Articles | Volume 19, issue 2
https://doi.org/10.5194/acp-19-1147-2019
© Author(s) 2019. 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-19-1147-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Jan 2019
Research article |
| 30 Jan 2019
| 30 Jan 2019
Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations
Institute of Climate and Atmospheric Sciences, University of Leeds, Leeds, UK
Paul R. Field
Institute of Climate and Atmospheric Sciences, University of Leeds, Leeds, UK
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Gregory S. Elsaesser
Department of Applied Physics and Applied Mathematics, Columbia
University and NASA Goddard Institute for Space Studies, New York, NY, USA
Alejandro Bodas-Salcedo
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Brian H. Kahn
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Mark D. Zelinka
Cloud Processes Research and Modeling Group, Lawrence Livermore
National Laboratory, Livermore, CA, USA
Chihiro Kodama
Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
Thorsten Mauritsen
Max Planck Institute for Meteorology, Hamburg, Germany
Department of Meteorology, Stockholm University, Stockholm, 106 91, Sweden
Benoit Vanniere
National Centre for Atmospheric Science-Climate, Department of
Meteorology, University of Reading, Reading, UK
Malcolm Roberts
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Pier L. Vidale
National Centre for Atmospheric Science-Climate, Department of
Meteorology, University of Reading, Reading, UK
David Saint-Martin
Centre National de Recherches Météorologiques (CNRM),
Météo-France/CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse, France
Aurore Voldoire
Centre National de Recherches Météorologiques (CNRM),
Météo-France/CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse, France
Rein Haarsma
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Adrian Hill
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Ben Shipway
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Jonathan Wilkinson
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
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Bianca Mezzina, Christopher David Roberts, Matthias Aengenheyster, Rohit Ghosh, Malcolm John Roberts, and Marc Batlle Martin
EGUsphere, https://doi.org/10.5194/egusphere-2026-547, https://doi.org/10.5194/egusphere-2026-547, 2026
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Xinyi Huang, Paul R. Field, Ross J. Herbert, Benjamin J. Murray, Floortje van den Heuvel, Daniel P. Grosvenor, Rachel W. N. Sansom, and Kenneth S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2026-311, https://doi.org/10.5194/egusphere-2026-311, 2026
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Timothy W. Juliano, Florian Tornow, Ann M. Fridlind, Andrew S. Ackerman, Gregory S. Elsaesser, Bart Geerts, Christian P. Lackner, David Painemal, Israel Silber, Mikhail Ovchinnikov, Gunilla Svensson, Michael Tjernström, Peng Wu, Alejandro Baró Pérez, Peter Bogenschutz, Dmitry Chechin, Kamal Kant Chandrakar, Jan Chylik, Andrey Debolskiy, Rostislav Fadeev, Anu Gupta, Luisa Ickes, Michail Karalis, Martin Köhler, Branko Kosović, Peter Kuma, Weiwei Li, Evgeny Mortikov, Hugh Morrison, Roel A. J. Neggers, Anna Possner, Tomi Raatikainen, Sami Romakkaniemi, Niklas Schnierstein, Shin-ichiro Shima, Nikita Silin, Mikhail Tolstykh, Lulin Xue, Meng Zhang, and Xue Zheng
EGUsphere, https://doi.org/10.5194/egusphere-2025-6217, https://doi.org/10.5194/egusphere-2025-6217, 2026
Preprint archived
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Models struggle to capture cloud and precipitation processes and their radiative effects in marine cold-air outbreaks. We use a quasi-Lagrangian framework to compare large-eddy simulation (LES) and single-column model (SCM) output with field and satellite observations. With fixed droplet and ice numbers, LES and SCM agree in liquid-only tests. In mixed-phase conditions, LES plausibly capture cloud thinning and breakup, while SCMs largely remain overcast and thereby miss cloud radiative effects.
Mengyu Sun, Paul J. Connolly, Paul R. Field, Declan L. Finney, and Alan M. Blyth
Atmos. Chem. Phys., 25, 18549–18569, https://doi.org/10.5194/acp-25-18549-2025, https://doi.org/10.5194/acp-25-18549-2025, 2025
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We investigated how extra ice particles form inside tropical storm clouds and how they affect rainfall and sunlight reflection. By using a weather model, we found that these extra ice particles can change how clouds grow, reduce heat escaping to space, and slightly shift where rain falls. This helps improve how weather and climate models predict tropical storms.
Anna Zehrung, Andrew D. King, Zebedee Nicholls, Mark D. Zelinka, and Malte Meinshausen
Geosci. Model Dev., 18, 9433–9450, https://doi.org/10.5194/gmd-18-9433-2025, https://doi.org/10.5194/gmd-18-9433-2025, 2025
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The Gregory method is a common approach for calculating the equilibrium climate sensitivity (ECS). However, studies which apply this method lack transparency in how model data is processed prior to calculating the ECS, inhibiting replicability. Different choices of global weighting, net radiative flux variable, anomaly calculation, and linear regression fit can affect the ECS estimates. We investigate the impact of these choices and propose a standardised method for future ECS calculations.
Mengyu Sun, Paul J. Connolly, Paul R. Field, Declan L. Finney, and Alan M. Blyth
EGUsphere, https://doi.org/10.5194/egusphere-2025-5665, https://doi.org/10.5194/egusphere-2025-5665, 2025
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We use a high resolution weather model together with satellite and radar data to study how small particles in the air influence ice and rain in a tropical storm near Darwin. We find that when particle levels are moderate, storm clouds form more ice high in the atmosphere, spread a wider cloud cover, and produce stronger rainfall concentrated in certain regions. These results help improve how weather and climate models represent tropical storms and their rainfall.
Ci Song, Daniel T. McCoy, Isabel L. McCoy, Hunter Brown, Andrew Gettelman, Trude Eidhammer, and Donifan Barahona
Atmos. Chem. Phys., 25, 16063–16083, https://doi.org/10.5194/acp-25-16063-2025, https://doi.org/10.5194/acp-25-16063-2025, 2025
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This study examines how aerosols from human activities alter cloud microphysical properties. Airborne observations from a field campaign are used to constrain an ensemble of global model configurations and their associated cloud property changes. Results show that airborne in-situ measurements of aerosol and cloud properties do provide insight into global changes in cloud microphysics but are sensitive to uncertainties in both airborne measurements and Earth system model emulators.
Ci Song, Daniel McCoy, Andrea Molod, Travis Aerenson, and Donifan Barahona
Atmos. Chem. Phys., 25, 15567–15592, https://doi.org/10.5194/acp-25-15567-2025, https://doi.org/10.5194/acp-25-15567-2025, 2025
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Uncertainty in how clouds respond to aerosols limits predictions of future warming. This study uses GiOcean, a global reanalysis with detailed cloud microphysics to represent aerosol–cloud interactions (ACI). We assess warm cloud responses by comparing variables important for ACI between GiOcean and satellite observations and further evaluate changes in cloud properties using a source–sink budget framework.
Weiyu Zhang, Paul R. Field, Kwinten Van Weverberg, Piers M. Forster, Cyril J. Morcrette, and Alexandru Rap
Atmos. Chem. Phys., 25, 14153–14166, https://doi.org/10.5194/acp-25-14153-2025, https://doi.org/10.5194/acp-25-14153-2025, 2025
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Contrail cirrus is the largest, yet the most uncertain, aviation climate impact term. A newly implemented contrail cirrus scheme in a double-moment cloud microphysics scheme in climate model realistically reproduces the contrail evolution and provides regional forcing estimates within the range reported by other models. The work highlights the importance of initial contrail characteristics and the need for detailed cloud particle representations in climate model contrail simulations.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
Geosci. Model Dev., 18, 7735–7761, https://doi.org/10.5194/gmd-18-7735-2025, https://doi.org/10.5194/gmd-18-7735-2025, 2025
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The Next Generation of Earth Modeling Systems project (nextGEMS) developed two Earth system models that use horizontal grid spacing of 10 km and finer, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS simulated the Earth System climate over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Weronika Osmolska, Charles Chemel, Amanda Maycock, and Paul Field
Weather Clim. Dynam., 6, 1221–1240, https://doi.org/10.5194/wcd-6-1221-2025, https://doi.org/10.5194/wcd-6-1221-2025, 2025
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Extreme cold temperatures have widespread impacts on health, agriculture, infrastructures and the economy. We develop for the first time a methodology to build a catalogue of cold spell events, tracked in space and time. This catalogue is used to examine the behaviour of cold spells and its climatology. The results reveal specific pathways through which cold air affect midlatitudes.
Ting-Chen Chen, Hugues Goosse, Cécile Davrinche, Stephy Libera, Christopher Roberts, Matthias Aengenheyster, Kristian Strommen, Malcolm Roberts, Rohit Ghosh, and Jin-Song von Storch
Weather Clim. Dynam., 6, 1179–1193, https://doi.org/10.5194/wcd-6-1179-2025, https://doi.org/10.5194/wcd-6-1179-2025, 2025
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Southern Annular Mode (SAM) is a leading mode of Southern Hemisphere climate variability, but global models often overestimate its persistence in summer. Bias in SAM persistence is reduced and jet latitude improved using high-resolution sea surface temperature (SST)-prescribed models, pointing to the central role of SSTs. Control experiments explore the influence of model resolution and mesoscale ocean features on SAM persistence, highlighting the complex and subtle nature of air-sea coupling.
August Mikkelsen, Virendra P. Ghate, Daniel T. McCoy, and Hamish Gordon
EGUsphere, https://doi.org/10.5194/egusphere-2025-4434, https://doi.org/10.5194/egusphere-2025-4434, 2025
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In this study, nearly 10 years of data from a radar wind profiler data stationed in the Azores is processed. The sensitivity and dynamic range of the radar are evaluated over time, and a methodology is developed and implemented to remove degraded data. With the remaining data, measurements of turbulence are retrieved and a climatology of wind data during marine conditions is created, showing increased turbulence in the marine boundary layer during autumn and winter months.
Xinyi Huang, Paul R. Field, Benjamin J. Murray, Daniel P. Grosvenor, Floortje van den Heuvel, and Kenneth S. Carslaw
Atmos. Chem. Phys., 25, 11363–11406, https://doi.org/10.5194/acp-25-11363-2025, https://doi.org/10.5194/acp-25-11363-2025, 2025
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Cold-air outbreak (CAO) clouds play a vital role in climate prediction. This study explores the responses of CAO clouds to aerosols and ice production under different environmental conditions. We found that CAO cloud responses vary with cloud temperature and are strongly controlled by the liquid–ice partitioning in these clouds, suggesting the importance of good representations of cloud microphysics properties to predict the behaviours of CAO clouds in a warming climate.
K. S. Apsara, Aravindakshan Jayakumar, Theethai Jacob Anurose, Saji Mohandas, Paul R. Field, Thara Prabhakaran, Mahen Konwar, and Vijayapurapu Srinivasa Prasad
Atmos. Chem. Phys., 25, 11423–11439, https://doi.org/10.5194/acp-25-11423-2025, https://doi.org/10.5194/acp-25-11423-2025, 2025
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Science has made significant strides in weather prediction, especially for intense tropical rainfall that can lead to floods and landslides. Our study aims to improve monsoon rainfall forecasts by analyzing raindrop sizes. Using a new approach to model raindrop growth, we achieved a more accurate depiction of large rainfall events. These improvements can be generalized to enhance early warning systems, offering reliable predictions that help reduce risks from severe tropical weather events.
Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, and Hamish Gordon
Atmos. Chem. Phys., 25, 11157–11182, https://doi.org/10.5194/acp-25-11157-2025, https://doi.org/10.5194/acp-25-11157-2025, 2025
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We study the life cycle of fog events in Europe using a weather and climate model. By incorporating droplet formation and growth driven by radiative cooling, our model better simulates the total liquid water in foggy atmospheric columns. We show that both adiabatic and radiative cooling play significant, often equally important, roles in driving droplet formation and growth. We discuss strategies to address droplet number overpredictions by improving model physics and addressing model artifacts.
Declan L. Finney, Alan M. Blyth, Paul R. Field, Martin I. Daily, Benjamin J. Murray, Mengyu Sun, Paul J. Connolly, Zhiqiang Cui, and Steven Böing
Atmos. Chem. Phys., 25, 10907–10929, https://doi.org/10.5194/acp-25-10907-2025, https://doi.org/10.5194/acp-25-10907-2025, 2025
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We present observation-informed modelling from the Deep Convective Microphysics Experiment (DCMEX) to study how environmental conditions and cloud processes affect anvil cloud albedo and radiation. Aerosols influencing cloud droplets or influencing ice formation yield varying radiative effects. We introduce fingerprint metrics to discern these effects. Using detailed observations and modelling, we offer insights into high-cloud radiative effects and feedbacks.
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
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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.
David Storkey, Pierre Mathiot, Michael J. Bell, Dan Copsey, Catherine Guiavarc'h, Helene T. Hewitt, Jeff Ridley, and Malcolm J. Roberts
Geosci. Model Dev., 18, 2725–2745, https://doi.org/10.5194/gmd-18-2725-2025, https://doi.org/10.5194/gmd-18-2725-2025, 2025
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The Southern Ocean is a key region of the world ocean in the context of climate change studies. We show that the Met Office Hadley Centre coupled model with intermediate ocean resolution struggles to accurately simulate the Southern Ocean. Increasing the frictional drag that the seafloor exerts on ocean currents and introducing a representation of unresolved ocean eddies both appear to reduce the large-scale biases in this model.
August Mikkelsen, Daniel T. McCoy, Trude Eidhammer, Andrew Gettelman, Ci Song, Hamish Gordon, and Isabel L. McCoy
Atmos. Chem. Phys., 25, 4547–4570, https://doi.org/10.5194/acp-25-4547-2025, https://doi.org/10.5194/acp-25-4547-2025, 2025
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Whether increased aerosol increases or decreases liquid cloud mass has been a longstanding question. Observed correlations suggest that aerosols thin liquid cloud, but we are able to show that observations were consistent with an increase in liquid cloud in response to aerosols by leveraging a model where causality could be traced.
Duncan Watson-Parris, Laura J. Wilcox, Camilla W. Stjern, Robert J. Allen, Geeta Persad, Massimo A. Bollasina, Annica M. L. Ekman, Carley E. Iles, Manoj Joshi, Marianne T. Lund, Daniel McCoy, Daniel M. Westervelt, Andrew I. L. Williams, and Bjørn H. Samset
Atmos. Chem. Phys., 25, 4443–4454, https://doi.org/10.5194/acp-25-4443-2025, https://doi.org/10.5194/acp-25-4443-2025, 2025
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In 2020, regulations by the International Maritime Organization aimed to reduce aerosol emissions from ships. These aerosols previously had a cooling effect, which the regulations might reduce, revealing more greenhouse gas warming. Here we find that, while there is regional warming, the global 2020–2040 temperature rise is only +0.03 °C. This small change is difficult to distinguish from natural climate variability, indicating the regulations have had a limited effect on observed warming to date.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Mark D. Zelinka, Li-Wei Chao, Timothy A. Myers, Yi Qin, and Stephen A. Klein
Atmos. Chem. Phys., 25, 1477–1495, https://doi.org/10.5194/acp-25-1477-2025, https://doi.org/10.5194/acp-25-1477-2025, 2025
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Clouds lie at the heart of uncertainty in both climate sensitivity and radiative forcing, making it imperative to properly diagnose their radiative effects. Here we provide a recommended methodology and code base for the community to use in performing such diagnoses using cloud radiative kernels. We show that properly accounting for changes in obscuration of lower-level clouds by upper-level clouds is important for accurate diagnosis and attribution of cloud feedbacks and adjustments.
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025, https://doi.org/10.5194/essd-17-135-2025, 2025
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Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
Weiyu Zhang, Kwinten Van Weverberg, Cyril J. Morcrette, Wuhu Feng, Kalli Furtado, Paul R. Field, Chih-Chieh Chen, Andrew Gettelman, Piers M. Forster, Daniel R. Marsh, and Alexandru Rap
Atmos. Chem. Phys., 25, 473–489, https://doi.org/10.5194/acp-25-473-2025, https://doi.org/10.5194/acp-25-473-2025, 2025
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Contrail cirrus is the largest, but also most uncertain, contribution of aviation to global warming. We evaluate, for the first time, the impact of the host climate model on contrail cirrus properties. Substantial differences exist between contrail cirrus formation, persistence, and radiative effects in the host climate models. Reliable contrail cirrus simulations require advanced representation of cloud optical properties and microphysics, which should be better constrained by observations.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Thomas Hocking, Thorsten Mauritsen, and Linda Megner
Atmos. Meas. Tech., 17, 7077–7095, https://doi.org/10.5194/amt-17-7077-2024, https://doi.org/10.5194/amt-17-7077-2024, 2024
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The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.
Erin N. Raif, Sarah L. Barr, Mark D. Tarn, James B. McQuaid, Martin I. Daily, Steven J. Abel, Paul A. Barrett, Keith N. Bower, Paul R. Field, Kenneth S. Carslaw, and Benjamin J. Murray
Atmos. Chem. Phys., 24, 14045–14072, https://doi.org/10.5194/acp-24-14045-2024, https://doi.org/10.5194/acp-24-14045-2024, 2024
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Ice-nucleating particles (INPs) allow ice to form in clouds at temperatures warmer than −35°C. We measured INP concentrations over the Norwegian and Barents seas in weather events where cold air is ejected from the Arctic. These concentrations were among the highest measured in the Arctic. It is likely that the INPs were transported to the Arctic from distant regions. These results show it is important to consider hemispheric-scale INP processes to understand INP concentrations in the Arctic.
Ashok K. Luhar, Anthony C. Jones, and Jonathan M. Wilkinson
Atmos. Chem. Phys., 24, 14005–14028, https://doi.org/10.5194/acp-24-14005-2024, https://doi.org/10.5194/acp-24-14005-2024, 2024
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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.
Alejandro Uribe, Frida A.-M. Bender, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 13371–13384, https://doi.org/10.5194/acp-24-13371-2024, https://doi.org/10.5194/acp-24-13371-2024, 2024
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Our study explores climate feedbacks, vital for understanding global warming. It links them to shifts in Earth's energy balance at the atmosphere's top due to natural temperature variations. It takes roughly 50 years to establish this connection. Combined satellite observations and reanalysis suggest that Earth cools more than expected under carbon dioxide influence. However, continuous satellite data until at least the mid-2030s are crucial for refining our understanding of climate feedbacks.
Alisée A. Chaigneau, Angélique Melet, Aurore Voldoire, Maialen Irazoqui Apecechea, Guillaume Reffray, Stéphane Law-Chune, and Lotfi Aouf
Nat. Hazards Earth Syst. Sci., 24, 4031–4048, https://doi.org/10.5194/nhess-24-4031-2024, https://doi.org/10.5194/nhess-24-4031-2024, 2024
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Climate-change-induced sea level rise increases the frequency of extreme sea levels. We analyze projected changes in extreme sea levels for western European coasts produced with high-resolution models (∼ 6 km). Unlike commonly used coarse-scale global climate models, this approach allows us to simulate key processes driving coastal sea level variations, such as long-term sea level rise, tides, storm surges induced by low atmospheric surface pressure and winds, waves, and their interactions.
Andrea Mosso, Thomas Hocking, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 12793–12806, https://doi.org/10.5194/acp-24-12793-2024, https://doi.org/10.5194/acp-24-12793-2024, 2024
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Clouds play a crucial role in the Earth's energy balance, as they can either warm up or cool down the area they cover depending on their height and depth. They are expected to alter their behaviour under climate change, affecting the warming generated by greenhouse gases. This paper proposes a new method to estimate their overall effect on this warming by simulating a climate where clouds are transparent. Results show that with the model used, clouds have a stabilising effect on climate.
Marc Mallet, Aurore Voldoire, Fabien Solmon, Pierre Nabat, Thomas Drugé, and Romain Roehrig
Atmos. Chem. Phys., 24, 12509–12535, https://doi.org/10.5194/acp-24-12509-2024, https://doi.org/10.5194/acp-24-12509-2024, 2024
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This study investigates the interactions between smoke aerosols and climate in tropical Africa using a coupled ocean–atmosphere–aerosol climate model. The work shows that smoke plumes have a significant impact by increasing the low-cloud fraction, decreasing the ocean and continental surface temperature and reducing the precipitation of coastal western Africa. It also highlights the role of the ocean temperature response and its feedbacks for the September–November season.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
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We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Antoine Hermant, Linnea Huusko, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 10707–10715, https://doi.org/10.5194/acp-24-10707-2024, https://doi.org/10.5194/acp-24-10707-2024, 2024
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Aerosol particles, from natural and human sources, have a cooling effect on the climate, partially offsetting global warming. They do this through direct (sunlight reflection) and indirect (cloud property alteration) mechanisms. Using a global climate model, we found that, despite declining emissions, the direct effect of human aerosols has increased while the indirect effect has decreased, which is attributed to the shift in emissions from North America and Europe to Southeast Asia.
Jacqueline E. Russell, Richard J. Bantges, Helen E. Brindley, and Alejandro Bodas-Salcedo
Earth Syst. Sci. Data, 16, 4243–4266, https://doi.org/10.5194/essd-16-4243-2024, https://doi.org/10.5194/essd-16-4243-2024, 2024
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We present a dataset of top-of-atmosphere diurnally resolved reflected solar and emitted thermal energy for Earth system model evaluation. The multi-year, monthly hourly dataset, derived from observations made by the Geostationary Earth Radiation Budget instrument, covers the range 60° N–60° S, 60° E–60° W at 1° resolution. Comparison with two versions of the Hadley Centre Global Environmental Model highlight how the data can be used to assess updates to key model parameterizations.
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, Erin McClymont, and Sze Ling Ho
Clim. Past, 20, 1989–1999, https://doi.org/10.5194/cp-20-1989-2024, https://doi.org/10.5194/cp-20-1989-2024, 2024
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We have created a new global surface temperature reconstruction of the climate of the mid-Pliocene Warm Period, representing the period roughly 3.2 million years before the present day. We estimate that the globally averaged mean temperature was around 3.9 °C warmer than it was in pre-industrial times, but there is significant uncertainty in this value.
Raphael Grodofzig, Martin Renoult, and Thorsten Mauritsen
Earth Syst. Dynam., 15, 913–927, https://doi.org/10.5194/esd-15-913-2024, https://doi.org/10.5194/esd-15-913-2024, 2024
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We investigate whether the Amazon rainforest has lost substantial resilience since 1990. This assertion is based on trends in the observational record of vegetation density. We calculate the same metrics in a large number of climate model simulations and find that several models behave indistinguishably from the observations, suggesting that the observed trend could be caused by internal variability and that the cause of the ongoing rapid loss of Amazon rainforest is not mainly global warming.
Omar V. Müller, Patrick C. McGuire, Pier Luigi Vidale, and Ed Hawkins
Hydrol. Earth Syst. Sci., 28, 2179–2201, https://doi.org/10.5194/hess-28-2179-2024, https://doi.org/10.5194/hess-28-2179-2024, 2024
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This work evaluates how rivers are projected to change in the near future compared to the recent past in the context of a warming world. We show that important rivers of the world will notably change their flows, mainly during peaks, exceeding the variations that rivers used to exhibit. Such large changes may produce more frequent floods, alter hydropower generation, and potentially affect the ocean's circulation.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Ming Luo, Helen M. Worden, Robert D. Field, Kostas Tsigaridis, and Gregory S. Elsaesser
Atmos. Meas. Tech., 17, 2611–2624, https://doi.org/10.5194/amt-17-2611-2024, https://doi.org/10.5194/amt-17-2611-2024, 2024
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The TROPESS CrIS single-pixel CO profile retrievals are compared to the MOPITT CO products in steps of adjusting them to the common a priori assumptions. The two data sets are found to agree within 5 %. We also demonstrated and analyzed the proper steps in evaluating GISS ModelE CO simulations using satellite CO retrieval products for the western US wildfire events in September 2020.
Declan L. Finney, Alan M. Blyth, Martin Gallagher, Huihui Wu, Graeme J. Nott, Michael I. Biggerstaff, Richard G. Sonnenfeld, Martin Daily, Dan Walker, David Dufton, Keith Bower, Steven Böing, Thomas Choularton, Jonathan Crosier, James Groves, Paul R. Field, Hugh Coe, Benjamin J. Murray, Gary Lloyd, Nicholas A. Marsden, Michael Flynn, Kezhen Hu, Navaneeth M. Thamban, Paul I. Williams, Paul J. Connolly, James B. McQuaid, Joseph Robinson, Zhiqiang Cui, Ralph R. Burton, Gordon Carrie, Robert Moore, Steven J. Abel, Dave Tiddeman, and Graydon Aulich
Earth Syst. Sci. Data, 16, 2141–2163, https://doi.org/10.5194/essd-16-2141-2024, https://doi.org/10.5194/essd-16-2141-2024, 2024
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The DCMEX (Deep Convective Microphysics Experiment) project undertook an aircraft- and ground-based measurement campaign of New Mexico deep convective clouds during July–August 2022. The campaign coordinated a broad range of instrumentation measuring aerosol, cloud physics, radar signals, thermodynamics, dynamics, electric fields, and weather. The project's objectives included the utilisation of these data with satellite observations to study the anvil cloud radiative effect.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Clare Marie Flynn, Linnea Huusko, Angshuman Modak, and Thorsten Mauritsen
Atmos. Chem. Phys., 23, 15121–15133, https://doi.org/10.5194/acp-23-15121-2023, https://doi.org/10.5194/acp-23-15121-2023, 2023
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The latest-generation climate models show surprisingly cold mid-20th century global-mean temperatures, often despite exhibiting more realistic late 20th/early 21st century temperatures. A too-strong aerosol forcing in many models was thought to the be primary cause of these too-cold mid-century temperatures, but this was found to only be a partial explanation. This also partly undermines the hope to construct a strong relationship between the mid-century temperatures and aerosol forcing.
Jon Seddon, Ag Stephens, Matthew S. Mizielinski, Pier Luigi Vidale, and Malcolm J. Roberts
Geosci. Model Dev., 16, 6689–6700, https://doi.org/10.5194/gmd-16-6689-2023, https://doi.org/10.5194/gmd-16-6689-2023, 2023
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The PRIMAVERA project aimed to develop a new generation of advanced global climate models. The large volume of data generated was uploaded to a central analysis facility (CAF) and was analysed by 100 PRIMAVERA scientists there. We describe how the PRIMAVERA project used the CAF's facilities to enable users to analyse this large dataset. We believe that similar, multi-institute, big-data projects could also use a CAF to efficiently share, organise and analyse large volumes of data.
Brian Kahn, Cameron Bertossa, Xiuhong Chen, Brian Drouin, Erin Hokanson, Xianglei Huang, Tristan L'Ecuyer, Kyle Mattingly, Aronne Merrelli, Tim Michaels, Nate Miller, Federico Donat, Tiziano Maestri, and Michele Martinazzo
EGUsphere, https://doi.org/10.5194/egusphere-2023-2463, https://doi.org/10.5194/egusphere-2023-2463, 2023
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A cloud detection mask algorithm is developed for the upcoming Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) satellite mission to be launched by NASA in May 2024. The cloud mask is compared to "truth" and is capable of detecting over 90 % of all clouds globally tested with simulated data, and about 87 % of all clouds in the Arctic region.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavčič, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 16, 5601–5626, https://doi.org/10.5194/gmd-16-5601-2023, https://doi.org/10.5194/gmd-16-5601-2023, 2023
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Three-dimensional climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
Sushant Das, Frida Bender, and Thorsten Mauritsen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1605, https://doi.org/10.5194/egusphere-2023-1605, 2023
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Quantifying global and Indian precipitation responses to anthropogenic aerosol and CO2 forcings using multiple models is needed for reducing climate uncertainty. The response to global warming from CO2 increases precipitation both globally and over India, whereas the cooling response to sulfate aerosol leads to a reduction in precipitation in both cases. An opposite response to black carbon is noted i.e., a global decrease but an increase of precipitation over India implying changes in dynamics.
Mark D. Zelinka, Christopher J. Smith, Yi Qin, and Karl E. Taylor
Atmos. Chem. Phys., 23, 8879–8898, https://doi.org/10.5194/acp-23-8879-2023, https://doi.org/10.5194/acp-23-8879-2023, 2023
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The primary uncertainty in how strongly Earth's climate has been perturbed by human activities comes from the unknown radiative impact of aerosol changes. Accurately quantifying these forcings – and their sub-components – in climate models is crucial for understanding the past and future simulated climate. In this study we describe biases in previously published estimates of aerosol radiative forcing in climate models and provide corrected estimates along with code for users to compute them.
Emmanouil Flaounas, Leonardo Aragão, Lisa Bernini, Stavros Dafis, Benjamin Doiteau, Helena Flocas, Suzanne L. Gray, Alexia Karwat, John Kouroutzoglou, Piero Lionello, Mario Marcello Miglietta, Florian Pantillon, Claudia Pasquero, Platon Patlakas, María Ángeles Picornell, Federico Porcù, Matthew D. K. Priestley, Marco Reale, Malcolm J. Roberts, Hadas Saaroni, Dor Sandler, Enrico Scoccimarro, Michael Sprenger, and Baruch Ziv
Weather Clim. Dynam., 4, 639–661, https://doi.org/10.5194/wcd-4-639-2023, https://doi.org/10.5194/wcd-4-639-2023, 2023
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Cyclone detection and tracking methods (CDTMs) have different approaches in defining and tracking cyclone centers. This leads to disagreements on extratropical cyclone climatologies. We present a new approach that combines tracks from individual CDTMs to produce new composite tracks. These new tracks are shown to correspond to physically meaningful systems with distinctive life stages.
Alisée A. Chaigneau, Stéphane Law-Chune, Angélique Melet, Aurore Voldoire, Guillaume Reffray, and Lotfi Aouf
Ocean Sci., 19, 1123–1143, https://doi.org/10.5194/os-19-1123-2023, https://doi.org/10.5194/os-19-1123-2023, 2023
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Wind waves and swells are major drivers of coastal environment changes and can drive coastal marine hazards such as coastal flooding. In this paper, by using numerical modeling along the European Atlantic coastline, we assess how present and future wave characteristics are impacted by sea level changes. For example, at the end of the century under the SSP5-8.5 climate change scenario, extreme significant wave heights are higher by up to +40 % due to the effect of tides and mean sea level rise.
Mark T. Richardson, Brian H. Kahn, and Peter Kalmus
Atmos. Chem. Phys., 23, 7699–7717, https://doi.org/10.5194/acp-23-7699-2023, https://doi.org/10.5194/acp-23-7699-2023, 2023
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Convection over land often triggers hours after a satellite last passed overhead and measured the state of the atmosphere, and during those hours the atmosphere can change greatly. Here we show that it is possible to reconstruct most of those changes by using weather forecast winds to predict where warm and moist air parcels will travel. The results can be used to better predict where precipitation is likely to happen in the hours after satellite measurements.
Angshuman Modak and Thorsten Mauritsen
Atmos. Chem. Phys., 23, 7535–7549, https://doi.org/10.5194/acp-23-7535-2023, https://doi.org/10.5194/acp-23-7535-2023, 2023
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We provide an improved estimate of equilibrium climate sensitivity (ECS) constrained based on the instrumental temperature record including the corrections for the pattern effect. The improved estimate factors in the uncertainty caused by the underlying sea-surface temperature datasets used in the estimates of pattern effect. This together with the inter-model spread lifts the corresponding IPCC AR6 estimate to 3.2 K [1.8 to 11.0], which is lower and better constrained than in past studies.
Thibault Guinaldo, Aurore Voldoire, Robin Waldman, Stéphane Saux Picart, and Hervé Roquet
Ocean Sci., 19, 629–647, https://doi.org/10.5194/os-19-629-2023, https://doi.org/10.5194/os-19-629-2023, 2023
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In the summer of 2022, France experienced a series of unprecedented heatwaves. This study is the first to examine the response of sea surface temperatures to these events, using spatial operational data and attributing the observed abnormally warm SSTs to atmospheric forcings. The findings of this study underscore the critical need for an efficient and sustainable operational system to monitor alterations that threaten the oceans in the context of climate change.
Gillian Young McCusker, Jutta Vüllers, Peggy Achtert, Paul Field, Jonathan J. Day, Richard Forbes, Ruth Price, Ewan O'Connor, Michael Tjernström, John Prytherch, Ryan Neely III, and Ian M. Brooks
Atmos. Chem. Phys., 23, 4819–4847, https://doi.org/10.5194/acp-23-4819-2023, https://doi.org/10.5194/acp-23-4819-2023, 2023
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In this study, we show that recent versions of two atmospheric models – the Unified Model and Integrated Forecasting System – overestimate Arctic cloud fraction within the lower troposphere by comparison with recent remote-sensing measurements made during the Arctic Ocean 2018 expedition. The overabundance of cloud is interlinked with the modelled thermodynamic structure, with strong negative temperature biases coincident with these overestimated cloud layers.
Jane P. Mulcahy, Colin G. Jones, Steven T. Rumbold, Till Kuhlbrodt, Andrea J. Dittus, Edward W. Blockley, Andrew Yool, Jeremy Walton, Catherine Hardacre, Timothy Andrews, Alejandro Bodas-Salcedo, Marc Stringer, Lee de Mora, Phil Harris, Richard Hill, Doug Kelley, Eddy Robertson, and Yongming Tang
Geosci. Model Dev., 16, 1569–1600, https://doi.org/10.5194/gmd-16-1569-2023, https://doi.org/10.5194/gmd-16-1569-2023, 2023
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Recent global climate models simulate historical global mean surface temperatures which are too cold, possibly to due to excessive aerosol cooling. This raises questions about the models' ability to simulate important climate processes and reduces confidence in future climate predictions. We present a new version of the UK Earth System Model, which has an improved aerosols simulation and a historical temperature record. Interestingly, the long-term response to CO2 remains largely unchanged.
Ruth Price, Andrea Baccarini, Julia Schmale, Paul Zieger, Ian M. Brooks, Paul Field, and Ken S. Carslaw
Atmos. Chem. Phys., 23, 2927–2961, https://doi.org/10.5194/acp-23-2927-2023, https://doi.org/10.5194/acp-23-2927-2023, 2023
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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.
Martin Renoult, Navjit Sagoo, Jiang Zhu, and Thorsten Mauritsen
Clim. Past, 19, 323–356, https://doi.org/10.5194/cp-19-323-2023, https://doi.org/10.5194/cp-19-323-2023, 2023
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The relationship between the Last Glacial Maximum and the sensitivity of climate models to a doubling of CO2 can be used to estimate the true sensitivity of the Earth. However, this relationship has varied in successive model generations. In this study, we assess multiple processes at the Last Glacial Maximum which weaken this relationship. For example, how models respond to the presence of ice sheets is a large contributor of uncertainty.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Julia F. Lockwood, Galina S. Guentchev, Alexander Alabaster, Simon J. Brown, Erika J. Palin, Malcolm J. Roberts, and Hazel E. Thornton
Nat. Hazards Earth Syst. Sci., 22, 3585–3606, https://doi.org/10.5194/nhess-22-3585-2022, https://doi.org/10.5194/nhess-22-3585-2022, 2022
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We describe how we developed a set of 1300 years' worth of European winter windstorm footprints, using a multi-model ensemble of high-resolution global climate models, for use by the insurance industry to analyse windstorm risk. The large amount of data greatly reduces uncertainty on risk estimates compared to using shorter observational data sets and also allows the relationship between windstorm risk and predictable large-scale climate indices to be quantified.
Rafaela Jane Delfino, Gerry Bagtasa, Kevin Hodges, and Pier Luigi Vidale
Nat. Hazards Earth Syst. Sci., 22, 3285–3307, https://doi.org/10.5194/nhess-22-3285-2022, https://doi.org/10.5194/nhess-22-3285-2022, 2022
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We showed the effects of altering the choice of cumulus schemes, surface flux options, and spectral nudging with a high level of sensitivity to cumulus schemes in simulating an intense typhoon. We highlight the advantage of using an ensemble of cumulus parameterizations to take into account the uncertainty in simulating typhoons such as Haiyan in 2013. This study is useful in addressing the growing need to plan and prepare for as well as reduce the impacts of intense typhoons in the Philippines.
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
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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.
James D. Annan, Julia C. Hargreaves, and Thorsten Mauritsen
Clim. Past, 18, 1883–1896, https://doi.org/10.5194/cp-18-1883-2022, https://doi.org/10.5194/cp-18-1883-2022, 2022
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We have created a new global surface temperature reconstruction of the climate of the Last Glacial Maximum, representing the period 19–23 000 years before the present day. We find that the globally averaged mean temperature was roughly 4.5 °C colder than it was in pre-industrial times, albeit there is significant uncertainty on this value.
Walter Hannah, Kyle Pressel, Mikhail Ovchinnikov, and Gregory Elsaesser
Geosci. Model Dev., 15, 6243–6257, https://doi.org/10.5194/gmd-15-6243-2022, https://doi.org/10.5194/gmd-15-6243-2022, 2022
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An unphysical checkerboard signal is identified in two configurations of the atmospheric component of E3SM. The signal is very persistent and visible after averaging years of data. The signal is very difficult to study because it is often mixed with realistic weather. A method is presented to detect checkerboard patterns and compare the model with satellite observations. The causes of the signal are identified, and a solution for one configuration is discussed.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Edward Gryspeerdt, Daniel T. McCoy, Ewan Crosbie, Richard H. Moore, Graeme J. Nott, David Painemal, Jennifer Small-Griswold, Armin Sorooshian, and Luke Ziemba
Atmos. Meas. Tech., 15, 3875–3892, https://doi.org/10.5194/amt-15-3875-2022, https://doi.org/10.5194/amt-15-3875-2022, 2022
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Droplet number concentration is a key property of clouds, influencing a variety of cloud processes. It is also used for estimating the cloud response to aerosols. The satellite retrieval depends on a number of assumptions – different sampling strategies are used to select cases where these assumptions are most likely to hold. Here we investigate the impact of these strategies on the agreement with in situ data, the droplet number climatology and estimates of the indirect radiative forcing.
Ambrogio Volonté, Andrew G. Turner, Reinhard Schiemann, Pier Luigi Vidale, and Nicholas P. Klingaman
Weather Clim. Dynam., 3, 575–599, https://doi.org/10.5194/wcd-3-575-2022, https://doi.org/10.5194/wcd-3-575-2022, 2022
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In this study we analyse the complex seasonal evolution of the East Asian summer monsoon. Using reanalysis data, we show the importance of the interaction between tropical and extratropical air masses converging at the monsoon front, particularly during its northward progression. The upper-level flow pattern (e.g. the westerly jet) controls the balance between the airstreams and thus the associated rainfall. This framework provides a basis for studies of extreme events and climate variability.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Qing Yue, Eric J. Fetzer, Likun Wang, Brian H. Kahn, Nadia Smith, John M. Blaisdell, Kerry G. Meyer, Mathias Schreier, Bjorn Lambrigtsen, and Irina Tkatcheva
Atmos. Meas. Tech., 15, 2099–2123, https://doi.org/10.5194/amt-15-2099-2022, https://doi.org/10.5194/amt-15-2099-2022, 2022
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The self-consistency and continuity of cloud retrievals from infrared sounders and imagers aboard Aqua and SNPP (Suomi National Polar-orbiting Partnership) are examined at the pixel scale. Cloud products are found to be consistent with each other. Differences between sounder products are mainly due to cloud clearing and the treatment of clouds in scenes with unsuccessful atmospheric retrievals. The impact of algorithm and instrument differences is clearly seen in the imager cloud retrievals.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Kalli Furtado and Paul Field
Atmos. Chem. Phys., 22, 3391–3407, https://doi.org/10.5194/acp-22-3391-2022, https://doi.org/10.5194/acp-22-3391-2022, 2022
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The complex processes involved mean that no simple answer to this
question has so far been discovered: do aerosols increase or decrease precipitation? Using high-resolution weather simulations, we find a self-similar property of rainfall that is not affected by aerosols. Using this invariant, we can collapse all our simulations to a single curve. So, although aerosol effects on rain are many, there may be a universal constraint on the number of degrees of freedom needed to represent them.
Alisée A. Chaigneau, Guillaume Reffray, Aurore Voldoire, and Angélique Melet
Geosci. Model Dev., 15, 2035–2062, https://doi.org/10.5194/gmd-15-2035-2022, https://doi.org/10.5194/gmd-15-2035-2022, 2022
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Climate-change-induced sea level rise is a major threat for coastal and low-lying regions. Projections of coastal sea level changes are thus of great interest for coastal risk assessment and have significantly developed in recent years. In this paper, the objective is to provide high-resolution (6 km) projections of sea level changes in the northeastern Atlantic region bordering western Europe. For that purpose, a regional model is used to refine existing coarse global projections.
Zhiqiang Cui, Alan Blyth, Yahui Huang, Gary Lloyd, Thomas Choularton, Keith Bower, Paul Field, Rachel Hawker, and Lindsay Bennett
Atmos. Chem. Phys., 22, 1649–1667, https://doi.org/10.5194/acp-22-1649-2022, https://doi.org/10.5194/acp-22-1649-2022, 2022
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High concentrations of ice particles were observed at temperatures greater than about –8 C. The default scheme of the secondary ice production cannot explain the high concentrations. Relaxing the conditions for secondary ice production or considering dust aerosol alone is insufficient to produce the observed amount of ice particles. It is likely that multi-thermals play an important role in producing very high concentrations of secondary ice particles in some tropical clouds.
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.
Eduardo Moreno-Chamarro, Louis-Philippe Caron, Saskia Loosveldt Tomas, Javier Vegas-Regidor, Oliver Gutjahr, Marie-Pierre Moine, Dian Putrasahan, Christopher D. Roberts, Malcolm J. Roberts, Retish Senan, Laurent Terray, Etienne Tourigny, and Pier Luigi Vidale
Geosci. Model Dev., 15, 269–289, https://doi.org/10.5194/gmd-15-269-2022, https://doi.org/10.5194/gmd-15-269-2022, 2022
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Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
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Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Mark R. Muetzelfeldt, Reinhard Schiemann, Andrew G. Turner, Nicholas P. Klingaman, Pier Luigi Vidale, and Malcolm J. Roberts
Hydrol. Earth Syst. Sci., 25, 6381–6405, https://doi.org/10.5194/hess-25-6381-2021, https://doi.org/10.5194/hess-25-6381-2021, 2021
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Simulating East Asian Summer Monsoon (EASM) rainfall poses many challenges because of its multi-scale nature. We evaluate three setups of a 14 km global climate model against observations to see if they improve simulated rainfall. We do this over catchment basins of different sizes to estimate how model performance depends on spatial scale. Using explicit convection improves rainfall diurnal cycle, yet more model tuning is needed to improve mean and intensity biases in simulated summer rainfall.
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.
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
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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.
Cited articles
AIRS Science Team/Joao Texeira: AIRS/Aqua L2 Support Retrieval
(AIRS + AMSU) V006, Goddard Earth Sciences Data and
Information Services Center (GES DISC), Greenbelt, MD, USA, https://doi.org/10.5067/Aqua/AIRS/DATA207, 2013.
Barnes, E. A. and Polvani, L.: Response of the Midlatitude Jets, and of
Their Variability, to Increased Greenhouse Gases in the CMIP5 Models,
J. Climate, 26, 7117–7135, https://doi.org/10.1175/jcli-d-12-00536.1, 2013.
Beare, R. J.: Boundary layer mechanisms in extratropical cyclones, Q. J. Roy. Meteor. Soc., 133, 503–515,
https://doi.org/10.1002/qj.30, 2007.
Bender, F. A. M., Charlson, R. J., Ekman, A. M. L., and Leahy, L. V.:
Quantification of Monthly Mean Regional-Scale Albedo of Marine Stratiform
Clouds in Satellite Observations and GCMs, J. Appl. Meteorol. Clim., 50, 2139–2148, https://doi.org/10.1175/jamc-d-11-049.1, 2011a.
Bender, F. A. M., Ramanathan, V., and Tselioudis, G.: Changes in
extratropical storm track cloudiness 1983–2008: observational support for a
poleward shift, Clim. Dynam., 38, 2037–2053, https://doi.org/10.1007/s00382-011-1065-6,
2011b.
Bender, F. A. M., Engström, A., Wood, R., and Charlson, R. J.:
Evaluation of Hemispheric Asymmetries in Marine Cloud Radiative Properties,
J. Climate, 30, 4131–4147, https://doi.org/10.1175/JCLI-D-16-0263.1, 2017.
Bengtsson, L., Hodges, K. I., and Roeckner, E.: Storm tracks and climate
change, J. Climate, 19, 3518–3543, 2006.
Bengtsson, L., Hodges, K. I., and Keenlyside, N.: Will Extratropical Storms
Intensify in a Warmer Climate?, J. Climate, 22, 2276–2301,
https://doi.org/10.1175/2008jcli2678.1, 2009.
Bennartz, R., Fan, J., Rausch, J., Leung, L. R., and Heidinger, A. K.:
Pollution from China increases cloud droplet number, suppresses rain over
the East China Sea, Geophys. Res. Lett., 38, L09704, https://doi.org/10.1029/2011gl047235,
2011.
Betts, A. K. and Harshvardhan: Thermodynamic constraint on the cloud liquid
water feedback in climate models, J. Geophys. Res.-Atmos., 92, 8483–8485, https://doi.org/10.1029/JD092iD07p08483, 1987.
Blender, R. and Schubert, M.: Cyclone tracking in different spatial and
temporal resolutions, Mon. Weather Rev., 128, 377–384, 2000.
Blossey, P. N., Bretherton, C. S., Zhang, M. H., Cheng, A. N., Endo, S.,
Heus, T., Liu, Y. G., Lock, A. P., de Roode, S. R., and Xu, K. M.: Marine
low cloud sensitivity to an idealized climate change: The CGILS LES
intercomparison, J. Adv. Model. Earth Sy., 5, 234–258, https://doi.org/10.1002/jame.20025,
2013.
Bodas-Salcedo, A.: Cloud Condensate and Radiative Feedbacks at Midlatitudes
in an Aquaplanet, Geophys. Res. Lett., 45, 3635–3643, https://doi.org/10.1002/2018GL077217,
2018.
Bodas-Salcedo, A., Williams, K. D., Ringer, M. A., Beau, I., Cole, J. N. S.,
Dufresne, J. L., Koshiro, T., Stevens, B., Wang, Z., and Yokohata, T.:
Origins of the Solar Radiation Biases over the Southern Ocean in CFMIP2
Models, J. Climate, 27, 41–56, https://doi.org/10.1175/jcli-d-13-00169.1, 2014.
Bodas-Salcedo, A., Andrews, T., Karmalkar, A. V., and Ringer, M. A.: Cloud
liquid water path and radiative feedbacks over the Southern Ocean, Geophys.
Res. Lett., 43, 10938–10946, https://doi.org/10.1002/2016GL070770, 2016.
Bosilovich, M., Akella, S., Coy, L., Cullather, R., Draper, C., and Gelaro,
R.: MERRA-2, Initial evaluation of the climate, Tech. Rep. Ser., Global
Modeling and Data Assimilation, edited by: Koster, R. D.,
NASA/TM-2015-104606, 2015.
Bretherton, C. S., Blossey, P. N., and Jones, C. R.: Mechanisms of marine
low cloud sensitivity to idealized climate perturbations: A single-LES
exploration extending the CGILS cases, J. Adv. Model. Earth Sy., 5,
316–337, https://doi.org/10.1002/jame.20019, 2013.
Bretherton, C. S.: Insights into low-latitude cloud feedbacks from
high-resolution models, Philos. T. Roy. Soc. A, 373, 20140415, 2015.
Bretherton, C. S. and Blossey, P. N.: Low cloud reduction in a
greenhouse-warmed climate: Results from Lagrangian LES of a subtropical
marine cloudiness transition, J. Adv. Model. Earth Sy., 6, 91–114, https://doi.org/10.1002/2013MS000250, 2014.
Caldwell, P. M., Zelinka, M. D., Taylor, K. E., and Marvel, K.: Quantifying
the Sources of Intermodel Spread in Equilibrium Climate Sensitivity, J. Climate, 29, 513–524, https://doi.org/10.1175/jcli-d-15-0352.1, 2016.
Catto, J. L.: Extratropical cyclone classification and its use in climate
studies, Rev. Geophys., 54, 486–520, https://doi.org/10.1002/2016RG000519, 2016.
Catto, J. L., Shaffrey, L. C., and Hodges, K. I.: Can climate models capture
the structure of extratropical cyclones?, J. Climate, 23, 1621–1635,
2010.
Ceppi, P., Hartmann, D. L., and Webb, M. J.: Mechanisms of the Negative
Shortwave Cloud Feedback in Middle to High Latitudes, J. Climate,
29, 139–157, https://doi.org/10.1175/JCLI-D-15-0327.1, 2016a.
Ceppi, P., McCoy, D. T., and Hartmann, D. L.: Observational evidence for a
negative shortwave cloud feedback in middle to high latitudes, Geophys. Res.
Lett., 43, 1331–1339, https://doi.org/10.1002/2015gl067499, 2016b.
Charlson, R. J., Lovelock, J. E., Andreae, M. O., and Warren, S. G.: Oceanic
phytoplankton, atmospheric sulfur, cloud albedo and climate, Nature, 326,
655–661, https://doi.org/10.1038/326655a0, 1987.
Cheng, A. N., Xu, K. M., Hu, Y. X., and Kato, S.: Impact of a cloud
thermodynamic phase parameterization based on CALIPSO observations on climate
simulation, J. Geophys. Res.-Atmos., 117, 15, https://doi.org/10.1029/2011jd017263,
2012.
Choi, Y. S., Ho, C. H., Park, C. E., Storelvmo, T., and Tan, I.: Influence
of cloud phase composition on climate feedbacks, J. Geophys. Res.-Atmos., 119, 3687–3700, 2014.
Chubb, T. H., Jensen, J. B., Siems, S. T., and Manton, M. J.: In situ
observations of supercooled liquid clouds over the Southern Ocean during the
HIAPER Pole-to-Pole Observation campaigns, Geophys. Res. Lett.,
40, 5280–5285, https://doi.org/10.1002/grl.50986, 2013.
Clement, A. C., Burgman, R., and Norris, J. R.: Observational and Model
Evidence for Positive Low-Level Cloud Feedback, Science, 325, 460–464, 2009.
Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran,
P., Hinton, T., Hughes, J., Jones, C. D., Joshi, M., Liddicoat, S., Martin,
G., O'Connor, F., Rae, J., Senior, C., Sitch, S., Totterdell, I., Wiltshire,
A., and Woodward, S.: Development and evaluation of an Earth-System model –
HadGEM2, Geosci. Model Dev., 4, 1051–1075,
https://doi.org/10.5194/gmd-4-1051-2011, 2011.
Doelling, D. R., Haney, C. O., Scarino, B. R., Gopalan, A., and Bhatt, R.:
Improvements to the Geostationary Visible Imager Ray-Matching Calibration
Algorithm for CERES Edition 4, J. Atmos. Ocean. Tech., 33, 2679–2698,
https://doi.org/10.1175/jtech-d-16-0113.1, 2016.
Donelan, M. A., Haus, B. K., Reul, N., Plant, W. J., Stiassnie, M., Graber,
H. C., Brown, O. B., and Saltzman, E. S.: On the limiting aerodynamic
roughness of the ocean in very strong winds, Geophys. Res. Lett., 31, L18306, https://doi.org/10.1029/2004GL019460, 2004.
Dufresne, J.-L., Foujols, M.-A., Denvil, S., Caubel, A., Marti, O., Aumont,
O., Balkanski, Y., Bekki, S., Bellenger, H., and Benshila, R.: Climate change
projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5, Clim.
Dynam., 40, 2123–2165, 2013.
Eckhardt, S., Stohl, A., Wernli, H., James, P., Forster, C., and Spichtinger,
N.: A 15-Year Climatology of Warm Conveyor Belts, J. Climate, 17, 218–237,
https://doi.org/10.1175/1520-0442(2004)017<0218:aycowc>2.0.co;2, 2004.
Elsaesser, G. S., O'Dell, C. W., Lebsock, M. D., Bennartz, R., Greenwald, T.
J., and Wentz, F. J.: The Multi-Sensor Advanced Climatology of Liquid Water
Path (MAC-LWP), J. Climate, 30, 10193–10210, https://doi.org/10.1175/jcli-d-16-0902.1, 2017.
Field, P. R. and Wood, R.: Precipitation and Cloud Structure in Midlatitude
Cyclones, J. Climate, 20, 233–254, https://doi.org/10.1175/JCLI3998.1, 2007.
Field, P. R., Gettelman, A., Neale, R. B., Wood, R., Rasch, P. J., and
Morrison, H.: Midlatitude Cyclone Compositing to Constrain Climate Model
Behavior Using Satellite Observations, J. Climate, 21, 5887–5903,
https://doi.org/10.1175/2008JCLI2235.1, 2008.
Field, P. R., Bodas-Salcedo, A., and Brooks, M. E.: Using model analysis and
satellite data to assess cloud and precipitation in midlatitude cyclones,
Q. J. Roy. Meteor. Soc., 137, 1501–1515, https://doi.org/10.1002/qj.858, 2011.
Field, P. R. and Heymsfield, A. J.: Importance of snow to global
precipitation, Geophys. Res. Lett., 42, 9512–9520, https://doi.org/10.1002/2015GL065497,
2015.
Field, P. R., Broz̆ková, R., Chen, M., Dudhia, J., Lac, C., Hara, T.,
Honnert, R., Olson, J., Siebesma, P., de Roode, S., Tomassini, L., Hill, A.,
and McTaggart-Cowan, R.: Exploring the convective grey zone with regional
simulations of a cold air outbreak, Q. J. Roy. Meteor. Soc., 143, 2537–2555, https://doi.org/10.1002/qj.3105, 2017.
Geng, Q. and Sugi, M.: Possible change of extratropical cyclone activity
due to enhanced greenhouse gases and sulfate aerosols – Study with a
high-resolution AGCM, J. Climate, 16, 2262–2274, 2003.
Giorgetta, M. A., Brokopf, R., Crueger, T., Esch, M., Fiedler, S., Helmert,
J., Hohenegger, C., Kornblueh, L., Köhler, M., and Manzini, E.: ICON-A,
the atmosphere component of the ICON Earth System Model. Part I: Model
Description, J. Adv. Model. Earth Sy., 10, 1613–1637, 2018.
Gordon, N. D. and Klein, S. A.: Low-cloud optical depth feedback in climate
models, J. Geophys. Res.-Atmos., 119, 6052–6065, https://doi.org/10.1002/2013JD021052, 2014.
Grandey, B. S., Stier, P., Grainger, R. G., and Wagner, T. M.: The
contribution of the strength and structure of extratropical cyclones to
observed cloud-aerosol relationships, Atmos. Chem. Phys., 13, 10689–10701,
https://doi.org/10.5194/acp-13-10689-2013, 2013.
Greenwald, T. J., Bennartz, R., Lebsock, M., and Teixeira, J.: An Uncertainty
Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid
Water Path, J. Geophys. Res.-Atmos., 123, 3668–3687,
https://doi.org/10.1002/2017jd027638, 2018.
Grise, K. M. and Medeiros, B.: Understanding the Varied Influence of
Midlatitude Jet Position on Clouds and Cloud Radiative Effects in
Observations and Global Climate Models, J. Climate, 29, 9005–9025,
https://doi.org/10.1175/jcli-d-16-0295.1, 2016.
Grise, K. M., Polvani, L. M., and Fasullo, J. T.: Reexamining the
Relationship between Climate Sensitivity and the Southern Hemisphere
Radiation Budget in CMIP Models, J. Climate, 28, 9298–9312,
https://doi.org/10.1175/JCLI-D-15-0031.1, 2015.
Haarsma, R.: EC-Earth3.2.P – The PRIMAVERA version, in preparation,
2018.
Hartmann, D. L. and Short, D. A.: On the Use of Earth Radiation Budget
Statistics for Studies of Clouds and Climate, J. Atmos. Sci., 37, 1233–1250,
https://doi.org/10.1175/1520-0469(1980)037<1233:OTUOER>2.0.CO;2, 1980.
Heymsfield, A. J., Kennedy, P. C., Massie, S., Schmitt, C., Wang, Z.,
Haimov, S., and Rangno, A.: Aircraft-Induced Hole Punch and Canal Clouds:
Inadvertent Cloud Seeding, B. Am. Meteorol. Soc.,
91, 753–766, https://doi.org/10.1175/2009BAMS2905.1, 2009.
Hill, A. A., Shipway, B. J., and Boutle, I. A.: How sensitive are
aerosol-precipitation interactions to the warm rain representation?, J. Adv. Model. Earth Sy., 7, 987–1004, https://doi.org/10.1002/2014MS000422,
2015.
Hoskins, B. J. and Hodges, K. I.: New perspectives on the Northern
Hemisphere winter storm tracks, J. Atmos. Sci., 59,
1041–1061, 2002.
Hourdin, F., Grandpeix, J.-Y., Rio, C., Bony, S., Jam, A., Cheruy, F.,
Rochetin, N., Fairhead, L., Idelkadi, A., Musat, I., Dufresne, J.-L.,
Lahellec, A., Lefebvre, M.-P., and Roehrig, R.: LMDZ5B: the atmospheric
component of the IPSL climate model with revisited parameterizations for
clouds and convection, Clim. Dynam., 40, 2193–2222, https://doi.org/10.1007/s00382-012-1343-y, 2013.
Hu, Y. X., Rodier, S., Xu, K. M., Sun, W. B., Huang, J. P., Lin, B., Zhai,
P. W., and Josset, D.: Occurrence, liquid water content, and fraction of
supercooled water clouds from combined CALIOP/IIR/MODIS measurements,
J. Geophys. Res.-Atmos., 115, D00H34, https://doi.org/10.1029/2009jd012384,
2010.
Jiang, J. H., Su, H., Zhai, C., Perun, V. S., Del Genio, A., Nazarenko, L.
S., Donner, L. J., Horowitz, L., Seman, C., Cole, J., Gettelman, A., Ringer,
M. A., Rotstayn, L., Jeffrey, S., Wu, T., Brient, F., Dufresne, J.-L.,
Kawai, H., Koshiro, T., Watanabe, M., LÉcuyer, T. S., Volodin, E. M.,
Iversen, T., Drange, H., Mesquita, M. D. S., Read, W. G., Waters, J. W.,
Tian, B., Teixeira, J., and Stephens, G. L.: Evaluation of cloud and water
vapor simulations in CMIP5 climate models using NASA “A-Train” satellite
observations, J. Geophys. Res.-Atmos., 117, D14105, https://doi.org/10.1029/2011JD017237, 2012.
Jin, H. and Nasiri, S. L.: Evaluation of AIRS cloud-thermodynamic-phase
determination with CALIPSO, J. Appl. Meteorol. Clim.,
53, 1012–1027, 2014.
Jung, T., Gulev, S. K., Rudeva, I., and Soloviov, V.: Sensitivity of
extratropical cyclone characteristics to horizontal resolution in the ECMWF
model, Q. J. Roy. Meteor. Soc., 132,
1839–1857, https://doi.org/10.1256/qj.05.212, 2006.
Kahn, B. H., Nasiri, S. L., Schreier, M. M., and Baum, B. A.: Impacts of
subpixel cloud heterogeneity on infrared thermodynamic phase assessment,
J. Geophys. Res.-Atmos., 116, D20201, https://doi.org/10.1029/2011JD015774, 2011.
Kahn, B. H., Irion, F. W., Dang, V. T., Manning, E. M., Nasiri, S. L., Naud,
C. M., Blaisdell, J. M., Schreier, M. M., Yue, Q., Bowman, K. W., Fetzer, E.
J., Hulley, G. C., Liou, K. N., Lubin, D., Ou, S. C., Susskind, J., Takano,
Y., Tian, B., and Worden, J. R.: The Atmospheric Infrared Sounder version 6
cloud products, Atmos. Chem. Phys., 14, 399–426,
https://doi.org/10.5194/acp-14-399-2014, 2014.
Kahn, B. H., Matheou, G., Yue, Q., Fauchez, T., Fetzer, E. J., Lebsock, M.,
Martins, J., Schreier, M. M., Suzuki, K., and Teixeira, J.: An A-train and
MERRA view of cloud, thermodynamic, and dynamic variability within the
subtropical marine boundary layer, Atmos. Chem. Phys., 17, 9451–9468,
https://doi.org/10.5194/acp-17-9451-2017, 2017.
Kanitz, T., Seifert, P., Ansmann, A., Engelmann, R., Althausen, D.,
Casiccia, C., and Rohwer, E. G.: Contrasting the impact of aerosols at
northern and southern midlatitudes on heterogeneous ice formation, Geophys.
Res. Lett., 38, L17802, https://doi.org/10.1029/2011gl048532, 2011.
Klein, S. A. and Hartmann, D. L.: The Seasonal Cycle of Low Stratiform
Clouds, J. Climate, 6, 1587–1606,
https://doi.org/10.1175/1520-0442(1993)006<1587:tscols>2.0.co;2, 1993.
Klein, S. A., Hartmann, D. L., and Norris, J. R.: On the Relationships among
Low-Cloud Structure, Sea Surface Temperature, and Atmospheric Circulation in
the Summertime Northeast Pacific, J. Climate, 8, 1140–1155,
https://doi.org/10.1175/1520-0442(1995)008<1140:OTRALC>2.0.CO;2, 1995.
Klein, S. A., Hall, A., Norris, J. R., and Pincus, R.: Low-Cloud Feedbacks
from Cloud-Controlling Factors: A Review, Surv. Geophys., 38,
1307–1329, https://doi.org/10.1007/s10712-017-9433-3, 2017.
Kodama, C., Iga, S., and Satoh, M.: Impact of the sea surface temperature
rise on storm-track clouds in global nonhydrostatic aqua planet simulations,
Geophys. Res. Lett., 41, 3545–3552, https://doi.org/10.1002/2014GL059972, 2014.
Kodama, C., Yamada, Y., Noda, A. T., Kikuchi, K., Kajikawa, Y., Nasuno, T.,
Tomita, T., Yamaura, T., Takahashi, H. G., Hara, M., Kawatani, Y., Satoh,
M., and Sugi, M.: A 20-Year Climatology of a NICAM AMIP-Type Simulation,
J. Meteorol. Soc. Jpn., 93, 393–424,
https://doi.org/10.2151/jmsj.2015-024, 2015.
Lambert, S. J. and Fyfe, J. C.: Changes in winter cyclone frequencies and
strengths simulated in enhanced greenhouse warming experiments: results from
the models participating in the IPCC diagnostic exercise, Clim. Dynam.,
26, 713–728, 2006.
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward Optimal Closure of the
Earth's Top-of-Atmosphere Radiation Budget, J. Climate, 22, 748–766,
https://doi.org/10.1175/2008jcli2637.1, 2009.
Löptien, U., Zolina, O., Gulev, S., Latif, M., and Soloviov, V.: Cyclone
life cycle characteristics over the Northern Hemisphere in coupled GCMs,
Clim. Dynam., 31, 507–532, 2008.
Lorenz, D. J. and DeWeaver, E. T.: Tropopause height and zonal wind
response to global warming in the IPCC scenario integrations, J. Geophys. Res.-Atmos., 112, D10119, https://doi.org/10.1029/2006JD008087,
2007.
Manaster, A., O'Dell, C. W., and Elsaesser, G.: Evaluation of Cloud Liquid
Water Path Trends Using a Multidecadal Record of Passive Microwave
Observations, J. Climate, 30, 5871–5884, https://doi.org/10.1175/jcli-d-16-0399.1,
2017.
McCoy, D. T., Hartmann, D. L., and Grosvenor, D. P.: Observed Southern Ocean
Cloud Properties and Shortwave Reflection. Part II: Phase Changes and Low
Cloud Feedback, J. Climate, 27, 8858–8868,
https://doi.org/10.1175/jcli-d-14-00288.1, 2014.
McCoy, D. T., Burrows, S. M., Wood, R., Grosvenor, D. P., Elliott, S. M., Ma,
P. L., Rasch, P. J., and Hartmann, D. L.: Natural aerosols explain seasonal
and spatial patterns of Southern Ocean cloud albedo, Sci. Adv., 1, e1500157,
https://doi.org/10.1126/sciadv.1500157, 2015a.
McCoy, D. T., Hartmann, D. L., Zelinka, M. D., Ceppi, P., and Grosvenor, D.
P.: Mixed-phase cloud physics and Southern Ocean cloud feedback in climate
models, J. Geophys. Res.-Atmos., 120, 9539–9554, https://doi.org/10.1002/2015jd023603, 2015b.
McCoy, D. T., Tan, I., Hartmann, D. L., Zelinka, M. D., and Storelvmo, T.:
On the relationships among cloud cover, mixed-phase partitioning, and
planetary albedo in GCMs, J. Adv. Model. Earth Sy., 8, 650–668, https://doi.org/10.1002/2015ms000589, 2016.
McCoy, D. T., Eastman, R., Hartmann, D. L., and Wood, R.: The Change in Low
Cloud Cover in a Warmed Climate Inferred from AIRS, MODIS, and ERA-Interim,
J. Climate, 30, 3609–3620, https://doi.org/10.1175/jcli-d-15-0734.1, 2017a.
McCoy, D. T., Hartmann, D. L., and Zelinka, M. D.: Mixed-Phase Cloud
Feedbacks in: Mixed-phase Clouds: Observations and Modeling, edited by:
Andronache, C., Elsevier, 2017b.
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, 2018a.
McCoy, D. T., Field, P. R., Schmidt, A., Grosvenor, D. P., Bender, F. A.-M.,
Shipway, B. J., Hill, A. A., Wilkinson, J. M., and Elsaesser, G. S.: Aerosol
midlatitude cyclone indirect effects in observations and high-resolution
simulations, Atmos. Chem. Phys., 18, 5821–5846,
https://doi.org/10.5194/acp-18-5821-2018, 2018b.
McCoy, I. L., Wood, R., and Fletcher, J. K.: Identifying Meteorological
Controls on Open and Closed Mesoscale Cellular Convection Associated with
Marine Cold Air Outbreaks, J. Geophys. Res.-Atmos., 122, 11678–11702, https://doi.org/10.1002/2017JD027031,
2017c.
Mears, C., Smith, D. K., and Wentz, F. J.: Comparison of special sensor
microwave imager and buoy-measured wind speeds from 1987 to 1997, J. Geophys. Res.-Oceans., 106, 11719–11729, 2001.
Meissner, T., Smith, D., and Wentz, F.: A 10 year intercomparison between
collocated Special Sensor Microwave Imager oceanic surface wind speed
retrievals and global analyses, J. Geophys. Res.-Oceans.,
106, 11731–11742, 2001.
Meskhidze, N. and Nenes, A.: Phytoplankton and Cloudiness in the Southern
Ocean, Science, 314, 1419–1423, https://doi.org/10.1126/science.1131779, 2006.
Morrison, H., de Boer, G., Feingold, G., Harrington, J., Shupe, M. D., and
Sulia, K.: Resilience of persistent Arctic mixed-phase clouds, Nat. Geosci., 5, 11–17, https://doi.org/10.1038/ngeo1332, 2011.
Myers, T. A. and Norris, J. R.: On the Relationships between Subtropical
Clouds and Meteorology in Observations and CMIP3 and CMIP5 Models, J. Climate, 28, 2945–2967, https://doi.org/10.1175/JCLI-D-14-00475.1, 2015.
Myers, T. A. and Norris, J. R.: Reducing the uncertainty in subtropical
cloud feedback, Geophys. Res. Lett., 43, 2144–2148, https://doi.org/10.1002/2015GL067416, 2016.
Nasiri, S. L. and Kahn, B. H.: Limitations of bispectral infrared cloud
phase determination and potential for improvement, J. Appl. Meteorol. Clim., 47, 2895–2910, 2008.
Naud, C. M. and Kahn, B. H.: Thermodynamic Phase and Ice Cloud Properties
in Northern Hemisphere Winter Extratropical Cyclones Observed by Aqua AIRS,
J. Appl. Meteorol. Clim., 54, 2283–2303,
https://doi.org/10.1175/jamc-d-15-0045.1, 2015.
Naud, C. M., Del Genio, A. D., and Bauer, M.: Observational constraints on
the cloud thermodynamic phase in midlatitude storms, J. Climate, 19,
5273–5288, 10.1175/jcli3919.1, 2006.
Naud, C. M., Posselt, D. J., and van den Heever, S. C.: Aerosol optical
depth distribution in extratropical cyclones over the Northern Hemisphere
oceans, Geophys. Res. Lett., 43, 10504–510511, https://doi.org/10.1002/2016GL070953, 2016.
Naud, C. M., Posselt, D. J., and van den Heever, S. C.: Observed
Covariations of Aerosol Optical Depth and Cloud Cover in Extratropical
Cyclones, J. Geophys. Res.-Atmos., 122, 10338–310356, https://doi.org/10.1002/2017JD027240, 2017.
Naud, C. M., Booth, J. F., Lebsock, M., and Grecu, M.: Observational
Constraint for Precipitation in Extratropical Cyclones: Sensitivity to Data
Sources, J. Appl. Meteorol. Clim., 57, 991–1009,
https://doi.org/10.1175/jamc-d-17-0289.1, 2018.
Norris, J. R. and Iacobellis, S. F.: North Pacific Cloud Feedbacks Inferred
from Synoptic-Scale Dynamic and Thermodynamic Relationships, J. Climate, 18, 4862–4878, https://doi.org/10.1175/jcli3558.1, 2005.
Norris, J. R., Allen, R. J., Evan, A. T., Zelinka, M. D., O'Dell, C. W., and
Klein, S. A.: Evidence for climate change in the satellite cloud record,
Nature, 536, 72–75, https://doi.org/10.1038/nature18273, 2016.
Pfahl, S. and Sprenger, M.: On the relationship between extratropical
cyclone precipitation and intensity, Geophys. Res. Lett., 43,
1752–1758, https://doi.org/10.1002/2016GL068018, 2016.
Qu, X., Hall, A., Klein, S. A., DeAngelis, and Anthony, M.: Positive
tropical marine low-cloud cover feedback inferred from cloud-controlling
factors, Geophys. Res. Lett., 42, 7767–7775, https://doi.org/10.1002/2015GL065627, 2015.
Rieck, M., Nuijens, L., and Stevens, B.: Marine Boundary Layer Cloud
Feedbacks in a Constant Relative Humidity Atmosphere, J. Atmos. Sci., 69, 2538–2550, https://doi.org/10.1175/JAS-D-11-0203.1, 2012.
Roehrig, R.: CMIP 6, available at: http://www.umr-cnrm.fr/cmip6/references, last access:
January 2019.
Shaw, T. A., Baldwin, M., Barnes, E. A., Caballero, R., Garfinkel, C. I.,
Hwang, Y. T., Li, C., O'Gorman, P. A., Rivière, G., Simpson, I. R., and
Voigt, A.: Storm track processes and the opposing influences of climate
change, Nat. Geosci., 9, 656–664, https://doi.org/10.1038/ngeo2783, 2016.
Sinclair, M. R.: An objective cyclone climatology for the Southern
Hemisphere, Mon. Weather Rev., 122, 2239–2256, 1994.
Soloviev, A. V., Lukas, R., Donelan, M. A., Haus, B. K., and Ginis, I.: The
air-sea interface and surface stress under tropical cyclones, Sci. Rep., 4, 5306, https://doi.org/10.1038/srep05306, 2014.
Strachan, J., Vidale, P. L., Hodges, K., Roberts, M., and Demory, M.-E.:
Investigating Global Tropical Cyclone Activity with a Hierarchy of AGCMs:
The Role of Model Resolution, J. Climate, 26, 133–152,
https://doi.org/10.1175/jcli-d-12-00012.1, 2013.
Tamarin, T. and Kaspi, Y.: The poleward shift of storm tracks under global
warming: A Lagrangian perspective, Geophys. Res. Lett., 44, 10666–10674, 2017.
Tamarin-Brodsky, T. and Kaspi, Y.: Enhanced poleward propagation of storms
under climate change, Nat. Geosci., 10, 908–913, https://doi.org/10.1038/s41561-017-0001-8, 2017.
Tan, I., Storelvmo, T., and Choi, Y.-S.: Spaceborne lidar observations of
the ice-nucleating potential of dust, polluted dust, and smoke aerosols in
mixed-phase clouds, J. Geophys. Res.-Atmos., 119, 6653–6665, https://doi.org/10.1002/2013JD021333, 2014.
Tan, I., Storelvmo, T., and Zelinka, M. D.: Observational constraints on
mixed-phase clouds imply higher climate sensitivity, Science, 352, 224–227,
https://doi.org/10.1126/science.aad5300, 2016.
Terai, C. R., Klein, S. A., and Zelinka, M. D.: Constraining the low-cloud
optical depth feedback at middle and high latitudes using satellite
observations, J. Geophys. Res.-Atmos., 121, 9696–9716, https://doi.org/10.1002/2016JD025233, 2016.
The HadGEM2 Development Team: Martin, G. M., Bellouin, N., Collins, W. J.,
Culverwell, I. D., Halloran, P. R., Hardiman, S. C., Hinton, T. J., Jones, C.
D., McDonald, R. E., McLaren, A. J., O'Connor, F. M., Roberts, M. J.,
Rodriguez, J. M., Woodward, S., Best, M. J., Brooks, M. E., Brown, A. R.,
Butchart, N., Dearden, C., Derbyshire, S. H., Dharssi, I., Doutriaux-Boucher,
M., Edwards, J. M., Falloon, P. D., Gedney, N., Gray, L. J., Hewitt, H. T.,
Hobson, M., Huddleston, M. R., Hughes, J., Ineson, S., Ingram, W. J., James,
P. M., Johns, T. C., Johnson, C. E., Jones, A., Jones, C. P., Joshi, M. M.,
Keen, A. B., Liddicoat, S., Lock, A. P., Maidens, A. V., Manners, J. C.,
Milton, S. F., Rae, J. G. L., Ridley, J. K., Sellar, A., Senior, C. A.,
Totterdell, I. J., Verhoef, A., Vidale, P. L., and Wiltshire, A.: The HadGEM2
family of Met Office Unified Model climate configurations, Geosci. Model
Dev., 4, 723–757, https://doi.org/10.5194/gmd-4-723-2011,
2011.
Titchner, H., A. and Rayner, N., A.: The Met Office Hadley Centre sea ice
and sea surface temperature data set, version 2: 1. Sea ice concentrations,
J. Geophys. Res.-Atmos., 119, 2864–2889, https://doi.org/10.1002/2013JD020316, 2014.
Trenberth, K. E. and Fasullo, J. T.: Simulation of Present-Day and
Twenty-First-Century Energy Budgets of the Southern Oceans, J. Climate, 23, 440–454, https://doi.org/10.1175/2009jcli3152.1, 2010.
Trenberth, K. E., Fasullo, J., and Smith, L.: Trends and variability in
column-integrated atmospheric water vapor, Clim. Dynam., 24, 741–758,
2005.
Tselioudis, G. and Rossow, W. B.: Climate feedback implied by observed
radiation and precipitation changes with midlatitude storm strength and
frequency, Geophys. Res. Lett., 33, L02704, https://doi.org/10.1029/2005GL024513, 2006.
Tsushima, Y., Emori, S., Ogura, T., Kimoto, M., Webb, M. J., Williams, K.
D., Ringer, M. A., Soden, B. J., Li, B., and Andronova, N.: Importance of
the mixed-phase cloud distribution in the control climate for assessing the
response of clouds to carbon dioxide increase: a multi-model study, Clim. Dynam., 27, 113–126, https://doi.org/10.1007/s00382-006-0127-7, 2006.
Ulbrich, U., Leckebusch, G., and Pinto, J. G.: Extra-tropical cyclones in
the present and future climate: a review, Theor. Appl. Climatol., 96, 117–131, 2009.
Voigt, A., Stevens, B., Bony, S., and Boucher, O.: Easy Aerosol – a modeling
framework to study robustness and sources of uncertainties in
aerosol-induced changes of the large-scale atmospheric circulation, WCRP, 2014.
Voldoire, A., Sanchez-Gomez, E., Salas y Mélia, D., Decharme, B.,
Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A., Chevallier,
M., Déqué, M., Deshayes, J., Douville, H., Fernandez, E., Madec, G.,
Maisonnave, E., Moine, M. P., Planton, S., Saint-Martin, D., Szopa, S.,
Tyteca, S., Alkama, R., Belamari, S., Braun, A., Coquart, L., and Chauvin,
F.: The CNRM-CM5.1 global climate model: description and basic evaluation,
Clim. Dynam., 40, 2091–2121, https://doi.org/10.1007/s00382-011-1259-y, 2013.
Watanabe, M., Suzuki, T., O'ishi, R., Komuro, Y., Watanabe, S., Emori, S.,
Takemura, T., Chikira, M., Ogura, T., and Sekiguchi, M.: Improved climate
simulation by MIROC5: mean states, variability, and climate sensitivity,
J. Climate, 23, 6312–6335, 2010.
Wentz, F. J.: A 17-yr climate record of environmental parameters derived
from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager,
J. Climate, 28, 6882–6902, 2015.
Wielicki, B. A., Barkstrom, B. R., Harrison, E. F., Robert III, B. L., Smith, G.
L., and Cooper, J. E.: Clouds and the Earth's Radiant Energy System (CERES):
An Earth Observing System Experiment, B. Am. Meteorol. Soc., 77, 853–868,
https://doi.org/10.1175/1520-0477(1996)077<0853:catere>2.0.co;2, 1996.
Williams, K., Copsey, D., Blockley, E., Bodas-Salcedo, A., Calvert, D.,
Comer, R., Davis, P., Graham, T., Hewitt, H., and Hill, R.: The Met Office
global coupled model 3.0 and 3.1 (GC3. 0 and GC3. 1) configurations, J. Adv. Model. Earth Sy., 10, 357–380, 2018.
Wood, R. and Bretherton, C. S.: On the relationship between stratiform low
cloud cover and lower-tropospheric stability, J. Climate, 19,
6425–6432, https://doi.org/10.1175/jcli3988.1, 2006.
Wood, R., Kubar, T. L., and Hartmann, D. L.: Understanding the Importance of
Microphysics and Macrophysics for Warm Rain in Marine Low Clouds. Part II:
Heuristic Models of Rain Formation, J. Atmos. Sci., 66,
2973–2990, https://doi.org/10.1175/2009jas3072.1, 2009.
Yin, J. H.: A consistent poleward shift of the storm tracks in simulations
of 21st century climate, Geophys. Res. Lett., 32, L18701, https://doi.org/10.1029/2005GL023684,
2005.
Zelinka, M. D., Klein, S. A., and Hartmann, D. L.: Computing and
Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part II:
Attribution to Changes in Cloud Amount, Altitude, and Optical Depth, J. Climate, 25, 3736–3754, https://doi.org/10.1175/jcli-d-11-00249.1, 2012a.
Zelinka, M. D., Klein, S. A., and Hartmann, D. L.: Computing and
Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud
Radiative Kernels, J. Climate, 25, 3715–3735,
https://doi.org/10.1175/jcli-d-11-00248.1, 2012b.
Zelinka, M. D., Klein, S. A., Taylor, K. E., Andrews, T., Webb, M. J.,
Gregory, J. M., and Forster, P. M.: Contributions of Different Cloud Types
to Feedbacks and Rapid Adjustments in CMIP5, J. Climate, 26,
5007–5027, https://doi.org/10.1175/jcli-d-12-00555.1, 2013.
Zelinka, M. D., Zhou, C., and Klein, S. A.: Insights from a refined
decomposition of cloud feedbacks, Geophys. Res. Lett., 43, 9259–9269, https://doi.org/10.1002/2016GL069917, 2016.
Short summary
The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
The largest single source of uncertainty in the climate sensitivity predicted by global climate...
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