Articles | Volume 25, issue 21
https://doi.org/10.5194/acp-25-15329-2025
© 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-25-15329-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Nov 2025
Research article |
| 10 Nov 2025
| 10 Nov 2025
The diurnal susceptibility of subtropical clouds to aerosols
Marcin J. Kurowski
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Matthew D. Lebsock
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Kevin M. Smalley
Lawrence Livermore National Laboratory, Livermore, California, USA
Related authors
Luis F. Millán, Matthew D. Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 18, 4483–4495, https://doi.org/10.5194/amt-18-4483-2025, https://doi.org/10.5194/amt-18-4483-2025, 2025
Short summary
Short summary
This study explores the potential of a hypothetical spaceborne radar to observe water vapor within clouds.
Juan Socuellamos, Matthew Lebsock, Raquel Rodriguez Monje, Marcin Kurowski, Derek Posselt, and Robert Beauchamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-4248, https://doi.org/10.5194/egusphere-2025-4248, 2025
Short summary
Short summary
Using simulated airborne and spaceborne W-band (94 GHz) and G-band (239 GHz) radar observations, this article presents an optimal estimation framework that includes dual-frequency reflectivity and differential absorption measurements to obtain more accurate drizzle retrievals. We demonstrate that an improvement of more than one order of magnitude in the retrieval of the drizzle mixing ratio, droplet concentration, and mass-weighted diameter can be achieved compared to W-band only results.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
Short summary
Short summary
In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
Short summary
Short summary
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
Short summary
Short summary
Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
Short summary
Short summary
This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
Short summary
Short summary
Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
Nitika Yadlapalli Yurk, Matt D. Lebsock, Juan M. Socuellamos, Raquel Rodriguez Monje, Ken B. Cooper, and Pavlos Kollias
Atmos. Meas. Tech., 18, 5141–5155, https://doi.org/10.5194/amt-18-5141-2025, https://doi.org/10.5194/amt-18-5141-2025, 2025
Short summary
Short summary
Current knowledge of the link between clouds and climate is limited by a lack of observations of the drop size distribution (DSD) within clouds, especially for the smallest drops. We demonstrate a method of retrieving DSDs down to small drop sizes using observations of drizzling marine layer clouds captured by the CloudCube millimeter-wave Doppler radar. We compare the shape of the observed spectra to theoretical expectations of radar echoes to solve for DSDs at each time step and elevation.
Luis F. Millán, Matthew D. Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 18, 4483–4495, https://doi.org/10.5194/amt-18-4483-2025, https://doi.org/10.5194/amt-18-4483-2025, 2025
Short summary
Short summary
This study explores the potential of a hypothetical spaceborne radar to observe water vapor within clouds.
Juan Socuellamos, Matthew Lebsock, Raquel Rodriguez Monje, Marcin Kurowski, Derek Posselt, and Robert Beauchamp
EGUsphere, https://doi.org/10.5194/egusphere-2025-4248, https://doi.org/10.5194/egusphere-2025-4248, 2025
Short summary
Short summary
Using simulated airborne and spaceborne W-band (94 GHz) and G-band (239 GHz) radar observations, this article presents an optimal estimation framework that includes dual-frequency reflectivity and differential absorption measurements to obtain more accurate drizzle retrievals. We demonstrate that an improvement of more than one order of magnitude in the retrieval of the drizzle mixing ratio, droplet concentration, and mass-weighted diameter can be achieved compared to W-band only results.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
Atmos. Meas. Tech., 17, 6965–6981, https://doi.org/10.5194/amt-17-6965-2024, https://doi.org/10.5194/amt-17-6965-2024, 2024
Short summary
Short summary
This article presents a novel technique to estimate liquid water content (LWC) profiles in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
Short summary
Short summary
This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
Short summary
Short summary
This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
Short summary
Short summary
In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
Atmos. Meas. Tech., 17, 539–559, https://doi.org/10.5194/amt-17-539-2024, https://doi.org/10.5194/amt-17-539-2024, 2024
Short summary
Short summary
In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
Matthew D. Lebsock and Mikael Witte
Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, https://doi.org/10.5194/acp-23-14293-2023, 2023
Short summary
Short summary
This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.
Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes
Atmos. Meas. Tech., 16, 3531–3546, https://doi.org/10.5194/amt-16-3531-2023, https://doi.org/10.5194/amt-16-3531-2023, 2023
Short summary
Short summary
In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.
Maria J. Chinita, Mikael Witte, Marcin J. Kurowski, Joao Teixeira, Kay Suselj, Georgios Matheou, and Peter Bogenschutz
Geosci. Model Dev., 16, 1909–1924, https://doi.org/10.5194/gmd-16-1909-2023, https://doi.org/10.5194/gmd-16-1909-2023, 2023
Short summary
Short summary
Low clouds are one of the largest sources of uncertainty in climate prediction. In this paper, we introduce the first version of the unified turbulence and shallow convection parameterization named SHOC+MF developed to improve the representation of shallow cumulus clouds in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). Here, we also show promising preliminary results in a single-column model framework for two benchmark cases of shallow cumulus convection.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
Short summary
Short summary
We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
Short summary
Short summary
Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
Short summary
Short summary
This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, https://doi.org/10.5194/amt-14-5555-2021, 2021
Short summary
Short summary
Modern and upcoming hyperspectral imagers will take images with spatial resolutions as fine as 20 m. They can retrieve column water vapour, and we show evidence that from these column measurements you can get statistics of planetary boundary layer (PBL) water vapour. This is important information for climate models that need to account for sub-grid mixing of water vapour near the surface in their PBL schemes.
David R. Thompson, Brian H. Kahn, Philip G. Brodrick, Matthew D. Lebsock, Mark Richardson, and Robert O. Green
Atmos. Meas. Tech., 14, 2827–2840, https://doi.org/10.5194/amt-14-2827-2021, https://doi.org/10.5194/amt-14-2827-2021, 2021
Short summary
Short summary
Concentrations of water vapor in the atmosphere vary dramatically over space and time. Mapping this variability can provide insights into atmospheric processes that help us understand atmospheric processes in the Earth system. Here we use a new measurement strategy based on imaging spectroscopy to map atmospheric water vapor concentrations at very small spatial scales. Experiments demonstrate the accuracy of this technique and some initial results from an airborne remote sensing experiment.
Kevin M. Smalley and Anita D. Rapp
Atmos. Chem. Phys., 21, 2765–2779, https://doi.org/10.5194/acp-21-2765-2021, https://doi.org/10.5194/acp-21-2765-2021, 2021
Short summary
Short summary
We use satellite observations of shallow cumulus clouds to investigate the influence of cloud size on the ratio of cloud water path to rainwater (WRR) in different environments. For a fixed temperature and relative humidity, WRR increases with cloud size, but it varies little with aerosols. These results imply that increasing WRR with rising temperature relates not only to deeper clouds but also to more frequent larger clouds.
Cited articles
Ackerman, A. S., Toon, O. B., Stevens, D. E., Heymsfield, A. J., Ramanathan, V., and Welton, E. J.: Reduction of tropical cloudiness by soot, Science, 288, 1042–1047, https://doi.org/10.1126/science.288.5468.1042, 2000. a
Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B.: The impact of humidity above stratiform clouds on indirect aerosol climate forcing, Nature, 432, 1014–1017, https://doi.org/10.1038/nature03174, 2004. a
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris, D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A.-L., Dufresne, J.-L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M., Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D. T., Myhre, G., Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.: Bounding Global Aerosol Radiative Forcing of Climate Change, Reviews of Geophysics, 58, e2019RG000660, https://doi.org/10.1029/2019RG000660, 2020. a, b
Berner, A. H., Bretherton, C. S., and Wood, R.: Large-eddy simulation of mesoscale dynamics and entrainment around a pocket of open cells observed in VOCALS-REx RF06, Atmos. Chem. Phys., 11, 10525–10540, https://doi.org/10.5194/acp-11-10525-2011, 2011. a
Boucher, O. and Lohmann, U.: The sulfate-CCN-cloud albedo effect: A sensitivity study with two general circulation models, Tellus B, 47, 281–300, https://doi.org/10.1034/j.1600-0889.47.issue3.1.x, 1995. a
Boucher, O., Randall, D., Artaxo, P., Bessafi, R., Dufresne, J. L., Forster, P., Kiehl, J., Klein, S. A., Knutti, R., Köhler, M., Lohmann, U., Ramaswamy, V., Sawyer, V., Shine, K., Simpson, I., Stuber, N., Vogel, B., and Zhang, X.: Clouds and Aerosols, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 571–657, https://doi.org/10.1017/cbo9781107415324.016, 2013. a
Brenguier, J.-L., Pawlowska, H., Schüller, L., Preusker, R., Fischer, J., and Fouquart, Y.: Radiative Properties of Boundary Layer Clouds: Droplet Effective Radius versus Number Concentration, Journal of the Atmospheric Sciences, 57, 803–821, https://doi.org/10.1175/1520-0469(2000)057<0803:RPOBLC>2.0.CO;2, 2000. a
Bretherton, C. S., Blossey, P. N., and Uchida, J.: Cloud droplet sedimentation, entrainment efficiency, and subtropical stratocumulus albedo, Geophysical Research Letters, 34, https://doi.org/https://doi.org/10.1029/2006GL027648, 2007. a
Christensen, M. W. and Stephens, G. L.: Microphysical and macrophysical responses of marine stratocumulus polluted by underlying ships: 2. Impacts of haze on precipitating clouds, Journal of Geophysical Research: Atmospheres, 117, https://doi.org/https://doi.org/10.1029/2011JD017125, 2012. a
Christensen, M. W., Neubauer, D., Poulsen, C. A., Thomas, G. E., McGarragh, G. R., Povey, A. C., Proud, S. R., and Grainger, R. G.: Unveiling aerosol–cloud interactions – Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate, Atmos. Chem. Phys., 17, 13151–13164, https://doi.org/10.5194/acp-17-13151-2017, 2017. a
Coakley, J. A. and Walsh, C. D.: Limits to the Aerosol Indirect Radiative Effect Derived from Observations of Ship Tracks, Journal of the Atmospheric Sciences, 59, 668–680, 2002. a
Diamond, M. S., Director, H. M., Eastman, R., Possner, A., and Wood, R.: Substantial Cloud Brightening From Shipping in Subtropical Low Clouds, AGU Advances, 1, e2019AV000111, https://doi.org/https://doi.org/10.1029/2019AV000111, 2020. a
Erfani, E., Blossey, P., Wood, R., Mohrmann, J., Doherty, S. J., Wyant, M., and O, K.-T.: Simulating Aerosol Lifecycle Impacts on the Subtropical Stratocumulus-to-Cumulus Transition Using Large-Eddy Simulations, Journal of Geophysical Research: Atmospheres, 127, e2022JD037258, https://doi.org/https://doi.org/10.1029/2022JD037258, 2022. a
Fan, J., Wang, Y., Rosenfeld, D., and Liu, X.: Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges, Journal of the Atmospheric Sciences, 73, 4221–4252, https://doi.org/10.1175/JAS-D-16-0037.1, 2016. a
Feingold, G., Cotton, W. R., Stevens, B., and Frisch, A. S.: The relationship between drop in-cloud residence time and drizzle production in numerically simulated stratocumulus clouds, Journal of the Atmospheric Sciences, 53, 1108–1122, https://doi.org/10.1175/1520-0469(1996)053<1108:TRBDIC>2.0.CO;2, 1999. a
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Journal of Climate, 30, 5419–5454, 2017. a
Gryspeerdt, E., Quaas, J., and Bellouin, N.: Constraining the aerosol influence on cloud fraction, Journal of Geophysical Research: Atmospheres, 121, 3566–3583, 2016. a
Gryspeerdt, E., Glassmeier, F., Feingold, G., Hoffmann, F., and Murray-Watson, R. J.: Observing short-timescale cloud development to constrain aerosol–cloud interactions, Atmos. Chem. Phys., 22, 11727–11738, https://doi.org/10.5194/acp-22-11727-2022, 2022. a, b
Haman, K. E., Malinowski, S. P., Kurowski, M. J., Gerber, H., and Brenguier, J.-L.: Small scale mixing processes at the top of a marine stratocumulus – a case study, Quarterly Journal of the Royal Meteorological Society, 133, 213–226, 2007. a
Han, Q., Rossow, W. B., Zeng, J., and Welch, R.: Three Different Behaviors of Liquid Water Path of Water Clouds in Aerosol–Cloud Interactions, Journal of the Atmospheric Sciences, 59, 726–735, 2002. a
Henyey, L. G. and Greenstein, J. L.: Diffuse radiation in the galaxy, Astrophysical Journal, 93, 70–83, https://doi.org/10.1086/144246, 1941. a
Hoffmann, F., Glassmeier, F., Yamaguchi, T., and Feingold, G.: Liquid Water Path Steady States in Stratocumulus: Insights from Process-Level Emulation and Mixed-Layer Theory, Journal of the Atmospheric Sciences, 77, 2203–2215, 2020. a
Hoffmann, F., Glassmeier, F., Yamaguchi, T., and Feingold, G.: On the Roles of Precipitation and Entrainment in Stratocumulus Transitions between Mesoscale States, Journal of the Atmospheric Sciences, 80, 2791–2803, https://doi.org/10.1175/JAS-D-22-0268.1, 2023. a
IPCC: Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157896, 2021. a
IPCC: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157926, 2022. a
Jiang, H., Feingold, G., and Cotton, W. R.: Simulations of aerosol-cloud-dynamical feedbacks resulting from entrainment of aerosol into the marine boundary layer during the Atlantic Stratocumulus Transition Experiment, Journal of Geophysical Research: Atmospheres, 107, AAC 17-1–AAC 17-13, https://doi.org/10.1029/2001JD001502, 2002. a
Khairoutdinov, M. F. and Randall, D. A.: Cloud Resolving Modeling of the ARM Summer 1997 IOP: Model Formulation, Results, Uncertainties, and Sensitivities, Journal of the Atmospheric Sciences, 60, 607–625, 2003. a
Kurowski, M. J.: The Diurnal Susceptibility of Subtropical Clouds to Aerosols, Zenodo [data set], https://doi.org/10.5281/zenodo.14873449, 2025. a
Kurowski, M. J., P. Malinowski, S., and W. Grabowski, W.: A numerical investigation of entrainment and transport within a stratocumulus-topped boundary layer, Quarterly Journal of the Royal Meteorological Society, 135, 77–92, 2009. a
Lebsock, M. D., Stephens, G. L., and Kummerow, C.: Multisensor satellite observations of aerosol effects on warm clouds, Journal of Geophysical Research: Atmospheres, 113, 2008. a
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: A review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005. a
Lu, M.-L. and Seinfeld, J. H.: Study of the aerosol indirect effect by large-eddy simulation of marine stratocumulus, Journal of the Atmospheric Sciences, 62, 3909–3923, https://doi.org/10.1175/JAS3551.1, 2005. a
Manshausen, P., Watson-Parris, D., Christensen, M. W., Stier, P., Neubauer, D., and Grosvenor, D. P.: Invisible ship tracks show large cloud sensitivity to aerosol, Nature, 610, 101–106, https://doi.org/10.1038/s41586-022-05122-0, 2022. a
Moeng, C.-H., Cotton, W. R., Bretherton, C., Chlond, A., Khairoutdinov, M., Krueger, S., Lewellen, W. S., MacVean, M. K., Pasquier, J. R. M., Rand, H. A., Siems, S. T., Stevens, B., and Sykes, R. I.: Simulation of a stratocumulus-topped planetary boundary layer: Intercomparison among different numerical codes, Bulletin of the American Meteorological Society, 77, 261–278, https://doi.org/10.1175/1520-0477(1996)077<0261:SOASTP>2.0.CO;2, 1996. a
Morrison, H. and Gettelman, A.: A New Two-Moment Bulk Stratiform Cloud Microphysics Scheme in the Community Atmosphere Model, Version 3 (CAM3), Part I: Description and Numerical Tests, Journal of Climate, 21, 3642–3659, 2008. a
Pincus, R. and Baker, M.: Effect of precipitation on the albedo susceptibility of clouds in the marine boundary layer, Nature, 372, 250–252, https://doi.org/10.1038/372250a0, 1994. a
Platnick, S. and Twomey, S.: Determining the Susceptibility of Cloud Albedo to Changes in Droplet Concentration with the Advanced Very High Resolution Radiometer, Journal of Applied Meteorology and Climatology, 33, 334–347, 1994. a
Prabhakaran, P., Hoffmann, F., and Feingold, G.: Effects of intermittent aerosol forcing on the stratocumulus-to-cumulus transition, Atmos. Chem. Phys., 24, 1919–1937, https://doi.org/10.5194/acp-24-1919-2024, 2024 a
Quaas, J., Arola, A., Cairns, B., Christensen, M., Deneke, H., Ekman, A. M. L., Feingold, G., Fridlind, A., Gryspeerdt, E., Hasekamp, O., Li, Z., Lipponen, A., Ma, P.-L., Mülmenstädt, J., Nenes, A., Penner, J. E., Rosenfeld, D., Schrödner, R., Sinclair, K., Sourdeval, O., Stier, P., Tesche, M., van Diedenhoven, B., and Wendisch, M.: Constraining the Twomey effect from satellite observations: issues and perspectives, Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, 2020. a
Sandu, I., Brenguier, J.-L., Geoffroy, O., Thouron, O., and Masson, V.: Aerosol Impacts on the Diurnal Cycle of Marine Stratocumulus, Journal of the Atmospheric Sciences, 65, 2705–2718, 2008. a
Smalley, K. M. and Lebsock, M. D.: Corrections for Geostationary Cloud Liquid Water Path Using Microwave Imagery, Journal of Atmospheric and Oceanic Technology, 40, 1049–1061, 2023. a
Smalley, K. M., Lebsock, M. D., Eastman, R., Smalley, M., and Witte, M. K.: A Lagrangian analysis of pockets of open cells over the southeastern Pacific, Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, 2022. a
Smalley, K. M., Lebsock, M. D., and Eastman, R.: Diurnal Patterns in the Observed Cloud Liquid Water Path Response to Droplet Number Perturbations, Geophysical Research Letters, 51, e2023GL107323, https://doi.org/https://doi.org/10.1029/2023GL107323, 2024. a, b
Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., eds.: Climate Change 2007: The Physical Science Basis, Cambridge University Press, Cambridge, UK and New York, NY, USA, contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, ISBN 978-0-521-88009-1, 2007. a
Stephens, G. L.: The Parametrization of Radiation for Numerical Weather Prediction and Climate Models, Monthly Weather Review, 112, 826–867, https://doi.org/10.1175/1520-0493(1984)112<0826:TPORFN>2.0.CO;2, 1984. a
Stevens, B., Cotton, W. R., Feingold, G., and Moeng, C.-H.: Large-Eddy Simulations of Strongly Precipitating, Shallow, Stratocumulus-Topped Boundary Layers, Journal of the Atmospheric Sciences, 55, 3616–3638, https://doi.org/10.1175/1520-0469(1998)055<3616:LESOSP>2.0.CO;2, 1998. a
Stevens, B., Moeng, C.-H., Ackerman, A. S., Bretherton, C. S., Chlond, A., de Roode, S., Edwards, J., Golaz, J.-C., Jiang, H., Khairoutdinov, M., Kirkpatrick, M. P., Lewellen, D. C., Lock, A., Müller, F., Stevens, D. E., Whelan, E., and Zhu, P.: Evaluation of Large-Eddy Simulations via Observations of Nocturnal Marine Stratocumulus, Monthly Weather Review, 133, 1443–1462, https://doi.org/10.1175/MWR2930.1, 2005. a, b
Toll, V., Christensen, M., Quaas, J., and Bellouin, N.: Weak average liquid-cloud-water response to anthropogenic aerosols, Nature, 572, 51–55, https://doi.org/10.1038/s41586-019-1423-9, 2019. a
Uchida, J., Bretherton, C. S., and Blossey, P. N.: The sensitivity of stratocumulus-capped mixed layers to cloud droplet concentration: do LES and mixed-layer models agree?, Atmos. Chem. Phys., 10, 4097–4109, https://doi.org/10.5194/acp-10-4097-2010, 2010. a
van der Dussen, J. J., de Roode, S. R., Ackerman, A. S., Blossey, P. N., Bretherton, C. S., Kurowski, M. J., Lock, A. P., Neggers, R. A. J., Sandu, I., and Siebesma, A. P.: The GASS/EUCLIPSE model intercomparison of the stratocumulus transition as observed during ASTEX: LES results, Journal of Advances in Modeling Earth Systems, 5, 483–499, 2013. a, b
Várnai, T. and Marshak, A.: MODIS observations of enhanced clear sky reflectance near clouds, Geophysical Research Letters, 36, 2009. a
Wall, C. J., Norris, J. R., Possner, A., McCoy, D. T., McCoy, I. L., and Lutsko, N. J.: Assessing effective radiative forcing from aerosol–cloud interactions over the global ocean, Proceedings of the National Academy of Sciences, 119, e2210481119, https://doi.org/https://doi.org/10.1073/pnas.2210481119, 2022. a
Wall, C. J., Storelvmo, T., and Possner, A.: Global observations of aerosol indirect effects from marine liquid clouds, Atmos. Chem. Phys., 23, 13125–13141, https://doi.org/10.5194/acp-23-13125-2023, 2023. a
Walther, A. and Straka, W.: Cloud optical depth from the National Oceanic and Atmospheric Administration (NOAA) comprehensive large array-data stewardship system (CLASS) [Dataset], retrieved from https://www.avl.class.noaa.gov/saa/products/search?sub_id=0&datatype_family=GRABIPRD&submit.x=20&submit.y=10 (last access: 01 November 2023), 2019–2021. a
Wentz, F. J. and Spencer, R. W.: SSM/I Rain Retrievals within a Unified All-Weather Ocean Algorithm, Journal of the Atmospheric Sciences, 55, 1613–1627, 1998. a
Wood, R.: Stratocumulus clouds, Monthly Weather Review, 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012. a, b
Zhang, J., Chen, Y.-S., Yamaguchi, T., and Feingold, G.: Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli, Atmos. Chem. Phys., 24, 10425–10440, https://doi.org/10.5194/acp-24-10425-2024, 2024. a
Short summary
This study explores how clouds respond to pollution throughout the day using high-resolution simulations. Polluted clouds show stronger daily changes: thicker clouds at night and in the morning but faster thinning in the afternoon. Pollution reduces rainfall but enhances drying, deepening the cloud layer. While the pollution initially brightens clouds, the daily cycle of cloudiness slightly reduces this brightening effect.
This study explores how clouds respond to pollution throughout the day using high-resolution...
Altmetrics
Final-revised paper
Preprint