Articles | Volume 24, issue 24
https://doi.org/10.5194/acp-24-14005-2024
© Author(s) 2024. 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-24-14005-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Dec 2024
Research article |
| 17 Dec 2024
| 17 Dec 2024
Quantifying the impact of global nitrate aerosol on tropospheric composition fields and its production from lightning NOx
CSIRO Environment, Aspendale, Victoria 3195, Australia
Anthony C. Jones
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
Jonathan M. Wilkinson
Met Office, Fitzroy Road, Exeter, EX1 3PB, UK
now at: Forecast Department, European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, UK
Related authors
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, 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
Short summary
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.
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.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Anthony Jones, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, Noah Asch, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2024-3376, https://doi.org/10.5194/egusphere-2024-3376, 2024
Short summary
Short summary
We study aerosol-fog interactions near Paris using a weather and climate model with high spatial resolution. We show that our model can simulate fog lifecycle effectively. We find that the fog droplet number concentrations, the amount of liquid water in the fog, and the vertical structure of the fog are highly sensitive to the parameterization that simulates droplet formation and growth. The changes we propose could improve fog forecasts significantly without increasing computational costs.
Natalie G. Ratcliffe, Claire L. Ryder, Nicolas Bellouin, Stephanie Woodward, Anthony Jones, Ben Johnson, Lisa-Maria Wieland, Maximilian Dollner, Josef Gasteiger, and Bernadett Weinzierl
Atmos. Chem. Phys., 24, 12161–12181, https://doi.org/10.5194/acp-24-12161-2024, https://doi.org/10.5194/acp-24-12161-2024, 2024
Short summary
Short summary
Large mineral dust particles are more abundant in the atmosphere than expected and have different impacts on the environment than small particles, which are better represented in climate models. We use aircraft measurements to assess a climate model representation of large-dust transport. We find that the model underestimates the amount of large dust at all stages of transport and that fast removal of the large particles increases this underestimation with distance from the Sahara.
Jim M. Haywood, Andy Jones, Anthony C. Jones, Paul Halloran, and Philip J. Rasch
Atmos. Chem. Phys., 23, 15305–15324, https://doi.org/10.5194/acp-23-15305-2023, https://doi.org/10.5194/acp-23-15305-2023, 2023
Short summary
Short summary
The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
Paul A. Barrett, Steven J. Abel, Hugh Coe, Ian Crawford, Amie Dobracki, James Haywood, Steve Howell, Anthony Jones, Justin Langridge, Greg M. McFarquhar, Graeme J. Nott, Hannah Price, Jens Redemann, Yohei Shinozuka, Kate Szpek, Jonathan W. Taylor, Robert Wood, Huihui Wu, Paquita Zuidema, Stéphane Bauguitte, Ryan Bennett, Keith Bower, Hong Chen, Sabrina Cochrane, Michael Cotterell, Nicholas Davies, David Delene, Connor Flynn, Andrew Freedman, Steffen Freitag, Siddhant Gupta, David Noone, Timothy B. Onasch, James Podolske, Michael R. Poellot, Sebastian Schmidt, Stephen Springston, Arthur J. Sedlacek III, Jamie Trembath, Alan Vance, Maria A. Zawadowicz, and Jianhao Zhang
Atmos. Meas. Tech., 15, 6329–6371, https://doi.org/10.5194/amt-15-6329-2022, https://doi.org/10.5194/amt-15-6329-2022, 2022
Short summary
Short summary
To better understand weather and climate, it is vital to go into the field and collect observations. Often measurements take place in isolation, but here we compared data from two aircraft and one ground-based site. This was done in order to understand how well measurements made on one platform compared to those made on another. Whilst this is easy to do in a controlled laboratory setting, it is more challenging in the real world, and so these comparisons are as valuable as they are rare.
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.
Anthony C. Jones, Adrian Hill, John Hemmings, Pascal Lemaitre, Arnaud Quérel, Claire L. Ryder, and Stephanie Woodward
Atmos. Chem. Phys., 22, 11381–11407, https://doi.org/10.5194/acp-22-11381-2022, https://doi.org/10.5194/acp-22-11381-2022, 2022
Short summary
Short summary
As raindrops fall to the ground, they capture aerosol (i.e. below-cloud scavenging or BCS). Many different BCS schemes are available to climate models, and it is unclear what the impact of selecting one scheme over another is. Here, various BCS models are outlined and then applied to mineral dust in climate model simulations. We find that dust concentrations are highly sensitive to the BCS scheme, with dust atmospheric lifetimes ranging from 5 to 44 d.
Rachel E. Hawker, Annette K. Miltenberger, Jill S. Johnson, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Paul R. Field, Benjamin J. Murray, and Ken S. Carslaw
Atmos. Chem. Phys., 21, 17315–17343, https://doi.org/10.5194/acp-21-17315-2021, https://doi.org/10.5194/acp-21-17315-2021, 2021
Short summary
Short summary
We find that ice-nucleating particles (INPs), aerosols that can initiate the freezing of cloud droplets, cause substantial changes to the properties of radiatively important convectively generated anvil cirrus. The number concentration of INPs had a large effect on ice crystal number concentration while the INP temperature dependence controlled ice crystal size and cloud fraction. The results indicate information on INP number and source is necessary for the representation of cloud glaciation.
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.
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
Short summary
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.
Rachel E. Hawker, Annette K. Miltenberger, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Zhiqiang Cui, Richard J. Cotton, Ken S. Carslaw, Paul R. Field, and Benjamin J. Murray
Atmos. Chem. Phys., 21, 5439–5461, https://doi.org/10.5194/acp-21-5439-2021, https://doi.org/10.5194/acp-21-5439-2021, 2021
Short summary
Short summary
The impact of aerosols on clouds is a large source of uncertainty for future climate projections. Our results show that the radiative properties of a complex convective cloud field in the Saharan outflow region are sensitive to the temperature dependence of ice-nucleating particle concentrations. This means that differences in the aerosol source or composition, for the same aerosol size distribution, can cause differences in the outgoing radiation from regions dominated by tropical convection.
Andy Jones, Jim M. Haywood, Anthony C. Jones, Simone Tilmes, Ben Kravitz, and Alan Robock
Atmos. Chem. Phys., 21, 1287–1304, https://doi.org/10.5194/acp-21-1287-2021, https://doi.org/10.5194/acp-21-1287-2021, 2021
Short summary
Short summary
Two different methods of simulating a geoengineering scenario are compared using data from two different Earth system models. One method is very idealised while the other includes details of a plausible mechanism. The results from both models agree that the idealised approach does not capture an impact found when detailed modelling is included, namely that geoengineering induces a positive phase of the North Atlantic Oscillation which leads to warmer, wetter winters in northern Europe.
Jim M. Haywood, Steven J. Abel, Paul A. Barrett, Nicolas Bellouin, Alan Blyth, Keith N. Bower, Melissa Brooks, Ken Carslaw, Haochi Che, Hugh Coe, Michael I. Cotterell, Ian Crawford, Zhiqiang Cui, Nicholas Davies, Beth Dingley, Paul Field, Paola Formenti, Hamish Gordon, Martin de Graaf, Ross Herbert, Ben Johnson, Anthony C. Jones, Justin M. Langridge, Florent Malavelle, Daniel G. Partridge, Fanny Peers, Jens Redemann, Philip Stier, Kate Szpek, Jonathan W. Taylor, Duncan Watson-Parris, Robert Wood, Huihui Wu, and Paquita Zuidema
Atmos. Chem. Phys., 21, 1049–1084, https://doi.org/10.5194/acp-21-1049-2021, https://doi.org/10.5194/acp-21-1049-2021, 2021
Short summary
Short summary
Every year, the seasonal cycle of biomass burning from agricultural practices in Africa creates a huge plume of smoke that travels many thousands of kilometres over the Atlantic Ocean. This study provides an overview of a measurement campaign called the cloud–aerosol–radiation interaction and forcing for year 2017 (CLARIFY-2017) and documents the rationale, deployment strategy, observations, and key results from the campaign which utilized the heavily equipped FAAM atmospheric research aircraft.
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.
Hamish Gordon, Paul R. Field, Steven J. Abel, Paul Barrett, Keith Bower, Ian Crawford, Zhiqiang Cui, Daniel P. Grosvenor, Adrian A. Hill, Jonathan Taylor, Jonathan Wilkinson, Huihui Wu, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10997–11024, https://doi.org/10.5194/acp-20-10997-2020, https://doi.org/10.5194/acp-20-10997-2020, 2020
Short summary
Short summary
The Met Office's Unified Model is widely used both for weather forecasting and climate prediction. We present the first version of the model in which both aerosol and cloud particle mass and number concentrations are allowed to evolve separately and independently, which is important for studying how aerosols affect weather and climate. We test the model against aircraft observations near Ascension Island in the Atlantic, focusing on how aerosols can "activate" to become cloud droplets.
Cited articles
Archer-Nicholls, S., Allen, R., Abraham, N. L., Griffiths, P. T., and Archibald, A. T.: Large simulated future changes in the nitrate radical under the CMIP6 SSP scenarios: implications for oxidation chemistry, Atmos. Chem. Phys., 23, 5801–5813, https://doi.org/10.5194/acp-23-5801-2023, 2023.
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.
Bauer, S. E., Koch, D., Unger, N., Metzger, S. M., Shindell, D. T., and Streets, D. G.: Nitrate aerosols today and in 2030: a global simulation including aerosols and tropospheric ozone, Atmos. Chem. Phys., 7, 5043–5059, https://doi.org/10.5194/acp-7-5043-2007, 2007.
Bellouin, N., Rae, J., Jones, A., Johnson, C., Haywood, J., and Boucher, O.: Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2-ES and the role of ammonium nitrate, J. Geophys. Res.-Atmos., 116, D20206, https://doi.org/10.1029/2011jd016074, 2011.
Bellouin, N., Mann, G. W., Woodhouse, M. T., Johnson, C., Carslaw, K. S., and Dalvi, M.: Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model, Atmos. Chem. Phys., 13, 3027–3044, https://doi.org/10.5194/acp-13-3027-2013, 2013.
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A.-L., Dufresne, J.-L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D. T., Myhre, G., Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.: Bounding global aerosol radiative forcing of climate change, Rev. Geophys., 58, e2019RG000660, https://doi.org/10.1029/2019RG000660, 2020.
Bian, H., Chin, M., Hauglustaine, D. A., Schulz, M., Myhre, G., Bauer, S. E., Lund, M. T., Karydis, V. A., Kucsera, T. L., Pan, X., Pozzer, A., Skeie, R. B., Steenrod, S. D., Sudo, K., Tsigaridis, K., Tsimpidi, A. P., and Tsyro, S. G.: Investigation of global particulate nitrate from the AeroCom phase III experiment, Atmos. Chem. Phys., 17, 12911–12940, https://doi.org/10.5194/acp-17-12911-2017, 2017.
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.
Brown, S. S., Ryerson, T. B., Wollny, A. G., Brock, C. A., Peltier, R., Sullivan, A. P., Weber, R. J., Dube, W. P., Trainer, M., Meagher, J. F., Fehsenfeld, F. C., and Ravishankara, A. R.: Variability in nocturnal nitrogen oxide processing and its role in regional air quality, Science, 311, 67–70, https://doi.org/10.1126/science.1120120, 2006.
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.
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.
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.
Drugé, T., Nabat, P., Mallet, M., and Somot, S.: Model simulation of ammonium and nitrate aerosols distribution in the Euro-Mediterranean region and their radiative and climatic effects over 1979–2016, Atmos. Chem. Phys., 19, 3707–3731, https://doi.org/10.5194/acp-19-3707-2019, 2019.
Fairlie, T. D., Jacob, D. J., Dibb, J. E., Alexander, B., Avery, M. A., van Donkelaar, A., and Zhang, L.: Impact of mineral dust on nitrate, sulfate, and ozone in transpacific Asian pollution plumes, Atmos. Chem. Phys., 10, 3999–4012, https://doi.org/10.5194/acp-10-3999-2010, 2010.
Finlayson-Pitts, B. J. and Pitts, J. N.: Chemistry of the Upper and Lower Atmosphere: Theory, Experiments and Applications, Academic Press, San Diego, ISBN 0-12-257060-x, 969 pp., 2000.
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.
Fuchs, N. A. and Sutugin, A. G.: Highly Dispersed Aerosols, Butterworth-Heinemann, Newton, Mass., USA, 105 pp., https://doi.org/10.1016/B978-0-08-016674-2.50006-6, 1970.
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.
Gressent, A., Sauvage, B., Cariolle, D., Evans, M., Leriche, M., Mari, C., and Thouret, V.: Modeling lightning-NOx chemistry on a sub-grid scale in a global chemical transport model, Atmos. Chem. Phys., 16, 5867–5889, https://doi.org/10.5194/acp-16-5867-2016, 2016.
Griffiths, P. T., Murray, L. T., Zeng, G., Shin, Y. M., Abraham, N. L., Archibald, A. T., Deushi, M., Emmons, L. K., Galbally, I. E., Hassler, B., Horowitz, L. W., Keeble, J., Liu, J., Moeini, O., Naik, V., O'Connor, F. M., Oshima, N., Tarasick, D., Tilmes, S., Turnock, S. T., Wild, O., Young, P. J., and Zanis, P.: Tropospheric ozone in CMIP6 simulations, Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, 2021.
Hauglustaine, D. A., Balkanski, Y., and Schulz, M.: A global model simulation of present and future nitrate aerosols and their direct radiative forcing of climate, Atmos. Chem. Phys., 14, 11031–11063, https://doi.org/10.5194/acp-14-11031-2014, 2014.
Haywood, J. and Boucher, O.: Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: A review, Rev. Geophys., 38, 513–543, https://doi.org/10.1029/1999RG000078, 2000.
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.
JASMIN: JASMIN, the UK's data analysis facility for environmental science,, http://www.jasmin.ac.uk (last access: 14 December 2024), 2024.
Jones, A. C., Hill, A., Remy, S., Abraham, N. L., Dalvi, M., Hardacre, C., Hewitt, A. J., Johnson, B., Mulcahy, J. P., and Turnock, S. T.: Exploring the sensitivity of atmospheric nitrate concentrations to nitric acid uptake rate using the Met Office's Unified Model, Atmos. Chem. Phys., 21, 15901–15927, https://doi.org/10.5194/acp-21-15901-2021, 2021.
Jones, A. C., Hill, A., Hemmings, J., Lemaitre, P., Quérel, A., Ryder, C. L., and Woodward, S.: Below-cloud scavenging of aerosol by rain: a review of numerical modelling approaches and sensitivity simulations with mineral dust in the Met Office's Unified Model, Atmos. Chem. Phys., 22, 11381–11407, https://doi.org/10.5194/acp-22-11381-2022, 2022.
Khan, M. A. H., Cooke, M. C., Utembe, S. R., Archibald, A. T., Derwent, R. G., Xiao, P., Percival, C. J., Jenkin, M. E., Morris, W. C., and Shallcross, D. E.: Global modeling of the nitrate radical (NO3) for present and pre-industrial scenarios, Atmos. Res., 164–165, 347–357, https://doi.org/10.1016/j.atmosres.2015.06.006, 2015.
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.
Li, W. J. and Shao, L. Y.: Observation of nitrate coatings on atmospheric mineral dust particles, Atmos. Chem. Phys., 9, 1863–1871, https://doi.org/10.5194/acp-9-1863-2009, 2009.
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.
Luhar, A. K., Galbally, I. E., Woodhouse, M. T., and Abraham, N. L.: 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, Atmos. Chem. Phys., 21, 7053–7082, https://doi.org/10.5194/acp-21-7053-2021, 2021.
Luhar, A. K., Galbally, I. E., and Woodhouse, M. T.: Radiative impact of improved global parameterisations of oceanic dry deposition of ozone and lightning-generated NOx, Atmos. Chem. Phys., 22, 13013–13033, https://doi.org/10.5194/acp-22-13013-2022, 2022.
Mann, G. W., Carslaw, K. S., Spracklen, D. V., Ridley, D. A., Manktelow, P. T., Chipperfield, M. P., Pickering, S. J., and Johnson, C. E.: Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model, Geosci. Model Dev., 3, 519–551, https://doi.org/10.5194/gmd-3-519-2010, 2010.
Manners, J., Edwards, J. M., Hill, P., and Thelen, J.-C.: SOCRATES Technical Guide Suite Of Community RAdiative Transfer codes based on Edwards and Slingo, Met Office, UK, available at: https://code.metoffice.gov.uk/trac/socrates (last access: 26 February 2024), 2023.
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.
Mertens, L. A., Winiberg, F. A. F., Allen, H. M., Sander, S. P., and Okumura, M.: Yields of HONO2 and HOONO products from the reaction of HO2 and NO using pulsed laser photolysis and mid-infrared cavity-ringdown spectroscopy, J. Phys. Chem. A, 126, 7342, https://doi.org/10.1021/acs.jpca.2c04643, 2022.
Met Office: Unified Model, http://www.metoffice.gov.uk/research/modelling-systems/unified-model (last access: 14 December 2024), 2024a.
Met Office: SciTools [software], https://scitools.org.uk (last access: 27 February 2024), 2024b.
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.
Mulcahy, J. P., Johnson, C., Jones, C. G., Povey, A. C., Scott, C. E., Sellar, A., Turnock, S. T., Woodhouse, M. T., Abraham, N. L., Andrews, M. B., Bellouin, N., Browse, J., Carslaw, K. S., Dalvi, M., Folberth, G. A., Glover, M., Grosvenor, D. P., Hardacre, C., Hill, R., Johnson, B., Jones, A., Kipling, Z., Mann, G., Mollard, J., O'Connor, F. M., Palmiéri, J., Reddington, C., Rumbold, S. T., Richardson, M., Schutgens, N. A. J., Stier, P., Stringer, M., Tang, Y., Walton, J., Woodward, S., and Yool, A.: Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations, Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, 2020.
Murray, L. T.: Lightning NOx and impacts on air quality, Current Pollution Reports, 2, 115–133, https://doi.org/10.1007/s40726-016-0031-7, 2016.
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.
NASA GHRC: Lightning & Atmospheric Electricity Research, https://lightning.nsstc.nasa.gov/data/data_lis-otd-climatology.html (last access: 14 December 2024), 2024
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.
Park, R. J., Jacob, D. J., Field, B. D., Yantosca, R. M., and Chin, M.: Natural and transboundary pollution influences on sulfate-nitrate-ammonium aerosols in the United States: Implications for policy, J. Geophys. Res.-Atmos., 109, D15204, https://doi.org/10.1029/2003jd004473, 2004.
Paulot, F., Ginoux, P., Cooke, W. F., Donner, L. J., Fan, S., Lin, M.-Y., Mao, J., Naik, V., and Horowitz, L. W.: Sensitivity of nitrate aerosols to ammonia emissions and to nitrate chemistry: implications for present and future nitrate optical depth, Atmos. Chem. Phys., 16, 1459–1477, https://doi.org/10.5194/acp-16-1459-2016, 2016.
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.
Python: Python [software], https://www.python.org (last access: 27 February 2024), 2024.
Rémy, S., Kipling, Z., Flemming, J., Boucher, O., Nabat, P., Michou, M., Bozzo, A., Ades, M., Huijnen, V., Benedetti, A., Engelen, R., Peuch, V.-H., and Morcrette, J.-J.: Description and evaluation of the tropospheric aerosol scheme in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS-AER, cycle 45R1), Geosci. Model Dev., 12, 4627–4659, https://doi.org/10.5194/gmd-12-4627-2019, 2019.
Russo, M. R., Kerridge, B. J., Abraham, N. L., Keeble, J., Latter, B. G., Siddans, R., Weber, J., Griffiths, P. T., Pyle, J. A., and Archibald, A. T.: Seasonal, interannual and decadal variability of tropospheric ozone in the North Atlantic: comparison of UM-UKCA and remote sensing observations for 2005–2018, Atmos. Chem. Phys., 23, 6169–6196, https://doi.org/10.5194/acp-23-6169-2023, 2023.
Sander, S. P., Abbatt, J., Barker, J. R., Burkholder, J. B., Friedl, R. R., Golden, D. M., Huie, R. E., Kolb, C. E., Kurylo, M. J., Moortgat, G. K., Orkin, V. L., and Wine, P. H.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation No. 17, JPL Publication 10-6, Jet Propulsion Laboratory, Pasadena, https://jpldataeval.jpl.nasa.gov/pdf/JPL 10-6 Final 15June2011.pdf (last access: 12 December 2024) 2011.
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.
Schwartz, S. E.: Mass transport considerations pertinent to aqueous phase reactions of gases in liquid-water clouds, in: Chemistry of Multiphase Atmospheric Systems, edited by: Jaeschke, W., Springer, New York, 415–471 pp., https://link.springer.com/chapter/10.1007/978-3-642-70627-1_16 (last access: 12 December 2024), 1986.
Stelson, A. W., Friedlander, S. K., and Seinfeld, J. H.: A note on the equilibrium relationship between ammonia and nitric acid and particulate ammonium nitrate, Atmos. Environ., 13, 369–371, https://doi.org/10.1016/0004-6981(79)90293-2, 1979.
Szopa, S., Naik, V., Adhikary, B., Artaxo, P., Berntsen, T., Collins, W. D., Fuzzi, S., Gallardo, L., Kiendler Scharr, A., Klimont, Z., Liao, H., Unger, N., and Zanis, P.: Short-Lived Climate Forcers, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, UK and New York, NY, USA, 817–922, https://doi.org/10.1017/9781009157896.008, 2021.
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.
Thornhill, G. D., Collins, W. J., Kramer, R. J., Olivié, D., Skeie, R. B., O'Connor, F. M., Abraham, N. L., Checa-Garcia, R., Bauer, S. E., Deushi, M., Emmons, L. K., Forster, P. M., Horowitz, L. W., Johnson, B., Keeble, J., Lamarque, J.-F., Michou, M., Mills, M. J., Mulcahy, J. P., Myhre, G., Nabat, P., Naik, V., Oshima, N., Schulz, M., Smith, C. J., Takemura, T., Tilmes, S., Wu, T., Zeng, G., and Zhang, J.: Effective radiative forcing from emissions of reactive gases and aerosols – a multi-model comparison, Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, 2021.
Tost, H.: Chemistry–climate interactions of aerosol nitrate from lightning, Atmos. Chem. Phys., 17, 1125–1142, https://doi.org/10.5194/acp-17-1125-2017, 2017.
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, 2019.
Wang, Q., Li, Z., Guo, J., Zhao, C., and Cribb, M.: The climate impact of aerosols on the lightning flash rate: is it detectable from long-term measurements?, Atmos. Chem. Phys., 18, 12797–12816, https://doi.org/10.5194/acp-18-12797-2018, 2018.
Wang, M., Kong, W., Marten, R., He, X.-C., Chen, D., Pfeifer, J., Heitto, A., Kontkanen, J., Dada, L., Kürten, A., Yli-Juuti, T., Manninen, H. E., Amanatidis, S., Amorim, A., Baalbaki, R., Baccarini, A., Bell, D. M., Bertozzi, B., Bräkling, S., Brilke, S., Murillo, L. C., Chiu, R., Chu, B., Menezes, L.-P. D., Duplissy, J., Finkenzeller, H., Carracedo, L. G., Granzin, M., Guida, R., Hansel, A., Hofbauer, V., Krechmer, J., Lehtipalo, K., Lamkaddam, H., Lampimäki, M., Lee, C. P., Makhmutov, V., Marie, G., Mathot, S., Mauldin, R. L., Mentler, B., Müller, T., Onnela, A., Partoll, E., Petäjä, T., Philippov, M., Pospisilova, V., Ranjithkumar, A., Rissanen, M., Rörup, B., Scholz, W., Shen, J., Simon, M., Sipilä, M., Steiner, G., Stolzenburg, D., Tham, Y. J., Tomé, A., Wagner, A. C., Wang, D. S., Wang, Y., Weber, S. K., Winkler, P. M., Wlasits, P. J., Wu, Y., Xiao, M., Ye, Q., Zauner-Wieczorek, M., Zhou, X., Volkamer, R., Riipinen, I., Dommen, J., Curtius, J., Baltensperger, U., Kulmala, M., Worsnop, D. R., Kirkby, J., Seinfeld, J. H., El-Haddad, I., Flagan, R. C., and Donahue, N. M.: Rapid growth of new atmospheric particles by nitric acid and ammonia condensation, Nature, 581, 184–189, https://doi.org/10.1038/s41586-020-2270-4, 2020.
Wang, H., Pei, Y., Yin, Y., Shen, L., Chen, K., Shi, Z., and Chen, J.: Observational evidence of lightning-generated ultrafine aerosols, Geophys. Res. Lett., 48, e2021GL093771, https://doi.org/10.1029/2021GL093771, 2021.
Wilson, D. R. and Ballard, S. P.: A microphysically based precipitation scheme for the UK Meteorological Office Unified Model, Q. J. Roy. Meteorol. Soc., 125, 1607–1636, https://doi.org/10.1002/qj.49712555707, 1999.
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D., and Morcrette, C. J.: PC2: A prognostic cloud fraction and condensation scheme. I: Scheme description, Q. J. Roy. Meteorol. Soc., 134, 2093–2107, https://doi.org/10.1002/qj.333, 2008.
Woodward, S.: Modeling the atmospheric life cycle and radiative impact of mineral dust in the Hadley Centre climate model, J. Geophys. Res.-Atmos., 106, 18155–18166, https://doi.org/10.1029/2000JD900795, 2001.
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.
Nitrate aerosol is often omitted in global chemistry–climate models, partly due to the chemical...
Altmetrics
Final-revised paper
Preprint