Articles | Volume 24, issue 14
https://doi.org/10.5194/acp-24-8295-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-8295-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A systematic evaluation of high-cloud controlling factors
Sarah Wilson Kemsley
CORRESPONDING AUTHOR
Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
Paulo Ceppi
Department of Physics, Imperial College London, London, UK
Hendrik Andersen
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Jan Cermak
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Philip Stier
Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
Peer Nowack
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Institute of Theoretical Informatics, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Related authors
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
Short summary
Short summary
This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Xiao Lu, Yiming Liu, Jiayin Su, Xiang Weng, Tabish Ansari, Yuqiang Zhang, Guowen He, Yuqi Zhu, Haolin Wang, Ganquan Zeng, Jingyu Li, Cheng He, Shuai Li, Teerachai Amnuaylojaroen, Tim Butler, Qi Fan, Shaojia Fan, Grant L. Forster, Meng Gao, Jianlin Hu, Yugo Kanaya, Mohd Talib Latif, Keding Lu, Philippe Nédélec, Peer Nowack, Bastien Sauvage, Xiaobin Xu, Lin Zhang, Ke Li, Ja-Ho Koo, and Tatsuya Nagashima
Atmos. Chem. Phys., 25, 7991–8028, https://doi.org/10.5194/acp-25-7991-2025, https://doi.org/10.5194/acp-25-7991-2025, 2025
Short summary
Short summary
This study analyzes summertime ozone trends in East and Southeast Asia derived from a comprehensive observational database spanning from 1995 to 2019, incorporating aircraft observations, ozonesonde data, and measurements from 2500 surface sites. Multiple models are applied to attribute to changes in anthropogenic emissions and climate. The results highlight that increases in anthropogenic emissions are the primary driver of ozone increases both in the free troposphere and at the surface.
Ross J. Herbert, Andrew I. L. Williams, Philipp Weiss, Duncan Watson-Parris, Elisabeth Dingley, Daniel Klocke, and Philip Stier
Atmos. Chem. Phys., 25, 7789–7814, https://doi.org/10.5194/acp-25-7789-2025, https://doi.org/10.5194/acp-25-7789-2025, 2025
Short summary
Short summary
Clouds exist at scales that climate models struggle to represent, limiting our knowledge of how climate change may impact clouds. Here we use a new kilometer-scale global model representing an important step towards the necessary scale. We focus on how aerosol particles modify clouds, radiation, and precipitation. We find the magnitude and manner of responses tend to vary from region to region, highlighting the potential of global kilometer-scale simulations and a need to represent aerosols in climate models.
Deepanshu Malik, Hendrik Andersen, Jan Cermak, Roland Vogt, and Bianca Adler
EGUsphere, https://doi.org/10.5194/egusphere-2025-2645, https://doi.org/10.5194/egusphere-2025-2645, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We investigated cloud base height changes in the Namib Desert and developed a method to estimate it using ground-based humidity data. This improves fog monitoring by distinguishing fog from low clouds, which satellites alone cannot reliably do. Our results reveal diurnal patterns and linkages to coastal proximity in the vertical dynamics of fog and low clouds, highlighting key atmospheric processes with potential importance for future research.
Philipp Weiss, Ross Herbert, and Philip Stier
Geosci. Model Dev., 18, 3877–3894, https://doi.org/10.5194/gmd-18-3877-2025, https://doi.org/10.5194/gmd-18-3877-2025, 2025
Short summary
Short summary
Aerosols strongly influence Earth's climate as they interact with radiation and clouds. New Earth system models run at resolutions of a few kilometers. To simulate the Earth system with interactive aerosols, we developed a new aerosol module. It represents aerosols as an ensemble of lognormal modes with given sizes and compositions. We present a year-long simulation with four modes at a resolution of 5 km. It captures key processes like the formation of dust storms in the Sahara.
Babak Jahani, Steffen Karalus, Julia Fuchs, Tobias Zech, Marina Zara, and Jan Cermak
Atmos. Meas. Tech., 18, 1927–1941, https://doi.org/10.5194/amt-18-1927-2025, https://doi.org/10.5194/amt-18-1927-2025, 2025
Short summary
Short summary
Fog and low stratus (FLS) are both persistent clouds close to the Earth's surface. This study introduces a new machine-learning-based algorithm developed for the Meteosat Second Generation geostationary satellites that can provide a coherent and detailed view of FLS development over large areas over the 24 h day cycle.
Kevin Debeire, Lisa Bock, Peer Nowack, Jakob Runge, and Veronika Eyring
Earth Syst. Dynam., 16, 607–630, https://doi.org/10.5194/esd-16-607-2025, https://doi.org/10.5194/esd-16-607-2025, 2025
Short summary
Short summary
Projecting future precipitation is essential for preparing for climate change, but current climate models still have large uncertainties, especially over land. This study presents a new method to improve precipitation projections by identifying which models best capture key climate patterns. By giving more weight to models that better represent these patterns, our approach leads to more reliable future precipitation projections over land.
Richard G. Williams, Philip Goodwin, Paulo Ceppi, Chris D. Jones, and Andrew MacDougall
EGUsphere, https://doi.org/10.5194/egusphere-2025-800, https://doi.org/10.5194/egusphere-2025-800, 2025
Short summary
Short summary
How the climate system responds when carbon emissions cease is an open question: some climate models reveal a slight warming, whereas most models reveal a slight cooling. Their climate response is affected by how the planet takes up heat and radiates heat back to space, and how the land and ocean sequester carbon from the atmosphere. A framework is developed to connect the temperature response of the climate models to competing and opposing-signed thermal and carbon contributions.
Peer Nowack and Duncan Watson-Parris
Atmos. Chem. Phys., 25, 2365–2384, https://doi.org/10.5194/acp-25-2365-2025, https://doi.org/10.5194/acp-25-2365-2025, 2025
Short summary
Short summary
In our article, we review uncertainties in global climate change projections and current methods using Earth observations as constraints, which is crucial for climate risk assessments and for informing society. We then discuss how machine learning can advance the field, discussing recent work that provides potentially stronger and more robust links between observed data and future climate projections. We further discuss the challenges of applying machine learning to climate science.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-509, https://doi.org/10.5194/egusphere-2025-509, 2025
Short summary
Short summary
The nextGEMS project developed two Earth system models that resolve processes of the order of 10 km, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS performed simulations with coupled ocean, land, and atmosphere 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.
Jingyu Wang, Gabriel Chiodo, Timofei Sukhodolov, Blanca Ayarzagüena, William T. Ball, Mohamadou Diallo, Birgit Hassler, James Keeble, Peer Nowack, Clara Orbe, and Sandro Vattioni
EGUsphere, https://doi.org/10.5194/egusphere-2025-340, https://doi.org/10.5194/egusphere-2025-340, 2025
Short summary
Short summary
We analyzed the ozone response under elevated CO2 using the data from CMIP6 DECK experiments. We then looked at the relations between ozone response and temperature and circulation changes to identify drivers of the ozone change. The climate feedback of ozone is investigated by doing offline calculations and comparing models with and without interactive chemistry. We find that ozone-climate interactions are important for Earth System Models, thus should be considered in future model development.
Mariya Petrenko, Ralph Kahn, Mian Chin, Susanne E. Bauer, Tommi Bergman, Huisheng Bian, Gabriele Curci, Ben Johnson, Johannes W. Kaiser, Zak Kipling, Harri Kokkola, Xiaohong Liu, Keren Mezuman, Tero Mielonen, Gunnar Myhre, Xiaohua Pan, Anna Protonotariou, Samuel Remy, Ragnhild Bieltvedt Skeie, Philip Stier, Toshihiko Takemura, Kostas Tsigaridis, Hailong Wang, Duncan Watson-Parris, and Kai Zhang
Atmos. Chem. Phys., 25, 1545–1567, https://doi.org/10.5194/acp-25-1545-2025, https://doi.org/10.5194/acp-25-1545-2025, 2025
Short summary
Short summary
We compared smoke plume simulations from 11 global models to each other and to satellite smoke amount observations aimed at constraining smoke source strength. In regions where plumes are thick and background aerosol is low, models and satellites compare well. However, the input emission inventory tends to underestimate in many places, and particle property and loss rate assumptions vary enormously among models, causing uncertainties that require systematic in situ measurements to resolve.
Philipp Breul, Paulo Ceppi, and Peer Nowack
EGUsphere, https://doi.org/10.5194/egusphere-2025-221, https://doi.org/10.5194/egusphere-2025-221, 2025
Short summary
Short summary
We explore how Pacific low-level clouds influence projections of regional climate change by adjusting a climate model to enhance low cloud response to surface temperatures. We find significant changes in projected warming patterns and circulation changes, under increased CO2 conditions. Our findings are supported by similar relationships across state-of-the-art climate models. These results highlight the importance of accurately representing clouds for predicting regional climate change impacts.
Alexandre Mass, Hendrik Andersen, Jan Cermak, Paola Formenti, Eva Pauli, and Julian Quinting
Atmos. Chem. Phys., 25, 491–510, https://doi.org/10.5194/acp-25-491-2025, https://doi.org/10.5194/acp-25-491-2025, 2025
Short summary
Short summary
This study investigates the interaction between smoke aerosols and fog and low clouds (FLCs) in the Namib Desert between June and October. Here, a satellite-based dataset of FLCs, reanalysis data and machine learning are used to systematically analyze FLC persistence under different aerosol loadings. Aerosol plumes are shown to modify local thermodynamics, which increase FLC persistence. But fully disentangling aerosol effects from meteorological ones remains a challenge.
Anna Tippett, Edward Gryspeerdt, Peter Manshausen, Philip Stier, and Tristan W. P. Smith
Atmos. Chem. Phys., 24, 13269–13283, https://doi.org/10.5194/acp-24-13269-2024, https://doi.org/10.5194/acp-24-13269-2024, 2024
Short summary
Short summary
Ship emissions can form artificially brightened clouds, known as ship tracks, and provide us with an opportunity to investigate how aerosols interact with clouds. Previous studies that used ship tracks suggest that clouds can experience large increases in the amount of water (LWP) from aerosols. Here, we show that there is a bias in previous research and that, when we account for this bias, the LWP response to aerosols is much weaker than previously reported.
Yichen Jia, Hendrik Andersen, and Jan Cermak
Atmos. Chem. Phys., 24, 13025–13045, https://doi.org/10.5194/acp-24-13025-2024, https://doi.org/10.5194/acp-24-13025-2024, 2024
Short summary
Short summary
We present a near-global observation-based explainable machine learning framework to quantify the response of cloud fraction (CLF) of marine low clouds to cloud droplet number concentration (Nd), accounting for the covariations with meteorological factors. This approach provides a novel data-driven method to analyse the CLF adjustment by assessing the CLF sensitivity to Nd and numerous meteorological factors as well as the dependence of the Nd–CLF sensitivity on the meteorological conditions.
Henrik Auestad, Clemens Spensberger, Andrea Marcheggiani, Paulo Ceppi, Thomas Spengler, and Tim Woollings
Weather Clim. Dynam., 5, 1269–1286, https://doi.org/10.5194/wcd-5-1269-2024, https://doi.org/10.5194/wcd-5-1269-2024, 2024
Short summary
Short summary
Latent heating due to condensation can influence atmospheric circulation by strengthening or weakening horizontal temperature contrasts. Strong temperature contrasts intensify storms and imply the existence of strong upper tropospheric winds called jets. It remains unclear whether latent heating preferentially reinforces or abates the existing jet. We show that this disagreement is attributable to how the jet is defined, confirming that latent heating reinforces the jet.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
Short summary
Short summary
Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Johannes Mülmenstädt, Edward Gryspeerdt, Sudhakar Dipu, Johannes Quaas, Andrew S. Ackerman, Ann M. Fridlind, Florian Tornow, Susanne E. Bauer, Andrew Gettelman, Yi Ming, Youtong Zheng, Po-Lun Ma, Hailong Wang, Kai Zhang, Matthew W. Christensen, Adam C. Varble, L. Ruby Leung, Xiaohong Liu, David Neubauer, Daniel G. Partridge, Philip Stier, and Toshihiko Takemura
Atmos. Chem. Phys., 24, 7331–7345, https://doi.org/10.5194/acp-24-7331-2024, https://doi.org/10.5194/acp-24-7331-2024, 2024
Short summary
Short summary
Human activities release copious amounts of small particles called aerosols into the atmosphere. These particles change how much sunlight clouds reflect to space, an important human perturbation of the climate, whose magnitude is highly uncertain. We found that the latest climate models show a negative correlation but a positive causal relationship between aerosols and cloud water. This means we need to be very careful when we interpret observational studies that can only see correlation.
William K. Jones, Martin Stengel, and Philip Stier
Atmos. Chem. Phys., 24, 5165–5180, https://doi.org/10.5194/acp-24-5165-2024, https://doi.org/10.5194/acp-24-5165-2024, 2024
Short summary
Short summary
Storm clouds cover large areas of the tropics. These clouds both reflect incoming sunlight and trap heat from the atmosphere below, regulating the temperature of the tropics. Over land, storm clouds occur in the late afternoon and evening and so exist both during the daytime and at night. Changes in this timing could upset the balance of the respective cooling and heating effects of these clouds. We find that isolated storms have a larger effect on this balance than their small size suggests.
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
Short summary
Short summary
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.
Karine Desboeufs, Paola Formenti, Raquel Torres-Sánchez, Kerstin Schepanski, Jean-Pierre Chaboureau, Hendrik Andersen, Jan Cermak, Stefanie Feuerstein, Benoit Laurent, Danitza Klopper, Andreas Namwoonde, Mathieu Cazaunau, Servanne Chevaillier, Anaïs Feron, Cécile Mirande-Bret, Sylvain Triquet, and Stuart J. Piketh
Atmos. Chem. Phys., 24, 1525–1541, https://doi.org/10.5194/acp-24-1525-2024, https://doi.org/10.5194/acp-24-1525-2024, 2024
Short summary
Short summary
This study investigates the fractional solubility of iron (Fe) in dust particles along the coast of Namibia, a critical region for the atmospheric Fe supply of the South Atlantic Ocean. Our results suggest a possible two-way interplay whereby marine biogenic emissions from the coastal marine ecosystems into the atmosphere would increase the solubility of Fe-bearing dust by photo-reduction processes. The subsequent deposition of soluble Fe could act to further enhance marine biogenic emissions.
Karoline Block, Mahnoosh Haghighatnasab, Daniel G. Partridge, Philip Stier, and Johannes Quaas
Earth Syst. Sci. Data, 16, 443–470, https://doi.org/10.5194/essd-16-443-2024, https://doi.org/10.5194/essd-16-443-2024, 2024
Short summary
Short summary
Aerosols being able to act as condensation nuclei for cloud droplets (CCNs) are a key element in cloud formation but very difficult to determine. In this study we present a new global vertically resolved CCN dataset for various humidity conditions and aerosols. It is obtained using an atmospheric model (CAMS reanalysis) that is fed by satellite observations of light extinction (AOD). We investigate and evaluate the abundance of CCNs in the atmosphere and their temporal and spatial occurrence.
Philip Goodwin, Richard Williams, Paulo Ceppi, and B. B. Cael
EGUsphere, https://doi.org/10.5194/egusphere-2023-2307, https://doi.org/10.5194/egusphere-2023-2307, 2023
Preprint archived
Short summary
Short summary
Climate feedbacks are normally evaluated by considering the change over time for Earth's energy balance and surface temperatures in the climate system. However, we only have around 1 degree Celsius of temperature change to utilise. Here, climate feedbacks are instead evaluated from the change in latitude of Earth's energy balance and surface temperatures, where we have around 70 degrees Celsius of temperature change to utilise.
Peter Manshausen, Duncan Watson-Parris, Matthew W. Christensen, Jukka-Pekka Jalkanen, and Philip Stier
Atmos. Chem. Phys., 23, 12545–12555, https://doi.org/10.5194/acp-23-12545-2023, https://doi.org/10.5194/acp-23-12545-2023, 2023
Short summary
Short summary
Aerosol from burning fuel changes cloud properties, e.g., the number of droplets and the content of water. Here, we study how clouds respond to different amounts of shipping aerosol. Droplet numbers increase linearly with increasing aerosol over a broad range until they stop increasing, while the amount of liquid water always increases, independently of emission amount. These changes in cloud properties can make them reflect more or less sunlight, which is important for the earth's climate.
Hendrik Andersen, Jan Cermak, Alyson Douglas, Timothy A. Myers, Peer Nowack, Philip Stier, Casey J. Wall, and Sarah Wilson Kemsley
Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, https://doi.org/10.5194/acp-23-10775-2023, 2023
Short summary
Short summary
This study uses an observation-based cloud-controlling factor framework to study near-global sensitivities of cloud radiative effects to a large number of meteorological and aerosol controls. We present near-global sensitivity patterns to selected thermodynamic, dynamic, and aerosol factors and discuss the physical mechanisms underlying the derived sensitivities. Our study hopes to guide future analyses aimed at constraining cloud feedbacks and aerosol–cloud interactions.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David M. H. Sexton, Christopher Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John W. Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
Atmos. Chem. Phys., 23, 8749–8768, https://doi.org/10.5194/acp-23-8749-2023, https://doi.org/10.5194/acp-23-8749-2023, 2023
Short summary
Short summary
Aerosol forcing of Earth’s energy balance has persisted as a major cause of uncertainty in climate simulations over generations of climate model development. We show that structural deficiencies in a climate model are exposed by comprehensively exploring parametric uncertainty and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. This provides a future pathway towards building models with greater physical realism and lower uncertainty.
Ross Herbert and Philip Stier
Atmos. Chem. Phys., 23, 4595–4616, https://doi.org/10.5194/acp-23-4595-2023, https://doi.org/10.5194/acp-23-4595-2023, 2023
Short summary
Short summary
We provide robust evidence from multiple sources showing that smoke from fires in the Amazon rainforest significantly modifies the diurnal cycle of convection and cools the climate. Low to moderate amounts of smoke increase deep convective clouds and rain, whilst beyond a threshold amount, the smoke starts to suppress the convection and rain. We are currently at this threshold, suggesting increases in fires from agricultural practices or droughts will reduce cloudiness and rain over the region.
William K. Jones, Matthew W. Christensen, and Philip Stier
Atmos. Meas. Tech., 16, 1043–1059, https://doi.org/10.5194/amt-16-1043-2023, https://doi.org/10.5194/amt-16-1043-2023, 2023
Short summary
Short summary
Geostationary weather satellites have been used to detect storm clouds since their earliest applications. However, this task remains difficult as imaging satellites cannot observe the strong vertical winds that are characteristic of storm clouds. Here we introduce a new method that allows us to detect the early development of storms and continue to track them throughout their lifetime, allowing us to study how their early behaviour affects subsequent weather.
Philipp Breul, Paulo Ceppi, and Theodore G. Shepherd
Weather Clim. Dynam., 4, 39–47, https://doi.org/10.5194/wcd-4-39-2023, https://doi.org/10.5194/wcd-4-39-2023, 2023
Short summary
Short summary
Accurately predicting the response of the midlatitude jet stream to climate change is very important, but models show a variety of possible scenarios. Previous work identified a relationship between climatological jet latitude and future jet shift in the southern hemispheric winter. We show that the relationship does not hold in separate sectors and propose that zonal asymmetries are the ultimate cause in the zonal mean. This questions the usefulness of the relationship.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David Sexton, Christopher C. Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2022-1330, https://doi.org/10.5194/egusphere-2022-1330, 2022
Preprint archived
Short summary
Short summary
We show that potential structural deficiencies in a climate model can be exposed by comprehensively exploring its parametric uncertainty, and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. Combined consideration of parametric and structural uncertainties provides a future pathway towards building models that have greater physical realism and lower uncertainty.
Johannes Quaas, Hailing Jia, Chris Smith, Anna Lea Albright, Wenche Aas, Nicolas Bellouin, Olivier Boucher, Marie Doutriaux-Boucher, Piers M. Forster, Daniel Grosvenor, Stuart Jenkins, Zbigniew Klimont, Norman G. Loeb, Xiaoyan Ma, Vaishali Naik, Fabien Paulot, Philip Stier, Martin Wild, Gunnar Myhre, and Michael Schulz
Atmos. Chem. Phys., 22, 12221–12239, https://doi.org/10.5194/acp-22-12221-2022, https://doi.org/10.5194/acp-22-12221-2022, 2022
Short summary
Short summary
Pollution particles cool climate and offset part of the global warming. However, they are washed out by rain and thus their effect responds quickly to changes in emissions. We show multiple datasets to demonstrate that aerosol emissions and their concentrations declined in many regions influenced by human emissions, as did the effects on clouds. Consequently, the cooling impact on the Earth energy budget became smaller. This change in trend implies a relative warming.
Haochi Che, Philip Stier, Duncan Watson-Parris, Hamish Gordon, and Lucia Deaconu
Atmos. Chem. Phys., 22, 10789–10807, https://doi.org/10.5194/acp-22-10789-2022, https://doi.org/10.5194/acp-22-10789-2022, 2022
Short summary
Short summary
Extensive stratocumulus clouds over the south-eastern Atlantic (SEA) can lead to a cooling effect on the climate. A key pathway by which aerosols affect cloud properties is by acting as cloud condensation nuclei (CCN). Here, we investigated the source attribution of CCN in the SEA as well as the cloud responses. Our results show that aerosol nucleation contributes most to CCN in the marine boundary layer. In terms of emissions, anthropogenic sources contribute most to the CCN and cloud droplets.
Julia Fuchs, Hendrik Andersen, Jan Cermak, Eva Pauli, and Rob Roebeling
Atmos. Meas. Tech., 15, 4257–4270, https://doi.org/10.5194/amt-15-4257-2022, https://doi.org/10.5194/amt-15-4257-2022, 2022
Short summary
Short summary
Two cloud-masking approaches, a local and a regional approach, using high-resolution satellite data are developed and validated for the region of Paris to improve applicability for analyses of urban effects on low clouds. We found that cloud masks obtained from the regional approach are more appropriate for the high-resolution analysis of locally induced cloud processes. Its applicability is tested for the analysis of typical fog conditions over different surface types.
Xiang Weng, Grant L. Forster, and Peer Nowack
Atmos. Chem. Phys., 22, 8385–8402, https://doi.org/10.5194/acp-22-8385-2022, https://doi.org/10.5194/acp-22-8385-2022, 2022
Short summary
Short summary
We use machine learning to quantify the meteorological drivers behind surface ozone variations in China between 2015 and 2019. Our novel approaches show improved performance when compared to previous analysis methods. We highlight that nonlinearity in driver relationships and the impacts of large-scale meteorological phenomena are key to understanding ozone pollution. Moreover, we find that almost half of the observed ozone trend between 2015 and 2019 might have been driven by meteorology.
Philipp Breul, Paulo Ceppi, and Theodore G. Shepherd
Weather Clim. Dynam., 3, 645–658, https://doi.org/10.5194/wcd-3-645-2022, https://doi.org/10.5194/wcd-3-645-2022, 2022
Short summary
Short summary
Understanding how the mid-latitude jet stream will respond to a changing climate is highly important. Unfortunately, climate models predict a wide variety of possible responses. Theoretical frameworks can link an internal jet variability timescale to its response. However, we show that stratospheric influence approximately doubles the internal timescale, inflating predicted responses. We demonstrate an approach to account for the stratospheric influence and recover correct response predictions.
Babak Jahani, Hendrik Andersen, Josep Calbó, Josep-Abel González, and Jan Cermak
Atmos. Chem. Phys., 22, 1483–1494, https://doi.org/10.5194/acp-22-1483-2022, https://doi.org/10.5194/acp-22-1483-2022, 2022
Short summary
Short summary
The change in the state of sky from cloudy to cloudless (or vice versa) comprises an additional phase called
transition zonewith characteristics laying between those of aerosols and clouds. This study presents an approach for the quantification of the broadband longwave radiative effects of the cloud–aerosol transition zone at the top of the atmosphere during daytime over the ocean based on satellite observations and radiative transfer simulations.
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
Short summary
Short summary
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.
Duncan Watson-Parris, Andrew Williams, Lucia Deaconu, and Philip Stier
Geosci. Model Dev., 14, 7659–7672, https://doi.org/10.5194/gmd-14-7659-2021, https://doi.org/10.5194/gmd-14-7659-2021, 2021
Short summary
Short summary
The Earth System Emulator (ESEm) provides a fast and flexible framework for emulating a wide variety of Earth science datasets and tools for constraining (or tuning) models of any complexity. Three distinct use cases are presented that demonstrate the utility of ESEm and provide some insight into the use of machine learning for emulation in these different settings. The open-source Python package is freely available so that it might become a valuable tool for the community.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
Short summary
Short summary
Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Peer Nowack, Lev Konstantinovskiy, Hannah Gardiner, and John Cant
Atmos. Meas. Tech., 14, 5637–5655, https://doi.org/10.5194/amt-14-5637-2021, https://doi.org/10.5194/amt-14-5637-2021, 2021
Short summary
Short summary
Machine learning (ML) calibration techniques could be an effective way to improve the performance of low-cost air pollution sensors. Here we provide novel insights from case studies within the urban area of London, UK, where we compared the performance of three ML techniques to calibrate low-cost measurements of NO2 and PM10. In particular, we highlight the key issue of the method-dependent robustness in maintaining calibration skill after transferring sensors to different measurement sites.
Carl Thomas, Apostolos Voulgarakis, Gerald Lim, Joanna Haigh, and Peer Nowack
Weather Clim. Dynam., 2, 581–608, https://doi.org/10.5194/wcd-2-581-2021, https://doi.org/10.5194/wcd-2-581-2021, 2021
Short summary
Short summary
Atmospheric blocking events are complex large-scale weather patterns which block the path of the jet stream. They are associated with heat waves in summer and cold snaps in winter. Blocking is poorly understood, and the effect of climate change is not clear. Here, we present a new method to study blocking using unsupervised machine learning. We show that this method performs better than previous methods used. These results show the potential for unsupervised learning in atmospheric science.
Shipeng Zhang, Philip Stier, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 10179–10197, https://doi.org/10.5194/acp-21-10179-2021, https://doi.org/10.5194/acp-21-10179-2021, 2021
Short summary
Short summary
The relationship between aerosol-induced changes in atmospheric energetics and precipitation responses across different scales is studied in terms of fast (radiatively or microphysically mediated) and slow (temperature-mediated) responses. We introduced a method to decompose rainfall changes into contributions from clouds, aerosols, and clear–clean sky from an energetic perspective. It provides a way to better interpret and quantify the precipitation changes caused by aerosol perturbations.
Alexander Kuhn-Régnier, Apostolos Voulgarakis, Peer Nowack, Matthias Forkel, I. Colin Prentice, and Sandy P. Harrison
Biogeosciences, 18, 3861–3879, https://doi.org/10.5194/bg-18-3861-2021, https://doi.org/10.5194/bg-18-3861-2021, 2021
Short summary
Short summary
Along with current climate, vegetation, and human influences, long-term accumulation of biomass affects fires. Here, we find that including the influence of antecedent vegetation and moisture improves our ability to predict global burnt area. Additionally, the length of the preceding period which needs to be considered for accurate predictions varies across regions.
Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 21, 6895–6917, https://doi.org/10.5194/acp-21-6895-2021, https://doi.org/10.5194/acp-21-6895-2021, 2021
Short summary
Short summary
Absorptive aerosol has a potentially large impact on climate change. We evaluate and intercompare four global satellite datasets of absorptive aerosol optical depth (AAOD) and single-scattering albedo (SSA). We show that these datasets show reasonable correlations with the AErosol RObotic NETwork (AERONET) reference, although significant biases remain. In a follow-up paper we show that these observations nevertheless can be used for model evaluation.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
Short summary
Short summary
Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Roland Stirnberg, Jan Cermak, Simone Kotthaus, Martial Haeffelin, Hendrik Andersen, Julia Fuchs, Miae Kim, Jean-Eudes Petit, and Olivier Favez
Atmos. Chem. Phys., 21, 3919–3948, https://doi.org/10.5194/acp-21-3919-2021, https://doi.org/10.5194/acp-21-3919-2021, 2021
Short summary
Short summary
Air pollution endangers human health and poses a problem particularly in densely populated areas. Here, an explainable machine learning approach is used to analyse periods of high particle concentrations for a suburban site southwest of Paris to better understand its atmospheric drivers. Air pollution is particularly excaberated by low temperatures and low mixed layer heights, but processes vary substantially between and within seasons.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
Short summary
Short summary
Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Jim M. Haywood, Steven J. Abel, Paul A. Barrett, Nicolas Bellouin, Alan Blyth, Keith N. Bower, Melissa Brooks, Ken Carslaw, Haochi Che, Hugh Coe, Michael I. Cotterell, Ian Crawford, Zhiqiang Cui, Nicholas Davies, Beth Dingley, Paul Field, Paola Formenti, Hamish Gordon, Martin de Graaf, Ross Herbert, Ben Johnson, Anthony C. Jones, Justin M. Langridge, Florent Malavelle, Daniel G. Partridge, Fanny Peers, Jens Redemann, Philip Stier, Kate Szpek, Jonathan W. Taylor, Duncan Watson-Parris, Robert Wood, Huihui Wu, and Paquita Zuidema
Atmos. Chem. Phys., 21, 1049–1084, https://doi.org/10.5194/acp-21-1049-2021, https://doi.org/10.5194/acp-21-1049-2021, 2021
Short summary
Short summary
Every year, the seasonal cycle of biomass burning from agricultural practices in Africa creates a huge plume of smoke that travels many thousands of kilometres over the Atlantic Ocean. This study provides an overview of a measurement campaign called the cloud–aerosol–radiation interaction and forcing for year 2017 (CLARIFY-2017) and documents the rationale, deployment strategy, observations, and key results from the campaign which utilized the heavily equipped FAAM atmospheric research aircraft.
Haochi Che, Philip Stier, Hamish Gordon, Duncan Watson-Parris, and Lucia Deaconu
Atmos. Chem. Phys., 21, 17–33, https://doi.org/10.5194/acp-21-17-2021, https://doi.org/10.5194/acp-21-17-2021, 2021
Short summary
Short summary
The south-eastern Atlantic is semi-permanently covered by some of the largest stratocumulus clouds and is influenced by one-third of the biomass burning emissions from African fires. A UKEMS1 model simulation shows that the absorption effect of biomass burning aerosols is the most significant on clouds and radiation. The dominate cooling and rapid adjustments induced by the radiative effects of biomass burning aerosols result in an overall cooling in the south-eastern Atlantic.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
Short summary
Short summary
Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Abdul Malik, Peer J. Nowack, Joanna D. Haigh, Long Cao, Luqman Atique, and Yves Plancherel
Atmos. Chem. Phys., 20, 15461–15485, https://doi.org/10.5194/acp-20-15461-2020, https://doi.org/10.5194/acp-20-15461-2020, 2020
Short summary
Short summary
Solar geoengineering has been introduced to mitigate human-caused global warming by reflecting sunlight back into space. This research investigates the impact of solar geoengineering on the tropical Pacific climate. We find that solar geoengineering can compensate some of the greenhouse-induced changes in the tropical Pacific but not all. In particular, solar geoengineering will result in significant changes in rainfall, sea surface temperatures, and increased frequency of extreme ENSO events.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
Short summary
Short summary
Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Nick Schutgens, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard, Robert C. Levy, Antti Lipponen, Alexei Lyapustin, Peter North, Thomas Popp, Caroline Poulsen, Virginia Sawyer, Larisa Sogacheva, Gareth Thomas, Omar Torres, Yujie Wang, Stefan Kinne, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 20, 12431–12457, https://doi.org/10.5194/acp-20-12431-2020, https://doi.org/10.5194/acp-20-12431-2020, 2020
Short summary
Short summary
We intercompare 14 different datasets of satellite observations of aerosol. Such measurements are challenging but also provide the best opportunity to globally observe an atmospheric component strongly related to air pollution and climate change. Our study shows that most datasets perform similarly well on a global scale but that locally errors can be quite different. We develop a technique to estimate satellite errors everywhere, even in the absence of surface reference data.
Cited articles
Anber, U., Wang, S., and Sobel, A.: Response of Atmospheric Convection to Vertical Wind Shear: Cloud-System-Resolving Simulations with Parameterized Large-Scale Circulation. Part I: Specified Radiative Cooling, J. Atmos. Sci., 71, 2976–2993, https://doi.org/10.1175/JAS-D-13-0320.1, 2014.
Andersen, H., Cermak, J., Fuchs, J., Knutti, R., and Lohmann, U.: Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks, Atmos. Chem. Phys., 17, 9535–9546, https://doi.org/10.5194/acp-17-9535-2017, 2017.
Andersen, H., Cermak, J., Zipfel, L., and Myers, T. A.: Attribution of Observed Recent Decrease in Low Clouds Over the Northeastern Pacific to Cloud-Controlling Factors, Geophys. Res. Lett., 49, e2021GL096498, https://doi.org/10.1029/2021GL096498, 2022.
Andersen, H., Cermak, J., Douglas, A., Myers, T. A., Nowack, P., Stier, P., Wall, C. J., and Wilson Kemsley, S.: Sensitivities of cloud radiative effects to large-scale meteorology and aerosols from global observations, Atmos. Chem. Phys., 23, 10775–10794, https://doi.org/10.5194/acp-23-10775-2023, 2023.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.: COSP: Satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011.
Bony, S., Lau, K.-M., and Sud, Y. C.: Sea Surface Temperature and Large-Scale Circulation Influences on Tropical Greenhouse Effect and Cloud Radiative Forcing, J. Climate, 10, 2055–2077, https://doi.org/10.1175/1520-0442(1997)010<2055:SSTALS>2.0.CO;2, 1997.
Bony, S., Dufresne, J.-L., Le Treut, H., Morcrette, J.-J., and Senior, C.: On dynamic and thermodynamic components of cloud changes, Clim. Dynam., 22, 71–86, https://doi.org/10.1007/s00382-003-0369-6, 2004.
Bony, S., Stevens, B., Coppin, D., Becker, T., Reed, K. A., Voigt, A., and Medeiros, B.: Thermodynamic control of anvil cloud amount, P. Natl. Acad. Sci. USA, 113, 8927–8932, https://doi.org/10.1073/pnas.1601472113, 2016.
Bretherton, C. S.: Insights into low-latitude cloud feedbacks from high-resolution models, Philos. T. R. Soc. A, 373, 20140415, https://doi.org/10.1098/rsta.2014.0415, 2015.
Brient, F. and Schneider, T.: Constraints on Climate Sensitivity from Space-Based Measurements of Low-Cloud Reflection, J. Climate, 29, 5821–5835, https://doi.org/10.1175/JCLI-D-15-0897.1, 2016.
Byrne, M. P. and Schneider, T.: Atmospheric Dynamics Feedback: Concept, Simulations, and Climate Implications, J. Climate, 31, 3249–3264, https://doi.org/10.1175/JCLI-D-17-0470.1, 2018.
CEDA: ESGF Portal, https://esgf-ui.ceda.ac.uk/cog/projects/esgf-ceda/ (last access: 18 July 2024), 2024.
Ceppi, P. and Fueglistaler, S.: The El Niño–Southern Oscillation Pattern Effect, Geophys. Res. Lett., 48, e2021GL095261, https://doi.org/10.1029/2021GL095261, 2021.
Ceppi, P. and Nowack, P.: Observational evidence that cloud feedback amplifies global warming, P. Natl. Acad. Sci. USA, 118, e2026290118, https://doi.org/10.1073/pnas.2026290118, 2021.
Ceppi, P., Brient, F., Zelinka, M. D., and Hartmann, D. L.: Cloud feedback mechanisms and their representation in global climate models, WIREs Climate Change, 8, e465, https://doi.org/10.1002/wcc.465, 2017.
Chakraborty, S., Fu, R., Massie, S. T., and Stephens, G.: Relative influence of meteorological conditions and aerosols on the lifetime of mesoscale convective systems, P. Natl. Acad. Sci. USA, 113, 7426–7431, https://doi.org/10.1073/pnas.1601935113, 2016.
Chen, T., Rossow, W. B., and Zhang, Y.: Radiative Effects of Cloud-Type Variations, J. Climate, 13, 264–286, https://doi.org/10.1175/1520-0442(2000)013<0264:REOCTV>2.0.CO;2, 2000.
Davison, A. C. and Hinkley, D. V.: Bootstrap Methods and Their Application, Cambridge University Press, 606 pp., https://doi.org/10.1017/CBO9780511802843, 1997.
Donner, L. J. and Phillips, V. T.: Boundary layer control on convective available potential energy: Implications for cumulus parameterization, J. Geophys. Res.-Atmos., 108, 4701, https://doi.org/10.1029/2003JD003773, 2003.
Fuchs, J., Cermak, J., and Andersen, H.: Building a cloud in the southeast Atlantic: understanding low-cloud controls based on satellite observations with machine learning, Atmos. Chem. Phys., 18, 16537–16552, https://doi.org/10.5194/acp-18-16537-2018, 2018.
Fueglistaler, S.: Observational Evidence for Two Modes of Coupling Between Sea Surface Temperatures, Tropospheric Temperature Profile, and Shortwave Cloud Radiative Effect in the Tropics, Geophys. Res. Lett., 46, 9890–9898, https://doi.org/10.1029/2019GL083990, 2019.
Fueglistaler, S., Dessler, A. E., Dunkerton, T. J., Folkins, I., Fu, Q., and Mote, P. W.: Tropical tropopause layer, Rev. Geophys., 47, RG1004, https://doi.org/10.1029/2008RG000267, 2009.
Gasparini, B., Blossey, P. N., Hartmann, D. L., Lin, G., and Fan, J.: What Drives the Life Cycle of Tropical Anvil Clouds?, J. Adv. Model. Earth Sy., 11, 2586–2605, https://doi.org/10.1029/2019MS001736, 2019.
Gasparini, B., Sullivan, S. C., Sokol, A. B., Kärcher, B., Jensen, E., and Hartmann, D. L.: Opinion: Tropical cirrus – from micro-scale processes to climate-scale impacts, Atmos. Chem. Phys., 23, 15413–15444, https://doi.org/10.5194/acp-23-15413-2023, 2023.
Ge, J., Wang, Z., Wang, C., Yang, X., Dong, Z., and Wang, M.: Diurnal variations of global clouds observed from the CATS spaceborne lidar and their links to large-scale meteorological factors, Clim. Dynam., 57, 2637–2651, https://doi.org/10.1007/s00382-021-05829-2, 2021.
Grise, K. M., Thompson, D. W. J., and Birner, T.: A Global Survey of Static Stability in the Stratosphere and Upper Troposphere, J. Climate, 23, 2275–2292, https://doi.org/10.1175/2009JCLI3369.1, 2010.
Hentgen, L., Ban, N., Kröner, N., Leutwyler, D., and Schär, C.: Clouds in Convection-Resolving Climate Simulations Over Europe, J. Geophys. Res.-Atmos., 124, 3849–3870, https://doi.org/10.1029/2018JD030150, 2019.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7, 2023a.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.6860a573, 2023b.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023c.
Hoerl, A. E. and Kennard, R. W.: Ridge Regression: Biased Estimation for Nonorthogonal Problems, Technometrics, 12, 55–67, https://doi.org/10.1080/00401706.1970.10488634, 1970.
Hubanks, P., Pincus, R., Platnick, S., and Meyer, K.: MODIS Standard Atmosphere Level-3 MCD06COSP, LAADS [data set], https://doi.org/10.5067/MODIS/MCD06COSP_M3_MODIS.062, 2022.
Jensen, E. J., Kinne, S., and Toon, O. B.: Tropical cirrus cloud radiative forcing: Sensitivity studies, Geophys. Res. Lett., 21, 2023–2026, https://doi.org/10.1029/94GL01358, 1994.
Jensen, E. J., Pfister, L., and Toon, O. B.: Impact of radiative heating, wind shear, temperature variability, and microphysical processes on the structure and evolution of thin cirrus in the tropical tropopause layer, J. Geophys. Res.-Atmos., 116, D12209, https://doi.org/10.1029/2010JD015417, 2011.
Jensen, M. and Delgenio, A.: Factors Limiting Convective Cloud-Top Height at the ARM Nauru Island Climate Research Facility, J. Climate, 19, 2105–2117, https://doi.org/10.1175/JCLI3722.1, 2006.
Kärcher, B.: Cirrus Clouds and Their Response to Anthropogenic Activities, Curr. Clim. Change Rep., 3, 45–57, https://doi.org/10.1007/s40641-017-0060-3, 2017.
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., 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.
Li, J.-L. F., Waliser, D. E., Chen, W.-T., Guan, B., Kubar, T., Stephens, G., Ma, H.-Y., Deng, M., Donner, L., Seman, C., and Horowitz, L.: An observationally based evaluation of cloud ice water in CMIP3 and CMIP5 GCMs and contemporary reanalyses using contemporary satellite data, J. Geophys. Res.-Atmos., 117, D16105, https://doi.org/10.1029/2012JD017640, 2012.
Li, Y., Thompson, D. W. J., Stephens, G. L., and Bony, S.: A global survey of the instantaneous linkages between cloud vertical structure and large-scale climate, J. Geophys. Res.-Atmos., 119, 3770–3792, https://doi.org/10.1002/2013JD020669, 2014.
Lin, J.-L. and Mapes, B.: Wind shear effects on cloud-radiation feedback in the western Pacific warm pool, Geophys. Res. Lett., 31, L16118, https://doi.org/10.1029/2004GL020199, 2004.
Louf, V., Jakob, C., Protat, A., Bergemann, M., and Narsey, S.: The Relationship of Cloud Number and Size With Their Large-Scale Environment in Deep Tropical Convection, Geophys. Res. Lett., 46, 9203–9212, https://doi.org/10.1029/2019GL083964, 2019.
Luo, Z. and Rossow, W. B.: Characterizing Tropical Cirrus Life Cycle, Evolution, and Interaction with Upper-Tropospheric Water Vapor Using Lagrangian Trajectory Analysis of Satellite Observations, J. Climate, 17, 4541–4563, https://doi.org/10.1175/3222.1, 2004.
Marsham, J. H. and Dobbie, S.: The effects of wind shear on cirrus: A large-eddy model and radar case-study, Q. J. Roy. Meteor. Soc., 131, 2937–2955, https://doi.org/10.1256/qj.04.122, 2005.
May, R. M., Arms, S. C., Marsh, P., Bruning, E., Leeman, J. R., Goebbert, K., Thielen, J. E., Bruick, Z. S., and Camron, M. D., MetPy: A Python Package for Meteorological Data v1.6.2, Unidata [code], https://doi.org/10.5065/D6WW7G29, 2024.
McFarquhar, G. M., Heymsfield, A. J., Spinhirne, J., and Hart, B.: Thin and Subvisual Tropopause Tropical Cirrus: Observations and Radiative Impacts, J. Atmos. Sci., 57, 1841–1853, https://doi.org/10.1175/1520-0469(2000)057<1841:TASTTC>2.0.CO;2, 2000.
McKim, B., Bony, S., and Dufresne, J.-L.: Weak anvil cloud area feedback suggested by physical and observational constraints, Nat. Geosci., 17, 1–6, https://doi.org/10.1038/s41561-024-01414-4, 2024.
Medeiros, B. and Stevens, B.: Revealing differences in GCM representations of low clouds, Clim. Dynam., 36, 385–399, https://doi.org/10.1007/s00382-009-0694-5, 2011.
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.
Myers, T. A., Scott, R. C., Zelinka, M. D., Klein, S. A., Norris, J. R., and Caldwell, P. M.: Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity, Nat. Clim. Change, 11, 501–507, https://doi.org/10.1038/s41558-021-01039-0, 2021.
Nelson, T. C., Marquis, J., Peters, J. M., and Friedrich, K.: Environmental Controls on Simulated Deep Moist Convection Initiation Occurring during RELAMPAGO-CACTI, J. Atmos. Sci., 79, 1941–1964, https://doi.org/10.1175/JAS-D-21-0226.1, 2022.
Nowack, P., Konstantinovskiy, L., Gardiner, H., and Cant, J.: Machine learning calibration of low-cost NO2 and PM10 sensors: non-linear algorithms and their impact on site transferability, Atmos. Meas. Tech., 14, 5637–5655, https://doi.org/10.5194/amt-14-5637-2021, 2021.
Pincus, R., Hubanks, P. A., Platnick, S., Meyer, K., Holz, R. E., Botambekov, D., and Wall, C. J.: Updated observations of clouds by MODIS for global model assessment, Earth Syst. Sci. Data, 15, 2483–2497, https://doi.org/10.5194/essd-15-2483-2023, 2023.
Qu, X., Hall, A., Klein, S. A., and Caldwell, P. M.: On the spread of changes in marine low cloud cover in climate model simulations of the 21st century, Clim. Dynam., 42, 2603–2626, https://doi.org/10.1007/s00382-013-1945-z, 2014.
Qu, X., Hall, A., Klein, S. A., and DeAngelis, A. 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.
Reichler, T., Dameris, M., and Sausen, R.: Determining the tropopause height from gridded data, Geophys. Res. Lett., 30, 1944–8007, https://doi.org/10.1029/2003GL018240, 2003.
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.
Riemann-Campe, K., Fraedrich, K., and Lunkeit, F.: Global climatology of Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN) in ERA-40 reanalysis, Atmos. Res., 93, 534–545, https://doi.org/10.1016/j.atmosres.2008.09.037, 2009.
Rio, C., Del Genio, A. D., and Hourdin, F.: Ongoing Breakthroughs in Convective Parameterization, Curr. Clim. Change Rep., 5, 95–111, https://doi.org/10.1007/s40641-019-00127-w, 2019.
Saint-Lu, M., Bony, S., and Dufresne, J.-L.: Observational Evidence for a Stability Iris Effect in the Tropics, Geophys. Res. Lett., 47, e2020GL089059, https://doi.org/10.1029/2020GL089059, 2020.
Saint-Lu, M., Bony, S., and Dufresne, J.-L.: Clear-sky control of anvils in response to increased CO2 or surface warming or volcanic eruptions, npj Clim. Atmos. Sci., 5, 1–8, https://doi.org/10.1038/s41612-022-00304-z, 2022.
Scott, R. C., Myers, T. A., Norris, J. R., Zelinka, M. D., Klein, S. A., Sun, M., and Doelling, D. R.: Observed Sensitivity of Low-Cloud Radiative Effects to Meteorological Perturbations over the Global Oceans, J. Climate, 33, 7717–7734, https://doi.org/10.1175/JCLI-D-19-1028.1, 2020.
Sherwood, S. C.: Convective Precursors and Predictability in the Tropical Western Pacific, Mon. Weather Rev., 127, 2977–2991, https://doi.org/10.1175/1520-0493(1999)127<2977:CPAPIT>2.0.CO;2, 1999.
Sherwood, S. C., Minnis, P., and McGill, M.: Deep convective cloud-top heights and their thermodynamic control during CRYSTAL-FACE, J. Geophys. Res.-Atmos., 109, D20119, https://doi.org/10.1029/2004JD004811, 2004.
Sherwood, S. C., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., Hegerl, G., Klein, S. A., Marvel, K. D., Rohling, E. J., Watanabe, M., Andrews, T., Braconnot, P., Bretherton, C. S., Foster, G. L., Hausfather, Z., von der Heydt, A. S., Knutti, R., Mauritsen, T., Norris, J. R., Proistosescu, C., Rugenstein, M., Schmidt, G. A., Tokarska, K. B., and Zelinka, M. D.: An Assessment of Earth's Climate Sensitivity Using Multiple Lines of Evidence, Rev. Geophys., 58, e2019RG000678, https://doi.org/10.1029/2019RG000678, 2020.
Siebesma, A. P., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J., Duynkerke, P. G., Jiang, H., Khairoutdinov, M., Lewellen, D., Moeng, C.-H., Sanchez, E., Stevens, B., and Stevens, D. E.: A Large Eddy Simulation Intercomparison Study of Shallow Cumulus Convection, J. Atmos. Sci., 60, 1201–1219, https://doi.org/10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2, 2003.
Srinivasan, J. and Smith, G. L.: The Role of Heat Fluxes and Moist Static Energy in Tropical Convergence Zones, Mon. Weather Rev., 124, 2089–2099, https://doi.org/10.1175/1520-0493(1996)124<2089:TROHFA>2.0.CO;2, 1996.
Tsushima, Y., Ringer, M. A., Webb, M. J., and Williams, K. D.: Quantitative evaluation of the seasonal variations in climate model cloud regimes, Clim. Dynam, 41, 2679–2696, https://doi.org/10.1007/s00382-012-1609-4, 2013.
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.
Xu, K.-M. and Cheng, A.: Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework, J. Adv. Model. Earth Sy., 8, 1825–1846, https://doi.org/10.1002/2016MS000767, 2016.
Zelinka, M.: Cloud Radiative Kernel code, GitHub [code], https://github.com/mzelinka/cloud-radiative-kernels (last access: 17 July 2024), 2024.
Zelinka, M. D. and Hartmann, D. L.: Why is longwave cloud feedback positive?, J. Geophys. Res., 115, D16117, https://doi.org/10.1029/2010JD013817, 2010.
Zelinka, M. D. and Hartmann, D. L.: The observed sensitivity of high clouds to mean surface temperature anomalies in the tropics, J. Geophys. Res.-Atmos., 116, D23103, https://doi.org/10.1029/2011JD016459, 2011.
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, 2012a.
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, 2012b.
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.
Zelinka, M. D., Klein, S. A., Qin, Y., and Myers, T. A.: Evaluating Climate Models' Cloud Feedbacks Against Expert Judgment, J. Geophys. Res.-Atmos., 127, e2021JD035198, https://doi.org/10.1029/2021JD035198, 2022.
Zhang, Y. and Fueglistaler, S.: How Tropical Convection Couples High Moist Static Energy Over Land and Ocean, Geophys. Res. Lett., 47, e2019GL086387, https://doi.org/10.1029/2019GL086387, 2020.
Short summary
Aiming to inform parameter selection for future observational constraint analyses, we incorporate five candidate meteorological drivers specifically targeting high clouds into a cloud controlling factor framework within a range of spatial domain sizes. We find a discrepancy between optimal domain size for predicting locally and globally aggregated cloud radiative anomalies and identify upper-tropospheric static stability as an important high-cloud controlling factor.
Aiming to inform parameter selection for future observational constraint analyses, we...
Altmetrics
Final-revised paper
Preprint