Articles | Volume 25, issue 2
https://doi.org/10.5194/acp-25-1353-2025
© Author(s) 2025. 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-25-1353-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 Jan 2025
Research article |
| 31 Jan 2025
| 31 Jan 2025
Evaluation of biases in mid-to-high-latitude surface snowfall and cloud phase in ERA5 and CMIP6 using satellite observations
Franziska Hellmuth
CORRESPONDING AUTHOR
Department of Geosciences, University of Oslo, Blindernveien 31, 0371 Oslo, Norway
Tim Carlsen
Department of Geosciences, University of Oslo, Blindernveien 31, 0371 Oslo, Norway
Anne Sophie Daloz
Center for International Climate Research (CICERO), Gaustadalleen 21, 0349 Oslo, Norway
Robert Oscar David
Department of Geosciences, University of Oslo, Blindernveien 31, 0371 Oslo, Norway
Haochi Che
Department of Geosciences, University of Oslo, Blindernveien 31, 0371 Oslo, Norway
Trude Storelvmo
Department of Geosciences, University of Oslo, Blindernveien 31, 0371 Oslo, Norway
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Atmos. Chem. Phys., 23, 13125–13141, https://doi.org/10.5194/acp-23-13125-2023, https://doi.org/10.5194/acp-23-13125-2023, 2023
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Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
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Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
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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
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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.
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
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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.
Britta Schäfer, Tim Carlsen, Ingrid Hanssen, Michael Gausa, and Trude Storelvmo
Atmos. Chem. Phys., 22, 9537–9551, https://doi.org/10.5194/acp-22-9537-2022, https://doi.org/10.5194/acp-22-9537-2022, 2022
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Cloud properties are important for the surface radiation budget. This study presents cold-cloud observations based on lidar measurements from the Norwegian Arctic between 2011 and 2017. Using statistical assessments and case studies, we give an overview of the macro- and microphysical properties of these clouds and demonstrate the capabilities of long-term cloud observations in the Norwegian Arctic from the ground-based lidar at Andenes.
Caroline Dang, Michal Segal-Rozenhaimer, Haochi Che, Lu Zhang, Paola Formenti, Jonathan Taylor, Amie Dobracki, Sara Purdue, Pui-Shan Wong, Athanasios Nenes, Arthur Sedlacek III, Hugh Coe, Jens Redemann, Paquita Zuidema, Steven Howell, and James Haywood
Atmos. Chem. Phys., 22, 9389–9412, https://doi.org/10.5194/acp-22-9389-2022, https://doi.org/10.5194/acp-22-9389-2022, 2022
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Transmission electron microscopy was used to analyze aged African smoke particles and how the smoke interacts with the marine atmosphere. We found that the volatility of organic aerosol increases with biomass burning plume age, that black carbon is often mixed with potassium salts and that the marine atmosphere can incorporate Na and Cl into smoke particles. Marine salts are more processed when mixed with smoke plumes, and there are interesting Cl-rich yet Na-absent marine particles.
Lu Zhang, Michal Segal-Rozenhaimer, Haochi Che, Caroline Dang, Arthur J. Sedlacek III, Ernie R. Lewis, Amie Dobracki, Jenny P. S. Wong, Paola Formenti, Steven G. Howell, and Athanasios Nenes
Atmos. Chem. Phys., 22, 9199–9213, https://doi.org/10.5194/acp-22-9199-2022, https://doi.org/10.5194/acp-22-9199-2022, 2022
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Widespread biomass burning (BB) events occur annually in Africa and contribute ~ 1 / 3 of global BB emissions, which contain a large family of light-absorbing organics, known as brown carbon (BrC), whose absorption of incident radiation is difficult to estimate, leading to large uncertainties in the global radiative forcing estimation. This study quantifies the BrC absorption of aged BB particles and highlights the potential presence of absorbing iron oxides in this climatically important region.
Haochi Che, Michal Segal-Rozenhaimer, Lu Zhang, Caroline Dang, Paquita Zuidema, Arthur J. Sedlacek III, Xiaoye Zhang, and Connor Flynn
Atmos. Chem. Phys., 22, 8767–8785, https://doi.org/10.5194/acp-22-8767-2022, https://doi.org/10.5194/acp-22-8767-2022, 2022
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A 17-month in situ study on Ascension Island found low single-scattering albedo and strong absorption enhancement of the marine boundary layer aerosols during biomass burnings on the African continent, along with apparent patterns of regular monthly variability. We further discuss the characteristics and drivers behind these changes and find that biomass burning conditions in Africa may be the main factor influencing the optical properties of marine boundary aerosols.
Anne Sophie Daloz, Clemens Schwingshackl, Priscilla Mooney, Susanna Strada, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Michal Belda, Tomas Halenka, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 2403–2419, https://doi.org/10.5194/tc-16-2403-2022, https://doi.org/10.5194/tc-16-2403-2022, 2022
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Snow plays a major role in the regulation of the Earth's surface temperature. Together with climate change, rising temperatures are already altering snow in many ways. In this context, it is crucial to better understand the ability of climate models to represent snow and snow processes. This work focuses on Europe and shows that the melting season in spring still represents a challenge for climate models and that more work is needed to accurately simulate snow–atmosphere interactions.
Sebastian Becker, André Ehrlich, Evelyn Jäkel, Tim Carlsen, Michael Schäfer, and Manfred Wendisch
Atmos. Meas. Tech., 15, 2939–2953, https://doi.org/10.5194/amt-15-2939-2022, https://doi.org/10.5194/amt-15-2939-2022, 2022
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Airborne radiation measurements are used to characterize the solar directional reflection of a mixture of Arctic sea ice and open-ocean surfaces in the transition zone between both surface types. The mixture reveals reflection properties of both surface types. It is shown that the directional reflection of the mixture can be reconstructed from the directional reflection of the individual surfaces, accounting for the special conditions present in the transition zone.
Priscilla A. Mooney, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Natalie de Noblet-Ducoudré, Marcus Breil, Rita M. Cardoso, Anne Sophie Daloz, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 1383–1397, https://doi.org/10.5194/tc-16-1383-2022, https://doi.org/10.5194/tc-16-1383-2022, 2022
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We use multiple regional climate models to show that afforestation in sub-polar and alpine regions reduces the radiative impact of snow albedo on the atmosphere, reduces snow cover, and delays the start of the snowmelt season. This is important for local communities that are highly reliant on snowpack for water resources and winter tourism. However, models disagree on the amount of change particularly when snow is melting. This shows that more research is needed on snow–vegetation interactions.
Sorin Nicolae Vâjâiac, Andreea Calcan, Robert Oscar David, Denisa-Elena Moacă, Gabriela Iorga, Trude Storelvmo, Viorel Vulturescu, and Valeriu Filip
Atmos. Meas. Tech., 14, 6777–6794, https://doi.org/10.5194/amt-14-6777-2021, https://doi.org/10.5194/amt-14-6777-2021, 2021
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Warm clouds (with liquid droplets) play an important role in modulating the amount of incoming solar radiation to Earth’s surface and thus the climate. The most efficient way to study them is by in situ optical measurements. This paper proposes a new methodology for providing more detailed and reliable structural analyses of warm clouds through post-flight processing of collected data. The impact fine aerosol incorporation in water droplets might have on such measurements is also discussed.
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
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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.
Anna J. Miller, Killian P. Brennan, Claudia Mignani, Jörg Wieder, Robert O. David, and Nadine Borduas-Dedekind
Atmos. Meas. Tech., 14, 3131–3151, https://doi.org/10.5194/amt-14-3131-2021, https://doi.org/10.5194/amt-14-3131-2021, 2021
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To characterize atmospheric ice nuclei, we present (1) the development of our home-built droplet freezing technique (DFT), which involves the Freezing Ice Nuclei Counter (FINC), (2) an intercomparison campaign using NX-illite and an ambient sample with two other DFTs, and (3) the application of lignin as a soluble and commercial ice nuclei standard with three DFTs. We further compiled the growing number of DFTs in use for atmospheric ice nucleation since 2000 and add FINC.
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
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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.
Evelyn Jäkel, Tim Carlsen, André Ehrlich, Manfred Wendisch, Michael Schäfer, Sophie Rosenburg, Konstantina Nakoudi, Marco Zanatta, Gerit Birnbaum, Veit Helm, Andreas Herber, Larysa Istomina, Linlu Mei, and Anika Rohde
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-14, https://doi.org/10.5194/tc-2021-14, 2021
Preprint withdrawn
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Different approaches to retrieve the optical-equivalent snow grain size using satellite, airborne, and ground-based observations were evaluated and compared to modeled data. The study is focused on low Sun and partly rough surface conditions encountered North of Greenland in March/April 2018. We proposed an adjusted airborne retrieval method to reduce the retrieval uncertainty.
Jim M. Haywood, Steven J. Abel, Paul A. Barrett, Nicolas Bellouin, Alan Blyth, Keith N. Bower, Melissa Brooks, Ken Carslaw, Haochi Che, Hugh Coe, Michael I. Cotterell, Ian Crawford, Zhiqiang Cui, Nicholas Davies, Beth Dingley, Paul Field, Paola Formenti, Hamish Gordon, Martin de Graaf, Ross Herbert, Ben Johnson, Anthony C. Jones, Justin M. Langridge, Florent Malavelle, Daniel G. Partridge, Fanny Peers, Jens Redemann, Philip Stier, Kate Szpek, Jonathan W. Taylor, Duncan Watson-Parris, Robert Wood, Huihui Wu, and Paquita Zuidema
Atmos. Chem. Phys., 21, 1049–1084, https://doi.org/10.5194/acp-21-1049-2021, https://doi.org/10.5194/acp-21-1049-2021, 2021
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Every year, the seasonal cycle of biomass burning from agricultural practices in Africa creates a huge plume of smoke that travels many thousands of kilometres over the Atlantic Ocean. This study provides an overview of a measurement campaign called the cloud–aerosol–radiation interaction and forcing for year 2017 (CLARIFY-2017) and documents the rationale, deployment strategy, observations, and key results from the campaign which utilized the heavily equipped FAAM atmospheric research aircraft.
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
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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.
Kine Onsum Moseid, Michael Schulz, Trude Storelvmo, Ingeborg Rian Julsrud, Dirk Olivié, Pierre Nabat, Martin Wild, Jason N. S. Cole, Toshihiko Takemura, Naga Oshima, Susanne E. Bauer, and Guillaume Gastineau
Atmos. Chem. Phys., 20, 16023–16040, https://doi.org/10.5194/acp-20-16023-2020, https://doi.org/10.5194/acp-20-16023-2020, 2020
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In this study we compare solar radiation at the surface from observations and Earth system models from 1961 to 2014. We find that the models do not reproduce the so-called
global dimmingas found in observations. Only model experiments with anthropogenic aerosol emissions display any dimming at all. The discrepancies between observations and models are largest in China, which we suggest is in part due to erroneous aerosol precursor emission inventories in the emission dataset used for CMIP6.
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Veit Helm, Evelyn Jäkel, Michael Schäfer, and Manfred Wendisch
The Cryosphere, 14, 3959–3978, https://doi.org/10.5194/tc-14-3959-2020, https://doi.org/10.5194/tc-14-3959-2020, 2020
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The angular reflection of solar radiation by snow surfaces is particularly anisotropic and highly variable. We measured the angular reflection from an aircraft using a digital camera in Antarctica in 2013/14 and studied its variability: the anisotropy increases with a lower Sun but decreases for rougher surfaces and larger snow grains. The applied methodology allows for a direct comparison with satellite observations, which generally underestimated the anisotropy measured within this study.
Anna J. Miller, Killian P. Brennan, Claudia Mignani, Jörg Wieder, Assaf Zipori, Robert O. David, and Nadine Borduas-Dedekind
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-361, https://doi.org/10.5194/amt-2020-361, 2020
Preprint withdrawn
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For characterizing atmospheric ice nuclei, we present (1) the development of our home-built droplet freezing technique (DFT), the Freezing Ice Nuclei Counter (FINC), (2) an intercomparison campaign using NX-illite and an ambient sample with three DFTs, and (3) the application of lignin as a soluble and commercial ice nuclei standard with four DFTs. We further compiled the growing number of DFTs in use for atmospheric ice nucleation since 2000, to which we add FINC.
Anne Sophie Daloz, Marian Mateling, Tristan L'Ecuyer, Mark Kulie, Norm B. Wood, Mikael Durand, Melissa Wrzesien, Camilla W. Stjern, and Ashok P. Dimri
The Cryosphere, 14, 3195–3207, https://doi.org/10.5194/tc-14-3195-2020, https://doi.org/10.5194/tc-14-3195-2020, 2020
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The total of snow that falls globally is a critical factor governing freshwater availability. To better understand how this resource is impacted by climate change, we need to know how reliable the current observational datasets for snow are. Here, we compare five datasets looking at the snow falling over the mountains versus the other continents. We show that there is a large consensus when looking at fractional contributions but strong dissimilarities when comparing magnitudes.
Robert O. David, Jonas Fahrni, Claudia Marcolli, Fabian Mahrt, Dominik Brühwiler, and Zamin A. Kanji
Atmos. Chem. Phys., 20, 9419–9440, https://doi.org/10.5194/acp-20-9419-2020, https://doi.org/10.5194/acp-20-9419-2020, 2020
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Ice crystal formation plays an important role in controlling the Earth's climate. However, the mechanisms responsible for ice formation in the atmosphere are still uncertain. Here we use surrogates for atmospherically relevant porous particles to determine the role of pore diameter and wettability on the ability of porous particles to nucleate ice in the atmosphere. Our results are consistent with the pore condensation and freeing mechanism.
María Cascajo-Castresana, Robert O. David, Maiara A. Iriarte-Alonso, Alexander M. Bittner, and Claudia Marcolli
Atmos. Chem. Phys., 20, 3291–3315, https://doi.org/10.5194/acp-20-3291-2020, https://doi.org/10.5194/acp-20-3291-2020, 2020
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Atmospheric ice-nucleating particles are rare but relevant for cloud glaciation. A source of particles that nucleate ice above −15 °C is biological material including some proteins. Here we show that proteins of very diverse functions and structures can nucleate ice. Among these, the iron storage protein apoferritin stands out, with activity up to −4 °C. We show that its activity does not stem from correctly assembled proteins but from misfolded protein monomers or oligomers and aggregates.
Killian P. Brennan, Robert O. David, and Nadine Borduas-Dedekind
Atmos. Chem. Phys., 20, 163–180, https://doi.org/10.5194/acp-20-163-2020, https://doi.org/10.5194/acp-20-163-2020, 2020
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To contribute to our understanding of the liquid water-to-ice ratio in mixed-phase clouds, this study provides a spatial and temporal dataset of ice-nucleating particle (INP) concentrations in meltwater of 88 snow samples across 17 locations in the Swiss Alps. The impact of altitude, terrain, time since last snowfall and depth on freezing temperatures was also investigated. The measured INP concentrations provide an estimate of cloud glaciation temperatures important for cloud lifetime.
Robert O. David, Maria Cascajo-Castresana, Killian P. Brennan, Michael Rösch, Nora Els, Julia Werz, Vera Weichlinger, Lin S. Boynton, Sophie Bogler, Nadine Borduas-Dedekind, Claudia Marcolli, and Zamin A. Kanji
Atmos. Meas. Tech., 12, 6865–6888, https://doi.org/10.5194/amt-12-6865-2019, https://doi.org/10.5194/amt-12-6865-2019, 2019
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Here we present the development and applicability of the DRoplet Ice Nuclei Counter Zurich (DRINCZ). DRINCZ allows for ice nuclei in the immersion mode to be quantified between 0 and -25 °C with an uncertainty of ±0.9 °C. Furthermore, we present a new method for assessing biases in drop-freezing apparatuses and cumulative ice-nucleating-particle concentrations from snow samples collected in the Austrian Alps at the Sonnblick Observatory.
Nadine Borduas-Dedekind, Rachele Ossola, Robert O. David, Lin S. Boynton, Vera Weichlinger, Zamin A. Kanji, and Kristopher McNeill
Atmos. Chem. Phys., 19, 12397–12412, https://doi.org/10.5194/acp-19-12397-2019, https://doi.org/10.5194/acp-19-12397-2019, 2019
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During atmospheric transport, dissolved organic matter (DOM) within aqueous aerosols undergoes photochemistry. We find that photochemical processing of DOM increases its ability to form cloud droplets but decreases its ability to form ice crystals over a simulated 4.6 days in the atmosphere. A photomineralization mechanism involving the loss of organic carbon and the production of organic acids, CO and CO2 explains the observed changes and affects the liquid-water-to-ice ratio in clouds.
Douglas H. Lowenthal, A. Gannet Hallar, Robert O. David, Ian B. McCubbin, Randolph D. Borys, and Gerald G. Mace
Atmos. Chem. Phys., 19, 5387–5401, https://doi.org/10.5194/acp-19-5387-2019, https://doi.org/10.5194/acp-19-5387-2019, 2019
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Snow and liquid cloud particles were measured during the StormVEx and IFRACS programs at Storm Peak Lab to better understand snow formation in wintertime mountain clouds. We found significant interactions between the ice and liquid phases of the cloud. A relationship between large droplet and small ice crystal concentrations suggested snow formation by droplet freezing. Blowing snow can bias surface measurements, but its effect was ambiguous, calling for further work on this issue.
Mikhail Paramonov, Robert O. David, Ruben Kretzschmar, and Zamin A. Kanji
Atmos. Chem. Phys., 18, 16515–16536, https://doi.org/10.5194/acp-18-16515-2018, https://doi.org/10.5194/acp-18-16515-2018, 2018
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The paper presents an overview of the ice nucleation activity of surface-collected mineral and soil dust. Emphasis is placed on disentangling the effects of mineral, biogenic and soluble components of the dust on its ice nucleation activity. The results revealed that it is not possible to predict the ice nucleation activity of the surface-collected dust based on the presence and amount of certain minerals or any particular class of compounds, such as soluble or proteinaceous/organic compounds.
Fabian Mahrt, Claudia Marcolli, Robert O. David, Philippe Grönquist, Eszter J. Barthazy Meier, Ulrike Lohmann, and Zamin A. Kanji
Atmos. Chem. Phys., 18, 13363–13392, https://doi.org/10.5194/acp-18-13363-2018, https://doi.org/10.5194/acp-18-13363-2018, 2018
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The ice nucleation ability of different soot particles in the cirrus and mixed-phase cloud temperature regime is presented. The impact of aerosol particle size, particle morphology, organic matter and hydrophilicity on ice nucleation is examined. We propose ice nucleation proceeds via a pore condensation freezing mechanism for soot particles with the necessary physicochemical properties that nucleated ice well below water saturation.
Alexander Beck, Jan Henneberger, Jacob P. Fugal, Robert O. David, Larissa Lacher, and Ulrike Lohmann
Atmos. Chem. Phys., 18, 8909–8927, https://doi.org/10.5194/acp-18-8909-2018, https://doi.org/10.5194/acp-18-8909-2018, 2018
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This study assesses the impact of surface processes (e.g. blowing snow) on in situ cloud observations at Sonnblick Observatory. Vertical profiles of ice crystal number concentrations (ICNCs) above a snow-covered surface were observed up to a height of 10 m. The ICNC near the ground is at least a factor of 2 larger than at 10 m. Therefore, in situ measurements of ICNCs at mountain-top research stations close to the surface are strongly influenced by surface processes and overestimate the ICNC.
Inger Helene Hafsahl Karset, Terje Koren Berntsen, Trude Storelvmo, Kari Alterskjær, Alf Grini, Dirk Olivié, Alf Kirkevåg, Øyvind Seland, Trond Iversen, and Michael Schulz
Atmos. Chem. Phys., 18, 7669–7690, https://doi.org/10.5194/acp-18-7669-2018, https://doi.org/10.5194/acp-18-7669-2018, 2018
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This study highlights the role of oxidants in modeling of the preindustrial-to-present-day aerosol indirect effects. We argue that the aerosol precursor gases should be exposed to oxidants of its era to get a more correct representation of secondary aerosol formation. Our global model simulations show that the total aerosol indirect effect changes from −1.32 to −1.07 W m−2 when the precursor gases in the preindustrial simulation are exposed to preindustrial instead of present-day oxidants.
Yaoxian Huang, Nadine Unger, Trude Storelvmo, Kandice Harper, Yiqi Zheng, and Chris Heyes
Atmos. Chem. Phys., 18, 5219–5233, https://doi.org/10.5194/acp-18-5219-2018, https://doi.org/10.5194/acp-18-5219-2018, 2018
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We apply a global 3-D climate model to quantify the climate impacts of carbonaceous aerosols from solid fuel cookstove emissions. Without black carbon (BC) serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have net global cooling impacts. However, when BC acts as IN, the net sign of radiative impacts of carbonaceous aerosols from solid fuel cookstove emissions varies with the choice of maximum freezing efficiency of BC during ice cloud formation.
Junting Zhong, Xiaoye Zhang, Yunsheng Dong, Yaqiang Wang, Cheng Liu, Jizhi Wang, Yangmei Zhang, and Haochi Che
Atmos. Chem. Phys., 18, 247–258, https://doi.org/10.5194/acp-18-247-2018, https://doi.org/10.5194/acp-18-247-2018, 2018
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Beijing heavy pollution episodes are characterized by the transport stage (TS) and the cumulative stage (CS). PM2.5 pollution formation in the TS is primarily caused by pollutants transported from the south of Beijing. PM2.5 cumulative explosive growth in the CS is dominated by stable atmospheric stratification due to the interaction of particulate matter (PM) and meteorological factors. The positive meteorological feedback on PM2.5 mass noted explains over 70% of cumulative explosive growth.
Tim Carlsen, Gerit Birnbaum, André Ehrlich, Johannes Freitag, Georg Heygster, Larysa Istomina, Sepp Kipfstuhl, Anaïs Orsi, Michael Schäfer, and Manfred Wendisch
The Cryosphere, 11, 2727–2741, https://doi.org/10.5194/tc-11-2727-2017, https://doi.org/10.5194/tc-11-2727-2017, 2017
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The optical size of snow grains (ropt) affects the reflectivity of snow surfaces and thus the local surface energy budget in particular in polar regions. The temporal evolution of ropt retrieved from ground-based, airborne, and spaceborne remote sensing could reproduce optical in situ measurements for a 2-month period in central Antarctica (2013/14). The presented validation study provided a unique testbed for retrievals of ropt under Antarctic conditions where in situ data are scarce.
Sarvesh Garimella, Daniel A. Rothenberg, Martin J. Wolf, Robert O. David, Zamin A. Kanji, Chien Wang, Michael Rösch, and Daniel J. Cziczo
Atmos. Chem. Phys., 17, 10855–10864, https://doi.org/10.5194/acp-17-10855-2017, https://doi.org/10.5194/acp-17-10855-2017, 2017
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This study investigates systematic and variable low bias in the measurement of ice nucleating particle concentration using continuous flow diffusion chambers. We find that non-ideal instrument behavior exposes particles to different humidities and/or temperatures than predicted from theory. We use a machine learning approach to quantify and minimize the uncertainty associated with this measurement bias.
Jane E. Smyth, Rick D. Russotto, and Trude Storelvmo
Atmos. Chem. Phys., 17, 6439–6453, https://doi.org/10.5194/acp-17-6439-2017, https://doi.org/10.5194/acp-17-6439-2017, 2017
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Geoengineering is a controversial proposal to counteract global warming by reducing the incoming solar radiation. Solar dimming could restore preindustrial temperatures, but global rainfall patterns would be altered. We analyze the global rainfall changes in 11 climate model simulations of solar dimming to better understand the underlying processes. We conclude that tropical precipitation would be substantially altered, in part due to changes in the large-scale atmospheric circulation.
B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe
Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, https://doi.org/10.5194/gmd-8-3379-2015, 2015
L. Zhang, J. Y. Sun, X. J. Shen, Y. M. Zhang, H. Che, Q. L. Ma, Y. W. Zhang, X. Y. Zhang, and J. A. Ogren
Atmos. Chem. Phys., 15, 8439–8454, https://doi.org/10.5194/acp-15-8439-2015, https://doi.org/10.5194/acp-15-8439-2015, 2015
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The aerosol hygroscopic properties at a rural background site in the Yangtze River delta of China was discussed. The results show the scattering coefficient and backscattering coefficient increased by 58 and 25% as relative humidity (RH) increased from 40 to 85%, while the hemispheric backscatter fraction decreased by 21%. Aerosol hygroscopic growth caused a 47% increase in calculated aerosol direct radiative forcing at 85% RH compared to the forcing at 40% RH. Nitrate played a vital role.
A. Takeishi and T. Storelvmo
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-24087-2014, https://doi.org/10.5194/acpd-14-24087-2014, 2014
Revised manuscript not accepted
Related subject area
Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Counteracting influences of gravitational settling modulate aerosol impacts on cloud-base-lowering fog characteristics
The critical number and size of precipitation embryos to accelerate warm rain initiation
Impact on the stratocumulus-to-cumulus transition of the interaction of cloud microphysics and macrophysics with large-scale circulation
Technical note: Phase space depiction of cloud condensation nuclei activation and cloud droplet diffusional growth
Impact of wildfire smoke on Arctic cirrus formation – Part 2: Simulation of MOSAiC 2019–2020 cases
Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble
Investigating ice formation pathways using a novel two-moment multi-class cloud microphysics scheme
Microphysics regimes due to haze–cloud interactions: cloud oscillation and cloud collapse
Impact of secondary ice production on thunderstorm electrification under different aerosol conditions
Accelerated impact of airborne glaciogenic seeding of stratiform clouds by turbulence
Model analysis of biases in the satellite-diagnosed aerosol effect on the cloud liquid water path
Failed cyclogenesis of a mesoscale convective system near Cape Verde: The role of the Saharan trade wind layer among other inhibiting factors observed during the CADDIWA field campaign
Dynamical imprints on precipitation cluster statistics across a hierarchy of high-resolution simulations
Ice formation processes key in determining WCB outflow cirrus properties
Role of a key microphysical factor in mixed-phase stratocumulus clouds and their interactions with aerosols
High-resolution modelling of early contrail evolution from hydrogen-powered aircraft
Investigating the impact of subgrid-scale aerosol-cloud interaction on mesoscale meteorology prediction
Correction of ERA5 temperature and relative humidity biases by bivariate quantile mapping for contrail formation analysis
Can pollen affect precipitation?
Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response
The impact of the mesh size and microphysics scheme on the representation of mid-level clouds in the ICON model in hilly and complex terrain
The role of ascent timescales for warm conveyor belt (WCB) moisture transport into the upper troposphere and lower stratosphere (UTLS)
Magnitude and timescale of liquid water path adjustments to cloud droplet number concentration perturbations for nocturnal non-precipitating marine stratocumulus
On the Processes Determining the Slope of Cloud-Water Adjustments in Non-Precipitating Stratocumulus
Estimating the concentration of silver iodide needed to detect unambiguous signatures of glaciogenic cloud seeding
On the impact of thunder on cloud ice crystals and droplets
Ice-nucleating particle concentration impacts cloud properties over Dronning Maud Land, East Antarctica, in COSMO-CLM2
Numerical simulation of aerosol concentration effects on cloud droplet size spectrum evolutions of warm stratiform clouds in Jiangxi, China
The impact of aerosol on cloud water: a heuristic perspective
Cold pools mediate mesoscale adjustments of trade-cumulus fields to changes in cloud-droplet number concentration
The presence of clouds lowers climate sensitivity in the MPI-ESM1.2 climate model
Diurnal variation in an amplified canopy urban heat island during heat wave periods in the megacity of Beijing: roles of mountain–valley breeze and urban morphology
Diurnal evolution of non-precipitating marine stratocumuli in a large-eddy simulation ensemble
Ambient and Intrinsic Dependencies of Evolving Ice-Phase Particles within a Decaying Winter Storm During IMPACTS
Building a comprehensive library of observed Lagrangian trajectories for testing modeled cloud evolution, aerosol-cloud interactions, and marine cloud brightening
Numerical Case Study of the Aerosol-Cloud-Interactions in Warm Boundary Layer Clouds over the Eastern North Atlantic with an Interactive Chemistry Module
High ice water content in tropical mesoscale convective systems (a conceptual model)
Evolution of cloud droplet temperature and lifetime in spatiotemporally varying subsaturated environments with implications for ice nucleation at cloud edges
Effect of secondary ice production processes on the simulation of ice pellets using the Predicted Particle Properties microphysics scheme
Simulated particle evolution within a winter storm: contributions of riming to radar moments and precipitation fallout
Arctic Multilayer Clouds Require Accurate Thermodynamic Profiles and Efficient Primary and Secondary Ice Processes for a Realistic Structure and Composition
A thermal-driven graupel generation process to explain dry-season convective vigor over the Amazon
Modeling homogeneous ice nucleation from drop-freezing experiments: impact of droplet volume dispersion and cooling rates
Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli
Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment
Influence of Temperature and Humidity on Contrail Formation Regions in EMAC: A Spring Case Study
Microphysical processes involving the vapour phase dominate in simulated low-level Arctic clouds
Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign
On the sensitivity of aerosol–cloud interactions to changes in sea surface temperature in radiative–convective equilibrium
Exploring aerosol–cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean using the WRF-Chem–SBM model
Nathan H. Pope and Adele L. Igel
Atmos. Chem. Phys., 25, 5433–5444, https://doi.org/10.5194/acp-25-5433-2025, https://doi.org/10.5194/acp-25-5433-2025, 2025
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We used an atmospheric model that simulates a single column to study the sensitivity of marine fog formed through the lowering of the base of a stratus cloud to meteorology and aerosols. We found that higher aerosol concentration reduces the likelihood and duration of fog but leads to denser fog. This overall trend was caused by multiple physical mechanisms depending on conditions.
Jung-Sub Lim, Yign Noh, Hyunho Lee, and Fabian Hoffmann
Atmos. Chem. Phys., 25, 5313–5329, https://doi.org/10.5194/acp-25-5313-2025, https://doi.org/10.5194/acp-25-5313-2025, 2025
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Rain formation in warm clouds begins when small droplets collide, but this process can be slow without larger droplets. We used simulations to explore the role of bigger droplets, known as precipitation embryos, in triggering rain. We found that they speed up rain only when their size and number exceed a critical threshold. This threshold becomes larger when collisions are naturally efficient, such as in clouds with broad droplet size distributions or strong turbulence.
Je-Yun Chun, Robert Wood, Peter N. Blossey, and Sarah J. Doherty
Atmos. Chem. Phys., 25, 5251–5271, https://doi.org/10.5194/acp-25-5251-2025, https://doi.org/10.5194/acp-25-5251-2025, 2025
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This study explores how aerosols affect clouds transitioning from stratocumulus to cumulus along trade winds under varying atmospheric conditions. We found that aerosols typically reduce precipitation and raise cloud height, but their impact changes when subsidence changes by aerosol enhancement are considered. Our findings indicate that the cooling effect of aerosols might be overestimated if these atmospheric changes are not accounted for.
Wojciech W. Grabowski and Hanna Pawlowska
Atmos. Chem. Phys., 25, 5273–5285, https://doi.org/10.5194/acp-25-5273-2025, https://doi.org/10.5194/acp-25-5273-2025, 2025
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A simple diagram to depict cloud droplets' formation via the activation of cloud condensation nuclei (CCN) as well as their subsequent growth and evaporation is presented.
Albert Ansmann, Cristofer Jimenez, Daniel A. Knopf, Johanna Roschke, Johannes Bühl, Kevin Ohneiser, and Ronny Engelmann
Atmos. Chem. Phys., 25, 4867–4884, https://doi.org/10.5194/acp-25-4867-2025, https://doi.org/10.5194/acp-25-4867-2025, 2025
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In this study, we focus on the potential impact of wildfire smoke on cirrus formation. Aerosol and cirrus observations with lidar and radar during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, presented in the companion paper (Ansmann et al., 2025), are closely linked to comprehensive modeling of ice nucleation in cirrus evolution processes, presented in this article. A clear impact of wildfire smoke on cirrus formation was found.
August Mikkelsen, Daniel T. McCoy, Trude Eidhammer, Andrew Gettelman, Ci Song, Hamish Gordon, and Isabel L. McCoy
Atmos. Chem. Phys., 25, 4547–4570, https://doi.org/10.5194/acp-25-4547-2025, https://doi.org/10.5194/acp-25-4547-2025, 2025
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Whether increased aerosol increases or decreases liquid cloud mass has been a longstanding question. Observed correlations suggest that aerosols thin liquid cloud, but we are able to show that observations were consistent with an increase in liquid cloud in response to aerosols by leveraging a model where causality could be traced.
Tim Lüttmer, Peter Spichtinger, and Axel Seifert
Atmos. Chem. Phys., 25, 4505–4529, https://doi.org/10.5194/acp-25-4505-2025, https://doi.org/10.5194/acp-25-4505-2025, 2025
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We investigate ice formation pathways in idealized convective clouds using a novel microphysics scheme that distinguishes between five ice classes each with their own unique formation mechanism. Ice crystals from rime splintering form the lowermost layer of ice crystals around the updraft core. The majority of ice crystals in the anvil of the convective cloud stems from frozen droplets. Ice stemming from homogeneous and deposition nucleation was only relevant in the overshoot.
Fan Yang, Hamed Fahandezh Sadi, Raymond A. Shaw, Fabian Hoffmann, Pei Hou, Aaron Wang, and Mikhail Ovchinnikov
Atmos. Chem. Phys., 25, 3785–3806, https://doi.org/10.5194/acp-25-3785-2025, https://doi.org/10.5194/acp-25-3785-2025, 2025
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Large-eddy simulations of a convection cloud chamber show two new microphysics regimes, cloud oscillation and cloud collapse, due to haze–cloud interactions. Our results suggest that haze particles and their interactions with cloud droplets should be considered especially in polluted conditions. To properly simulate haze–cloud interactions, we need to resolve droplet activation and deactivation processes, instead of using Twomey-type activation parameterization.
Shiye Huang, Jing Yang, Jiaojiao Li, Qian Chen, Qilin Zhang, and Fengxia Guo
Atmos. Chem. Phys., 25, 1831–1850, https://doi.org/10.5194/acp-25-1831-2025, https://doi.org/10.5194/acp-25-1831-2025, 2025
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Aerosol and secondary ice production are both vital to charge separation in thunderstorms, but the relative importance of different SIP processes to cloud electrification under different aerosol conditions is not well understood. In this study, we show in a clean environment, the shattering of freezing drops has the greatest effect on the charging rate, while in a polluted environment, both rime splintering and the shattering of freezing drops have a significant effect on cloud electrification.
Meilian Chen, Xiaoqin Jing, Jiaojiao Li, Jing Yang, Xiaobo Dong, Bart Geerts, Yan Yin, Baojun Chen, Lulin Xue, Mengyu Huang, Ping Tian, and Shaofeng Hua
EGUsphere, https://doi.org/10.5194/egusphere-2025-47, https://doi.org/10.5194/egusphere-2025-47, 2025
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Several recent studies have reported complete cloud glaciation induced by airborne-based glaciogenic cloud seeding over plains. Since turbulence is an important factor to maintain clouds in mixed-phase, it is hypothesized that turbulence may have an impact on the seeding effect. This hypothesis is evident in the present study, which shows turbulence can accelerate the impact of airborne glaciogenic seeding of stratiform clouds.
Harri Kokkola, Juha Tonttila, Silvia M. Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo Henrik Virtanen, Pekka Kolmonen, and Antti Arola
Atmos. Chem. Phys., 25, 1533–1543, https://doi.org/10.5194/acp-25-1533-2025, https://doi.org/10.5194/acp-25-1533-2025, 2025
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Understanding how atmospheric aerosols affect clouds is a scientific challenge. One question is how aerosols affects the amount of cloud water. We used a cloud-scale model to study these effects on marine clouds. The study showed that variations in cloud properties and instrument noise can cause bias in satellite-derived cloud water content. However, our results suggest that for similar weather conditions with well-defined aerosol concentrations, satellite data can reliably track these effects.
Guillaume Feger, Jean-Pierre Chaboureau, Thibaut Dauhut, Julien Delanoë, and Pierre Coutris
EGUsphere, https://doi.org/10.5194/egusphere-2025-105, https://doi.org/10.5194/egusphere-2025-105, 2025
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The Saharan air at trade wind layer, cold pools, and upper tropospheric dry air are identified as the three main factors inhibiting the cyclogenesis of the Pierre Henri mesoscale convective system. The findings were obtained trough observations made during two flights of the CADDIWA campaign and a convection-permitting simulation run with the Meso-NH model. They provide new insights into the complex dynamics of cyclogenesis in the Cape Verde region and challenge the existing model of the SAL.
Claudia Christine Stephan and Bjorn Stevens
Atmos. Chem. Phys., 25, 1209–1226, https://doi.org/10.5194/acp-25-1209-2025, https://doi.org/10.5194/acp-25-1209-2025, 2025
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Tropical precipitation cluster area and intensity distributions follow power laws, but the physical processes responsible for this behavior remain unknown. We analyze global simulations that realistically represent precipitation processes. We consider Earth-like planets as well as virtual planets to realize different types of large-scale dynamics. Our finding is that power laws in Earth’s precipitation cluster statistics stem from the robust power laws in Earth’s atmospheric wind field.
Tim Lüttmer, Annette Miltenberger, and Peter Spichtinger
EGUsphere, https://doi.org/10.5194/egusphere-2025-185, https://doi.org/10.5194/egusphere-2025-185, 2025
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We investigate ice formation pathways in a warm conveyor belt case study. We employ a multi-phase microphysics scheme that distinguishes between ice from different nucleation processes. Ice crystals in the cirrus outflow mostly stem from in-situ formation. Hence they were formed directly from the vapor phase. Sedimentational redistribution modulates cirrus properties and leads to a disagreement between cirrus origin classifications based on thermodynamic history and nucleation processes.
Seoung Soo Lee, Chang Hoon Jung, Jinho Choi, Young Jun Yoon, Junshik Um, Youtong Zheng, Jianping Guo, Manguttathil G. Manoj, Sang-Keun Song, and Kyung-Ja Ha
Atmos. Chem. Phys., 25, 705–726, https://doi.org/10.5194/acp-25-705-2025, https://doi.org/10.5194/acp-25-705-2025, 2025
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This study attempts to test a general factor that explains differences in the properties of different mixed-phase clouds using a modeling tool. Although this attempt is not to identify a factor that can perfectly explain and represent the properties of different mixed-phase clouds, we believe that this attempt acts as a valuable stepping stone towards a more complete, general way of using climate models to better predict climate change.
Annemarie Lottermoser and Simon Unterstraßer
EGUsphere, https://doi.org/10.5194/egusphere-2024-3859, https://doi.org/10.5194/egusphere-2024-3859, 2025
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Contrail-cirrus significantly contributes to aviation's overall climate impact. As hydrogen combustion and fuel cell use are emerging technologies for aircraft propulsion, we simulated individual contrails from hydrogen propulsion during the first six minutes after exhaust emission, termed the vortex phase. The ice crystal loss during that stage is crucial as the number of ice crystals has a large impact on the further evolution of contrails into contrail-cirrus and their radiative forcing.
Wenjie Zhang, Hong Wang, Xiaoye Zhang, Yue Peng, Zhaodong Liu, Deying Wang, Da Zhang, Chen Han, Yang Zhao, Junting Zhong, Wenxing Jia, Huiqiong Ning, and Huizheng Che
EGUsphere, https://doi.org/10.5194/egusphere-2024-3677, https://doi.org/10.5194/egusphere-2024-3677, 2025
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We implement a real-time subgrid-scale aerosol-cloud interaction (ACI) mechanism in a mesoscale atmospheric chemistry system and find that subgrid-scale ACI can improve meteorological factors predictions. This study demonstrates the importance of real-time subgrid-scale ACI to weather forecast and the necessity of multiscale ACI studies.
Kevin Wolf, Nicolas Bellouin, Olivier Boucher, Susanne Rohs, and Yun Li
Atmos. Chem. Phys., 25, 157–181, https://doi.org/10.5194/acp-25-157-2025, https://doi.org/10.5194/acp-25-157-2025, 2025
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ERA5 atmospheric reanalysis and airborne in situ observations from IAGOS are compared in terms of the representation of the contrail formation potential and the presence of supersaturation. Differences are traced back to biases in ERA5 relative humidity fields. Those biases are addressed by applying a quantile mapping technique that significantly improved contrail estimation based on post-processed ERA5 data.
Marje Prank, Juha Tonttila, Xiaoxia Shang, Sami Romakkaniemi, and Tomi Raatikainen
Atmos. Chem. Phys., 25, 183–197, https://doi.org/10.5194/acp-25-183-2025, https://doi.org/10.5194/acp-25-183-2025, 2025
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Large primary bioparticles such as pollen can be abundant in the atmosphere. In humid conditions pollen can rupture and release a large number of fine sub-pollen particles (SPPs). The paper investigates what kind of birch pollen concentrations are needed for the pollen and SPPs to start playing a noticeable role in cloud processes and alter precipitation formation. In the studied cases only the largest observed pollen concentrations were able to noticeably alter the precipitation formation.
Luís Filipe Escusa dos Santos, Hannah C. Frostenberg, Alejandro Baró Pérez, Annica M. L. Ekman, Luisa Ickes, and Erik S. Thomson
Atmos. Chem. Phys., 25, 119–142, https://doi.org/10.5194/acp-25-119-2025, https://doi.org/10.5194/acp-25-119-2025, 2025
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The Arctic is experiencing enhanced surface warming. The observed decline in Arctic sea-ice extent is projected to lead to an increase in Arctic shipping activity, which may lead to further climatic feedbacks. Using an atmospheric model and results from marine engine experiments that focused on fuel sulfur content reduction and exhaust wet scrubbing, we investigate how ship exhaust particles influence the properties of Arctic clouds. Implications for radiative surface processes are discussed.
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
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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.
Cornelis Schwenk and Annette Miltenberger
Atmos. Chem. Phys., 24, 14073–14099, https://doi.org/10.5194/acp-24-14073-2024, https://doi.org/10.5194/acp-24-14073-2024, 2024
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Warm conveyor belts (WCBs) transport moisture into the upper atmosphere, where it acts as a greenhouse gas. This transport is not well understood, and the role of rapidly rising air is unclear. We simulate a WCB and look at fast- and slow-rising air to see how moisture is (differently) transported. We find that for fast-ascending air more ice particles reach higher into the atmosphere and that frozen cloud particles are removed differently than during slow ascent, which has more water vapour.
Yao-Sheng Chen, Prasanth Prabhakaran, Fabian Hoffmann, Jan Kazil, Takanobu Yamaguchi, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2024-3891, https://doi.org/10.5194/egusphere-2024-3891, 2024
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Injecting sea salt aerosols into marine stratiform clouds can distribute the cloud water over more droplets in smaller sizes. This process is expected to make the clouds brighter, allowing them to reflect more sunlight back to space. However, it may also cause the clouds to lose water over time, reducing their ability to reflect sunlight. We use a computer model to show that the loss of cloud water occurs relatively quickly and does not completely offset the initial brightening.
Fabian Hoffmann, Yao-Sheng Chen, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2024-3893, https://doi.org/10.5194/egusphere-2024-3893, 2024
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Clouds reflect a substantial portion of the incoming solar radiation back into space. This capacity is determined by the number of cloud droplets, which in turn is influenced by the number of aerosol particles, forming the basis for aerosol-cloud-climate interactions. In this study, we use a simple mixed-layer approach to understand the effect of aerosol on cloud water in non-precipitating stratocumulus.
Jing Yang, Jiaojiao Li, Meilian Chen, Xiaoqin Jing, Yan Yin, Bart Geerts, Zhien Wang, Yubao Liu, Baojun Chen, Shaofeng Hua, Hao Hu, Xiaobo Dong, Ping Tian, Qian Chen, and Yang Gao
Atmos. Chem. Phys., 24, 13833–13848, https://doi.org/10.5194/acp-24-13833-2024, https://doi.org/10.5194/acp-24-13833-2024, 2024
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Detecting unambiguous signatures is vital for examining cloud-seeding impacts, but often, seeding signatures are immersed in natural variability. In this study, reflectivity changes induced by glaciogenic seeding using different AgI concentrations are investigated under various conditions, and a method is developed to estimate the AgI concentration needed to detect unambiguous seeding signatures. The results aid in operational seeding-based decision-making regarding the amount of AgI dispersed.
Konstantinos Kourtidis, Stavros Stathopoulos, and Vassilis Amiridis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3314, https://doi.org/10.5194/egusphere-2024-3314, 2024
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The loud sound of thunder will induce mechanical effects on cloud droplets and ice particles, causing changes in their size distribution.
Florian Sauerland, Niels Souverijns, Anna Possner, Heike Wex, Preben Van Overmeiren, Alexander Mangold, Kwinten Van Weverberg, and Nicole van Lipzig
Atmos. Chem. Phys., 24, 13751–13768, https://doi.org/10.5194/acp-24-13751-2024, https://doi.org/10.5194/acp-24-13751-2024, 2024
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We use a regional climate model, COSMO-CLM², enhanced with a module resolving aerosol processes, to study Antarctic clouds. We prescribe different concentrations of ice-nucleating particles to our model to assess how these clouds respond to concentration changes, validating results with cloud and aerosol observations from the Princess Elisabeth Antarctica station. Our results show that aerosol–cloud interactions vary with temperature, providing valuable insights into Antarctic cloud dynamics.
Yi Li, Xiaoli Liu, and Hengjia Cai
Atmos. Chem. Phys., 24, 13525–13540, https://doi.org/10.5194/acp-24-13525-2024, https://doi.org/10.5194/acp-24-13525-2024, 2024
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The influence of different aerosol modes on cloud processes remains controversial. We modified the aerosol spectra and concentrations to simulate a warm stratiform cloud process in Jiangxi, China, using the WRF-SBM scheme. Research shows that different aerosol spectra have diverse effects on cloud droplet spectra, cloud development, and the correlation between dispersion (ε) and cloud physics quantities. Compared to cloud droplet concentration, ε is more sensitive to the volume radius.
Fabian Hoffmann, Franziska Glassmeier, and Graham Feingold
Atmos. Chem. Phys., 24, 13403–13412, https://doi.org/10.5194/acp-24-13403-2024, https://doi.org/10.5194/acp-24-13403-2024, 2024
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Clouds constitute a major cooling influence on Earth's climate system by reflecting a large fraction of the incident solar radiation back to space. This ability is controlled by the number of cloud droplets, which is governed by the number of aerosol particles in the atmosphere, laying the foundation for so-called aerosol–cloud–climate interactions. In this study, a simple model to understand the effect of aerosol on cloud water is developed and applied.
Pouriya Alinaghi, Fredrik Jansson, Daniel A. Blázquez, and Franziska Glassmeier
EGUsphere, https://doi.org/10.5194/egusphere-2024-3501, https://doi.org/10.5194/egusphere-2024-3501, 2024
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Shallow clouds in the trades are a major source of uncertainty in climate projections. These clouds organize into striking mesoscale patterns that are exactly what climate models lack. This study explores the origin of such patterns and investigates how variations in microscale properties control them. The importance of microscale effects is compared to that of large-scale forcing on the mesoscale organization of trade-cumulus fields.
Andrea Mosso, Thomas Hocking, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 12793–12806, https://doi.org/10.5194/acp-24-12793-2024, https://doi.org/10.5194/acp-24-12793-2024, 2024
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Clouds play a crucial role in the Earth's energy balance, as they can either warm up or cool down the area they cover depending on their height and depth. They are expected to alter their behaviour under climate change, affecting the warming generated by greenhouse gases. This paper proposes a new method to estimate their overall effect on this warming by simulating a climate where clouds are transparent. Results show that with the model used, clouds have a stabilising effect on climate.
Tao Shi, Yuanjian Yang, Ping Qi, and Simone Lolli
Atmos. Chem. Phys., 24, 12807–12822, https://doi.org/10.5194/acp-24-12807-2024, https://doi.org/10.5194/acp-24-12807-2024, 2024
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This paper explored the formation mechanisms of the amplified canopy urban heat island intensity (ΔCUHII) during heat wave (HW) periods in the megacity of Beijing from the perspectives of mountain–valley breeze and urban morphology. During the mountain breeze phase, high-rise buildings with lower sky view factors (SVFs) had a pronounced effect on the ΔCUHII. During the valley breeze phase, high-rise buildings exerted a dual influence on the ΔCUHII.
Yao-Sheng Chen, Jianhao Zhang, Fabian Hoffmann, Takanobu Yamaguchi, Franziska Glassmeier, Xiaoli Zhou, and Graham Feingold
Atmos. Chem. Phys., 24, 12661–12685, https://doi.org/10.5194/acp-24-12661-2024, https://doi.org/10.5194/acp-24-12661-2024, 2024
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Marine stratocumulus cloud is a type of shallow cloud that covers the vast areas of Earth's surface. It plays an important role in Earth's energy balance by reflecting solar radiation back to space. We used numerical models to simulate a large number of marine stratocumuli with different characteristics. We found that how the clouds develop throughout the day is affected by the level of humidity in the air above the clouds and how closely the clouds connect to the ocean surface.
Andrew DeLaFrance, Lynn McMurdie, Angela Rowe, and Andrew Heymsfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3423, https://doi.org/10.5194/egusphere-2024-3423, 2024
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Numerical modeling simulations are used to investigate ice crystal growth and decay processes within a banded region of enhanced precipitation rates during a prominent winter storm. We identify robust primary ice growth in the upper portion of the cloud but decay exceeding 70 % during fallout through a subsaturated layer. The ice fall characteristics and decay rate are sensitive to the ambient cloud properties which has implications for radar-based measurements and precipitation accumulations.
Ehsan Erfani, Robert Wood, Peter Blossey, Sarah J. Doherty, and Ryan Eastman
EGUsphere, https://doi.org/10.5194/egusphere-2024-3232, https://doi.org/10.5194/egusphere-2024-3232, 2024
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In this study, we explore how marine clouds interact with aerosols. We introduce a novel approach to identify a reduced number of representative cases from a wide array of observed environmental conditions prevalent in the Northeast Pacific. We created over 2200 trajectories from observations and used cloud-resolving simulations to investigate how marine low clouds evolve in two different cases. It is shown that aerosols can delay cloud breakup, but their impact depends on precipitation.
Hsiang-He Lee, Xue Zheng, Shaoyue Qiu, and Yuan Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3199, https://doi.org/10.5194/egusphere-2024-3199, 2024
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The study investigates how aerosol-cloud interactions affect warm boundary layer stratiform clouds over the Eastern North Atlantic. High-resolution WRF-Chem simulations reveal that non-rain clouds at the edges of cloud systems are prone to evaporation, leading to an aerosol drying effect and a transition of aerosols back to accumulation mode for future activation. The study emphasizes that this dynamic behavior is often not adequately represented in most previous prescribed-aerosol simulations.
Alexei Korolev, Zhipeng Qu, Jason Milbrandt, Ivan Heckman, Mélissa Cholette, Mengistu Wolde, Cuong Nguyen, Greg M. McFarquhar, Paul Lawson, and Ann M. Fridlind
Atmos. Chem. Phys., 24, 11849–11881, https://doi.org/10.5194/acp-24-11849-2024, https://doi.org/10.5194/acp-24-11849-2024, 2024
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The phenomenon of high ice water content (HIWC) occurs in mesoscale convective systems (MCSs) when a large number of small ice particles with typical sizes of a few hundred micrometers is found at high altitudes. It was found that secondary ice production in the vicinity of the melting layer plays a key role in the formation and maintenance of HIWC. This study presents a conceptual model of the formation of HIWC in tropical MCSs based on in situ observations and numerical simulation.
Puja Roy, Robert M. Rauber, and Larry Di Girolamo
Atmos. Chem. Phys., 24, 11653–11678, https://doi.org/10.5194/acp-24-11653-2024, https://doi.org/10.5194/acp-24-11653-2024, 2024
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Cloud droplet temperature and lifetime impact cloud microphysical processes such as the activation of ice-nucleating particles. We investigate the thermal and radial evolution of supercooled cloud droplets and their surrounding environments with an aim to better understand observed enhanced ice formation at supercooled cloud edges. This analysis shows that the magnitude of droplet cooling during evaporation is greater than estimated from past studies, especially for drier environments.
Mathieu Lachapelle, Mélissa Cholette, and Julie M. Thériault
Atmos. Chem. Phys., 24, 11285–11304, https://doi.org/10.5194/acp-24-11285-2024, https://doi.org/10.5194/acp-24-11285-2024, 2024
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Hazardous precipitation types such as ice pellets and freezing rain are difficult to predict because they are associated with complex microphysical processes. Using Predicted Particle Properties (P3), this work shows that secondary ice production processes increase the amount of ice pellets simulated while decreasing the amount of freezing rain. Moreover, the properties of the simulated precipitation compare well with those that were measured.
Andrew DeLaFrance, Lynn A. McMurdie, Angela K. Rowe, and Andrew J. Heymsfield
Atmos. Chem. Phys., 24, 11191–11206, https://doi.org/10.5194/acp-24-11191-2024, https://doi.org/10.5194/acp-24-11191-2024, 2024
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Using a numerical model, the process whereby falling ice crystals accumulate supercooled liquid water droplets is investigated to elucidate its effects on radar-based measurements and surface precipitation. We demonstrate that this process accounted for 55% of the precipitation during a wintertime storm and is uniquely discernable from other ice crystal growth processes in Doppler velocity measurements. These results have implications for measurements from airborne and spaceborne platforms.
Gabriella Wallentin, Annika Oertel, Luisa Ickes, Peggy Achtert, Matthias Tesche, and Corinna Hoose
EGUsphere, https://doi.org/10.5194/egusphere-2024-2988, https://doi.org/10.5194/egusphere-2024-2988, 2024
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Multilayer clouds are common in the Arctic but remain understudied. We use an atmospheric model to simulate multilayer cloud cases from the Arctic expedition MOSAiC 2019/2020. We find that it is complex to accurately model these cloud layers due to the lack of correct temperature and humidity profiles. The model also struggles to capture the observed cloud phase, the relative concentration of cloud droplets and cloud ice. We constrain our model to measured aerosols to mitigate this issue.
Toshi Matsui, Daniel Hernandez-Deckers, Scott E. Giangrande, Thiago S. Biscaro, Ann Fridlind, and Scott Braun
Atmos. Chem. Phys., 24, 10793–10814, https://doi.org/10.5194/acp-24-10793-2024, https://doi.org/10.5194/acp-24-10793-2024, 2024
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Using computer simulations and real measurements, we discovered that storms over the Amazon were narrower but more intense during the dry periods, producing heavier rain and more ice particles in the clouds. Our research showed that cumulus bubbles played a key role in creating these intense storms. This study can improve the representation of the effect of continental and ocean environments on tropical regions' rainfall patterns in simulations.
Ravi Kumar Reddy Addula, Ingrid de Almeida Ribeiro, Valeria Molinero, and Baron Peters
Atmos. Chem. Phys., 24, 10833–10848, https://doi.org/10.5194/acp-24-10833-2024, https://doi.org/10.5194/acp-24-10833-2024, 2024
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Ice nucleation from supercooled droplets is important in many weather and climate modeling efforts. For experiments where droplets are steadily supercooled from the freezing point, our work combines nucleation theory and survival probability analysis to predict the nucleation spectrum, i.e., droplet freezing probabilities vs. temperature. We use the new framework to extract approximately consistent rate parameters from experiments with different cooling rates and droplet sizes.
Jianhao Zhang, Yao-Sheng Chen, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 24, 10425–10440, https://doi.org/10.5194/acp-24-10425-2024, https://doi.org/10.5194/acp-24-10425-2024, 2024
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Quantifying cloud response to aerosol perturbations presents a major challenge in understanding the human impact on climate. Using a large number of process-resolving simulations of marine stratocumulus, we show that solar heating drives a negative feedback mechanism that buffers the persistent negative trend in cloud water adjustment after sunrise. This finding has implications for the dependence of the cloud cooling effect on the timing of deliberate aerosol perturbations.
Aaron Wang, Steve Krueger, Sisi Chen, Mikhail Ovchinnikov, Will Cantrell, and Raymond A. Shaw
Atmos. Chem. Phys., 24, 10245–10260, https://doi.org/10.5194/acp-24-10245-2024, https://doi.org/10.5194/acp-24-10245-2024, 2024
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We employ two methods to examine a laboratory experiment on clouds with both ice and liquid phases. The first assumes well-mixed properties; the second resolves the spatial distribution of turbulence and cloud particles. Results show that while the trends in mean properties generally align, when turbulence is resolved, liquid droplets are not fully depleted by ice due to incomplete mixing. This underscores the threshold of ice mass fraction in distinguishing mixed-phase clouds from ice clouds.
Patrick Peter, Sigrun Matthes, Christine Frömming, Patrick Jöckel, Luca Bugliaro, Andreas Giez, Martina Krämer, and Volker Grewe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2142, https://doi.org/10.5194/egusphere-2024-2142, 2024
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Our study examines how temperature and humidity representations influence contrail (-cirrus) formation criteria. Using various model setups, we identified biases that lead to overestimation of contrail formation areas. By comparing simulations with in-flight and satellite observations, we confirmed that humidity threshold choices greatly affect contrail predictions. These findings can help develop strategies for climate-optimized flight routes, potentially reducing aviation's climate effect.
Theresa Kiszler, Davide Ori, and Vera Schemann
Atmos. Chem. Phys., 24, 10039–10053, https://doi.org/10.5194/acp-24-10039-2024, https://doi.org/10.5194/acp-24-10039-2024, 2024
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Microphysical processes impact the phase-partitioning of clouds. In this study we evaluate these processes while focusing on low-level Arctic clouds. To achieve this we used an extensive simulation set in combination with a new diagnostic tool. This study presents our findings on the relevance of these processes and their behaviour under different thermodynamic regimes.
Shuaiqi Tang, Hailong Wang, Xiang-Yu Li, Jingyi Chen, Armin Sorooshian, Xubin Zeng, Ewan Crosbie, Kenneth L. Thornhill, Luke D. Ziemba, and Christiane Voigt
Atmos. Chem. Phys., 24, 10073–10092, https://doi.org/10.5194/acp-24-10073-2024, https://doi.org/10.5194/acp-24-10073-2024, 2024
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We examined marine boundary layer clouds and their interactions with aerosols in the E3SM single-column model (SCM) for a case study. The SCM shows good agreement when simulating the clouds with high-resolution models. It reproduces the relationship between cloud droplet and aerosol particle number concentrations as produced in global models. However, the relationship between cloud liquid water and droplet number concentration is different, warranting further investigation.
Suf Lorian and Guy Dagan
Atmos. Chem. Phys., 24, 9323–9338, https://doi.org/10.5194/acp-24-9323-2024, https://doi.org/10.5194/acp-24-9323-2024, 2024
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We examine the combined effect of aerosols and sea surface temperature (SST) on clouds under equilibrium conditions in cloud-resolving radiative–convective equilibrium simulations. We demonstrate that the aerosol–cloud interaction's effect on top-of-atmosphere energy gain strongly depends on the underlying SST, while the shortwave part of the spectrum is significantly more sensitive to SST. Furthermore, increasing aerosols influences upper-troposphere stability and thus anvil cloud fraction.
Jianqi Zhao, Xiaoyan Ma, Johannes Quaas, and Hailing Jia
Atmos. Chem. Phys., 24, 9101–9118, https://doi.org/10.5194/acp-24-9101-2024, https://doi.org/10.5194/acp-24-9101-2024, 2024
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We explore aerosol–cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean in winter based on the WRF-Chem–SBM model, which couples a spectral-bin microphysics scheme and an online aerosol module. Our study highlights the differences in aerosol–cloud interactions between land and ocean and between precipitation clouds and non-precipitation clouds, and it differentiates and quantifies their underlying mechanisms.
Cited articles
Abel, S. J., Boutle, I. A., Waite, K., Fox, S., Brown, P. R. A., Cotton, R., Lloyd, G., Choularton, T. W., and Bower, K. N.: The Role of Precipitation in Controlling the Transition from Stratocumulus to Cumulus Clouds in a Northern Hemisphere Cold-Air Outbreak, J. Atmos. Sci., 74, 2293–2314, https://doi.org/10.1175/JAS-D-16-0362.1, 2017. a
Ackermann, L., Danek, C., Gierz, P., and Lohmann, G.: AMOC Recovery in a Multicentennial Scenario Using a Coupled Atmosphere-Ocean-Ice Sheet Model, Geophys. Res. Lett., 47, e2019GL086810, https://doi.org/10.1029/2019GL086810, 2020. a
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, https://doi.org/10.1038/nature04141, 2005. a
Bennartz, R., Shupe, M. D., Turner, D. D., Walden, V. P., Steffen, K., Cox, C. J., Kulie, M. S., Miller, N. B., and Pettersen, C.: July 2012 Greenland melt extent enhanced by low-level liquid clouds, Nature, 496, 83–86, https://doi.org/10.1038/nature12002, 2013. a
Bergeron, T.: Über die dreidimensional verknüpfende Wetteranalyse, Det Norske videnskapsakademi i Oslo, Geofysiske publikasjoner, 5, 1–111, Nkr 14.60, 1928. a
Bjordal, J., Storelvmo, T., Alterskjær, K., and Carlsen, T.: Equilibrium climate sensitivity above 5 °C plausible due to state-dependent cloud feedback, Nat. Geosci., 13, 718–721, https://doi.org/10.1038/s41561-020-00649-1, 2020. a
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.: COSP: Satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011. a
Boisvert, L. N., Webster, M. A., Petty, A. A., Markus, T., Bromwich, D. H., and Cullather, R. I.: Intercomparison of Precipitation Estimates over the Arctic Ocean and Its Peripheral Seas from Reanalyses, J. Climate, 31, 8441–8462, https://doi.org/10.1175/JCLI-D-18-0125.1, 2018. a, b
Bokhorst, S., Pedersen, S. H., Brucker, L., Anisimov, O., Bjerke, J. W., Brown, R. D., Ehrich, D., Essery, R. L. H., Heilig, A., Ingvander, S., Johansson, C., Johansson, M., Jónsdóttir, I. S., Inga, N., Luojus, K., Macelloni, G., Mariash, H., McLennan, D., Rosqvist, G. N., Sato, A., Savela, H., Schneebeli, M., Sokolov, A., Sokratov, S. A., Terzago, S., Vikhamar-Schuler, D., Williamson, S., Qiu, Y., and Callaghan, T. V.: Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts, Ambio, 45, 516–537, https://doi.org/10.1007/s13280-016-0770-0, 2016. a
Boucher, O., Denvil, S., Levavasseur, G., Cozic, A., Caubel, A., Foujols, M.-A., Meurdesoif, Y., Cadule, P., Devilliers, M., Ghattas, J., Lebas, N., Lurton, T., Mellul, L., Musat, I., Mignot, J., and Cheruy, F.: IPSL IPSL-CM6A-LR model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.5195, variable versions: clw (20180804), tas (20180711), prsn (20180711), areacella (20180711), 2018. a
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., Bekki, S., Bonnet, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Caubel, A., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., D'Andrea, F., Davini, P., de Lavergne, C., Denvil, S., Deshayes, J., Devilliers, M., Ducharne, A., Dufresne, J.-L., Dupont, E., Éthé, C., Fairhead, L., Falletti, L., Flavoni, S., Foujols, M.-A., Gardoll, S., Gastineau, G., Ghattas, J., Grandpeix, J.-Y., Guenet, B., Guez, Lionel, E., Guilyardi, E., Guimberteau, M., Hauglustaine, D., Hourdin, F., Idelkadi, A., Joussaume, S., Kageyama, M., Khodri, M., Krinner, G., Lebas, N., Levavasseur, G., Lévy, C., Li, L., Lott, F., Lurton, T., Luyssaert, S., Madec, G., Madeleine, J.-B., Maignan, F., Marchand, M., Marti, O., Mellul, L., Meurdesoif, Y., Mignot, J., Musat, I., Ottlé, C., Peylin, P., Planton, Y., Polcher, J., Rio, C., Rochetin, N., Rousset, C., Sepulchre, P., Sima, A., Swingedouw, D., Thiéblemont, R., Traore, A. K., Vancoppenolle, M., Vial, J., Vialard, J., Viovy, N., and Vuichard, N.: Presentation and Evaluation of the IPSL-CM6A-LR Climate Model, J. Adv. Model. Earth Sy., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010, 2020a. a
Boucher, O., Denvil, S., Levavasseur, G., Cozic, A., Caubel, A., Foujols, M.-A., Meurdesoif, Y., Balkanski, Y., Checa-Garcia, R., Hauglustaine, D., Bekki, S., and Marchand, M.: IPSL IPSL-CM5A2-INCA model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.13661, variable versions: clw (20200608), tas (20200528), prsn (20200528), areacella (20200528), 2020b. a
Bruno, O., Hoose, C., Storelvmo, T., Coopman, Q., and Stengel, M.: Exploring the Cloud Top Phase Partitioning in Different Cloud Types Using Active and Passive Satellite Sensors, Geophys. Res. Lett., 48, e2020GL089863, https://doi.org/10.1029/2020GL089863, 2021. a, b
Callaghan, T. V., Johansson, M., Brown, R. D., Groisman, P. Y., Labba, N., Radionov, V., Bradley, R. S., Blangy, S., Bulygina, O. N., Christensen, T. R., Colman, J. E., Essery, R. L. H., Forbes, B. C., Forchhammer, M. C., Golubev, V. N., Honrath, R. E., Juday, G. P., Meshcherskaya, A. V., Phoenix, G. K., Pomeroy, J., Rautio, A., Robinson, D. A., Schmidt, N. M., Serreze, M. C., Shevchenko, V. P., Shiklomanov, A. I., Shmakin, A. B., Sköld, P., Sturm, M., Woo, M.-k., and Wood, E. F.: Multiple Effects of Changes in Arctic Snow Cover, AMBIO, 40, 32–45, https://doi.org/10.1007/s13280-011-0213-x, 2011. a
Carlsen, T. and David, R. O.: Spaceborne Evidence That Ice-Nucleating Particles Influence High-Latitude Cloud Phase, Geophys. Res. Lett., 49, e2022GL098041, https://doi.org/10.1029/2022GL098041, 2022. a
Carlsen, T., Birnbaum, G., Ehrlich, A., Freitag, J., Heygster, G., Istomina, L., Kipfstuhl, S., Orsi, A., Schäfer, M., and Wendisch, M.: Comparison of different methods to retrieve optical-equivalent snow grain size in central Antarctica, The Cryosphere, 11, 2727–2741, https://doi.org/10.5194/tc-11-2727-2017, 2017. a
Cesana, G., Kay, J. E., Chepfer, H., English, J. M., and de Boer, G.: Ubiquitous low-level liquid-containing Arctic clouds: New observations and climate model constraints from CALIPSO-GOCCP, Geophys. Res. Lett., 39, L20804, https://doi.org/10.1029/2012GL053385, 2012. a, b, c
Cesana, G., Waliser, D. E., Jiang, X., and Li, J.-L. F.: Multimodel evaluation of cloud phase transition using satellite and reanalysis data, J. Geophys. Res.-Atmos., 120, 7871–7892, https://doi.org/10.1002/2014JD022932, 2015. a, b, c, d
Chen, H., Sun, J., and Lin, W.: Anthropogenic influence would increase intense snowfall events over parts of the Northern Hemisphere in the future, Environ. Res. Lett., 15, 114022, https://doi.org/10.1088/1748-9326/abbc93, publisher: IOP Publishing, 2020. a, b, c, d
CIRA: 2C-SNOW-PROFILE: CloudSat Snow Profile, Colorado State University, Cooperative Institute for Research in the Atmosphere (CIRA), https://www.cloudsat.cira.colostate.edu/data-products/2c-snow-profile, last access: 31 March 2018. a
CIRA: 2B-CLDCLASS-LIDAR: Cloud Classification and Cloud Properties from Lidar, Colorado State University, Cooperative Institute for Research in the Atmosphere (CIRA), https://www.cloudsat.cira.colostate.edu/data-products/2b-cldclass-lidar, last access: 24 February 2019a. a
CIRA: ECMWF Auxiliary Data for CloudSat, Colorado State University, Cooperative Institute for Research in the Atmosphere (CIRA), https://www.cloudsat.cira.colostate.edu/data-products/ecmwf-aux, last access: 25 September 2019b. a
Copernicus Climate Change Service (C3S): ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) [data set], variables downloaded: Total column cloud liquid water, Total column rain water, 2m temperature, Mean snowfall rate, retrieved May 2023, https://doi.org/10.24381/cds.adbb2d47, 2018. a, b
Costa, A., Meyer, J., Afchine, A., Luebke, A., Günther, G., Dorsey, J. R., Gallagher, M. W., Ehrlich, A., Wendisch, M., Baumgardner, D., Wex, H., and Krämer, M.: Classification of Arctic, midlatitude and tropical clouds in the mixed-phase temperature regime, Atmos. Chem. Phys., 17, 12219–12238, https://doi.org/10.5194/acp-17-12219-2017, 2017. a
Crameri, F.: Scientific colour maps, 1.4, Zenodo [code], https://doi.org/10.5281/zenodo.8409685, 2018. a
Cucchi, M., Amici, A., Mavel, V., Bergeron, C., Brookshaw, A., Comyn-Platt, E., and Cagnazzo, C.: Daily statistics calculated from ERA5 data, https://datastore.copernicus-climate.eu/documents/app-c3s-daily-era5-statistics/C3S_Application-Documentation_ERA5-daily-statistics-v2.pdf (last access: 12 October 2022), 2021. a
Daloz, A. S., Mateling, M., L'Ecuyer, T., Kulie, M., Wood, N. B., Durand, M., Wrzesien, M., Stjern, C. W., and Dimri, A. P.: How much snow falls in the world's mountains? A first look at mountain snowfall estimates in A-train observations and reanalyses, The Cryosphere, 14, 3195–3207, https://doi.org/10.5194/tc-14-3195-2020, 2020. a, b, c, d
Danco, J. F., DeAngelis, A. M., Raney, B. K., and Broccoli, A. J.: Effects of a Warming Climate on Daily Snowfall Events in the Northern Hemisphere, J. Climate, 29, 6295–6318, https://doi.org/10.1175/JCLI-D-15-0687.1, 2016. a, b
Danek, C., Shi, X., Stepanek, C., Yang, H., Barbi, D., Hegewald, J., and Lohmann, G.: AWI AWI-ESM1.1LR model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.9328, variable versions: clw (20200401), tas (20200401), prsn (20200401), areacella (20200401), 2020. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D., Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: Predicting global atmospheric ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci. USA, 107, 11217–11222, https://doi.org/10.1073/pnas.0910818107, 2010. a
Douville, H., Raghavan, K., Renwick, J., Allan, R., Arias, P., Barlow, M., Cerezo-Mota, R., Cherchi, A., Gan, T., Gergis, J., Jiang, D., Khan, A., Pokam Mba, W., Rosenfeld, D., Tierney, J., and Zolina, O.: Chapter 8: Water Cycle Changes, 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., 1055–1210, Cambridge University Press, Cambridge, https://doi.org/10.1017/9781009157896.010, 2023. a
Edel, L., Claud, C., Genthon, C., Palerme, C., Wood, N., L’Ecuyer, T., and Bromwich, D.: Arctic Snowfall from CloudSat Observations and Reanalyses, J. Climate, 33, 2093–2109, https://doi.org/10.1175/JCLI-D-19-0105.1, 2020. a, b, c, d
Ehrlich, A., Wendisch, M., Bierwirth, E., Gayet, J.-F., Mioche, G., Lampert, A., and Mayer, B.: Evidence of ice crystals at cloud top of Arctic boundary-layer mixed-phase clouds derived from airborne remote sensing, Atmos. Chem. Phys., 9, 9401–9416, https://doi.org/10.5194/acp-9-9401-2009, 2009. a
Eisenberg, D. and Warner, K. E.: Effects of Snowfalls on Motor Vehicle Collisions, Injuries, and Fatalities, Am. J. Public Health, 95, 120–124, https://doi.org/10.2105/AJPH.2004.048926, 2005. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b
Findeisen, W.: Die kolloidmeteorologischen Vorgänge bei der Niederschlagsbildung (Colloidal meteorological processes in the formation of precipitation), Meteorol. Z., 121–133, https://doi.org/10.1127/metz/2015/0675, translated and edited by: Volken, E., Giesche, A. M., and Brönnimann, S., Meteorol. Z., 24 (2015), Schweizerbart'sche Verlagsbuchhandlung, 1938. a
Fletcher, J. K., Mason, S., and Jakob, C.: A Climatology of Clouds in Marine Cold Air Outbreaks in Both Hemispheres, J. Climate, 29, 6677–6692, https://doi.org/10.1175/JCLI-D-15-0783.1, 2016. a
Forbes, R. and Tompkins, A.: An improved representation of cloud and precipitation, ECMWF Newsletter, https://doi.org/10.21957/NFGULZHE, 2011. a
Forbes, R., Tompkins, A., and Untch, A.: A new prognostic bulk microphysics scheme for the IFS, ECMWF Technical Memorandum, 649, https://www.ecmwf.int/sites/default/files/elibrary/2011/9441-new-prognostic-bulk-microphysics-scheme-ifs.pdf (last access: 2 February 2022), 2011. a
Forbes, R. M. and Ahlgrimm, M.: On the Representation of High-Latitude Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model, Mon. Weather Rev., 142, 3425–3445, https://doi.org/10.1175/MWR-D-13-00325.1, 2014. a, b, c
Fox, S., Crawford, A., McCrystall, M., Stroeve, J., Lukovich, J., Loeb, N., Natanine, J., and Serreze, M.: Extreme Arctic Weather and Community Impacts in Nunavut: A Case Study of One Winter’s Storms and Lessons for Local Climate Change Preparedness, Weather Clim. Soc., 15, 881–892, https://doi.org/10.1175/WCAS-D-23-0006.1, 2023. a
Geerts, B., Giangrande, S. E., McFarquhar, G. M., Xue, L., Abel, S. J., Comstock, J. M., Crewell, S., DeMott, P. J., Ebell, K., Field, P., Hill, T. C. J., Hunzinger, A., Jensen, M. P., Johnson, K. L., Juliano, T. W., Kollias, P., Kosovic, B., Lackner, C., Luke, E., Lüpkes, C., Matthews, A. A., Neggers, R., Ovchinnikov, M., Powers, H., Shupe, M. D., Spengler, T., Swanson, B. E., Tjernström, M., Theisen, A. K., Wales, N. A., Wang, Y., Wendisch, M., and Wu, P.: The COMBLE Campaign: A Study of Marine Boundary Layer Clouds in Arctic Cold-Air Outbreaks, B. Am. Meteorol. Soc., 103, E1371–E1389, https://doi.org/10.1175/BAMS-D-21-0044.1, 2022. a
Hellmuth, F.: franzihe/CloudSat_ERA5_CMIP6_analysis: Code for “Evaluation of Biases in mid-to-high latitudes Surface Snowfall and Cloud Phase in ERA5 and CMIP6 using Satellite Observations”, (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.14179823, 2024. a
Henderson, D. S., L’Ecuyer, T., Stephens, G., Partain, P., and Sekiguchi, M.: A Multisensor Perspective on the Radiative Impacts of Clouds and Aerosols, J. Appl. Meteorol. Clim., 52, 853–871, https://doi.org/10.1175/JAMC-D-12-025.1, 2013. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
Heymsfield, A. J., Schmitt, C., Chen, C.-C.-J., Bansemer, A., Gettelman, A., Field, P. R., and Liu, C.: Contributions of the Liquid and Ice Phases to Global Surface Precipitation: Observations and Global Climate Modeling, J. Atmos. Sci., 77, 2629–2648, https://doi.org/10.1175/JAS-D-19-0352.1, 2020. a, b
Hiley, M. J., Kulie, M. S., and Bennartz, R.: Uncertainty Analysis for CloudSat Snowfall Retrievals, J. Appl. Meteorol. Clim., 50, 399–418, https://doi.org/10.1175/2010JAMC2505.1, 2011. a, b, c
Hofer, S., Tedstone, A. J., Fettweis, X., and Bamber, J. L.: Cloud microphysics and circulation anomalies control differences in future Greenland melt, Nat. Clim. Chang., 9, 523–528, https://doi.org/10.1038/s41558-019-0507-8, 2019. a
Imura, Y. and Michibata, T.: Too Frequent and Too Light Arctic Snowfall With Incorrect Precipitation Phase Partitioning in the MIROC6 GCM, J. Adv. Model. Earth Sy., 14, e2022MS003 046, https://doi.org/10.1029/2022MS003046, 2022. a, b
Jiusto, J. E. and Weickmann, H. K.: Types of snowfall, B. Am. Meteorol. Soc., 54, 1148–1162, https://doi.org/10.1175/1520-0477(1973)054<1148:TOS>2.0.CO;2, 1973. a, b
Kay, J. E., Bourdages, L., Miller, N. B., Morrison, A., Yettella, V., Chepfer, H., and Eaton, B.: Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations, J. Geophys. Res.-Atmos., 121, 4162–4176, https://doi.org/10.1002/2015JD024699, 2016. a, b, c
Keys, D. J.: Wilkinson Microwave Anisotropy Probe (WMAP) Battery Operations Problem Resolution Team (PRT), Tech. Rep. NF1676L-11245, NASA Goddard Space Flight Center, https://ntrs.nasa.gov/citations/20100030608 (last access: 7 December 2023), 2010. a
Kiszler, T., Ori, D., and Schemann, V.: Microphysical processes involving the vapour phase dominate in simulated low-level Arctic clouds, Atmos. Chem. Phys., 24, 10039–10053, https://doi.org/10.5194/acp-24-10039-2024, 2024. a
Korolev, A.: Limitations of the Wegener–Bergeron–Findeisen Mechanism in the Evolution of Mixed-Phase Clouds, J. Atmos. Sci., 64, 3372–3375, https://doi.org/10.1175/JAS4035.1, 2007. a
Korolev, A. and Milbrandt, J.: How Are Mixed-Phase Clouds Mixed?, Geophys. Res. Lett., 49, e2022GL099578, https://doi.org/10.1029/2022GL099578, 2022. a, b
Korolev, A., McFarquhar, G., Field, P. R., Franklin, C., Lawson, P., Wang, Z., Williams, E., Abel, S. J., Axisa, D., Borrmann, S., Crosier, J., Fugal, J., Krämer, M., Lohmann, U., Schlenczek, O., Schnaiter, M., and Wendisch, M.: Mixed-Phase Clouds: Progress and Challenges, Meteor. Mon., 58, 5.1–5.50, https://doi.org/10.1175/AMSMONOGRAPHS-D-17-0001.1, 2017. a, b, c
Korolev, A. V. and Mazin, I. P.: Supersaturation of Water Vapor in Clouds, J. Atmos. Sci., 60, 2957–2974, https://doi.org/10.1175/1520-0469(2003)060<2957:SOWVIC>2.0.CO;2, 2003. a
Kotarba, A. Z.: Errors in global cloud climatology due to transect sampling with the CALIPSO satellite lidar mission, Atmos. Res., 279, 106379, https://doi.org/10.1016/j.atmosres.2022.106379, 2022. a, b, c
Kulie, M. S. and Bennartz, R.: Utilizing Spaceborne Radars to Retrieve Dry Snowfall, J. Appl. Meteorol. Clim., 48, 2564–2580, https://doi.org/10.1175/2009JAMC2193.1, 2009. a
Lavers, D. A., Harrigan, S., and Prudhomme, C.: Precipitation Biases in the ECMWF Integrated Forecasting System, J. Hydrometeorol., 22, 1187–1198, https://doi.org/10.1175/JHM-D-20-0308.1, 2021. a, b, c
Lenaerts, J. T. M., Van Tricht, K., Lhermitte, S., and L'Ecuyer, T. S.: Polar clouds and radiation in satellite observations, reanalyses, and climate models, Geophys. Res. Lett., 44, 3355–3364, https://doi.org/10.1002/2016GL072242, 2017. a
Lenaerts, J. T. M., Gettelman, A., Van Tricht, K., van Kampenhout, L., and Miller, N. B.: Impact of Cloud Physics on the Greenland Ice Sheet Near-Surface Climate: A Study With the Community Atmosphere Model, J. Geophys. Res.-Atmos., 125, e2019JD031470, https://doi.org/10.1029/2019JD031470, 2020. a, b
Liu, G.: Deriving snow cloud characteristics from CloudSat observations, J. Geophys. Res.-Atmos., 113, D00A09, https://doi.org/10.1029/2007JD009766, 2008. a
Liu, Y. and Key, J. R.: Assessment of Arctic Cloud Cover Anomalies in Atmospheric Reanalysis Products Using Satellite Data, J. Climate, 29, 6065–6083, https://doi.org/10.1175/JCLI-D-15-0861.1, 2016. a
Lohmann, U. and Diehl, K.: Sensitivity Studies of the Importance of Dust Ice Nuclei for the Indirect Aerosol Effect on Stratiform Mixed-Phase Clouds, J. Atmos. Sci., 63, 968–982, https://doi.org/10.1175/JAS3662.1, 2006. a
Mateling, M. E., Pettersen, C., Kulie, M. S., and L’Ecuyer, T. S.: Marine Cold-Air Outbreak Snowfall in the North Atlantic: A CloudSat Perspective, J. Geophys. Res.-Atmos., 128, e2022JD038053, https://doi.org/10.1029/2022JD038053, 2023. a
Matus, A. V. and L'Ecuyer, T. S.: The role of cloud phase in Earth's radiation budget, J. Geophys. Res.-Atmos., 122, 2559–2578, https://doi.org/10.1002/2016JD025951, 2017. a, b, c, d
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., Brovkin, V., Claussen, M., Crueger, T., Esch, M., Fast, I., Fiedler, S., Fläschner, D., Gayler, V., Giorgetta, M., Goll, D. S., Haak, H., Hagemann, S., Hedemann, C., Hohenegger, C., Ilyina, T., Jahns, T., Jimenéz-de-la Cuesta, D., Jungclaus, J., Kleinen, T., Kloster, S., Kracher, D., Kinne, S., Kleberg, D., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Möbis, B., Müller, W. A., Nabel, J. E. M. S., Nam, C. C. W., Notz, D., Nyawira, S.-S., Paulsen, H., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Popp, M., Raddatz, T. J., Rast, S., Redler, R., Reick, C. H., Rohrschneider, T., Schemann, V., Schmidt, H., Schnur, R., Schulzweida, U., Six, K. D., Stein, L., Stemmler, I., Stevens, B., von Storch, J.-S., Tian, F., Voigt, A., Vrese, P., Wieners, K.-H., Wilkenskjeld, S., Winkler, A., and Roeckner, E.: Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Sy., 11, 998–1038, https://doi.org/10.1029/2018MS001400, 2019. a
Melsheimer, C. and Spreen, G.: AMSR2 ASI sea ice concentration data, Antarctic, version 5.4 (NetCDF) (July 2012–December 2019), https://doi.org/10.1594/PANGAEA.898400, 2019a. a
Melsheimer, C. and Spreen, G.: AMSR2 ASI sea ice concentration data, Arctic, version 5.4 (NetCDF) (July 2012–December 2019), https://doi.org/10.1594/PANGAEA.898399, 2019b. a
Melsheimer, C. and Spreen, G.: AMSR-E ASI sea ice concentration data, Antarctic, version 5.4 (NetCDF) (June 2002–September 2011), https://doi.org/10.1594/PANGAEA.919778, 2020a. a
Melsheimer, C. and Spreen, G.: AMSR-E ASI sea ice concentration data, Arctic, version 5.4 (NetCDF) (June 2002–September 2011), https://doi.org/10.1594/PANGAEA.919777, 2020b. a
Milani, L., Kulie, M. S., Casella, D., Dietrich, S., L’Ecuyer, T. S., Panegrossi, G., Porcù, F., Sanò, P., and Wood, N. B.: CloudSat snowfall estimates over Antarctica and the Southern Ocean: An assessment of independent retrieval methodologies and multi-year snowfall analysis, Atmos. Res., 213, 121–135, https://doi.org/10.1016/j.atmosres.2018.05.015, 2018. a, b, c, d, e
Murray, B. J., Carslaw, K. S., and Field, P. R.: Opinion: Cloud-phase climate feedback and the importance of ice-nucleating particles, Atmos. Chem. Phys., 21, 665–679, https://doi.org/10.5194/acp-21-665-2021, 2021. a
Mülmenstädt, J., Nam, C., Salzmann, M., Kretzschmar, J., L’Ecuyer, T. S., Lohmann, U., Ma, P.-L., Myhre, G., Neubauer, D., Stier, P., Suzuki, K., Wang, M., and Quaas, J.: Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes, Sci. Adv., 6, eaaz6433, https://doi.org/10.1126/sciadv.aaz6433, 2020. a, b, c
Mülmenstädt, J., Salzmann, M., Kay, J. E., Zelinka, M. D., Ma, P.-L., Nam, C., Kretzschmar, J., Hörnig, S., and Quaas, J.: An underestimated negative cloud feedback from cloud lifetime changes, Nat. Clim. Chang., 11, 508–513, https://doi.org/10.1038/s41558-021-01038-1, 2021. a, b
Notz, D. and Stroeve, J.: Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission, Science, 354, 747–750, https://doi.org/10.1126/science.aag2345, 2016. a
Papritz, L. and Sodemann, H.: Characterizing the Local and Intense Water Cycle during a Cold Air Outbreak in the Nordic Seas, Mon. Weather Rev., 146, 3567–3588, https://doi.org/10.1175/MWR-D-18-0172.1, 2018. a
Picard, G., Domine, F., Krinner, G., Arnaud, L., and Lefebvre, E.: Inhibition of the positive snow-albedo feedback by precipitation in interior Antarctica, Nat. Clim. Change, 2, 795–798, https://doi.org/10.1038/nclimate1590, 2012. a
Proske, U., Bessenbacher, V., Dedekind, Z., Lohmann, U., and Neubauer, D.: How frequent is natural cloud seeding from ice cloud layers (< −35 °C) over Switzerland?, Atmos. Chem. Phys., 21, 5195–5216, https://doi.org/10.5194/acp-21-5195-2021, 2021. a
Quante, L., Willner, S. N., Middelanis, R., and Levermann, A.: Regions of intensification of extreme snowfall under future warming, Sci. Rep., 11, 16 621, https://doi.org/10.1038/s41598-021-95979-4, 2021. a
Ridley, J., Menary, M., Kuhlbrodt, T., Andrews, M., and Andrews, T.: MOHC HadGEM3-GC31-LL model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6109, variable versions: clw (20210313), tas (20210312), prsn (20210312), phalf (20210313), 2019. a
Roberts, M. J., Baker, A., Blockley, E. W., Calvert, D., Coward, A., Hewitt, H. T., Jackson, L. C., Kuhlbrodt, T., Mathiot, P., Roberts, C. D., Schiemann, R., Seddon, J., Vannière, B., and Vidale, P. L.: Description of the resolution hierarchy of the global coupled HadGEM3-GC3.1 model as used in CMIP6 HighResMIP experiments, Geosci. Model Dev., 12, 4999–5028, https://doi.org/10.5194/gmd-12-4999-2019, 2019. a
Rosenfeld, D., Yu, X., Liu, G., Xu, X., Zhu, Y., Yue, Z., Dai, J., Dong, Z., Dong, Y., and Peng, Y.: Glaciation temperatures of convective clouds ingesting desert dust, air pollution and smoke from forest fires, Geophys. Res. Lett., 38, L21804, https://doi.org/10.1029/2011GL049423, 2011. a
Roussel, M.-L., Lemonnier, F., Genthon, C., and Krinner, G.: Brief communication: Evaluating Antarctic precipitation in ERA5 and CMIP6 against CloudSat observations, The Cryosphere, 14, 2715–2727, https://doi.org/10.5194/tc-14-2715-2020, 2020. a, b, c, d
Sassen, K., Wang, Z., and Liu, D.: Global distribution of cirrus clouds from CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements, J. Geophys. Res.-Atmos., 113, https://doi.org/10.1029/2008JD009972, 2008. a
Schirmacher, I., Kollias, P., Lamer, K., Mech, M., Pfitzenmaier, L., Wendisch, M., and Crewell, S.: Assessing Arctic low-level clouds and precipitation from above – a radar perspective, Atmos. Meas. Tech., 16, 4081–4100, https://doi.org/10.5194/amt-16-4081-2023, 2023. a
Scott, D., Dawson, J., and Jones, B.: Climate change vulnerability of the US Northeast winter recreation– tourism sector, Mitig. Adapt. Strateg. Glob. Change, 13, 577–596, https://doi.org/10.1007/s11027-007-9136-z, 2008. a
Seferian, R.: CNRM-CERFACS CNRM-ESM2-1 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4068, variable versions: clw (20180805), tas (20180610), prsn (20180714), areacella (20180903), 2018. a
Sellar, A. A., Jones, C. G., Mulcahy, J. P., Tang, Y., Yool, A., Wiltshire, A., O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., de Mora, L., Kuhlbrodt, T., Rumbold, S. T., Kelley, D. I., Ellis, R., Johnson, C. E., Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald, A. T., Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M., Edwards, J., Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B., Hendry, M. A., Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble, J., Liddicoat, S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson, E., Siahaan, A., Smith, R. S., Swaminathan, R., Woodhouse, M. T., Zeng, G., and Zerroukat, M.: UKESM1: Description and Evaluation of the U.K. Earth System Model, J. Adv. Model. Earth Sy., 11, 4513–4558, https://doi.org/10.1029/2019MS001739, 2019. a
Sepulchre, P., Caubel, A., Ladant, J.-B., Bopp, L., Boucher, O., Braconnot, P., Brockmann, P., Cozic, A., Donnadieu, Y., Dufresne, J.-L., Estella-Perez, V., Ethé, C., Fluteau, F., Foujols, M.-A., Gastineau, G., Ghattas, J., Hauglustaine, D., Hourdin, F., Kageyama, M., Khodri, M., Marti, O., Meurdesoif, Y., Mignot, J., Sarr, A.-C., Servonnat, J., Swingedouw, D., Szopa, S., and Tardif, D.: IPSL-CM5A2 – an Earth system model designed for multi-millennial climate simulations, Geosci. Model Dev., 13, 3011–3053, https://doi.org/10.5194/gmd-13-3011-2020, 2020. a
Shaw, J., McGraw, Z., Bruno, O., Storelvmo, T., and Hofer, S.: Using Satellite Observations to Evaluate Model Microphysical Representation of Arctic Mixed-Phase Clouds, Geophys. Res. Lett., 49, e2021GL096191, https://doi.org/10.1029/2021GL096191, 2022. a, b
Shupe, M. D. and Intrieri, J. M.: Cloud Radiative Forcing of the Arctic Surface: The Influence of Cloud Properties, Surface Albedo, and Solar Zenith Angle, J. Climate, 17, 616–628, https://doi.org/10.1175/1520-0442(2004)017<0616:CRFOTA>2.0.CO;2, 2004. a
Shupe, M. D., Turner, D. D., Walden, V. P., Bennartz, R., Cadeddu, M. P., Castellani, B. B., Cox, C. J., Hudak, D. R., Kulie, M. S., Miller, N. B., Neely, R. R., Neff, W. D., and Rowe, P. M.: High and Dry: New Observations of Tropospheric and Cloud Properties above the Greenland Ice Sheet, B. Am. Meteorol. Soc., 94, 169–186, https://doi.org/10.1175/BAMS-D-11-00249.1, 2013. a
Simmons, A., Uppala, S., Dee, D., and Kobayashi, S.: ERA-Interim: New ECMWF reanalysis products from 1989 onwards, https://doi.org/10.21957/pocnex23c6, 2007. a
Spreen, G., Kaleschke, L., and Heygster, G.: Sea ice remote sensing using AMSR-E 89-GHz channels, J. Geophys. Res.-Oceans, 113, C02S03, https://doi.org/10.1029/2005JC003384, 2008. a, b
Stanford, M. W., Fridlind, A. M., Silber, I., Ackerman, A. S., Cesana, G., Mülmenstädt, J., Protat, A., Alexander, S., and McDonald, A.: Earth-system-model evaluation of cloud and precipitation occurrence for supercooled and warm clouds over the Southern Ocean's Macquarie Island, Atmos. Chem. Phys., 23, 9037–9069, https://doi.org/10.5194/acp-23-9037-2023, 2023. a
Stephens, G. L. and Kummerow, C. D.: The Remote Sensing of Clouds and Precipitation from Space: A Review, J. Atmos. Sci., 64, 3742–3765, https://doi.org/10.1175/2006JAS2375.1, 2007. a, b, c
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z., Illingworth, A. J., O'connor, E. J., Rossow, W. B., Durden, S. L., Miller, S. D., Austin, R. T., Benedetti, A., and Mitrescu, C.: The cloudsat mission and the a-train, Bull. Amer. Meteor. Soc., 83, 1771–1790, https://doi.org/10.1175/BAMS-83-12-1771, 2002. a, b
Storelvmo, T. and Tan, I.: The Wegener-Bergeron-Findeisen process – Its discovery and vital importance for weather and climate, Meteorol. Z., 24, 455–461, https://doi.org/10.1127/metz/2015/0626, 2015. a, b
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019a. a
Swart, N. C., Cole, J. N., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M.: CCCma CanESM5 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.3610, variable versions: clw (20190429), tas (20190429), prsn (20190429), areacella (20190429), 2019b. a
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A., Colin, J., Decharme, B., Delire, C., Berthet, S., Chevallier, M., Sénési, S., Franchisteguy, L., Vial, J., Mallet, M., Joetzjer, E., Geoffroy, O., Guérémy, J.-F., Moine, M.-P., Msadek, R., Ribes, A., Rocher, M., Roehrig, R., Salas-y Mélia, D., Sanchez, E., Terray, L., Valcke, S., Waldman, R., Aumont, O., Bopp, L., Deshayes, J., Éthé, C., and Madec, G.: Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in Present-Day and Future Climate, J. Adv. Model. Earth Sy., 11, 4182–4227, https://doi.org/10.1029/2019MS001791, 2019. a
Tan, I. and Storelvmo, T.: Sensitivity Study on the Influence of Cloud Microphysical Parameters on Mixed-Phase Cloud Thermodynamic Phase Partitioning in CAM5, J. Atmos. Sci., 73, 709–728, https://doi.org/10.1175/JAS-D-15-0152.1, 2016. a, b, c
Tang, Y., Rumbold, S., Ellis, R., Kelley, D., Mulcahy, J., Sellar, A., Walton, J., and Jones, C.: MOHC UKESM1.0-LL model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6113, variable versions: clw (20191114), tas (20191105), prsn (20191105), phalf (20191114), 2019. a
Tatebe, H. and Watanabe, M.: MIROC MIROC6 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.5603, variable versions: clw (20191127), tas (20190830), prsn (20190830), areacella (20190218), 2018. a
Tatebe, H., Ogura, T., Nitta, T., Komuro, Y., Ogochi, K., Takemura, T., Sudo, K., Sekiguchi, M., Abe, M., Saito, F., Chikira, M., Watanabe, S., Mori, M., Hirota, N., Kawatani, Y., Mochizuki, T., Yoshimura, K., Takata, K., O'ishi, R., Yamazaki, D., Suzuki, T., Kurogi, M., Kataoka, T., Watanabe, M., and Kimoto, M.: Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6, Geosci. Model Dev., 12, 2727–2765, https://doi.org/10.5194/gmd-12-2727-2019, 2019. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the Experiment Design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a
Vergara-Temprado, J., Miltenberger, A. K., Furtado, K., Grosvenor, D. P., Shipway, B. J., Hill, A. A., Wilkinson, J. M., Field, P. R., Murray, B. J., and Carslaw, K. S.: Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles, P. Natl. Acad. Sci. USA, 115, 2687–2692, https://doi.org/10.1073/pnas.1721627115, 2018. a, b
Voldoire, A.: CMIP6 simulations of the CNRM-CERFACS based on CNRM-CM6-1 model for CMIP experiment historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4066, variable versions: clw (20180724), tas (20180620), prsn (20180713), areacella (20180701), 2018. a
Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M., Colin, J., Guérémy, J.-F., Michou, M., Moine, M.-P., Nabat, P., Roehrig, R., Salas y Mélia, D., Séférian, R., Valcke, S., Beau, I., Belamari, S., Berthet, S., Cassou, C., Cattiaux, J., Deshayes, J., Douville, H., Ethé, C., Franchistéguy, L., Geoffroy, O., Lévy, C., Madec, G., Meurdesoif, Y., Msadek, R., Ribes, A., Sanchez-Gomez, E., Terray, L., and Waldman, R.: Evaluation of CMIP6 DECK Experiments With CNRM-CM6-1, J. Adv. Model. Earth Sy., 11, 2177–2213, https://doi.org/10.1029/2019MS001683, 2019. a
von Lerber, A., Mech, M., Rinke, A., Zhang, D., Lauer, M., Radovan, A., Gorodetskaya, I., and Crewell, S.: Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic, Atmos. Chem. Phys., 22, 7287–7317, https://doi.org/10.5194/acp-22-7287-2022, 2022. a, b, c
Wang, C., Graham, R. M., Wang, K., Gerland, S., and Granskog, M. A.: Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution, The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, 2019. a, b
Wang, Z. and Sassen, K.: Level 2 Cloud Scenario Classification Product Process Description and Interface Control Document, Tech. rep., A NASA Earth System Science Pathfinder Mission, 1, 2019. a
Warren, S. G., Hahn, C. J., London, J., Chervin, R. M., Jenne, R. L.: Global distribution of total cloud cover and cloud type amounts over the ocean, Tech. Rep., DOE/ER-0406, NCAR/TN-317-STR, USDOE Office of Energy Research, Washington, DC (USA), Carbon Dioxide Research Div., National Center for Atmospheric Research, Boulder, CO, USA, https://doi.org/10.2172/5415329, 1988. a, b
Wegener, A.: Thermodynamik der Atmosphäre, Nature, 90, 31–31, https://doi.org/10.1038/090031a0, 1912. a
Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner, M., Legutke, S., Schupfner, M., Wachsmann, F., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6595, variable versions: clw (20210923), tas (20210923), prsn (20210923), areacella (20210923), 2019. a
Winker, D. M., Hunt, W. H., and McGill, M. J.: Initial performance assessment of CALIOP, Geophys. Res. Lett., 34, L19803, https://doi.org/10.1029/2007GL030135, 2007. a
Winker, D. M., Pelon, J., Coakley, J. A., Ackerman, S. A., Charlson, R. J., Colarco, P. R., Flamant, P., Fu, Q., Hoff, R. M., Kittaka, C., Kubar, T. L., Treut, H. L., Mccormick, M. P., Mégie, G., Poole, L., Powell, K., Trepte, C., Vaughan, M. A., and Wielicki, B. A.: The CALIPSO Mission: A Global 3D View of Aerosols and Clouds, B. Am. Meteorol. Soc., 91, 1211–1230, https://doi.org/10.1175/2010BAMS3009.1, 2010. a, b
Wood, N. B., L'Ecuyer, T. S., Heymsfield, A. J., Stephens, G. L., Hudak, D. R., and Rodriguez, P.: Estimating snow microphysical properties using collocated multisensor observations, J. Geophys. Res.-Atmos., 119, 8941–8961, https://doi.org/10.1002/2013JD021303, 2014. a, b
Young, G., Connolly, P. J., Jones, H. M., and Choularton, T. W.: Microphysical sensitivity of coupled springtime Arctic stratocumulus to modelled primary ice over the ice pack, marginal ice, and ocean, Atmos. Chem. Phys., 17, 4209–4227, https://doi.org/10.5194/acp-17-4209-2017, 2017. a
Zelinka, M. D., Myers, T. A., McCoy, D. T., Po-Chedley, S., Caldwell, P. M., Ceppi, P., Klein, S. A., and Taylor, K. E.: Causes of Higher Climate Sensitivity in CMIP6 Models, Geophys. Res. Lett., 47, e2019GL085782, https://doi.org/10.1029/2019GL085782, 2020. a, b
Zhang, D., Wang, Z., and Liu, D.: A global view of midlevel liquid-layer topped stratiform cloud distribution and phase partition from CALIPSO and CloudSat measurements, J. Geophys. Res.-Atmos., 115, D00H13, https://doi.org/10.1029/2009JD012143, 2010. a
Zhang, T.: Influence of the seasonal snow cover on the ground thermal regime: An overview, Rev. Geophys., 43, RG4002, https://doi.org/10.1029/2004RG000157, 2005. a
Short summary
This article compares the occurrence of supercooled liquid-containing clouds (sLCCs) and their link to surface snowfall in CloudSat–CALIPSO, ERA5, and the CMIP6 models. Significant discrepancies were found, with ERA5 and CMIP6 consistently overestimating sLCC and snowfall frequency. This bias is likely due to cloud microphysics parameterization. This conclusion has implications for accurately representing cloud phase and snowfall in future climate projections.
This article compares the occurrence of supercooled liquid-containing clouds (sLCCs) and their...
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