Articles | Volume 24, issue 5
https://doi.org/10.5194/acp-24-2913-2024
https://doi.org/10.5194/acp-24-2913-2024
Research article
 | 
06 Mar 2024
Research article |  | 06 Mar 2024

Daytime variation in the aerosol indirect effect for warm marine boundary layer clouds in the eastern North Atlantic

Shaoyue Qiu, Xue Zheng, David Painemal, Christopher R. Terai, and Xiaoli Zhou

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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Cited articles

Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. 
Arola, A., Lipponen, A., Kolmonen, P., Virtanen, T. H., Bellouin, N., Grosvenor, D. P., Gryspeerdt, E., Quaas, J., and Kokkola, H.: Aerosol effects on clouds are concealed by natural cloud heterogeneity and satellite retrieval errors, Nat. Commun., 13, 7357 https://doi.org/10.1038/s41467-022-34948-5, 2022. 
Atmospheric Radiation Measurement (ARM) user facility: Active Remote Sensing of CLouds (ARSCL) product using Ka-band ARM Zenith Radars (ARSCLKAZR1KOLLIAS), 2015-07-17 to 2022-03-31, Eastern North Atlantic (ENA) Graciosa Island, Azores, Portugal (C1), compiled by: Johnson, K., Giangrande, S., and Toto, T., ARM Data Center [data set], https://doi.org/10.5439/1393437, 2015. 
Atmospheric Radiation Measurement (ARM) user facility: Minnis Cloud Products Using Visst Algorithm (VISSTGRIDM11MINNIS), 2018-02-20 to 2021-12-31, Eastern North Atlantic (ENA) External Data (satellites and others) (X1), ARM Data Center [data set], https://adc.arm.gov/discovery/#/results/datastream::enavisstgridm11minnisX1.c1 (last access: 25 January 2023), 2018. 
Bennartz, R.: Global assessment of marine boundary layer cloud droplet number concentration from satellite, J. Geophys. Res., 112, D02201, https://doi.org/10.1029/2006JD007547, 2007. 
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The aerosol indirect effect (AIE) depends on cloud states, which exhibit significant diurnal variations in the northeastern Atlantic. Yet the AIE diurnal cycle remains poorly understood. Using satellite retrievals, we find a pronounced “U-shaped” diurnal variation in the AIE, which is contributed to by the transition of cloud states combined with the lagged cloud responses. This suggests that polar-orbiting satellites with overpass times at noon underestimate daytime mean values of the AIE.
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