Articles | Volume 22, issue 9
https://doi.org/10.5194/acp-22-6197-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-6197-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 May 2022
Research article |
| 11 May 2022
| 11 May 2022
Long- and short-term temporal variability in cloud condensation nuclei spectra over a wide supersaturation range in the Southern Great Plains site
Russell J. Perkins
CORRESPONDING AUTHOR
Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
Peter J. Marinescu
Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, USA
Ezra J. T. Levin
Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
Handix Scientific, Fort Collins, CO 80525, USA
Don R. Collins
Department of Chemical and Environmental Engineering, University of California Riverside, Riverside, CA 92521, USA
Sonia M. Kreidenweis
Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523, USA
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Aino Ovaska, Elio Rauth, Daniel Holmberg, Paulo Artaxo, John Backman, Benjamin Bergmans, Don Collins, Marco Aurélio Franco, Shahzad Gani, Roy M. Harrison, Rakesh K. Hooda, Tareq Hussein, Antti-Pekka Hyvärinen, Kerneels Jaars, Adam Kristensson, Markku Kulmala, Lauri Laakso, Ari Laaksonen, Nikolaos Mihalopoulos, Colin O'Dowd, Jakub Ondracek, Tuukka Petäjä, Kristina Plauškaitė, Mira Pöhlker, Ximeng Qi, Peter Tunved, Ville Vakkari, Alfred Wiedensohler, Kai Puolamäki, Tuomo Nieminen, Veli-Matti Kerminen, Victoria A. Sinclair, and Pauli Paasonen
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We trained machine learning models to estimate the number of aerosol particles large enough to form clouds and generated daily estimates for the entire globe. The models performed well in many continental regions but struggled in remote and marine areas. Still, this approach offers a way to quantify these particles in areas that lack direct measurements, helping us understand their influence on clouds and climate on a global scale.
Kevin R. Barry, Thomas C. J. Hill, Sonia M. Kreidenweis, Paul J. DeMott, Yutaka Tobo, and Jessie M. Creamean
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Ningjin Xu, Chen Le, David R. Cocker, Kunpeng Chen, Ying-Hsuan Lin, and Don R. Collins
Atmos. Meas. Tech., 17, 4227–4243, https://doi.org/10.5194/amt-17-4227-2024, https://doi.org/10.5194/amt-17-4227-2024, 2024
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A flow-through reactor was developed that exposes known mixtures of gases or ambient air to very high concentrations of the oxidants that are responsible for much of the chemistry that takes place in the atmosphere. Like other reactors of its type, it is primarily used to study the formation of particulate matter from the oxidation of common gases. Unlike other reactors of its type, it can simulate the chemical reactions that occur in liquid water that is present in particles or cloud droplets.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Zihan Zhu, Javier González-Rocha, Yifan Ding, Isis Frausto-Vicencio, Sajjan Heerah, Akula Venkatram, Manvendra Dubey, Don Collins, and Francesca M. Hopkins
Atmos. Meas. Tech., 17, 3883–3895, https://doi.org/10.5194/amt-17-3883-2024, https://doi.org/10.5194/amt-17-3883-2024, 2024
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Increases in agriculture, oil and gas, and waste management activities have contributed to the increase in atmospheric methane levels and resultant climate warming. In this paper, we explore the use of small uncrewed aircraft systems (sUASs) and AirCore technology to detect and quantify methane emissions. Results from field experiments demonstrate that sUASs and AirCore technology can be effective for detecting and quantifying methane emissions in near real time.
Ryan J. Patnaude, Kathryn A. Moore, Russell J. Perkins, Thomas C. J. Hill, Paul J. DeMott, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 24, 911–928, https://doi.org/10.5194/acp-24-911-2024, https://doi.org/10.5194/acp-24-911-2024, 2024
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In this study we examined the effect of atmospheric aging on sea spray aerosols (SSAs) to form ice and how newly formed secondary marine aerosols (SMAs) may freeze at cirrus temperatures (< −38 °C). Results show that SSAs freeze at different relative humidities (RHs) depending on the temperature and that the ice-nucleating ability of SSA was not hindered by atmospheric aging. SMAs are shown to freeze at high RHs and are likely inefficient at forming ice at cirrus temperatures.
Kevin R. Barry, Thomas C. J. Hill, Marina Nieto-Caballero, Thomas A. Douglas, Sonia M. Kreidenweis, Paul J. DeMott, and Jessie M. Creamean
Atmos. Chem. Phys., 23, 15783–15793, https://doi.org/10.5194/acp-23-15783-2023, https://doi.org/10.5194/acp-23-15783-2023, 2023
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Ice-nucleating particles (INPs) are important for the climate due to their influence on cloud properties. To understand potential land-based sources of them in the Arctic, we carried out a survey near the northernmost point of Alaska, a landscape connected to the permafrost (thermokarst). Permafrost contained high concentrations of INPs, with the largest values near the coast. The thermokarst lakes were found to emit INPs, and the water contained elevated concentrations.
Nicole A. June, Anna L. Hodshire, Elizabeth B. Wiggins, Edward L. Winstead, Claire E. Robinson, K. Lee Thornhill, Kevin J. Sanchez, Richard H. Moore, Demetrios Pagonis, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Matthew M. Coggon, Jonathan M. Dean-Day, T. Paul Bui, Jeff Peischl, Robert J. Yokelson, Matthew J. Alvarado, Sonia M. Kreidenweis, Shantanu H. Jathar, and Jeffrey R. Pierce
Atmos. Chem. Phys., 22, 12803–12825, https://doi.org/10.5194/acp-22-12803-2022, https://doi.org/10.5194/acp-22-12803-2022, 2022
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The evolution of organic aerosol composition and size is uncertain due to variability within and between smoke plumes. We examine the impact of plume concentration on smoke evolution from smoke plumes sampled by the NASA DC-8 during FIREX-AQ. We find that observed organic aerosol and size distribution changes are correlated to plume aerosol mass concentrations. Additionally, coagulation explains the majority of the observed growth.
Mariko Oue, Stephen M. Saleeby, Peter J. Marinescu, Pavlos Kollias, and Susan C. van den Heever
Atmos. Meas. Tech., 15, 4931–4950, https://doi.org/10.5194/amt-15-4931-2022, https://doi.org/10.5194/amt-15-4931-2022, 2022
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This study provides an optimization of radar observation strategies to better capture convective cell evolution in clean and polluted environments as well as a technique for the optimization. The suggested optimized radar observation strategy is to better capture updrafts at middle and upper altitudes and precipitation particle evolution of isolated deep convective clouds. This study sheds light on the challenge of designing remote sensing observation strategies in pre-field campaign periods.
Anna L. Hodshire, Ezra J. T. Levin, A. Gannet Hallar, Christopher N. Rapp, Dan R. Gilchrist, Ian McCubbin, and Gavin R. McMeeking
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-216, https://doi.org/10.5194/amt-2022-216, 2022
Publication in AMT not foreseen
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The new Continuous Flow Diffusion Chamber-Ice Activation Spectrometer collected 4 months of ice nucleating particle (INP) measurements at a 5-minute resolution at the mountainside Storm Peak Laboratory. Most long-term INP measurements are at a time resolution of a day or longer: our instrument is a promising advance towards high-resolution long-term INP measurements. We observe higher peak INP concentrations than previous mountain studies, possibly due to the higher time resolution of our data.
Lu Chen, Fang Zhang, Don Collins, Jingye Ren, Jieyao Liu, Sihui Jiang, and Zhanqing Li
Atmos. Chem. Phys., 22, 2293–2307, https://doi.org/10.5194/acp-22-2293-2022, https://doi.org/10.5194/acp-22-2293-2022, 2022
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Understanding the volatility and mixing state of atmospheric aerosols is important for elucidating their formation. Here, the size-resolved volatility of fine particles is characterized using field measurements. On average, the particles are more volatile in the summer. The retrieved mixing state shows that black carbon (BC)-containing particles dominate and contribute 67–77 % toward the total number concentration in the winter, while the non-BC particles accounted for 52–69 % in the summer.
Anna L. Hodshire, Ezra J. T. Levin, A. Gannet Hallar, Christopher N. Rapp, Dan R. Gilchrist, Ian McCubbin, and Gavin R. McMeeking
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-29, https://doi.org/10.5194/acp-2022-29, 2022
Preprint withdrawn
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The new Continuous Flow Diffusion Chamber-Ice Activation Spectrometer collected 4 months of ice nucleating particle (INP) measurements at a 5-minute resolution at the mountainside Storm Peak Laboratory. Most long-term INP measurements are at a time resolution of a day or longer: our instrument is a promising advance towards high-resolution long-term INP measurements. We observe higher peak INP concentrations than previous mountain studies, possibly due to the higher time resolution of our data.
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Short summary
We used 5 years (2009–2013) of aerosol and cloud condensation nuclei (CCN) data from a total of seven instruments housed at the Southern Great Plains site, which were merged into a quality-controlled, continuous dataset of CCN spectra at ~45 min resolution. The data cover all seasons, are representative of a rural, agricultural mid-continental site, and are useful for model initialization and validation. Our analysis of this dataset focuses on seasonal and hourly variability.
We used 5 years (2009–2013) of aerosol and cloud condensation nuclei (CCN) data from a total of...
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