Articles | Volume 20, issue 24
https://doi.org/10.5194/acp-20-15681-2020
© Author(s) 2020. 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-20-15681-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Dec 2020
Research article |
| 17 Dec 2020
| 17 Dec 2020
The decomposition of cloud–aerosol forcing in the UK Earth System Model (UKESM1)
Daniel P. Grosvenor
CORRESPONDING AUTHOR
National Centre for Atmospheric Sciences, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
Kenneth S. Carslaw
Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
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Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David M. H. Sexton, Christopher Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John W. Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
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Daniel P. Grosvenor and Kenneth S. Carslaw
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We determine what causes long-term trends in short-wave (SW) radiative fluxes in two climate models. A positive trend occurs between 1850 and 1970 (increasing SW reflection) and a negative trend between 1970 and 2014; the pre-1970 positive trend is mainly driven by an increase in cloud droplet number concentrations due to increases in aerosol, and the 1970–2014 trend is driven by a decrease in cloud fraction, which we attribute to changes in clouds caused by greenhouse gas-induced warming.
Ernesto Reyes-Villegas, Douglas Lowe, Jill S. Johnson, Kenneth S. Carslaw, Eoghan Darbyshire, Michael Flynn, James D. Allan, Hugh Coe, Ying Chen, Oliver Wild, Scott Archer-Nicholls, Alex Archibald, Siddhartha Singh, Manish Shrivastava, Rahul A. Zaveri, Vikas Singh, Gufran Beig, Ranjeet Sokhi, and Gordon McFiggans
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Xuemei Wang, Hamish Gordon, Daniel P. Grosvenor, Meinrat O. Andreae, and Ken S. Carslaw
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Ruth Price, Andrea Baccarini, Julia Schmale, Paul Zieger, Ian M. Brooks, Paul Field, and Ken S. Carslaw
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Arctic clouds can control how much energy is absorbed by the surface or reflected back to space. Using a computer model of the atmosphere we investigated the formation of atmospheric particles that allow cloud droplets to form. We found that particles formed aloft are transported to the lowest part of the Arctic atmosphere and that this is a key source of particles. Our results have implications for the way Arctic clouds will behave in the future as climate change continues to impact the region.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David Sexton, Christopher C. Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2022-1330, https://doi.org/10.5194/egusphere-2022-1330, 2022
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We show that potential structural deficiencies in a climate model can be exposed by comprehensively exploring its parametric uncertainty, and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. Combined consideration of parametric and structural uncertainties provides a future pathway towards building models that have greater physical realism and lower uncertainty.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
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We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Johannes Quaas, Hailing Jia, Chris Smith, Anna Lea Albright, Wenche Aas, Nicolas Bellouin, Olivier Boucher, Marie Doutriaux-Boucher, Piers M. Forster, Daniel Grosvenor, Stuart Jenkins, Zbigniew Klimont, Norman G. Loeb, Xiaoyan Ma, Vaishali Naik, Fabien Paulot, Philip Stier, Martin Wild, Gunnar Myhre, and Michael Schulz
Atmos. Chem. Phys., 22, 12221–12239, https://doi.org/10.5194/acp-22-12221-2022, https://doi.org/10.5194/acp-22-12221-2022, 2022
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Pollution particles cool climate and offset part of the global warming. However, they are washed out by rain and thus their effect responds quickly to changes in emissions. We show multiple datasets to demonstrate that aerosol emissions and their concentrations declined in many regions influenced by human emissions, as did the effects on clouds. Consequently, the cooling impact on the Earth energy budget became smaller. This change in trend implies a relative warming.
Amy H. Peace, Ben B. B. Booth, Leighton A. Regayre, Ken S. Carslaw, David M. H. Sexton, Céline J. W. Bonfils, and John W. Rostron
Earth Syst. Dynam., 13, 1215–1232, https://doi.org/10.5194/esd-13-1215-2022, https://doi.org/10.5194/esd-13-1215-2022, 2022
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Anthropogenic aerosol emissions have been linked to driving climate responses such as shifts in the location of tropical rainfall. However, the interaction of aerosols with climate remains one of the most uncertain aspects of climate modelling and limits our ability to predict future climate change. We use an ensemble of climate model simulations to investigate what impact the large uncertainty in how aerosols interact with climate has on predicting future tropical rainfall shifts.
Alexander D. Harrison, Daniel O'Sullivan, Michael P. Adams, Grace C. E. Porter, Edmund Blades, Cherise Brathwaite, Rebecca Chewitt-Lucas, Cassandra Gaston, Rachel Hawker, Ovid O. Krüger, Leslie Neve, Mira L. Pöhlker, Christopher Pöhlker, Ulrich Pöschl, Alberto Sanchez-Marroquin, Andrea Sealy, Peter Sealy, Mark D. Tarn, Shanice Whitehall, James B. McQuaid, Kenneth S. Carslaw, Joseph M. Prospero, and Benjamin J. Murray
Atmos. Chem. Phys., 22, 9663–9680, https://doi.org/10.5194/acp-22-9663-2022, https://doi.org/10.5194/acp-22-9663-2022, 2022
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The formation of ice in clouds fundamentally alters cloud properties; hence it is important we understand the special aerosol particles that can nucleate ice when immersed in supercooled cloud droplets. In this paper we show that African desert dust that has travelled across the Atlantic to the Caribbean nucleates ice much less well than we might have expected.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
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Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
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
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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.
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys., 21, 15351–15374, https://doi.org/10.5194/acp-21-15351-2021, https://doi.org/10.5194/acp-21-15351-2021, 2021
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We present the first full year of surface aerosol number concentration measurements from the central Greenland Ice Sheet. Aerosol concentrations here have a distinct seasonal cycle from those at lower-altitude Arctic sites, which is driven by large-scale atmospheric circulation. Our results can be used to help understand the role aerosols might play in Greenland surface melt through the modification of cloud properties. This is crucial in a rapidly changing region where observations are sparse.
Mao Xiao, Christopher R. Hoyle, Lubna Dada, Dominik Stolzenburg, Andreas Kürten, Mingyi Wang, Houssni Lamkaddam, Olga Garmash, Bernhard Mentler, Ugo Molteni, Andrea Baccarini, Mario Simon, Xu-Cheng He, Katrianne Lehtipalo, Lauri R. Ahonen, Rima Baalbaki, Paulus S. Bauer, Lisa Beck, David Bell, Federico Bianchi, Sophia Brilke, Dexian Chen, Randall Chiu, António Dias, Jonathan Duplissy, Henning Finkenzeller, Hamish Gordon, Victoria Hofbauer, Changhyuk Kim, Theodore K. Koenig, Janne Lampilahti, Chuan Ping Lee, Zijun Li, Huajun Mai, Vladimir Makhmutov, Hanna E. Manninen, Ruby Marten, Serge Mathot, Roy L. Mauldin, Wei Nie, Antti Onnela, Eva Partoll, Tuukka Petäjä, Joschka Pfeifer, Veronika Pospisilova, Lauriane L. J. Quéléver, Matti Rissanen, Siegfried Schobesberger, Simone Schuchmann, Yuri Stozhkov, Christian Tauber, Yee Jun Tham, António Tomé, Miguel Vazquez-Pufleau, Andrea C. Wagner, Robert Wagner, Yonghong Wang, Lena Weitz, Daniela Wimmer, Yusheng Wu, Chao Yan, Penglin Ye, Qing Ye, Qiaozhi Zha, Xueqin Zhou, Antonio Amorim, Ken Carslaw, Joachim Curtius, Armin Hansel, Rainer Volkamer, Paul M. Winkler, Richard C. Flagan, Markku Kulmala, Douglas R. Worsnop, Jasper Kirkby, Neil M. Donahue, Urs Baltensperger, Imad El Haddad, and Josef Dommen
Atmos. Chem. Phys., 21, 14275–14291, https://doi.org/10.5194/acp-21-14275-2021, https://doi.org/10.5194/acp-21-14275-2021, 2021
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Experiments at CLOUD show that in polluted environments new particle formation (NPF) is largely driven by the formation of sulfuric acid–base clusters, stabilized by amines, high ammonia concentrations or lower temperatures. While oxidation products of aromatics can nucleate, they play a minor role in urban NPF. Our experiments span 4 orders of magnitude variation of observed NPF rates in ambient conditions. We provide a framework based on NPF and growth rates to interpret ambient observations.
Ramiro Checa-Garcia, Yves Balkanski, Samuel Albani, Tommi Bergman, Ken Carslaw, Anne Cozic, Chris Dearden, Beatrice Marticorena, Martine Michou, Twan van Noije, Pierre Nabat, Fiona M. O'Connor, Dirk Olivié, Joseph M. Prospero, Philippe Le Sager, Michael Schulz, and Catherine Scott
Atmos. Chem. Phys., 21, 10295–10335, https://doi.org/10.5194/acp-21-10295-2021, https://doi.org/10.5194/acp-21-10295-2021, 2021
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Thousands of tons of dust are emitted into the atmosphere every year, producing important impacts on the Earth system. However, current global climate models are not yet able to reproduce dust emissions, transport and depositions with the desirable accuracy. Our study analyses five different Earth system models to report aspects to be improved to reproduce better available observations, increase the consistency between models and therefore decrease the current uncertainties.
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
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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.
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
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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.
Kamalika Sengupta, Kirsty Pringle, Jill S. Johnson, Carly Reddington, Jo Browse, Catherine E. Scott, and Ken Carslaw
Atmos. Chem. Phys., 21, 2693–2723, https://doi.org/10.5194/acp-21-2693-2021, https://doi.org/10.5194/acp-21-2693-2021, 2021
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Global models consistently underestimate atmospheric secondary organic aerosol (SOA), which has significant climatic implications. We use a perturbed parameter model ensemble and ground-based observations to reduce the uncertainty in modelling SOA formation from oxidation of volatile organic compounds. We identify plausible parameter spaces for the yields of extremely low-volatility, low-volatility, and semi-volatile organic compounds based on model–observation match for three key model outputs.
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
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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.
Benjamin J. Murray, Kenneth S. Carslaw, and Paul R. Field
Atmos. Chem. Phys., 21, 665–679, https://doi.org/10.5194/acp-21-665-2021, https://doi.org/10.5194/acp-21-665-2021, 2021
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The balance between the amounts of ice and supercooled water in clouds over the world's oceans strongly influences how much these clouds can dampen or amplify global warming. Aerosol particles which catalyse ice formation can dramatically reduce the amount of supercooled water in clouds; hence we argue that we need a concerted effort to improve our understanding of these ice-nucleating particles if we are to improve our predictions of climate change.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
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Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
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
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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.
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
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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.
Leighton A. Regayre, Julia Schmale, Jill S. Johnson, Christian Tatzelt, Andrea Baccarini, Silvia Henning, Masaru Yoshioka, Frank Stratmann, Martin Gysel-Beer, Daniel P. Grosvenor, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 10063–10072, https://doi.org/10.5194/acp-20-10063-2020, https://doi.org/10.5194/acp-20-10063-2020, 2020
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The amount of energy reflected back into space because of man-made particles is highly uncertain. Processes related to naturally occurring particles cause most of the uncertainty, but these processes are poorly constrained by present-day measurements. We show that measurements over the Southern Ocean, far from pollution sources, efficiently reduce climate model uncertainties. Our results pave the way to designing experiments and measurement campaigns that reduce this uncertainty even further.
Cited articles
Abdul-Razzak, H. and Ghan, S. J.: A Parameterization of Aerosol Activation: 2.
Multiple Aerosol Types, J. Geophys. Res., 105, 6837–6844,
https://doi.org/10.1029/1999JD901161, 2000. a
Abel, S. J. and Shipway, B. J.: A comparison of cloud-resolving model
simulations of trade wind cumulus with aircraft observations taken during
RICO, Q. J. R. Meteorol. Soc., 133, 781–794, https://doi.org/10.1002/qj.55,
2007. a
Ackerley, D., Booth, B. B. B., Knight, S. H. E., Highwood, E. J., Frame, D. J.,
Allen, M. R., and Rowell, D. P.: Sensitivity of Twentieth-Century Sahel
Rainfall to Sulfate Aerosol and CO2Forcing, J. Climate, 24,
4999–5014, https://doi.org/10.1175/jcli-d-11-00019.1,
2011. a
Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B.: The
impact of humidity above stratiform clouds on indirect aerosol climate
forcing, Nature, 432, 1014–1017, https://doi.org/10.1038/nature03174,
2004. a, b, c
Ahmad, I., Mielonen, T., Grosvenor, D. P., Portin, H. J., Arola, A., Mikkonen,
S., Kühn, T., Leskinen, A., Joutsensaari, J., Komppula, M., Lehtinen,
K. E. J., Laaksonen, A., and Romakkaniemi, S.: Long-term measurements of
cloud droplet concentrations and aerosol-cloud
interactions in continental boundary layer clouds, Tellus B, 65, 20138,
https://doi.org/10.3402/tellusb.v65i0.20138,
2013. a
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness,
Science, 245, 1227–1230,
http://www.jstor.org/stable/1704234, 1989. a
Albrecht, B. A., Fairall, C. W., Thomson, D. W., White, A. B., Snider, J. B.,
and Schubert, W. H.: Surface-Based Remote-Sensing Of The Observed And The
Adiabatic Liquid Water-Content Of Stratocumulus Clouds, Geophys. Res. Lett.,
17, 89–92, https://doi.org/10.1029/Gl017i001p00089, 1990. a
Andreae, M. O., Jones, C. D., and Cox, P. M.: Strong present-day aerosol
cooling implies a hot future, Nature, 435, 1187–1190,
https://doi.org/10.1038/nature03671, 2005. a
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. a
Ba, J., Keenlyside, N. S., Latif, M., Park, W., Ding, H., Lohmann, K., Mignot,
J., Menary, M., Wouters, O. H. O. B., Melia, D. S., Oka, A., Bellucci, A.,
and Volodin, E.: A multi-model comparison of Atlantic multidecadal
variability, Clim. Dynam., 43, 2333–2348, https://doi.org/10.1007/s00382-014-2056-1,
2014. a
Bennartz, R.: Global assessment of marine boundary layer cloud droplet number
concentration from satellite, J. Geophys. Res.-Atmos., 112, 1–16,
https://doi.org/10.1029/2006JD007547, 2007. a, b, c
Berner, A. H., Bretherton, C. S., Wood, R., and Muhlbauer, A.: Marine boundary layer cloud regimes and POC formation in a CRM coupled to a bulk aerosol scheme, Atmos. Chem. Phys., 13, 12549–12572, https://doi.org/10.5194/acp-13-12549-2013, 2013. a, b
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein,
S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.:
COSP: Satellite simulation software for model assessment, B. Am.
Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011bams2856.1, 2011. a
Boers, R., Acarreta, J. R., and Gras, J. L.: Satellite monitoring of the first
indirect aerosol effect: Retrieval of the droplet concentration of water
clouds, J. Geophys. Res., 111, D22208, https://doi.org/10.1029/2005JD006838, 2006. a
Booth, B. B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., and Bellouin,
N.: Aerosols implicated as a prime driver of twentieth-century North
Atlantic climate variability, Nature, 484, 228–232,
https://doi.org/10.1038/nature10946,
2012. a, b, c
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster,
P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh,
S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and Aerosols,
in: Climate Change 2013: The Physical Science Basis. Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge
University Press, Cambridge, UK and New York, USA, 571–658, 2013. a
Boutle, I. A., Abel, S. J., Hill, P. G., and Morcrette, C. J.: Spatial
variability of liquid cloud and rain: Observations and microphysical
effects, Q. J. R. Meteorol. Soc., 140, 583–594, https://doi.org/10.1002/qj.2140,
2014. a
Brenguier, J.-L., Pawlowska, H., Schuller, L., Preusker, R., Fischer, J., and
Fouquart, Y.: Radiative properties of boundary layer clouds: Droplet
effective radius versus number concentration, J. Atmos. Sci., 57, 803–821,
https://doi.org/10.1175/1520-0469(2000)057<0803:RPOBLC>2.0.CO;2, 2000. a
Bretherton, C. S., Blossey, P. N., and Uchida, J.: Cloud droplet
sedimentation, entrainment efficiency, and subtropical stratocumulus albedo,
Geophys. Res. Lett., 34, L03813, https://doi.org/10.1029/2006GL027648, 2007. a, b
Brown, A. R., Beare, R. J., Edwards, J. M., Lock, A. P., Keogh, S. J., Milton,
S. F., and Walters, D. N.: Upgrades to the boundary-layer scheme in the met
office numerical weather prediction model, Boundary-Layer Meteorol., 128,
117–132, https://doi.org/10.1007/s10546-008-9275-0, 2008. a
Carslaw, K. S., Lee, L. A., Reddington, C. L., Pringle, K. J., Rap, A.,
Forster, P. M., Mann, G. W., Spracklen, D. V., Woodhouse, M. T., Regayre,
L. A., and Pierce, J. R.: Large contribution of natural aerosols to
uncertainty in indirect forcing, Nature, 503, 67–71,
https://doi.org/10.1038/nature12674,
2013. a
Cavalieri, D. J., Parkinson, C. L., Gloersen, P., and Zwally, H. J.: Sea Ice
Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave
Data, Version 1, NASA National Snow and Ice Data
Center Distributed Active Archive Center, Boulder, Colorado USA,
https://doi.org/10.5067/8gq8lzqvl0vl, 1996. a
Chepfer, H., Bony, S., Winker, D., Cesana, G., Dufresne, J. L., Minnis, P.,
Stubenrauch, C. J., and Zeng, S.: The GCM-oriented CALIPSO cloud product
(CALIPSO-GOCCP), J. Geophys. Res.-Atmos., 115, 1–13,
https://doi.org/10.1029/2009JD012251, 2010. a, b
Cox, P. M.: Description of the “TRIFFID” dynamic global vegetation model,
Hadley Centre Technical Note, Met Office Hadley Centre, Exeter, Devon, UK, 16 pp., 2001. a
Dunstone, N. J., Smith, D. M., Booth, B. B. B., Hermanson, L., and Eade, R.:
Anthropogenic aerosol forcing of Atlantic tropical storms, Nat. Geosci., 6,
534–539, https://doi.org/10.1038/ngeo1854,
2013. a
Eastman, R. and Wood, R.: Factors controlling low-cloud evolution over the
eastern subtropical oceans: A Lagrangian perspective using the A-train
satellites, J. Atmos. Sci., 73, 331–351, https://doi.org/10.1175/JAS-D-15-0193.1,
2016. a
Eastman, R. and Wood, R.: The competing effects of stability and humidity on
subtropical stratocumulus entrainment and cloud evolution from a Lagrangian
perspective, J. Atmos. Sci., 75, 2563–2578, https://doi.org/10.1175/JAS-D-18-0030.1,
2018. a
Eastman, R., Wood, R., and Bretherton, C. S.: Time scales of clouds and
cloud-controlling variables in subtropical stratocumulus from a Lagrangian
perspective, J. Atmos. Sci., 73, 3079–3091, https://doi.org/10.1175/JAS-D-16-0050.1,
2016. a
Elsaesser, G. S., O'Dell, C. W., Lebsock, M. D., Bennartz, R., Greenwald,
T. J., and Wentz, F. J.: The multisensor Advanced climatology of liquid
water path (MAC-LWP), J. Climate, 30, 10193–10210,
https://doi.org/10.1175/JCLI-D-16-0902.1, 2017. a, b, c
Feingold, G., Koren, I., Yamaguchi, T., and Kazil, J.: On the reversibility of transitions between closed and open cellular convection, Atmos. Chem. Phys., 15, 7351–7367, https://doi.org/10.5194/acp-15-7351-2015, 2015. a
Furtado, K., Field, P. R., Boutle, I. A., Morcrette, C. J., and Wilkinson,
J. M.: A Physically Based Subgrid Parameterization for the Production and
Maintenance of Mixed-Phase Clouds in a General Circulation Model, J. Atmos.
Sci., 73, 279–291, https://doi.org/10.1175/JAS-D-15-0021.1,
2016. a, b
Ghan, S. J.: Technical Note: Estimating aerosol effects on cloud radiative forcing, Atmos. Chem. Phys., 13, 9971–9974, https://doi.org/10.5194/acp-13-9971-2013, 2013. a
Golaz, J. C., Golaz, J. C., and Levy, H.: Cloud tuning in a coupled climate
model: Impact on 20th century warming, Geophys. Res. Lett., 40, 2246–2251,
https://doi.org/10.1002/grl.50232, 2013. a
Gordon, H., Field, P. R., Abel, S. J., Dalvi, M., Grosvenor, D. P., Hill, A. A., Johnson, B. T., Miltenberger, A. K., Yoshioka, M., and Carslaw, K. S.: Large simulated radiative effects of smoke in the south-east Atlantic, Atmos. Chem. Phys., 18, 15261–15289, https://doi.org/10.5194/acp-18-15261-2018, 2018. a
Grosvenor, D. P. and Wood, R.: The effect of solar zenith angle on MODIS cloud optical and microphysical retrievals within marine liquid water clouds, Atmos. Chem. Phys., 14, 7291–7321, https://doi.org/10.5194/acp-14-7291-2014, 2014. a
Grosvenor, D. P. and Wood, R.: Daily MODIS (MODerate Imaging
Spectroradiometer) derived cloud droplet number concentration global dataset
for 2003–2015, availabe at:
http://catalogue.ceda.ac.uk/uuid/cf97ccc802d348ec8a3b6f2995dfbbff (last access: 11 December 2020),
2018. a
Grosvenor, D. P., Field, P. R., Hill, A. A., and Shipway, B. J.: The relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects in closed-cell stratocumulus: insight from the modelling of a case study, Atmos. Chem. Phys., 17, 5155–5183, https://doi.org/10.5194/acp-17-5155-2017, 2017. a, b, c
Grosvenor, D. P., Sourdeval, O., and Wood, R.: Parameterizing cloud top effective radii from satellite retrieved values, accounting for vertical photon transport: quantification and correction of the resulting bias in droplet concentration and liquid water path retrievals, Atmos. Meas. Tech., 11, 4273–4289, https://doi.org/10.5194/amt-11-4273-2018, 2018a. a, b, c
Grosvenor, D. P., Sourdeval, O., Zuidema, P., Ackerman, A., Alexandrov, M. D.,
Bennartz, R., Boers, R., Cairns, B., Chiu, J. C., Christensen, M., Deneke,
H., Diamond, M., Feingold, G., Fridlind, A., Hünerbein, A., Knist, C.,
Kollias, P., Marshak, A., McCoy, D., Merk, D., Painemal, D., Rausch, J.,
Rosenfeld, D., Russchenberg, H., Seifert, P., Sinclair, K., Stier, P.,
van Diedenhoven, B., Wendisch, M., Werner, F., Wood, R., Zhang, Z., and
Quaas, J.: Remote Sensing of Droplet Number Concentration in Warm Clouds: A
Review of the Current State of Knowledge and Perspectives, Rev. Geophys.,
56, 409–453, https://doi.org/10.1029/2017RG000593, 2018b. a, b, c, d, e
Gryspeerdt, E., Mülmenstädt, J., Gettelman, A., Malavelle, F. F., Morrison, H., Neubauer, D., Partridge, D. G., Stier, P., Takemura, T., Wang, H., Wang, M., and Zhang, K.: Surprising similarities in model and observational aerosol radiative forcing estimates, Atmos. Chem. Phys., 20, 613–623, https://doi.org/10.5194/acp-20-613-2020, 2020. a
Gustafson, W. I. and Yu, S.: Generalized approach for using unbiased symmetric
metrics with negative values: Normalized mean bias factor and normalized mean
absolute error factor, Atmos. Sci. Lett., 13, 262–267,
https://doi.org/10.1002/asl.393, 2012. a, b, c, d
Han, Q., Rossow, W. B., Chou, J., and Welch, R. M.: Global variations of
column droplet concentration in low-level clouds, Geophys. Res. Lett., 25,
1419–1422, https://doi.org/10.1029/98GL01095, 1998. a
Hanna, E., Jones, J. M., Cappelen, J., Mernild, S. H., Wood, L., Steffen, K.,
and Huybrechts, P.: The influence of North Atlantic atmospheric and oceanic
forcing effects on 1900–2010 Greenland summer climate and ice melt/runoff,
Int. J. Climatol., 33, 862–880, https://doi.org/10.1002/joc.3475,
2012. a
Hill, A. A., Feingold, G., and Jiang, H.: The Influence of Entrainment and
Mixing Assumption on Aerosol-Cloud Interactions
in Marine Stratocumulus, J. Atmos. Sci., 66, 1450–1464,
https://doi.org/10.1175/2008jas2909.1,
2009. a, b
Hoerling, M., Hurrell, J., Eischeid, J., and Phillips, A.: Detection and
Attribution of Twentieth-Century Northern and Southern African Rainfall
Change, J. Climate, 19, 3989–4008, https://doi.org/10.1175/jcli3842.1,
2006. a
Holland, D. M., Thomas, R. H., de Young, B., Ribergaard, M. H., and Lyberth,
B.: Acceleration of Jakobshavn Isbrætriggered by warm subsurface
ocean waters, Nat. Geosci., 1, 659–664, https://doi.org/10.1038/ngeo316,
2008. a
Jiang, Y., Lu, Z., Liu, X., Qian, Y., Zhang, K., Wang, Y., and Yang, X.-Q.: Impacts of global open-fire aerosols on direct radiative, cloud and surface-albedo effects simulated with CAM5, Atmos. Chem. Phys., 16, 14805–14824, https://doi.org/10.5194/acp-16-14805-2016, 2016. a
Khairoutdinov, M. and Kogan, Y.: A New Cloud Physics Parameterization in a
Large-Eddy Simulation Model of Marine Stratocumulus, Mon. Weather Rev., 128,
229–243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2,
2000. a
Knight, J. R.: A signature of persistent natural thermohaline circulation
cycles in observed climate, Geophys. Res. Lett., 32, L20708,
https://doi.org/10.1029/2005gl024233,
2005. a
Knight, J. R., Folland, C. K., and Scaife, A. A.: Climate impacts of the
Atlantic Multidecadal Oscillation, Geophys. Res. Lett., 33, L17706,
https://doi.org/10.1029/2006gl026242,
2006. a
Kuhlbrodt, T., Jones, C. G., Sellar, A., Storkey, D., Blockley, E., Stringer,
M., Hill, R., Graham, T., Ridley, J., Blaker, A., Calvert, D., Copsey, D.,
Ellis, R., Hewitt, H., Hyder, P., Ineson, S., Mulcahy, J., Siahaan, A., and
Walton, J.: The Low-Resolution Version of HadGEM3 GC3.1: Development and
Evaluation for Global Climate, J. Adv. Model. Earth Syst., 10, 2865–2888,
https://doi.org/10.1029/2018MS001370, 2018. a
Lebsock, M. and Su, H.: Application of active spaceborne remote sensing for
understanding biases between passive cloud water path retrievals, J.
Geophys. Res.-Atmos., 119, 8962–8979, https://doi.org/10.1002/2014jd021568,
2014. a, b, c
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013, 2013. a
Liu, Y., Daum, P. H., Guo, H., and Peng, Y.: Dispersion bias, dispersion
effect, and the aerosol-cloud conundrum, Environ. Res. Lett., 3, 045021,
https://doi.org/10.1088/1748-9326/3/4/045021, 2008. a, b, c, d
Liu, Y., Zhang, K., Qian, Y., Wang, Y., Zou, Y., Song, Y., Wan, H., Liu, X., and Yang, X.-Q.: Investigation of short-term effective radiative forcing of fire aerosols over North America using nudged hindcast ensembles, Atmos. Chem. Phys., 18, 31–47, https://doi.org/10.5194/acp-18-31-2018, 2018. a
Lock, A. P.: The Numerical Representation of Entrainment in Parameterizations
of Boundary Layer Turbulent Mixing, Mon. Weather Rev., 129, 1148–1163,
https://doi.org/10.1175/1520-0493(2001)129<1148:TNROEI>2.0.CO;2,
2001. a
Lock, A. P., Brown, A. R., Bush, M. R., Martin, G. M., and Smith, R. N. B.: A
New Boundary Layer Mixing Scheme. Part I: Scheme Description and
Single-Column Model Tests, Mon. Wea. Rev., 128, 3187–3199,
https://doi.org/10.1175/1520-0493(2000)128<3187:anblms>2.0.co;2,
2000. a
Malavelle, F. F., Haywood, J. M., Jones, A., Gettelman, A., Clarisse, L.,
Bauduin, S., Allan, R. P., Karset, I. H. H., Kristjánsson, J. E.,
Oreopoulos, L., Cho, N., Lee, D., Bellouin, N., Boucher, O., Grosvenor,
D. P., Carslaw, K. S., Dhomse, S., Mann, G. W., Schmidt, A., Coe, H.,
Hartley, M. E., Dalvi, M., Hill, A. A., Johnson, B. T., Johnson, C. E.,
Knight, J. R., O'Connor, F. M., Partridge, D. G., Stier, P., Myhre, G.,
Platnick, S., Stephens, G. L., Takahashi, H., and Thordarson, T.: Strong
constraints on aerosol-cloud interactions from
volcanic eruptions, Nature, 546, 485–491, https://doi.org/10.1038/nature22974,
2017. a, b, c, d, e, f, g
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. a, b
Mann, G. W., Carslaw, K. S., Ridley, D. A., Spracklen, D. V., Pringle, K. J., Merikanto, J., Korhonen, H., Schwarz, J. P., Lee, L. A., Manktelow, P. T., Woodhouse, M. T., Schmidt, A., Breider, T. J., Emmerson, K. M., Reddington, C. L., Chipperfield, M. P., and Pickering, S. J.: Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model, Atmos. Chem. Phys., 12, 4449–4476, https://doi.org/10.5194/acp-12-4449-2012, 2012. a, b
Martin, G. M., Johnson, D. W., and Spice, A.: The measurement and
parameterization of effective radius of droplets in warm stratocumulus
clouds, J. Atmos. Sci., 51, 1823–1842,
https://doi.org/10.1175/1520-0469(1994)051<1823:TMAPOE>2.0.CO;2, 1994. a
McCarthy, G. D., Haigh, I. D., Hirschi, J. J.-M., Grist, J. P., and Smeed,
D. A.: Ocean impact on decadal Atlantic climate variability revealed by
sea-level observations, Nature, 521, 508–510, https://doi.org/10.1038/nature14491,
2015. a
McCoy, D. T., Field, P., Gordon, H., Elsaesser, G. S., and Grosvenor, D. P.: Untangling causality in midlatitude aerosol–cloud adjustments, Atmos. Chem. Phys., 20, 4085–4103, https://doi.org/10.5194/acp-20-4085-2020, 2020. a
McCoy, D. T., Bender, F. A.-M., Grosvenor, D. P., Mohrmann, J. K., Hartmann, D. L., Wood, R., and Field, P. R.: Predicting decadal trends in cloud droplet number concentration using reanalysis and satellite data, Atmos. Chem. Phys., 18, 2035–2047, https://doi.org/10.5194/acp-18-2035-2018, 2018. a
Menary, M. B., Hodson, D. L. R., Robson, J. I., Sutton, R. T., Wood, R. A.,
Menary, M. B., Hodson, D. L. R., Robson, J. I., Sutton, R. T., and Wood,
R. A.: A Mechanism of Internal Decadal Atlantic Ocean Variability in a
High-Resolution Coupled Climate Model, J. Climate, 28, 7764–7785,
https://doi.org/10.1175/JCLI-D-15-0106.1,
2015. a
Miles, N. L., Verlinde, J., and Clothiaux, E. E.: Cloud droplet size
distributions in low-level stratiform clouds, J. Atmos. Sci., 57, 295–311,
https://doi.org/10.1175/1520-0469(2000)057<0295:CDSDIL>2.0.CO;2, 2000. a
Miltenberger, A. K., Field, P. R., Hill, A. A., Rosenberg, P., Shipway, B. J., Wilkinson, J. M., Scovell, R., and Blyth, A. M.: Aerosol–cloud interactions in mixed-phase convective clouds – Part 1: Aerosol perturbations, Atmos. Chem. Phys., 18, 3119–3145, https://doi.org/10.5194/acp-18-3119-2018, 2018a. a
Miltenberger, A. K., Field, P. R., Hill, A. A., Shipway, B. J., and Wilkinson, J. M.: Aerosol–cloud interactions in mixed-phase convective clouds – Part 2: Meteorological ensemble, Atmos. Chem. Phys., 18, 10593–10613, https://doi.org/10.5194/acp-18-10593-2018, 2018b. a
Morcrette, C. J.: Improvements to a prognostic cloud scheme through changes to
its cloud erosion parametrization, Atmos. Sci. Lett., 13, 95–102,
https://doi.org/10.1002/asl.374,
2012. a
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., Hardacre, C., Hill, R., Johnson, B., Jones, A., Kipling, Z., Mann, G., Mollard, J., O'Connor, F. M., Palmieri, 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. Discuss., https://doi.org/10.5194/gmd-2019-357, in review, 2020. a, b, c, d, e, f
Mulcahy, J. P., Jones, C., Sellar, A., Johnson, B., Boutle, I. A., Jones, A.,
Andrews, T., Rumbold, S. T., Mollard, J., Bellouin, N., Johnson, C. E.,
Williams, K. D., Grosvenor, D. P., and McCoy, D. T.: Improved Aerosol
Processes and Effective Radiative Forcing in HadGEM3 and UKESM1, J. Adv.
Model. Earth Syst., 10, 2786–2805, https://doi.org/10.1029/2018MS001464, 2018. a, b, c
Mülmenstädt, J. and Feingold, G.: The Radiative Forcing of
Aerosol-Cloud Interactions in Liquid Clouds: Wrestling and Embracing
Uncertainty, Curr. Clim. Chang. Reports, 4, 23–40,
https://doi.org/10.1007/s40641-018-0089-y, 2018. a
Mülmenstädt, J., Gryspeerdt, E., Salzmann, M., Ma, P.-L., Dipu, S., and Quaas, J.: Separating radiative forcing by aerosol–cloud interactions and rapid cloud adjustments in the ECHAM–HAMMOZ aerosol–climate model using the method of partial radiative perturbations, Atmos. Chem. Phys., 19, 15415–15429, https://doi.org/10.5194/acp-19-15415-2019, 2019. a, b, c, d
Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J.,
Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T.,
Robock, A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and
Natural Radiative Forcing, in: limate Change 2013: The Physical Science Basis. Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge
University Press, Cambridge, UK and New York, USA, 659–740, https://doi.org/10.1017/CBO9781107415324.018, 2013. a
Nakajima, T. and King, M. D.: Determination of the optical-thickness and
effective particle radius of clouds from reflected solar-radiation
measurements 1. Theory, J. Atmos. Sci., 47, 1878–1893,
https://doi.org/10.1175/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2, 1990. a
O'Dell, C. W., Wentz, F. J., and Bennartz, R.: Cloud liquid water path from
satellite-based passive microwave observations: A new climatology over the
global oceans, J. Clim., 21, 1721–1739, https://doi.org/10.1175/2007JCLI1958.1, 2008. a
Painemal, D. and Zuidema, P.: Assessment of MODIS cloud effective radius and
optical thickness retrievals over the Southeast Pacific with VOCALS-REx in
situ measurements, J. Geophys. Res.-Atmos., 116, D24206, https://doi.org/10.1029/2011JD016155, 2011. a, b, c
Robson, J., Ortega, P., and Sutton, R.: A reversal of climatic trends in the
North Atlantic since 2005, Nat. Geosci., 9, 513–517,
https://doi.org/10.1038/ngeo2727,
2016. a
Robson, J., Sutton, R. T., Archibald, A., Cooper, F., Christensen, M., Gray,
L. J., Holliday, N. P., Macintosh, C., McMillan, M., Moat, B., Russo, M.,
Tilling, R., Carslaw, K., Desbruyères, D., Embury, O., Feltham, D. L.,
Grosvenor, D. P., Josey, S., King, B., Lewis, A., McCarthy, G. D., Merchant,
C., New, A. L., O'Reilly, C. H., Osprey, S. M., Read, K., Scaife, A.,
Shepherd, A., Sinha, B., Smeed, D., Smith, D., Ridout, A., Woollings, T., and
Yang, M.: Recent multivariate changes in the North Atlantic climate system,
with a focus on 2005–2016, Int. J. Climatol., 38, 5050–5076,
https://doi.org/10.1002/joc.5815, 2018. a
Rossow, W. B., Schiffer, R. A., Rossow, W. B., and Schiffer, R. A.: Advances
in Understanding Clouds from ISCCP, B. Am. Meteorol. Soc., 80,
2261–2287, https://doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2,
1999. a
Salomonson, V. V., Barnes, W. L., Maymon, P. W., Montgomery, H. E., and Ostrow,
H.: MODIS: advanced facility instrument for studies of the
Earth as a system, IEEE Trans. Geosci. Remote Sens., 27, 145–153,
https://doi.org/10.1109/36.20292, 1998. a
Seethala, C. and Horváth, Á.: Global assessment of AMSR-E and
MODIS cloud liquid water path retrievals in warm oceanic clouds, J.
Geophys. Res., 115, D13202, https://doi.org/10.1029/2009JD012662, 2010. a
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics : from
air pollution to climate change, Wiley, Hoboken, NJ, USA, 2006. a
Sellar, A. A., Jones, C. G., Mulcahy, J., Tang, Y., Yool, A., Wiltshire, A.,
O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., Mora,
L., Kuhlbrodt, T., Rumbold, S., Kelley, D. I., Ellis, R., Johnson, C. E.,
Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald, A. T.,
Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M., Edwards, J.,
Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B., Hendry, M. A.,
Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble, J., Liddicoat,
S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson, E., Siahaan, A.,
Smith, R. S., Swaminathan, R., Woodhouse, M. T., Zeng, G., and Zerroukat, M.:
UKESM1: Description and evaluation of the UK Earth System Model, J. Adv.
Model. Earth Syst., 11, 4513–4558, https://doi.org/10.1029/2019ms001739, 2019. a, b, c
Smith, D. M., Eade, R., Dunstone, N. J., Fereday, D., Murphy, J. M., Pohlmann,
H., and Scaife, A. A.: Skilful multi-year predictions of Atlantic
hurricane frequency, Nat. Geosci., 3, 846–849, https://doi.org/10.1038/ngeo1004,
2010. a
Stevens, B., Cotton, W. R., Feingold, G., and Moeng, C.-H.: Large-Eddy
Simulations of Strongly Precipitating, Shallow, Stratocumulus-Topped Boundary
Layers, J. Atmos. Sci., 55, 3616–3638,
https://doi.org/10.1175/1520-0469(1998)055<3616:lesosp>2.0.co;2,
1998. a, b
Stevens, R. G., Loewe, K., Dearden, C., Dimitrelos, A., Possner, A., Eirund, G. K., Raatikainen, T., Hill, A. A., Shipway, B. J., Wilkinson, J., Romakkaniemi, S., Tonttila, J., Laaksonen, A., Korhonen, H., Connolly, P., Lohmann, U., Hoose, C., Ekman, A. M. L., Carslaw, K. S., and Field, P. R.: A model intercomparison of CCN-limited tenuous clouds in the high Arctic, Atmos. Chem. Phys., 18, 11041–11071, https://doi.org/10.5194/acp-18-11041-2018, 2018. a
Sutton, R. T. and Dong, B.: Atlantic Ocean influence on a shift in European
climate in the 1990s, Nat. Geosci., 5, 788–792, https://doi.org/10.1038/ngeo1595,
2012. a
Sutton, R. T. and Hodson, D. L. R.: Atlantic Ocean Forcing of North American
and European Summer Climate, Science, 309, 115–118,
https://doi.org/10.1126/science.1109496,
2005. a
Taylor, K., Williamson, D., and Zwiers, F.: The sea surface temperature and
sea ice concentration boundary conditions for AMIP II simulations, PCMDI
Rep. 60, Progr. Clim. Model Diagnosis Intercomparison, Lawrence Livermore
Natl. Lab., 24 pp., 2000. a
Twomey, S.: The Influence of Pollution on the Shortwave Albedo of Clouds, J.
Atmos. Sci., 34, 1149–1152,
https://doi.org/10.1175/1520-0469(1977)034<1149:tiopot>2.0.co;2,
1977. a
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. a, b
Wentz, F. J. and Meissner, T.: AMSR Ocean Algorithm, Version 2, report number
121599A-1, Tech. rep., Remote Sensing Systems, Santa Rosa, CA, availabe at:
http://images.remss.com/papers/rsstech/2000_121599A-1_Wentz_AMSR_Ocean_ATBD_V2.pdf (last access: 11 December 2020),
2000. a
West, R. E. L., Stier, P., Jones, A., Johnson, C. E., Mann, G. W., Bellouin, N., Partridge, D. G., and Kipling, Z.: The importance of vertical velocity variability for estimates of the indirect aerosol effects, Atmos. Chem. Phys., 14, 6369–6393, https://doi.org/10.5194/acp-14-6369-2014, 2014. a
Williams, K. D., Copsey, D., Blockley, E. W., Bodas-Salcedo, A., Calvert, D.,
Comer, R., Davis, P., Graham, T., Hewitt, H. T., Hill, R., Hyder, P., Ineson,
S., Johns, T. C., Keen, A. B., Lee, R. W., Megann, A., Milton, S. F., Rae,
J. G., Roberts, M. J., Scaife, A. A., Schiemann, R., Storkey, D., Thorpe, L.,
Watterson, I. G., Walters, D. N., West, A., Wood, R. A., Woollings, T., and
Xavier, P. K.: The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and
GC3.1) Configurations, J. Adv. Model. Earth Syst., 10, 357–380,
https://doi.org/10.1002/2017MS001115,
2017. a
Wilson, D. R. and Ballard, S. P.: A microphysically based precipitation scheme
for the UK Meteorological Office Unified Model, Q. J. R. Meteorol. Soc.,
125, 1607–1636, https://doi.org/10.1256/smsqj.55706, 1999. a, b
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. R. Meteorol. Soc., 134, 2093–2107,
https://doi.org/10.1002/qj.333,
2008a. a
Wilson, D. R., Bushell, A. C., Kerr-Munslow, A. M., Price, J. D., Morcrette,
C. J., and Bodas-Salcedo, A.: PC2: A prognostic cloud fraction and
condensation scheme, II: Climate model simulations, Q. J. R. Meteorol. Soc.,
134, 2109–2125, https://doi.org/10.1002/qj.332,
2008b. a
Wood, R.: Drizzle in stratiform boundary layer clouds, Part 1: Vertical and
horizontal structure, J. Atmos. Sci., 62, 3011–3033,
https://doi.org/10.1175/JAS3529.1, 2005. a
Wood, R.: Stratocumulus Clouds, Mon. Weather Rev., 140, 2373–2423,
https://doi.org/10.1175/MWR-D-11-00121.1, 2012. a, b, c
Wood, R., Stemmler, J. D., Rémillard, J., and Jefferson, A.: Low-CCN
concentration air masses over the eastern North Atlantic: Seasonality,
meteorology, and drivers, J. Geophys. Res., 122, 1203–1223,
https://doi.org/10.1002/2016JD025557, 2017. a, b
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. a
Woollings, T., Franzke, C., Hodson, D. L. R., Dong, B., Barnes, E. A., Raible,
C. C., and Pinto, J. G.: Contrasting interannual and multidecadal NAO
variability, Clim. Dynam., 45, 539–556, https://doi.org/10.1007/s00382-014-2237-y,
2015. a
Yan, X., Zhang, R., and Knutson, T. R.: Underestimated AMOC
Variability and Implications for AMV and Predictability in
CMIP Models, Geophys. Res. Lett., 45, 4319–4328,
https://doi.org/10.1029/2018gl077378,
2018. a
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies, Geosci. Model Dev., 6, 1767–1811, https://doi.org/10.5194/gmd-6-1767-2013, 2013. a
Zhang, K., Wan, H., Liu, X., Ghan, S. J., Kooperman, G. J., Ma, P.-L., Rasch, P. J., Neubauer, D., and Lohmann, U.: Technical Note: On the use of nudging for aerosol–climate model intercomparison studies, Atmos. Chem. Phys., 14, 8631–8645, https://doi.org/10.5194/acp-14-8631-2014, 2014. a
Zhang, R. and Delworth, T. L.: Impact of Atlantic multidecadal oscillations on
India/Sahel rainfall and Atlantic hurricanes, Geophys. Res. Lett., 33, L17712,
https://doi.org/10.1029/2006gl026267,
2006. a
Zhang, R., Delworth, T. L., Sutton, R., Hodson, D. L. R., Dixon, K. W., Held,
I. M., Kushnir, Y., Marshall, J., Ming, Y., Msadek, R., Robson, J., Rosati,
A. J., Ting, M., and Vecchi, G. A.: Have Aerosols Caused the Observed
Atlantic Multidecadal Variability?, J. Atmos. Sci., 70, 1135–1144,
https://doi.org/10.1175/jas-d-12-0331.1,
2013.
a
Zhang, R., Sutton, R., Danabasoglu, G., Delworth, T. L., Kim, W. M., Robson,
J., and Yeager, S. G.: Comment on “The Atlantic Multidecadal Oscillation
without a role for ocean circulation”, Science, 352, 1527,
https://doi.org/10.1126/science.aaf1660,
2016. a
Zhang, Z., Ackerman, A. S., Feingold, G., Platnick, S., Pincus, R., and Xue,
H.: Effects of cloud horizontal inhomogeneity and drizzle on remote sensing
of cloud droplet effective radius: Case studies based on large-eddy
simulations, J. Geophys. Res.-Atmos., 117, 1–18,
https://doi.org/10.1029/2012JD017655, 2012. a
Zhang, Z., Werner, F., Cho, H. M., Wind, G., Platnick, S., Ackerman, A. S., Di
Girolamo, L., Marshak, A., and Meyer, K.: A framework based on 2-D Taylor
expansion for quantifying the impacts of subpixel reflectance variance and
covariance on cloud optical thickness and effective radius retrievals based
on the bispectral method, J. Geophys. Res.-Atmos., 121, 7007–7025,
https://doi.org/10.1002/2016JD024837, 2016. a
Zuidema, P., Westwater, E. R., Fairall, C., and Hazen, D.: Ship-based liquid
water path estimates in marine stratocumulus, J. Geophys. Res., 110, D20206,
https://doi.org/10.1029/2005JD005833, 2005. a
Short summary
Particles arising from human activity interact with clouds and affect how much of the Sun's energy is reflected away. Lack of understanding about how to represent this in models leads to large uncertainties in climate predictions. We quantify cloud responses to particles in the latest UK Met Office climate model over the North Atlantic Ocean, showing that, in contrast to suggestions elsewhere, increases in cloud coverage and thickness are important over large areas.
Particles arising from human activity interact with clouds and affect how much of the Sun's...
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