https://doi.org/10.5194/acp-17-2297-2017, 2017
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We present a model framework that accounts for coagulation in chamber studies where high seed aerosol surface area concentrations are used. The uncertainties in the calculated SOA mass concentrations and yields between four different particle-wall loss correction methods over the series of α-pinene ozonolysis experiments are also assessed. We show that SOA mass yields calculated by the four methods can deviate significantly in studies where high seed aerosol surface area concentrations are used.
Matthew J. Alvarado, Chantelle R. Lonsdale, Helen L. Macintyre, Huisheng Bian, Mian Chin, David A. Ridley, Colette L. Heald, Kenneth L. Thornhill, Bruce E. Anderson, Michael J. Cubison, Jose L. Jimenez, Yutaka Kondo, Lokesh K. Sahu, Jack E. Dibb, and Chien Wang
Atmos. Chem. Phys., 16, 9435–9455, https://doi.org/10.5194/acp-16-9435-2016, https://doi.org/10.5194/acp-16-9435-2016, 2016
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Understanding the scattering and absorption of light by aerosols is necessary for understanding air quality and climate change. We used data from the 2008 ARCTAS campaign to evaluate aerosol optical property models using a closure methodology that separates errors in these models from other errors in aerosol emissions, chemistry, or transport. We find that the models on average perform reasonably well, and make suggestions for how remaining biases could be reduced.
Anna L. Hodshire, Michael J. Lawler, Jun Zhao, John Ortega, Coty Jen, Taina Yli-Juuti, Jared F. Brewer, Jack K. Kodros, Kelley C. Barsanti, Dave R. Hanson, Peter H. McMurry, James N. Smith, and Jeffery R. Pierce
Atmos. Chem. Phys., 16, 9321–9348, https://doi.org/10.5194/acp-16-9321-2016, https://doi.org/10.5194/acp-16-9321-2016, 2016
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Processes that control the growth of newly formed particles are not well understood and limit predictions of aerosol climate impacts. We combine state-of-the-art measurements at a central-US site with a particle-growth model to investigate the species and processes contributing to growth. Observed growth was dominated by organics, sulfate salts, or a mixture of these two. The model qualitatively captures the variability between different days.
Kimiko M. Sakamoto, James R. Laing, Robin G. Stevens, Daniel A. Jaffe, and Jeffrey R. Pierce
Atmos. Chem. Phys., 16, 7709–7724, https://doi.org/10.5194/acp-16-7709-2016, https://doi.org/10.5194/acp-16-7709-2016, 2016
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We determine how various meteorological and fire factors contribute to shaping the aged biomass-burning particle size distribution through coagulation. The mass emissions flux, fire area, and wind speed are dominant factors controlling the aged size distribution. We parameterize the aged size distribution for global/regional aerosol models. We estimate that the aged biomass-burning particle size distribution may be more sensitive to variability in coagulation than SOA formation.
John K. Kodros, Rachel Cucinotta, David A. Ridley, Christine Wiedinmyer, and Jeffrey R. Pierce
Atmos. Chem. Phys., 16, 6771–6784, https://doi.org/10.5194/acp-16-6771-2016, https://doi.org/10.5194/acp-16-6771-2016, 2016
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We provide a first estimate of the aerosol radiative effects from open, uncontrolled combustion of domestic waste. We find the direct and cloud-albedo indirect radiative effects are predominantly negative (cooling tendency) with regional forcings exceeding −0.4 W m−2; however, the magnitude of these effects depends on the assumed emitted aerosol size, mass, and optical properties.
Betty Croft, Randall V. Martin, W. Richard Leaitch, Peter Tunved, Thomas J. Breider, Stephen D. D'Andrea, and Jeffrey R. Pierce
Atmos. Chem. Phys., 16, 3665–3682, https://doi.org/10.5194/acp-16-3665-2016, https://doi.org/10.5194/acp-16-3665-2016, 2016
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Measurements at high-Arctic sites show a strong annual cycle in atmospheric particle number and size. Previous studies identified poor scientific understanding related to global model representation of Arctic particle number and size, limiting ability to simulate this environment. Here we evaluate state-of-science ability to simulate Arctic particles using GEOS-Chem-TOMAS model, documenting key roles and interconnections of particle formation, cloud-related processes and remaining uncertainties.
N. I. Kristiansen, A. Stohl, D. J. L. Olivié, B. Croft, O. A. Søvde, H. Klein, T. Christoudias, D. Kunkel, S. J. Leadbetter, Y. H. Lee, K. Zhang, K. Tsigaridis, T. Bergman, N. Evangeliou, H. Wang, P.-L. Ma, R. C. Easter, P. J. Rasch, X. Liu, G. Pitari, G. Di Genova, S. Y. Zhao, Y. Balkanski, S. E. Bauer, G. S. Faluvegi, H. Kokkola, R. V. Martin, J. R. Pierce, M. Schulz, D. Shindell, H. Tost, and H. Zhang
Atmos. Chem. Phys., 16, 3525–3561, https://doi.org/10.5194/acp-16-3525-2016, https://doi.org/10.5194/acp-16-3525-2016, 2016
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Processes affecting aerosol removal from the atmosphere are not fully understood. In this study we investigate to what extent atmospheric transport models can reproduce observed loss of aerosols. We compare measurements of radioactive isotopes, that attached to ambient sulfate aerosols during the 2011 Fukushima nuclear accident, to 19 models using identical emissions. Results indicate aerosol removal that is too fast in most models, and apply to aerosols that have undergone long-range transport.
Gregory R. Wentworth, Jennifer G. Murphy, Betty Croft, Randall V. Martin, Jeffrey R. Pierce, Jean-Sébastien Côté, Isabelle Courchesne, Jean-Éric Tremblay, Jonathan Gagnon, Jennie L. Thomas, Sangeeta Sharma, Desiree Toom-Sauntry, Alina Chivulescu, Maurice Levasseur, and Jonathan P. D. Abbatt
Atmos. Chem. Phys., 16, 1937–1953, https://doi.org/10.5194/acp-16-1937-2016, https://doi.org/10.5194/acp-16-1937-2016, 2016
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Air near the surface in the summertime Arctic is extremely clean and typically has very low concentrations of both gases and particles. However, atmospheric measurements taken throughout the Canadian Arctic in the summer of 2014 revealed higher-than-expected amounts of gaseous ammonia. It is likely the majority of this ammonia is coming from migratory seabird colonies throughout the Arctic. Seabird guano (dung) releases ammonia which could impact climate and sensitive Arctic ecosystems.
S. D. D'Andrea, J. Y. Ng, J. K. Kodros, S. A. Atwood, M. J. Wheeler, A. M. Macdonald, W. R. Leaitch, and J. R. Pierce
Atmos. Chem. Phys., 16, 383–396, https://doi.org/10.5194/acp-16-383-2016, https://doi.org/10.5194/acp-16-383-2016, 2016
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We evaluate aerosol size distributions predicted by GEOS-Chem-TOMAS using measurements from the peak of Whistler Mountain. We improve model-measurement comparisons of aerosol number, size, and composition during periods of free-tropospheric and boundary-layer influence by developing simple filtering techniques, and determine the influence of Asian anthropogenic and biomass burning emissions. The low-cost filtering techniques and source apportionment methods can be used for other mountain sites.
R. S. Humphries, R. Schofield, M. D. Keywood, J. Ward, J. R. Pierce, C. M. Gionfriddo, M. T. Tate, D. P. Krabbenhoft, I. E. Galbally, S. B. Molloy, A. R. Klekociuk, P. V. Johnston, K. Kreher, A. J. Thomas, A. D. Robinson, N. R. P. Harris, R. Johnson, and S. R. Wilson
Atmos. Chem. Phys., 15, 13339–13364, https://doi.org/10.5194/acp-15-13339-2015, https://doi.org/10.5194/acp-15-13339-2015, 2015
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An atmospheric new particle formation event that was observed in the pristine East Antarctic pack ice during a springtime voyage in 2012 is characterised in terms of formation and growth rates. Known nucleation mechanisms (e.g. those involving sulfate, iodine and organics) were unable to explain observations; however, correlations with total gaseous mercury were found, leading to the suggestion of a possible mercury-driven nucleation mechanism not previously described.
C. E. Scott, D. V. Spracklen, J. R. Pierce, I. Riipinen, S. D. D'Andrea, A. Rap, K. S. Carslaw, P. M. Forster, P. Artaxo, M. Kulmala, L. V. Rizzo, E. Swietlicki, G. W. Mann, and K. J. Pringle
Atmos. Chem. Phys., 15, 12989–13001, https://doi.org/10.5194/acp-15-12989-2015, https://doi.org/10.5194/acp-15-12989-2015, 2015
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To understand the radiative effects of biogenic secondary organic aerosol (SOA) it is necessary to consider the manner in which it is distributed across the existing aerosol size distribution. We explore the importance of the approach taken by global-scale models to do this, when calculating the direct radiative effect (DRE) & first aerosol indirect effect (AIE) due to biogenic SOA. This choice has little effect on the DRE, but a substantial impact on the magnitude and even sign of the first AIE
Q. Bian, A. A. May, S. M. Kreidenweis, and J. R. Pierce
Atmos. Chem. Phys., 15, 11027–11045, https://doi.org/10.5194/acp-15-11027-2015, https://doi.org/10.5194/acp-15-11027-2015, 2015
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Losses of semi-volatile vapors to Teflon walls may contribute to significant primary particle evaporation during wood-smoke aerosol experiments. These vapor losses may also affect secondary organic aerosol formation during these experiments.
J. K. Kodros, C. E. Scott, S. C. Farina, Y. H. Lee, C. L'Orange, J. Volckens, and J. R. Pierce
Atmos. Chem. Phys., 15, 8577–8596, https://doi.org/10.5194/acp-15-8577-2015, https://doi.org/10.5194/acp-15-8577-2015, 2015
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We examine sensitivities in aerosol concentration and climate effects from biofuel combustion emissions. We find a strong sensitivity in the overall sign and magnitude of the direct radiative effect and cloud-albedo indirect effect due to uncertainties regarding emissions size distribution, composition, mass, and optical mixing state. This uncertainty limits our ability to evaluate black carbon mitigation strategies to counter warming effects from greenhouse gases.
M. J. Alvarado, C. R. Lonsdale, R. J. Yokelson, S. K. Akagi, H. Coe, J. S. Craven, E. V. Fischer, G. R. McMeeking, J. H. Seinfeld, T. Soni, J. W. Taylor, D. R. Weise, and C. E. Wold
Atmos. Chem. Phys., 15, 6667–6688, https://doi.org/10.5194/acp-15-6667-2015, https://doi.org/10.5194/acp-15-6667-2015, 2015
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Being able to understand and simulate the chemical evolution of biomass burning smoke plumes under a wide variety of conditions is a critical part of forecasting the impact of these fires on air quality, atmospheric composition, and climate. Here we use an improved model of this chemistry to simulate the evolution of ozone and secondary organic aerosol within a young biomass burning smoke plume from the Williams prescribed burn in chaparral, which was sampled over California in November 2009.
J. R. Pierce, B. Croft, J. K. Kodros, S. D. D'Andrea, and R. V. Martin
Atmos. Chem. Phys., 15, 6147–6158, https://doi.org/10.5194/acp-15-6147-2015, https://doi.org/10.5194/acp-15-6147-2015, 2015
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In this paper we show that coagulation of cloud droplets with interstitial aerosol particles, a process often neglected in atmospheric aerosol models, has a significant impact on aerosol size distributions and radiative forcings.
S. D. D'Andrea, J. C. Acosta Navarro, S. C. Farina, C. E. Scott, A. Rap, D. K. Farmer, D. V. Spracklen, I. Riipinen, and J. R. Pierce
Atmos. Chem. Phys., 15, 2247–2268, https://doi.org/10.5194/acp-15-2247-2015, https://doi.org/10.5194/acp-15-2247-2015, 2015
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We use modeled estimates of BVOCs from the years 1000 to 2000 to test the effect of anthropogenic BVOC emission changes on SOA formation, aerosol size distributions, and radiative effects using the GEOS-Chem-TOMAS model. Changes of >25% in the number of particles with diameters >80nm are predicted regionally due to extensive land-use changes, leading to increases in combined radiative effect of >0.5 Wm-2. This change in radiative forcing could be an overlooked anthropogenic effect on climate.
M. J. Alvarado, V. H. Payne, K. E. Cady-Pereira, J. D. Hegarty, S. S. Kulawik, K. J. Wecht, J. R. Worden, J. V. Pittman, and S. C. Wofsy
Atmos. Meas. Tech., 8, 965–985, https://doi.org/10.5194/amt-8-965-2015, https://doi.org/10.5194/amt-8-965-2015, 2015
K. M. Sakamoto, J. D. Allan, H. Coe, J. W. Taylor, T. J. Duck, and J. R. Pierce
Atmos. Chem. Phys., 15, 1633–1646, https://doi.org/10.5194/acp-15-1633-2015, https://doi.org/10.5194/acp-15-1633-2015, 2015
M. D. Gibson, J. Haelssig, J. R. Pierce, M. Parrington, J. E. Franklin, J. T. Hopper, Z. Li, and T. J. Ward
Atmos. Chem. Phys., 15, 815–827, https://doi.org/10.5194/acp-15-815-2015, https://doi.org/10.5194/acp-15-815-2015, 2015
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This paper presents a quantitative comparison of the four most commonly used receptor models, namely absolute principal component scores, pragmatic mass closure, chemical mass balance, and positive matrix factorization. The receptor models were used to predict the contributions of boreal wild-fire smoke and other sources to PM2.5 mass in Halifax, Nova Scotia, Canada during the BORTAS-B experiment. This paper also presents a new woodsmoke PM2.5 enrichment factor (levoglucosan x 52).
R. G. Stevens and J. R. Pierce
Atmos. Chem. Phys., 14, 13661–13679, https://doi.org/10.5194/acp-14-13661-2014, https://doi.org/10.5194/acp-14-13661-2014, 2014
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We implement a parameterization of sub-grid new-particle formation in sulfur-rich plumes (P6) for the first time into a global chemical-transport model with online aerosol microphysics. Compared with previous treatments of sub-grid particle formation, use of the P6 parameterization limits sub-grid particle formation in polluted or low-sunlight regions. We also test the sensitivity of sub-grid particle formation to changes in SO2 or NOx emissions due to emissions controls.
V. H. Payne, M. J. Alvarado, K. E. Cady-Pereira, J. R. Worden, S. S. Kulawik, and E. V. Fischer
Atmos. Meas. Tech., 7, 3737–3749, https://doi.org/10.5194/amt-7-3737-2014, https://doi.org/10.5194/amt-7-3737-2014, 2014
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Peroxyacetyl nitrate (PAN) plays an important role in the distribution of lower-atmospheric ozone. PAN can be transported far from the original pollution source, leading to ozone formation and degraded air quality in remote areas. Satellite observations from the Tropospheric Emission Spectrometer (TES) are sensitive to PAN at lower altitude than previous global data sets. We describe characteristics of the data and show elevated PAN associated with boreal fires and outflow of Asian pollution.
J. R. Pierce, D. M. Westervelt, S. A. Atwood, E. A. Barnes, and W. R. Leaitch
Atmos. Chem. Phys., 14, 8647–8663, https://doi.org/10.5194/acp-14-8647-2014, https://doi.org/10.5194/acp-14-8647-2014, 2014
D. M. Westervelt, J. R. Pierce, and P. J. Adams
Atmos. Chem. Phys., 14, 5577–5597, https://doi.org/10.5194/acp-14-5577-2014, https://doi.org/10.5194/acp-14-5577-2014, 2014
C. L. Heald, D. A. Ridley, J. H. Kroll, S. R. H. Barrett, K. E. Cady-Pereira, M. J. Alvarado, and C. D. Holmes
Atmos. Chem. Phys., 14, 5513–5527, https://doi.org/10.5194/acp-14-5513-2014, https://doi.org/10.5194/acp-14-5513-2014, 2014
B. Croft, J. R. Pierce, and R. V. Martin
Atmos. Chem. Phys., 14, 4313–4325, https://doi.org/10.5194/acp-14-4313-2014, https://doi.org/10.5194/acp-14-4313-2014, 2014
R. G. Stevens and J. R. Pierce
Atmos. Chem. Phys., 13, 12117–12133, https://doi.org/10.5194/acp-13-12117-2013, https://doi.org/10.5194/acp-13-12117-2013, 2013
S. D. D'Andrea, S. A. K. Häkkinen, D. M. Westervelt, C. Kuang, E. J. T. Levin, V. P. Kanawade, W. R. Leaitch, D. V. Spracklen, I. Riipinen, and J. R. Pierce
Atmos. Chem. Phys., 13, 11519–11534, https://doi.org/10.5194/acp-13-11519-2013, https://doi.org/10.5194/acp-13-11519-2013, 2013
G. S. Stuart, R. G. Stevens, A.-I. Partanen, A. K. L. Jenkins, H. Korhonen, P. M. Forster, D. V. Spracklen, and J. R. Pierce
Atmos. Chem. Phys., 13, 10385–10396, https://doi.org/10.5194/acp-13-10385-2013, https://doi.org/10.5194/acp-13-10385-2013, 2013
L. A. Lee, K. J. Pringle, C. L. Reddington, G. W. Mann, P. Stier, D. V. Spracklen, J. R. Pierce, and K. S. Carslaw
Atmos. Chem. Phys., 13, 8879–8914, https://doi.org/10.5194/acp-13-8879-2013, https://doi.org/10.5194/acp-13-8879-2013, 2013
Y. H. Lee, J. R. Pierce, and P. J. Adams
Geosci. Model Dev., 6, 1221–1232, https://doi.org/10.5194/gmd-6-1221-2013, https://doi.org/10.5194/gmd-6-1221-2013, 2013
S. A. K. Häkkinen, H. E. Manninen, T. Yli-Juuti, J. Merikanto, M. K. Kajos, T. Nieminen, S. D. D'Andrea, A. Asmi, J. R. Pierce, M. Kulmala, and I. Riipinen
Atmos. Chem. Phys., 13, 7665–7682, https://doi.org/10.5194/acp-13-7665-2013, https://doi.org/10.5194/acp-13-7665-2013, 2013
D. M. Westervelt, J. R. Pierce, I. Riipinen, W. Trivitayanurak, A. Hamed, M. Kulmala, A. Laaksonen, S. Decesari, and P. J. Adams
Atmos. Chem. Phys., 13, 7645–7663, https://doi.org/10.5194/acp-13-7645-2013, https://doi.org/10.5194/acp-13-7645-2013, 2013
M. D. Gibson, J. R. Pierce, D. Waugh, J. S. Kuchta, L. Chisholm, T. J. Duck, J. T. Hopper, S. Beauchamp, G. H. King, J. E. Franklin, W. R. Leaitch, A. J. Wheeler, Z. Li, G. A. Gagnon, and P. I. Palmer
Atmos. Chem. Phys., 13, 7199–7213, https://doi.org/10.5194/acp-13-7199-2013, https://doi.org/10.5194/acp-13-7199-2013, 2013
M. J. Alvarado, V. H. Payne, E. J. Mlawer, G. Uymin, M. W. Shephard, K. E. Cady-Pereira, J. S. Delamere, and J.-L. Moncet
Atmos. Chem. Phys., 13, 6687–6711, https://doi.org/10.5194/acp-13-6687-2013, https://doi.org/10.5194/acp-13-6687-2013, 2013
P. I. Palmer, M. Parrington, J. D. Lee, A. C. Lewis, A. R. Rickard, P. F. Bernath, T. J. Duck, D. L. Waugh, D. W. Tarasick, S. Andrews, E. Aruffo, L. J. Bailey, E. Barrett, S. J.-B. Bauguitte, K. R. Curry, P. Di Carlo, L. Chisholm, L. Dan, G. Forster, J. E. Franklin, M. D. Gibson, D. Griffin, D. Helmig, J. R. Hopkins, J. T. Hopper, M. E. Jenkin, D. Kindred, J. Kliever, M. Le Breton, S. Matthiesen, M. Maurice, S. Moller, D. P. Moore, D. E. Oram, S. J. O'Shea, R. C. Owen, C. M. L. S. Pagniello, S. Pawson, C. J. Percival, J. R. Pierce, S. Punjabi, R. M. Purvis, J. J. Remedios, K. M. Rotermund, K. M. Sakamoto, A. M. da Silva, K. B. Strawbridge, K. Strong, J. Taylor, R. Trigwell, K. A. Tereszchuk, K. A. Walker, D. Weaver, C. Whaley, and J. C. Young
Atmos. Chem. Phys., 13, 6239–6261, https://doi.org/10.5194/acp-13-6239-2013, https://doi.org/10.5194/acp-13-6239-2013, 2013
J. Worden, K. Wecht, C. Frankenberg, M. Alvarado, K. Bowman, E. Kort, S. Kulawik, M. Lee, V. Payne, and H. Worden
Atmos. Chem. Phys., 13, 3679–3692, https://doi.org/10.5194/acp-13-3679-2013, https://doi.org/10.5194/acp-13-3679-2013, 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
C. R. Lonsdale, R. G. Stevens, C. A. Brock, P. A. Makar, E. M. Knipping, and J. R. Pierce
Atmos. Chem. Phys., 12, 11519–11531, https://doi.org/10.5194/acp-12-11519-2012, https://doi.org/10.5194/acp-12-11519-2012, 2012
Related subject area
Atmospheric sciences
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
The MESSy DWARF (based on MESSy v2.55.2)
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification 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 model in atmospheric sciences.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
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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 more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Felipe Cifuentes, Henk Eskes, Folkert Boersma, Enrico Dammers, and Charlotte Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2225, https://doi.org/10.5194/egusphere-2024-2225, 2024
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOX emissions using synthetic NO2 satellite column retrievals derived from high-resolution model simulations. The FDA accurately reproduced NOX emissions when column observations were limited to the boundary layer and when the variability of NO2 lifetime, NOX:NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces a strong model dependency, reducing the simplicity of the original FDA formulation.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-117, https://doi.org/10.5194/gmd-2024-117, 2024
Revised manuscript accepted for GMD
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This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
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Short summary
The System for Atmospheric Modelling (SAM) has been coupled with the detailed gas/aerosol chemistry model, the Aerosol Simulation Program (ASP), to capture cross-plume concentration gradients as fire plumes evolve downwind. SAM-ASP v1.0 will lead to the development of parameterizations of near-source biomass burning chemistry that can be used to more accurately simulate biomass burning chemical and physical transformations of trace gases and aerosols within coarser chemical transport models.
The System for Atmospheric Modelling (SAM) has been coupled with the detailed gas/aerosol...
