Articles | Volume 21, issue 9
https://doi.org/10.5194/acp-21-7053-2021
© 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-21-7053-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 May 2021
Research article |
| 10 May 2021
| 10 May 2021
Assessing and improving cloud-height-based parameterisations of global lightning flash rate, and their impact on lightning-produced NOx and tropospheric composition in a chemistry–climate model
CSIRO Oceans and Atmosphere, Aspendale, Australia
Ian E. Galbally
CSIRO Oceans and Atmosphere, Aspendale, Australia
Matthew T. Woodhouse
CSIRO Oceans and Atmosphere, Aspendale, Australia
Nathan Luke Abraham
National Centre for Atmospheric Science, Department of Chemistry,
University of Cambridge, Cambridge, UK
Department of Chemistry, University of Cambridge, Cambridge, UK
Related authors
Ashok K. Luhar, Anthony C. Jones, and Jonathan M. Wilkinson
Atmos. Chem. Phys., 24, 14005–14028, https://doi.org/10.5194/acp-24-14005-2024, https://doi.org/10.5194/acp-24-14005-2024, 2024
Short summary
Short summary
Nitrate aerosol is often omitted in global chemistry–climate models, partly due to the chemical complexity of its formation process. Using a global model, we show that including nitrate aerosol significantly impacts tropospheric composition fields, such as ozone, and radiation. Additionally, lightning-generated oxides of nitrogen influence both nitrate aerosol mass concentrations and aerosol size distribution, which has important implications for radiative fluxes and indirect aerosol effects.
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
Short summary
Short summary
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.
Ashok K. Luhar, David M. Etheridge, Zoë M. Loh, Julie Noonan, Darren Spencer, Lisa Smith, and Cindy Ong
Atmos. Chem. Phys., 20, 15487–15511, https://doi.org/10.5194/acp-20-15487-2020, https://doi.org/10.5194/acp-20-15487-2020, 2020
Short summary
Short summary
With the sharp rise in coal seam gas (CSG) production in Queensland’s Surat Basin, there is much interest in quantifying methane emissions from this area and from unconventional gas production in general. We develop and apply a regional Bayesian inverse model that uses hourly methane concentration data from two sites and modelled backward dispersion to quantify emissions. The model requires a narrow prior and suggests that the emissions from the CSG areas are 33% larger than bottom-up estimates.
Xu-Cheng He, Nathan Luke Abraham, Han Ding, Maria R. Russo, Daniel P. Grosvenor, Yao Ge, Xuemei Wang, Anthony C. Jones, Pedro Campuzano-Jost, Benjamin Nault, Agnieszka Kupc, Donald Blake, Jose L. Jimenez, Christina J. Williamson, Kenneth S. Carslaw, James Weber, Alexander T. Archibald, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2025-3700, https://doi.org/10.5194/egusphere-2025-3700, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Aerosols affect clouds and climate. However, current climate models still struggle to simulate them accurately. We used aircraft data from a global mission to evaluate how well the UK Earth System Model represents aerosols and their precursors. Our results show that the model misses key formation processes in clean ocean regions, suggesting that future improvements should focus on better representing how aerosols form naturally in the atmosphere.
William J. Collins, Fiona M. O'Connor, Rachael E. Byrom, Øivind Hodnebrog, Patrick Jöckel, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
Atmos. Chem. Phys., 25, 9031–9060, https://doi.org/10.5194/acp-25-9031-2025, https://doi.org/10.5194/acp-25-9031-2025, 2025
Short summary
Short summary
We used 7 climate models that include atmospheric chemistry and find that in a scenario with weak controls on air quality, the warming effects (over 2015 to 2050) of decreases in ozone-depleting substances and increases in air quality pollutants are approximately equal and would make ozone the second highest contributor to warming over this period. We find that for stratospheric ozone recovery, the standard measure of climate effects underestimates a more comprehensive measure.
Megan A. J. Brown, Nicola J . Warwick, Nathan Luke Abraham, Paul T. Griffiths, Steve T. Rumbold, Gerd A. Folberth, Fiona M. O'Connor, and Alex T. Archibald
EGUsphere, https://doi.org/10.5194/egusphere-2025-2676, https://doi.org/10.5194/egusphere-2025-2676, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Hydrogen (H2) is an indirect greenhouse gas by increasing methane (CH4) lifetime. Interaction between H2 and CH4 is important for hydrogen’s global warming potential (GWP). Global models do not represent this interaction well; H2 or CH4 are prescribed at the surface. We implement an interactive H2 scheme into a global model coupled with interactive CH4. We simulate scenarios demonstrating its capability, improving model performance and more accurately representing H2-CH4 interaction.
Lauren R. Marshall, Anja Schmidt, Andrew P. Schurer, Nathan Luke Abraham, Lucie J. Lücke, Rob Wilson, Kevin J. Anchukaitis, Gabriele C. Hegerl, Ben Johnson, Bette L. Otto-Bliesner, Esther C. Brady, Myriam Khodri, and Kohei Yoshida
Clim. Past, 21, 161–184, https://doi.org/10.5194/cp-21-161-2025, https://doi.org/10.5194/cp-21-161-2025, 2025
Short summary
Short summary
Large volcanic eruptions have caused temperature deviations over the past 1000 years; however, climate model results and reconstructions of surface cooling using tree rings do not match. We explore this mismatch using the latest models and find a better match to tree-ring reconstructions for some eruptions. Our results show that the way in which eruptions are simulated in models matters for the comparison to tree-rings, particularly regarding the spatial spread of volcanic aerosol.
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025, https://doi.org/10.5194/essd-17-135-2025, 2025
Short summary
Short summary
Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
Short summary
Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Ashok K. Luhar, Anthony C. Jones, and Jonathan M. Wilkinson
Atmos. Chem. Phys., 24, 14005–14028, https://doi.org/10.5194/acp-24-14005-2024, https://doi.org/10.5194/acp-24-14005-2024, 2024
Short summary
Short summary
Nitrate aerosol is often omitted in global chemistry–climate models, partly due to the chemical complexity of its formation process. Using a global model, we show that including nitrate aerosol significantly impacts tropospheric composition fields, such as ozone, and radiation. Additionally, lightning-generated oxides of nitrogen influence both nitrate aerosol mass concentrations and aerosol size distribution, which has important implications for radiative fluxes and indirect aerosol effects.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev., 16, 6187–6209, https://doi.org/10.5194/gmd-16-6187-2023, https://doi.org/10.5194/gmd-16-6187-2023, 2023
Short summary
Short summary
Development and performance of the new DEST chemistry scheme of UM–UKCA is described. The scheme extends the standard StratTrop scheme by including important updates to the halogen chemistry, thus allowing process-oriented studies of stratospheric ozone depletion and recovery, including impacts from both controlled long-lived ozone-depleting substances and emerging issues around uncontrolled, very short-lived substances. It will thus aid studies in support of future ozone assessment reports.
Maria Rosa Russo, Brian John Kerridge, Nathan Luke Abraham, James Keeble, Barry Graham Latter, Richard Siddans, James Weber, Paul Thomas Griffiths, John Adrian Pyle, and Alexander Thomas Archibald
Atmos. Chem. Phys., 23, 6169–6196, https://doi.org/10.5194/acp-23-6169-2023, https://doi.org/10.5194/acp-23-6169-2023, 2023
Short summary
Short summary
Tropospheric ozone is an important component of the Earth system as it can affect both climate and air quality. In this work we use observed tropospheric ozone derived from satellite observations and compare it to tropospheric ozone from model simulations. Our aim is to investigate recent changes (2005–2018) in tropospheric ozone in the North Atlantic region and to understand what factors are driving such changes.
Scott Archer-Nicholls, Rachel Allen, Nathan L. Abraham, Paul T. Griffiths, and Alex T. Archibald
Atmos. Chem. Phys., 23, 5801–5813, https://doi.org/10.5194/acp-23-5801-2023, https://doi.org/10.5194/acp-23-5801-2023, 2023
Short summary
Short summary
The nitrate radical is a major oxidant at nighttime, but much less is known about it than about the other oxidants ozone and OH. We use Earth system model calculations to show how the nitrate radical has changed in abundance from 1850–2014 and to 2100 under a range of different climate and emission scenarios. Depending on the emissions and climate scenario, significant increases are projected with implications for the oxidation of volatile organic compounds and the formation of fine aerosol.
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.
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
Short summary
Short summary
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.
Ewa M. Bednarz, Ryan Hossaini, Martyn P. Chipperfield, N. Luke Abraham, and Peter Braesicke
Atmos. Chem. Phys., 22, 10657–10676, https://doi.org/10.5194/acp-22-10657-2022, https://doi.org/10.5194/acp-22-10657-2022, 2022
Short summary
Short summary
Atmospheric impacts of chlorinated very short-lived substances (Cl-VSLS) over the first two decades of the 21st century are assessed using the UM-UKCA chemistry–climate model. Stratospheric input of Cl from Cl-VSLS is estimated at ~130 ppt in 2019. The use of model set-up with constrained meteorology significantly increases the abundance of Cl-VSLS in the lower stratosphere relative to the free-running set-up. The growth in Cl-VSLS emissions significantly impacted recent HCl and COCl2 trends.
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.
Anthony C. Jones, Adrian Hill, Samuel Remy, N. Luke Abraham, Mohit Dalvi, Catherine Hardacre, Alan J. Hewitt, Ben Johnson, Jane P. Mulcahy, and Steven T. Turnock
Atmos. Chem. Phys., 21, 15901–15927, https://doi.org/10.5194/acp-21-15901-2021, https://doi.org/10.5194/acp-21-15901-2021, 2021
Short summary
Short summary
Ammonium nitrate is hard to model because it forms and evaporates rapidly. One approach is to relate its equilibrium concentration to temperature, humidity, and the amount of nitric acid and ammonia gases. Using this approach, we limit the rate at which equilibrium is reached using various condensation rates in a climate model. We show that ammonium nitrate concentrations are highly sensitive to the condensation rate. Our results will help improve the representation of nitrate in climate models.
James Weber, Scott Archer-Nicholls, Nathan Luke Abraham, Youngsub M. Shin, Thomas J. Bannan, Carl J. Percival, Asan Bacak, Paulo Artaxo, Michael Jenkin, M. Anwar H. Khan, Dudley E. Shallcross, Rebecca H. Schwantes, Jonathan Williams, and Alex T. Archibald
Geosci. Model Dev., 14, 5239–5268, https://doi.org/10.5194/gmd-14-5239-2021, https://doi.org/10.5194/gmd-14-5239-2021, 2021
Short summary
Short summary
The new mechanism CRI-Strat 2 features state-of-the-art isoprene chemistry not previously available in UKCA and improves UKCA's ability to reproduce observed concentrations of isoprene, monoterpenes, and OH in tropical regions. The enhanced ability to model isoprene, the most widely emitted non-methane volatile organic compound (VOC), will allow understanding of how isoprene and other biogenic VOCs affect atmospheric composition and, through biosphere–atmosphere feedbacks, climate change.
John Staunton-Sykes, Thomas J. Aubry, Youngsub M. Shin, James Weber, Lauren R. Marshall, Nathan Luke Abraham, Alex Archibald, and Anja Schmidt
Atmos. Chem. Phys., 21, 9009–9029, https://doi.org/10.5194/acp-21-9009-2021, https://doi.org/10.5194/acp-21-9009-2021, 2021
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
Short summary
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.
Ananth Ranjithkumar, Hamish Gordon, Christina Williamson, Andrew Rollins, Kirsty Pringle, Agnieszka Kupc, Nathan Luke Abraham, Charles Brock, and Ken Carslaw
Atmos. Chem. Phys., 21, 4979–5014, https://doi.org/10.5194/acp-21-4979-2021, https://doi.org/10.5194/acp-21-4979-2021, 2021
Short summary
Short summary
The effect aerosols have on climate can be better understood by studying their vertical and spatial distribution throughout the atmosphere. We use observation data from the ATom campaign and evaluate the vertical profile of aerosol number concentration, sulfur dioxide and condensation sink using the UKESM (UK Earth System Model). We identify uncertainties in key atmospheric processes that help improve their theoretical representation in global climate models.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
Short summary
Short summary
We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Peter Sherman, Meng Gao, Shaojie Song, Alex T. Archibald, Nathan Luke Abraham, Jean-François Lamarque, Drew Shindell, Gregory Faluvegi, and Michael B. McElroy
Atmos. Chem. Phys., 21, 3593–3605, https://doi.org/10.5194/acp-21-3593-2021, https://doi.org/10.5194/acp-21-3593-2021, 2021
Short summary
Short summary
The aims here are to assess the role of aerosols in India's monsoon precipitation and to determine the relative contributions from Chinese and Indian emissions using CMIP6 models. We find that increased sulfur emissions reduce precipitation, which is primarily dynamically driven due to spatial shifts in convection over the region. A significant increase in precipitation (up to ~ 20 %) is found only when both Indian and Chinese sulfate emissions are regulated.
Fiona M. O'Connor, N. Luke Abraham, Mohit Dalvi, Gerd A. Folberth, Paul T. Griffiths, Catherine Hardacre, Ben T. Johnson, Ron Kahana, James Keeble, Byeonghyeon Kim, Olaf Morgenstern, Jane P. Mulcahy, Mark Richardson, Eddy Robertson, Jeongbyn Seo, Sungbo Shim, João C. Teixeira, Steven T. Turnock, Jonny Williams, Andrew J. Wiltshire, Stephanie Woodward, and Guang Zeng
Atmos. Chem. Phys., 21, 1211–1243, https://doi.org/10.5194/acp-21-1211-2021, https://doi.org/10.5194/acp-21-1211-2021, 2021
Short summary
Short summary
This paper calculates how changes in emissions and/or concentrations of different atmospheric constituents since the pre-industrial era have altered the Earth's energy budget at the present day using a metric called effective radiative forcing. The impact of land use change is also assessed. We find that individual contributions do not add linearly, and different Earth system interactions can affect the magnitude of the calculated effective radiative forcing.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
Short summary
Short summary
This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
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
Short summary
Short summary
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.
Ashok K. Luhar, David M. Etheridge, Zoë M. Loh, Julie Noonan, Darren Spencer, Lisa Smith, and Cindy Ong
Atmos. Chem. Phys., 20, 15487–15511, https://doi.org/10.5194/acp-20-15487-2020, https://doi.org/10.5194/acp-20-15487-2020, 2020
Short summary
Short summary
With the sharp rise in coal seam gas (CSG) production in Queensland’s Surat Basin, there is much interest in quantifying methane emissions from this area and from unconventional gas production in general. We develop and apply a regional Bayesian inverse model that uses hourly methane concentration data from two sites and modelled backward dispersion to quantify emissions. The model requires a narrow prior and suggests that the emissions from the CSG areas are 33% larger than bottom-up estimates.
Sandip S. Dhomse, Graham W. Mann, Juan Carlos Antuña Marrero, Sarah E. Shallcross, Martyn P. Chipperfield, Kenneth S. Carslaw, Lauren Marshall, N. Luke Abraham, and Colin E. Johnson
Atmos. Chem. Phys., 20, 13627–13654, https://doi.org/10.5194/acp-20-13627-2020, https://doi.org/10.5194/acp-20-13627-2020, 2020
Short summary
Short summary
We confirm downward adjustment of SO2 emission to simulate the Pinatubo aerosol cloud with aerosol microphysics models. Similar adjustment is also needed to simulate the El Chichón and Agung volcanic cloud, indicating potential missing removal or vertical redistribution process in models. Important inhomogeneities in the CMIP6 forcing datasets after Agung and El Chichón eruptions are difficult to reconcile. Quasi-biennial oscillation plays an important role in modifying stratospheric warming.
Andrew Orr, J. Scott Hosking, Aymeric Delon, Lars Hoffmann, Reinhold Spang, Tracy Moffat-Griffin, James Keeble, Nathan Luke Abraham, and Peter Braesicke
Atmos. Chem. Phys., 20, 12483–12497, https://doi.org/10.5194/acp-20-12483-2020, https://doi.org/10.5194/acp-20-12483-2020, 2020
Short summary
Short summary
Polar stratospheric clouds (PSCs) are clouds found in the Antarctic winter stratosphere and are implicated in the formation of the ozone hole. These clouds can sometimes be formed or enhanced by mountain waves, formed as air passes over hills or mountains. However, this important mechanism is missing in coarse-resolution climate models, limiting our ability to simulate ozone. This study examines an attempt to include the effects of mountain waves and their impact on PSCs and ozone.
Cited articles
Abraham, N. L., Archibald, A. T., Bellouin, N., Boucher, O., Braesicke, P.,
Bushell, A., Carslaw, K. S., Collins, W., Dalvi, M., Emmerson, K. M.,
Folberth, G., Haywood, J., Johnson, C., Kipling, Z., Macintyre, H., Mann, G.
W., Telford, P. J., Merikanto, J., Morgenstern, O., O'Connor, F., Ordonez,
C., Osprey, S., Pringle, K. J., Pyle, J. A., Rae, J. G. L., Reddington, C.
L., Savage, D., Spracklen, D., Stier, P., and West, R.: Unified Model
Documentation Paper No. 84, available at: http://www.ukca.ac.uk/images/b/b1/Umdp_084-umdp84.pdf (last access: 6 May 2021),
United Kingdom Chemistry and Aerosol (UKCA) Technical Description MetUM
Version 8.4. UK Met Office, Exeter (UK), pp. 74, 2012.
Allen, D. J. and Pickering, K. E.: Evaluation of lightning flash rate
parameterizations for use in a global chemical transport model, J. Geophys.
Res., 107, 4711, https://doi.org/10.1029/2002JD002066, 2002.
Allen, D. J., Pickering, K. E., Bucsela, E., Krotkov, N., and Holzworth, R.:
Lightning NOx production in the tropics as determined using OMI
NO2 retrievals and WWLLN stroke data, J. Geophys. Res.-Atmos., 124,
13498–13518, https://doi.org/10.1029/2018JD029824, 2019.
Archibald, A. T., O'Connor, F. M., Abraham, N. L., Archer-Nicholls, S., Chipperfield, M. P., Dalvi, M., Folberth, G. A., Dennison, F., Dhomse, S. S., Griffiths, P. T., Hardacre, C., Hewitt, A. J., Hill, R. S., Johnson, C. E., Keeble, J., Köhler, M. O., Morgenstern, O., Mulcahy, J. P., Ordóñez, C., Pope, R. J., Rumbold, S. T., Russo, M. R., Savage, N. H., Sellar, A., Stringer, M., Turnock, S. T., Wild, O., and Zeng, G.: Description and evaluation of the UKCA stratosphere–troposphere chemistry scheme (StratTrop vn 1.0) implemented in UKESM1, Geosci. Model Dev., 13, 1223–1266, https://doi.org/10.5194/gmd-13-1223-2020, 2020.
Banerjee, A., Archibald, A. T., Maycock, A. C., Telford, P., Abraham, N. L., Yang, X., Braesicke, P., and Pyle, J. A.: Lightning NOx, a key chemistry–climate interaction: impacts of future climate change and consequences for tropospheric oxidising capacity, Atmos. Chem. Phys., 14, 9871–9881, https://doi.org/10.5194/acp-14-9871-2014, 2014.
Banerjee, A., Maycock, A. C., and Pyle, J. A.: Chemical and climatic drivers of radiative forcing due to changes in stratospheric and tropospheric ozone over the 21st century, Atmos. Chem. Phys., 18, 2899–2911, https://doi.org/10.5194/acp-18-2899-2018, 2018.
Barthe, C. and Barth, M. C.: Evaluation of a new lightning-produced NOx parameterization for cloud resolving models and its associated uncertainties, Atmos. Chem. Phys., 8, 4691–4710, https://doi.org/10.5194/acp-8-4691-2008, 2008.
Bi, D. H., Dix, M., Marsland, S. J., O'Farrell, S., Rashid, H. A., Uotila,
P., Hirst, A. C., Kowalczyk, E., Golebiewski, M., Sullivan, A., Yan, H. L.,
Hannah, N., Franklin, C., Sun, Z. A., Vohralik, P., Watterson, I., Zhou, X.
B., Fiedler, R., Collier, M., Ma, Y. M., Noonan, J., Stevens, L., Uhe, P.,
Zhu, H. Y., Griffies, S. M., Hill, R., Harris, C., and Puri, K.: The ACCESS
coupled model: description, control climate and evaluation, Aust.
Meteorol. Ocean., 63, 41–64, 2013.
Boccippio, D. J.: Lightning scaling relations revisited, J. Atmos. Sci., 59,
1086–1104, https://doi.org/10.1175/1520-0469(2002)059<1086:LSRR>2.0.CO;2, 2002.
Boccippio, D. J., Cummins, K. L., Christian, H. J., and Goodman, S. J.:
Combined satellite- and surface-based estimation of the
intracloud-cloud-to-ground lightning ratio over the continental United
States, Mon. Weather Rev., 129, 108–122, https://doi.org/10.1175/WAF-D-10-05026.1, 2001.
Boersma, K. F., Eskes, H. J., Meijer, E. W., and Kelder, H. M.: Estimates of lightning NOx production from GOME satellite observations, Atmos. Chem. Phys., 5, 2311–2331, https://doi.org/10.5194/acp-5-2311-2005, 2005.
Boersma, K. F., Van Geffen, J., Eskes, H., Van der A, R., De Smedt, I., Van
Roozendael, M., Yu, H., Richter, A., Peters, E., Beirle, S., Wagner, T.,
Lorente, A., Scanlon, T., Compernolle, S., and Lambert, J.-C.: Product
Specification Document for the QA4ECV NO2 ECV precursor product
(Version 1.1), Project Number 607405, Deliverable D4.6, Royal Netherlands
Meteorological Institute (KNMI), 32 pp., available at:
http://temis.nl/qa4ecv/no2col/QA4ECV_NO2_PSD_v1.1.compressed.pdf (last access: 6 May 2021), 2017.
Boersma, K. F., Eskes, H. J., Richter, A., De Smedt, I., Lorente, A., Beirle, S., van Geffen, J. H. G. M., Zara, M., Peters, E., Van Roozendael, M., Wagner, T., Maasakkers, J. D., van der A, R. J., Nightingale, J., De Rudder, A., Irie, H., Pinardi, G., Lambert, J.-C., and Compernolle, S. C.: Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project, Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, 2018.
Bond, D. W., Steiger, S., Zhang, R., Tie, X., and Orville, R. E.: The
importance of NOx production by lightning in the tropics, Atmos.
Environ., 36, 1509–1519, https://doi.org/10.1016/S1352-2310(01)00553-2, 2002.
Bucsela, E., Pickering, K. E., Allen, D., Holzworth, R., and Krotkov, N.:
Midlatitude lightning NOx production efficiency inferred from OMI and
WWLLN data. J. Geophys. Res.-Atmos., 124, 13475–13497,
https://doi.org/10.1029/2019JD030561, 2019.
Butkovskaya, N., Kukui, A., and Le Bras, G.: HNO3 Forming Channel of
the HO2+ NO Reaction as a Function of Pressure and Temperature in
the Ranges of 72–600 Torr and 223–323 K, Phys. Chem. A, 111, 9047–9053,
https://doi.org/10.1021/jp074117m, 2007.
Carpenter, L. J., Monks, P. S., Bandy, B. J., Penkett, S. A., Galbally, I.
E., and Meyer, C. P.: A study of peroxy radicals and ozone photochemistry at
coastal sites in the northern and southern hemispheres, J. Geophys. Res., 102,
25417–25427, https://doi.org/10.1029/97JD02242, 1997.
Cecil, D. J., Buechler, D. E., and Blakeslee, R. J.: Gridded lightning
climatology from TRMM-LIS and OTD: Dataset description, Atmos. Res.,
135–136, 404–414, https://doi.org/10.1016/j.atmosres.2012.06.028, 2014.
Choi, Y., Wang, Y., Zeng, T., Martin, R. V., Kurosu, T. P., and Chance, K.:
Evidence of lightning NOx and convective transport of pollutants in
satellite observations over North America, Geophys. Res. Lett., 32, L02805,
https://doi.org/10.1029/2004GL021436, 2005.
Clark, S. K., Ward, D. S., and Mahowald, N. M.: Parameterization-based
uncertainty in future lightning flash density, Geophys. Res. Lett., 44,
2893–2901, https://doi.org/10.1002/2017GL073017, 2017.
Cummings, K. A., Huntemann, T. L., Pickering, K. E., Barth, M. C., Skamarock, W. C., Höller, H., Betz, H.-D., Volz-Thomas, A., and Schlager, H.: Cloud-resolving chemistry simulation of a Hector thunderstorm, Atmos. Chem. Phys., 13, 2757–2777, https://doi.org/10.5194/acp-13-2757-2013, 2013.
Dahlmann, K., Grewe, V., Ponater, M., and Matthes, S.: Quantifying the
contributions of individual NOx sources to the trend in ozone radiative
forcing, Atmos. Environ., 45, 2860–2868,
https://doi.org/10.1016/j.atmosenv.2011.02.071, 2011.
DeCaria, A. J., Pickering, K. E., Stenchikov, G. L., and Ott, L. E.:
Lightning-generated NOx and its impact on tropospheric ozone
production: A three-dimensional modeling study of a Stratosphere-Troposphere
Experiment: Radiation, Aerosols and Ozone (STERAO-A) thunderstorm, J.
Geophys. Res., 110, 1–13, https://doi.org/10.1029/2004JD005556, 2005.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J.-N., and Vitarta,
F.: The ERA-Interim reanalysis: configuration and performance of the data
assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011.
Deierling, W. and Petersen, W. A.: Total lightning activity as an indicator
of updraft characteristics, J. Geophys. Res., 113, D16210,
https://doi.org/10.1029/2007JD009598, 2008.
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 Petron, G.: The Chemistry Mechanism in the Community Earth
System Model Version 2 (CESM2), J. Adv. Model. Earth
Sy., 12, e2019MS001882, https://doi.org/10.1029/2019MS001882, 2020.
Esentürk, E., Abraham, N. L., Archer-Nicholls, S., Mitsakou, C., Griffiths, P., Archibald, A., and Pyle, J.: Quasi-Newton methods for atmospheric chemistry simulations: implementation in UKCA UM vn10.8, Geosci. Model Dev., 11, 3089–3108, https://doi.org/10.5194/gmd-11-3089-2018, 2018.
Fehr, T., Höller, H., and Huntrieser, H.: Model study on production and
transport of lightning-produced NOx in a EULINOX supercell storm, J.
Geophys. Res., 109, 1–17, https://doi.org/10.1029/2003JD003935, 2004.
Finney, D. L., Doherty, R. M., Wild, O., Huntrieser, H., Pumphrey, H. C., and Blyth, A. M.: Using cloud ice flux to parametrise large-scale lightning, Atmos. Chem. Phys., 14, 12665–12682, https://doi.org/10.5194/acp-14-12665-2014, 2014.
Finney, D. L., Doherty, R. M., Wild, O., and Abraham, N. L.: The impact of lightning on tropospheric ozone chemistry using a new global lightning parametrisation, Atmos. Chem. Phys., 16, 7507–7522, https://doi.org/10.5194/acp-16-7507-2016, 2016.
Finney, D. L., Doherty, R. M., Wild, O., Stevenson, D. S., MacKenzie, I. A.,
and Blyth, A. M.: A projected decrease in lightning under climate change,
Nat. Clim. Change, 8, 210–213, https://doi.org/10.1038/s41558-018-0072-6, 2018.
Forster, P. M. D. and Shine, K. P.: Radiative forcing and temperature trends
from stratospheric ozone changes, J. Geophys. Res., 102, 10841–10855,
https://doi.org/10.1029/96JD03510, 1997.
Futyan, J. M. and Del Genio, A. D.: Relationships between lightning and
properties of convective cloud clusters, Geophys. Res. Lett., 34,
L15705, https://doi.org/10.1029/2007GL030227, 2007.
Gordillo-Vázquez, F. J., Pérez-Invernón, F. J., Huntrieser, H.,
and Smith, A. K.: Comparison of six lightning parameterizations in CAM5 and
the impact on global atmospheric chemistry, Earth Space Sci., 6,
2317–2346, https://doi.org/10.1029/2019EA000873, 2019.
Gregory, D. and Rowntree, P. R.: A mass flux convection scheme with
representation of cloud ensemble characteristics and stability-dependent
closure, Mon. Weather Rev., 118, 1483–1506,
https://doi.org/10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2,
1990.
Grewe, V.: Impact of climate variability on tropospheric ozone, Sci. Total
Environ., 374, 167–181, https://doi.org/10.1016/j.scitotenv.2007.01.032, 2007.
Grewe, V., Brunner, D., Dameris, M., Grenfell, J. L., Hein, R., Shindell, D.,
and Staehelin, J.: Origin and variability of upper tropospheric nitrogen
oxides and ozone at northern mid-latitudes, Atmos. Environ., 35, 3421–3433,
https://doi.org/10.1016/S1352-2310(01)00134-0, 2001.
Gultepe, I. and Isaac, G. A.: Aircraft observations of cloud droplet number
concentration: Implications for climate studies, Q. J. R. Meteor. Soc.,
130, 2377–2390, https://doi.org/10.1256/qj.03.120, 2004.
Hardiman, S. C., Boutle, I. A., Bushell, A. C., Butchart, N., Cullen, M. J.
P., Field, P. R., Furtado, K., Manners, J. C., Milton, S. F., Morcrette, C.,
O'Connor, F. M., Shipway, B. J., Smith, C., Walters, D. N., Willett, M. R.,
Williams, K. D., Wood, N., Abraham, N. L., Keeble, J., Maycock, A. C.,
Thuburn, J., and Woodhouse, M. T.: Processes controlling tropical tropopause
temperature and stratospheric water vapor in climate models, J. Climate, 28,
6516–6535, https://doi.org/10.1175/JCLI-D-15-0075.1, 2015.
Hassler, B., Bodeker, G. E., Cionni, I., and Dameris, M.: A vertically resolved, monthly mean, ozone database from 1979 to 2100 for constraining global climate model simulations, Int. J. Remote Sens., 30, 4009–4018, https://doi.org/10.1080/01431160902821874, 2009.
Hoerling, M. P., Schaack, T. K., and Lenzen, A. J.: A global analysis of
stratosphere-tropospheric exchange during northern winter, Mon. Weather
Rev., 121, 162–172, https://doi.org/10.1175/1520-0493(1993)121<0162:AGAOSE>2.0.CO;2,
1993.
Hudman, R. C., Jacob, D. J., Turquety, S., Leibensperger, E. M., Murray, L. T., Wu, S., Gilliland, A. B., Avery, M., Bertram, T. H., Brune, W., Cohen, R. C., Dibb, J. E., Flocke, F. M., Fried, A., Holloway, J., Neuman, J. A., Orville, R., Perring, A., Ren, X., Sachse, G. W., Singh, H. B., Swanson, A., and Wooldridge, P.: Surface and lightning
sources of nitrogen oxides over the United States: Magnitudes, chemical
evolution, and outflow, J. Geophys. Res., 112, D12S05,
https://doi.org/10.1029/2006JD007912, 2007.
Huntrieser, H., Schumann, U., Schlager, H., Höller, H., Giez, A., Betz, H.-D., Brunner, D., Forster, C., Pinto Jr., O., and Calheiros, R.: Lightning activity in Brazilian thunderstorms during TROCCINOX: implications for NOx production, Atmos. Chem. Phys., 8, 921–953, https://doi.org/10.5194/acp-8-921-2008, 2008.
Iglesias-Suarez, F., Kinnison, D. E., Rap, A., Maycock, A. C., Wild, O., and Young, P. J.: Key drivers of ozone change and its radiative forcing over the 21st century, Atmos. Chem. Phys., 18, 6121–6139, https://doi.org/10.5194/acp-18-6121-2018, 2018.
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019.
Jöckel, P., Tost, H., Pozzer, A., Brühl, C., Buchholz, J., Ganzeveld, L., Hoor, P., Kerkweg, A., Lawrence, M. G., Sander, R., Steil, B., Stiller, G., Tanarhte, M., Taraborrelli, D., van Aardenne, J., and Lelieveld, J.: The atmospheric chemistry general circulation model ECHAM5/MESSy1: consistent simulation of ozone from the surface to the mesosphere, Atmos. Chem. Phys., 6, 5067–5104, https://doi.org/10.5194/acp-6-5067-2006, 2006.
Klein, S. A., Zhang, Y., Zelinka, M. D., Pincus, R., Boyle, J., and
Gleckler, P. J.: Are climate model simulations of clouds improving? An
evaluation using the ISCCP simulator, J. Geophys. Res.-Atmos., 118,
1329–1342, https://doi.org/10.1002/jgrd.50141, 2013.
Koshak, W. J., Peterson, H., Biazar, A. P., Khan, M., and Wang, L.: The NASA
Lightning Nitrogen Oxides Model (LNOM): application to air quality modeling.
Atmos Res., 135–136, 363–369, https://doi.org/10.1016/j.atmosres.2012.12.015, 2014.
Krause, A., Kloster, S., Wilkenskjeld, S., and Paeth H.: The sensitivity of
global wildfires to simulated past, present, and future lightning frequency,
J. Geophys. Res.-Biogeo., 119, 312–322, https://doi.org/10.1002/2013JG002502, 2014.
Labrador, L. J., von Kuhlmann, R., and Lawrence, M. G.: The effects of lightning-produced NOx and its vertical distribution on atmospheric chemistry: sensitivity simulations with MATCH-MPIC, Atmos. Chem. Phys., 5, 1815–1834, https://doi.org/10.5194/acp-5-1815-2005, 2005.
Lamarque, J.-F., Emmons, L. K., Hess, P. G., Kinnison, D. E., Tilmes, S., Vitt, F., Heald, C. L., Holland, E. A., Lauritzen, P. H., Neu, J., Orlando, J. J., Rasch, P. J., and Tyndall, G. K.: CAM-chem: description and evaluation of interactive atmospheric chemistry in the Community Earth System Model, Geosci. Model Dev., 5, 369–411, https://doi.org/10.5194/gmd-5-369-2012, 2012.
Lauer, A., Dameris, M., Richter, A., and Burrows, J. P.: Tropospheric NO2 columns: a comparison between model and retrieved data from GOME measurements, Atmos. Chem. Phys., 2, 67–78, https://doi.org/10.5194/acp-2-67-2002, 2002.
Lelieveld, J., Gromov, S., Pozzer, A., and Taraborrelli, D.: Global tropospheric hydroxyl distribution, budget and reactivity, Atmos. Chem. Phys., 16, 12477–12493, https://doi.org/10.5194/acp-16-12477-2016, 2016.
Luhar, A. K., Galbally, I. E., Woodhouse, M. T., and Thatcher, M.: An improved parameterisation of ozone dry deposition to the ocean and its impact in a global climate–chemistry model, Atmos. Chem. Phys., 17, 3749–3767, https://doi.org/10.5194/acp-17-3749-2017, 2017.
Luhar, A. K., Woodhouse, M. T., and Galbally, I. E.: A revised global ozone dry deposition estimate based on a new two-layer parameterisation for air–sea exchange and the multi-year MACC composition reanalysis, Atmos. Chem. Phys., 18, 4329–4348, https://doi.org/10.5194/acp-18-4329-2018, 2018.
Luo, C., Wang, Y., and Koshak, W. J.: Development of a self-consistent
lightning NOx simulation in large-scale 3-D models, J. Geophys. Res.-Atmos., 122, 3141–3154, https://doi.org/10.1002/2016JD026225, 2017.
Marais, E. A., Jacob, D. J., Choi, S., Joiner, J., Belmonte-Rivas, M., Cohen, R. C., Beirle, S., Murray, L. T., Schiferl, L. D., Shah, V., and Jaeglé, L.: Nitrogen oxides in the global upper troposphere: interpreting cloud-sliced NO2 observations from the OMI satellite instrument, Atmos. Chem. Phys., 18, 17017–17027, https://doi.org/10.5194/acp-18-17017-2018, 2018.
Martin, R. V., Sauvage, B., Folkins, I., Sioris, C. E., Boone, C., Bernath,
P., and Ziemke, J.: Space-based constraints on the production of nitric
oxide by lightning, J. Geophys. Res., 112, D09309, https://doi.org/10.1029/2006JD007831,
2007.
Michalon, N., Nassif, A., Saouri, T., Royer, J. F., and Pontikis, C. A.:
Contribution to the climatological study of lightning, Geophys. Res. Lett.,
26, 3097–3100, https://doi.org/10.1029/1999GL010837, 1999.
Miyazaki, K., Eskes, H. J., Sudo, K., and Zhang, C.: Global lightning NOx production estimated by an assimilation of multiple satellite data sets, Atmos. Chem. Phys., 14, 3277–3305, https://doi.org/10.5194/acp-14-3277-2014, 2014.
Molinié, J. and Pontikis, C. A.: A climatological study of tropical
thunderstorm clouds and lightning frequencies on the French Guyana coast,
Geophys. Res. Lett., 22, 1085–1088, https://doi.org/10.1029/95GL01036, 1995.
Morgenstern, O., Braesicke, P., O'Connor, F. M., Bushell, A. C., Johnson, C. E., Osprey, S. M., and Pyle, J. A.: Evaluation of the new UKCA climate-composition model – Part 1: The stratosphere, Geosci. Model Dev., 2, 43–57, https://doi.org/10.5194/gmd-2-43-2009, 2009.
Murray, L. T.: Lightning NOx and impacts on air quality, Curr.
Pollut. Rep., 2, 115–133, https://doi.org/10.1007/s40726-016-0031-7, 2016.
Murray, L. T., Jacob, D. J., Logan, J. A., Hudman, R. C., and Koshak, W. J.:
Optimized regional and interannual variability of lightning in a global
chemical transport model constrained by LIS/OTD satellite data, J. Geophys.
Res., 117, D20307, https://doi.org/10.1029/2012JD017934, 2012.
Naik, V., Voulgarakis, A., Fiore, A. M., Horowitz, L. W., Lamarque, J.-F., Lin, M., Prather, M. J., Young, P. J., Bergmann, D., Cameron-Smith, P. J., Cionni, I., Collins, W. J., Dalsøren, S. B., Doherty, R., Eyring, V., Faluvegi, G., Folberth, G. A., Josse, B., Lee, Y. H., MacKenzie, I. A., Nagashima, T., van Noije, T. P. C., Plummer, D. A., Righi, M., Rumbold, S. T., Skeie, R., Shindell, D. T., Stevenson, D. S., Strode, S., Sudo, K., Szopa, S., and Zeng, G.: Preindustrial to present-day changes in tropospheric hydroxyl radical and methane lifetime from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), Atmos. Chem. Phys., 13, 5277–5298, https://doi.org/10.5194/acp-13-5277-2013, 2013.
Nault, B. A., Laughner, J. L.,Wooldridge, P. J., Crounse, J. D., Dibb, J.,
Diskin, G., Peischl, J., Podolske, J. R., Pollack, I. B., Ryerson, T. B.,
Scheuer, E., Wennberg, P. O., and Cohen, R. C.: Lightning NOx
emissions: reconciling measured and modeled estimates with updated NOx
Chemistry, Geophys. Res. Lett., 44, 9479–9488,
https://doi.org/10.1002/2017GL074436, 2017.
Neu, J. L., Prather, M. J., and Penner, J. E.: Global atmospheric chemistry:
Integrating over fractional cloud cover, J. Geophys. Res., 112, D11306,
https://doi.org/10.1029/2006JD008007, 2007.
O'Connor, F. M., Johnson, C. E., Morgenstern, O., Abraham, N. L., Braesicke, P., Dalvi, M., Folberth, G. A., Sanderson, M. G., Telford, P. J., Voulgarakis, A., Young, P. J., Zeng, G., Collins, W. J., and Pyle, J. A.: Evaluation of the new UKCA climate-composition model – Part 2: The Troposphere, Geosci. Model Dev., 7, 41–91, https://doi.org/10.5194/gmd-7-41-2014, 2014.
Ott, L. E., Pickering, K. E., Stenchhikov, G. L., Huntrieser, H., and
Schumann, U.: Effects of lightning NOx production during the 21 July
European Lightning Nitrogen Oxides Project storm studied with a
three-dimensional cloud-scale chemical transport model, J. Geophys. Res.,
112, D05307, https://doi.org/10.1029/2006JD007365, 2007.
Ott, L. E., Pickering, K. E., Stenchikov, G. L., Allen, D. J., DeCaria, A.
J., Ridley, B., Lin, R.-F., Lang, S., and Tao, W.-K.: Production of
lightning NOx and its vertical distribution calculated from
three-dimensional cloud-scale chemical transport model simulations, J.
Geophys. Res., 115, D04301, https://doi.org/10.1029/2009JD011880, 2010.
Pickering, K. E., Wang, Y., Tao, W.-K., Price, C., and Müller, J.-F.:
Vertical distributions of lightning NOx for use in regional and global
chemical transport models, J. Geophys. Res., 103, 31203–31216,
https://doi.org/10.1029/98JD02651, 1998.
Price, C. and Rind, D.: A simple lightning parameterization for calculating
global lightning distributions, J. Geophys. Res.-Atmos., 97, 9919–9933,
https://doi.org/10.1029/92JD00719, 1992.
Price, C. and Rind, D.: What determines the cloud-to-ground lightning
fraction in thunderstorms?, Geophys. Res. Lett., 20, 463–466, https://doi.org/10.1029/93GL00226, 1993.
Price, C. and Rind, D.: Modeling global lightning distributions in a general
circulation model, Mon. Weather Rev., 122, 1930–1939, https://doi.org/10.1175/1520-0493(1994)122<1930:MGLDIA>2.0.CO;2, 1994.
Price, C., Penner, J., and Prather, M.: NOx from lightning. 1. Global
distribution based on lightning physics, J. Geophys. Res., 102, 5929–5941,
https://doi.org/10.1029/96JD03504, 1997.
Ridley, B. A., Pickering, K. E., and Dye, J. E.: Comments on the
parameterization of lightning-produced NO in global chemistry-transport
models, Atmos. Environ., 39, 6184–6187, https://doi.org/10.1016/j.atmosenv.2005.06.054, 2005.
Romps, D. M., Seeley, J. T., Vollaro, D., and Molinari, J.: Projected
increase in lightning strikes in the United States due to global warming,
Science, 346, 851–854, https://doi.org/10.1126/science.1259100, 2014.
Rosenfeld, D. and Lensky, I. M.: Satellite-based insights into precipitation
formation processes in continental and maritime convective clouds, B.
Am. Meteorol. Soc., 79, 2457–2476, https://doi.org/10.1175/1520-0477(1998)079<2457:SBIIPF>2.0.CO;2, 1998.
Schumann, U. and Huntrieser, H.: The global lightning-induced nitrogen oxides source, Atmos. Chem. Phys., 7, 3823–3907, https://doi.org/10.5194/acp-7-3823-2007, 2007.
Telford, P. J., Abraham, N. L., Archibald, A. T., Braesicke, P., Dalvi, M., Morgenstern, O., O'Connor, F. M., Richards, N. A. D., and Pyle, J. A.: Implementation of the Fast-JX Photolysis scheme (v6.4) into the UKCA component of the MetUM chemistry-climate model (v7.3), Geosci. Model Dev., 6, 161–177, https://doi.org/10.5194/gmd-6-161-2013, 2013.
Tost, H., Jöckel, P., and Lelieveld, J.: Lightning and convection parameterisations – uncertainties in global modelling, Atmos. Chem. Phys., 7, 4553–4568, https://doi.org/10.5194/acp-7-4553-2007, 2007.
Uhe, P. and Thatcher, M.: A spectral nudging method for the ACCESS1.3 atmospheric model, Geosci. Model Dev., 8, 1645–1658, https://doi.org/10.5194/gmd-8-1645-2015, 2015.
Ushio, T., Heckman, S. J., Boccippio, D. J., Christian, H. J., and Kawasaki,
Z.-I.: A survey of thunderstorm flash rates compared to cloud top height
using TRMM satellite data, J. Geophys. Res., 106, 24089–24095,
https://doi.org/10.1029/2001JD900233, 2001.
Vonnegut, B.: Some facts and speculation concerning the origin and role of
thunderstorm electricity, in: Severe Local Storms, Meteorological
Monographs, 5, 224–241, American Meteorological Society, Boston, MA,
https://doi.org/10.1007/978-1-940033-56-3_11,
1963.
Walters, D. N., Williams, K. D., Boutle, I. A., Bushell, A. C., Edwards, J. M., Field, P. R., Lock, A. P., Morcrette, C. J., Stratton, R. A., Wilkinson, J. M., Willett, M. R., Bellouin, N., Bodas-Salcedo, A., Brooks, M. E., Copsey, D., Earnshaw, P. D., Hardiman, S. C., Harris, C. M., Levine, R. C., MacLachlan, C., Manners, J. C., Martin, G. M., Milton, S. F., Palmer, M. D., Roberts, M. J., Rodríguez, J. M., Tennant, W. J., and Vidale, P. L.: The Met Office Unified Model Global Atmosphere 4.0 and JULES Global Land 4.0 configurations, Geosci. Model Dev., 7, 361–386, https://doi.org/10.5194/gmd-7-361-2014, 2014.
Williams, E. R.: Large-scale charge separation in thunderclouds, J. Geophys.
Res., 90, 6013–6025, https://doi.org/10.1029/JD090iD04p06013,
1985.
Williams, E. R.: Lightning and climate: A review, Atmos. Res., 76, 272–287,
https://doi.org/10.1016/j.atmosres.2004.11.014, 2005.
Witte, J. C., Thompson, A. M., Smit, H. G. J., Fujiwara, M., Posny, F.,
Coetzee, G. J. R., Northam, E. T., Johnson, B. J., Sterling, C. W.,
Mohammed, M., Ogino, S-Y., Jordan, A., and da Silva, F. R.: First
reprocessing of Southern Hemisphere ADditional OZonesondes (SHADOZ) profile
records (1998–2015) 1: Methodology and evaluation, J. Geophys. Res., 122,
6611–6636, https://doi.org/10.1002/2016JD026403, 2017.
Wolfe, G. M., Nicely, J. M., Clair, J. M. S., Hanisco, T. F., Liao, J.,
Oman, L. D., Brune, W. B., Miller, D., Thames, A., Abad, G. G., Ryerson, T. B., Thompson, C. R., Peischl, J., McKain, K., Sweeney, C., Wennberg, P. O., Kim, M., Crounse, J. D., Hall, S. R., Ullmann, K., Diskin, G., Bui, P., Chang, C., and Dean-Day, J.: Mapping hydroxyl variability throughout the global
remote troposphere via synthesis of airborne and satellite formaldehyde
observations, P. Natl. Acad. Sci. USA, 116, 11171–11180, https://doi.org/10.1073/pnas.1821661116, 2019.
Woodhouse, M. T., Luhar, A. K., Stevens, L., Galbally, I., Thatcher, M.,
Uhe, P., Wolff, H., Noonan, J., and Molloy, S.: Australian reactive-gas
emissions in a global chemistry-climate model and initial results, Air
Quality and Climate Change, 49, 31–38, 2015.
Worden, H. M., Bowman, K. W., Kulawik, S. S., and Aghedo, A. M.:
Sensitivity of outgoing longwave radiative flux to the global vertical
distribution of ozone characterized by instantaneous radiative kernels from
Aura-TES, J. Geophys. Res., 116, D14115, 6013–6025,
https://doi.org/10.1029/2010JD015101, 2011.
Yoshida, S., Morimoto, T., Ushio, T., and Kawasaki, Z.: A fifth-power
relationship for lightning activity from Tropical Rainfall Measuring Mission
satellite observations, J. Geophys. Res., 114, D09104,
https://doi.org/10.1029/2008JD010370, 2009.
Young, P. J., Archibald, A. T., Bowman, K. W., Lamarque, J.-F., Naik, V., Stevenson, D. S., Tilmes, S., Voulgarakis, A., Wild, O., Bergmann, D., Cameron-Smith, P., Cionni, I., Collins, W. J., Dalsøren, S. B., Doherty, R. M., Eyring, V., Faluvegi, G., Horowitz, L. W., Josse, B., Lee, Y. H., MacKenzie, I. A., Nagashima, T., Plummer, D. A., Righi, M., Rumbold, S. T., Skeie, R. B., Shindell, D. T., Strode, S. A., Sudo, K., Szopa, S., and Zeng, G.: Pre-industrial to end 21st century projections of tropospheric ozone from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), Atmos. Chem. Phys., 13, 2063–2090, https://doi.org/10.5194/acp-13-2063-2013, 2013.
Zhu, Q., Laughner, J. L., and Cohen, R. C.: Lightning NO2 simulation over the contiguous US and its effects on satellite NO2 retrievals, Atmos. Chem. Phys., 19, 13067–13078, https://doi.org/10.5194/acp-19-13067-2019, 2019.
Short summary
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.
Lightning-generated nitrogen oxides (LNOx) greatly influence tropospheric photochemistry. The...
Altmetrics
Final-revised paper
Preprint