Articles | Volume 6, issue 4
https://doi.org/10.5194/gmd-6-1221-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-1221-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Methods for assessment of models
| 
13 Aug 2013
Methods for assessment of models |
| 13 Aug 2013
Representation of nucleation mode microphysics in a global aerosol model with sectional microphysics
Y. H. Lee
NASA Goddard Institute for Space Studies, and Center for Climate Systems Research, Columbia University, New York, NY, USA
J. R. Pierce
Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
P. J. Adams
Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA
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Yunha Lee, Drew T. Shindell, Greg Faluvegi, and Rob W. Pinder
Atmos. Chem. Phys., 16, 5323–5342, https://doi.org/10.5194/acp-16-5323-2016, https://doi.org/10.5194/acp-16-5323-2016, 2016
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We studied the impact of US air quality (AQ) regulations and hypothetical CO2 reduction policy on public health and climate change. We find that AQ regulations are projected to have strong health benefits in the near future but result in a positive radiative forcing (RF), ~ 0.8 W m−2, over the USA. Under the US CO2 policy we find air quality co-benefits. However, despite CO2 reductions, it leads to overall positive RF (+0.22 W m−2 in 2055) over the USA mainly by lowering SO2 via less coal usage.
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.
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.
Y. H. Lee, P. J. Adams, and D. T. Shindell
Geosci. Model Dev., 8, 631–667, https://doi.org/10.5194/gmd-8-631-2015, https://doi.org/10.5194/gmd-8-631-2015, 2015
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We have implemented the TwO-Moment Aerosol Sectional (TOMAS) microphysics model in NASA GISS ModelE2, called “ModelE2-TOMAS”. We compared global budgets of ModelE2-TOMAS to other global aerosol models and evaluated the model with various observations such as aerosol precursor gas, aerosol mass, number concentrations, and aerosol optical depth. We found that ModelE2-TOMAS agrees with observations reasonably and that its predictions are within the range of other global aerosol model predictions.
J.-F. Lamarque, F. Dentener, J. McConnell, C.-U. Ro, M. Shaw, R. Vet, D. Bergmann, P. Cameron-Smith, S. Dalsoren, R. Doherty, G. Faluvegi, S. J. Ghan, B. Josse, Y. H. Lee, I. A. MacKenzie, D. Plummer, D. T. Shindell, R. B. Skeie, D. S. Stevenson, S. Strode, G. Zeng, M. Curran, D. Dahl-Jensen, S. Das, D. Fritzsche, and M. Nolan
Atmos. Chem. Phys., 13, 7997–8018, https://doi.org/10.5194/acp-13-7997-2013, https://doi.org/10.5194/acp-13-7997-2013, 2013
V. Naik, A. Voulgarakis, A. M. Fiore, L. W. Horowitz, J.-F. Lamarque, M. Lin, M. J. Prather, P. J. Young, D. Bergmann, P. J. Cameron-Smith, I. Cionni, W. J. Collins, S. B. Dalsøren, R. Doherty, V. Eyring, G. Faluvegi, G. A. Folberth, B. Josse, Y. H. Lee, I. A. MacKenzie, T. Nagashima, T. P. C. van Noije, D. A. Plummer, M. Righi, S. T. Rumbold, R. Skeie, D. T. Shindell, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, and G. Zeng
Atmos. Chem. Phys., 13, 5277–5298, https://doi.org/10.5194/acp-13-5277-2013, https://doi.org/10.5194/acp-13-5277-2013, 2013
K. W. Bowman, D. T. Shindell, H. M. Worden, J.F. Lamarque, P. J. Young, D. S. Stevenson, Z. Qu, M. de la Torre, D. Bergmann, P. J. Cameron-Smith, W. J. Collins, R. Doherty, S. B. Dalsøren, G. Faluvegi, G. Folberth, L. W. Horowitz, B. M. Josse, Y. H. Lee, I. A. MacKenzie, G. Myhre, T. Nagashima, V. Naik, D. A. Plummer, S. T. Rumbold, R. B. Skeie, S. A. Strode, K. Sudo, S. Szopa, A. Voulgarakis, G. Zeng, S. S. Kulawik, A. M. Aghedo, and J. R. Worden
Atmos. Chem. Phys., 13, 4057–4072, https://doi.org/10.5194/acp-13-4057-2013, https://doi.org/10.5194/acp-13-4057-2013, 2013
D. S. Stevenson, P. J. Young, V. Naik, J.-F. Lamarque, D. T. Shindell, A. Voulgarakis, R. B. Skeie, S. B. Dalsoren, G. Myhre, T. K. Berntsen, G. A. Folberth, S. T. Rumbold, W. J. Collins, I. A. MacKenzie, R. M. Doherty, G. Zeng, T. P. C. van Noije, A. Strunk, D. Bergmann, P. Cameron-Smith, D. A. Plummer, S. A. Strode, L. Horowitz, Y. H. Lee, S. Szopa, K. Sudo, T. Nagashima, B. Josse, I. Cionni, M. Righi, V. Eyring, A. Conley, K. W. Bowman, O. Wild, and A. Archibald
Atmos. Chem. Phys., 13, 3063–3085, https://doi.org/10.5194/acp-13-3063-2013, https://doi.org/10.5194/acp-13-3063-2013, 2013
P. J. Young, A. T. Archibald, K. W. Bowman, J.-F. Lamarque, V. Naik, D. S. Stevenson, S. Tilmes, A. Voulgarakis, O. Wild, D. Bergmann, P. Cameron-Smith, I. Cionni, W. J. Collins, S. B. Dalsøren, R. M. Doherty, V. Eyring, G. Faluvegi, L. W. Horowitz, B. Josse, Y. H. Lee, I. A. MacKenzie, T. Nagashima, D. A. Plummer, M. Righi, S. T. Rumbold, R. B. Skeie, D. T. Shindell, S. A. Strode, K. Sudo, S. Szopa, and G. Zeng
Atmos. Chem. Phys., 13, 2063–2090, https://doi.org/10.5194/acp-13-2063-2013, https://doi.org/10.5194/acp-13-2063-2013, 2013
J.-F. Lamarque, D. T. Shindell, B. Josse, P. J. Young, I. Cionni, V. Eyring, D. Bergmann, P. Cameron-Smith, W. J. Collins, R. Doherty, S. Dalsoren, G. Faluvegi, G. Folberth, S. J. Ghan, L. W. Horowitz, Y. H. Lee, I. A. MacKenzie, T. Nagashima, V. Naik, D. Plummer, M. Righi, S. T. Rumbold, M. Schulz, R. B. Skeie, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, A. Voulgarakis, and G. Zeng
Geosci. Model Dev., 6, 179–206, https://doi.org/10.5194/gmd-6-179-2013, https://doi.org/10.5194/gmd-6-179-2013, 2013
Linia Tashmim, William C. Porter, Qianjie Chen, Becky Alexander, Charles H. Fite, Christopher D. Holmes, Jeffrey R. Pierce, Betty Croft, and Sakiko Ishino
Atmos. Chem. Phys., 24, 3379–3403, https://doi.org/10.5194/acp-24-3379-2024, https://doi.org/10.5194/acp-24-3379-2024, 2024
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Dimethyl sulfide (DMS) is mostly emitted from ocean surfaces and represents the largest natural source of sulfur for the atmosphere. Once in the atmosphere, DMS forms stable oxidation products such as SO2 and H2SO4, which can subsequently contribute to airborne particle formation and growth. In this study, we update the DMS oxidation mechanism in the chemical transport model GEOS-Chem and describe resulting changes in particle growth as well as the overall global sulfur budget.
Lixu Jin, Wade Permar, Vanessa Selimovic, Damien Ketcherside, Robert J. Yokelson, Rebecca S. Hornbrook, Eric C. Apel, I-Ting Ku, Jeffrey L. Collett Jr., Amy P. Sullivan, Daniel A. Jaffe, Jeffrey R. Pierce, Alan Fried, Matthew M. Coggon, Georgios I. Gkatzelis, Carsten Warneke, Emily V. Fischer, and Lu Hu
Atmos. Chem. Phys., 23, 5969–5991, https://doi.org/10.5194/acp-23-5969-2023, https://doi.org/10.5194/acp-23-5969-2023, 2023
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Air quality in the USA has been improving since 1970 due to anthropogenic emission reduction. Those gains have been partly offset by increased wildfire pollution in the western USA in the past 20 years. Still, we do not understand wildfire emissions well due to limited measurements. Here, we used a global transport model to evaluate and constrain current knowledge of wildfire emissions with recent observational constraints, showing the underestimation of wildfire emissions in the western USA.
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
Atmos. Chem. Phys., 23, 5023–5042, https://doi.org/10.5194/acp-23-5023-2023, https://doi.org/10.5194/acp-23-5023-2023, 2023
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Particle size of atmospheric aerosol is important for estimating its climate and health effects, but simulating atmospheric aerosol size is computationally demanding. This study derives a simple parameterization of the size of organic and secondary inorganic ambient aerosol that can be applied to atmospheric models. Applying this parameterization allows a better representation of the global spatial pattern of aerosol size, as verified by ground and airborne measurements.
Nicole A. June, Anna L. Hodshire, Elizabeth B. Wiggins, Edward L. Winstead, Claire E. Robinson, K. Lee Thornhill, Kevin J. Sanchez, Richard H. Moore, Demetrios Pagonis, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Matthew M. Coggon, Jonathan M. Dean-Day, T. Paul Bui, Jeff Peischl, Robert J. Yokelson, Matthew J. Alvarado, Sonia M. Kreidenweis, Shantanu H. Jathar, and Jeffrey R. Pierce
Atmos. Chem. Phys., 22, 12803–12825, https://doi.org/10.5194/acp-22-12803-2022, https://doi.org/10.5194/acp-22-12803-2022, 2022
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The evolution of organic aerosol composition and size is uncertain due to variability within and between smoke plumes. We examine the impact of plume concentration on smoke evolution from smoke plumes sampled by the NASA DC-8 during FIREX-AQ. We find that observed organic aerosol and size distribution changes are correlated to plume aerosol mass concentrations. Additionally, coagulation explains the majority of the observed growth.
Junri Zhao, Weichun Ma, Kelsey R. Bilsback, Jeffrey R. Pierce, Shengqian Zhou, Ying Chen, Guipeng Yang, and Yan Zhang
Atmos. Chem. Phys., 22, 9583–9600, https://doi.org/10.5194/acp-22-9583-2022, https://doi.org/10.5194/acp-22-9583-2022, 2022
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Marine dimethylsulfide (DMS) emissions play important roles in atmospheric sulfur cycle and climate effects. In this study, DMS emissions were estimated by using the machine learning method and drove the global 3D chemical transport model to simulate their climate effects. To our knowledge, this is the first study in the Asian region that quantifies the combined impacts of DMS on sulfate, particle number concentration, and radiative forcings.
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
Atmos. Chem. Phys., 22, 4491–4508, https://doi.org/10.5194/acp-22-4491-2022, https://doi.org/10.5194/acp-22-4491-2022, 2022
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Characteristics of particle number size distributions and new particle formation in six locations in India were analyzed. New particle formation occurred frequently during the pre-monsoon (spring) season and it significantly modulates the shape of the particle number size distributions. The contribution of newly formed particles to cloud condensation nuclei concentrations was ~3 times higher in urban locations than in mountain background locations.
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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This article predicts concentrations of airborne particulate matter over wintertime Denver, CO, USA, using meteorological and geographic information, as well as low-cost aerosol optical depth (AOD) measurements captured by citizen scientists. Machine learning methods revealed that low boundary layer heights and stagnant air were the best predictors of poor air quality, while AOD provided little skill in predicting particulate matter for this location and time period.
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
Atmos. Meas. Tech., 14, 6023–6038, https://doi.org/10.5194/amt-14-6023-2021, https://doi.org/10.5194/amt-14-6023-2021, 2021
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Fine particulate matter air pollution is one of the leading contributors to adverse health outcomes on the planet. Here, we describe the design and validation of a low-cost, compact, and autonomous instrument capable of measuring particulate matter levels directly, via mass sampling, and optically, via mass and sunlight extinction measurements. We demonstrate the instrument's accuracy relative to reference measurements and its potential for community-level sampling.
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
Atmos. Chem. Phys., 21, 6839–6855, https://doi.org/10.5194/acp-21-6839-2021, https://doi.org/10.5194/acp-21-6839-2021, 2021
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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.
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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North Atlantic Aerosols and Marine Ecosystems Study measurements combined with GEOS-Chem-TOMAS modeling suggest that several not-well-understood key factors control northwest Atlantic aerosol number and size. These synergetic and climate-relevant factors include particle formation near and above the marine boundary layer top, particle growth by marine secondary organic aerosol on descent, particle formation/growth related to dimethyl sulfide, sea spray aerosol, and ship emissions.
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.
Chantelle R. Lonsdale, Matthew J. Alvarado, Anna L. Hodshire, Emily Ramnarine, and Jeffrey R. Pierce
Geosci. Model Dev., 13, 4579–4593, https://doi.org/10.5194/gmd-13-4579-2020, https://doi.org/10.5194/gmd-13-4579-2020, 2020
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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.
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.
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.
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.
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.
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.
Yunha Lee, Drew T. Shindell, Greg Faluvegi, and Rob W. Pinder
Atmos. Chem. Phys., 16, 5323–5342, https://doi.org/10.5194/acp-16-5323-2016, https://doi.org/10.5194/acp-16-5323-2016, 2016
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We studied the impact of US air quality (AQ) regulations and hypothetical CO2 reduction policy on public health and climate change. We find that AQ regulations are projected to have strong health benefits in the near future but result in a positive radiative forcing (RF), ~ 0.8 W m−2, over the USA. Under the US CO2 policy we find air quality co-benefits. However, despite CO2 reductions, it leads to overall positive RF (+0.22 W m−2 in 2055) over the USA mainly by lowering SO2 via less coal usage.
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.
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.
Y. H. Lee, P. J. Adams, and D. T. Shindell
Geosci. Model Dev., 8, 631–667, https://doi.org/10.5194/gmd-8-631-2015, https://doi.org/10.5194/gmd-8-631-2015, 2015
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We have implemented the TwO-Moment Aerosol Sectional (TOMAS) microphysics model in NASA GISS ModelE2, called “ModelE2-TOMAS”. We compared global budgets of ModelE2-TOMAS to other global aerosol models and evaluated the model with various observations such as aerosol precursor gas, aerosol mass, number concentrations, and aerosol optical depth. We found that ModelE2-TOMAS agrees with observations reasonably and that its predictions are within the range of other global aerosol model predictions.
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.
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.
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014, https://doi.org/10.5194/acp-14-10845-2014, 2014
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
S. H. Jathar, N. M. Donahue, P. J. Adams, and A. L. Robinson
Atmos. Chem. Phys., 14, 5771–5780, https://doi.org/10.5194/acp-14-5771-2014, https://doi.org/10.5194/acp-14-5771-2014, 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
G. W. Mann, K. S. Carslaw, C. L. Reddington, K. J. Pringle, M. Schulz, A. Asmi, D. V. Spracklen, D. A. Ridley, M. T. Woodhouse, L. A. Lee, K. Zhang, S. J. Ghan, R. C. Easter, X. Liu, P. Stier, Y. H. Lee, P. J. Adams, H. Tost, J. Lelieveld, S. E. Bauer, K. Tsigaridis, T. P. C. van Noije, A. Strunk, E. Vignati, N. Bellouin, M. Dalvi, C. E. Johnson, T. Bergman, H. Kokkola, K. von Salzen, F. Yu, G. Luo, A. Petzold, J. Heintzenberg, A. Clarke, J. A. Ogren, J. Gras, U. Baltensperger, U. Kaminski, S. G. Jennings, C. D. O'Dowd, R. M. Harrison, D. C. S. Beddows, M. Kulmala, Y. Viisanen, V. Ulevicius, N. Mihalopoulos, V. Zdimal, M. Fiebig, H.-C. Hansson, E. Swietlicki, and J. S. Henzing
Atmos. Chem. Phys., 14, 4679–4713, https://doi.org/10.5194/acp-14-4679-2014, https://doi.org/10.5194/acp-14-4679-2014, 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
W. Trivitayanurak and P. J. Adams
Atmos. Chem. Phys., 14, 995–1010, https://doi.org/10.5194/acp-14-995-2014, https://doi.org/10.5194/acp-14-995-2014, 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
J.-F. Lamarque, F. Dentener, J. McConnell, C.-U. Ro, M. Shaw, R. Vet, D. Bergmann, P. Cameron-Smith, S. Dalsoren, R. Doherty, G. Faluvegi, S. J. Ghan, B. Josse, Y. H. Lee, I. A. MacKenzie, D. Plummer, D. T. Shindell, R. B. Skeie, D. S. Stevenson, S. Strode, G. Zeng, M. Curran, D. Dahl-Jensen, S. Das, D. Fritzsche, and M. Nolan
Atmos. Chem. Phys., 13, 7997–8018, https://doi.org/10.5194/acp-13-7997-2013, https://doi.org/10.5194/acp-13-7997-2013, 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
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
V. Naik, A. Voulgarakis, A. M. Fiore, L. W. Horowitz, J.-F. Lamarque, M. Lin, M. J. Prather, P. J. Young, D. Bergmann, P. J. Cameron-Smith, I. Cionni, W. J. Collins, S. B. Dalsøren, R. Doherty, V. Eyring, G. Faluvegi, G. A. Folberth, B. Josse, Y. H. Lee, I. A. MacKenzie, T. Nagashima, T. P. C. van Noije, D. A. Plummer, M. Righi, S. T. Rumbold, R. Skeie, D. T. Shindell, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, and G. Zeng
Atmos. Chem. Phys., 13, 5277–5298, https://doi.org/10.5194/acp-13-5277-2013, https://doi.org/10.5194/acp-13-5277-2013, 2013
K. W. Bowman, D. T. Shindell, H. M. Worden, J.F. Lamarque, P. J. Young, D. S. Stevenson, Z. Qu, M. de la Torre, D. Bergmann, P. J. Cameron-Smith, W. J. Collins, R. Doherty, S. B. Dalsøren, G. Faluvegi, G. Folberth, L. W. Horowitz, B. M. Josse, Y. H. Lee, I. A. MacKenzie, G. Myhre, T. Nagashima, V. Naik, D. A. Plummer, S. T. Rumbold, R. B. Skeie, S. A. Strode, K. Sudo, S. Szopa, A. Voulgarakis, G. Zeng, S. S. Kulawik, A. M. Aghedo, and J. R. Worden
Atmos. Chem. Phys., 13, 4057–4072, https://doi.org/10.5194/acp-13-4057-2013, https://doi.org/10.5194/acp-13-4057-2013, 2013
D. S. Stevenson, P. J. Young, V. Naik, J.-F. Lamarque, D. T. Shindell, A. Voulgarakis, R. B. Skeie, S. B. Dalsoren, G. Myhre, T. K. Berntsen, G. A. Folberth, S. T. Rumbold, W. J. Collins, I. A. MacKenzie, R. M. Doherty, G. Zeng, T. P. C. van Noije, A. Strunk, D. Bergmann, P. Cameron-Smith, D. A. Plummer, S. A. Strode, L. Horowitz, Y. H. Lee, S. Szopa, K. Sudo, T. Nagashima, B. Josse, I. Cionni, M. Righi, V. Eyring, A. Conley, K. W. Bowman, O. Wild, and A. Archibald
Atmos. Chem. Phys., 13, 3063–3085, https://doi.org/10.5194/acp-13-3063-2013, https://doi.org/10.5194/acp-13-3063-2013, 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
P. J. Young, A. T. Archibald, K. W. Bowman, J.-F. Lamarque, V. Naik, D. S. Stevenson, S. Tilmes, A. Voulgarakis, O. Wild, D. Bergmann, P. Cameron-Smith, I. Cionni, W. J. Collins, S. B. Dalsøren, R. M. Doherty, V. Eyring, G. Faluvegi, L. W. Horowitz, B. Josse, Y. H. Lee, I. A. MacKenzie, T. Nagashima, D. A. Plummer, M. Righi, S. T. Rumbold, R. B. Skeie, D. T. Shindell, S. A. Strode, K. Sudo, S. Szopa, and G. Zeng
Atmos. Chem. Phys., 13, 2063–2090, https://doi.org/10.5194/acp-13-2063-2013, https://doi.org/10.5194/acp-13-2063-2013, 2013
J.-F. Lamarque, D. T. Shindell, B. Josse, P. J. Young, I. Cionni, V. Eyring, D. Bergmann, P. Cameron-Smith, W. J. Collins, R. Doherty, S. Dalsoren, G. Faluvegi, G. Folberth, S. J. Ghan, L. W. Horowitz, Y. H. Lee, I. A. MacKenzie, T. Nagashima, V. Naik, D. Plummer, M. Righi, S. T. Rumbold, M. Schulz, R. B. Skeie, D. S. Stevenson, S. Strode, K. Sudo, S. Szopa, A. Voulgarakis, and G. Zeng
Geosci. Model Dev., 6, 179–206, https://doi.org/10.5194/gmd-6-179-2013, https://doi.org/10.5194/gmd-6-179-2013, 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
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
The ddeq Python library for point source quantification from remote sensing images (Version 1.0)
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
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Application of regional meteorology and air quality models based on MIPS CPU Platform
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
How the meteorological spectral nudging impacts on aerosol radiation clouds interactions?
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Nathan Patrick Arnold
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-245, https://doi.org/10.5194/gmd-2023-245, 2024
Revised manuscript accepted for GMD
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Earth System Models often represent the land surface at smaller scales than the atmosphere, but surface-atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter Notebooks included in the library.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure facilitating further processing to allow emission processing from continental to street scale.
Najmeh Kaffashzadeh and Abbas Ali Aliakbari Bidokhti
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-226, https://doi.org/10.5194/gmd-2023-226, 2024
Revised manuscript accepted for GMD
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Reanalysis data have been widely used as an initial condition for the daily forecast of the atmosphere or boundary conditions in regional models, for the study of climate change, and as proxies to complement insufficient in situ measurements. This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2023-2962, https://doi.org/10.5194/egusphere-2023-2962, 2024
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There are relatively limited researches on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPU, have distinct advantages in energy efficiency and scalability. In this study, the air quality modeling system can run stably on MIPS CPU platform, and the experiment results verify the stability of scientific computing on the platform. The work provides a technical foundation for the scientific application based on MIPS CPU platforms.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-209, https://doi.org/10.5194/gmd-2023-209, 2023
Revised manuscript accepted for GMD
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This study is about the modelling of the atmospheric composition in Europe and during the summer 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impact of two modelling processes able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Cited articles
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Anttila, T., Kerminen, V. M., and Lehtinen, K. E. J.: Parameterizing the formation rate of new particles: The effect of nuclei self-coagulation, J. Aerosol. Sci., 41, 621–636, https://doi.org/10.1016/j.jaerosci.2010.04.008, 2010.
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Jung, J. G., Pandis, S. N., and Adams, P. J.: Evaluation of nucleation theories in a sulfur-rich environment, Aerosol Sci. Technol., 42, 495–504, https://doi.org/10.1080/02786820802187085, 2008.
Kerminen, V. M., Anttila, T., Lehtinen, K. E. J., and Kulmala, M.: Parameterization for atmospheric new-particle formation: Application to a system involving sulfuric acid and condensable water-soluble organic vapors, Aerosol Sci. Technol., 38, 1001–1008, 2004a.
Kerminen, V. M., Lehtinen, K. E. J., Anttila, T., and Kulmala, M.: Dynamics of atmospheric nucleation mode particles: a timescale analysis, Tellus Ser. B, 56, 135–146, https://doi.org/10.1111/j.1600-0889.2004.00095.x, 2004b.
Kristjánsson, J. E., Stjern, C. W., Stordal, F., Fjæraa, A. M., Myhre, G., and Jónasson, K.: Cosmic rays, cloud condensation nuclei and clouds – a reassessment using MODIS data, Atmos. Chem. Phys., 8, 7373–7387, https://doi.org/10.5194/acp-8-7373-2008, 2008.
Kulmala, M., Vehkamaki, H., Petaja, T., Dal Maso, M., Lauri, A., Kerminen, V. M., Birmili, W., and McMurry, P. H.: Formation and growth rates of ultrafine atmospheric particles: a review of observations, J. Aerosol. Sci., 35, 143–176, 2004.
Lee, Y. H. and Adams, P. J.: Evaluation of aerosol distributions in the GISS-TOMAS global aerosol microphysics model with remote sensing observations, Atmos. Chem. Phys., 10, 2129–2144, https://doi.org/10.5194/acp-10-2129-2010, 2010.
Lee, Y. H. and Adams, P. J.: A Fast and Efficient Version of the TwO-Moment Aerosol Sectional (TOMAS) Global Aerosol Microphysics Model, Aerosol Sci. Technol., 46, 678–689, https://doi.org/10.1080/02786826.2011.643259, 2012.
Lee, Y. H., Chen, K., and Adams, P. J.: Development of a global model of mineral dust aerosol microphysics, Atmos. Chem. Phys., 9, 2441–2458, https://doi.org/10.5194/acp-9-2441-2009, 2009.
Lehtinen, K. E. J., Dal Maso, M., Kulmala, M., and Kerminen, V. M.: Estimating nucleation rates from apparent particle formation rates and vice versa: Revised formulation of the Kerminen-Kulmala equation, J. Aerosol. Sci., 38, 988–994, https://doi.org/10.1016/j.jaerosci.2007.06.009, 2007.
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Napari, I., Noppel, M., Vehkamaki, H., and Kulmala, M.: Parametrization of ternary nucleation rates for H2SO4-NH3-H2O vapors, J. Geophys. Res.-Atmos., 107, 4381, https://doi.org/10.1029/2002JD002132, 2002.
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Pierce, J. R. and Adams, P. J.: A Computationally Efficient Aerosol Nucleation/Condensation Method: Pseudo-Steady-State Sulfuric Acid, Aerosol Sci. Technol., 43, 216–226, 2009a.
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