Articles | Volume 26, issue 12
https://doi.org/10.5194/acp-26-8505-2026
© Author(s) 2026. 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-26-8505-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impacts of fire-induced heat, moisture, and aerosol-radiation interactions on wildfire plume rise during the 2019/2020 Australian fires
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Gholam Ali Hoshyaripour
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Bernhard Vogel
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Heike Vogel
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Corinna Hoose
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Related authors
Gholam Ali Hoshyaripour, Andreas Baer, Sascha Bierbauer, Julia Bruckert, Dominik Brunner, Jochen Förstner, Arash Hamzehloo, Valentin Hanft, Corina Keller, Martina Klose, Pankaj Kumar, Patrick Ludwig, Enrico Metzner, Lisa Muth, Andreas Pauling, Nikolas Porz, Maryam Ramezani Ziarani, Thomas Reddmann, Luca Reißig, Roland Ruhnke, Khompat Satitkovitchai, Axel Seifert, Miriam Sinnhuber, Michael Steiner, Stefan Versick, Heike Vogel, Michael Weimer, Sven Werchner, and Corinna Hoose
Geosci. Model Dev., 19, 1645–1681, https://doi.org/10.5194/gmd-19-1645-2026, https://doi.org/10.5194/gmd-19-1645-2026, 2026
Short summary
Short summary
This paper presents recent advances in ICON-ART, a modeling system that simulates atmospheric composition – such as gases and particles – and their interactions with weather and climate. By integrating updated chemistry, emissions, and aerosol processes, ICON-ART enables detailed, scale-spanning simulations. It supports both scientific research and operational forecasts, contributing to improved air quality, weather and climate predictions.
Lisa Janina Muth, Sascha Bierbauer, Corinna Hoose, Bernhard Vogel, Heike Vogel, and Gholam Ali Hoshyaripour
Atmos. Chem. Phys., 25, 16027–16040, https://doi.org/10.5194/acp-25-16027-2025, https://doi.org/10.5194/acp-25-16027-2025, 2025
Short summary
Short summary
In our study, we explore how intense wildfires create thunderstorm-like clouds that can affect weather and climate globally. Using simulations with high resolution, we found that fire heat and moisture help form these clouds, lifting particles high into the atmosphere. This process is crucial for understanding how fires affect the environment. Despite some differences from observational data, our findings match well over time, showing the importance of fire-induced heat in cloud formation.
Christian Barthlott, Beata Czajka, Christoph Gebhardt, and Corinna Hoose
Atmos. Chem. Phys., 26, 6061–6081, https://doi.org/10.5194/acp-26-6061-2026, https://doi.org/10.5194/acp-26-6061-2026, 2026
Short summary
Short summary
The study uses the ICOsahedral Non-hydrostatic (ICON) model to examine how microphysical uncertainties affect summertime convection in central Europe. A 108-member ensemble varying aerosol and cloud parameters showed strong differences in precipitation intensity and location but little impact on convection onset. Results highlight that cloud microphysics is a key source of forecast uncertainty in convective weather prediction.
Gabriella Wallentin, Luisa Ickes, Peggy Achtert, Matthias Tesche, and Corinna Hoose
Atmos. Chem. Phys., 26, 3069–3089, https://doi.org/10.5194/acp-26-3069-2026, https://doi.org/10.5194/acp-26-3069-2026, 2026
Short summary
Short summary
Multilayer clouds are cloud systems with two or more vertically stacked cloud layers. Using a weather prediction model, we simulate clouds in the Arctic during a month. The model is evaluated against observations collected during the ship campaign MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate). We find that multilayer clouds frequently occur in the region, in fact, they dominate the cloud occurrence. The study highlights the importance of representing these clouds in simulations over the Arctic.
Peggy Achtert, Torsten Seelig, Gabriella Wallentin, Luisa Ickes, Matthew D. Shupe, Corinna Hoose, and Matthias Tesche
Atmos. Chem. Phys., 26, 3049–3068, https://doi.org/10.5194/acp-26-3049-2026, https://doi.org/10.5194/acp-26-3049-2026, 2026
Short summary
Short summary
We quantify the occurrence of single- and multi-layer clouds in the Arctic based on combining soundings with cloud-radar observations. We also assess the rate of ice-crystal seeding in multi-layer cloud systems as this is an important initiator of glaciation in super-cooled liquid cloud layers. We find an abundance of multi-layer clouds in the Arctic with seeding in about half to two thirds of cases in which the gap between upper and lower layers ranges between 100 and 1000 m.
Gholam Ali Hoshyaripour, Andreas Baer, Sascha Bierbauer, Julia Bruckert, Dominik Brunner, Jochen Förstner, Arash Hamzehloo, Valentin Hanft, Corina Keller, Martina Klose, Pankaj Kumar, Patrick Ludwig, Enrico Metzner, Lisa Muth, Andreas Pauling, Nikolas Porz, Maryam Ramezani Ziarani, Thomas Reddmann, Luca Reißig, Roland Ruhnke, Khompat Satitkovitchai, Axel Seifert, Miriam Sinnhuber, Michael Steiner, Stefan Versick, Heike Vogel, Michael Weimer, Sven Werchner, and Corinna Hoose
Geosci. Model Dev., 19, 1645–1681, https://doi.org/10.5194/gmd-19-1645-2026, https://doi.org/10.5194/gmd-19-1645-2026, 2026
Short summary
Short summary
This paper presents recent advances in ICON-ART, a modeling system that simulates atmospheric composition – such as gases and particles – and their interactions with weather and climate. By integrating updated chemistry, emissions, and aerosol processes, ICON-ART enables detailed, scale-spanning simulations. It supports both scientific research and operational forecasts, contributing to improved air quality, weather and climate predictions.
Yichen Jia, Hendrik Andersen, David Neubauer, Ulrike Lohmann, Corinna Hoose, and Jan Cermak
EGUsphere, https://doi.org/10.5194/egusphere-2026-569, https://doi.org/10.5194/egusphere-2026-569, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Understanding how ocean clouds respond to air pollution is important for climate projections. Using artificial intelligence and a climate model, we show that some model settings produce very high cloud cover, leaving little room for further cloud growth as pollution increases. This “headroom effect” can make cloud responses appear weak. Our results highlight the need to consider existing cloud conditions when interpreting how cloud cover responds to the environment.
Hengheng Zhang, Gholam Ali Hoshyaripour, Heike Vogel, Frank Wagner, Thomas Leisner, Jochen Förstner, and Harald Saathoff
EGUsphere, https://doi.org/10.5194/egusphere-2025-5980, https://doi.org/10.5194/egusphere-2025-5980, 2026
Short summary
Short summary
We studied several major dust storms that traveled from the Sahara to Europe using ground-based light measurements, sunlight sensors, particle counters, and a modern weather and dust model. We reveal when the dust arrived, how it moved and mixed in the air, and why each event behaved differently. Our results help improve forecasts of dust episodes that influence air quality, visibility, and solar energy across Europe.
Deepak Waman, Julian Meusel, Behrooz Keshtgar, Gabriella Wallentin, Christian Barthlott, Sachin Patade, Sonali Shete, Thara Prabhakaran, Romain Fievet, Declan Finney, Alan Blyth, and Corinna Hoose
EGUsphere, https://doi.org/10.5194/egusphere-2025-6129, https://doi.org/10.5194/egusphere-2025-6129, 2026
Short summary
Short summary
We use a weather model with aircraft and satellite data to study ice multiplication in thunderstorms across India, Mexico, Oklahoma, and the Atlantic. This process can create spurious ice particles in clouds, thereby increasing latent and radiative heating that strengthens storms and extends cloud lifetimes. These results improve our understanding of how small-scale ice processes influence large-scale storm behavior and rainfall patterns.
Fatemeh Zarei, Julia Bruckert, Gholam Ali Hoshyaripour, and Corinna Hoose
EGUsphere, https://doi.org/10.5194/egusphere-2025-6082, https://doi.org/10.5194/egusphere-2025-6082, 2026
Short summary
Short summary
Volcanic eruptions are a rich source of aerosol particles, such as sulfate and ash, that can impact cloud droplet and ice crystal formation. They lead to strong local perturbations of clouds. In this study, these processes were simulated with a numerical model. In two contrasting case studies of an Icelandic and a Caribbean volcano, the perturbations to processes involving liquid droplets and ice crystals are investigated.
Sebastian Vergara-Palacio, Alexei Kiselev, Franziska Vogel, Adolfo González-Romero, Romy Fösig, Xavier Querol, Corinna Hoose, Ottmar Möhler, Konrad Kandler, Carlos Pérez García-Pando, and Martina Klose
EGUsphere, https://doi.org/10.5194/egusphere-2025-6240, https://doi.org/10.5194/egusphere-2025-6240, 2026
Short summary
Short summary
Atmospheric mineral dust can help clouds form ice, changing cloud properties and affecting weather and climate. We tested dust from Morocco and Iceland in more than 300 controlled laboratory experiments. Icelandic samples were up to 100 times less able to promote ice formation than Moroccan samples, and showed mineral-composition dependence. The results show the role of larger dust particles in ice nucleation and their relationship with mineralogy and size for low- and high-latitude sources.
Lina Lucas, Christian Barthlott, Corinna Hoose, and Peter Knippertz
Atmos. Chem. Phys., 25, 18527–18548, https://doi.org/10.5194/acp-25-18527-2025, https://doi.org/10.5194/acp-25-18527-2025, 2025
Short summary
Short summary
We studied how climate change and cleaner air could affect severe storms in Germany. Using high-resolution weather simulations of past supercell storms under warmer and less polluted conditions, we found that storms may become more intense, with heavier rainfall and larger hailstones. These changes suggest an increased risk of damage in the future. Our findings help improve understanding of how extreme storms may evolve in a changing climate.
Lisa Janina Muth, Sascha Bierbauer, Corinna Hoose, Bernhard Vogel, Heike Vogel, and Gholam Ali Hoshyaripour
Atmos. Chem. Phys., 25, 16027–16040, https://doi.org/10.5194/acp-25-16027-2025, https://doi.org/10.5194/acp-25-16027-2025, 2025
Short summary
Short summary
In our study, we explore how intense wildfires create thunderstorm-like clouds that can affect weather and climate globally. Using simulations with high resolution, we found that fire heat and moisture help form these clouds, lifting particles high into the atmosphere. This process is crucial for understanding how fires affect the environment. Despite some differences from observational data, our findings match well over time, showing the importance of fire-induced heat in cloud formation.
Marco Zanatta, Pia Bogert, Patrick Ginot, Yiwei Gong, Gholam Ali Hoshyaripour, Yaqiong Hu, Feng Jiang, Paolo Laj, Yanxia Li, Claudia Linke, Ottmar Möhler, Harald Saathoff, Martin Schnaiter, Nsikanabasi Silas Umo, Franziska Vogel, and Robert Wagner
Aerosol Research, 3, 477–502, https://doi.org/10.5194/ar-3-477-2025, https://doi.org/10.5194/ar-3-477-2025, 2025
Short summary
Short summary
Back carbon is an atmospheric pollutant from combustion and contributes to the Arctic warming. However, its properties change as it travels through the atmosphere, affecting its impact. We recreated Arctic transport conditions in a laboratory to study how black carbon evolves over time. Our findings show that temperature and altitude strongly influence its transformation, providing key insights for improving climate models and understanding Arctic pollution.
Julia Bruckert, Simran Chopra, Richard Siddans, Charlotte Wedler, and Gholam Ali Hoshyaripour
Atmos. Chem. Phys., 25, 9859–9884, https://doi.org/10.5194/acp-25-9859-2025, https://doi.org/10.5194/acp-25-9859-2025, 2025
Short summary
Short summary
The 2022 Hunga eruption emitted about 150 Tg of water vapor into the stratosphere. Here, we show that the water vapor injection not only accelerates SO2 oxidation and sulfate production but also increases the aging of ash (coating of ash by sulfate). Our study shows that aerosol aging alone does not explain the rapid loss of ash after the Hunga eruption as observed by satellite instruments. However, some ash might be masked in the observation due to the strong coating.
Gabriella Wallentin, Annika Oertel, Luisa Ickes, Peggy Achtert, Matthias Tesche, and Corinna Hoose
Atmos. Chem. Phys., 25, 6607–6631, https://doi.org/10.5194/acp-25-6607-2025, https://doi.org/10.5194/acp-25-6607-2025, 2025
Short summary
Short summary
Multilayer clouds are common in the Arctic but remain underrepresented. We use an atmospheric model to simulate multilayer cloud cases from the Arctic expedition MOSAiC 2019/2020. We find that it is complex to accurately model these cloud layers due to the lack of correct temperature profiles. The model also struggles to capture the observed cloud phase and the relative concentration of cloud droplets and cloud ice. We constrain our model to measured aerosols to mitigate this issue.
Hiram Abif Meza-Landero, Julia Bruckert, Ronny Petrick, Pascal Simon, Heike Vogel, Volker Matthias, Johannes Bieser, and Martin Ramacher
EGUsphere, https://doi.org/10.5194/egusphere-2025-2289, https://doi.org/10.5194/egusphere-2025-2289, 2025
Short summary
Short summary
To understand how persistent hazardous industrial chemicals travel through the air and are deposited back on Earth's surface, we created a new computer model that combines meteorology and chemistry in clouds and clean air. Using the most recent global emissions data, this model represents the trajectory and changes of these chemicals, matching patterns in many areas and overlooking others. The work seeks to improve global monitoring and modeling of hazardous chemicals.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
Short summary
Short summary
Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Barbara Dietel, Odran Sourdeval, and Corinna Hoose
Atmos. Chem. Phys., 24, 7359–7383, https://doi.org/10.5194/acp-24-7359-2024, https://doi.org/10.5194/acp-24-7359-2024, 2024
Short summary
Short summary
Uncertainty with respect to cloud phases over the Southern Ocean and Arctic marine regions leads to large uncertainties in the radiation budget of weather and climate models. This study investigates the phases of low-base and mid-base clouds using satellite-based remote sensing data. A comprehensive analysis of the correlation of cloud phase with various parameters, such as temperature, aerosols, sea ice, vertical and horizontal cloud extent, and cloud radiative effect, is presented.
Behrooz Keshtgar, Aiko Voigt, Bernhard Mayer, and Corinna Hoose
Atmos. Chem. Phys., 24, 4751–4769, https://doi.org/10.5194/acp-24-4751-2024, https://doi.org/10.5194/acp-24-4751-2024, 2024
Short summary
Short summary
Cloud-radiative heating (CRH) affects extratropical cyclones but is uncertain in weather and climate models. We provide a framework to quantify uncertainties in CRH within an extratropical cyclone due to four factors and show that the parameterization of ice optical properties contributes significantly to uncertainty in CRH. We also argue that ice optical properties, by affecting CRH on spatial scales of 100 km, are relevant for the large-scale dynamics of extratropical cyclones.
Hyunju Jung, Peter Knippertz, Yvonne Ruckstuhl, Robert Redl, Tijana Janjic, and Corinna Hoose
Weather Clim. Dynam., 4, 1111–1134, https://doi.org/10.5194/wcd-4-1111-2023, https://doi.org/10.5194/wcd-4-1111-2023, 2023
Short summary
Short summary
A narrow rainfall belt in the tropics is an important feature for large-scale circulations and the global water cycle. The accurate simulation of this rainfall feature has been a long-standing problem, with the reasons behind that unclear. We present a novel diagnostic tool that allows us to disentangle processes important for rainfall, which changes due to modifications in model. Using our diagnostic tool, one can potentially identify sources of uncertainty in weather and climate models.
Cunbo Han, Corinna Hoose, Martin Stengel, Quentin Coopman, and Andrew Barrett
Atmos. Chem. Phys., 23, 14077–14095, https://doi.org/10.5194/acp-23-14077-2023, https://doi.org/10.5194/acp-23-14077-2023, 2023
Short summary
Short summary
Cloud phase has been found to significantly impact cloud thermodynamics and Earth’s radiation budget, and various factors influence it. This study investigates the sensitivity of the cloud-phase distribution to the ice-nucleating particle concentration and thermodynamics. Multiple simulation experiments were performed using the ICON model at the convection-permitting resolution of 1.2 km. Simulation results were compared to two different retrieval products based on SEVIRI measurements.
Annika Oertel, Annette K. Miltenberger, Christian M. Grams, and Corinna Hoose
Atmos. Chem. Phys., 23, 8553–8581, https://doi.org/10.5194/acp-23-8553-2023, https://doi.org/10.5194/acp-23-8553-2023, 2023
Short summary
Short summary
Warm conveyor belts (WCBs) are cloud- and precipitation-producing airstreams in extratropical cyclones that are important for the large-scale flow and cloud radiative forcing. We analyze cloud formation processes during WCB ascent in a two-moment microphysics scheme. Quantification of individual diabatic heating rates shows the importance of condensation, vapor deposition, rain evaporation, melting, and cloud-top radiative cooling for total heating and WCB-related potential vorticity structure.
Axel Seifert, Vanessa Bachmann, Florian Filipitsch, Jochen Förstner, Christian M. Grams, Gholam Ali Hoshyaripour, Julian Quinting, Anika Rohde, Heike Vogel, Annette Wagner, and Bernhard Vogel
Atmos. Chem. Phys., 23, 6409–6430, https://doi.org/10.5194/acp-23-6409-2023, https://doi.org/10.5194/acp-23-6409-2023, 2023
Short summary
Short summary
We investigate how mineral dust can lead to the formation of cirrus clouds. Dusty cirrus clouds lead to a reduction in solar radiation at the surface and, hence, a reduced photovoltaic power generation. Current weather prediction systems are not able to predict this interaction between mineral dust and cirrus clouds. We have developed a new physical description of the formation of dusty cirrus clouds. Overall we can show a considerable improvement in the forecast quality of clouds and radiation.
Julia Thomas, Andrew Barrett, and Corinna Hoose
Atmos. Chem. Phys., 23, 1987–2002, https://doi.org/10.5194/acp-23-1987-2023, https://doi.org/10.5194/acp-23-1987-2023, 2023
Short summary
Short summary
We study the sensitivity of rain formation processes during a heavy-rainfall event over mountains to changes in temperature and pollution. Total rainfall increases by 2 % K−1, and a 6 % K−1 increase is found at the highest altitudes, caused by a mixed-phase seeder–feeder mechanism (frozen cloud particles melt and grow further as they fall through a liquid cloud layer). In a cleaner atmosphere this process is enhanced. Thus the risk of severe rainfall in mountains may increase in the future.
Behrooz Keshtgar, Aiko Voigt, Corinna Hoose, Michael Riemer, and Bernhard Mayer
Weather Clim. Dynam., 4, 115–132, https://doi.org/10.5194/wcd-4-115-2023, https://doi.org/10.5194/wcd-4-115-2023, 2023
Short summary
Short summary
Forecasting extratropical cyclones is challenging due to many physical factors influencing their behavior. One such factor is the impact of heating and cooling of the atmosphere by the interaction between clouds and radiation. In this study, we show that cloud-radiative heating (CRH) increases the intensity of an idealized cyclone and affects its predictability. We find that CRH affects the cyclone mostly via increasing latent heat release and subsequent changes in the synoptic circulation.
Ákos Horváth, James L. Carr, Dong L. Wu, Julia Bruckert, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 22, 12311–12330, https://doi.org/10.5194/acp-22-12311-2022, https://doi.org/10.5194/acp-22-12311-2022, 2022
Short summary
Short summary
We estimate plume heights for the April 2021 La Soufrière daytime eruptions using GOES-17 near-limb side views and GOES-16–MODIS stereo views. These geometric heights are then compared with brightness-temperature-based radiometric height estimates to characterize the biases of the latter. We also show that the side view method can be applied to infrared imagery and thus nighttime eruptions, albeit with larger uncertainty.
Natalia E. Chubarova, Heike Vogel, Elizaveta E. Androsova, Alexander A. Kirsanov, Olga B. Popovicheva, Bernhard Vogel, and Gdaliy S. Rivin
Atmos. Chem. Phys., 22, 10443–10466, https://doi.org/10.5194/acp-22-10443-2022, https://doi.org/10.5194/acp-22-10443-2022, 2022
Short summary
Short summary
Effects of urban aerosol pollution in Moscow were analyzed using the COSMO-ART chemical transport model and intensive measurement campaigns. We show that urban aerosol comprises about 15–20% of columnar aerosol content, consisting mainly of fine aerosol mode. The black carbon (BC) fraction is about 5 %, depending on particle dispersion intensity (IPD). The BC fraction low value explains weak absorbing properties of the Moscow atmosphere. IPD also defines the daily cycle of urban aerosol species.
Julia Bruckert, Gholam Ali Hoshyaripour, Ákos Horváth, Lukas O. Muser, Fred J. Prata, Corinna Hoose, and Bernhard Vogel
Atmos. Chem. Phys., 22, 3535–3552, https://doi.org/10.5194/acp-22-3535-2022, https://doi.org/10.5194/acp-22-3535-2022, 2022
Short summary
Short summary
Volcanic emissions endanger aviation and public health and also influence weather and climate. Forecasting the volcanic-plume dispersion is therefore a critical yet sophisticated task. Here, we show that explicit treatment of volcanic-plume dynamics and eruption source parameters significantly improves volcanic-plume dispersion forecasts. We further demonstrate the lofting of the SO2 due to a heating of volcanic particles by sunlight with major implications for volcanic aerosol research.
Ákos Horváth, James L. Carr, Olga A. Girina, Dong L. Wu, Alexey A. Bril, Alexey A. Mazurov, Dmitry V. Melnikov, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 21, 12189–12206, https://doi.org/10.5194/acp-21-12189-2021, https://doi.org/10.5194/acp-21-12189-2021, 2021
Short summary
Short summary
We give a detailed description of a new technique to estimate the height of volcanic eruption columns from near-limb geostationary imagery. Such oblique angle observations offer spectacular side views of eruption columns protruding from the Earth ellipsoid and thereby facilitate a height-by-angle estimation method. Due to its purely geometric nature, the new technique is unaffected by the limitations of traditional brightness-temperature-based height retrievals.
Ákos Horváth, Olga A. Girina, James L. Carr, Dong L. Wu, Alexey A. Bril, Alexey A. Mazurov, Dmitry V. Melnikov, Gholam Ali Hoshyaripour, and Stefan A. Buehler
Atmos. Chem. Phys., 21, 12207–12226, https://doi.org/10.5194/acp-21-12207-2021, https://doi.org/10.5194/acp-21-12207-2021, 2021
Short summary
Short summary
We demonstrate the side view plume height estimation technique described in Part 1 on seven volcanic eruptions from 2019 and 2020, including the 2019 Raikoke eruption. We explore the strengths and limitations of the new technique in comparison to height estimation from brightness temperatures, stereo observations, and ground-based video footage.
Hengheng Zhang, Frank Wagner, Harald Saathoff, Heike Vogel, Gholam Ali Hoshyaripour, Vanessa Bachmann, Jochen Förstner, and Thomas Leisner
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-193, https://doi.org/10.5194/amt-2021-193, 2021
Revised manuscript not accepted
Short summary
Short summary
The evolution and the properties of Saharan dust plume were characterized by LIDARs, a sun photometer, and a regional transport model. Comparison between LIDAR measurements, sun photometer and ICON-ART predictions shows a good agreement for dust arrival time, dust layer height, and dust structure but also that the model overestimates the backscatter coefficients by a factor of (2.2 ± 0.16) and underestimate aerosol optical depth by a factor of (1.5 ± 0.11).
Cited articles
Andela, N., Kaiser, J. W., van der Werf, G. R., and Wooster, M. J.: New fire diurnal cycle characterizations to improve fire radiative energy assessments made from MODIS observations, Atmos. Chem. Phys., 15, 8831–8846, https://doi.org/10.5194/acp-15-8831-2015, 2015. a
Andreae, M. O., Rosenfeld, D., Artaxo, P., Costa, A. A., Frank, G., Longo, K. M., and Silva-Dias, M. A. F. D.: Smoking rain clouds over the Amazon, Science, 303, 1337–1342, https://doi.org/10.1126/science.1092779, 2004. a
Beeler, P., Kumar, J., Schwarz, J. P., Adachi, K., Fierce, L., Perring, A. E., Katich, J. M., and Chakrabarty, R. K.: Light absorption enhancement of black carbon in a pyrocumulonimbus cloud, Nat. Commun., 15, 6243, https://doi.org/10.1038/s41467-024-50070-0, 2024. a
Bohren, C. F. and Huffman, D. R.: Absorption and scattering of light by small particles, John Wiley & Sons, ISBN 978-3-527-61816-3, 2008. a
Bond, T. C. and Bergstrom, R. W.: Light Absorption by Carbonaceous Particles: An Investigative Review, Aerosol Science and Technology, 40, 27–67, https://doi.org/10.1080/02786820500421521, 2006. a
Bond, T. C., Habib, G., and Bergstrom, R. W.: Limitations in the enhancement of visible light absorption due to mixing state, Journal of Geophysical Research Atmospheres, 111, D20211, https://doi.org/10.1029/2006JD007315, 2006. a, b
Briggs, G. A.: Plume rise predictions, in: Lectures on air pollution and environmental impact analyses, 59–111, American Meteorological Society, Boston, MA, ISBN 978-1-935704-23-2, https://doi.org/10.1007/978-1-935704-23-2_3, 1975. a
Brito, J., Rizzo, L. V., Morgan, W. T., Coe, H., Johnson, B., Haywood, J., Longo, K., Freitas, S., Andreae, M. O., and Artaxo, P.: Ground-based aerosol characterization during the South American Biomass Burning Analysis (SAMBBA) field experiment, Atmos. Chem. Phys., 14, 12069–12083, https://doi.org/10.5194/acp-14-12069-2014, 2014. a, b, c
Brown, H., Liu, X., Pokhrel, R., Murphy, S., Lu, Z., Saleh, R., Mielonen, T., Kokkola, H., Bergman, T., Myhre, G., Skeie, R. B., Watson-Paris, D., Stier, P., Johnson, B., Bellouin, N., Schulz, M., Vakkari, V., Beukes, J. P., van Zyl, P. G., Liu, S., and Chand, D.: Biomass burning aerosols in most climate models are too absorbing, Nat. Commun., 12, 277, https://doi.org/10.1038/s41467-020-20482-9, 2021. a
Buchholz, R. R., Emmons, L. K., Tilmes, S., and The CESM2 Development Team: CESM2.1/CAM-chem Instantaneous Output for Boundary Conditions, UCAR/NCAR – Atmospheric Chemistry Observations and Modeling Laboratory, https://doi.org/10.5065/NMP7-EP60, 2019. a
Carr, J. L., Wu, D. L., A. Kelly, M., and Gong, J.: MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds, Remote Sensing, 10, 1885, https://doi.org/10.3390/rs10121885, 2018. a
Carr, J. L., Wu, D. L., Wolfe, R. E., Madani, H., Lin, G., and Tan, B.: Joint 3D-wind retrievals with stereoscopic views from MODIS and GOES, Remote Sensing, 11, 2100, https://doi.org/10.3390/rs11182100, 2019. a, b
Carr, J. L., Wu, D. L., Daniels, J., Friberg, M. D., Bresky, W., and Madani, H.: GEO–GEO stereo-tracking of atmospheric motion vectors (AMVs) from the geostationary ring, Remote Sensing, 12, 3779, https://doi.org/10.3390/rs12223779, 2020. a
Centre for Air pollution, energy and health Research: National Air Pollution Monitoring Database, derived from regulatory monitor data from NSW DPIE, Vic EPA, Qld DES, SA EPA, WA DEWR, Tas EPA, NT EPA, and ACT Health, Centre for Air pollution, energy and health Research, https://doi.org/10.17605/OSF.IO/JXD98, 2021. a
Chen, L.-W. A., Moosmüller, H., Arnott, W. P., Chow, J. C., Watson, J. G., Susott, R. A., Babbitt, R. E., Wold, C. E., Lincoln, E. N., and Hao, W. M.: Particle emissions from laboratory combustion of wildland fuels: In situ optical and mass measurements, Geophysical Research Letters, 33, https://doi.org/10.1029/2005GL024838, 2006. a
Colarco, P., Schoeberl, M., Doddridge, B., Marufu, L., Torres, O., and Welton, E.: Transport of smoke from Canadian forest fires to the surface near Washington, DC: Injection height, entrainment, and optical properties, Journal of Geophysical Research: Atmospheres, 109, https://doi.org/10.1029/2003JD004248, 2004. a
Copernicus Atmosphere Monitoring Service (CAMS): CAMS global biomass burning emissions based on fire radiative power (GFAS), Copernicus Atmosphere Monitoring Service (CAMS) Atmosphere Data Store, https://doi.org/10.24381/a05253c7, 2021. a, b
Deb, P., Moradkhani, H., Abbaszadeh, P., Kiem, A. S., Engström, J., Keellings, D., and Sharma, A.: Causes of the Widespread 2019–2020 Australian Bushfire Season, Earth's Future, 8, e2020EF001671, https://doi.org/10.1029/2020EF001671, 2020. a, b
Dirksen, R. J., Folkert Boersma, K., de Laat, J., Stammes, P., van der Werf, G. R., Val Martin, M., and Kelder, H. M.: An aerosol boomerang: Rapid around-the-world transport of smoke from the December 2006 Australian forest fires observed from space, Journal of Geophysical Research: Atmospheres, 114, D21201, https://doi.org/10.1029/2009JD012360, 2009. a, b
Emmons, L. K., Schwantes, R. H., Orlando, J. J., Tyndall, G., Kinnison, D., Lamarque, J.-F., Marsh, D., Mills, M. J., Tilmes, S., Bardeen, C., Buchholz, R. R., Conley, A., Gettelman, A., Garcia, R., Simpson, I., Blake, D. R., Meinardi, S., and Pétron, G.: The Chemistry Mechanism in the Community Earth System Model Version 2 (CESM2), Journal of Advances in Modeling Earth Systems, 12, e2019MS001882, https://doi.org/10.1029/2019MS001882, 2020. a
Fountoukis, C. and Nenes, A.: ISORROPIA II: a computationally efficient thermodynamic equilibrium model for K+–Ca2+–Mg2+–NH –Na+–SO –NO –Cl−–H2O aerosols, Atmos. Chem. Phys., 7, 4639–4659, https://doi.org/10.5194/acp-7-4639-2007, 2007. a
Freitas, S. R., Longo, K. M., and Andreae, M. O.: Impact of including the plume rise of vegetation fires in numerical simulations of associated atmospheric pollutants, Geophys. Res. Lett., 33, 1–5, https://doi.org/10.1029/2006GL026608, 2006. a, b, c, d
Freitas, S. R., Longo, K. M., Chatfield, R., Latham, D., Silva Dias, M. A. F., Andreae, M. O., Prins, E., Santos, J. C., Gielow, R., and Carvalho Jr., J. A.: Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models, Atmos. Chem. Phys., 7, 3385–3398, https://doi.org/10.5194/acp-7-3385-2007, 2007. a, b
Freitas, S. R., Longo, K. M., Trentmann, J., and Latham, D.: Technical Note: Sensitivity of 1-D smoke plume rise models to the inclusion of environmental wind drag, Atmos. Chem. Phys., 10, 585–594, https://doi.org/10.5194/acp-10-585-2010, 2010. a
Fromm, M., Servranckx, R., Peterson, D. A., and Stocks, B. J.: Understanding the critical elements of the pyrocumulonimbus storm sparked by high-intensity wildland fire, Communications Earth & Environment, 3, 1–12, https://doi.org/10.1038/s43247-022-00566-8, 2022. a
Galanter, M., Levy, H., and Carmichael, G.: Impacts of biomass burning on tropospheric CO, NOx, and O3, Journal of Geophysical Research, 105, 6633–6653, 2010. a
Generoso, S., Bey, I., Attié, J.-L., and Bréon, F.-M.: A satellite-and model-based assessment of the 2003 Russian fires: Impact on the Arctic region, Journal of Geophysical Research: Atmospheres, 112, https://doi.org/10.1029/2006JD008344, 2007. a
Giglio, L.: Characterization of the tropical diurnal fire cycle using VIRS and MODIS observations, Remote Sensing of Environment, 108, 407–421, https://doi.org/10.1016/j.rse.2006.11.018, 2007. a
Giorgetta, M. A., Brokopf, R., Crueger, T., Esch, M., Fiedler, S., Helmert, J., Hohenegger, C., Kornblueh, L., Köhler, M., Manzini, E., Mauritsen, T., Nam, C., Raddatz, T., Rast, S., Reinert, D., Sakradzija, M., Schmidt, H., Schneck, R., Schnur, R., Silvers, L., Wan, H., Zängl, G., and Stevens, B.: ICON-A, the atmosphere component of the ICON Earth System Model: I. Model description, Journal of Advances in Modeling Earth Systems, 10, 1613–1637, https://doi.org/10.1029/2017MS001233, 2018. a
Heinze, R., Dipankar, A., Henken, C. C., Moseley, C., Sourdeval, O., Trömel, S., Xie, X., Adamidis, P., Ament, F., Baars, H., Barthlott, C., Behrendt, A., Blahak, U., Bley, S., Brdar, S., Brueck, M., Crewell, S., Deneke, H., Di Girolamo, P., Evaristo, R., Fischer, J., Frank, C., Friederichs, P., Göcke, T., Gorges, K., Hande, L., Hanke, M., Hansen, A., Hege, H.-C., Hoose, C., Jahns, T., Kalthoff, N., Klocke, D., Kneifel, S., Knippertz, P., Kuhn, A., van Laar, T., Macke, A., Maurer, V., Mayer, B., Meyer, C. I., Muppa, S. K., Neggers, R. A. J., Orlandi, E., Pantillon, F., Pospichal, B., Röber, N., Scheck, L., Seifert, A., Seifert, P., Senf, F., Siligam, P., Simmer, C., Steinke, S., Stevens, B., Wapler, K., Weniger, M., Wulfmeyer, V., Zängl, G., Zhang, D., and Quaas, J.: Large-eddy simulations over Germany using ICON: A comprehensive evaluation, Quarterly Journal of the Royal Meteorological Society, 143, 69–100, https://doi.org/10.1002/qj.2947, 2017. a
Hogan, R. J. and Bozzo, A.: A Flexible and Efficient Radiation Scheme for the ECMWF Model, Journal of Advances in Modeling Earth Systems, 10, 1990–2008, https://doi.org/10.1029/2018MS001364, 2018. a
Hoshyaripour, G. A., Baer, A., Bierbauer, S., Bruckert, J., Brunner, D., Förstner, J., Hamzehloo, A., Hanft, V., Keller, C., Klose, M., Kumar, P., Ludwig, P., Metzner, E., Muth, L., Pauling, A., Porz, N., Ramezani Ziarani, M., Reddmann, T., Reißig, L., Ruhnke, R., Satitkovitchai, K., Seifert, A., Sinnhuber, M., Steiner, M., Versick, S., Vogel, H., Weimer, M., Werchner, S., and Hoose, C.: The atmospheric composition component of the ICON modeling framework: ICON-ART version 2025.10, Geosci. Model Dev., 19, 1645–1681, https://doi.org/10.5194/gmd-19-1645-2026, 2026. a
Hoshyaripour, A.: art_pytools, GitHub [code], https://github.com/alihoshy/art_pytools, last access: 8 April 2026. a
Hyer, E. J., Allen, D. J., and Kasischke, E. S.: Examining injection properties of boreal forest fires using surface and satellite measurements of CO transport, Journal of Geophysical Research: Atmospheres, 112, D18307, https://doi.org/10.1029/2006JD008232, 2007. a
ICON partnership (DWD; MPI-M; DKRZ; KIT; C2SM): ICON release 2024.10., World Data Center for Climate (WDCC) at DKRZ [code], https://doi.org/10.35089/WDCC/IconRelease2024.10, 2024. a
Janhäll, S., Andreae, M. O., and Pöschl, U.: Biomass burning aerosol emissions from vegetation fires: particle number and mass emission factors and size distributions, Atmos. Chem. Phys., 10, 1427–1439, https://doi.org/10.5194/acp-10-1427-2010, 2010. a
Justice, C. O., Giglio, L., Roy, D., Boschetti, L., Csiszar, I., Davies, D., Korontzi, S., Schroeder, W., O'Neal, K., and Morisette, J.: MODIS-derived global fire products, Land Remote Sensing and Global Environmental Change: NASA's Earth Observing System and the Science of ASTER and MODIS, 661–679, https://doi.org/10.1007/978-1-4419-6749-7_29, 2011. a
Kablick III, G., Fromm, M., Miller, S., Partain, P., Peterson, D., Lee, S., Zhang, Y., Lambert, A., and Li, Z.: The Great Slave Lake PyroCb of 5 August 2014: Observations, Simulations, Comparisons With Regular Convection, and Impact on UTLS Water Vapor, Journal of Geophysical Research: Atmospheres, 123, 12332–12352, https://doi.org/10.1029/2018JD028965, 2018. a
Kahn, R. A., Li, W.-H., Moroney, C., Diner, D. J., Martonchik, J. V., and Fishbein, E.: Aerosol source plume physical characteristics from space-based multiangle imaging, Journal of Geophysical Research: Atmospheres, 112, D11205, https://doi.org/10.1029/2006JD007647, 2007. a
Kaiser, J. W., Suttie, M., Flemming, J., Morcrette, J., Boucher, O., and Schultz, M. G.: Global Real-time Fire Emission Estimates Based on Space-borne Fire Radiative Power Observations, AIP Conference Proceedings, 1100, 645–648, https://doi.org/10.1063/1.3117069, 2009. a, b
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012. a, b, c, d, e
Ke, Z., Wang, Y., Zou, Y., Song, Y., and Liu, Y.: Global Wildfire Plume-Rise Data Set and Parameterizations for Climate Model Applications, Journal of Geophysical Research: Atmospheres, 126, e2020JD033085, https://doi.org/10.1029/2020JD033085, 2021. a, b, c
Konovalov, I. B., Lvova, D. A., and Beekmann, M.: Estimation of the Elemental to Organic Carbon Ratio in Biomass Burning Aerosol Using AERONET Retrievals, Atmosphere, 8, https://doi.org/10.3390/atmos8070122, 2017. a
Koren, I., Kaufman, Y. J., Rosenfeld, D., Remer, L. A., and Rudich, Y.: Aerosol invigoration and restructuring of Atlantic convective clouds, Geophysical Research Letters, 32, https://doi.org/10.1029/2005GL023187, 2005. a
Lamarque, J.-F., Edwards, D. P., Emmons, L. K., Gille, J. C., Wilhelmi, O., Gerbig, C., Prevedel, D., Deeter, M. N., Warner, J., Ziskin, D. C., Khattatov, B., Francis, G. L., Yudin, V., Ho, S., Mao, D., Chen, J., and Drummond, J. R.: Identification of CO plumes from MOPITT data: Application to the August 2000 Idaho-Montana forest fires, Geophysical Research Letters, 30, https://doi.org/10.1029/2003GL017503, 2003. a
Lavoué, D., Liousse, C., Cachier, H., Stocks, B. J., and Goldammer, J. G.: Modeling of carbonaceous particles emitted by boreal and temperate wildfires at northern latitudes, Journal of Geophysical Research: Atmospheres, 105, 26871–26890, https://doi.org/10.1029/2000JD900180, 2000. a, b
Leung, F.-Y. T., Logan, J. A., Park, R., Hyer, E., Kasischke, E., Streets, D., and Yurganov, L.: Impacts of enhanced biomass burning in the boreal forests in 1998 on tropospheric chemistry and the sensitivity of model results to the injection height of emissions, Journal of Geophysical Research: Atmospheres, 112, D10313, https://doi.org/10.1029/2006JD008132, 2007. a
Levin, E. J., McMeeking, G. R., Carrico, C. M., Mack, L. E., Kreidenweis, S. M., Wold, C. E., Moosmüller, H., Arnott, W. P., Hao, W. M., Collett, J. L., and Malm, W. C.: Biomass burning smoke aerosol properties measured during Fire Laboratory at Missoula Experiments (FLAME), Journal of Geophysical Research Atmospheres, 115, 1–15, https://doi.org/10.1029/2009JD013601, 2010. a
Li, Y., Tong, D., Ma, S., Freitas, S. R., Ahmadov, R., Sofiev, M., Zhang, X., Kondragunta, S., Kahn, R., Tang, Y., Baker, B., Campbell, P., Saylor, R., Grell, G., and Li, F.: Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: a comparison of three schemes (Briggs, Freitas, and Sofiev), Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, 2023. a
Liu, Z., Kar, J., Zeng, S., Tackett, J., Vaughan, M., Avery, M., Pelon, J., Getzewich, B., Lee, K.-P., Magill, B., Omar, A., Lucker, P., Trepte, C., and Winker, D.: Discriminating between clouds and aerosols in the CALIOP version 4.1 data products, Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, 2019. a
Lu, Z., Liu, X., Ke, Z., Zhang, K., Ma, P.-L., and Fan, J.: Incorporating an Interactive Fire Plume-Rise Model in the DOE's Energy Exascale Earth System Model Version 1 (E3SMv1) and Examining Aerosol Radiative Effect, Journal of Advances in Modeling Earth Systems, 16, e2023MS003818, https://doi.org/10.1029/2023MS003818, 2024. a
Luderer, G., Trentmann, J., Winterrath, T., Textor, C., Herzog, M., Graf, H. F., and Andreae, M. O.: Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part II): sensitivity studies, Atmos. Chem. Phys., 6, 5261–5277, https://doi.org/10.5194/acp-6-5261-2006, 2006. a, b
Ma, C., Su, H., Lelieveld, J., Randel, W., Yu, P., Andreae, M. O., and Cheng, Y.: Smoke-charged vortex doubles hemispheric aerosol in the middle stratosphere and buffers ozone depletion, Science Advances, 10, eadn3657, https://doi.org/10.1126/sciadv.adn3657, 2024. a
Ma, Q., Wei, L., Wang, Y., Zhang, G. J., Zhou, X., and Wang, B.: Fire heat affects the impacts of wildfires on air pollution in the United States, Science, 389, 1137–1142, https://doi.org/10.1126/science.ads1957, 2025. a
Mätzler, C.: MATLAB functions for Mie scattering and absorption, version 2, IAP Res. Rep., 8, 1–24, 2002. a
Moisseeva, N. and Stull, R.: Wildfire smoke-plume rise: a simple energy balance parameterization, Atmos. Chem. Phys., 21, 1407–1425, https://doi.org/10.5194/acp-21-1407-2021, 2021. a
Muser, L. O., Hoshyaripour, G. A., Bruckert, J., Horváth, Á., Malinina, E., Wallis, S., Prata, F. J., Rozanov, A., von Savigny, C., Vogel, H., and Vogel, B.: Particle aging and aerosol–radiation interaction affect volcanic plume dispersion: evidence from the Raikoke 2019 eruption, Atmos. Chem. Phys., 20, 15015–15036, https://doi.org/10.5194/acp-20-15015-2020, 2020. a, b, c, d
Muth, L. J.: Data for “Impacts of Fire-Induced Heat, Moisture, and Aerosol–Radiation Interactions on Wildfire Plume Rise During the 2019/2020 Australian Fires”, Radar4KIT [data set], https://doi.org/10.35097/a0ug2j340wes39xt, 2026. a
Muth, L. J., Bierbauer, S., Hoose, C., Vogel, B., Vogel, H., and Hoshyaripour, G. A.: Influence of fire-induced heat and moisture release on pyro-convective cloud dynamics during the Australian New Year’s Event: a study using convection-resolving simulations and satellite data, Atmos. Chem. Phys., 25, 16027–16040, https://doi.org/10.5194/acp-25-16027-2025, 2025. a, b
Nolan, R. H., Boer, M. M., Resco de Dios, V., Caccamo, G., and Bradstock, R. A.: Large-scale, dynamic transformations in fuel moisture drive wildfire activity across southeastern Australia, Geophysical Research Letters, 43, 4229–4238, https://doi.org/10.1002/2016GL068614, 2016. a, b
Ohneiser, K., Ansmann, A., Witthuhn, J., Deneke, H., Chudnovsky, A., Walter, G., and Senf, F.: Self-lofting of wildfire smoke in the troposphere and stratosphere: simulations and space lidar observations, Atmos. Chem. Phys., 23, 2901–2925, https://doi.org/10.5194/acp-23-2901-2023, 2023. a
Pang, Y., Chen, M., Wang, Y., Chen, X., Teng, X., Kong, S., Zheng, Z., and Li, W.: Morphology and Fractal Dimension of Size-Resolved Soot Particles Emitted From Combustion Sources, Journal of Geophysical Research: Atmospheres, 128, e2022JD037711, https://doi.org/10.1029/2022JD037711, 2023. a
Parmar, R. S., Welling, M., Andreae, M. O., and Helas, G.: Water vapor release from biomass combustion, Atmos. Chem. Phys., 8, 6147–6153, https://doi.org/10.5194/acp-8-6147-2008, 2008. a
Peterson, D. A., Fromm, M. D., McRae, R. H., Campbell, J. R., Hyer, E. J., Taha, G., Camacho, C. P., Kablick III, G. P., Schmidt, C. C., and DeLand, M. T.: Australia’s Black Summer pyrocumulonimbus super outbreak reveals potential for increasingly extreme stratospheric smoke events, NPJ Climate and Atmospheric Science, 4, 38, https://doi.org/10.1038/s41612-021-00192-9, 2021. a, b
Petzold, A., Gysel, M., Vancassel, X., Hitzenberger, R., Puxbaum, H., Vrochticky, S., Weingartner, E., Baltensperger, U., and Mirabel, P.: On the effects of organic matter and sulphur-containing compounds on the CCN activation of combustion particles, Atmos. Chem. Phys., 5, 3187–3203, https://doi.org/10.5194/acp-5-3187-2005, 2005. a
Pfister, G. G., Emmons, L. K., Hess, P. G., Honrath, R., Lamarque, J.-F., Val Martin, M., Owen, R. C., Avery, M. A., Browell, E. V., Holloway, J. S., Nedelec, P., Purvis, R., Ryerson, T. B., Sachse, G. W., and Schlager, H.: Ozone production from the 2004 North American boreal fires, Journal of Geophysical Research: Atmospheres, 111, https://doi.org/10.1029/2006JD007695, 2006. a
Raffuse, S. M., Craig, K. J., Larkin, N. K., Strand, T. T., Sullivan, D. C., Wheeler, N. J., and Solomon, R.: An evaluation of modeled plume injection height with satellite-derived observed plume height, Atmosphere, 3, 103–123, https://doi.org/10.3390/atmos3010103, 2012. a, b
Reid, J. S., Hobbs, P. V., Ferek, R. J., Blake, D. R., Martins, J. V., Dunlap, M. R., and Liousse, C.: Physical, chemical, and optical properties of regional hazes dominated by smoke in Brazil, Journal of Geophysical Research Atmospheres, 103, 32059–32080, https://doi.org/10.1029/98JD00458, 1998a. a
Reid, J. S., Hobbs, P. V., Liousse, C., Martins, J. V., Weiss, R. E., and Eck, T. F.: Comparisons of techniques for measuring shortwave absorption and black carbon content of aerosols from biomass burning in Brazil, Journal of Geophysical Research: Atmospheres, 103, 32031–32040, https://doi.org/10.1029/98JD00773, 1998b. a
Rieger, D., Bangert, M., Bischoff-Gauss, I., Förstner, J., Lundgren, K., Reinert, D., Schröter, J., Vogel, H., Zängl, G., Ruhnke, R., and Vogel, B.: ICON–ART 1.0 – a new online-coupled model system from the global to regional scale, Geosci. Model Dev., 8, 1659–1676, https://doi.org/10.5194/gmd-8-1659-2015, 2015. a, b
Rodgers, C. D.: Inverse methods for atmospheric sounding: theory and practice, vol. 2, World Scientific, https://doi.org/10.1142/3171, 2000. a
Romshoo, B., Pöhlker, M., Wiedensohler, A., Pfeifer, S., Saturno, J., Nowak, A., Ciupek, K., Quincey, P., Vasilatou, K., Ess, M. N., Gini, M., Eleftheriadis, K., Robins, C., Gaie-Levrel, F., and Müller, T.: Importance of size representation and morphology in modelling optical properties of black carbon: comparison between laboratory measurements and model simulations, Atmos. Meas. Tech., 15, 6965–6989, https://doi.org/10.5194/amt-15-6965-2022, 2022. a
Sakamoto, K. M., Allan, J. D., Coe, H., Taylor, J. W., Duck, T. J., and Pierce, J. R.: Aged boreal biomass-burning aerosol size distributions from BORTAS 2011, Atmos. Chem. Phys., 15, 1633–1646, https://doi.org/10.5194/acp-15-1633-2015, 2015. a
Schröter, J., Rieger, D., Stassen, C., Vogel, H., Weimer, M., Werchner, S., Förstner, J., Prill, F., Reinert, D., Zängl, G., Giorgetta, M., Ruhnke, R., Vogel, B., and Braesicke, P.: ICON-ART 2.1: a flexible tracer framework and its application for composition studies in numerical weather forecasting and climate simulations, Geosci. Model Dev., 11, 4043–4068, https://doi.org/10.5194/gmd-11-4043-2018, 2018. a
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics, John Wiley & Sons, Hoboken, New Jersey, ISBN 9780471720171, 2006. a
Sofiev, M., Ermakova, T., and Vankevich, R.: Evaluation of the smoke-injection height from wild-land fires using remote-sensing data, Atmos. Chem. Phys., 12, 1995–2006, https://doi.org/10.5194/acp-12-1995-2012, 2012. a
Urbanski, S.: Wildland fire emissions, carbon, and climate: Emission factors, Forest Ecology and Management, 317, 51–60, https://doi.org/10.1016/j.foreco.2013.05.045, 2014. a
Val Martin, M., Honrath, R. E., Owen, R. C., Pfister, G., Fialho, P., and Barata, F.: Significant enhancements of nitrogen oxides, black carbon, and ozone in the North Atlantic lower free troposphere resulting from North American boreal wildfires, Journal of Geophysical Research: Atmospheres, 111, D23S60, https://doi.org/10.1029/2006JD007530, 2006. a
Val Martin, M., Logan, J. A., Kahn, R. A., Leung, F.-Y., Nelson, D. L., and Diner, D. J.: Smoke injection heights from fires in North America: analysis of 5 years of satellite observations, Atmos. Chem. Phys., 10, 1491–1510, https://doi.org/10.5194/acp-10-1491-2010, 2010. a
Vermote, E., Ellicott, E., Dubovik, O., Lapyonok, T., Chin, M., Giglio, L., and Roberts, G. J.: An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power, Journal of Geophysical Research: Atmospheres, 114, https://doi.org/10.1029/2008JD011188, 2009. a
Wang, H., Skamarock, W. C., and Feingold, G.: Evaluation of Scalar Advection Schemes in the Advanced Research WRF Model Using Large-Eddy Simulations of Aerosol-Cloud Interactions, Monthly Weather Review, 137, 2547–2558, https://doi.org/10.1175/2009MWR2820.1, 2009. a
Wang, J., Christopher, S. A., Nair, U., Reid, J. S., Prins, E. M., Szykman, J., and Hand, J. L.: Mesoscale modeling of Central American smoke transport to the United States: 1.“Top-down” assessment of emission strength and diurnal variation impacts, Journal of Geophysical Research: Atmospheres, 111, https://doi.org/10.1029/2005JD006416, 2006. a
Wang, S.: Emulating Wildfire Plume Injection Using Machine Learning Trained by Large Eddy Simulation (LES), Environmental Science & Technology, 58, 22204–22212, https://doi.org/10.1021/acs.est.4c05095, 2024. a, b
Weimer, M., Schröter, J., Eckstein, J., Deetz, K., Neumaier, M., Fischbeck, G., Hu, L., Millet, D. B., Rieger, D., Vogel, H., Vogel, B., Reddmann, T., Kirner, O., Ruhnke, R., and Braesicke, P.: An emission module for ICON-ART 2.0: implementation and simulations of acetone, Geosci. Model Dev., 10, 2471–2494, https://doi.org/10.5194/gmd-10-2471-2017, 2017. a
Wilmot, T. Y., Mallia, D. V., Hallar, A. G., and Lin, J. C.: Wildfire plumes in the Western US are reaching greater heights and injecting more aerosols aloft as wildfire activity intensifies, Scientific Reports, 12, 12400, https://doi.org/10.1038/s41598-022-16607-3, 2022. a, b
Zängl, G., Reinert, D., Rpodas, P., and Baldauf, M.: The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc, 141, 563579, https://doi.org/10.1002/qj.2378, 2015. a
Zauscher, M. D., Wang, Y., Moore, M. J. K., Gaston, C. J., and Prather, K. A.: Air Quality Impact and Physicochemical Aging of Biomass Burning Aerosols during the 2007 San Diego Wildfires, Environmental Science & Technology, 47, 7633–7643, https://doi.org/10.1021/es4004137, 2013. a
Zheng, B., Ciais, P., Chevallier, F., Chuvieco, E., Chen, Y., and Yang, H.: Increasing forest fire emissions despite the decline in global burned area, Science Advances, 7, eabh2646, https://doi.org/10.1126/sciadv.abh2646, 2021. a
Short summary
Wildfire plume injection height is key for atmospheric impact but hard to model. This study simulates the 2019/2020 Australian wildfires, testing fire-atmosphere feedbacks. Heat release increases plume rise; moisture has minor effects. Aerosol-radiation interaction lowers injection height initially, then lofts it. Only the combined simulation matches observed upper troposphere aerosol layers, especially during peak fire intensity.
Wildfire plume injection height is key for atmospheric impact but hard to model. This study...
Altmetrics
Final-revised paper
Preprint