Articles | Volume 21, issue 8
https://doi.org/10.5194/acp-21-5883-2021
© Author(s) 2021. 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-21-5883-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Coral-reef-derived dimethyl sulfide and the climatic impact of the loss of coral reefs
Australian-German Climate and Energy College, University of Melbourne, Parkville, Australia
ARC Centre of Excellence for Climate System Science, School of Earth Sciences, University of Melbourne, Parkville, Australia
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
now at: Australian Antarctic Program Partnership, Institute of Marine and Antarctic Studies, University of Tasmania, Hobart, Australia
Matthew T. Woodhouse
Climate Science Centre, Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Australia
Todd P. Lane
ARC Centre of Excellence for Climate Extremes, School of Earth Sciences, University of Melbourne, Parkville, Australia
Robyn Schofield
ARC Centre of Excellence for Climate Extremes, School of Earth Sciences, University of Melbourne, Parkville, Australia
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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
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This manuscript defines as a list of variables and scientific opportunities which are requested from the CMIP7 Assessment Fast Track to address open atmospheric science questions. The list reflects the output of a large public community engagement effort, coordinated across autumn 2025 through to summer 2025.
Sonya L. Fiddes, Matthew T. Woodhouse, Marc D. Mallet, Liam Lamprey, Ruhi S. Humphries, Alain Protat, Simon P. Alexander, Hakase Hayashida, Samuel G. Putland, Branka Miljevic, and Robyn Schofield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3125, https://doi.org/10.5194/egusphere-2024-3125, 2024
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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.
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.
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.
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.
Sonya L. Fiddes, Matthew T. Woodhouse, Steve Utembe, Robyn Schofield, Simon P. Alexander, Joel Alroe, Scott D. Chambers, Zhenyi Chen, Luke Cravigan, Erin Dunne, Ruhi S. Humphries, Graham Johnson, Melita D. Keywood, Todd P. Lane, Branka Miljevic, Yuko Omori, Alain Protat, Zoran Ristovski, Paul Selleck, Hilton B. Swan, Hiroshi Tanimoto, Jason P. Ward, and Alastair G. Williams
Atmos. Chem. Phys., 22, 2419–2445, https://doi.org/10.5194/acp-22-2419-2022, https://doi.org/10.5194/acp-22-2419-2022, 2022
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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.
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
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This manuscript defines as a list of variables and scientific opportunities which are requested from the CMIP7 Assessment Fast Track to address open atmospheric science questions. The list reflects the output of a large public community engagement effort, coordinated across autumn 2025 through to summer 2025.
Sonya L. Fiddes, Matthew T. Woodhouse, Marc D. Mallet, Liam Lamprey, Ruhi S. Humphries, Alain Protat, Simon P. Alexander, Hakase Hayashida, Samuel G. Putland, Branka Miljevic, and Robyn Schofield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3125, https://doi.org/10.5194/egusphere-2024-3125, 2024
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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.
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.
Robert G. Ryan, Lilani Toms-Hardman, Alexander Smirnov, Daniel Harrison, and Robyn Schofield
EGUsphere, https://doi.org/10.5194/egusphere-2024-1111, https://doi.org/10.5194/egusphere-2024-1111, 2024
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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.
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.
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.
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.
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
Short summary
Short summary
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.
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.
Sonya L. Fiddes, Matthew T. Woodhouse, Steve Utembe, Robyn Schofield, Simon P. Alexander, Joel Alroe, Scott D. Chambers, Zhenyi Chen, Luke Cravigan, Erin Dunne, Ruhi S. Humphries, Graham Johnson, Melita D. Keywood, Todd P. Lane, Branka Miljevic, Yuko Omori, Alain Protat, Zoran Ristovski, Paul Selleck, Hilton B. Swan, Hiroshi Tanimoto, Jason P. Ward, and Alastair G. Williams
Atmos. Chem. Phys., 22, 2419–2445, https://doi.org/10.5194/acp-22-2419-2022, https://doi.org/10.5194/acp-22-2419-2022, 2022
Short summary
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.
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.
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 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.
Coral reefs are known to produce the aerosol precursor dimethyl sulfide (DMS). Currently, this...
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