Articles | Volume 9, issue 1
https://doi.org/10.5194/gmd-9-111-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-111-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
19 Jan 2016
Model description paper |
| 19 Jan 2016
Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods
Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC, USA
S. M. Kreidenweis
Department of Atmospheric Sciences, Colorado State University, Fort Collins, CO, USA
P. J. Ziemann
Department of Chemistry and Biochemistry, Colorado University, Boulder, CO, USA
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P. J. DeMott, A. J. Prenni, G. R. McMeeking, R. C. Sullivan, M. D. Petters, Y. Tobo, M. Niemand, O. Möhler, J. R. Snider, Z. Wang, and S. M. Kreidenweis
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J. D. Hader, T. P. Wright, and M. D. Petters
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M. D. Petters and S. M. Kreidenweis
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Kevin R. Barry, Thomas C. J. Hill, Sonia M. Kreidenweis, Paul J. DeMott, Yutaka Tobo, and Jessie M. Creamean
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The Arctic is changing rapidly, and we sought to better understand how their clouds may change in the future through quantifying the natural cloud seeding particles over a year and uncover what they are made of. We wanted to determine their likely sources through concurrent DNA sequencing of airborne bacteria and fungi and found a persistent mixture of local and longer-range sources at all times.
Paul J. DeMott, Jessica A. Mirrielees, Sarah Suda Petters, Daniel J. Cziczo, Markus D. Petters, Heinz G. Bingemer, Thomas C. J. Hill, Karl Froyd, Sarvesh Garimella, A. Gannet Hallar, Ezra J. T. Levin, Ian B. McCubbin, Anne E. Perring, Christopher N. Rapp, Thea Schiebel, Jann Schrod, Kaitlyn J. Suski, Daniel Weber, Martin J. Wolf, Maria Zawadowicz, Jake Zenker, Ottmar Möhler, and Sarah D. Brooks
Atmos. Meas. Tech., 18, 639–672, https://doi.org/10.5194/amt-18-639-2025, https://doi.org/10.5194/amt-18-639-2025, 2025
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The Fifth International Ice Nucleation Workshop Phase 3 (FIN-03) compared the ambient atmospheric performance of ice-nucleating particle (INP) measuring systems and explored general methods for discerning atmospheric INP compositions. Mirroring laboratory results, INP concentrations agreed within 5–10 factors. Measurements of total aerosol properties and investigations of INP compositions supported a dominant role of soil and plant organic aerosol elements as INPs during the study.
Tommaso Galeazzo, Bernard Aumont, Marie Camredon, Richard Valorso, Yong B. Lim, Paul J. Ziemann, and Manabu Shiraiwa
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Melinda K. Schueneman, Douglas A. Day, Dongwook Kim, Pedro Campuzano-Jost, Seonsik Yun, Marla P. DeVault, Anna C. Ziola, Paul J. Ziemann, and Jose L. Jimenez
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Melissa A. Morris, Demetrios Pagonis, Douglas A. Day, Joost A. de Gouw, Paul J. Ziemann, and Jose L. Jimenez
Atmos. Meas. Tech., 17, 1545–1559, https://doi.org/10.5194/amt-17-1545-2024, https://doi.org/10.5194/amt-17-1545-2024, 2024
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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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Markus D. Petters, Tyas Pujiastuti, Ajmal Rasheeda Satheesh, Sabin Kasparoglu, Bethany Sutherland, and Nicholas Meskhidze
Atmos. Chem. Phys., 24, 745–762, https://doi.org/10.5194/acp-24-745-2024, https://doi.org/10.5194/acp-24-745-2024, 2024
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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.
Sabin Kasparoglu, Mohammad Maksimul Islam, Nicholas Meskhidze, and Markus D. Petters
Atmos. Meas. Tech., 15, 5007–5018, https://doi.org/10.5194/amt-15-5007-2022, https://doi.org/10.5194/amt-15-5007-2022, 2022
Short summary
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A modified version of a Handix Scientific printed optical particle spectrometer is introduced. The paper presents characterization experiments, including concentration, size, and time responses. Integration of an external multichannel analyzer card removes counting limitations of the original instrument. It is shown that the high-resolution light-scattering amplitude data can be used to sense particle-phase transitions.
Russell J. Perkins, Peter J. Marinescu, Ezra J. T. Levin, Don R. Collins, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 22, 6197–6215, https://doi.org/10.5194/acp-22-6197-2022, https://doi.org/10.5194/acp-22-6197-2022, 2022
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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.
Markus D. Petters
Atmos. Meas. Tech., 14, 7909–7928, https://doi.org/10.5194/amt-14-7909-2021, https://doi.org/10.5194/amt-14-7909-2021, 2021
Short summary
Short summary
Inverse methods infer physical properties from a measured instrument response. Measurement noise often interferes with the inversion. This work presents a general, domain-independent, accessible, and computationally efficient software implementation of a common class of statistical inversion methods. In addition, a new method to invert data from humidified tandem differential mobility analyzers is introduced. Results show that the approach is suitable for inversion of large-scale datasets.
Anna L. Hodshire, Emily Ramnarine, Ali Akherati, Matthew L. Alvarado, Delphine K. Farmer, Shantanu H. Jathar, Sonia M. Kreidenweis, Chantelle R. Lonsdale, Timothy B. Onasch, Stephen R. Springston, Jian Wang, Yang Wang, Lawrence I. Kleinman, Arthur J. Sedlacek III, and Jeffrey R. Pierce
Atmos. Chem. Phys., 21, 6839–6855, https://doi.org/10.5194/acp-21-6839-2021, https://doi.org/10.5194/acp-21-6839-2021, 2021
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Biomass burning emits particles and vapors that can impact both health and climate. Here, we investigate the role of dilution in the evolution of aerosol size and composition in observed US wildfire smoke plumes. Centers of plumes dilute more slowly than edges. We see differences in concentrations and composition between the centers and edges both in the first measurement and in subsequent measurements. Our findings support the hypothesis that plume dilution influences smoke aging.
Sabin Kasparoglu, Ying Li, Manabu Shiraiwa, and Markus D. Petters
Atmos. Chem. Phys., 21, 1127–1141, https://doi.org/10.5194/acp-21-1127-2021, https://doi.org/10.5194/acp-21-1127-2021, 2021
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Viscosity is important because it determines the lifetime, impact, and fate of particulate matter. We collected new data to rigorously test a framework that is used to constrain the phase state in global simulations. We find that the framework is accurate as long as appropriate compound specific inputs are available.
Megan S. Claflin, Demetrios Pagonis, Zachary Finewax, Anne V. Handschy, Douglas A. Day, Wyatt L. Brown, John T. Jayne, Douglas R. Worsnop, Jose L. Jimenez, Paul J. Ziemann, Joost de Gouw, and Brian M. Lerner
Atmos. Meas. Tech., 14, 133–152, https://doi.org/10.5194/amt-14-133-2021, https://doi.org/10.5194/amt-14-133-2021, 2021
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We have developed a field-deployable gas chromatograph with thermal desorption preconcentration and detector switching between two high-resolution mass spectrometers for in situ measurements of volatile organic compounds (VOCs). This system combines chromatography with both proton transfer and electron ionization to offer fast time response and continuous molecular speciation. This technique was applied during the 2018 ATHLETIC campaign to characterize VOC emissions in an indoor environment.
Steven Albers, Stephen M. Saleeby, Sonia Kreidenweis, Qijing Bian, Peng Xian, Zoltan Toth, Ravan Ahmadov, Eric James, and Steven D. Miller
Atmos. Meas. Tech., 13, 3235–3261, https://doi.org/10.5194/amt-13-3235-2020, https://doi.org/10.5194/amt-13-3235-2020, 2020
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A fast 3D visible-light forward operator is used to realistically visualize, validate, and potentially assimilate ground- and space-based camera and satellite imagery with NWP models. Three-dimensional fields of hydrometeors, aerosols, and 2D land surface variables are considered in the generation of radiance fields and RGB imagery from a variety of vantage points.
Peter J. Marinescu, Ezra J. T. Levin, Don Collins, Sonia M. Kreidenweis, and Susan C. van den Heever
Atmos. Chem. Phys., 19, 11985–12006, https://doi.org/10.5194/acp-19-11985-2019, https://doi.org/10.5194/acp-19-11985-2019, 2019
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We characterized and provided fits for the seasonal aerosol size distributions (7 nm–14 µm diameter) at a North American, long–term surface site (SGP), which can be applied to models. Key cycles on timescales of several hours to weeks were also assessed using power spectra for various aerosol size ranges. One key finding is the consistent presence of diurnal cycles in the smallest particles in each season, providing insights into the formation and roles of new particle formation at SGP.
Steven D. Miller, Louie D. Grasso, Qijing Bian, Sonia M. Kreidenweis, Jack F. Dostalek, Jeremy E. Solbrig, Jennifer Bukowski, Susan C. van den Heever, Yi Wang, Xiaoguang Xu, Jun Wang, Annette L. Walker, Ting-Chi Wu, Milija Zupanski, Christine Chiu, and Jeffrey S. Reid
Atmos. Meas. Tech., 12, 5101–5118, https://doi.org/10.5194/amt-12-5101-2019, https://doi.org/10.5194/amt-12-5101-2019, 2019
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Satellite–based detection of lofted mineral via infrared–window channels, well established in the literature, faces significant challenges in the presence of atmospheric moisture. Here, we consider a case featuring the juxtaposition of two dust plumes embedded within dry and moist air masses. The case is considered from the vantage points of numerical modeling, multi–sensor observations, and radiative transfer theory arriving at a new method for mitigating the water vapor masking effect.
Stephen M. Saleeby, Susan C. van den Heever, Jennie Bukowski, Annette L. Walker, Jeremy E. Solbrig, Samuel A. Atwood, Qijing Bian, Sonia M. Kreidenweis, Yi Wang, Jun Wang, and Steven D. Miller
Atmos. Chem. Phys., 19, 10279–10301, https://doi.org/10.5194/acp-19-10279-2019, https://doi.org/10.5194/acp-19-10279-2019, 2019
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This study seeks to understand how intense dust storms impact the heating and cooling of the land surface and atmosphere. Dust storms that are intense enough to substantially impact visibility can also alter how much sunlight reaches the surface during the day and how much heat is trapped in the atmosphere at night. These radiation changes can impact the temperature of the atmosphere and impact the weather in the vicinity.
Benjamin L. Deming, Demetrios Pagonis, Xiaoxi Liu, Douglas A. Day, Ranajit Talukdar, Jordan E. Krechmer, Joost A. de Gouw, Jose L. Jimenez, and Paul J. Ziemann
Atmos. Meas. Tech., 12, 3453–3461, https://doi.org/10.5194/amt-12-3453-2019, https://doi.org/10.5194/amt-12-3453-2019, 2019
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Losses or measurement delays of gas-phase compounds sampled through tubing are important to atmospheric science. Here we characterize 14 tubing materials by measuring the effects on step changes in organic compound concentration. We find that polymeric tubings exhibit absorptive partitioning behaviour while glass and metal tubings show adsorptive partitioning. Adsorptive materials impart complex humidity, concentration, and VOC–VOC interaction dependencies that absorptive tubings do not.
Xiaoxi Liu, Benjamin Deming, Demetrios Pagonis, Douglas A. Day, Brett B. Palm, Ranajit Talukdar, James M. Roberts, Patrick R. Veres, Jordan E. Krechmer, Joel A. Thornton, Joost A. de Gouw, Paul J. Ziemann, and Jose L. Jimenez
Atmos. Meas. Tech., 12, 3137–3149, https://doi.org/10.5194/amt-12-3137-2019, https://doi.org/10.5194/amt-12-3137-2019, 2019
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Delays or losses of gases in sampling tubing and instrumental surfaces due to surface interactions can lead to inaccurate quantification. By sampling with several chemical ionization mass spectrometers and six tubing materials, we quantify delays of semivolatile organic compounds and small polar gases. Delay times generally increase with decreasing volatility or increasing polarity and also depend on materials. The method and results will inform inlet material selection and instrumental design.
Samuel A. Atwood, Sonia M. Kreidenweis, Paul J. DeMott, Markus D. Petters, Gavin C. Cornwell, Andrew C. Martin, and Kathryn A. Moore
Atmos. Chem. Phys., 19, 6931–6947, https://doi.org/10.5194/acp-19-6931-2019, https://doi.org/10.5194/acp-19-6931-2019, 2019
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This paper presents measurements of aerosol particles at a coastal location. The particles were classified into distinct aerosol types using both microphysical measurements and meteorological information, allowing rapid changes between the aerosol types to be reliably identified. These particles can alter cloud and precipitation processes, and inclusion of the differences between types can improve atmospheric models and remote sensing retrievals in littoral zones.
Naruki Hiranuma, Kouji Adachi, David M. Bell, Franco Belosi, Hassan Beydoun, Bhaskar Bhaduri, Heinz Bingemer, Carsten Budke, Hans-Christian Clemen, Franz Conen, Kimberly M. Cory, Joachim Curtius, Paul J. DeMott, Oliver Eppers, Sarah Grawe, Susan Hartmann, Nadine Hoffmann, Kristina Höhler, Evelyn Jantsch, Alexei Kiselev, Thomas Koop, Gourihar Kulkarni, Amelie Mayer, Masataka Murakami, Benjamin J. Murray, Alessia Nicosia, Markus D. Petters, Matteo Piazza, Michael Polen, Naama Reicher, Yinon Rudich, Atsushi Saito, Gianni Santachiara, Thea Schiebel, Gregg P. Schill, Johannes Schneider, Lior Segev, Emiliano Stopelli, Ryan C. Sullivan, Kaitlyn Suski, Miklós Szakáll, Takuya Tajiri, Hans Taylor, Yutaka Tobo, Romy Ullrich, Daniel Weber, Heike Wex, Thomas F. Whale, Craig L. Whiteside, Katsuya Yamashita, Alla Zelenyuk, and Ottmar Möhler
Atmos. Chem. Phys., 19, 4823–4849, https://doi.org/10.5194/acp-19-4823-2019, https://doi.org/10.5194/acp-19-4823-2019, 2019
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A total of 20 ice nucleation measurement techniques contributed to investigate the immersion freezing behavior of cellulose particles – natural polymers. Our data showed several types of cellulose are able to nucleate ice as efficiently as some mineral dust samples and cellulose has the potential to be an important atmospheric ice-nucleating particle. Continued investigation/collaboration is necessary to obtain further insight into consistency or diversity of ice nucleation measurements.
Ankit Tandon, Nicholas E. Rothfuss, and Markus D. Petters
Atmos. Chem. Phys., 19, 3325–3339, https://doi.org/10.5194/acp-19-3325-2019, https://doi.org/10.5194/acp-19-3325-2019, 2019
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Organic compounds may form a barrier to condensation. Such barriers have been hypothesized to prevent water and other substances from mixing with salt cores. This will hinder the particles' ability to aid cloud formation of < 100 nm particles. Here we perform experiments encasing particles in plastic shells akin to water bottles. Against expectations, the plastic shell did not alter the droplet activation behavior of the encased particles. Water appears to readily permeate the plastic shell.
Yajuan Duan, Markus D. Petters, and Ana P. Barros
Atmos. Chem. Phys., 19, 1413–1437, https://doi.org/10.5194/acp-19-1413-2019, https://doi.org/10.5194/acp-19-1413-2019, 2019
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A new cloud parcel model that simulates entrainment, condensational growth, and collision–coalescence processes is presented and evaluated against airborne observations in complex terrain during IPHEx. Analysis of model simulations reveals that nonlinear interactions among turbulent dispersion, activation, and droplet growth processes modulate spectral width and explain the emergence of bimodal cloud drop spectra in aircraft measurements from different cloud regions and at different heights.
Jian Wang, John E. Shilling, Jiumeng Liu, Alla Zelenyuk, David M. Bell, Markus D. Petters, Ryan Thalman, Fan Mei, Rahul A. Zaveri, and Guangjie Zheng
Atmos. Chem. Phys., 19, 941–954, https://doi.org/10.5194/acp-19-941-2019, https://doi.org/10.5194/acp-19-941-2019, 2019
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Earlier studies showed organic hygroscopicity increases with oxidation level. Such increases have been attributed to higher water solubility for more oxidized organics. By systematically varying the water content of activating droplets, we show that for secondary organic aerosols, essentially all organics are dissolved at the point of droplet activation. Therefore, the organic hygroscopicity is not limited by solubility but is dictated mainly by the molecular weight of organic species.
Paul J. DeMott, Ottmar Möhler, Daniel J. Cziczo, Naruki Hiranuma, Markus D. Petters, Sarah S. Petters, Franco Belosi, Heinz G. Bingemer, Sarah D. Brooks, Carsten Budke, Monika Burkert-Kohn, Kristen N. Collier, Anja Danielczok, Oliver Eppers, Laura Felgitsch, Sarvesh Garimella, Hinrich Grothe, Paul Herenz, Thomas C. J. Hill, Kristina Höhler, Zamin A. Kanji, Alexei Kiselev, Thomas Koop, Thomas B. Kristensen, Konstantin Krüger, Gourihar Kulkarni, Ezra J. T. Levin, Benjamin J. Murray, Alessia Nicosia, Daniel O'Sullivan, Andreas Peckhaus, Michael J. Polen, Hannah C. Price, Naama Reicher, Daniel A. Rothenberg, Yinon Rudich, Gianni Santachiara, Thea Schiebel, Jann Schrod, Teresa M. Seifried, Frank Stratmann, Ryan C. Sullivan, Kaitlyn J. Suski, Miklós Szakáll, Hans P. Taylor, Romy Ullrich, Jesus Vergara-Temprado, Robert Wagner, Thomas F. Whale, Daniel Weber, André Welti, Theodore W. Wilson, Martin J. Wolf, and Jake Zenker
Atmos. Meas. Tech., 11, 6231–6257, https://doi.org/10.5194/amt-11-6231-2018, https://doi.org/10.5194/amt-11-6231-2018, 2018
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The ability to measure ice nucleating particles is vital to quantifying their role in affecting clouds and precipitation. Methods for measuring droplet freezing were compared while co-sampling relevant particle types. Measurement correspondence was very good for ice nucleating particles of bacterial and natural soil origin, and somewhat more disparate for those of mineral origin. Results reflect recently improved capabilities and provide direction toward addressing remaining measurement issues.
Kaitlyn J. Suski, Tom C. J. Hill, Ezra J. T. Levin, Anna Miller, Paul J. DeMott, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 18, 13755–13771, https://doi.org/10.5194/acp-18-13755-2018, https://doi.org/10.5194/acp-18-13755-2018, 2018
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The harvesting of crops emits large amounts of particles into the air. These particles can form and interact with clouds to alter cloud properties and precipitation, but the magnitude of these effects is unknown. This study looked at the ability of harvest particles to form ice in clouds by sampling with an ice nucleation chamber downwind of fields being harvested. Some crops emitted large amounts of ice-nucleating particles, and harvest emissions are mixtures of organics, soil, and minerals.
Gregory P. Schill, Paul J. DeMott, Ezra J. T. Levin, and Sonia M. Kreidenweis
Atmos. Meas. Tech., 11, 3007–3020, https://doi.org/10.5194/amt-11-3007-2018, https://doi.org/10.5194/amt-11-3007-2018, 2018
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Few techniques can measure the contribution of refractory black carbon (rBC) to ice-nucleating particle (INP) concentrations. One technique uses the single particle soot photometer (SP2) as a pre-filter to an online INP counter to selectively remove rBC particles from an aerosol stream. In this work, we expand upon this technique by determining the effect of the SP2 laser on INP proxies mixed with rBC. We also bounded the SP2 conditions under which rBC is fully vaporized in the SP2 exhaust.
Qijing Bian, Badr Alharbi, Mohammed M. Shareef, Tahir Husain, Mohammad J. Pasha, Samuel A. Atwood, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 18, 3969–3985, https://doi.org/10.5194/acp-18-3969-2018, https://doi.org/10.5194/acp-18-3969-2018, 2018
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We report long-term and spatially resolved hourly measurements of organic carbon (OC) and elemental carbon (EC) concentrations in ambient particulate matter in Riyadh, Saudi Arabia. Our analysis suggests both local vehicular emissions and regional sources (e.g., oil extraction and refining) were strong influences. Our work informs the development of pollution control strategies for Riyadh.
Demetrios Pagonis, Jordan E. Krechmer, Joost de Gouw, Jose L. Jimenez, and Paul J. Ziemann
Atmos. Meas. Tech., 10, 4687–4696, https://doi.org/10.5194/amt-10-4687-2017, https://doi.org/10.5194/amt-10-4687-2017, 2017
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Laboratory studies were conducted to investigate gas-wall partitioning of atmospheric organic compounds in Teflon tubing and inside an instrument used to monitor concentrations. Rapid partitioning caused time delays in instrument response that vary with tubing length and diameter, flow rate, and compound volatility. Tubing delay times of seconds to hours were described using a model that also included effects of instrument surfaces. The results can enable better design of air sampling systems.
Paul J. DeMott, Thomas C. J. Hill, Markus D. Petters, Allan K. Bertram, Yutaka Tobo, Ryan H. Mason, Kaitlyn J. Suski, Christina S. McCluskey, Ezra J. T. Levin, Gregory P. Schill, Yvonne Boose, Anne Marie Rauker, Anna J. Miller, Jake Zaragoza, Katherine Rocci, Nicholas E. Rothfuss, Hans P. Taylor, John D. Hader, Cedric Chou, J. Alex Huffman, Ulrich Pöschl, Anthony J. Prenni, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 17, 11227–11245, https://doi.org/10.5194/acp-17-11227-2017, https://doi.org/10.5194/acp-17-11227-2017, 2017
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The consistency and complementarity of different methods for measuring the numbers of particles capable of forming ice in clouds are examined in the atmosphere. Four methods for collecting particles for later (offline) freezing studies are compared to a common instantaneous method. Results support very good agreement in many cases but also biases that require further research. Present capabilities and uncertainties for obtaining global data on these climate-relevant aerosols are thus defined.
Yajuan Duan, Markus D. Petters, and Ana P. Barros
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-396, https://doi.org/10.5194/acp-2017-396, 2017
Revised manuscript not accepted
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To investigate aerosol-cloud interactions in cumulus development, a new cloud parcel model is developed to predict the vertical structure of cloud formation at early stages and evaluated against airborne observations during the Integrated Precipitation and Hydrology Experiment over the Southern Appalachian Mountains. The findings provide new insights into determinant factors of mid-day cumulus congestus formation that can explain a large fraction of warm season rainfall in mountainous regions.
Qijing Bian, Shantanu H. Jathar, John K. Kodros, Kelley C. Barsanti, Lindsay E. Hatch, Andrew A. May, Sonia M. Kreidenweis, and Jeffrey R. Pierce
Atmos. Chem. Phys., 17, 5459–5475, https://doi.org/10.5194/acp-17-5459-2017, https://doi.org/10.5194/acp-17-5459-2017, 2017
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In this paper, we perform simulations of the evolution of biomass-burning organic aerosol in laboratory smog-chamber experiments and ambient plumes. We find that in smog-chamber experiments, vapor wall losses lead to a large reduction in the apparent secondary organic aerosol formation. In ambient plumes, fire size and meteorology regulate the plume dilution rate, primary organic aerosol evaporation rate, and secondary organic aerosol formation rate.
Andrew C. Martin, Gavin C. Cornwell, Samuel A. Atwood, Kathryn A. Moore, Nicholas E. Rothfuss, Hans Taylor, Paul J. DeMott, Sonia M. Kreidenweis, Markus D. Petters, and Kimberly A. Prather
Atmos. Chem. Phys., 17, 1491–1509, https://doi.org/10.5194/acp-17-1491-2017, https://doi.org/10.5194/acp-17-1491-2017, 2017
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Anthropogenic influence on air quality, aerosol properties, and cloud activity was observed at Bodega Bay, CA, during periods when air from California's interior was transported to the coast. The sudden change in aerosol properties can impact atmospheric radiative balance and cloud formation in ways that must be accounted for in regional climate simulations.
Samuel A. Atwood, Jeffrey S. Reid, Sonia M. Kreidenweis, Donald R. Blake, Haflidi H. Jonsson, Nofel D. Lagrosas, Peng Xian, Elizabeth A. Reid, Walter R. Sessions, and James B. Simpas
Atmos. Chem. Phys., 17, 1105–1123, https://doi.org/10.5194/acp-17-1105-2017, https://doi.org/10.5194/acp-17-1105-2017, 2017
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Aerosol particles were measured by ship in remote marine regions of the South China Sea as part of the 2012 7 Southeast Asian Studies (7SEAS) experiments. As the particle populations changed throughout the experiment, the distribution of particle sizes and the amount of water that collected on them changed as well. These changes were associated with various impacts from smoke, sea salt, and pollution sources, and impact how clouds form and precipitation occurs in the region.
Jeffrey S. Reid, Peng Xian, Brent N. Holben, Edward J. Hyer, Elizabeth A. Reid, Santo V. Salinas, Jianglong Zhang, James R. Campbell, Boon Ning Chew, Robert E. Holz, Arunas P. Kuciauskas, Nofel Lagrosas, Derek J. Posselt, Charles R. Sampson, Annette L. Walker, E. Judd Welton, and Chidong Zhang
Atmos. Chem. Phys., 16, 14041–14056, https://doi.org/10.5194/acp-16-14041-2016, https://doi.org/10.5194/acp-16-14041-2016, 2016
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This paper describes aspects of the 2012 7 Southeast Asian Studies (7SEAS) operations period, the largest within the Maritime Continent. Included were an enhanced deployment of Aerosol Robotic Network (AERONET) sun photometers, multiple lidars, and a Singapore supersite. Simultaneously, a ship was dispatched to the Palawan Archipelago and Sulu Sea of the Philippines for September 2012 to observe transported smoke and pollution as it entered the southwest monsoon trough.
Jeffrey S. Reid, Nofel D. Lagrosas, Haflidi H. Jonsson, Elizabeth A. Reid, Samuel A. Atwood, Thomas J. Boyd, Virendra P. Ghate, Peng Xian, Derek J. Posselt, James B. Simpas, Sherdon N. Uy, Kimo Zaiger, Donald R. Blake, Anthony Bucholtz, James R. Campbell, Boon Ning Chew, Steven S. Cliff, Brent N. Holben, Robert E. Holz, Edward J. Hyer, Sonia M. Kreidenweis, Arunas P. Kuciauskas, Simone Lolli, Min Oo, Kevin D. Perry, Santo V. Salinas, Walter R. Sessions, Alexander Smirnov, Annette L. Walker, Qing Wang, Liya Yu, Jianglong Zhang, and Yongjing Zhao
Atmos. Chem. Phys., 16, 14057–14078, https://doi.org/10.5194/acp-16-14057-2016, https://doi.org/10.5194/acp-16-14057-2016, 2016
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This paper describes aspects of the 2012 7 Southeast Asian Studies (7SEAS) operations period, the largest within the Maritime Continent. Included were an enhanced deployment of Aerosol Robotic Network (AERONET) sun photometers, multiple lidars, and a Singapore supersite. Simultaneously, a ship was dispatched to the Palawan Archipelago and Sulu Sea of the Philippines for September 2012 to observe transported smoke and pollution as it entered the southwest monsoon trough.
Tom C. J. Hill, Paul J. DeMott, Yutaka Tobo, Janine Fröhlich-Nowoisky, Bruce F. Moffett, Gary D. Franc, and Sonia M. Kreidenweis
Atmos. Chem. Phys., 16, 7195–7211, https://doi.org/10.5194/acp-16-7195-2016, https://doi.org/10.5194/acp-16-7195-2016, 2016
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Even though aerosols that trigger the freezing of cloud droplets are rare, they can modify cloud properties and seed precipitation. While soil organic matter is a rich source of ice nucleating particles (INPs), we know little about them. The most active INPs (freeze supercooled water > −12 °C) in Wyoming and Colorado soils were organic, sensitive to heat (105 °C), and possibly fungal proteins in several soils, but they were not known species of ice nucleating bacteria. Many may also be carbohydrates.
Y. S. La, M. Camredon, P. J. Ziemann, R. Valorso, A. Matsunaga, V. Lannuque, J. Lee-Taylor, A. Hodzic, S. Madronich, and B. Aumont
Atmos. Chem. Phys., 16, 1417–1431, https://doi.org/10.5194/acp-16-1417-2016, https://doi.org/10.5194/acp-16-1417-2016, 2016
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The potential impact of chamber walls on the loss of gaseous organic species and secondary organic aerosol (SOA) formation has been explored using the GECKO-A modeling tool, which explicitly represents SOA formation and gas-wall partitioning. The model was compared with 41 smog chamber experiments of SOA formation under OH oxidation of alkane and alkene serie. The organic vapor loss to the chamber walls is found to affect SOA yields as well as the composition of the gas and the particle phase.
Q. Bian, A. A. May, S. M. Kreidenweis, and J. R. Pierce
Atmos. Chem. Phys., 15, 11027–11045, https://doi.org/10.5194/acp-15-11027-2015, https://doi.org/10.5194/acp-15-11027-2015, 2015
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Losses of semi-volatile vapors to Teflon walls may contribute to significant primary particle evaporation during wood-smoke aerosol experiments. These vapor losses may also affect secondary organic aerosol formation during these experiments.
A. A. May, T. Lee, G. R. McMeeking, S. Akagi, A. P. Sullivan, S. Urbanski, R. J. Yokelson, and S. M. Kreidenweis
Atmos. Chem. Phys., 15, 6323–6335, https://doi.org/10.5194/acp-15-6323-2015, https://doi.org/10.5194/acp-15-6323-2015, 2015
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Smoke plumes from some prescribed fires in the southeastern United States were sampled via aircraft to observe changes in organic aerosol (OA) with atmospheric transport. These plumes underwent rapid mixing, and, hence, substantial dilution with background air occurred. Dilution-driven evaporation appears to be the primary driver of OA transformations within the sampled plumes rather than photochemistry.
N. Hiranuma, S. Augustin-Bauditz, H. Bingemer, C. Budke, J. Curtius, A. Danielczok, K. Diehl, K. Dreischmeier, M. Ebert, F. Frank, N. Hoffmann, K. Kandler, A. Kiselev, T. Koop, T. Leisner, O. Möhler, B. Nillius, A. Peckhaus, D. Rose, S. Weinbruch, H. Wex, Y. Boose, P. J. DeMott, J. D. Hader, T. C. J. Hill, Z. A. Kanji, G. Kulkarni, E. J. T. Levin, C. S. McCluskey, M. Murakami, B. J. Murray, D. Niedermeier, M. D. Petters, D. O'Sullivan, A. Saito, G. P. Schill, T. Tajiri, M. A. Tolbert, A. Welti, T. F. Whale, T. P. Wright, and K. Yamashita
Atmos. Chem. Phys., 15, 2489–2518, https://doi.org/10.5194/acp-15-2489-2015, https://doi.org/10.5194/acp-15-2489-2015, 2015
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Seventeen ice nucleation measurement techniques contributed to investigate the immersion freezing behavior of illite NX. All data showed a similar temperature trend, but the measured ice nucleation activity was on average smaller for the wet suspended samples and higher for the dry-dispersed aerosol samples at high temperatures. A continued investigation and collaboration is necessary to obtain further insights into consistency or diversity of ice nucleation measurements.
M. I. Schurman, T. Lee, Y. Sun, B. A. Schichtel, S. M. Kreidenweis, and J. L. Collett Jr.
Atmos. Chem. Phys., 15, 737–752, https://doi.org/10.5194/acp-15-737-2015, https://doi.org/10.5194/acp-15-737-2015, 2015
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Atmospheric particles can contribute to environmental degradation. An aerosol mass spectrometer was used with positive matrix factorization to explore submicron particle sources in Rocky Mountain National Park, finding that ammonium (3.9%), nitrate (4.3%), sulfate (16.6%), and two types of oxidized organic aerosol (66.9% total) are transported on upslope winds from the urban Front Range, while local campfires contribute 8.4% of mass.
P. J. DeMott, A. J. Prenni, G. R. McMeeking, R. C. Sullivan, M. D. Petters, Y. Tobo, M. Niemand, O. Möhler, J. R. Snider, Z. Wang, and S. M. Kreidenweis
Atmos. Chem. Phys., 15, 393–409, https://doi.org/10.5194/acp-15-393-2015, https://doi.org/10.5194/acp-15-393-2015, 2015
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Laboratory and field data are used together to develop an empirical relation between the concentrations of mineral dust particles at sizes above 0.5 microns, approximated as a single compositional type, and ice nucleating particle concentrations measured versus temperature. This should be useful in global modeling of ice cloud formation. The utility of laboratory data for parameterization development is reinforced, and the need for careful interpretation of ice nucleation data is emphasized.
T. K. V. Nguyen, M. D. Petters, S. R. Suda, H. Guo, R. J. Weber, and A. G. Carlton
Atmos. Chem. Phys., 14, 10911–10930, https://doi.org/10.5194/acp-14-10911-2014, https://doi.org/10.5194/acp-14-10911-2014, 2014
A. P. Sullivan, A. A. May, T. Lee, G. R. McMeeking, S. M. Kreidenweis, S. K. Akagi, R. J. Yokelson, S. P. Urbanski, and J. L. Collett Jr.
Atmos. Chem. Phys., 14, 10535–10545, https://doi.org/10.5194/acp-14-10535-2014, https://doi.org/10.5194/acp-14-10535-2014, 2014
C. E. Stockwell, R. J. Yokelson, S. M. Kreidenweis, A. L. Robinson, P. J. DeMott, R. C. Sullivan, J. Reardon, K. C. Ryan, D. W. T. Griffith, and L. Stevens
Atmos. Chem. Phys., 14, 9727–9754, https://doi.org/10.5194/acp-14-9727-2014, https://doi.org/10.5194/acp-14-9727-2014, 2014
Y. Tobo, P. J. DeMott, T. C. J. Hill, A. J. Prenni, N. G. Swoboda-Colberg, G. D. Franc, and S. M. Kreidenweis
Atmos. Chem. Phys., 14, 8521–8531, https://doi.org/10.5194/acp-14-8521-2014, https://doi.org/10.5194/acp-14-8521-2014, 2014
S. Nakao, S. R. Suda, M. Camp, M. D. Petters, and S. M. Kreidenweis
Atmos. Meas. Tech., 7, 2227–2241, https://doi.org/10.5194/amt-7-2227-2014, https://doi.org/10.5194/amt-7-2227-2014, 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
J. D. Hader, T. P. Wright, and M. D. Petters
Atmos. Chem. Phys., 14, 5433–5449, https://doi.org/10.5194/acp-14-5433-2014, https://doi.org/10.5194/acp-14-5433-2014, 2014
E. J. T. Levin, A. J. Prenni, B. B. Palm, D. A. Day, P. Campuzano-Jost, P. M. Winkler, S. M. Kreidenweis, P. J. DeMott, J. L. Jimenez, and J. N. Smith
Atmos. Chem. Phys., 14, 2657–2667, https://doi.org/10.5194/acp-14-2657-2014, https://doi.org/10.5194/acp-14-2657-2014, 2014
C. L. Loza, J. S. Craven, L. D. Yee, M. M. Coggon, R. H. Schwantes, M. Shiraiwa, X. Zhang, K. A. Schilling, N. L. Ng, M. R. Canagaratna, P. J. Ziemann, R. C. Flagan, and J. H. Seinfeld
Atmos. Chem. Phys., 14, 1423–1439, https://doi.org/10.5194/acp-14-1423-2014, https://doi.org/10.5194/acp-14-1423-2014, 2014
L. D. Yee, J. S. Craven, C. L. Loza, K. A. Schilling, N. L. Ng, M. R. Canagaratna, P. J. Ziemann, R. C. Flagan, and J. H. Seinfeld
Atmos. Chem. Phys., 13, 11121–11140, https://doi.org/10.5194/acp-13-11121-2013, https://doi.org/10.5194/acp-13-11121-2013, 2013
J. A. Huffman, A. J. Prenni, P. J. DeMott, C. Pöhlker, R. H. Mason, N. H. Robinson, J. Fröhlich-Nowoisky, Y. Tobo, V. R. Després, E. Garcia, D. J. Gochis, E. Harris, I. Müller-Germann, C. Ruzene, B. Schmer, B. Sinha, D. A. Day, M. O. Andreae, J. L. Jimenez, M. Gallagher, S. M. Kreidenweis, A. K. Bertram, and U. Pöschl
Atmos. Chem. Phys., 13, 6151–6164, https://doi.org/10.5194/acp-13-6151-2013, https://doi.org/10.5194/acp-13-6151-2013, 2013
S. K. Akagi, R. J. Yokelson, I. R. Burling, S. Meinardi, I. Simpson, D. R. Blake, G. R. McMeeking, A. Sullivan, T. Lee, S. Kreidenweis, S. Urbanski, J. Reardon, D. W. T. Griffith, T. J. Johnson, and D. R. Weise
Atmos. Chem. Phys., 13, 1141–1165, https://doi.org/10.5194/acp-13-1141-2013, https://doi.org/10.5194/acp-13-1141-2013, 2013
M. D. Petters and S. M. Kreidenweis
Atmos. Chem. Phys., 13, 1081–1091, https://doi.org/10.5194/acp-13-1081-2013, https://doi.org/10.5194/acp-13-1081-2013, 2013
J. S. Craven, L. D. Yee, N. L. Ng, M. R. Canagaratna, C. L. Loza, K. A. Schilling, R. L. N. Yatavelli, J. A. Thornton, P. J. Ziemann, R. C. Flagan, and J. H. Seinfeld
Atmos. Chem. Phys., 12, 11795–11817, https://doi.org/10.5194/acp-12-11795-2012, https://doi.org/10.5194/acp-12-11795-2012, 2012
Related subject area
Atmospheric sciences
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
Atmospheric moisture tracking with WAM2layers v3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
EGUsphere, https://doi.org/10.5194/egusphere-2024-3401, https://doi.org/10.5194/egusphere-2024-3401, 2024
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We introduce a new version of WAM2layers, a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data became a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent and reliable, and easier to maintain.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
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Short summary
Organic particles suspended in air serve as nucleation seeds for droplets in atmospheric clouds. Over time their chemical composition changes towards more functionalized compounds. This work presents a model that can predict an organic compounds' ability promote the nucleation of cloud drops from its functional group composition. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote droplet nucleation. Methylene and nitrate moieties inhibit droplet nucleation.
Organic particles suspended in air serve as nucleation seeds for droplets in atmospheric clouds....
