Articles | Volume 22, issue 4
https://doi.org/10.5194/acp-22-2419-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-2419-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Feb 2022
Research article |
| 22 Feb 2022
| 22 Feb 2022
The contribution of coral-reef-derived dimethyl sulfide to aerosol burden over the Great Barrier Reef: a modelling study
ARC Centre of Excellence for Climate System Science and the Australian-German Climate and Energy College, University of Melbourne, Melbourne, Australia
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
now at: the Australian Antarctic Program Partnership, Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
Matthew T. Woodhouse
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
Steve Utembe
Environmental Protection Authority Victoria, Macleod, Australia
Robyn Schofield
ARC Centre of Excellence for Climate Extremes, University of Melbourne, Melbourne, Australia
Simon P. Alexander
Australian Antarctic Division, Hobart, Australia
Joel Alroe
International Laboratory for Air Quality and Health, School of Earth and Atmospheric Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Scott D. Chambers
Australian Nuclear Science and Technology Organisation, Lucas Heights, New South Wales, Australia
Zhenyi Chen
Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, 230031 Hefei, China
Luke Cravigan
International Laboratory for Air Quality and Health, School of Earth and Atmospheric Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Erin Dunne
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
Ruhi S. Humphries
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
Graham Johnson
International Laboratory for Air Quality and Health, School of Earth and Atmospheric Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Melita D. Keywood
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
Todd P. Lane
ARC Centre of Excellence for Climate Extremes, University of Melbourne, Melbourne, Australia
Branka Miljevic
International Laboratory for Air Quality and Health, School of Earth and Atmospheric Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Yuko Omori
Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan
Alain Protat
Australian Bureau of Meteorology, Melbourne, Australia
Zoran Ristovski
International Laboratory for Air Quality and Health, School of Earth and Atmospheric Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Paul Selleck
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
Hilton B. Swan
Faculty of Science and Engineering, Southern Cross University, Lismore, Australia
Hiroshi Tanimoto
Earth System Division, National Institute for Environmental Studies, Tsukuba, Japan
Jason P. Ward
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
Alastair G. Williams
Australian Nuclear Science and Technology Organisation, Lucas Heights, New South Wales, Australia
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Atmos. Chem. Phys., 25, 16451–16477, https://doi.org/10.5194/acp-25-16451-2025, https://doi.org/10.5194/acp-25-16451-2025, 2025
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The interaction between natural marine aerosols, clouds and radiation in the Southern Ocean is a major source of uncertainty in climate models. We evaluate the Australian climate model using aerosol observations and find it underestimates aerosol number often by over 50%. Model changes were tested to improve aerosol concentrations, but some of our changes had severe negative effects on the larger climate system, highlighting issues in aerosol-cloud interaction modelling.
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
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In this paper, we use ground-based observations to evaluate a climate model and a satellite product in simulating surface radiation and investigate how radiation biases are influenced by cloud properties over the Southern Ocean. We find that significant radiation biases exist in both the model and satellite. The cloud fraction and cloud occurrence play an important role in affecting radiation biases. We suggest further development for the model and satellite using ground-based observations.
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Atmos. Chem. Phys., 22, 14603–14630, https://doi.org/10.5194/acp-22-14603-2022, https://doi.org/10.5194/acp-22-14603-2022, 2022
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Climate models have difficulty simulating Southern Ocean clouds, impacting how much sunlight reaches the surface. We use machine learning to group different cloud types observed from satellites and simulated in a climate model. We find the model does a poor job of simulating the same cloud type as what the satellite shows and, even when it does, the cloud properties and amount of reflected sunlight are incorrect. We have a lot of work to do to model clouds correctly over the Southern Ocean.
Sonya L. Fiddes, Matthew T. Woodhouse, Todd P. Lane, and Robyn Schofield
Atmos. Chem. Phys., 21, 5883–5903, https://doi.org/10.5194/acp-21-5883-2021, https://doi.org/10.5194/acp-21-5883-2021, 2021
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Coral reefs are known to produce the aerosol precursor dimethyl sulfide (DMS). Currently, this source of coral DMS is unaccounted for in climate modelling, and the impact of coral reef extinction on aerosol and climate is unknown. In this study, we address this problem using a coupled chemistry–climate model for the first time. We find that coral reefs make a minimal contribution to the aerosol population and are unlikely to play a role in climate modulation.
Sonya L. Fiddes, Matthew T. Woodhouse, Marc D. Mallet, Liam J. Lamprey, Ruhi S. Humphries, Alain Protat, Simon P. Alexander, Hakase Hayashida, Samuel Putland, Branka Miljevic, and Robyn Schofield
Atmos. Chem. Phys., 25, 16451–16477, https://doi.org/10.5194/acp-25-16451-2025, https://doi.org/10.5194/acp-25-16451-2025, 2025
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The interaction between natural marine aerosols, clouds and radiation in the Southern Ocean is a major source of uncertainty in climate models. We evaluate the Australian climate model using aerosol observations and find it underestimates aerosol number often by over 50%. Model changes were tested to improve aerosol concentrations, but some of our changes had severe negative effects on the larger climate system, highlighting issues in aerosol-cloud interaction modelling.
Scott D. Chambers, Ute Karstens, Alan D. Griffiths, Stefan Röttger, Arnoud Frumau, Christopher T. Roulston, Peter Sperlich, Felix Vogel, Agnieszka Podstawczyńska, Dafina Kikaj, Maksym Gachkivskyi, Michel Ramonet, Blagoj Mitrevski, Janja Vaupotič, Xuemeng Chen, and Annette Röttger
EGUsphere, https://doi.org/10.5194/egusphere-2025-5042, https://doi.org/10.5194/egusphere-2025-5042, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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The Radon Tracer Method (RTM) is a top-down approach to estimate greenhouse gas emissions. While simple in principle, incorrect use can complicate interpretation of results. Based on observations from a range of contrasting sites, this article reviews the underlying assumptions and key considerations for applying the RTM. It also introduces the concept of coupling RTM analyses with nocturnal stability classification, to reduce uncertainty of fetch estimates and improve interpretation of results.
Robert G. Ryan, Lilani Toms-Hardman, Alexander Smirnov, Daniel P. Harrison, and Robyn Schofield
Atmos. Chem. Phys., 25, 11183–11197, https://doi.org/10.5194/acp-25-11183-2025, https://doi.org/10.5194/acp-25-11183-2025, 2025
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Measurements of aerosol vertical distribution are key for understanding how they interact with clouds and sunlight. Such measurements are currently lacking at the Great Barrier Reef, limiting our ability to validate climate models in this sensitive, ecologically rich environment. Here we use a range of techniques to quantify the vertical variation of aerosols above the Great Barrier Reef for the first time, using the comparison of techniques to also infer aerosol spatial variation.
E. Johanna Horchler, Joel Alroe, Luke Harrison, Luke Cravigan, Daniel P. Harrison, and Zoran D. Ristovski
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Aerosols play a role in global climate by interacting with incoming solar radiation and by taking up water vapour from the atmosphere to form clouds. Enhancing local-scale cloud cover can reduce sea surface temperatures. Coral bleaching events have increased in the Great Barrier Reef (GBR) as sea surface temperatures have risen. Our study found that the number of aerosols and the cloud-forming ability over the GBR increased if the aerosols were transported from inland Australia rather than the ocean.
Jhonathan Ramirez-Gamboa, Clare Paton-Walsh, Melita Keywood, Ruhi Humphries, Asher Mouat, Jennifer Kaiser, Malcom Possell, Jack Simmons, and Travis Naylor
Atmos. Chem. Phys., 25, 9937–9955, https://doi.org/10.5194/acp-25-9937-2025, https://doi.org/10.5194/acp-25-9937-2025, 2025
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Yik-Sze Lau, Zoran Ristovski, and Branka Miljevic
Atmos. Meas. Tech., 18, 3945–3958, https://doi.org/10.5194/amt-18-3945-2025, https://doi.org/10.5194/amt-18-3945-2025, 2025
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Beth Dingley, James A. Anstey, Marta Abalos, Carsten Abraham, Tommi Bergman, Lisa Bock, Sonya Fiddes, Birgit Hassler, Ryan J. Kramer, Fei Luo, Fiona M. O'Connor, Petr Šácha, Isla R. Simpson, Laura J. Wilcox, and Mark D. Zelinka
EGUsphere, https://doi.org/10.5194/egusphere-2025-3189, https://doi.org/10.5194/egusphere-2025-3189, 2025
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Airborne particles are crucial in environmental and health studies, requiring precise sampling for accurate characterisation. Our study examines the optimal sampling time for the TSI Nanometer Aerosol Sampler 3089 at different input concentrations. Aerosols from low-, medium-, and high-concentration environments were sampled over 1, 3, and 6 h. A linear relationship was observed using a regression model between the deposition densities and the product of input concentration and sampling time.
Tahereh Alinejadtabrizi, Yi Huang, Francisco Lang, Steven Siems, Michael Manton, Luis Ackermann, Melita Keywood, Ruhi Humphries, Paul Krummel, Alastair Williams, and Greg Ayers
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Clouds over the Southern Ocean are crucial to Earth's energy balance, but understanding the factors that control them is complex. Our research examines how weather patterns affect tiny particles called cloud condensation nuclei (CCN), which influence cloud properties. Using data from Kennaook / Cape Grim, we found that winter air from Antarctica brings cleaner conditions with lower CCN, while summer patterns from Australia transport more particles. Precipitation also helps reduce CCN in winter.
Dafina Kikaj, Edward Chung, Alan D. Griffiths, Scott D. Chambers, Grant Forster, Angelina Wenger, Penelope Pickers, Chris Rennick, Simon O'Doherty, Joseph Pitt, Kieran Stanley, Dickon Young, Leigh S. Fleming, Karina Adcock, Emmal Safi, and Tim Arnold
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Matthew Boyer, Diego Aliaga, Lauriane L. J. Quéléver, Silvia Bucci, Hélène Angot, Lubna Dada, Benjamin Heutte, Lisa Beck, Marina Duetsch, Andreas Stohl, Ivo Beck, Tiia Laurila, Nina Sarnela, Roseline C. Thakur, Branka Miljevic, Markku Kulmala, Tuukka Petäjä, Mikko Sipilä, Julia Schmale, and Tuija Jokinen
Atmos. Chem. Phys., 24, 12595–12621, https://doi.org/10.5194/acp-24-12595-2024, https://doi.org/10.5194/acp-24-12595-2024, 2024
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We analyze the seasonal cycle and sources of gases that are relevant for the formation of aerosol particles in the central Arctic. Since theses gases can form new particles, they can influence Arctic climate. We show that the sources of these gases are associated with changes in the Arctic environment during the year, especially with respect to sea ice. Therefore, the concentration of these gases will likely change in the future as the Arctic continues to warm.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Luis Ackermann, Joshua Soderholm, Alain Protat, Rhys Whitley, Lisa Ye, and Nina Ridder
Atmos. Meas. Tech., 17, 407–422, https://doi.org/10.5194/amt-17-407-2024, https://doi.org/10.5194/amt-17-407-2024, 2024
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The paper addresses the crucial topic of hail damage quantification using radar observations. We propose a new radar-derived hail product that utilizes a large dataset of insurance hail damage claims and radar observations. A deep neural network was employed, trained with local meteorological variables and the radar observations, to better quantify hail damage. Key meteorological variables were identified to have the most predictive capability in this regard.
Ben A. Cala, Scott Archer-Nicholls, James Weber, N. Luke Abraham, Paul T. Griffiths, Lorrie Jacob, Y. Matthew Shin, Laura E. Revell, Matthew Woodhouse, and Alexander T. Archibald
Atmos. Chem. Phys., 23, 14735–14760, https://doi.org/10.5194/acp-23-14735-2023, https://doi.org/10.5194/acp-23-14735-2023, 2023
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Dimethyl sulfide (DMS) is an important trace gas emitted from the ocean recognised as setting the sulfate aerosol background, but its oxidation is complex. As a result representation in chemistry-climate models is greatly simplified. We develop and compare a new mechanism to existing mechanisms via a series of global and box model experiments. Our studies show our updated DMS scheme is a significant improvement but significant variance exists between mechanisms.
Zhangcheng Pei, Sonya L. Fiddes, W. John R. French, Simon P. Alexander, Marc D. Mallet, Peter Kuma, and Adrian McDonald
Atmos. Chem. Phys., 23, 14691–14714, https://doi.org/10.5194/acp-23-14691-2023, https://doi.org/10.5194/acp-23-14691-2023, 2023
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In this paper, we use ground-based observations to evaluate a climate model and a satellite product in simulating surface radiation and investigate how radiation biases are influenced by cloud properties over the Southern Ocean. We find that significant radiation biases exist in both the model and satellite. The cloud fraction and cloud occurrence play an important role in affecting radiation biases. We suggest further development for the model and satellite using ground-based observations.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
McKenna W. Stanford, Ann M. Fridlind, Israel Silber, Andrew S. Ackerman, Greg Cesana, Johannes Mülmenstädt, Alain Protat, Simon Alexander, and Adrian McDonald
Atmos. Chem. Phys., 23, 9037–9069, https://doi.org/10.5194/acp-23-9037-2023, https://doi.org/10.5194/acp-23-9037-2023, 2023
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Clouds play an important role in the Earth’s climate system as they modulate the amount of radiation that either reaches the surface or is reflected back to space. This study demonstrates an approach to robustly evaluate surface-based observations against a large-scale model. We find that the large-scale model precipitates too infrequently relative to observations, contrary to literature documentation suggesting otherwise based on satellite measurements.
Claudia Grossi, Daniel Rabago, Scott Chambers, Carlos Sáinz, Roger Curcoll, Peter P. S. Otáhal, Eliška Fialová, Luis Quindos, and Arturo Vargas
Atmos. Meas. Tech., 16, 2655–2672, https://doi.org/10.5194/amt-16-2655-2023, https://doi.org/10.5194/amt-16-2655-2023, 2023
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The automatic and low-maintenance radon flux system Autoflux, completed with environmental soil and atmosphere sensors, has been theoretically and experimentally characterized and calibrated under laboratory conditions to be used as transfer standard for in situ measurements. It will offer for the first time long-term measurements to validate radon flux maps used by the climate and the radiation protection communities for assessing the radon gas emissions in the atmosphere.
Manon Rocco, Erin Dunne, Alexia Saint-Macary, Maija Peltola, Theresa Barthelmeß, Neill Barr, Karl Safi, Andrew Marriner, Stacy Deppeler, James Harnwell, Anja Engel, Aurélie Colomb, Alfonso Saiz-Lopez, Mike Harvey, Cliff S. Law, and Karine Sellegri
EGUsphere, https://doi.org/10.5194/egusphere-2023-516, https://doi.org/10.5194/egusphere-2023-516, 2023
Preprint archived
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During the Sea2cloud campaign in the Southern Pacific Ocean, we measured air-sea emissions from phytopankton of two key atmospheric compounds: DMS and MeSH. These compounds are well-known to play a great role in atmospheric chemistry and climate. We see in this paper that these compounds are most emited by the nanophytoplankton population. We provide here parameters for climate models to predict future trends of the emissions of these compounds and their roles and impacts on the global warming.
Ruhi S. Humphries, Melita D. Keywood, Jason P. Ward, James Harnwell, Simon P. Alexander, Andrew R. Klekociuk, Keiichiro Hara, Ian M. McRobert, Alain Protat, Joel Alroe, Luke T. Cravigan, Branka Miljevic, Zoran D. Ristovski, Robyn Schofield, Stephen R. Wilson, Connor J. Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Greg M. McFarquhar, Scott D. Chambers, Alastair G. Williams, and Alan D. Griffiths
Atmos. Chem. Phys., 23, 3749–3777, https://doi.org/10.5194/acp-23-3749-2023, https://doi.org/10.5194/acp-23-3749-2023, 2023
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Observations of aerosols in pristine regions are rare but are vital to constraining the natural baseline from which climate simulations are calculated. Here we present recent seasonal observations of aerosols from the Southern Ocean and contrast them with measurements from Antarctica, Australia and regionally relevant voyages. Strong seasonal cycles persist, but striking differences occur at different latitudes. This study highlights the need for more long-term observations in remote regions.
Gerald G. Mace, Sally Benson, Ruhi Humphries, Peter M. Gombert, and Elizabeth Sterner
Atmos. Chem. Phys., 23, 1677–1685, https://doi.org/10.5194/acp-23-1677-2023, https://doi.org/10.5194/acp-23-1677-2023, 2023
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The number of cloud droplets per unit volume is a significantly important property of clouds that controls their reflective properties. Computer models of the Earth's atmosphere and climate have low skill at predicting the reflective properties of Southern Ocean clouds. Here we investigate the properties of those clouds using satellite data and find that the cloud droplet number and cloud albedo in the Southern Ocean are related to the oceanic phytoplankton abundance near Antarctica.
Sonya L. Fiddes, Alain Protat, Marc D. Mallet, Simon P. Alexander, and Matthew T. Woodhouse
Atmos. Chem. Phys., 22, 14603–14630, https://doi.org/10.5194/acp-22-14603-2022, https://doi.org/10.5194/acp-22-14603-2022, 2022
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Climate models have difficulty simulating Southern Ocean clouds, impacting how much sunlight reaches the surface. We use machine learning to group different cloud types observed from satellites and simulated in a climate model. We find the model does a poor job of simulating the same cloud type as what the satellite shows and, even when it does, the cloud properties and amount of reflected sunlight are incorrect. We have a lot of work to do to model clouds correctly over the Southern Ocean.
M. White, X. Huang, N. Langenheim, T. Yang, R. Schofield, M. Young, S. J. Livesley, S. Seneviratne, and M. Stevenson
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4-W3-2022, 269–276, https://doi.org/10.5194/isprs-annals-X-4-W3-2022-269-2022, https://doi.org/10.5194/isprs-annals-X-4-W3-2022-269-2022, 2022
Ashok K. Luhar, Ian E. Galbally, and Matthew T. Woodhouse
Atmos. Chem. Phys., 22, 13013–13033, https://doi.org/10.5194/acp-22-13013-2022, https://doi.org/10.5194/acp-22-13013-2022, 2022
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Recent improvements to global parameterisations of oceanic ozone dry deposition and lightning-generated oxides of nitrogen (LNOx) have consequent impacts on earth's radiative fluxes. Uncertainty in radiative fluxes arising from uncertainty in LNOx is of significant magnitude in comparison with the
present-dayIPCC AR6 anthropogenic effective radiative forcing (ERF) due to ozone. Hence, uncertainty in LNOx needs to be explicitly addressed in relation to the GWP and ERF of anthropogenic methane.
Youwen Sun, Hao Yin, Wei Wang, Changgong Shan, Justus Notholt, Mathias Palm, Ke Liu, Zhenyi Chen, and Cheng Liu
Atmos. Meas. Tech., 15, 4819–4834, https://doi.org/10.5194/amt-15-4819-2022, https://doi.org/10.5194/amt-15-4819-2022, 2022
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This study summarizes an overview of the status and perspective of GHG monitoring in China. This study not only improves our understanding with respect to the status, advances, and challenges of GHG monitoring in China but also presents an outlook for further improving GHG monitoring capacity in China.
Adrien Guyot, Alain Protat, Simon P. Alexander, Andrew R. Klekociuk, Peter Kuma, and Adrian McDonald
Atmos. Meas. Tech., 15, 3663–3681, https://doi.org/10.5194/amt-15-3663-2022, https://doi.org/10.5194/amt-15-3663-2022, 2022
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Ceilometers are instruments that are widely deployed as part of operational networks. They are usually not able to detect cloud phase. Here, we propose an evaluation of various methods to detect supercooled liquid water with ceilometer observations, using an extensive dataset from Davis, Antarctica. Our results highlight the possibility for ceilometers to detect supercooled liquid water in clouds.
Scott D. Chambers, Alan D. Griffiths, Alastair G. Williams, Ot Sisoutham, Viacheslav Morosh, Stefan Röttger, Florian Mertes, and Annette Röttger
Adv. Geosci., 57, 63–80, https://doi.org/10.5194/adgeo-57-63-2022, https://doi.org/10.5194/adgeo-57-63-2022, 2022
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There is a growing need in health and climate research for high-quality radon observations. A variety of radon monitors, with different uncertainties, operate across global networks. Better compatibility between the measurements is required. Here we describe a novel, portable two-filter radon monitor with a calibration traceable to the International System of Units, and demonstrate the transfer of a traceable calibration from this instrument to a separate monitor under field conditions.
Zhenyi Chen, Robyn Schofield, Melita Keywood, Sam Cleland, Alastair G. Williams, Alan Griffiths, Stephen Wilson, Peter Rayner, and Xiaowen Shu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-104, https://doi.org/10.5194/acp-2022-104, 2022
Revised manuscript not accepted
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This study studied the marine boundary layer (MBL) process and aerosol properties in the Southern Ocean using miniMPL, ceilometer and sodar. Compared to the gradient method, the Image Edge Detection Algorithm provides more reliable boundary layer height estimations, especially when a convective MBL with stratification existed. The diurnal characteristic of BLH with the veering of the wind vector was also observed. Under the continental sources, the MBL maintained a well-mixed layer of 0.3 km.
Alain Protat, Valentin Louf, Joshua Soderholm, Jordan Brook, and William Ponsonby
Atmos. Meas. Tech., 15, 915–926, https://doi.org/10.5194/amt-15-915-2022, https://doi.org/10.5194/amt-15-915-2022, 2022
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This study uses collocated ship-based, ground-based, and spaceborne radar observations to validate the concept of using the GPM spaceborne radar observations to calibrate national weather radar networks to the accuracy required for operational severe weather applications such as rainfall and hail nowcasting.
Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
Atmos. Chem. Phys., 21, 17185–17223, https://doi.org/10.5194/acp-21-17185-2021, https://doi.org/10.5194/acp-21-17185-2021, 2021
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Aerosol particles are a complex component of the atmospheric system the effects of which are among the most uncertain in climate change projections. Using data collected at 62 stations, this study provides the most up-to-date picture of the spatial distribution of particle number concentration and size distribution worldwide, with the aim of contributing to better representation of aerosols and their interactions with clouds in models and, therefore, better evaluation of their impact on climate.
Kamil Mroz, Alessandro Battaglia, Cuong Nguyen, Andrew Heymsfield, Alain Protat, and Mengistu Wolde
Atmos. Meas. Tech., 14, 7243–7254, https://doi.org/10.5194/amt-14-7243-2021, https://doi.org/10.5194/amt-14-7243-2021, 2021
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A method for estimating microphysical properties of ice clouds based on radar measurements is presented. The algorithm exploits the information provided by differences in the radar response at different frequency bands in relation to changes in the snow morphology. The inversion scheme is based on a statistical relation between the radar simulations and the properties of snow calculated from in-cloud sampling.
Ruhi S. Humphries, Melita D. Keywood, Sean Gribben, Ian M. McRobert, Jason P. Ward, Paul Selleck, Sally Taylor, James Harnwell, Connor Flynn, Gourihar R. Kulkarni, Gerald G. Mace, Alain Protat, Simon P. Alexander, and Greg McFarquhar
Atmos. Chem. Phys., 21, 12757–12782, https://doi.org/10.5194/acp-21-12757-2021, https://doi.org/10.5194/acp-21-12757-2021, 2021
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The Southern Ocean region is one of the most pristine in the world and serves as an important proxy for the pre-industrial atmosphere. Improving our understanding of the natural processes in this region is likely to result in the largest reductions in the uncertainty of climate and earth system models. In this paper we present a statistical summary of the latitudinal gradient of aerosol and cloud condensation nuclei concentrations obtained from five voyages spanning the Southern Ocean.
Jack B. Simmons, Ruhi S. Humphries, Stephen R. Wilson, Scott D. Chambers, Alastair G. Williams, Alan D. Griffiths, Ian M. McRobert, Jason P. Ward, Melita D. Keywood, and Sean Gribben
Atmos. Chem. Phys., 21, 9497–9513, https://doi.org/10.5194/acp-21-9497-2021, https://doi.org/10.5194/acp-21-9497-2021, 2021
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Aerosols have a climate forcing effect in the Earth's atmosphere. Few measurements exist of aerosols in the Southern Ocean, a region key to our understanding of this effect. In this study, aerosol measurements from a summer 2017 campaign in the East Antarctic seasonal ice zone are examined. Higher concentrations of aerosols were found in dry air with origins from above the Antarctic continent compared to other periods of the voyage.
Ashok K. Luhar, Ian E. Galbally, Matthew T. Woodhouse, and Nathan Luke Abraham
Atmos. Chem. Phys., 21, 7053–7082, https://doi.org/10.5194/acp-21-7053-2021, https://doi.org/10.5194/acp-21-7053-2021, 2021
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Lightning-generated nitrogen oxides (LNOx) greatly influence tropospheric photochemistry. The most common parameterisation of lightning flash rate used to calculate LNOx in global composition models underestimates measurements over the ocean by a factor of 20–25. We formulate and validate an alternative parameterisation to remedy this problem. The new scheme causes an increase in the ozone burden by 8.5 % and the hydroxyl radical by 13 %, and these have implications for climate and air quality.
Sonya L. Fiddes, Matthew T. Woodhouse, Todd P. Lane, and Robyn Schofield
Atmos. Chem. Phys., 21, 5883–5903, https://doi.org/10.5194/acp-21-5883-2021, https://doi.org/10.5194/acp-21-5883-2021, 2021
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Coral reefs are known to produce the aerosol precursor dimethyl sulfide (DMS). Currently, this source of coral DMS is unaccounted for in climate modelling, and the impact of coral reef extinction on aerosol and climate is unknown. In this study, we address this problem using a coupled chemistry–climate model for the first time. We find that coral reefs make a minimal contribution to the aerosol population and are unlikely to play a role in climate modulation.
Kevin J. Sanchez, Gregory C. Roberts, Georges Saliba, Lynn M. Russell, Cynthia Twohy, J. Michael Reeves, Ruhi S. Humphries, Melita D. Keywood, Jason P. Ward, and Ian M. McRobert
Atmos. Chem. Phys., 21, 3427–3446, https://doi.org/10.5194/acp-21-3427-2021, https://doi.org/10.5194/acp-21-3427-2021, 2021
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Measurements of particles and their properties were made from aircraft over the Southern Ocean. Aerosol transported from the Antarctic coast is shown to greatly enhance particle concentrations over the Southern Ocean. The occurrence of precipitation was shown to be associated with the lowest particle concentrations over the Southern Ocean. These particles are important due to their ability to enhance cloud droplet concentrations, resulting in more sunlight being reflected by the clouds.
Bo Zhang, Hongyu Liu, James H. Crawford, Gao Chen, T. Duncan Fairlie, Scott Chambers, Chang-Hee Kang, Alastair G. Williams, Kai Zhang, David B. Considine, Melissa P. Sulprizio, and Robert M. Yantosca
Atmos. Chem. Phys., 21, 1861–1887, https://doi.org/10.5194/acp-21-1861-2021, https://doi.org/10.5194/acp-21-1861-2021, 2021
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We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn emissions and characterize convective transport in the model. We demonstrate the potential of a customized global 222Rn emission scenario to improve simulated surface 222Rn concentrations and seasonality. We assess convective transport using observed 222Rn vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
Robert Jackson, Scott Collis, Valentin Louf, Alain Protat, Die Wang, Scott Giangrande, Elizabeth J. Thompson, Brenda Dolan, and Scott W. Powell
Atmos. Meas. Tech., 14, 53–69, https://doi.org/10.5194/amt-14-53-2021, https://doi.org/10.5194/amt-14-53-2021, 2021
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About 4 years of 2D video disdrometer data in Darwin are used to develop and validate rainfall retrievals for tropical convection in C- and X-band radars in Darwin. Using blended techniques previously used for Colorado and Manus and Gan islands, with modified coefficients in each estimator, provided the most optimal results. Using multiple radar observables to develop a rainfall retrieval provided a greater advantage than using a single observable, including using specific attenuation.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Robert G. Ryan, Jeremy D. Silver, Richard Querel, Dan Smale, Steve Rhodes, Matt Tully, Nicholas Jones, and Robyn Schofield
Atmos. Meas. Tech., 13, 6501–6519, https://doi.org/10.5194/amt-13-6501-2020, https://doi.org/10.5194/amt-13-6501-2020, 2020
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Models have identified Australasia as a formaldehyde (HCHO) hotspot from vegetation sources, but few measurement studies exist to verify this. We compare, and find good agreement between, HCHO measurements using three – two ground-based and one satellite-based – different spectroscopic techniques in Australia and New Zealand. This gives confidence in using satellite observations to study HCHO and associated air chemistry and pollution problems in this under-studied part of the world.
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Short summary
Coral reefs have been found to produce the climatically relevant chemical compound dimethyl sulfide (DMS). It has been suggested that corals can modify their environment via the production of DMS. We use an atmospheric chemistry model to test this theory at a regional scale for the first time. We find that it is unlikely that coral-reef-derived DMS has an influence over local climate, in part due to the proximity to terrestrial and anthropogenic aerosol sources.
Coral reefs have been found to produce the climatically relevant chemical compound dimethyl...
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