Articles | Volume 24, issue 15
https://doi.org/10.5194/acp-24-8653-2024
© 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-24-8653-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Investigating the sign of stratocumulus adjustments to aerosols in the ICON global storm-resolving model
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Ann Kristin Naumann
Climate Physics Department, Max Planck Institute for Meteorology, Hamburg, Germany
Meteorological Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
David Neubauer
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Theresa Lang
Climate Physics Department, Max Planck Institute for Meteorology, Hamburg, Germany
Meteorological Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
Ulrike Lohmann
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Related authors
No articles found.
Kai Jeggle, David Neubauer, Hanin Binder, and Ulrike Lohmann
Atmos. Chem. Phys., 25, 7227–7243, https://doi.org/10.5194/acp-25-7227-2025, https://doi.org/10.5194/acp-25-7227-2025, 2025
Short summary
Short summary
This work uncovers the formation regimes of cirrus clouds and how dust particles influence their properties. By applying machine learning to a combination of satellite and reanalysis data, cirrus clouds are classified into different formation regimes. Depending on the regime, increasing dust aerosol concentrations can either decrease or increase the number of ice crystals. This challenges the idea of using cloud seeding to cool the planet, as it may unintentionally lead to warming instead.
Christopher Fuchs, Fabiola Ramelli, David Schweizer, Ulrike Lohmann, and Jan Henneberger
Atmos. Meas. Tech., 18, 2969–2986, https://doi.org/10.5194/amt-18-2969-2025, https://doi.org/10.5194/amt-18-2969-2025, 2025
Short summary
Short summary
We present a new instrument based on digital in-line holography (SmHOLIMO) for in situ cloud measurements. SmHOLIMO is designed to specifically measure small cloud droplets with diameters > 3.7 μm. This way we retrieve accurate cloud droplet size distributions, which are crucial to understand the evolution and governing microphysical processes of a cloud. Results of a field study are compared to co-located measurements of a second holographic imager, microwave radiometer, and cloud radar.
Ann Kristin Naumann, Monika Esch, and Bjorn Stevens
Atmos. Chem. Phys., 25, 6429–6444, https://doi.org/10.5194/acp-25-6429-2025, https://doi.org/10.5194/acp-25-6429-2025, 2025
Short summary
Short summary
This study explores how uncertainties in the representation of microphysical processes affect the tropical condensate distribution in the global storm-resolving model ICON. The results point to the importance of the fall speed of hydrometeor particles and to a simple relationship: the faster a condensate falls, the less there is of it. Implications for the energy balance and precipitation properties are discussed.
Guangyu Li, André Welti, Iris Thurnherr, Ulrike Lohmann, and Zamin A. Kanji
EGUsphere, https://doi.org/10.5194/egusphere-2025-2798, https://doi.org/10.5194/egusphere-2025-2798, 2025
Short summary
Short summary
This study presents ship-based measurements of summertime ice-nucleating particles (INPs) over the data-scarce Eurasian-Arctic Seas. We found that INPs are driven by both local and regional sources, with the highest levels observed near land and over ice-free waters. This study is highlighted for improving the understanding of INP abundance, sources, and their role in cloud processes in the rapidly warming Arctic.
Yusuf Bhatti, Duncan Watson-Parris, Leighton Regayre, Hailing Jia, David Neubauer, Ulas Im, Carl Svenhag, Nick Schutgens, Athanasios Tsikerdekis, Athanasios Nenes, Irfan Muhammed, Bastiaan van Diedenhoven, Ardit Arifi, Guangliang Fu, and Otto Hasekamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-2848, https://doi.org/10.5194/egusphere-2025-2848, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Aerosols (small airborne particles) impact Earth's climate, but their extent is unknown. By running climate model simulations and emulating millions of additional variants with different settings, we found that natural emissions like sea spray and sulfur are key sources of uncertainty in climate predictions. Our work shows that understanding these natural processes better can help improve climate models and make future climate projections more accurate.
Anna J. Miller, Christopher Fuchs, Fabiola Ramelli, Huiying Zhang, Nadja Omanovic, Robert Spirig, Claudia Marcolli, Zamin A. Kanji, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 25, 5387–5407, https://doi.org/10.5194/acp-25-5387-2025, https://doi.org/10.5194/acp-25-5387-2025, 2025
Short summary
Short summary
We analyzed the ability of silver iodide particles (a commonly used cloud-seeding agent) to form ice crystals in naturally occurring liquid clouds at −5 to −8 °C and found that only ≈ 0.1 %−1 % of particles nucleate ice, with a negative dependence on temperature. By contextualizing our results with previous laboratory studies, we help to bridge the gap between laboratory and field experiments, which also helps to inform future cloud-seeding projects.
Sini Talvinen, Paul Kim, Emanuele Tovazzi, Eemeli Holopainen, Roxana Cremer, Thomas Kühn, Harri Kokkola, Zak Kipling, David Neubauer, João C. Teixeira, Alistair Sellar, Duncan Watson-Parris, Yang Yang, Jialei Zhu, Srinath Krishnan, Annele Virtanen, and Daniel G. Partridge
EGUsphere, https://doi.org/10.5194/egusphere-2025-721, https://doi.org/10.5194/egusphere-2025-721, 2025
Short summary
Short summary
Climate models struggle to predict how clouds and aerosols interact, affecting Earth’s energy balance. This study compares models to observations to see how they describe effects of clouds and rain on aerosols. While both models show similar overall trends, seasonal differences emerged. These, however, align with differences in key variables participating in cloud formation. The study provides tools to improve the representation of aerosol-cloud interactions in climate models.
Felix Pithan, Ann Kristin Naumann, and Marion Maturilli
Atmos. Chem. Phys., 25, 3269–3285, https://doi.org/10.5194/acp-25-3269-2025, https://doi.org/10.5194/acp-25-3269-2025, 2025
Short summary
Short summary
Representing the exchange of air masses between the Arctic and mid-latitudes and the associated cloud formation is difficult for climate models. We compare climate model output to temperature and humidity measurements from weather balloons to provide suggestions for model improvements. Cold biases mostly occur in air that is exported from the Arctic. Models that compute the number of ice particles in a cloud better represent humidity than models that assume a fixed number of ice particles.
Christopher Fuchs, Fabiola Ramelli, Anna J. Miller, Nadja Omanovic, Robert Spirig, Huiying Zhang, Patric Seifert, Kevin Ohneiser, Ulrike Lohmann, and Jan Henneberger
EGUsphere, https://doi.org/10.5194/egusphere-2025-688, https://doi.org/10.5194/egusphere-2025-688, 2025
Short summary
Short summary
We quantify diffusional ice crystal growth in natural clouds using cloud seeding experiments. We report growth rates for 14 experiments between -5.1°C and -8.3°C and observe strong variations depending on the cloud characteristics. Comparing our growth rates to laboratory data, we found similar temperature-dependent trends, but the laboratory rates are higher. This data fills the gap in quantitative in situ observation of ice crystal growth, helping to validate models and laboratory experiments.
George Jordan, Florent Malavelle, Jim Haywood, Ying Chen, Ben Johnson, Daniel Partridge, Amy Peace, Eliza Duncan, Duncan Watson-Parris, David Neubauer, Anton Laakso, Martine Michou, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2025-835, https://doi.org/10.5194/egusphere-2025-835, 2025
Short summary
Short summary
The 2014–15 Holuhraun eruption created a vast aerosol plume that acted as a natural experiment to assess how well climate models capture changes in cloud properties due to increased aerosol. We find that the models accurately represent the observed shift to smaller, more numerous cloud droplets. However, the models diverge in their aerosol induced changes to large-scale cloud properties, particularly cloud liquid water content. Our study shows that Holuhraun had a cooling effect on the Earth.
Judith Kleinheins, Nadia Shardt, Ulrike Lohmann, and Claudia Marcolli
Atmos. Chem. Phys., 25, 881–903, https://doi.org/10.5194/acp-25-881-2025, https://doi.org/10.5194/acp-25-881-2025, 2025
Short summary
Short summary
We model the cloud condensation nuclei (CCN) activation of sea spray aerosol particles with classical Köhler theory and with a new model approach that takes surface tension lowering into account. We categorize organic compounds into weak, intermediate, and strong surfactants, and we outline for which composition surface tension lowering is important. The results suggest that surface tension lowering allows sea spray aerosol particles in the Aitken mode to be a source of CCN in marine updraughts.
Nadja Omanovic, Brigitta Goger, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 14145–14175, https://doi.org/10.5194/acp-24-14145-2024, https://doi.org/10.5194/acp-24-14145-2024, 2024
Short summary
Short summary
We evaluated the numerical weather model ICON in two horizontal resolutions with two bulk microphysics schemes over hilly and complex terrain in Switzerland and Austria, respectively. We focused on the model's ability to simulate mid-level clouds in summer and winter. By combining observational data from two different field campaigns, we show that an increase in the horizontal resolution and a more advanced cloud microphysics scheme is strongly beneficial for cloud representation.
Alkiviadis Kalisoras, Aristeidis K. Georgoulias, Dimitris Akritidis, Robert J. Allen, Vaishali Naik, Chaincy Kuo, Sophie Szopa, Pierre Nabat, Dirk Olivié, Twan van Noije, Philippe Le Sager, David Neubauer, Naga Oshima, Jane Mulcahy, Larry W. Horowitz, and Prodromos Zanis
Atmos. Chem. Phys., 24, 7837–7872, https://doi.org/10.5194/acp-24-7837-2024, https://doi.org/10.5194/acp-24-7837-2024, 2024
Short summary
Short summary
Effective radiative forcing (ERF) is a metric for estimating how human activities and natural agents change the energy flow into and out of the Earth’s climate system. We investigate the anthropogenic aerosol ERF, and we estimate the contribution of individual processes to the total ERF using simulations from Earth system models within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our findings highlight that aerosol–cloud interactions drive ERF variability during the last 150 years.
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.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
Short summary
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Nadja Omanovic, Sylvaine Ferrachat, Christopher Fuchs, Jan Henneberger, Anna J. Miller, Kevin Ohneiser, Fabiola Ramelli, Patric Seifert, Robert Spirig, Huiying Zhang, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 6825–6844, https://doi.org/10.5194/acp-24-6825-2024, https://doi.org/10.5194/acp-24-6825-2024, 2024
Short summary
Short summary
We present simulations with a high-resolution numerical weather prediction model to study the growth of ice crystals in low clouds following glaciogenic seeding. We show that the simulated ice crystals grow slower than observed and do not consume as many cloud droplets as measured in the field. This may have implications for forecasting precipitation, as the ice phase is crucial for precipitation at middle and high latitudes.
Ulrike Proske, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys., 24, 5907–5933, https://doi.org/10.5194/acp-24-5907-2024, https://doi.org/10.5194/acp-24-5907-2024, 2024
Short summary
Short summary
Climate models include treatment of aerosol particles because these influence clouds and radiation. Over time their representation has grown increasingly detailed. This complexity may hinder our understanding of model behaviour. Thus here we simplify the aerosol representation of our climate model by prescribing mean concentrations, which saves run time and helps to discover unexpected model behaviour. We conclude that simplifications provide a new perspective for model study and development.
Zane Dedekind, Ulrike Proske, Sylvaine Ferrachat, Ulrike Lohmann, and David Neubauer
Atmos. Chem. Phys., 24, 5389–5404, https://doi.org/10.5194/acp-24-5389-2024, https://doi.org/10.5194/acp-24-5389-2024, 2024
Short summary
Short summary
Ice particles precipitating into lower clouds from an upper cloud, the seeder–feeder process, can enhance precipitation. A numerical modeling study conducted in the Swiss Alps found that 48 % of observed clouds were overlapping, with the seeder–feeder process occurring in 10 % of these clouds. Inhibiting the seeder–feeder process reduced the surface precipitation and ice particle growth rates, which were further reduced when additional ice multiplication processes were included in the model.
George Jordan, Florent Malavelle, Ying Chen, Amy Peace, Eliza Duncan, Daniel G. Partridge, Paul Kim, Duncan Watson-Parris, Toshihiko Takemura, David Neubauer, Gunnar Myhre, Ragnhild Skeie, Anton Laakso, and James Haywood
Atmos. Chem. Phys., 24, 1939–1960, https://doi.org/10.5194/acp-24-1939-2024, https://doi.org/10.5194/acp-24-1939-2024, 2024
Short summary
Short summary
The 2014–15 Holuhraun eruption caused a huge aerosol plume in an otherwise unpolluted region, providing a chance to study how aerosol alters cloud properties. This two-part study uses observations and models to quantify this relationship’s impact on the Earth’s energy budget. Part 1 suggests the models capture the observed spatial and chemical evolution of the plume, yet no model plume is exact. Understanding these differences is key for Part 2, where changes to cloud properties are explored.
Anna J. Miller, Fabiola Ramelli, Christopher Fuchs, Nadja Omanovic, Robert Spirig, Huiying Zhang, Ulrike Lohmann, Zamin A. Kanji, and Jan Henneberger
Atmos. Meas. Tech., 17, 601–625, https://doi.org/10.5194/amt-17-601-2024, https://doi.org/10.5194/amt-17-601-2024, 2024
Short summary
Short summary
We present a method for aerosol and cloud research using two uncrewed aerial vehicles (UAVs). The UAVs have a propeller heating mechanism that allows flights in icing conditions, which has so far been a limitation for cloud research with UAVs. One UAV burns seeding flares, producing a plume of particles that causes ice formation in supercooled clouds. The second UAV measures aerosol size distributions and is used for measuring the seeding plume or for characterizing the boundary layer.
Guangyu Li, Elise K. Wilbourn, Zezhen Cheng, Jörg Wieder, Allison Fagerson, Jan Henneberger, Ghislain Motos, Rita Traversi, Sarah D. Brooks, Mauro Mazzola, Swarup China, Athanasios Nenes, Ulrike Lohmann, Naruki Hiranuma, and Zamin A. Kanji
Atmos. Chem. Phys., 23, 10489–10516, https://doi.org/10.5194/acp-23-10489-2023, https://doi.org/10.5194/acp-23-10489-2023, 2023
Short summary
Short summary
In this work, we present results from an Arctic field campaign (NASCENT) in Ny-Ålesund, Svalbard, on the abundance, variability, physicochemical properties, and potential sources of ice-nucleating particles (INPs) relevant for mixed-phase cloud formation. This work improves the data coverage of Arctic INPs and aerosol properties, allowing for the validation of models predicting cloud microphysical and radiative properties of mixed-phase clouds in the rapidly warming Arctic.
Bernhard M. Enz, Jan P. Engelmann, and Ulrike Lohmann
Geosci. Model Dev., 16, 5093–5112, https://doi.org/10.5194/gmd-16-5093-2023, https://doi.org/10.5194/gmd-16-5093-2023, 2023
Short summary
Short summary
An algorithm to track tropical cyclones in model simulation data has been developed. The algorithm uses many combinations of varying parameter thresholds to detect weaker phases of tropical cyclones while still being resilient to false positives. It is shown that the algorithm performs well and adequately represents the tropical cyclone activity of the underlying simulation data. The impact of false positives on overall tropical cyclone activity is shown to be insignificant.
Colin Tully, David Neubauer, Diego Villanueva, and Ulrike Lohmann
Atmos. Chem. Phys., 23, 7673–7698, https://doi.org/10.5194/acp-23-7673-2023, https://doi.org/10.5194/acp-23-7673-2023, 2023
Short summary
Short summary
This study details the first attempt with a GCM to simulate a fully prognostic aerosol species specifically for cirrus climate intervention. The new approach is in line with the real-world delivery mechanism via aircraft. However, to achieve an appreciable signal from seeding, smaller particles were needed, and their mass emissions needed to be scaled by at least a factor of 100. These biases contributed to either overseeding or small and insignificant effects in response to seeding cirrus.
Colin Tully, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 16, 2957–2973, https://doi.org/10.5194/gmd-16-2957-2023, https://doi.org/10.5194/gmd-16-2957-2023, 2023
Short summary
Short summary
A new method to simulate deterministic ice nucleation processes based on the differential activated fraction was evaluated against a cumulative approach. Box model simulations of heterogeneous-only ice nucleation within cirrus suggest that the latter approach likely underpredicts the ice crystal number concentration. Longer simulations with a GCM show that choosing between these two approaches impacts ice nucleation competition within cirrus but leads to small and insignificant climate effects.
Zane Dedekind, Jacopo Grazioli, Philip H. Austin, and Ulrike Lohmann
Atmos. Chem. Phys., 23, 2345–2364, https://doi.org/10.5194/acp-23-2345-2023, https://doi.org/10.5194/acp-23-2345-2023, 2023
Short summary
Short summary
Simulations allowing ice particles to collide with one another producing more ice particles represented surface observations of ice particles accurately. An increase in ice particles formed through collisions was related to sharp changes in the wind direction and speed with height. Changes in wind speed and direction can therefore cause more enhanced collisions between ice particles and alter how fast and how much precipitation forms. Simulations were conducted with the atmospheric model COSMO.
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
Short summary
Short summary
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.
Julie Thérèse Pasquier, Jan Henneberger, Fabiola Ramelli, Annika Lauber, Robert Oscar David, Jörg Wieder, Tim Carlsen, Rosa Gierens, Marion Maturilli, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 15579–15601, https://doi.org/10.5194/acp-22-15579-2022, https://doi.org/10.5194/acp-22-15579-2022, 2022
Short summary
Short summary
It is important to understand how ice crystals and cloud droplets form in clouds, as their concentrations and sizes determine the exact radiative properties of the clouds. Normally, ice crystals form from aerosols, but we found evidence for the formation of additional ice crystals from the original ones over a large temperature range within Arctic clouds. In particular, additional ice crystals were formed during collisions of several ice crystals or during the freezing of large cloud droplets.
Florin N. Isenrich, Nadia Shardt, Michael Rösch, Julia Nette, Stavros Stavrakis, Claudia Marcolli, Zamin A. Kanji, Andrew J. deMello, and Ulrike Lohmann
Atmos. Meas. Tech., 15, 5367–5381, https://doi.org/10.5194/amt-15-5367-2022, https://doi.org/10.5194/amt-15-5367-2022, 2022
Short summary
Short summary
Ice nucleation in the atmosphere influences cloud properties and lifetimes. Microfluidic instruments have recently been used to investigate ice nucleation, but these instruments are typically made out of a polymer that contributes to droplet instability over extended timescales and relatively high temperature uncertainty. To address these drawbacks, we develop and validate a new microfluidic instrument that uses fluoropolymer tubing to extend droplet stability and improve temperature accuracy.
Colin Tully, David Neubauer, Nadja Omanovic, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 11455–11484, https://doi.org/10.5194/acp-22-11455-2022, https://doi.org/10.5194/acp-22-11455-2022, 2022
Short summary
Short summary
The proposed geoengineering method, cirrus cloud thinning, was evaluated using a more physically based microphysics scheme coupled to a more realistic approach for calculating ice cloud fractions in the ECHAM-HAM GCM. Sensitivity tests reveal that using the new ice cloud fraction approach and increasing the critical ice saturation ratio for ice nucleation on seeding particles reduces warming from overseeding. However, this geoengineering method is unlikely to be feasible on a global scale.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
Short summary
Short summary
Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Jörg Wieder, Nikola Ihn, Claudia Mignani, Moritz Haarig, Johannes Bühl, Patric Seifert, Ronny Engelmann, Fabiola Ramelli, Zamin A. Kanji, Ulrike Lohmann, and Jan Henneberger
Atmos. Chem. Phys., 22, 9767–9797, https://doi.org/10.5194/acp-22-9767-2022, https://doi.org/10.5194/acp-22-9767-2022, 2022
Short summary
Short summary
Ice formation and its evolution in mixed-phase clouds are still uncertain. We evaluate the lidar retrieval of ice-nucleating particle concentration in dust-dominated and continental air masses over the Swiss Alps with in situ observations. A calibration factor to improve the retrieval from continental air masses is proposed. Ice multiplication factors are obtained with a new method utilizing remote sensing. Our results indicate that secondary ice production occurs at temperatures down to −30 °C.
Ulrike Proske, Sylvaine Ferrachat, David Neubauer, Martin Staab, and Ulrike Lohmann
Atmos. Chem. Phys., 22, 4737–4762, https://doi.org/10.5194/acp-22-4737-2022, https://doi.org/10.5194/acp-22-4737-2022, 2022
Short summary
Short summary
Cloud microphysical processes shape cloud properties and are therefore important to represent in climate models. Their parameterization has grown more complex, making the model results more difficult to interpret. Using sensitivity analysis we test how the global aerosol–climate model ECHAM-HAM reacts to changes to these parameterizations. The model is sensitive to the parameterization of ice crystal autoconversion but not to, e.g., self-collection, suggesting that it may be simplified.
Jörg Wieder, Claudia Mignani, Mario Schär, Lucie Roth, Michael Sprenger, Jan Henneberger, Ulrike Lohmann, Cyril Brunner, and Zamin A. Kanji
Atmos. Chem. Phys., 22, 3111–3130, https://doi.org/10.5194/acp-22-3111-2022, https://doi.org/10.5194/acp-22-3111-2022, 2022
Short summary
Short summary
We investigate the variation in ice-nucleating particles (INPs) relevant for primary ice formation in mixed-phased clouds over the Alps based on simultaneous in situ observations at a mountaintop and a nearby high valley (1060 m height difference). In most cases, advection from the surrounding lower regions was responsible for changes in INP concentration, causing a diurnal cycle at the mountaintop. Our study underlines the importance of the planetary boundary layer as an INP reserve.
Zane Dedekind, Annika Lauber, Sylvaine Ferrachat, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 15115–15134, https://doi.org/10.5194/acp-21-15115-2021, https://doi.org/10.5194/acp-21-15115-2021, 2021
Short summary
Short summary
The RACLETS campaign combined cloud and snow research to improve the understanding of precipitation formation in clouds. A numerical weather prediction model, COSMO, was used to assess the importance of ice crystal enhancement by ice–ice collisions for cloud properties. We found that the number of ice crystals increased by 1 to 3 orders of magnitude when ice–ice collisions were permitted to occur, reducing localized regions of high precipitation and, thereby, improving the model performance.
Paolo Pelucchi, David Neubauer, and Ulrike Lohmann
Geosci. Model Dev., 14, 5413–5434, https://doi.org/10.5194/gmd-14-5413-2021, https://doi.org/10.5194/gmd-14-5413-2021, 2021
Short summary
Short summary
Stratocumulus are thin clouds whose cloud cover is underestimated in climate models partly due to overly low vertical resolution. We develop a scheme that locally refines the vertical grid based on a physical constraint for the cloud top. Global simulations show that the scheme, implemented only in the radiation routine, can increase stratocumulus cloud cover. However, this effect is poorly propagated to the simulated cloud cover. The scheme's limitations and possible ways forward are discussed.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Paraskevi Georgakaki, Aikaterini Bougiatioti, Jörg Wieder, Claudia Mignani, Fabiola Ramelli, Zamin A. Kanji, Jan Henneberger, Maxime Hervo, Alexis Berne, Ulrike Lohmann, and Athanasios Nenes
Atmos. Chem. Phys., 21, 10993–11012, https://doi.org/10.5194/acp-21-10993-2021, https://doi.org/10.5194/acp-21-10993-2021, 2021
Short summary
Short summary
Aerosol and cloud observations coupled with a droplet activation parameterization was used to investigate the aerosol–cloud droplet link in alpine mixed-phase clouds. Predicted droplet number, Nd, agrees with observations and never exceeds a characteristic “limiting droplet number”, Ndlim, which depends solely on σw. Nd becomes velocity limited when it is within 50 % of Ndlim. Identifying when dynamical changes control Nd variability is central for understanding aerosol–cloud interactions.
Hyunju Jung, Ann Kristin Naumann, and Bjorn Stevens
Atmos. Chem. Phys., 21, 10337–10345, https://doi.org/10.5194/acp-21-10337-2021, https://doi.org/10.5194/acp-21-10337-2021, 2021
Short summary
Short summary
We analyze the behavior of organized convection in a large-scale flow by imposing a mean flow to idealized simulations. In the mean flow, organized convection initially propagates slower than the mean wind speed and becomes stationary. The initial upstream and downstream difference in surface fluxes becomes symmetric as the surface momentum flux acts as a drag, resulting in the stationarity. Meanwhile, the surface enthalpy flux has a minor role in the propagation of the convection.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Johannes Bühl, Martin Radenz, Patric Seifert, Jörg Wieder, Annika Lauber, Julie T. Pasquier, Ronny Engelmann, Claudia Mignani, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 6681–6706, https://doi.org/10.5194/acp-21-6681-2021, https://doi.org/10.5194/acp-21-6681-2021, 2021
Short summary
Short summary
Orographic mixed-phase clouds are an important source of precipitation, but the ice formation processes within them remain uncertain. Here we investigate the origin of ice crystals in a mixed-phase cloud in the Swiss Alps using aerosol and cloud data from in situ and remote sensing observations. We found that ice formation primarily occurs in cloud top generating cells. Our results indicate that secondary ice processes are active in the feeder region, which can enhance orographic precipitation.
Fabiola Ramelli, Jan Henneberger, Robert O. David, Annika Lauber, Julie T. Pasquier, Jörg Wieder, Johannes Bühl, Patric Seifert, Ronny Engelmann, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 5151–5172, https://doi.org/10.5194/acp-21-5151-2021, https://doi.org/10.5194/acp-21-5151-2021, 2021
Short summary
Short summary
Interactions between dynamics, microphysics and orography can enhance precipitation. Yet the exact role of these interactions is still uncertain. Here we investigate the role of low-level blocking and turbulence for precipitation by combining remote sensing and in situ observations. The observations show that blocked flow can induce the formation of feeder clouds and that turbulence can enhance hydrometeor growth, demonstrating the importance of local flow effects for orographic precipitation.
Ulrike Proske, Verena Bessenbacher, Zane Dedekind, Ulrike Lohmann, and David Neubauer
Atmos. Chem. Phys., 21, 5195–5216, https://doi.org/10.5194/acp-21-5195-2021, https://doi.org/10.5194/acp-21-5195-2021, 2021
Short summary
Short summary
Ice crystals falling out of one cloud can initiate freezing in a second cloud below. We estimate the occurrence frequency of this natural cloud seeding over Switzerland from satellite data and sublimation calculations. We find that such situations with an ice cloud above another cloud are frequent and that the falling crystals survive the fall between two clouds in a significant number of cases, suggesting that natural cloud seeding is an important phenomenon over Switzerland.
Annika Lauber, Jan Henneberger, Claudia Mignani, Fabiola Ramelli, Julie T. Pasquier, Jörg Wieder, Maxime Hervo, and Ulrike Lohmann
Atmos. Chem. Phys., 21, 3855–3870, https://doi.org/10.5194/acp-21-3855-2021, https://doi.org/10.5194/acp-21-3855-2021, 2021
Short summary
Short summary
An accurate prediction of the ice crystal number concentration (ICNC) is important to determine the radiation budget, lifetime, and precipitation formation of clouds. Even though secondary-ice processes can increase the ICNC by several orders of magnitude, they are poorly constrained and lack a well-founded quantification. During measurements on a mountain slope, a high ICNC of small ice crystals was observed just below 0 °C, attributed to a secondary-ice process and parametrized in this study.
Jonas Gliß, Augustin Mortier, Michael Schulz, Elisabeth Andrews, Yves Balkanski, Susanne E. Bauer, Anna M. K. Benedictow, Huisheng Bian, Ramiro Checa-Garcia, Mian Chin, Paul Ginoux, Jan J. Griesfeller, Andreas Heckel, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Paolo Laj, Philippe Le Sager, Marianne Tronstad Lund, Cathrine Lund Myhre, Hitoshi Matsui, Gunnar Myhre, David Neubauer, Twan van Noije, Peter North, Dirk J. L. Olivié, Samuel Rémy, Larisa Sogacheva, Toshihiko Takemura, Kostas Tsigaridis, and Svetlana G. Tsyro
Atmos. Chem. Phys., 21, 87–128, https://doi.org/10.5194/acp-21-87-2021, https://doi.org/10.5194/acp-21-87-2021, 2021
Short summary
Short summary
Simulated aerosol optical properties as well as the aerosol life cycle are investigated for 14 global models participating in the AeroCom initiative. Considerable diversity is found in the simulated aerosol species emissions and lifetimes, also resulting in a large diversity in the simulated aerosol mass, composition, and optical properties. A comparison with observations suggests that, on average, current models underestimate the direct effect of aerosol on the atmosphere radiation budget.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
Short summary
Short summary
A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Augustin Mortier, Jonas Gliß, Michael Schulz, Wenche Aas, Elisabeth Andrews, Huisheng Bian, Mian Chin, Paul Ginoux, Jenny Hand, Brent Holben, Hua Zhang, Zak Kipling, Alf Kirkevåg, Paolo Laj, Thibault Lurton, Gunnar Myhre, David Neubauer, Dirk Olivié, Knut von Salzen, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 20, 13355–13378, https://doi.org/10.5194/acp-20-13355-2020, https://doi.org/10.5194/acp-20-13355-2020, 2020
Short summary
Short summary
We present a multiparameter analysis of the aerosol trends over the last 2 decades in the different regions of the world. In most of the regions, ground-based observations show a decrease in aerosol content in both the total atmospheric column and at the surface. The use of climate models, assessed against these observations, reveals however an increase in the total aerosol load, which is not seen with the sole use of observation due to partial coverage in space and time.
Cited articles
Ahlgrimm, M., Forbes, R. M., Hogan, R. J., and Sandu, I.: Understanding Global Model Systematic Shortwave Radiation Errors in Subtropical Marine Boundary Layer Cloud Regimes, J. Adv. Model. Earth Sy., 10, 2042–2060, https://doi.org/10.1029/2018MS001346, 2018. a
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. a, b, c
Allen, G., Coe, H., Clarke, A., Bretherton, C., Wood, R., Abel, S. J., Barrett, P., Brown, P., George, R., Freitag, S., McNaughton, C., Howell, S., Shank, L., Kapustin, V., Brekhovskikh, V., Kleinman, L., Lee, Y.-N., Springston, S., Toniazzo, T., Krejci, R., Fochesatto, J., Shaw, G., Krecl, P., Brooks, B., McMeeking, G., Bower, K. N., Williams, P. I., Crosier, J., Crawford, I., Connolly, P., Allan, J. D., Covert, D., Bandy, A. R., Russell, L. M., Trembath, J., Bart, M., McQuaid, J. B., Wang, J., and Chand, D.: South East Pacific atmospheric composition and variability sampled along 20° S during VOCALS-REx, Atmos. Chem. Phys., 11, 5237–5262, https://doi.org/10.5194/acp-11-5237-2011, 2011. a
Amazon Web Services: noaa-goes16, AWS S3 Explorer, Amazon Web Services [data set], https://noaa-goes16.s3.amazonaws.com/index.html, last access: 1 August 2024a. a
Amazon Web Services: noaa-goes17, AWS S3 Explorer, Amazon Web Services [data set], https://noaa-goes17.s3.amazonaws.com/index.html, last access: 1 August 2024b. a
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. a
Arola, A., Lipponen, A., Kolmonen, P., Virtanen, T. H., Bellouin, N., Grosvenor, D. P., Gryspeerdt, E., Quaas, J., and Kokkola, H.: Aerosol Effects on Clouds Are Concealed by Natural Cloud Heterogeneity and Satellite Retrieval Errors, Nat. Commun., 13, 7357, https://doi.org/10.1038/s41467-022-34948-5, 2022. a
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A.-L., Dufresne, J.-L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D. T., Myhre, G., Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.: Bounding Global Aerosol Radiative Forcing of Climate Change, Rev. Geophys., 58, e2019RG000660, https://doi.org/10.1029/2019RG000660, 2020. a
Benas, N., Solodovnik, I., Stengel, M., Hüser, I., Karlsson, K.-G., Håkansson, N., Johansson, E., Eliasson, S., Schröder, M., Hollmann, R., and Meirink, J. F.: CLAAS-3: the third edition of the CM SAF cloud data record based on SEVIRI observations, Earth Syst. Sci. Data, 15, 5153–5170, https://doi.org/10.5194/essd-15-5153-2023, 2023 (data available at: https://wui.cmsaf.eu/safira, last access: 30 July 2024). a, b, c, d
Bogenschutz, P. A., Lee, H.-H., Tang, Q., and Yamaguchi, T.: Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1, Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, 2023. a
Brenguier, J.-L., Pawlowska, H., Schüller, L., Preusker, R., Fischer, J., and Fouquart, Y.: Radiative Properties of Boundary Layer Clouds: Droplet Effective Radius versus Number Concentration, J. Atmos. Sci., 57, 803–821, https://doi.org/10.1175/1520-0469(2000)057<0803:RPOBLC>2.0.CO;2, 2000. a
Bretherton, C. S., Blossey, P. N., and 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. a
Chen, Y., Haywood, J., Wang, Y., Malavelle, F., Jordan, G., Partridge, D., Fieldsend, J., De Leeuw, J., Schmidt, A., Cho, N., Oreopoulos, L., Platnick, S., Grosvenor, D., Field, P., and Lohmann, U.: Machine Learning Reveals Climate Forcing from Aerosols Is Dominated by Increased Cloud Cover, Nat. Geosci., 15, 609–614, https://doi.org/10.1038/s41561-022-00991-6, 2022. a
Chen, Y., Haywood, J., Wang, Y., Malavelle, F., Jordan, G., Peace, A., Partridge, D. G., Cho, N., Oreopoulos, L., Grosvenor, D., Field, P., Allan, R. P., and Lohmann, U.: Substantial Cooling Effect from Aerosol-Induced Increase in Tropical Marine Cloud Cover, Nat. Geosci., 17, 404–410, https://doi.org/10.1038/s41561-024-01427-z, 2024. a
Christensen, M., Jones, W. K., and Stier, P.: Aerosols Enhance Cloud Lifetime and Brightness along the Stratus-to-Cumulus Transition, P. Natl. Acad. Sci. USA, 117, 17591–17598, https://doi.org/10.1073/pnas.1921231117, 2020. a, b
Christensen, M. W. and Stephens, G. L.: Microphysical and Macrophysical Responses of Marine Stratocumulus Polluted by Underlying Ships: Evidence of Cloud Deepening, J. Geophys. Res.-Atmos., 116, D03201, https://doi.org/10.1029/2010JD014638, 2011. a, b
Christensen, M. W., Gettelman, A., Cermak, J., Dagan, G., Diamond, M., Douglas, A., Feingold, G., Glassmeier, F., Goren, T., Grosvenor, D. P., Gryspeerdt, E., Kahn, R., Li, Z., Ma, P.-L., Malavelle, F., McCoy, I. L., McCoy, D. T., McFarquhar, G., Mülmenstädt, J., Pal, S., Possner, A., Povey, A., Quaas, J., Rosenfeld, D., Schmidt, A., Schrödner, R., Sorooshian, A., Stier, P., Toll, V., Watson-Parris, D., Wood, R., Yang, M., and Yuan, T.: Opportunistic experiments to constrain aerosol effective radiative forcing, Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, 2022. a
Dagan, G., Yeheskel, N., and Williams, A. I. L.: Radiative Forcing from Aerosol–Cloud Interactions Enhanced by Large-Scale Circulation Adjustments, Nat. Geosci., 16, 1092–1098, https://doi.org/10.1038/s41561-023-01319-8, 2023. a
Dipankar, A., Stevens, B., Heinze, R., Moseley, C., Zängl, G., Giorgetta, M., and Brdar, S.: Large Eddy Simulation Using the General Circulation Model ICON, J. Adv. Model. Earth Sy., 7, 963–986, https://doi.org/10.1002/2015MS000431, 2015. a
Douglas, A. and L'Ecuyer, T.: Global evidence of aerosol-induced invigoration in marine cumulus clouds, Atmos. Chem. Phys., 21, 15103–15114, https://doi.org/10.5194/acp-21-15103-2021, 2021. a, b
Fons, E., Ferrachat, S., Naumann, A. K., Neubauer, D., Lang, T., and Lohmann, U.: Software for paper “Investigating the sign of stratocumulus adjustments to aerosols in the global storm-resolving model ICON” (1.0), Zenodo [code], https://doi.org/10.5281/zenodo.10580242, 2024a. a
Fons, E., Ferrachat, S., Naumann, A. K., Neubauer, D., Lang, T., and Lohmann, U.: Data for paper “Investigating the sign of stratocumulus adjustments to aerosols in the global storm-resolving model ICON”, Zenodo [data set], https://doi.org/10.5281/zenodo.10580438, 2024b. a
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame, D., Lunt, D., Mauritsen, T., Palmer, M., Watanabe, M., Wild, M., and Zhang, H.: The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 923–1054, https://doi.org/10.1017/9781009157896.009, 2021. a, b
Glassmeier, F., Hoffmann, F., Johnson, J. S., Yamaguchi, T., Carslaw, K. S., and Feingold, G.: An emulator approach to stratocumulus susceptibility, Atmos. Chem. Phys., 19, 10191–10203, https://doi.org/10.5194/acp-19-10191-2019, 2019. a, b
Grandey, B. S., Gururaj, A., Stier, P., and Wagner, T. M.: Rainfall-Aerosol Relationships Explained by Wet Scavenging and Humidity, Geophys. Res. Lett., 41, 5678–5684, https://doi.org/10.1002/2014GL060958, 2014. a, b, c
Gryspeerdt, E., Quaas, J., and Bellouin, N.: Constraining the Aerosol Influence on Cloud Fraction, J. Geophys. Res.-Atmos., 121, 3566–3583, https://doi.org/10.1002/2015JD023744, 2016. a
Gryspeerdt, E., Goren, T., Sourdeval, O., Quaas, J., Mülmenstädt, J., Dipu, S., Unglaub, C., Gettelman, A., and Christensen, M.: Constraining the aerosol influence on cloud liquid water path, Atmos. Chem. Phys., 19, 5331–5347, https://doi.org/10.5194/acp-19-5331-2019, 2019. a
Heim, C., Hentgen, L., Ban, N., and Schär, C.: Inter-model Variability in Convection-Resolving Simulations of Subtropical Marine Low Clouds, J. Meteorol. Soc. Jpn. Ser. II, 99, 1271–1295, https://doi.org/10.2151/jmsj.2021-062, 2021. a, b, c
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 Thébaut, J.-N.: ERA5 Hourly Data on Pressure Levels from 1959 to Present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2018a. a, b, c
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 Thébaut, J.-N.: ERA5 Hourly Data on Single Levels from 1959 to Present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018b. a, b, c
Hill, A. A., Feingold, G., and Jiang, H.: The Influence of Entrainment and Mixing Assumption on Aerosol–Cloud Interactions in Marine Stratocumulus, J. Atmos. Sci., 66, 1450–1464, https://doi.org/10.1175/2008JAS2909.1, 2009. a, b
Hohenegger, C., Korn, P., Linardakis, L., Redler, R., Schnur, R., Adamidis, P., Bao, J., Bastin, S., Behravesh, M., Bergemann, M., Biercamp, J., Bockelmann, H., Brokopf, R., Brüggemann, N., Casaroli, L., Chegini, F., Datseris, G., Esch, M., George, G., Giorgetta, M., Gutjahr, O., Haak, H., Hanke, M., Ilyina, T., Jahns, T., Jungclaus, J., Kern, M., Klocke, D., Kluft, L., Kölling, T., Kornblueh, L., Kosukhin, S., Kroll, C., Lee, J., Mauritsen, T., Mehlmann, C., Mieslinger, T., Naumann, A. K., Paccini, L., Peinado, A., Praturi, D. S., Putrasahan, D., Rast, S., Riddick, T., Roeber, N., Schmidt, H., Schulzweida, U., Schütte, F., Segura, H., Shevchenko, R., Singh, V., Specht, M., Stephan, C. C., von Storch, J.-S., Vogel, R., Wengel, C., Winkler, M., Ziemen, F., Marotzke, J., and Stevens, B.: ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales, Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, 2023. a, b, c
Howes, C., Saide, P. E., Coe, H., Dobracki, A., Freitag, S., Haywood, J. M., Howell, S. G., Gupta, S., Uin, J., Kacarab, M., Kuang, C., Leung, L. R., Nenes, A., McFarquhar, G. M., Podolske, J., Redemann, J., Sedlacek, A. J., Thornhill, K. L., Wong, J. P. S., Wood, R., Wu, H., Zhang, Y., Zhang, J., and Zuidema, P.: Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns, Atmos. Chem. Phys., 23, 13911–13940, https://doi.org/10.5194/acp-23-13911-2023, 2023. a
Huffman, G., Stocker, E., Bolvin, D., Nelkin, E., and Tan, J.: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/IMERG/3B-HH/07, 2023. a, b, c
Jiang, H., Xue, H., Teller, A., Feingold, G., and Levin, Z.: Aerosol Effects on the Lifetime of Shallow Cumulus, Geophys. Res. Lett., 33, L14806, https://doi.org/10.1029/2006GL026024, 2006. a, b
Judt, F., Klocke, D., Rios-Berrios, R., Vanniere, B., Ziemen, F., Auger, L., Biercamp, J., Bretherton, C., Chen, X., Düben, P., Hohenegger, C., Khairoutdinov, M., Kodama, C., Kornblueh, L., Lin, S.-J., Nakano, M., Neumann, P., Putman, W., Röber, N., Roberts, M., Satoh, M., Shibuya, R., Stevens, B., Vidale, P. L., Wedi, N., and Zhou, L.: Tropical Cyclones in Global Storm-Resolving Models, J. Meteorol. Soc. Jpn. Ser. II, 99, 579–602, https://doi.org/10.2151/jmsj.2021-029, 2021. a
Kalmus, P., Wong, S., and Teixeira, J.: The Pacific Subtropical Cloud Transition: A MAGIC Assessment of AIRS and ECMWF Thermodynamic Structure, IEEE Geosci. Remote S., 12, 1586–1590, https://doi.org/10.1109/LGRS.2015.2413771, 2015. a
Karset, I. H. H., Gettelman, A., Storelvmo, T., Alterskjær, K., and Berntsen, T. K.: Exploring Impacts of Size-Dependent Evaporation and Entrainment in a Global Model, J. Geophys. Res.-Atmos., 125, e2019JD031817, https://doi.org/10.1029/2019JD031817, 2020. a
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. a
Köhler, M., Ahlgrimm, M., and Beljaars, A.: Unified Treatment of Dry Convective and Stratocumulus-Topped Boundary Layers in the ECMWF Model, Q. J. Roy. Meteor. Soc., 137, 43–57, https://doi.org/10.1002/qj.713, 2011. a
Lang, T., Naumann, A. K., Buehler, S. A., Stevens, B., Schmidt, H., and Aemisegger, F.: Sources of Uncertainty in Mid-Tropospheric Tropical Humidity in Global Storm-Resolving Simulations, J. Adv. Model. Earth Sy., 15, e2022MS003443, https://doi.org/10.1029/2022MS003443, 2023. a, b
Lee, J., Hohenegger, C., Chlond, A., and Schnur, R.: The Climatic Role of Interactive Leaf Phenology in the Vegetation-Atmosphere System of Radiative-Convective Equilibrium Storm-Resolving Simulations, Tellus B, 74, 164–175, https://doi.org/10.16993/tellusb.26, 2022. a
Lilly, D. K.: On the Numerical Simulation of Buoyant Convection, Tellus, 14, 148–172, https://doi.org/10.1111/j.2153-3490.1962.tb00128.x, 1962. a
Lohmann, U., Lüönd, F., and Mahrt, F.: Microphysical Processes in Warm Clouds, in: An Introduction to Clouds: From the Microscale to Climate, Cambridge University Press, Cambridge, 186–217, https://doi.org/10.1017/CBO9781139087513, 2016. a, b
Lu, M.-L. and Seinfeld, J. H.: Study of the Aerosol Indirect Effect by Large-Eddy Simulation of Marine Stratocumulus, J. Atmos. Sci., 62, 3909–3932, https://doi.org/10.1175/JAS3584.1, 2005. a, b
Malavelle, F. F., Haywood, J. M., Jones, A., Gettelman, A., Clarisse, L., Bauduin, S., Allan, R. P., Karset, I. H. H., Kristjánsson, J. E., Oreopoulos, L., Cho, N., Lee, D., Bellouin, N., Boucher, O., Grosvenor, D. P., Carslaw, K. S., Dhomse, S., Mann, G. W., Schmidt, A., Coe, H., Hartley, M. E., Dalvi, M., Hill, A. A., Johnson, B. T., Johnson, C. E., Knight, J. R., O'Connor, F. M., Partridge, D. G., Stier, P., Myhre, G., Platnick, S., Stephens, G. L., Takahashi, H., and Thordarson, T.: Strong Constraints on Aerosol-Cloud Interactions from Volcanic Eruptions, Nature, 546, 485–491, https://doi.org/10.1038/nature22974, 2017. a
Manshausen, P., Watson-Parris, D., Christensen, M. W., Jalkanen, J.-P., and Stier, P.: Invisible Ship Tracks Show Large Cloud Sensitivity to Aerosol, Nature, 610, 101–106, https://doi.org/10.1038/s41586-022-05122-0, 2022. a
Mauger, G. S. and Norris, J. R.: Meteorological Bias in Satellite Estimates of Aerosol-Cloud Relationships, Geophys. Res. Lett., 34, L16824, https://doi.org/10.1029/2007GL029952, 2007. a
McCoy, D. T., Field, P., Gordon, H., Elsaesser, G. S., and Grosvenor, D. P.: Untangling causality in midlatitude aerosol–cloud adjustments, Atmos. Chem. Phys., 20, 4085–4103, https://doi.org/10.5194/acp-20-4085-2020, 2020. a, b
McCoy, I. L., McCoy, D. T., Wood, R., Zuidema, P., and Bender, F. A.-M.: The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback, Geophys. Res. Lett., 50, e2022GL101042, https://doi.org/10.1029/2022GL101042, 2023. a
Met Office: Cartopy: a cartographic python library with a Matplotlib interface, Exeter, Devon, https://scitools.org.uk/cartopy (last access: 25 July 2024), 2010–2015. a
Michibata, T., Suzuki, K., Sato, Y., and Takemura, T.: The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals, Atmos. Chem. Phys., 16, 15413–15424, https://doi.org/10.5194/acp-16-15413-2016, 2016. a
Neubauer, D., Christensen, M. W., Poulsen, C. A., and Lohmann, U.: Unveiling aerosol–cloud interactions – Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data, Atmos. Chem. Phys., 17, 13165–13185, https://doi.org/10.5194/acp-17-13165-2017, 2017. a
Nowack, P., Runge, J., Eyring, V., and Haigh, J. D.: Causal Networks for Climate Model Evaluation and Constrained Projections, Nat. Commun., 11, 1415, https://doi.org/10.1038/s41467-020-15195-y, 2020. a
Nugent, J. M., Turbeville, S. M., Bretherton, C. S., Blossey, P. N., and Ackerman, T. P.: Tropical Cirrus in Global Storm-Resolving Models: 1. Role of Deep Convection, Earth and Space Science, 9, e2021EA001965, https://doi.org/10.1029/2021EA001965, 2022. a
Pearl, J.: Causality: Models, Reasoning, and Inference, 2nd edn., Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9780511803161, 2009. a, b
Pincus, R., Mlawer, E. J., and Delamere, J. S.: Balancing Accuracy, Efficiency, and Flexibility in Radiation Calculations for Dynamical Models, J. Adv. Model. Earth Sy., 11, 3074–3089, https://doi.org/10.1029/2019MS001621, 2019. a
Platnick, S., King, M., and Hubanks, P.: MODIS Atmosphere L3 Daily Product, NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA [data set], https://doi.org/10.5067/MODIS/MOD08_D3.006, 2015. a, b
Possner, A., Zubler, E., Fuhrer, O., Lohmann, U., and Schär, C.: A Case Study in Modeling Low-Lying Inversions and Stratocumulus Cloud Cover in the Bay of Biscay, Weather Forecast., 29, 289–304, https://doi.org/10.1175/WAF-D-13-00039.1, 2014. a
Possner, A., Eastman, R., Bender, F., and Glassmeier, F.: Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks, Atmos. Chem. Phys., 20, 3609–3621, https://doi.org/10.5194/acp-20-3609-2020, 2020. a
Quaas, J., Boucher, O., and Lohmann, U.: Constraining the total aerosol indirect effect in the LMDZ and ECHAM4 GCMs using MODIS satellite data, Atmos. Chem. Phys., 6, 947–955, https://doi.org/10.5194/acp-6-947-2006, 2006. a
Quaas, J., Ming, Y., Menon, S., Takemura, T., Wang, M., Penner, J. E., Gettelman, A., Lohmann, U., Bellouin, N., Boucher, O., Sayer, A. M., Thomas, G. E., McComiskey, A., Feingold, G., Hoose, C., Kristjánsson, J. E., Liu, X., Balkanski, Y., Donner, L. J., Ginoux, P. A., Stier, P., Grandey, B., Feichter, J., Sednev, I., Bauer, S. E., Koch, D., Grainger, R. G., Kirkevåg, A., Iversen, T., Seland, Ø., Easter, R., Ghan, S. J., Rasch, P. J., Morrison, H., Lamarque, J.-F., Iacono, M. J., Kinne, S., and Schulz, M.: Aerosol indirect effects – general circulation model intercomparison and evaluation with satellite data, Atmos. Chem. Phys., 9, 8697–8717, https://doi.org/10.5194/acp-9-8697-2009, 2009. a
Raddatz, T. J., Reick, C. H., Knorr, W., Kattge, J., Roeckner, E., Schnur, R., Schnitzler, K.-G., Wetzel, P., and Jungclaus, J.: Will the Tropical Land Biosphere Dominate the Climate–Carbon Cycle Feedback during the Twenty-First Century?, Clim. Dynam., 29, 565–574, https://doi.org/10.1007/s00382-007-0247-8, 2007. a
Redemann, J., Wood, R., Zuidema, P., Doherty, S. J., Luna, B., LeBlanc, S. E., Diamond, M. S., Shinozuka, Y., Chang, I. Y., Ueyama, R., Pfister, L., Ryoo, J.-M., Dobracki, A. N., da Silva, A. M., Longo, K. M., Kacenelenbogen, M. S., Flynn, C. J., Pistone, K., Knox, N. M., Piketh, S. J., Haywood, J. M., Formenti, P., Mallet, M., Stier, P., Ackerman, A. S., Bauer, S. E., Fridlind, A. M., Carmichael, G. R., Saide, P. E., Ferrada, G. A., Howell, S. G., Freitag, S., Cairns, B., Holben, B. N., Knobelspiesse, K. D., Tanelli, S., L'Ecuyer, T. S., Dzambo, A. M., Sy, O. O., McFarquhar, G. M., Poellot, M. R., Gupta, S., O'Brien, J. R., Nenes, A., Kacarab, M., Wong, J. P. S., Small-Griswold, J. D., Thornhill, K. L., Noone, D., Podolske, J. R., Schmidt, K. S., Pilewskie, P., Chen, H., Cochrane, S. P., Sedlacek, A. J., Lang, T. J., Stith, E., Segal-Rozenhaimer, M., Ferrare, R. A., Burton, S. P., Hostetler, C. A., Diner, D. J., Seidel, F. C., Platnick, S. E., Myers, J. S., Meyer, K. G., Spangenberg, D. A., Maring, H., and Gao, L.: An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin, Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, 2021. a
Roberts, G. C., Day, D. A., Russell, L. M., Dunlea, E. J., Jimenez, J. L., Tomlinson, J. M., Collins, D. R., Shinozuka, Y., and Clarke, A. D.: Characterization of particle cloud droplet activity and composition in the free troposphere and the boundary layer during INTEX-B, Atmos. Chem. Phys., 10, 6627–6644, https://doi.org/10.5194/acp-10-6627-2010, 2010. a
Rosenfeld, D., Zhu, Y., Wang, M., Zheng, Y., Goren, T., and Yu, S.: Aerosol-Driven Droplet Concentrations Dominate Coverage and Water of Oceanic Low-Level Clouds, Science, 363, eaav0566, https://doi.org/10.1126/science.aav0566, 2019. a
Runge, J.: Causal Network Reconstruction from Time Series: From Theoretical Assumptions to Practical Estimation, Chaos, 28, 075310, https://doi.org/10.1063/1.5025050, 2018. a, b, c
Runge, J.: Necessary and Sufficient Graphical Conditions for Optimal Adjustment Sets in Causal Graphical Models with Hidden Variables, in: Advances in Neural Information Processing Systems, vol. 34, edited by: Ranzato, M., Beygelzimer, A., Dauphin, Y., Liang, P., and Vaughan, J. W., Curran Associates, Inc., 15762–15773, ISBN 978-171384539-3, 2021. a
Runge, J., Petoukhov, V., Donges, J. F., Hlinka, J., Jajcay, N., Vejmelka, M., Hartman, D., Marwan, N., Paluš, M., and Kurths, J.: Identifying Causal Gateways and Mediators in Complex Spatio-Temporal Systems, Nat. Commun., 6, 8502, https://doi.org/10.1038/ncomms9502, 2015. a
Runge, J., Gerhardus, A., Varando, G., Eyring, V., and Camps-Valls, G.: Causal Inference for Time Series, Nature Reviews Earth & Environment, 4, 487–505, https://doi.org/10.1038/s43017-023-00431-y, 2023. a, b
Salzmann, M., Ferrachat, S., Tully, C., Münch, S., Watson-Parris, D., Neubauer, D., Siegenthaler-Le Drian, C., Rast, S., Heinold, B., Crueger, T., Brokopf, R., Mülmenstädt, J., Quaas, J., Wan, H., Zhang, K., Lohmann, U., Stier, P., and Tegen, I.: The Global Atmosphere-aerosol Model ICON-A-HAM2.3–Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness, J. Adv. Model. Earth Sy., 14, e2021MS002699, https://doi.org/10.1029/2021MS002699, 2022. a
Sandu, I., Brenguier, J.-L., Geoffroy, O., Thouron, O., and Masson, V.: Aerosol Impacts on the Diurnal Cycle of Marine Stratocumulus, J. Atmos. Sci., 65, 2705–2718, https://doi.org/10.1175/2008JAS2451.1, 2008. a
Satoh, M., Stevens, B., Judt, F., Khairoutdinov, M., Lin, S.-J., Putman, W. M., and Düben, P.: Global Cloud-Resolving Models, Current Climate Change Reports, 5, 172–184, https://doi.org/10.1007/s40641-019-00131-0, 2019. a
Segal, Y. and Kain, A.: Dependence of Droplet Concentration on Aerosol Conditions in Different Cloud Types: Application to Droplet Concentration Parameterization of Aerosol Conditions, J. Geophys. Res.-Atmos., 111, D15204, https://doi.org/10.1029/2005JD006561, 2006. a, b
Seifert, A. and Beheng, K. D.: A Two-Moment Cloud Microphysics Parameterization for Mixed-Phase Clouds. Part 1: Model Description, Meteorol. Atmos. Phys., 92, 45–66, https://doi.org/10.1007/s00703-005-0112-4, 2006. a, b, c, d
Shi, X., Hagen, H. L., Chow, F. K., Bryan, G. H., and Street, R. L.: Large-Eddy Simulation of the Stratocumulus-Capped Boundary Layer with Explicit Filtering and Reconstruction Turbulence Modeling, J. Atmos. Sci., 75, 611–637, https://doi.org/10.1175/JAS-D-17-0162.1, 2018. a
Smagorinsky, J.: General Circulation Experiments with the Primitive Equations: I. The Basic Experiment, Mon. Weather Rev., 91, 99–164, https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. a
Stevens, B. and Seifert, A.: Understanding Macrophysical Outcomes of Microphysical Choices in Simulations of Shallow Cumulus Convection, J. Meteorol. Soc. Jpn. Ser. II, 86A, 143–162, https://doi.org/10.2151/jmsj.86A.143, 2008. a
Stevens, B., Satoh, M., Auger, L., Biercamp, J., Bretherton, C. S., Chen, X., Düben, P., Judt, F., Khairoutdinov, M., Klocke, D., Kodama, C., Kornblueh, L., Lin, S.-J., Neumann, P., Putman, W. M., Röber, N., Shibuya, R., Vanniere, B., Vidale, P. L., Wedi, N., and Zhou, L.: DYAMOND: The DYnamics of the Atmospheric General Circulation Modeled On Non-hydrostatic Domains, Progress in Earth and Planetary Science, 6, 61, https://doi.org/10.1186/s40645-019-0304-z, 2019. a
Stevens, B., Acquistaoace, C., Hansen, A., Heinze, R., Klinger, C., Klocke, D., Rybka, H., Schubotz, W., Windmiller, J., Adamidis, P., Arka, I., Barlakas, V., Biercamp, J., Brueck, M., Brune, S., Buehler, S. A., Burkhardt, U., Cioni, G., Costa-Suros, M., Crewell, S., Crüger, T., Deneke, H., Friedrichs, P., Henken, C. C., Hohenegger, C., Jacob, M., Jakub, F., Kalthoff, N., Köhler, M., van Laar, T. W., Li, P., Löhnert, U., Macke, A., Madenach, N., Mayer, B., Nam, C., Naumann, A. K., Peters, K., Poll, S., Quaas, J., Röber, N., Rochetin, N., Scheck, L., Schemann, V., Schnitt, S., Seifert, A., Senf, F., Shapkalijevski, M., Simmer, C., Singh, S., Sourdeval, O., Spickermann, D., Strandgren, J., Tessiot, O., Vercauteren, N., Vial, J., Voigt, A., and Zängl, G.: The Added Value of Large-Eddy and Storm-Resolving Models for Simulating Clouds and Precipitation, J. Meteorol. Soc. Jpn., 98, 395, https://doi.org/10.2151/jmsj.2020-021, 2020. a
Stier, P.: Limitations of passive remote sensing to constrain global cloud condensation nuclei, Atmos. Chem. Phys., 16, 6595–6607, https://doi.org/10.5194/acp-16-6595-2016, 2016. a
Stier, P., Feichter, J., Kinne, S., Kloster, S., Vignati, E., Wilson, J., Ganzeveld, L., Tegen, I., Werner, M., Balkanski, Y., Schulz, M., Boucher, O., Minikin, A., and Petzold, A.: The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 5, 1125–1156, https://doi.org/10.5194/acp-5-1125-2005, 2005. a
Stull, R. B. (Ed.): An Introduction to Boundary Layer Meteorology, Springer Netherlands, Dordrecht, https://doi.org/10.1007/978-94-009-3027-8, 1988. a, b
Terai, C. R. and Wood, R.: Aircraft observations of cold pools under marine stratocumulus, Atmos. Chem. Phys., 13, 9899–9914, https://doi.org/10.5194/acp-13-9899-2013, 2013. a
Toll, V., Christensen, M., Gassó, S., and Bellouin, N.: Volcano and Ship Tracks Indicate Excessive Aerosol-Induced Cloud Water Increases in a Climate Model, Geophys. Res. Lett., 44, 492–500, https://doi.org/10.1002/2017GL075280, 2017. a, b
Toll, V., Christensen, M., Quaas, J., and Bellouin, N.: Weak Average Liquid-Cloud-Water Response to Anthropogenic Aerosols, Nature, 572, 51–55, https://doi.org/10.1038/s41586-019-1423-9, 2019. a
Twomey, S.: The Influence of Pollution on the Shortwave Albedo of Clouds, J. Atmos. Sci., 34, 1149–1152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2, 1977. a
Varble, A.: Erroneous Attribution of Deep Convective Invigoration to Aerosol Concentration, J. Atmos. Sci., 75, 1351–1368, https://doi.org/10.1175/JAS-D-17-0217.1, 2018. a
Vogel, R., Nuijens, L., and Stevens, B.: The Role of Precipitation and Spatial Organization in the Response of Trade-Wind Clouds to Warming, J. Adv. Model. Earth Sy., 8, 843–862, https://doi.org/10.1002/2015MS000568, 2016. a, b
Wall, C. J., Norris, J. R., Possner, A., McCoy, D. T., McCoy, I. L., and Lutsko, N. J.: Assessing Effective Radiative Forcing from Aerosol–Cloud Interactions over the Global Ocean, P. Natl. Acad. Sci. USA, 119, e2210481119, https://doi.org/10.1073/pnas.2210481119, 2022. a, b
Walther, A. and Straka, W.: Algorithm Theoretical Basis Document For Daytime Cloud Optical and Microphysical Properties (DCOMP), NOAA NESDIS Center for Satellite Applications and Research, https://www.star.nesdis.noaa.gov/goesr/documents/ATBDs/Enterprise/ATBD_Enterprise_Daytime_Cloud_Optical_and_Microphysical_Properties(DCOMP)_v1.2_2020-10-09.pdf (last access: 25 July 2024), 2020. a, b, c, d
Wang, H., Rasch, P. J., and Feingold, G.: Manipulating marine stratocumulus cloud amount and albedo: a process-modelling study of aerosol-cloud-precipitation interactions in response to injection of cloud condensation nuclei, Atmos. Chem. Phys., 11, 4237–4249, https://doi.org/10.5194/acp-11-4237-2011, 2011. a
Wang, J., Wood, R., Jensen, M. P., Chiu, J. C., Liu, Y., Lamer, K., Desai, N., Giangrande, S. E., Knopf, D. A., Kollias, P., Laskin, A., Liu, X., Lu, C., Mechem, D., Mei, F., Starzec, M., Tomlinson, J., Wang, Y., Yum, S. S., Zheng, G., Aiken, A. C., Azevedo, E. B., Blanchard, Y., China, S., Dong, X., Gallo, F., Gao, S., Ghate, V. P., Glienke, S., Goldberger, L., Hardin, J. C., Kuang, C., Luke, E. P., Matthews, A. A., Miller, M. A., Moffet, R., Pekour, M., Schmid, B., Sedlacek, A. J., Shaw, R. A., Shilling, J. E., Sullivan, A., Suski, K., Veghte, D. P., Weber, R., Wyant, M., Yeom, J., Zawadowicz, M., and Zhang, Z.: Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), B. Am. Meteorol. Soc., 103, E619–E641, https://doi.org/10.1175/BAMS-D-19-0220.1, 2022. a
Wang, M., Ghan, S., Liu, X., L'Ecuyer, T. S., Zhang, K., Morrison, H., Ovchinnikov, M., Easter, R., Marchand, R., Chand, D., Qian, Y., and Penner, J. E.: Constraining cloud lifetime effects of aerosols using A-Train satellite observations, Geophys. Res. Lett., 39, L15709, https://doi.org/10.1029/2012GL052204, 2012. a
Wang, S., Wang, Q., and Feingold, G.: Turbulence, Condensation, and Liquid Water Transport in Numerically Simulated Nonprecipitating Stratocumulus Clouds, J. Atmos. Sci., 60, 262–278, https://doi.org/10.1175/1520-0469(2003)060<0262:TCALWT>2.0.CO;2, 2003. a
Wood, R.: Cancellation of Aerosol Indirect Effects in Marine Stratocumulus through Cloud Thinning, J. Atmos. Sci., 64, 2657–2669, https://doi.org/10.1175/JAS3942.1, 2007. a, b, c
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. a, b
Wood, R. and Hartmann, D. L.: Spatial Variability of Liquid Water Path in Marine Low Cloud: The Importance of Mesoscale Cellular Convection, J. Climate, 19, 1748–1764, https://doi.org/10.1175/JCLI3702.1, 2006. a, b
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON (ICOsahedral Non-hydrostatic) Modelling Framework of DWD and MPI-M: Description of the Non-Hydrostatic Dynamical Core, Q. J. Roy. Meteor. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a, b
Zhang, J., Chen, Y.-S., Yamaguchi, T., and Feingold, G.: Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-1021, 2024. a
Zheng, Q. and Miller, M. A.: Summertime Marine Boundary Layer Cloud, Thermodynamic, and Drizzle Morphology over the Eastern North Atlantic: A Four-Year Study, J. Climate, 35, 4805–4825, https://doi.org/10.1175/JCLI-D-21-0568.1, 2022. a
Zhu, Z., Kollias, P., Luke, E., and Yang, F.: New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra, Atmos. Chem. Phys., 22, 7405–7416, https://doi.org/10.5194/acp-22-7405-2022, 2022. a, b
Short summary
Aerosols can modify the liquid water path (LWP) of stratocumulus and, thus, their radiative effect. We compare storm-resolving model and satellite data that disagree on the sign of LWP adjustments and diagnose this discrepancy with causal inference. We find that strong precipitation, the absence of wet scavenging, and cloud deepening under a weak inversion contribute to positive LWP adjustments to aerosols in the model, despite weak negative effects from cloud-top entrainment enhancement.
Aerosols can modify the liquid water path (LWP) of stratocumulus and, thus, their radiative...
Altmetrics
Final-revised paper
Preprint