Articles | Volume 24, issue 22
https://doi.org/10.5194/acp-24-12661-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-12661-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Nov 2024
Research article |
| 14 Nov 2024
| 14 Nov 2024
Diurnal evolution of non-precipitating marine stratocumuli in a large-eddy simulation ensemble
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Jianhao Zhang
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Fabian Hoffmann
Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany
Takanobu Yamaguchi
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Franziska Glassmeier
Department of Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
Xiaoli Zhou
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Graham Feingold
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
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The subtropical Atlantic hosts one of the planet's largest marine low cloud decks and interacts with biomass burning aerosol from approximately July through October. This study clarifies how the monthly evolution in meteorology and the biomass burning aerosol vertical structure affects the seasonal cycle in its low cloud fraction, such that the July–October evolution in low cloud cover and morphology are reinforced, when compared to scenarios with less aerosol present.
Robert Pincus, Chris W. Fairall, Adriana Bailey, Haonan Chen, Patrick Y. Chuang, Gijs de Boer, Graham Feingold, Dean Henze, Quinn T. Kalen, Jan Kazil, Mason Leandro, Ashley Lundry, Ken Moran, Dana A. Naeher, David Noone, Akshar J. Patel, Sergio Pezoa, Ivan PopStefanija, Elizabeth J. Thompson, James Warnecke, and Paquita Zuidema
Earth Syst. Sci. Data, 13, 3281–3296, https://doi.org/10.5194/essd-13-3281-2021, https://doi.org/10.5194/essd-13-3281-2021, 2021
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This paper describes observations taken from a research aircraft during a field experiment in the western Atlantic Ocean during January and February 2020. The plane made 11 flights, most 8-9 h long, and measured the properties of the atmosphere and ocean with a combination of direct measurements, sensors falling from the plane to profile the atmosphere and ocean, and remote sensing measurements of clouds and the ocean surface.
Johannes Quaas, Antti Arola, Brian Cairns, Matthew Christensen, Hartwig Deneke, Annica M. L. Ekman, Graham Feingold, Ann Fridlind, Edward Gryspeerdt, Otto Hasekamp, Zhanqing Li, Antti Lipponen, Po-Lun Ma, Johannes Mülmenstädt, Athanasios Nenes, Joyce E. Penner, Daniel Rosenfeld, Roland Schrödner, Kenneth Sinclair, Odran Sourdeval, Philip Stier, Matthias Tesche, Bastiaan van Diedenhoven, and Manfred Wendisch
Atmos. Chem. Phys., 20, 15079–15099, https://doi.org/10.5194/acp-20-15079-2020, https://doi.org/10.5194/acp-20-15079-2020, 2020
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Anthropogenic pollution particles – aerosols – serve as cloud condensation nuclei and thus increase cloud droplet concentration and the clouds' reflection of sunlight (a cooling effect on climate). This Twomey effect is poorly constrained by models and requires satellite data for better quantification. The review summarizes the challenges in properly doing so and outlines avenues for progress towards a better use of aerosol retrievals and better retrievals of droplet concentrations.
Simon Unterstrasser, Fabian Hoffmann, and Marion Lerch
Geosci. Model Dev., 13, 5119–5145, https://doi.org/10.5194/gmd-13-5119-2020, https://doi.org/10.5194/gmd-13-5119-2020, 2020
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Particle-based cloud models use simulation particles for the representation of cloud particles like droplets or ice crystals. The collision and merging of cloud particles (i.e. collisional growth a.k.a. collection in the case of cloud droplets and aggregation in the case of ice crystals) was found to be a numerically challenging process in such models. The study presents verification exercises in a 1D column model, where sedimentation and collisional growth are the only active processes.
Peter A. Bogenschutz, Shuaiqi Tang, Peter M. Caldwell, Shaocheng Xie, Wuyin Lin, and Yao-Sheng Chen
Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020, https://doi.org/10.5194/gmd-13-4443-2020, 2020
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This paper documents a tool that has been developed that can be used to accelerate the development and understanding of climate models. This version of the model, known as a the single-column model, is much faster to run than the full climate model, and we demonstrate that this tool can be used to quickly exploit model biases that arise due to physical processes. We show examples of how this single-column model can directly benefit the field.
Cited articles
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
Ackerman, A. S., vanZanten, M. C., Stevens, B., Savic-Jovcic, V., Bretherton, C. S., Chlond, A., Golaz, J.-C., Jiang, H., Khairoutdinov, M., Krueger, S. K., Lewellen, D. C., Lock, A., Moeng, C.-H., Nakamura, K., Petters, M. D., Snider, J. R., Weinbrecht, S., and Zulauf, M.: Large-eddy simulations of a drizzling, stratocumulus-topped marine boundary layer, Mon. Weather Rev., 137, 1083–1110, https://doi.org/10.1175/2008MWR2582.1, 2009. a, b
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. a
Boers, R. and Mitchell, R. M.: Absorption feedback in stratocumulus clouds influence on cloud top albedo, Tellus A, 46, 229, https://doi.org/10.3402/tellusa.v46i3.15476, 1994. a
Bretherton, C. S. and Blossey, P. N.: Low cloud reduction in a greenhouse‐warmed climate: Results from Lagrangian LES of a subtropical marine cloudiness transition, J. Adv. Model. Earth Sy., 6, 91–114, https://doi.org/10.1002/2013MS000250, 2014. a
Bretherton, C. S. and Wyant, M. C.: Moisture transport, lower-tropospheric stability, and decoupling of cloud-topped boundary layers, J. Atmos. Sci., 54, 148–167, https://doi.org/10.1175/1520-0469(1997)054<0148:MTLTSA>2.0.CO;2, 1997. a
Bretherton, C. S., Blossey, P. N., and Uchida, J.: Cloud droplet sedimentation, entrainment efficiency, and subtropical stratocumulus albedo, Geophys. Res. Lett., 34, L03813, https://doi.org/10.1029/2006GL027648, 2007. a
Bretherton, C. S., Blossey, P. N., and Jones, C. R.: Mechanisms of marine low cloud sensitivity to idealized climate perturbations: A single-LES exploration extending the CGILS cases, J. Adv. Model. Earth Sy., 5, 316–337, https://doi.org/10.1002/jame.20019, 2013. a
Caldwell, P. and Bretherton, C. S.: Large eddy simulation of the diurnal cycle in Southeast Pacific stratocumulus, J. Atmos. Sci., 66, 432–449, https://doi.org/10.1175/2008JAS2785.1, 2009. a, b
Chen, Y.: Model outputs, NOAA Chemical Sciences Laboratory (CSL) [data set], https://csl.noaa.gov/groups/csl9/datasets/data/2024-Chen-etal/, last access: 27 September 2024. a
Chen, Y.-C., Xue, L., Lebo, Z. J., Wang, H., Rasmussen, R. M., and Seinfeld, J. H.: A comprehensive numerical study of aerosol-cloud-precipitation interactions in marine stratocumulus, Atmos. Chem. Phys., 11, 9749–9769, https://doi.org/10.5194/acp-11-9749-2011, 2011. a
Chun, J.-Y., Wood, R., Blossey, P., and Doherty, S. J.: Microphysical, macrophysical, and radiative responses of subtropical marine clouds to aerosol injections, Atmos. Chem. Phys., 23, 1345–1368, https://doi.org/10.5194/acp-23-1345-2023, 2023. a, b
Chung, D., Matheou, G., and Teixeira, J.: Steady-state large-eddy simulations to study the stratocumulus to shallow cumulus cloud transition, J. Atmos. Sci., 69, 3264–3276, https://doi.org/10.1175/JAS-D-11-0256.1, 2012. a
Deardorff, J. W.: Stratocumulus-capped mixed layers derived from a three-dimensional model, Bound.-Lay. Meteorol., 18, 495–527, https://doi.org/10.1007/bf00119502, 1980. a
De Roode, S. R., Siebesma, A. P., Dal Gesso, S., Jonker, H. J. J., Schalkwijk, J., and Sival, J.: A mixed‐layer model study of the stratocumulus response to changes in large‐scale conditions, J. Adv. Model. Earth Sy., 6, 1256–1270, https://doi.org/10.1002/2014MS000347, 2014. a
de Roode, S. R., Sandu, I., van der Dussen, J. J., Ackerman, A. S., Blossey, P., Jarecka, D., Lock, A., Siebesma, A. P., and Stevens, B.: Large-eddy simulations of EUCLIPSE–GASS Lagrangian stratocumulus-to-cumulus transitions: Mean state, turbulence, and decoupling, J. Atmos. Sci., 73, 2485–2508, https://doi.org/10.1175/JAS-D-15-0215.1, 2016. a
Eastman, R. and Wood, R.: The competing effects of stability and humidity on subtropical stratocumulus entrainment and cloud evolution from a Lagrangian perspective, J. Atmos. Sci., 75, 2563–2578, https://doi.org/10.1175/JAS-D-18-0030.1, 2018. a, b, c
Feingold, G., Walko, R. L., Stevens, B., and Cotton, W. R.: Simulations of marine stratocumulus using a new microphysical parameterization scheme, Atmos. Res., 47–48, 505–528, https://doi.org/10.1016/S0169-8095(98)00058-1, 1998. a
Feingold, G., McComiskey, A., Yamaguchi, T., Johnson, J. S., Carslaw, K. S., and Schmidt, K. S.: New approaches to quantifying aerosol influence on the cloud radiative effect, P. Natl. Acad. Sci USA, 113, 5812–5819, https://doi.org/10.1073/pnas.1514035112, 2016. a, b
Feingold, G., Ghate, V. P., Russell, L. M., Blossey, P., Cantrell, W., Christensen, M. W., Diamond, M. S., Gettelman, A., Glassmeier, F., Gryspeerdt, E., Haywood, J., Hoffmann, F., Kaul, C. M., Lebsock, M., McComiskey, A. C., McCoy, D. T., Ming, Y., Mülmenstädt, J., Possner, A., Prabhakaran, P., Quinn, P. K., Schmidt, K. S., Shaw, R. A., Singer, C. E., Sorooshian, A., Toll, V., Wan, J. S., Wood, R., Yang, F., Zhang, J., and Zheng, X.: Physical science research needed to evaluate the viability and risks of marine cloud brightening, Science Advances, 10, eadi8594, https://doi.org/10.1126/sciadv.adi8594, 2024. a
Garrett, T. J., Radke, L. F., and Hobbs, P. V.: Aerosol effects on cloud emissivity and surface longwave heating in the Arctic, J. Atmos. Sci., 59, 769–778, https://doi.org/10.1175/1520-0469(2002)059<0769:AEOCEA>2.0.CO;2, 2002. a
Ghonima, M. S., Norris, J. R., Heus, T., and Kleissl, J.: Reconciling and validating the cloud thickness and liquid water path tendencies proposed by R. Wood and J. J. van der Dussen et al., J. Atmos. Sci., 72, 2033–2040, https://doi.org/10.1175/jas-d-14-0287.1, 2015. a, b
Glassmeier, F., Hoffmann, F., Johnson, J. S., Yamaguchi, T., Carslaw, K. S., and Feingold, G.: Aerosol-cloud-climate cooling overestimated by ship-track data, Science, 371, 485–489, https://doi.org/10.1126/science.abd3980, 2021. a, b, c
Gryspeerdt, E., Goren, T., Sourdeval, O., Quaas, J., Mülmenstädt, J., Dipu, S., Unglaub, C., Gettelman, A., and Christensen, M.: Constraining the aerosol influence on cloud liquid water path, Atmos. Chem. Phys., 19, 5331–5347, https://doi.org/10.5194/acp-19-5331-2019, 2019. a
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
Haman, K. E., Malinowski, S. P., Kurowski, M. J., Gerber, H., and Brenguier, J.: Small scale mixing processes at the top of a marine stratocumulus – a case study, Q. J. Roy. Meteor. Soc., 133, 213–226, https://doi.org/10.1002/qj.5, 2007. a
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., 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.: Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate, Copernicus Climate Change Service (C3S) Data Store (CDS) [data set], https://doi.org/10.24381/cds.143582cf, 2017. a
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., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R. M., 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
Hoffmann, F., Glassmeier, F., Yamaguchi, T., and Feingold, G.: On the roles of precipitation and entrainment in stratocumulus transitions between mesoscale states, J. Atmos. Sci., 80, 2791–2803, https://doi.org/10.1175/JAS-D-22-0268.1, 2023. a, b, c
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008jd009944, 2008. a
Jones, C. R., Bretherton, C. S., and Leon, D.: Coupled vs. decoupled boundary layers in VOCALS-REx, Atmos. Chem. Phys., 11, 7143–7153, https://doi.org/10.5194/acp-11-7143-2011, 2011. a
Kazil, J., Wang, H., Feingold, G., Clarke, A. D., Snider, J. R., and Bandy, A. R.: Modeling chemical and aerosol processes in the transition from closed to open cells during VOCALS-REx, Atmos. Chem. Phys., 11, 7491–7514, https://doi.org/10.5194/acp-11-7491-2011, 2011. a
Kazil, J., Feingold, G., Wang, H., and Yamaguchi, T.: On the interaction between marine boundary layer cellular cloudiness and surface heat fluxes, Atmos. Chem. Phys., 14, 61–79, https://doi.org/10.5194/acp-14-61-2014, 2014. a
Kazil, J., Feingold, G., and Yamaguchi, T.: Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations, Atmos. Chem. Phys., 16, 5811–5839, https://doi.org/10.5194/acp-16-5811-2016, 2016. a, b
Kazil, J., Yamaguchi, T., and Feingold, G.: Mesoscale organization, entrainment, and the properties of a closed-cell stratocumulus cloud, J. Adv. Model. Earth Sy., 9, 2214–2229, https://doi.org/10.1002/2017MS001072, 2017. a, b
Kazil, J., Christensen, M. W., Abel, S. J., Yamaguchi, T., and Feingold, G.: Realism of Lagrangian large eddy simulations driven by reanalysis meteorology: Tracking a pocket of open cells under a biomass burning aerosol layer, J. Adv. Model. Earth Sy., 13, e2021MS002664, https://doi.org/10.1029/2021MS002664, 2021. a, b
Keeler, E., Burk, K., and Kyrouac, J.: Balloon-Borne Sounding System (SONDEWNPN), 2012-10-01 to 2013-10-03, ARM Mobile Facility (MAG) Los Angeles, CA to Honolulu, HI – container ship Horizon Spirit; AMF2 (M1), 19 September 2022, Atmospheric Radiation Measurement (ARM) user facility [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.5439/1595321, 2012. a
Khairoutdinov, M.: SAM source code, Stony Brook repository [code], http://rossby.msrc.sunysb.edu/SAM/, last access: 10 November 2024. a
Khairoutdinov, M. F. and Randall, D. A.: Cloud Resolving Modeling of the ARM Summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities, J. Atmos. Sci., 60, 607–625, https://doi.org/10.1175/1520-0469(2003)060<0607:CRMOTA>2.0.CO;2, 2003. a, b
Klein, S. A. and Hartmann, D. L.: The seasonal cycle of low stratiform clouds, J. Climate, 6, 1587–1606, https://doi.org/10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2, 1993. a
Kurowski, M. J., Malinowski, S. P., and Grabowski, W. W.: A numerical investigation of entrainment and transport within a stratocumulus‐topped boundary layer, Q. J. Roy. Meteor. Soc., 135, 77–92, https://doi.org/10.1002/qj.354, 2009. a
Latham, J.: Control of global warming?, Nature, 347, 339–340, https://doi.org/10.1038/347339b0, 1990. a
Lewis, E. R., Wiscombe, W. J., Albrecht, B. A., Bland, G. L., Flagg, C. N., Klein, S. A., Kollias, P., Mace, G., Reynolds, R. M., Schwartz, S. E., Siebesma, A. P., Teixeira, J., Wood, R., and Zhang, M.: MAGIC: Marine ARM GPCI investigation of clouds, Tech. Rep. DOE/SC-ARM-12-020, U.S. Department of Energy, https://www.arm.gov/publications/programdocs/doe-sc-arm-12-020.pdf (last access: 10 November 2024), 2012. a
Lilly, D. K.: Models of cloud-topped mixed layers under a strong inversion, Q. J. Roy. Meteor. Soc., 94, 292–309, https://doi.org/10.1002/qj.49709440106, 1968. a, b
Manshausen, P., Watson-Parris, D., Christensen, M. W., Jalkanen, J.-P., and Stier, P.: Invisible ship tracks show large cloud sensitivity to aerosol, Nature, 610, 101–106, https://doi.org/10.1038/s41586-022-05122-0, 2022. a
Matheou, G. and Teixeira, J. A.: Sensitivity to physical and numerical aspects of large-eddy simulation of stratocumulus, Mon. Weather Rev., 147, 2621–2639, https://doi.org/10.1175/MWR-D-18-0294.1, 2019. a
Mellado, J. P., Bretherton, C. S., Stevens, B., and Wyant, M. C.: DNS and LES for simulating stratocumulus: Better together, J. Adv. Model. Earth Sy., 10, 1421–1438, https://doi.org/10.1029/2018MS001312, 2018. a, b
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, https://doi.org/10.1029/97JD00237, 1997. a
Moeng, C.-H., Stevens, B., and Sullivan, P. P.: Where is the interface of the stratocumulus-topped PBL?, J. Atmos. Sci., 62, 2626–2631, https://doi.org/10.1175/JAS3470.1, 2005. a
Morrison, H., Jensen, A. A., Harrington, J. Y., and Milbrandt, J. A.: Advection of coupled hydrometeor quantities in bulk cloud microphysics schemes, Mon. Weather Rev., 144, 2809–2829, https://doi.org/10.1175/MWR-D-15-0368.1, 2016. a
Mülmenstädt, J. and Feingold, G.: The radiative forcing of aerosol–cloud interactions in liquid clouds: Wrestling and embracing uncertainty, Current Climate Change Reports, 4, 23–40, https://doi.org/10.1007/s40641-018-0089-y, 2018. a
Nicholls, S.: The dynamics of stratocumulus: aircraft observations and comparisons with a mixed layer model, Q. J. Roy. Meteor. Soc., 110, 783–820, https://doi.org/10.1002/qj.49711046603, 1984. a
Nowak, J. L., Siebert, H., Szodry, K.-E., and Malinowski, S. P.: Coupled and decoupled stratocumulus-topped boundary layers: turbulence properties, Atmos. Chem. Phys., 21, 10965–10991, https://doi.org/10.5194/acp-21-10965-2021, 2021. a
Ovtchinnikov, M. and Easter, R. C.: Nonlinear advection algorithms applied to interrelated tracers: Errors and implications for modeling aerosol–cloud interactions, Mon. Weather Rev., 137, 632–644, https://doi.org/10.1175/2008MWR2626.1, 2009. a
Pedersen, J. G., Malinowski, S. P., and Grabowski, W. W.: Resolution and domain‐size sensitivity in implicit large‐eddy simulation of the stratocumulus‐topped boundary layer, J. Adv. Model. Earth Sy., 8, 885–903, https://doi.org/10.1002/2015MS000572, 2016. a
Petters, J. L., Harrington, J. Y., and Clothiaux, E. E.: Radiative–dynamical feedbacks in low liquid water path stratiform clouds, J. Atmos. Sci., 69, 1498–1512, https://doi.org/10.1175/JAS-D-11-0169.1, 2012. a, b
Pincus, R. and Baker, M. B.: 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
Possner, A., Wang, H., Wood, R., Caldeira, K., and Ackerman, T. P.: The efficacy of aerosol–cloud radiative perturbations from near-surface emissions in deep open-cell stratocumuli, Atmos. Chem. Phys., 18, 17475–17488, https://doi.org/10.5194/acp-18-17475-2018, 2018. a
Prabhakaran, P., Hoffmann, F., and Feingold, G.: Evaluation of pulse aerosol forcing on marine stratocumulus clouds in the context of marine cloud brightening, J. Atmos. Sci., 80, 1585–1604, https://doi.org/10.1175/JAS-D-22-0207.1, 2023. a
Qiu, S., Zheng, X., Painemal, D., Terai, C. R., and Zhou, X.: Daytime variation in the aerosol indirect effect for warm marine boundary layer clouds in the eastern North Atlantic, Atmos. Chem. Phys., 24, 2913–2935, https://doi.org/10.5194/acp-24-2913-2024, 2024. a
Sandu, I. and Stevens, B.: On the factors modulating the stratocumulus to cumulus transitions, J. Atmos. Sci., 68, 1865–1881, https://doi.org/10.1175/2011JAS3614.1, 2011. a
Sandu, I., Brenguier, J.-L., Geoffroy, O., Thouron, O., and Masson, V.: Aerosol impacts on the diurnal cycle of marine stratocumulus, J. Atmos. Sci., 65, 2705–2718, https://doi.org/10.1175/2008JAS2451.1, 2008. a
Smalley, K. M., Lebsock, M. D., and Eastman, R.: Diurnal patterns in the observed cloud liquid water path response to droplet number perturbations, Geophys. Res. Lett., 51, e2023GL107323, https://doi.org/10.1029/2023GL107323, 2024. a
Stevens, B. and Feingold, G.: Untangling aerosol effects on clouds and precipitation in a buffered system, Nature, 461, 607–613, https://doi.org/10.1038/nature08281, 2009. a, b
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, Mon. Weather Rev., 133, 1443–1462, https://doi.org/10.1175/MWR2930.1, 2005. a, b
Stevens, D. E., Bell, J. B., Almgren, A. S., Beckner, V. E., and Rendleman, C. A.: Small-scale processes and entrainment in a stratocumulus marine boundary layer, J. Atmos. Sci., 57, 567–581, https://doi.org/10.1175/1520-0469(2000)057<0567:SSPAEI>2.0.CO;2, 2000. a
Teixeira, J., Cardoso, S., Bonazzola, M., Cole, J., DelGenio, A., DeMott, C., Franklin, C., Hannay, C., Jakob, C., Jiao, Y., Karlsson, J., Kitagawa, H., Köhler, M., Kuwano-Yoshida, A., LeDrian, C., Li, J., Lock, A., Miller, M. J., Marquet, P., Martins, J., Mechoso, C. R., v. Meijgaard, E., Meinke, I., Miranda, P. M. A., Mironov, D., Neggers, R., Pan, H. L., Randall, D. A., Rasch, P. J., Rockel, B., Rossow, W. B., Ritter, B., Siebesma, A. P., Soares, P. M. M., Turk, F. J., Vaillancourt, P. A., Engeln, A. V., and Zhao, M.: Tropical and subtropical cloud transitions in weather and climate prediction models: The GCSS/WGNE Pacific Cross-section Intercomparison (GPCI), J. Climate, 24, 5223–5256, https://doi.org/10.1175/2011JCLI3672.1, 2011. a
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
Turton, J. D. and Nicholls, S.: A study of the diurnal variation of stratocumulus using a multiple mixed layer model, Q. J. Royal Meteor. Soc., 113, 969–1009, https://doi.org/10.1002/qj.49711347712, 1987. a, b
Twomey, S.: Pollution and the planetary albedo, Atmos. Environ., 8, 1251–1256, https://doi.org/10.1016/0004-6981(74)90004-3, 1974. a
Twomey, S.: The influence of pollution on the shortwave albedo of clouds, J. Atmos. Sci., 34, 1149–1152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2, 1977. a
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, J. Adv. Model. Earth Sy., 5, 483–499, https://doi.org/10.1002/jame.20033, 2013. a
van der Dussen, J. J., de Roode, S. R., and Siebesma, A. P.: Factors controlling rapid stratocumulus cloud thinning, J. Atmos. Sci., 71, 655–664, https://doi.org/10.1175/JAS-D-13-0114.1, 2014. a, b
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
Wang, H. and Feingold, G.: Modeling mesoscale cellular structures and drizzle in marine stratocumulus. Part I: Impact of drizzle on the formation and evolution of open cells, J. Atmos. Sci., 66, 3237–3256, https://doi.org/10.1175/2009JAS3022.1, 2009a. a
Wang, H. and Feingold, G.: Modeling mesoscale cellular structures and drizzle in marine stratocumulus. Part II: The microphysics and dynamics of the boundary region between open and closed cells, J. Atmos. Sci., 66, 3257–3275, https://doi.org/10.1175/2009JAS3120.1, 2009b. a
Wang, H., Feingold, G., Wood, R., and Kazil, J.: Modelling microphysical and meteorological controls on precipitation and cloud cellular structures in Southeast Pacific stratocumulus, Atmos. Chem. Phys., 10, 6347–6362, https://doi.org/10.5194/acp-10-6347-2010, 2010. a, b
Wang, S., Wang, Q., and Feingold, G.: Turbulence, condensation, and liquid water transport in numerically simulated nonprecipitating stratocumulus clouds, J. Atmos. Sci., 60, 262–278, https://doi.org/10.1175/1520-0469(2003)060<0262:TCALWT>2.0.CO;2, 2003. a
Wood, R.: Cancellation of aerosol indirect effects in marine stratocumulus through cloud thinning, J. Atmos. Sci., 64, 2657–2669, https://doi.org/10.1175/JAS3942.1, 2007. a
Wood, R.: Stratocumulus clouds, Mon. Weather Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012. a, b, c, d
Wood, R. and Bretherton, C. S.: On the relationship between stratiform low cloud cover and lower-tropospheric stability, J. Climate, 19, 6425–6432, https://doi.org/10.1175/JCLI3988.1, 2006. a
Yamaguchi, T., Feingold, G., Kazil, J., and McComiskey, A.: Stratocumulus to cumulus transition in the presence of elevated smoke layers, Geophys. Res. Lett., 42, 10–478, https://doi.org/10.1002/2015GL066544, 2015. a, b, c
Yamaguchi, T., Feingold, G., and Kazil, J.: Stratocumulus to cumulus transition by drizzle, J. Adv. Model. Earth Sy., 9, 2333–2349, https://doi.org/10.1002/2017MS001104, 2017. a, b
Yamaguchi, T., Feingold, G., and Kazil, J.: Aerosol-cloud interactions in trade wind cumulus clouds and the role of vertical wind shear, J. Geophys. Res.-Atmos., 124, 12244–12261, https://doi.org/10.1029/2019JD031073, 2019. a
Yuan, T., Song, H., Wood, R., Oreopoulos, L., Platnick, S., Wang, C., Yu, H., Meyer, K., and Wilcox, E.: Observational evidence of strong forcing from aerosol effect on low cloud coverage, Science Advances, 9, eadh7716, https://doi.org/10.1126/sciadv.adh7716, 2023. a
Zhang, J. and Feingold, G.: Distinct regional meteorological influences on low-cloud albedo susceptibility over global marine stratocumulus regions, Atmos. Chem. Phys., 23, 1073–1090, https://doi.org/10.5194/acp-23-1073-2023, 2023. a
Zhang, J., Zhou, X., Goren, T., and Feingold, G.: Albedo susceptibility of northeastern Pacific stratocumulus: the role of covarying meteorological conditions, Atmos. Chem. Phys., 22, 861–880, https://doi.org/10.5194/acp-22-861-2022, 2022. a
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
Zhou, X. and Bretherton, C. S.: Simulation of mesoscale cellular convection in marine stratocumulus: 2. Nondrizzling conditions, J. Adv. Model. Earth Sy., 11, 3–18, https://doi.org/10.1029/2018MS001448, 2019. a
Zhou, X., Kollias, P., and Lewis, E. R.: Clouds, precipitation, and marine boundary layer structure during the MAGIC field campaign, J. Climate, 28, 2420–2442, https://doi.org/10.1175/JCLI-D-14-00320.1, 2015. a
Short summary
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.
Marine stratocumulus cloud is a type of shallow cloud that covers the vast areas of Earth's...
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