Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2569-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-2569-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
03 Jun 2020
Development and technical paper |
| 03 Jun 2020
Development of a reduced-complexity plant canopy physics surrogate model for use in chemical transport models: a case study with GEOS-Chem v12.3.0
Department of Civil and Environmental Engineering, Massachusetts
Institute of Technology, Cambridge, MA, USA
now at: Pacific Northwest National Laboratory, Richland, WA, USA
Department of Civil and Environmental Engineering, Massachusetts
Institute of Technology, Cambridge, MA, USA
Alex B. Guenther
Department of Earth System Science, University of California Irvine,
Irvine, CA, USA
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This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
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Dry deposition is an important, but highly uncertain, sink for surface ozone. Several popular parameterizations exist to model this process, which vary with respect to how they depend on land cover and environmental variables. Here, we predict ozone dry deposition globally over 30 years, comparing four different approaches. We find that the choice of dry deposition parameterization affects the distribution, seasonal means, long-term trends, and interannual variability of surface ozone.
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Atmos. Chem. Phys., 16, 10621–10635, https://doi.org/10.5194/acp-16-10621-2016, https://doi.org/10.5194/acp-16-10621-2016, 2016
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Therese S. Carter, Colette L. Heald, Jesse H. Kroll, Eric C. Apel, Donald Blake, Matthew Coggon, Achim Edtbauer, Georgios Gkatzelis, Rebecca S. Hornbrook, Jeff Peischl, Eva Y. Pfannerstill, Felix Piel, Nina G. Reijrink, Akima Ringsdorf, Carsten Warneke, Jonathan Williams, Armin Wisthaler, and Lu Xu
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Deanna C. Myers, Saewung Kim, Steven Sjostedt, Alex B. Guenther, Roger Seco, Oscar Vega Bustillos, Julio Tota, Rodrigo A. F. Souza, and James N. Smith
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Ka Ming Fung, Colette L. Heald, Jesse H. Kroll, Siyuan Wang, Duseong S. Jo, Andrew Gettelman, Zheng Lu, Xiaohong Liu, Rahul A. Zaveri, Eric C. Apel, Donald R. Blake, Jose-Luis Jimenez, Pedro Campuzano-Jost, Patrick R. Veres, Timothy S. Bates, John E. Shilling, and Maria Zawadowicz
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Understanding the natural aerosol burden in the preindustrial era is crucial for us to assess how atmospheric aerosols affect the Earth's radiative budgets. Our study explores how a detailed description of dimethyl sulfide (DMS) oxidation (implemented in the Community Atmospheric Model version 6 with chemistry, CAM6-chem) could help us better estimate the present-day and preindustrial concentrations of sulfate and other relevant chemicals, as well as the resulting aerosol radiative impacts.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697, https://doi.org/10.5194/acp-21-15663-2021, https://doi.org/10.5194/acp-21-15663-2021, 2021
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This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Chinmoy Sarkar, Gracie Wong, Anne Mielnik, Sanjeevi Nagalingam, Nicole Jenna Gross, Alex B. Guenther, Taehyoung Lee, Taehyun Park, Jihee Ban, Seokwon Kang, Jin-Soo Park, Joonyoung Ahn, Danbi Kim, Hyunjae Kim, Jinsoo Choi, Beom-Keun Seo, Jong-Ho Kim, Jeong-Ho Kim, Soo Bog Park, and Saewung Kim
Atmos. Chem. Phys., 21, 11505–11518, https://doi.org/10.5194/acp-21-11505-2021, https://doi.org/10.5194/acp-21-11505-2021, 2021
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We present experimental proofs illustrating the emission of an unexplored volatile organic compound, tentatively assigned as ketene, in an industrial facility in South Korea. The emission of such a compound has rarely been reported, but our experimental data show that the emission rate is substantial. It potentially has tremendous implications for regional air quality and public health, as it is highly reactive and toxic at the same time.
Beata Opacka, Jean-François Müller, Trissevgeni Stavrakou, Maite Bauwens, Katerina Sindelarova, Jana Markova, and Alex B. Guenther
Atmos. Chem. Phys., 21, 8413–8436, https://doi.org/10.5194/acp-21-8413-2021, https://doi.org/10.5194/acp-21-8413-2021, 2021
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Isoprene is mainly emitted from plants, and about 80 % of its global emissions occur in the tropics. Current isoprene inventories are usually based on modelled vegetation maps, but high pressure on land use over the last decades has led to severe losses, especially in tropical forests, that are not considered by models. We provide a study on the present-day impact of spaceborne land cover changes on isoprene emissions and the first inventory based on high-resolution Landsat tree cover dataset.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev., 14, 3067–3077, https://doi.org/10.5194/gmd-14-3067-2021, https://doi.org/10.5194/gmd-14-3067-2021, 2021
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
Dianne Sanchez, Roger Seco, Dasa Gu, Alex Guenther, John Mak, Youngjae Lee, Danbi Kim, Joonyoung Ahn, Don Blake, Scott Herndon, Daun Jeong, John T. Sullivan, Thomas Mcgee, Rokjin Park, and Saewung Kim
Atmos. Chem. Phys., 21, 6331–6345, https://doi.org/10.5194/acp-21-6331-2021, https://doi.org/10.5194/acp-21-6331-2021, 2021
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We present observations of total reactive gases in a suburban forest observatory in the Seoul metropolitan area. The quantitative comparison with speciated trace gas observations illustrated significant underestimation in atmospheric reactivity from the speciated trace gas observational dataset. We present scientific discussion about potential causes.
Hui Wang, Qizhong Wu, Alex B. Guenther, Xiaochun Yang, Lanning Wang, Tang Xiao, Jie Li, Jinming Feng, Qi Xu, and Huaqiong Cheng
Atmos. Chem. Phys., 21, 4825–4848, https://doi.org/10.5194/acp-21-4825-2021, https://doi.org/10.5194/acp-21-4825-2021, 2021
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We assessed the influence of the greening trend on BVOC emission in China. The comparison among different scenarios showed that vegetation changes resulting from land cover management are the main driver of BVOC emission change in China. Climate variability contributed significantly to interannual variations but not much to the long-term trend during the study period.
Ruud H. H. Janssen, Colette L. Heald, Allison L. Steiner, Anne E. Perring, J. Alex Huffman, Ellis S. Robinson, Cynthia H. Twohy, and Luke D. Ziemba
Atmos. Chem. Phys., 21, 4381–4401, https://doi.org/10.5194/acp-21-4381-2021, https://doi.org/10.5194/acp-21-4381-2021, 2021
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Bioaerosols are ubiquitous in the atmosphere and have the potential to affect cloud formation, as well as human and ecosystem health. However, their emissions are not well quantified, which hinders the assessment of their role in atmospheric processes. Here, we develop two new emission schemes for fungal spores based on multi-annual datasets of spore counts. We find that our modeled global emissions and burden are an order of magnitude lower than previous estimates.
Chen Dayan, Erick Fredj, Pawel K. Misztal, Maor Gabay, Alex B. Guenther, and Eran Tas
Atmos. Chem. Phys., 20, 12741–12759, https://doi.org/10.5194/acp-20-12741-2020, https://doi.org/10.5194/acp-20-12741-2020, 2020
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We studied the emission of biogenic volatile organic compounds from both marine and terrestrial ecosystems in the Eastern Mediterranean Basin, a global warming hot spot. We focused on isoprene and dimethyl sulfide (DMS), which are well recognized for their effect on climate and strong impact on photochemical pollution by the former. We found high emissions of isoprene and a strong decadal decrease in the emission of DMS which can both be attributed to the strong increase in seawater temperature.
Archit Mehra, Jordan E. Krechmer, Andrew Lambe, Chinmoy Sarkar, Leah Williams, Farzaneh Khalaj, Alex Guenther, John Jayne, Hugh Coe, Douglas Worsnop, Celia Faiola, and Manjula Canagaratna
Atmos. Chem. Phys., 20, 10953–10965, https://doi.org/10.5194/acp-20-10953-2020, https://doi.org/10.5194/acp-20-10953-2020, 2020
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Emissions of volatile organic compounds (VOCs) from plants are important for tropospheric ozone and secondary organic aerosol (SOA) formation. Real plant emissions are much more diverse than the few proxies widely used for studies of plant SOA. Here we present the first study of SOA from Californian sage plants and the oxygenated monoterpenes representing their major emissions. We identify SOA products and show the importance of the formation of highly oxygenated organic molecules and oligomers.
Katherine R. Travis, Colette L. Heald, Hannah M. Allen, Eric C. Apel, Stephen R. Arnold, Donald R. Blake, William H. Brune, Xin Chen, Róisín Commane, John D. Crounse, Bruce C. Daube, Glenn S. Diskin, James W. Elkins, Mathew J. Evans, Samuel R. Hall, Eric J. Hintsa, Rebecca S. Hornbrook, Prasad S. Kasibhatla, Michelle J. Kim, Gan Luo, Kathryn McKain, Dylan B. Millet, Fred L. Moore, Jeffrey Peischl, Thomas B. Ryerson, Tomás Sherwen, Alexander B. Thames, Kirk Ullmann, Xuan Wang, Paul O. Wennberg, Glenn M. Wolfe, and Fangqun Yu
Atmos. Chem. Phys., 20, 7753–7781, https://doi.org/10.5194/acp-20-7753-2020, https://doi.org/10.5194/acp-20-7753-2020, 2020
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Atmospheric models overestimate the rate of removal of trace gases by the hydroxyl radical (OH). This is a concern for studies of the climate and air quality impacts of human activities. Here, we evaluate the performance of a commonly used model of atmospheric chemistry against data from the NASA Atmospheric Tomography Mission (ATom) over the remote oceans where models have received little validation. The model is generally successful, suggesting that biases in OH may be a concern over land.
Chinmoy Sarkar, Alex B. Guenther, Jeong-Hoo Park, Roger Seco, Eliane Alves, Sarah Batalha, Raoni Santana, Saewung Kim, James Smith, Julio Tóta, and Oscar Vega
Atmos. Chem. Phys., 20, 7179–7191, https://doi.org/10.5194/acp-20-7179-2020, https://doi.org/10.5194/acp-20-7179-2020, 2020
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Biogenic volatile organic compounds (BVOCs) are important components of the atmosphere due to their contribution to atmospheric chemistry and biogeochemical cycles. In this study, we report major BVOCs, e.g. isoprene and total monoterpene flux measurements with a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) using the eddy covariance (EC) method at a primary rainforest in eastern Amazonia. We used the measured data to evaluate the MEGAN2.1 model for the emission site.
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.
Therese S. Carter, Colette L. Heald, Jose L. Jimenez, Pedro Campuzano-Jost, Yutaka Kondo, Nobuhiro Moteki, Joshua P. Schwarz, Christine Wiedinmyer, Anton S. Darmenov, Arlindo M. da Silva, and Johannes W. Kaiser
Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, https://doi.org/10.5194/acp-20-2073-2020, 2020
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Fires and the smoke they emit impact air quality, health, and climate, but the abundance and properties of smoke remain uncertain and poorly constrained. To explore this, we compare model simulations driven by four commonly-used fire emission inventories with surface, aloft, and satellite observations. We show that across inventories smoke emissions differ by factors of 4 to 7 over North America, challenging our ability to accurately characterize the impact of smoke on air quality and climate.
Anthony Y. H. Wong, Jeffrey A. Geddes, Amos P. K. Tai, and Sam J. Silva
Atmos. Chem. Phys., 19, 14365–14385, https://doi.org/10.5194/acp-19-14365-2019, https://doi.org/10.5194/acp-19-14365-2019, 2019
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Dry deposition is an important, but highly uncertain, sink for surface ozone. Several popular parameterizations exist to model this process, which vary with respect to how they depend on land cover and environmental variables. Here, we predict ozone dry deposition globally over 30 years, comparing four different approaches. We find that the choice of dry deposition parameterization affects the distribution, seasonal means, long-term trends, and interannual variability of surface ozone.
Maria A. Zawadowicz, Karl D. Froyd, Anne E. Perring, Daniel M. Murphy, Dominick V. Spracklen, Colette L. Heald, Peter R. Buseck, and Daniel J. Cziczo
Atmos. Chem. Phys., 19, 13859–13870, https://doi.org/10.5194/acp-19-13859-2019, https://doi.org/10.5194/acp-19-13859-2019, 2019
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We report measurements of small particles of biological origin (for example, fragments of bacteria, pollen, or fungal spores) in the atmosphere over the continental United States. We use a recently developed identification technique based on airborne mass spectrometry in conjunction with an extensive aircraft dataset. We show that biological particles are present at altitudes up to 10 km and we quantify typical concentrations.
William C. Porter and Colette L. Heald
Atmos. Chem. Phys., 19, 13367–13381, https://doi.org/10.5194/acp-19-13367-2019, https://doi.org/10.5194/acp-19-13367-2019, 2019
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In this paper we explore the connection between changes in surface temperature and changes in ozone pollution. While explanations for this connection have been proposed in the past, we attempt to better quantify them using models and statistics. We find that some of the most commonly cited mechanisms, including biogenic emissions and temperature-dependent chemical processes, can explain less than half of the O3–T correlation. Meteorology is identified as the most likely driver for the remainder.
Daun Jeong, Roger Seco, Dasa Gu, Youngro Lee, Benjamin A. Nault, Christoph J. Knote, Tom Mcgee, John T. Sullivan, Jose L. Jimenez, Pedro Campuzano-Jost, Donald R. Blake, Dianne Sanchez, Alex B. Guenther, David Tanner, L. Gregory Huey, Russell Long, Bruce E. Anderson, Samuel R. Hall, Kirk Ullmann, Hye-jung Shin, Scott C. Herndon, Youngjae Lee, Danbi Kim, Joonyoung Ahn, and Saewung Kim
Atmos. Chem. Phys., 19, 12779–12795, https://doi.org/10.5194/acp-19-12779-2019, https://doi.org/10.5194/acp-19-12779-2019, 2019
Emma L. D'Ambro, Siegfried Schobesberger, Cassandra J. Gaston, Felipe D. Lopez-Hilfiker, Ben H. Lee, Jiumeng Liu, Alla Zelenyuk, David Bell, Christopher D. Cappa, Taylor Helgestad, Ziyue Li, Alex Guenther, Jian Wang, Matthew Wise, Ryan Caylor, Jason D. Surratt, Theran Riedel, Noora Hyttinen, Vili-Taneli Salo, Galib Hasan, Theo Kurtén, John E. Shilling, and Joel A. Thornton
Atmos. Chem. Phys., 19, 11253–11265, https://doi.org/10.5194/acp-19-11253-2019, https://doi.org/10.5194/acp-19-11253-2019, 2019
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Isoprene is the most abundantly emitted reactive organic gas globally, and thus it is important to understand its fate and role in aerosol formation and growth. A major product of its oxidation is an epoxydiol, IEPOX, which can be efficiently taken up by acidic aerosol to generate substantial amounts of secondary organic aerosol (SOA). We present chamber experiments exploring the properties of IEPOX SOA and reconcile discrepancies between field, laboratory, and model studies of this process.
Karena A. McKinney, Daniel Wang, Jianhuai Ye, Jean-Baptiste de Fouchier, Patricia C. Guimarães, Carla E. Batista, Rodrigo A. F. Souza, Eliane G. Alves, Dasa Gu, Alex B. Guenther, and Scot T. Martin
Atmos. Meas. Tech., 12, 3123–3135, https://doi.org/10.5194/amt-12-3123-2019, https://doi.org/10.5194/amt-12-3123-2019, 2019
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Volatile organic compound (VOC) emissions influence air quality and particulate distributions, particularly in major source regions such as the Amazon. A sampler for collecting VOCs from an unmanned aerial vehicle (UAV) is described. Field tests of its performance and an initial example data set collected in the Amazon are also presented. The low cost, ease of use, and maneuverability of UAVs give this method the potential to significantly advance knowledge of the spatial distribution of VOCs.
Moshe Shechner, Alex Guenther, Robert Rhew, Asher Wishkerman, Qian Li, Donald Blake, Gil Lerner, and Eran Tas
Atmos. Chem. Phys., 19, 7667–7690, https://doi.org/10.5194/acp-19-7667-2019, https://doi.org/10.5194/acp-19-7667-2019, 2019
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Along with other recent studies, our findings point to strong emission of a suite of volatile halogenated organic compounds (VHOCs) from saline soils and salt lakes. Some emitted VHOCs were not known to be emitted from terrestrial sources, and our observations point to apparent new common controls for the emission of several VHOCs. These findings are an important milestone toward a more complete understanding of the effect of VHOCs on atmospheric ozone concentrations and oxidation capacity.
Shan S. Zhou, Amos P. K. Tai, Shihan Sun, Mehliyar Sadiq, Colette L. Heald, and Jeffrey A. Geddes
Atmos. Chem. Phys., 18, 14133–14148, https://doi.org/10.5194/acp-18-14133-2018, https://doi.org/10.5194/acp-18-14133-2018, 2018
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Surface ozone pollution harms vegetation. As plants play key roles shaping air quality, the plant damage may further worsen air pollution. We use various computer models to examine such feedback effects, and find that ozone-induced decline in leaf density can lead to much higher ozone levels in forested regions, mostly due to the reduced ability of leaves to absorb pollutants. This study highlights the importance of considering the two-way interactions between plants and air pollution.
Harri Kokkola, Thomas Kühn, Anton Laakso, Tommi Bergman, Kari E. J. Lehtinen, Tero Mielonen, Antti Arola, Scarlet Stadtler, Hannele Korhonen, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Ina Tegen, Colombe Siegenthaler-Le Drian, Martin G. Schultz, Isabelle Bey, Philip Stier, Nikos Daskalakis, Colette L. Heald, and Sami Romakkaniemi
Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, https://doi.org/10.5194/gmd-11-3833-2018, 2018
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In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.
Fernando Santos, Karla Longo, Alex Guenther, Saewung Kim, Dasa Gu, Dave Oram, Grant Forster, James Lee, James Hopkins, Joel Brito, and Saulo Freitas
Atmos. Chem. Phys., 18, 12715–12734, https://doi.org/10.5194/acp-18-12715-2018, https://doi.org/10.5194/acp-18-12715-2018, 2018
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We investigated the impact of biomass burning on the chemical composition of trace gases in the Amazon. The findings corroborate the influence of biomass burning activity not only on direct emissions of particulate matter but also on the oxidative capacity to produce secondary organic aerosol. The scientists plan to use this information to improve the numerical model simulation with a better representativeness of the chemical processes, which can impact on global climate prediction.
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.
Luke D. Schiferl, Colette L. Heald, and David Kelly
Biogeosciences, 15, 4301–4315, https://doi.org/10.5194/bg-15-4301-2018, https://doi.org/10.5194/bg-15-4301-2018, 2018
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To understand future food security, it is critical to develop realistic crop models with reliable sensitivity to environmental factors. We find that particulate matter (PM) causes a significant, but smaller, enhancement for global wheat and rice production than estimated without nutrient and physiological limitations imposed by a crop model. In contrast, maize grows near its physiological maximum, with little enhancement from PM. Nitrogen deposition leads to a small increase in crop production.
Eliane G. Alves, Julio Tóta, Andrew Turnipseed, Alex B. Guenther, José Oscar W. Vega Bustillos, Raoni A. Santana, Glauber G. Cirino, Julia V. Tavares, Aline P. Lopes, Bruce W. Nelson, Rodrigo A. de Souza, Dasa Gu, Trissevgeni Stavrakou, David K. Adams, Jin Wu, Scott Saleska, and Antonio O. Manzi
Biogeosciences, 15, 4019–4032, https://doi.org/10.5194/bg-15-4019-2018, https://doi.org/10.5194/bg-15-4019-2018, 2018
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This study shows that leaf quantity and leaf age have an important effect on seasonal changes in isoprene emissions and that these could play an even more important role in regulating ecosystem isoprene fluxes than light and temperature at seasonal timescales in tropical forests. These results bring novelty and new insight for future research because in the past leaf phenology was not considered as an important factor that controls biological processes in the tropics.
Chunxiang Ye, Xianliang Zhou, Dennis Pu, Jochen Stutz, James Festa, Max Spolaor, Catalina Tsai, Christopher Cantrell, Roy L. Mauldin III, Andrew Weinheimer, Rebecca S. Hornbrook, Eric C. Apel, Alex Guenther, Lisa Kaser, Bin Yuan, Thomas Karl, Julie Haggerty, Samuel Hall, Kirk Ullmann, James Smith, and John Ortega
Atmos. Chem. Phys., 18, 9107–9120, https://doi.org/10.5194/acp-18-9107-2018, https://doi.org/10.5194/acp-18-9107-2018, 2018
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Substantial levels of HONO existed during the day throughout the troposphere over the southeastern US during NOMADSS 2013. Particulate nitrate photolysis appeared to be the major volume HONO source, while NOx was an important HONO precursor only in industrial and urban plumes. HONO was not a significant OH radical precursor in the rural troposphere away from the ground surface; however, its production from particulate nitrate photolysis was an important renoxification pathway.
Maite Bauwens, Trissevgeni Stavrakou, Jean-François Müller, Bert Van Schaeybroeck, Lesley De Cruz, Rozemien De Troch, Olivier Giot, Rafiq Hamdi, Piet Termonia, Quentin Laffineur, Crist Amelynck, Niels Schoon, Bernard Heinesch, Thomas Holst, Almut Arneth, Reinhart Ceulemans, Arturo Sanchez-Lorenzo, and Alex Guenther
Biogeosciences, 15, 3673–3690, https://doi.org/10.5194/bg-15-3673-2018, https://doi.org/10.5194/bg-15-3673-2018, 2018
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Biogenic isoprene fluxes are simulated over Europe with the MEGAN–MOHYCAN model for the recent past and end-of-century climate at high spatiotemporal resolution (0.1°, 3 min). Due to climate change, fluxes increased by 40 % over 1979–2014. Climate scenarios for 2070–2099 suggest an increase by 83 % due to climate, and an even stronger increase when the potential impact of CO2 fertilization is considered (up to 141 %). Accounting for CO2 inhibition cancels out a large part of these increases.
Nan Li, Qingyang He, Jim Greenberg, Alex Guenther, Jingyi Li, Junji Cao, Jun Wang, Hong Liao, Qiyuan Wang, and Qiang Zhang
Atmos. Chem. Phys., 18, 7489–7507, https://doi.org/10.5194/acp-18-7489-2018, https://doi.org/10.5194/acp-18-7489-2018, 2018
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O3 pollution has been increasing in most Chinese cities in recent years. Our study reveals that the synergistic impact of individual source contributions to O3 formation should be considered in the formation of air pollution control strategies, especially for big cities in the vicinity of forests.
Luke D. Schiferl and Colette L. Heald
Atmos. Chem. Phys., 18, 5953–5966, https://doi.org/10.5194/acp-18-5953-2018, https://doi.org/10.5194/acp-18-5953-2018, 2018
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Global population growth and industrialization have contributed to poor air quality worldwide, and increasing population will put pressure on global food production. We therefore assess how air pollution may impact crop growth. Ozone has previously been shown to damage crops. We demonstrate that the impact of particles associated with enhanced light scattering promotes growth, offsetting much, if not all, ozone damage. This has implications for air quality management and global food security.
Jingqiu Mao, Annmarie Carlton, Ronald C. Cohen, William H. Brune, Steven S. Brown, Glenn M. Wolfe, Jose L. Jimenez, Havala O. T. Pye, Nga Lee Ng, Lu Xu, V. Faye McNeill, Kostas Tsigaridis, Brian C. McDonald, Carsten Warneke, Alex Guenther, Matthew J. Alvarado, Joost de Gouw, Loretta J. Mickley, Eric M. Leibensperger, Rohit Mathur, Christopher G. Nolte, Robert W. Portmann, Nadine Unger, Mika Tosca, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 2615–2651, https://doi.org/10.5194/acp-18-2615-2018, https://doi.org/10.5194/acp-18-2615-2018, 2018
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This paper is aimed at discussing progress in evaluating, diagnosing, and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models.
Xuan Wang, Colette L. Heald, Jiumeng Liu, Rodney J. Weber, Pedro Campuzano-Jost, Jose L. Jimenez, Joshua P. Schwarz, and Anne E. Perring
Atmos. Chem. Phys., 18, 635–653, https://doi.org/10.5194/acp-18-635-2018, https://doi.org/10.5194/acp-18-635-2018, 2018
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Brown carbon (BrC) contributes significantly to uncertainty in estimating the global direct radiative effect (DRE) of aerosols. We develop a global model simulation of BrC and test it against BrC absorption measurements from two aircraft campaigns in the continental United States. We suggest that BrC DRE has been overestimated previously due to the lack of observational constraints from direct measurements and omission of the effects of photochemical whitening.
Brett B. Palm, Suzane S. de Sá, Douglas A. Day, Pedro Campuzano-Jost, Weiwei Hu, Roger Seco, Steven J. Sjostedt, Jeong-Hoo Park, Alex B. Guenther, Saewung Kim, Joel Brito, Florian Wurm, Paulo Artaxo, Ryan Thalman, Jian Wang, Lindsay D. Yee, Rebecca Wernis, Gabriel Isaacman-VanWertz, Allen H. Goldstein, Yingjun Liu, Stephen R. Springston, Rodrigo Souza, Matt K. Newburn, M. Lizabeth Alexander, Scot T. Martin, and Jose L. Jimenez
Atmos. Chem. Phys., 18, 467–493, https://doi.org/10.5194/acp-18-467-2018, https://doi.org/10.5194/acp-18-467-2018, 2018
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Ambient air was oxidized by OH or O3 in an oxidation flow reactor during both wet and dry seasons in the GoAmazon2014/5 campaign to study secondary organic aerosol (SOA) formation. We investigated how much biogenic, urban, and biomass burning sources contributed to the ambient concentrations of SOA precursor gases and how their contributions changed diurnally and seasonally. SOA yields and hygroscopicity of organic aerosol in the oxidation flow reactor were also studied.
David H. Hagan, Gabriel Isaacman-VanWertz, Jonathan P. Franklin, Lisa M. M. Wallace, Benjamin D. Kocar, Colette L. Heald, and Jesse H. Kroll
Atmos. Meas. Tech., 11, 315–328, https://doi.org/10.5194/amt-11-315-2018, https://doi.org/10.5194/amt-11-315-2018, 2018
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The use of low-cost sensors for air pollution research has outpaced our understanding of their capabilities and limitations under real-world conditions. Here we describe the deployment, calibration and evaluation of electrochemical sensors on the Island of Hawai‘i. We obtain excellent performance (RMSE < 7 ppb, r2 = 0.997) across a wide dynamic range (1 ppb–2 ppm). We introduce a hybrid regression algorithm which works across a large dynamic range and shows little decay in sensitivity over time.
Robert C. Rhew, Malte Julian Deventer, Andrew A. Turnipseed, Carsten Warneke, John Ortega, Steve Shen, Luis Martinez, Abigail Koss, Brian M. Lerner, Jessica B. Gilman, James N. Smith, Alex B. Guenther, and Joost A. de Gouw
Atmos. Chem. Phys., 17, 13417–13438, https://doi.org/10.5194/acp-17-13417-2017, https://doi.org/10.5194/acp-17-13417-2017, 2017
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Alkenes emanate from both natural and anthropogenic sources and can contribute to atmospheric ozone production. This study measured
lightalkene (ethene, propene and butene) fluxes from a ponderosa pine forest using a novel relaxed eddy accumulation method, revealing much larger emissions than previously estimated and accounting for a significant fraction of OH reactivity. Emissions have a diurnal cycle related to sunlight and temperature, and the forest canopy appears to be the source.
Min Huang, Gregory R. Carmichael, James H. Crawford, Armin Wisthaler, Xiwu Zhan, Christopher R. Hain, Pius Lee, and Alex B. Guenther
Geosci. Model Dev., 10, 3085–3104, https://doi.org/10.5194/gmd-10-3085-2017, https://doi.org/10.5194/gmd-10-3085-2017, 2017
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Various sensitivity simulations during two airborne campaigns were performed to assess the impact of different initialization methods and model resolutions on NUWRF-modeled weather states, heat fluxes, and the follow-on MEGAN isoprene emission calculations. Proper land initialization is shown to be important to the coupled weather modeling and the follow-on emission modeling, which is also critical to accurately representing other processes in air quality modeling and data assimilation.
Molly B. Smith, Natalie M. Mahowald, Samuel Albani, Aaron Perry, Remi Losno, Zihan Qu, Beatrice Marticorena, David A. Ridley, and Colette L. Heald
Atmos. Chem. Phys., 17, 3253–3278, https://doi.org/10.5194/acp-17-3253-2017, https://doi.org/10.5194/acp-17-3253-2017, 2017
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Using different meteorology reanalyses to drive dust in climate modeling can produce dissimilar global dust distributions, especially in the Southern Hemisphere (SH). It may therefore not be advisable for SH dust studies to base results on simulations driven by one reanalysis. Northern Hemisphere dust varies mostly on seasonal timescales, while SH dust varies on interannual timescales. Dust is an important part of climate modeling, and we hope this contributes to understanding these simulations.
Kerneels Jaars, Pieter G. van Zyl, Johan P. Beukes, Heidi Hellén, Ville Vakkari, Micky Josipovic, Andrew D. Venter, Matti Räsänen, Leandra Knoetze, Dirk P. Cilliers, Stefan J. Siebert, Markku Kulmala, Janne Rinne, Alex Guenther, Lauri Laakso, and Hannele Hakola
Atmos. Chem. Phys., 16, 15665–15688, https://doi.org/10.5194/acp-16-15665-2016, https://doi.org/10.5194/acp-16-15665-2016, 2016
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Biogenic volatile organic compounds (BVOCs) – important in tropospheric ozone and secondary organic aerosol formation – were measured at a savannah grassland in South Africa. Results presented are the most extensive for this type of landscape. Compared to other parts of the world, monoterpene levels were similar, while very low isoprene levels led to significantly lower total BVOC levels. BVOC levels were an order of magnitude lower compared to anthropogenic VOC levels measured at Welgegund.
David A. Ridley, Colette L. Heald, Jasper F. Kok, and Chun Zhao
Atmos. Chem. Phys., 16, 15097–15117, https://doi.org/10.5194/acp-16-15097-2016, https://doi.org/10.5194/acp-16-15097-2016, 2016
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Mineral dust aerosol affects climate through interaction with radiation and clouds, human health through contribution to particulate matter, and ecosystem health through nutrient transport and deposition. In this study, we use satellite and in situ retrievals to derive an observational estimate of the global dust AOD with which evaluate modeled dust AOD. Differences in the seasonality and regional distribution of dust AOD between observations and models are highlighted.
Colette L. Heald and Jeffrey A. Geddes
Atmos. Chem. Phys., 16, 14997–15010, https://doi.org/10.5194/acp-16-14997-2016, https://doi.org/10.5194/acp-16-14997-2016, 2016
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Humans have altered the surface of the Earth since preindustrial times. These changes (largely expansion of croplands and pasturelands) have modified biosphere–atmosphere fluxes. In this study we use a global model to assess the impact of these changes on the formation of secondary particulate matter and troposphere ozone. We find that there are significant air quality and climate impacts associated with these changes.
Xuan Wang, Colette L. Heald, Arthur J. Sedlacek, Suzane S. de Sá, Scot T. Martin, M. Lizabeth Alexander, Thomas B. Watson, Allison C. Aiken, Stephen R. Springston, and Paulo Artaxo
Atmos. Chem. Phys., 16, 12733–12752, https://doi.org/10.5194/acp-16-12733-2016, https://doi.org/10.5194/acp-16-12733-2016, 2016
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We describe a new approach to estimate the absorption of brown carbon (BrC) from multiple-wavelength absorption measurements. By applying this method to column and surface observations globally, we find that BrC contributes up to 40 % of the absorption measured at 440 nm. The analysis of two surface sites also suggests that BrC absorptivity decreases with photochemical aging in biomass burning plumes, but not in typical urban conditions.
Luke D. Schiferl, Colette L. Heald, Martin Van Damme, Lieven Clarisse, Cathy Clerbaux, Pierre-François Coheur, John B. Nowak, J. Andrew Neuman, Scott C. Herndon, Joseph R. Roscioli, and Scott J. Eilerman
Atmos. Chem. Phys., 16, 12305–12328, https://doi.org/10.5194/acp-16-12305-2016, https://doi.org/10.5194/acp-16-12305-2016, 2016
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This study combines new observations and a simulation to assess the interannual variability of atmospheric ammonia concentrations over the United States. The model generally underrepresents the observed variability. Nearly two-thirds of the simulated variability is caused by meteorology, twice that caused by regulations on fossil fuel combustion emissions. Adding ammonia emissions variability does not substantially improve the simulation and has little impact on summer particle concentrations.
Ivan Kourtchev, Ricardo H. M. Godoi, Sarah Connors, James G. Levine, Alex T. Archibald, Ana F. L. Godoi, Sarah L. Paralovo, Cybelli G. G. Barbosa, Rodrigo A. F. Souza, Antonio O. Manzi, Roger Seco, Steve Sjostedt, Jeong-Hoo Park, Alex Guenther, Saewung Kim, James Smith, Scot T. Martin, and Markus Kalberer
Atmos. Chem. Phys., 16, 11899–11913, https://doi.org/10.5194/acp-16-11899-2016, https://doi.org/10.5194/acp-16-11899-2016, 2016
Weiwei Hu, Brett B. Palm, Douglas A. Day, Pedro Campuzano-Jost, Jordan E. Krechmer, Zhe Peng, Suzane S. de Sá, Scot T. Martin, M. Lizabeth Alexander, Karsten Baumann, Lina Hacker, Astrid Kiendler-Scharr, Abigail R. Koss, Joost A. de Gouw, Allen H. Goldstein, Roger Seco, Steven J. Sjostedt, Jeong-Hoo Park, Alex B. Guenther, Saewung Kim, Francesco Canonaco, André S. H. Prévôt, William H. Brune, and Jose L. Jimenez
Atmos. Chem. Phys., 16, 11563–11580, https://doi.org/10.5194/acp-16-11563-2016, https://doi.org/10.5194/acp-16-11563-2016, 2016
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IEPOX-SOA is biogenically derived secondary organic aerosol under anthropogenic influence, which has been shown to comprise a substantial fraction of OA globally. We investigated the lifetime of ambient IEPOX-SOA in the SE US and Amazonia, with an oxidation flow reactor and thermodenuder coupled with MS-based instrumentation. The low volatility and long lifetime of IEPOX-SOA against OH radicals' oxidation (> 2 weeks) was observed, which can help to constrain OA impact on air quality and climate.
Sam J. Silva, Colette L. Heald, Jeffrey A. Geddes, Kemen G. Austin, Prasad S. Kasibhatla, and Miriam E. Marlier
Atmos. Chem. Phys., 16, 10621–10635, https://doi.org/10.5194/acp-16-10621-2016, https://doi.org/10.5194/acp-16-10621-2016, 2016
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We investigate the impacts of current (2010) and future (2020) oil palm plantations across Southeast Asia on surface–atmosphere exchange and air quality using satellite data, land maps, and a chemical transport model. These changes lead to increases in surface ozone and particulate matter. Oil palm plantations are likely to continue to degrade regional air quality in the coming decade and hinder efforts to achieve air quality regulations in major urban areas such as Kuala Lumpur and Singapore.
Maite Bauwens, Trissevgeni Stavrakou, Jean-François Müller, Isabelle De Smedt, Michel Van Roozendael, Guido R. van der Werf, Christine Wiedinmyer, Johannes W. Kaiser, Katerina Sindelarova, and Alex Guenther
Atmos. Chem. Phys., 16, 10133–10158, https://doi.org/10.5194/acp-16-10133-2016, https://doi.org/10.5194/acp-16-10133-2016, 2016
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Relying on a 9-year record of satellite observations of formaldehyde, we use inverse techniques to derive global top–down hydrocarbon fluxes over 2005–2013, infer seasonal and interannual variability, and detect emission trends. Our results suggest changes in fire seasonal patterns, a stronger contribution of agricultural burning, overestimated isoprene flux rates in the tropics, overly decreased isoprene emissions due to soil moisture stress in arid areas, and enhanced isoprene trends.
Pawel K. Misztal, Jeremy C. Avise, Thomas Karl, Klaus Scott, Haflidi H. Jonsson, Alex B. Guenther, and Allen H. Goldstein
Atmos. Chem. Phys., 16, 9611–9628, https://doi.org/10.5194/acp-16-9611-2016, https://doi.org/10.5194/acp-16-9611-2016, 2016
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In this study, for the first time regional BVOC models are compared with direct regional measurements of fluxes from aircraft, allowing assessment of model accuracy at scales relevant to air quality modeling. We directly assess modeled isoprene emission inventories which are important for regional air quality simulations of ozone and secondary particle concentrations.
Matthew J. Alvarado, Chantelle R. Lonsdale, Helen L. Macintyre, Huisheng Bian, Mian Chin, David A. Ridley, Colette L. Heald, Kenneth L. Thornhill, Bruce E. Anderson, Michael J. Cubison, Jose L. Jimenez, Yutaka Kondo, Lokesh K. Sahu, Jack E. Dibb, and Chien Wang
Atmos. Chem. Phys., 16, 9435–9455, https://doi.org/10.5194/acp-16-9435-2016, https://doi.org/10.5194/acp-16-9435-2016, 2016
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Understanding the scattering and absorption of light by aerosols is necessary for understanding air quality and climate change. We used data from the 2008 ARCTAS campaign to evaluate aerosol optical property models using a closure methodology that separates errors in these models from other errors in aerosol emissions, chemistry, or transport. We find that the models on average perform reasonably well, and make suggestions for how remaining biases could be reduced.
Albert Rivas-Ubach, Yina Liu, Jordi Sardans, Malak M. Tfaily, Young-Mo Kim, Eric Bourrianne, Ljiljana Paša-Tolić, Josep Peñuelas, and Alex Guenther
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-209, https://doi.org/10.5194/amt-2016-209, 2016
Revised manuscript not accepted
Kathryn M. Emmerson, Ian E. Galbally, Alex B. Guenther, Clare Paton-Walsh, Elise-Andree Guerette, Martin E. Cope, Melita D. Keywood, Sarah J. Lawson, Suzie B. Molloy, Erin Dunne, Marcus Thatcher, Thomas Karl, and Simin D. Maleknia
Atmos. Chem. Phys., 16, 6997–7011, https://doi.org/10.5194/acp-16-6997-2016, https://doi.org/10.5194/acp-16-6997-2016, 2016
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We have tested how a model using a global inventory of plant-based emissions compares with four sets of measurements made in southeast Australia. This region is known for its eucalypt species, which dominate the summertime global inventory. The Australian part of the inventory has been produced using measurements made on eucalypt saplings. The model could not match the measurements, and the inventory needs to be improved by taking measurements of a wider range of Australian plant types and ages.
Chun Zhao, Maoyi Huang, Jerome D. Fast, Larry K. Berg, Yun Qian, Alex Guenther, Dasa Gu, Manish Shrivastava, Ying Liu, Stacy Walters, Gabriele Pfister, Jiming Jin, John E. Shilling, and Carsten Warneke
Geosci. Model Dev., 9, 1959–1976, https://doi.org/10.5194/gmd-9-1959-2016, https://doi.org/10.5194/gmd-9-1959-2016, 2016
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In this study, the latest version of MEGAN is coupled within CLM4 in WRF-Chem. In this implementation, MEGAN shares a consistent vegetation map with CLM4. This improved modeling framework is used to investigate the impact of two land surface schemes on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models.
Eliane G. Alves, Kolby Jardine, Julio Tota, Angela Jardine, Ana Maria Yãnez-Serrano, Thomas Karl, Julia Tavares, Bruce Nelson, Dasa Gu, Trissevgeni Stavrakou, Scot Martin, Paulo Artaxo, Antonio Manzi, and Alex Guenther
Atmos. Chem. Phys., 16, 3903–3925, https://doi.org/10.5194/acp-16-3903-2016, https://doi.org/10.5194/acp-16-3903-2016, 2016
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For a long time, it was thought that tropical rainforests are evergreen forests and the processes involved in these ecosystems do not change all year long. However, some satellite retrievals have suggested that ecophysiological processes may present seasonal variations mainly due to variation in light and leaf phenology in Amazonia. These in situ measurements are the first showing of a seasonal trend of volatile organic compound emissions, correlating with light and leaf phenology in Amazonia.
Bonne Ford and Colette L. Heald
Atmos. Chem. Phys., 16, 3499–3523, https://doi.org/10.5194/acp-16-3499-2016, https://doi.org/10.5194/acp-16-3499-2016, 2016
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As motivation for air quality research, many studies cite the fact that exposure to particulate matter is associated with premature mortality. Recently, more studies have also tried to quantify this burden; however, there are many data sets that can be used and many different methodological choices to be made. In this paper, we seek to explain the different sources of uncertainty in health impact assessments through the example of using model and satellite-based PM2.5 concentrations.
Jeffrey A. Geddes, Colette L. Heald, Sam J. Silva, and Randall V. Martin
Atmos. Chem. Phys., 16, 2323–2340, https://doi.org/10.5194/acp-16-2323-2016, https://doi.org/10.5194/acp-16-2323-2016, 2016
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Land use and land cover changes driven by anthropogenic activities or natural causes (e.g., forestry management, agriculture, wildfires) can impact climate and air quality in many complex ways. Using a state-of-the-art chemistry model, we investigate how tree mortality in the US due to insect infestation and disease outbreak may impact atmospheric composition. We find that the surface concentrations of ozone and aerosol can be altered due to changing background emissions and loss processes.
R. Gonzalez-Abraham, S. H. Chung, J. Avise, B. Lamb, E. P. Salathé Jr., C. G. Nolte, D. Loughlin, A. Guenther, C. Wiedinmyer, T. Duhl, Y. Zhang, and D. G. Streets
Atmos. Chem. Phys., 15, 12645–12665, https://doi.org/10.5194/acp-15-12645-2015, https://doi.org/10.5194/acp-15-12645-2015, 2015
T. Stavrakou, J.-F. Müller, M. Bauwens, I. De Smedt, M. Van Roozendael, M. De Mazière, C. Vigouroux, F. Hendrick, M. George, C. Clerbaux, P.-F. Coheur, and A. Guenther
Atmos. Chem. Phys., 15, 11861–11884, https://doi.org/10.5194/acp-15-11861-2015, https://doi.org/10.5194/acp-15-11861-2015, 2015
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Formaldehyde columns from two space sensors, GOME-2 and OMI, constrain by inverse modeling the global emissions of HCHO precursors in 2010. The resulting biogenic and pyrogenic fluxes from both optimizations show a very good degree of consistency. The isoprene fluxes are reduced globally by ca. 10%, and emissions from fires decrease by ca. 35%, compared to the prior. Anthropogenic emissions are weakly constrained except over China. Sensitivity inversions show robustness of the inferred fluxes.
F. Xiong, K. M. McAvey, K. A. Pratt, C. J. Groff, M. A. Hostetler, M. A. Lipton, T. K. Starn, J. V. Seeley, S. B. Bertman, A. P. Teng, J. D. Crounse, T. B. Nguyen, P. O. Wennberg, P. K. Misztal, A. H. Goldstein, A. B. Guenther, A. R. Koss, K. F. Olson, J. A. de Gouw, K. Baumann, E. S. Edgerton, P. A. Feiner, L. Zhang, D. O. Miller, W. H. Brune, and P. B. Shepson
Atmos. Chem. Phys., 15, 11257–11272, https://doi.org/10.5194/acp-15-11257-2015, https://doi.org/10.5194/acp-15-11257-2015, 2015
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Hydroxynitrates from isoprene oxidation were quantified both in the laboratory and through field studies. The yield of hydroxynitrates 9(+4/-3)% derived from chamber experiments was applied in a zero-dimensional model to simulate the production and loss of isoprene hydroxynitrates in an ambient environment during the 2013 Southern Oxidant and Aerosol Study (SOAS). NOx was determined to be the limiting factor for the formation of isoprene hydroxynitrates during SOAS.
W. C. Porter, C. L. Heald, D. Cooley, and B. Russell
Atmos. Chem. Phys., 15, 10349–10366, https://doi.org/10.5194/acp-15-10349-2015, https://doi.org/10.5194/acp-15-10349-2015, 2015
L. Zhou, R. Gierens, A. Sogachev, D. Mogensen, J. Ortega, J. N. Smith, P. C. Harley, A. J. Prenni, E. J. T. Levin, A. Turnipseed, A. Rusanen, S. Smolander, A. B. Guenther, M. Kulmala, T. Karl, and M. Boy
Atmos. Chem. Phys., 15, 8643–8656, https://doi.org/10.5194/acp-15-8643-2015, https://doi.org/10.5194/acp-15-8643-2015, 2015
G. Wohlfahrt, C. Amelynck, C. Ammann, A. Arneth, I. Bamberger, A. H. Goldstein, L. Gu, A. Guenther, A. Hansel, B. Heinesch, T. Holst, L. Hörtnagl, T. Karl, Q. Laffineur, A. Neftel, K. McKinney, J. W. Munger, S. G. Pallardy, G. W. Schade, R. Seco, and N. Schoon
Atmos. Chem. Phys., 15, 7413–7427, https://doi.org/10.5194/acp-15-7413-2015, https://doi.org/10.5194/acp-15-7413-2015, 2015
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Methanol is the second most abundant volatile organic compound in the troposphere and plays a significant role in atmospheric chemistry. While there is consensus about the dominant role of plants as the major source and the reaction with OH as the major sink, global methanol budgets diverge considerably in terms of source/sink estimates. Here we present micrometeorological methanol flux data from eight sites in order to provide a first cross-site synthesis of the terrestrial methanol exchange.
S. Kim, S.-Y. Kim, M. Lee, H. Shim, G. M. Wolfe, A. B. Guenther, A. He, Y. Hong, and J. Han
Atmos. Chem. Phys., 15, 4357–4371, https://doi.org/10.5194/acp-15-4357-2015, https://doi.org/10.5194/acp-15-4357-2015, 2015
M. Val Martin, C. L. Heald, J.-F. Lamarque, S. Tilmes, L. K. Emmons, and B. A. Schichtel
Atmos. Chem. Phys., 15, 2805–2823, https://doi.org/10.5194/acp-15-2805-2015, https://doi.org/10.5194/acp-15-2805-2015, 2015
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We present for the first time the relative effect of climate, emissions, and land use change on ozone and PM25 over the United States, focusing on the national parks. Air quality in 2050 will likely be dominated by emission patterns, but climate and land use changes alone can lead to a substantial increase in air pollution over most of the US, with important implications for O3 air quality, visibility and ecosystem health degradation in the national parks.
C. S. Brauer, T. A. Blake, A. B. Guenther, S. W. Sharpe, R. L. Sams, and T. J. Johnson
Atmos. Meas. Tech., 7, 3839–3847, https://doi.org/10.5194/amt-7-3839-2014, https://doi.org/10.5194/amt-7-3839-2014, 2014
Y. You, V. P. Kanawade, J. A. de Gouw, A. B. Guenther, S. Madronich, M. R. Sierra-Hernández, M. Lawler, J. N. Smith, S. Takahama, G. Ruggeri, A. Koss, K. Olson, K. Baumann, R. J. Weber, A. Nenes, H. Guo, E. S. Edgerton, L. Porcelli, W. H. Brune, A. H. Goldstein, and S.-H. Lee
Atmos. Chem. Phys., 14, 12181–12194, https://doi.org/10.5194/acp-14-12181-2014, https://doi.org/10.5194/acp-14-12181-2014, 2014
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Amiens play important roles in atmospheric secondary aerosol formation and human health, but the fast response measurements of amines are lacking. Here we show measurements in a southeastern US forest and a moderately polluted midwestern site. Our results show that gas to particle conversion is an important process that controls ambient amine concentrations and that biomass burning is an important source of amines.
X. Wang, C. L. Heald, D. A. Ridley, J. P. Schwarz, J. R. Spackman, A. E. Perring, H. Coe, D. Liu, and A. D. Clarke
Atmos. Chem. Phys., 14, 10989–11010, https://doi.org/10.5194/acp-14-10989-2014, https://doi.org/10.5194/acp-14-10989-2014, 2014
P. K. Misztal, T. Karl, R. Weber, H. H. Jonsson, A. B. Guenther, and A. H. Goldstein
Atmos. Chem. Phys., 14, 10631–10647, https://doi.org/10.5194/acp-14-10631-2014, https://doi.org/10.5194/acp-14-10631-2014, 2014
S. Smolander, Q. He, D. Mogensen, L. Zhou, J. Bäck, T. Ruuskanen, S. Noe, A. Guenther, H. Aaltonen, M. Kulmala, and M. Boy
Biogeosciences, 11, 5425–5443, https://doi.org/10.5194/bg-11-5425-2014, https://doi.org/10.5194/bg-11-5425-2014, 2014
K. Sindelarova, C. Granier, I. Bouarar, A. Guenther, S. Tilmes, T. Stavrakou, J.-F. Müller, U. Kuhn, P. Stefani, and W. Knorr
Atmos. Chem. Phys., 14, 9317–9341, https://doi.org/10.5194/acp-14-9317-2014, https://doi.org/10.5194/acp-14-9317-2014, 2014
D. V. Spracklen and C. L. Heald
Atmos. Chem. Phys., 14, 9051–9059, https://doi.org/10.5194/acp-14-9051-2014, https://doi.org/10.5194/acp-14-9051-2014, 2014
R. J. Park, S. K. Hong, H.-A. Kwon, S. Kim, A. Guenther, J.-H. Woo, and C. P. Loughner
Atmos. Chem. Phys., 14, 7929–7940, https://doi.org/10.5194/acp-14-7929-2014, https://doi.org/10.5194/acp-14-7929-2014, 2014
E. A. Marais, D. J. Jacob, A. Guenther, K. Chance, T. P. Kurosu, J. G. Murphy, C. E. Reeves, and H. O. T. Pye
Atmos. Chem. Phys., 14, 7693–7703, https://doi.org/10.5194/acp-14-7693-2014, https://doi.org/10.5194/acp-14-7693-2014, 2014
J. P. Greenberg, J. Peñuelas, A. Guenther, R. Seco, A. Turnipseed, X. Jiang, I. Filella, M. Estiarte, J. Sardans, R. Ogaya, J. Llusia, and F. Rapparini
Atmos. Meas. Tech., 7, 2263–2271, https://doi.org/10.5194/amt-7-2263-2014, https://doi.org/10.5194/amt-7-2263-2014, 2014
K. Jaars, J. P. Beukes, P. G. van Zyl, A. D. Venter, M. Josipovic, J. J. Pienaar, V. Vakkari, H. Aaltonen, H. Laakso, M. Kulmala, P. Tiitta, A. Guenther, H. Hellén, L. Laakso, and H. Hakola
Atmos. Chem. Phys., 14, 7075–7089, https://doi.org/10.5194/acp-14-7075-2014, https://doi.org/10.5194/acp-14-7075-2014, 2014
J. Ortega, A. Turnipseed, A. B. Guenther, T. G. Karl, D. A. Day, D. Gochis, J. A. Huffman, A. J. Prenni, E. J. T. Levin, S. M. Kreidenweis, P. J. DeMott, Y. Tobo, E. G. Patton, A. Hodzic, Y. Y. Cui, P. C. Harley, R. S. Hornbrook, E. C. Apel, R. K. Monson, A. S. D. Eller, J. P. Greenberg, M. C. Barth, P. Campuzano-Jost, B. B. Palm, J. L. Jimenez, A. C. Aiken, M. K. Dubey, C. Geron, J. Offenberg, M. G. Ryan, P. J. Fornwalt, S. C. Pryor, F. N. Keutsch, J. P. DiGangi, A. W. H. Chan, A. H. Goldstein, G. M. Wolfe, S. Kim, L. Kaser, R. Schnitzhofer, A. Hansel, C. A. Cantrell, R. L. Mauldin, and J. N. Smith
Atmos. Chem. Phys., 14, 6345–6367, https://doi.org/10.5194/acp-14-6345-2014, https://doi.org/10.5194/acp-14-6345-2014, 2014
D. A. Ridley, C. L. Heald, and J. M. Prospero
Atmos. Chem. Phys., 14, 5735–5747, https://doi.org/10.5194/acp-14-5735-2014, https://doi.org/10.5194/acp-14-5735-2014, 2014
C. L. Heald, D. A. Ridley, J. H. Kroll, S. R. H. Barrett, K. E. Cady-Pereira, M. J. Alvarado, and C. D. Holmes
Atmos. Chem. Phys., 14, 5513–5527, https://doi.org/10.5194/acp-14-5513-2014, https://doi.org/10.5194/acp-14-5513-2014, 2014
M. Liu, K. Rajagopalan, S. H. Chung, X. Jiang, J. Harrison, T. Nergui, A. Guenther, C. Miller, J. Reyes, C. Tague, J. Choate, E. P. Salathé, C. O. Stöckle, and J. C. Adam
Biogeosciences, 11, 2601–2622, https://doi.org/10.5194/bg-11-2601-2014, https://doi.org/10.5194/bg-11-2601-2014, 2014
M. Van Damme, L. Clarisse, C. L. Heald, D. Hurtmans, Y. Ngadi, C. Clerbaux, A. J. Dolman, J. W. Erisman, and P. F. Coheur
Atmos. Chem. Phys., 14, 2905–2922, https://doi.org/10.5194/acp-14-2905-2014, https://doi.org/10.5194/acp-14-2905-2014, 2014
R. Zhang, T. Duhl, M. T. Salam, J. M. House, R. C. Flagan, E. L. Avol, F. D. Gilliland, A. Guenther, S. H. Chung, B. K. Lamb, and T. M. VanReken
Biogeosciences, 11, 1461–1478, https://doi.org/10.5194/bg-11-1461-2014, https://doi.org/10.5194/bg-11-1461-2014, 2014
L. Kaser, T. Karl, A. Guenther, M. Graus, R. Schnitzhofer, A. Turnipseed, L. Fischer, P. Harley, M. Madronich, D. Gochis, F. N. Keutsch, and A. Hansel
Atmos. Chem. Phys., 13, 11935–11947, https://doi.org/10.5194/acp-13-11935-2013, https://doi.org/10.5194/acp-13-11935-2013, 2013
S. Situ, A. Guenther, X. Wang, X. Jiang, A. Turnipseed, Z. Wu, J. Bai, and X. Wang
Atmos. Chem. Phys., 13, 11803–11817, https://doi.org/10.5194/acp-13-11803-2013, https://doi.org/10.5194/acp-13-11803-2013, 2013
N. Unger, K. Harper, Y. Zheng, N. Y. Kiang, I. Aleinov, A. Arneth, G. Schurgers, C. Amelynck, A. Goldstein, A. Guenther, B. Heinesch, C. N. Hewitt, T. Karl, Q. Laffineur, B. Langford, K. A. McKinney, P. Misztal, M. Potosnak, J. Rinne, S. Pressley, N. Schoon, and D. Serça
Atmos. Chem. Phys., 13, 10243–10269, https://doi.org/10.5194/acp-13-10243-2013, https://doi.org/10.5194/acp-13-10243-2013, 2013
J. E. Mak, L. Su, A. Guenther, and T. Karl
Atmos. Meas. Tech., 6, 2703–2712, https://doi.org/10.5194/amt-6-2703-2013, https://doi.org/10.5194/amt-6-2703-2013, 2013
B. Ford and C. L. Heald
Atmos. Chem. Phys., 13, 9269–9283, https://doi.org/10.5194/acp-13-9269-2013, https://doi.org/10.5194/acp-13-9269-2013, 2013
M. Val Martin, C. L. Heald, B. Ford, A. J. Prenni, and C. Wiedinmyer
Atmos. Chem. Phys., 13, 7429–7439, https://doi.org/10.5194/acp-13-7429-2013, https://doi.org/10.5194/acp-13-7429-2013, 2013
X. Tie, F. Geng, A. Guenther, J. Cao, J. Greenberg, R. Zhang, E. Apel, G. Li, A. Weinheimer, J. Chen, and C. Cai
Atmos. Chem. Phys., 13, 5655–5669, https://doi.org/10.5194/acp-13-5655-2013, https://doi.org/10.5194/acp-13-5655-2013, 2013
T. R. Duhl, R. Zhang, A. Guenther, S. H. Chung, M. T. Salam, J. M. House, R. C. Flagan, E. L. Avol, F. D. Gilliland, B. K. Lamb, T. M. VanReken, Y. Zhang, and E. Salathé
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-2325-2013, https://doi.org/10.5194/gmdd-6-2325-2013, 2013
Revised manuscript not accepted
A. R. Berg, C. L. Heald, K. E. Huff Hartz, A. G. Hallar, A. J. H. Meddens, J. A. Hicke, J.-F. Lamarque, and S. Tilmes
Atmos. Chem. Phys., 13, 3149–3161, https://doi.org/10.5194/acp-13-3149-2013, https://doi.org/10.5194/acp-13-3149-2013, 2013
L. Kaser, T. Karl, R. Schnitzhofer, M. Graus, I. S. Herdlinger-Blatt, J. P. DiGangi, B. Sive, A. Turnipseed, R. S. Hornbrook, W. Zheng, F. M. Flocke, A. Guenther, F. N. Keutsch, E. Apel, and A. Hansel
Atmos. Chem. Phys., 13, 2893–2906, https://doi.org/10.5194/acp-13-2893-2013, https://doi.org/10.5194/acp-13-2893-2013, 2013
T. R. Duhl, D. Gochis, A. Guenther, S. Ferrenberg, and E. Pendall
Biogeosciences, 10, 483–499, https://doi.org/10.5194/bg-10-483-2013, https://doi.org/10.5194/bg-10-483-2013, 2013
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An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing
On the use of Infrared Atmospheric Sounding Interferometer (IASI) spectrally resolved radiances to test the EC-Earth climate model (v3.3.3) in clear-sky conditions
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ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application
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Chuanhua Ren, Xin Huang, Tengyu Liu, Yu Song, Zhang Wen, Xuejun Liu, Aijun Ding, and Tong Zhu
Geosci. Model Dev., 16, 1641–1659, https://doi.org/10.5194/gmd-16-1641-2023, https://doi.org/10.5194/gmd-16-1641-2023, 2023
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Ammonia in the atmosphere has wide impacts on the ecological environment and air quality, and its emission from soil volatilization is highly sensitive to meteorology, making it challenging to be well captured in models. We developed a dynamic emission model capable of calculating ammonia emission interactively with meteorological and soil conditions. Such a coupling of soil emission with meteorology provides a better understanding of ammonia emission and its contribution to atmospheric aerosol.
Linlu Mei, Vladimir Rozanov, Alexei Rozanov, and John P. Burrows
Geosci. Model Dev., 16, 1511–1536, https://doi.org/10.5194/gmd-16-1511-2023, https://doi.org/10.5194/gmd-16-1511-2023, 2023
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This paper summarizes recent developments of aerosol, cloud and surface reflectance databases and models in the framework of the software package SCIATRAN. These updates and developments extend the capabilities of the radiative transfer modeling, especially by accounting for different kinds of vertical inhomogeneties. Vertically inhomogeneous clouds and different aerosol types can be easily accounted for within SCIATRAN (V4.6). The widely used surface models and databases are now available.
Adrian Rojas-Campos, Michael Langguth, Martin Wittenbrink, and Gordon Pipa
Geosci. Model Dev., 16, 1467–1480, https://doi.org/10.5194/gmd-16-1467-2023, https://doi.org/10.5194/gmd-16-1467-2023, 2023
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Our paper presents an alternative approach for generating high-resolution precipitation maps based on the nonlinear combination of the complete set of variables of the numerical weather predictions. This process combines the super-resolution task with the bias correction in a single step, generating high-resolution corrected precipitation maps with a lead time of 3 h. We used using deep learning algorithms to combine the input information and increase the accuracy of the precipitation maps.
Robin N. Thor, Mariano Mertens, Sigrun Matthes, Mattia Righi, Johannes Hendricks, Sabine Brinkop, Phoebe Graf, Volker Grewe, Patrick Jöckel, and Steven Smith
Geosci. Model Dev., 16, 1459–1466, https://doi.org/10.5194/gmd-16-1459-2023, https://doi.org/10.5194/gmd-16-1459-2023, 2023
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We report on an inconsistency in the latitudinal distribution of aviation emissions between two versions of a data product which is widely used by researchers. From the available documentation, we do not expect such an inconsistency. We run a chemistry–climate model to compute the effect of the inconsistency in emissions on atmospheric chemistry and radiation and find that the radiative forcing associated with aviation ozone is 7.6 % higher when using the less recent version of the data.
Stefano Della Fera, Federico Fabiano, Piera Raspollini, Marco Ridolfi, Ugo Cortesi, Flavio Barbara, and Jost von Hardenberg
Geosci. Model Dev., 16, 1379–1394, https://doi.org/10.5194/gmd-16-1379-2023, https://doi.org/10.5194/gmd-16-1379-2023, 2023
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The long-term comparison between observed and simulated outgoing longwave radiances represents a strict test to evaluate climate model performance. In this work, 9 years of synthetic spectrally resolved radiances, simulated online on the basis of the atmospheric fields predicted by the EC-Earth global climate model (v3.3.3) in clear-sky conditions, are compared to IASI spectral radiance climatology in order to detect model biases in temperature and humidity at different atmospheric levels.
Marine Bonazzola, Hélène Chepfer, Po-Lun Ma, Johannes Quaas, David M. Winker, Artem Feofilov, and Nick Schutgens
Geosci. Model Dev., 16, 1359–1377, https://doi.org/10.5194/gmd-16-1359-2023, https://doi.org/10.5194/gmd-16-1359-2023, 2023
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Aerosol has a large impact on climate. Using a lidar aerosol simulator ensures consistent comparisons between modeled and observed aerosol. We present a lidar aerosol simulator that applies a cloud masking and an aerosol detection threshold. We estimate the lidar signals that would be observed at 532 nm by the Cloud-Aerosol Lidar with Orthogonal Polarization overflying the atmosphere predicted by a climate model. Our comparison at the seasonal timescale shows a discrepancy in the Southern Ocean.
Michael S. Walters and David C. Wong
Geosci. Model Dev., 16, 1179–1190, https://doi.org/10.5194/gmd-16-1179-2023, https://doi.org/10.5194/gmd-16-1179-2023, 2023
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A typical numerical simulation that associates with a large amount of input and output data, applying popular compression software, gzip or bzip2, on data is one good way to mitigate data storage burden. This article proposes a simple technique to alter input, output, or input and output by keeping a specific number of significant digits in data and demonstrates an enhancement in compression efficiency on the altered data but maintains similar statistical performance of the numerical simulation.
Sylvain Mailler, Laurent Menut, Arineh Cholakian, and Romain Pennel
Geosci. Model Dev., 16, 1119–1127, https://doi.org/10.5194/gmd-16-1119-2023, https://doi.org/10.5194/gmd-16-1119-2023, 2023
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Large or even
giantparticles of mineral dust exist in the atmosphere but, so far, solving an non-linear equation was needed to calculate the speed at which they fall in the atmosphere. The model we present, AerSett v1.0 (AERosol SETTling version 1.0), provides a new and simple way of calculating their free-fall velocity in the atmosphere, which will be useful to anyone trying to understand and represent adequately the transport of giant dust particles by the wind.
Yen-Sen Lu, Garrett H. Good, and Hendrik Elbern
Geosci. Model Dev., 16, 1083–1104, https://doi.org/10.5194/gmd-16-1083-2023, https://doi.org/10.5194/gmd-16-1083-2023, 2023
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The Weather Forecasting and Research (WRF) model consists of many parameters and options that can be adapted to different conditions. This expansive sensitivity study uses a large-scale simulation system to determine the most suitable options for predicting cloud cover in Europe for deterministic and probabilistic weather predictions for day-ahead forecasting simulations.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
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When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi.
Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Phuc Thi Minh Ha, Yugo Kanaya, Fumikazu Taketani, Maria Dolores Andrés Hernández, Benjamin Schreiner, Klaus Pfeilsticker, and Kengo Sudo
Geosci. Model Dev., 16, 927–960, https://doi.org/10.5194/gmd-16-927-2023, https://doi.org/10.5194/gmd-16-927-2023, 2023
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HONO affects tropospheric oxidizing capacity; thus, it is implemented into the chemistry–climate model CHASER. The model substantially underpredicts daytime HONO, while nitrate photolysis on surfaces can supplement the daytime HONO budget. Current HONO chemistry predicts reductions of 20.4 % for global tropospheric NOx, 40–67 % for OH, and 30–45 % for O3 in the summer North Pacific. In contrast, OH and O3 winter levels in China are greatly enhanced.
Ryan Vella, Matthew Forrest, Jos Lelieveld, and Holger Tost
Geosci. Model Dev., 16, 885–906, https://doi.org/10.5194/gmd-16-885-2023, https://doi.org/10.5194/gmd-16-885-2023, 2023
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Biogenic volatile organic compounds (BVOCs) are released by vegetation and have a major impact on atmospheric chemistry and aerosol formation. Non-interacting vegetation constrains the majority of numerical models used to estimate global BVOC emissions, and thus, the effects of changing vegetation on emissions are not addressed. In this work, we replace the offline vegetation with dynamic vegetation states by linking a chemistry–climate model with a global dynamic vegetation model.
Danny McCulloch, Denis E. Sergeev, Nathan Mayne, Matthew Bate, James Manners, Ian Boutle, Benjamin Drummond, and Kristzian Kohary
Geosci. Model Dev., 16, 621–657, https://doi.org/10.5194/gmd-16-621-2023, https://doi.org/10.5194/gmd-16-621-2023, 2023
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We present results from the Met Office Unified Model (UM) to study the dry Martian climate. We describe our model set-up conditions and run two scenarios, with radiatively active/inactive dust. We compare both scenarios to results from an existing Mars climate model, the planetary climate model. We find good agreement in winds and air temperatures, but dust amounts differ between models. This study highlights the importance of using the UM for future Mars research.
Sam-Erik Walker, Sverre Solberg, Philipp Schneider, and Cristina Guerreiro
Geosci. Model Dev., 16, 573–595, https://doi.org/10.5194/gmd-16-573-2023, https://doi.org/10.5194/gmd-16-573-2023, 2023
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We have developed a statistical model for estimating trends in the daily air quality observations of NO2, O3, PM10 and PM2.5, adjusting for trends and short-term variations in meteorology. The model is general and may also be used for prediction purposes, including forecasting. It has been applied in a recent comprehensive study in Europe. Significant declines are shown for the pollutants from 2005 to 2019, mainly due to reductions in emissions not attributable to changes in meteorology.
Bianca Adler, James M. Wilczak, Jaymes Kenyon, Laura Bianco, Irina V. Djalalova, Joseph B. Olson, and David D. Turner
Geosci. Model Dev., 16, 597–619, https://doi.org/10.5194/gmd-16-597-2023, https://doi.org/10.5194/gmd-16-597-2023, 2023
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Rapid changes in wind speed make the integration of wind energy produced during persistent orographic cold-air pools difficult to integrate into the electrical grid. By evaluating three versions of NOAA’s High-Resolution Rapid Refresh model, we demonstrate how model developments targeted during the second Wind Forecast Improvement Project improve the forecast of a persistent cold-air pool event.
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023, https://doi.org/10.5194/gmd-16-509-2023, 2023
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We focus on the challenges associated with comparing atmospheric composition models with satellite products such as tropospheric NO2 columns. The aim is to highlight the methodological difficulties and propose sound ways of doing such comparisons. Building on the comparisons, a new satellite product is proposed and made available, which takes advantage of higher-resolution, regional atmospheric modelling to improve estimates of troposheric NO2 columns over Europe.
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Dominique Fonteyn, Frederik Tack, Felix Deutsch, Quentin Laffineur, Roeland Van Malderen, and Nele Veldeman
Geosci. Model Dev., 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023, https://doi.org/10.5194/gmd-16-479-2023, 2023
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High-resolution WRF-Chem simulations are conducted over Antwerp, Belgium, in June 2019 and evaluated using meteorological data and in situ, airborne, and spaceborne NO2 measurements. An intercomparison of model, aircraft, and TROPOMI NO2 columns is conducted to characterize biases in versions 1.3.1 and 2.3.1 of the satellite product. A mass balance method is implemented to provide improved emissions for simulating NO2 distribution over the study area.
Daan R. Scheepens, Irene Schicker, Kateřina Hlaváčková-Schindler, and Claudia Plant
Geosci. Model Dev., 16, 251–270, https://doi.org/10.5194/gmd-16-251-2023, https://doi.org/10.5194/gmd-16-251-2023, 2023
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The production of wind energy is increasing rapidly and relies heavily on atmospheric conditions. To ensure power grid stability, accurate predictions of wind speed are needed, especially in the short range and for extreme wind speed ranges. In this work, we demonstrate the forecasting skills of a data-driven deep learning model with model adaptations to suit higher wind speed ranges. The resulting model can be applied to other data and parameters, too, to improve nowcasting predictions.
Peter J. M. Bosman and Maarten C. Krol
Geosci. Model Dev., 16, 47–74, https://doi.org/10.5194/gmd-16-47-2023, https://doi.org/10.5194/gmd-16-47-2023, 2023
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We describe an inverse modelling framework constructed around a simple model for the atmospheric boundary layer. This framework can be fed with various observation types to study the boundary layer and land–atmosphere exchange. With this framework, it is possible to estimate model parameters and the associated uncertainties. Some of these parameters are difficult to obtain directly by observations. An example application for a grassland in the Netherlands is included.
Kun Wang, Chao Gao, Haofan Wang, Kai Wu, Qingqing Tong, Mo Dan, Kaiyun Liu, and Xiaohui Ji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-266, https://doi.org/10.5194/gmd-2022-266, 2023
Revised manuscript accepted for GMD
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This study established an easy-to-use and integrated framework on model ready emission inventory for Weather Research and Forecasting (WRF)-Air quality numerical model (AQM). A free tool named ISAT (Inventory Spatial Allocation Tool) was developed based on this framework. ISAT help user complete the workflow from WRF nested domain configuration to model ready emission inventory for AQM with regional emission inventory and shapefile for target region.
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023, https://doi.org/10.5194/gmd-16-1-2023, 2023
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Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Walter Hannah and Kyle Pressel
Geosci. Model Dev., 15, 8999–9013, https://doi.org/10.5194/gmd-15-8999-2022, https://doi.org/10.5194/gmd-15-8999-2022, 2022
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A multiscale modeling framework couples two models of the atmosphere that each cover different scale ranges. Traditionally, fluctuations in the small-scale model are not transported by the flow on the large-scale model grid, but this is hypothesized to be responsible for a persistent, unphysical checkerboard pattern. A method is presented to facilitate the transport of these small-scale fluctuations, analogous to how small-scale clouds and turbulence are transported in the real atmosphere.
Reimar Bauer, Jens-Uwe Grooß, Jörn Ungermann, May Bär, Markus Geldenhuys, and Lars Hoffmann
Geosci. Model Dev., 15, 8983–8997, https://doi.org/10.5194/gmd-15-8983-2022, https://doi.org/10.5194/gmd-15-8983-2022, 2022
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The Mission Support System (MSS) is an open source software package that has been used for planning flight tracks of scientific aircraft in multiple measurement campaigns during the last decade. Here, we describe the MSS software and its use during the SouthTRAC measurement campaign in 2019. As an example for how the MSS software is used in conjunction with many datasets, we describe the planning of a single flight probing orographic gravity waves propagating up into the lower mesosphere.
Zhizhao Wang, Florian Couvidat, and Karine Sartelet
Geosci. Model Dev., 15, 8957–8982, https://doi.org/10.5194/gmd-15-8957-2022, https://doi.org/10.5194/gmd-15-8957-2022, 2022
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Air quality models need to reliably predict secondary organic aerosols (SOAs) at a reasonable computational cost. Thus, we developed GENOA v1.0, a mechanism reduction algorithm that preserves the accuracy of detailed gas-phase chemical mechanisms for SOA formation, thereby improving the practical use of actual chemistry in SOA models. With GENOA, a near-explicit chemical scheme was reduced to 2 % of its original size and computational time, with an average error of less than 3 %.
Felix Kleinert, Lukas H. Leufen, Aurelia Lupascu, Tim Butler, and Martin G. Schultz
Geosci. Model Dev., 15, 8913–8930, https://doi.org/10.5194/gmd-15-8913-2022, https://doi.org/10.5194/gmd-15-8913-2022, 2022
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We examine the effects of spatially aggregated upstream information as input for a deep learning model forecasting near-surface ozone levels. Using aggregated data from one upstream sector (45°) improves the forecast by ~ 10 % for 4 prediction days. Three upstream sectors improve the forecasts by ~ 14 % on the first 2 d only. Our results serve as an orientation for other researchers or environmental agencies focusing on pointwise time-series predictions, for example, due to regulatory purposes.
Brian T. Dinkelacker, Pablo Garcia Rivera, Ioannis Kioutsioukis, Peter J. Adams, and Spyros N. Pandis
Geosci. Model Dev., 15, 8899–8912, https://doi.org/10.5194/gmd-15-8899-2022, https://doi.org/10.5194/gmd-15-8899-2022, 2022
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The performance of a chemical transport model in reproducing PM2.5 concentrations and composition was evaluated at the finest scale using measurements from regulatory sites as well as a network of low-cost monitors. Total PM2.5 mass is reproduced well by the model during the winter when compared to regulatory measurements, but in the summer PM2.5 is underpredicted, mainly due to difficulties in reproducing regional secondary organic aerosol levels.
Shizhang Wang and Xiaoshi Qiao
Geosci. Model Dev., 15, 8869–8897, https://doi.org/10.5194/gmd-15-8869-2022, https://doi.org/10.5194/gmd-15-8869-2022, 2022
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A local data assimilation scheme (Local DA v1.0) was proposed to leverage the advantage of hybrid covariance, multiscale localization, and parallel computation. The Local DA can perform covariance localization in model space, observation space, or both spaces. The Local DA that used the hybrid covariance and double-space localization produced the lowest analysis and forecast errors among all observing system simulation experiments.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
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Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
Daiwen Kang, Nicholas K. Heath, Robert C. Gilliam, Tanya L. Spero, and Jonathan E. Pleim
Geosci. Model Dev., 15, 8561–8579, https://doi.org/10.5194/gmd-15-8561-2022, https://doi.org/10.5194/gmd-15-8561-2022, 2022
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A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF) convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the KF scheme on simulations with and without LTA are assessed. The model's performance is improved significantly by LTA, but it is sensitive to various factors.
Sujeong Lim, Hyeon-Ju Gim, Ebony Lee, Seungyeon Lee, Won Young Lee, Yong Hee Lee, Claudio Cassardo, and Seon Ki Park
Geosci. Model Dev., 15, 8541–8559, https://doi.org/10.5194/gmd-15-8541-2022, https://doi.org/10.5194/gmd-15-8541-2022, 2022
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The land surface model (LSM) contains various uncertain parameters, which are obtained by the empirical relations reflecting the specific local region and can be a source of uncertainty. To seek the optimal parameter values in the snow-related processes of the Noah LSM over South Korea, we have implemented an optimization algorithm, a micro-genetic algorithm using the observations. As a result, the optimized snow parameters improve snowfall prediction.
Haochen Sun, Jimmy C. H. Fung, Yiang Chen, Zhenning Li, Dehao Yuan, Wanying Chen, and Xingcheng Lu
Geosci. Model Dev., 15, 8439–8452, https://doi.org/10.5194/gmd-15-8439-2022, https://doi.org/10.5194/gmd-15-8439-2022, 2022
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This study developed a novel deep-learning layer, the broadcasting layer, to build an end-to-end LSTM-based deep-learning model for regional air pollution forecast. By combining the ground observation, WRF-CMAQ simulation, and the broadcasting LSTM deep-learning model, forecast accuracy has been significantly improved when compared to other methods. The broadcasting layer and its variants can also be applied in other research areas to supersede the traditional numerical interpolation methods.
Shunji Kotsuki, Takemasa Miyoshi, Keiichi Kondo, and Roland Potthast
Geosci. Model Dev., 15, 8325–8348, https://doi.org/10.5194/gmd-15-8325-2022, https://doi.org/10.5194/gmd-15-8325-2022, 2022
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Data assimilation plays an important part in numerical weather prediction (NWP) in terms of combining forecasted states and observations. While data assimilation methods in NWP usually assume the Gaussian error distribution, some variables in the atmosphere, such as precipitation, are known to have non-Gaussian error statistics. This study extended a widely used ensemble data assimilation algorithm to enable the assimilation of more non-Gaussian observations.
Martin Vojta, Andreas Plach, Rona L. Thompson, and Andreas Stohl
Geosci. Model Dev., 15, 8295–8323, https://doi.org/10.5194/gmd-15-8295-2022, https://doi.org/10.5194/gmd-15-8295-2022, 2022
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In light of recent global warming, we aim to improve methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Ruizi Shi and Fanghua Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-233, https://doi.org/10.5194/gmd-2022-233, 2022
Revised manuscript accepted for GMD
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Based on Gaussian Quadrature method, a fast parameterization scheme of sea spray-mediated heat flux is developed. Compared with the widely-used single-radius scheme, the new scheme shows a better agreement with the full spectrum integral of spray-flux. The new scheme is evaluated in a coupled modeling system, and the simulations of sea surface temperature, wind speed and wave height are improved. Thereby, the new scheme has a great potential to be used in coupled modeling systems.
Alvaro Criado, Jan Mateu Armengol, Hervé Petetin, Daniel Rodríguez-Rey, Jaime Benavides, Marc Guevara, Carlos Pérez García-Pando, Albert Soret, and Oriol Jorba
EGUsphere, https://doi.org/10.5194/egusphere-2022-1147, https://doi.org/10.5194/egusphere-2022-1147, 2022
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The goal of this work is to derive and evaluate a general statistical post-processing tool specifically designed for the street scale that can be applied to any urban air quality system. Our data-fusion methodology corrects NO2 fields based on continuous hourly observations and experimental campaigns. This study able us to obtain exceedance probability maps of air quality standards. In 2019, 13 % of the Barcelona area had a 70 % or higher probability of exceeding the annual legal NO2 limit.
Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
Geosci. Model Dev., 15, 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022, https://doi.org/10.5194/gmd-15-7977-2022, 2022
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This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
Elena Fillola, Raul Santos-Rodriguez, Alistair Manning, Simon O'Doherty, and Matt Rigby
EGUsphere, https://doi.org/10.5194/egusphere-2022-1174, https://doi.org/10.5194/egusphere-2022-1174, 2022
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Lagrangian particle dispersion models are used extensively for the estimation of greenhouse gas (GHG) fluxes using atmospheric observations. However, these models do not scale well as data volumes increase. Here, we develop a proof-of-concept machine learning emulator that can produce outputs similar to those of the dispersion model, but 50,000 times faster, using only meteorological inputs. This works demonstrates the potential of machine learning to accelerate GHG estimations across the globe.
Zhiquan Liu, Chris Snyder, Jonathan J. Guerrette, Byoung-Joo Jung, Junmei Ban, Steven Vahl, Yali Wu, Yannick Trémolet, Thomas Auligné, Benjamin Ménétrier, Anna Shlyaeva, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 15, 7859–7878, https://doi.org/10.5194/gmd-15-7859-2022, https://doi.org/10.5194/gmd-15-7859-2022, 2022
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JEDI-MPAS 1.0.0, a new data assimilation (DA) system for the MPAS model, was publicly released for community use. This article describes JEDI-MPAS's implementation of the ensemble–variational DA technique and demonstrates its robustness and credible performance by incrementally adding three types of microwave radiances (clear-sky AMSU-A, all-sky AMSU-A, clear-sky MHS) to a non-radiance DA experiment. We intend to periodically release new and improved versions of JEDI-MPAS in upcoming years.
Li Fang, Jianbing Jin, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao
Geosci. Model Dev., 15, 7791–7807, https://doi.org/10.5194/gmd-15-7791-2022, https://doi.org/10.5194/gmd-15-7791-2022, 2022
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This study proposes a regional feature selection-based machine learning system to predict short-term air quality in China. The system has a tool that can figure out the importance of input data for better prediction. It provides large-scale air quality prediction that exhibits improved interpretability, fewer training costs, and higher accuracy compared with a standard machine learning system. It can act as an early warning for citizens and reduce exposure to PM2.5 and other air pollutants.
Stella E. I. Manavi and Spyros N. Pandis
Geosci. Model Dev., 15, 7731–7749, https://doi.org/10.5194/gmd-15-7731-2022, https://doi.org/10.5194/gmd-15-7731-2022, 2022
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The paper describes the first step towards the development of a simulation framework for the chemistry and secondary organic aerosol production of intermediate-volatility organic compounds (IVOCs). These compounds can be a significant source of organic particulate matter. Our approach treats IVOCs as lumped compounds that retain their chemical characteristics. Estimated IVOC emissions from road transport were a factor of 8 higher than emissions used in previous applications.
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
EGUsphere, https://doi.org/10.5194/egusphere-2022-1093, https://doi.org/10.5194/egusphere-2022-1093, 2022
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Kinetic multi-layer models (KM) successfully describe heterogeneous and multiphase atmospheric chemistry. In applications requiring repeated execution, however, these models can be too expensive. We trained machine learning surrogate models on output of the model KM-SUB and achieve high correlations. The surrogate models run orders of magnitudes faster, which suggests potential applicability in global optimization tasks and as sub-modules in large-scale atmospheric models.
Peter Bräuer and Matthias Tesche
Geosci. Model Dev., 15, 7557–7572, https://doi.org/10.5194/gmd-15-7557-2022, https://doi.org/10.5194/gmd-15-7557-2022, 2022
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This paper presents a tool for (i) finding temporally and spatially resolved intersections between two- or three-dimensional geographical tracks (trajectories) and (ii) extracting of data in the vicinity of intersections to achieve the optimal combination of various data sets.
Benjamin Zanger, Jia Chen, Man Sun, and Florian Dietrich
Geosci. Model Dev., 15, 7533–7556, https://doi.org/10.5194/gmd-15-7533-2022, https://doi.org/10.5194/gmd-15-7533-2022, 2022
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Gaussian priors (GPs) used in least squares inversion do not reflect the true distributions of greenhouse gas emissions well. A method that does not rely on GPs is sparse reconstruction (SR). We show that necessary conditions for SR are satisfied for cities and that the application of a wavelet transform can further enhance sparsity. We apply the theory of compressed sensing to SR. Our results show that SR needs fewer measurements and is superior for assessing unknown emitters compared to GPs.
Jonathan D. Labriola and Louis J. Wicker
EGUsphere, https://doi.org/10.5194/egusphere-2022-1033, https://doi.org/10.5194/egusphere-2022-1033, 2022
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Observing system simulation experiments (OSSEs) are simulated case studies used to understand how different assimilated weather observations impact forecast skill. This study introduces the methods used to create an OSSE for a tornadic quasi-linear convective system event. These steps provide an opportunity to simulate a realistic high-impact weather event and can be used to encourage a more diverse set of OSSEs.
Paul Konopka, Mengchu Tao, Marc von Hobe, Lars Hoffmann, Corinna Kloss, Fabrizio Ravegnani, C. Michael Volk, Valentin Lauther, Andreas Zahn, Peter Hoor, and Felix Ploeger
Geosci. Model Dev., 15, 7471–7487, https://doi.org/10.5194/gmd-15-7471-2022, https://doi.org/10.5194/gmd-15-7471-2022, 2022
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Pure trajectory-based transport models driven by meteorology derived from reanalysis products (ERA5) take into account only the resolved, advective part of transport. That means neither mixing processes nor unresolved subgrid-scale advective processes like convection are included. The Chemical Lagrangian Model of the Stratosphere (CLaMS) includes these processes. We show that isentropic mixing dominates unresolved transport. The second most important transport process is unresolved convection.
Forwood Wiser, Bryan Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-240, https://doi.org/10.5194/gmd-2022-240, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
We developed an automated method, AMORE, to simplify complex chemical mechanisms. We applied AMORE to the oxidation mechanism for isoprene, an abundant biogenic volatile organic compound. Using AMORE with minimal manual adjustments to the output, we created the AMORE-isoprene mechanism, with improved accuracy and similar size to other reduced isoprene mechanisms. AMORE-Isoprene improved the accuracy of EPA’s CMAQ model compared to observations.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Yongbo Zhou, Yubao Liu, Zhaoyang Huo, and Yang Li
Geosci. Model Dev., 15, 7397–7420, https://doi.org/10.5194/gmd-15-7397-2022, https://doi.org/10.5194/gmd-15-7397-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
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Short summary
Simulating the influence of the biosphere on atmospheric chemistry has traditionally been computationally intensive. We describe a surrogate canopy physics model parameterized using a statistical learning technique and specifically designed for use in large-scale chemical transport models. Our surrogate model reproduces a more detailed model to within 10 % without a large computational demand, improving the process representation of biosphere–atmosphere exchange.
Simulating the influence of the biosphere on atmospheric chemistry has traditionally been...
