Articles | Volume 20, issue 22
https://doi.org/10.5194/acp-20-13771-2020
https://doi.org/10.5194/acp-20-13771-2020
Research article
 | 
16 Nov 2020
Research article |  | 16 Nov 2020

Snow-induced buffering in aerosol–cloud interactions

Takuro Michibata, Kentaroh Suzuki, and Toshihiko Takemura

Related authors

Droplet collection efficiencies estimated from satellite retrievals constrain effective radiative forcing of aerosol-cloud interactions
Charlotte M. Beall, Po-Lun Ma, Matthew W. Christensen, Johannes Mülmenstädt, Adam Varble, Kentaroh Suzuki, and Takuro Michibata
EGUsphere, https://doi.org/10.5194/egusphere-2023-2161,https://doi.org/10.5194/egusphere-2023-2161, 2023
Short summary
Incorporation of inline warm rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation
Takuro Michibata, Kentaroh Suzuki, Tomoo Ogura, and Xianwen Jing
Geosci. Model Dev., 12, 4297–4307, https://doi.org/10.5194/gmd-12-4297-2019,https://doi.org/10.5194/gmd-12-4297-2019, 2019
Short summary
The source of discrepancies in aerosol–cloud–precipitation interactions between GCM and A-Train retrievals
Takuro Michibata, Kentaroh Suzuki, Yousuke Sato, and Toshihiko Takemura
Atmos. Chem. Phys., 16, 15413–15424, https://doi.org/10.5194/acp-16-15413-2016,https://doi.org/10.5194/acp-16-15413-2016, 2016
Short summary
The effects of aerosols on water cloud microphysics and macrophysics based on satellite-retrieved data over East Asia and the North Pacific
T. Michibata, K. Kawamoto, and T. Takemura
Atmos. Chem. Phys., 14, 11935–11948, https://doi.org/10.5194/acp-14-11935-2014,https://doi.org/10.5194/acp-14-11935-2014, 2014
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Above-cloud concentrations of cloud condensation nuclei help to sustain some Arctic low-level clouds
Lucas J. Sterzinger and Adele L. Igel
Atmos. Chem. Phys., 24, 3529–3540, https://doi.org/10.5194/acp-24-3529-2024,https://doi.org/10.5194/acp-24-3529-2024, 2024
Short summary
Contrail formation on ambient aerosol particles for aircraft with hydrogen combustion: a box model trajectory study
Andreas Bier, Simon Unterstrasser, Josef Zink, Dennis Hillenbrand, Tina Jurkat-Witschas, and Annemarie Lottermoser
Atmos. Chem. Phys., 24, 2319–2344, https://doi.org/10.5194/acp-24-2319-2024,https://doi.org/10.5194/acp-24-2319-2024, 2024
Short summary
Effects of intermittent aerosol forcing on the stratocumulus-to-cumulus transition
Prasanth Prabhakaran, Fabian Hoffmann, and Graham Feingold
Atmos. Chem. Phys., 24, 1919–1937, https://doi.org/10.5194/acp-24-1919-2024,https://doi.org/10.5194/acp-24-1919-2024, 2024
Short summary
Cloud properties and their projected changes in CMIP models with low to high climate sensitivity
Lisa Bock and Axel Lauer
Atmos. Chem. Phys., 24, 1587–1605, https://doi.org/10.5194/acp-24-1587-2024,https://doi.org/10.5194/acp-24-1587-2024, 2024
Short summary
Water isotopic characterisation of the cloud–circulation coupling in the North Atlantic trades – Part 2: The imprint of the atmospheric circulation at different scales
Leonie Villiger and Franziska Aemisegger
Atmos. Chem. Phys., 24, 957–976, https://doi.org/10.5194/acp-24-957-2024,https://doi.org/10.5194/acp-24-957-2024, 2024
Short summary

Cited articles

Abdul-Razzak, H. and Ghan, J.: A parameterization of aerosol activation 2. Multiple aerosol types, J. Geophys. Res., 105, 6837–6844, 2000. a
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989. a, b
Beheng, K. D.: A parameterization of warm cloud microphysical conversion processes, Atmos. Res., 33, 193–206, 1994. a
Bellouin, N., Quaas, J., Morcrette, J.-J., and Boucher, O.: Estimates of aerosol radiative forcing from the MACC re-analysis, Atmos. Chem. Phys., 13, 2045–2062, https://doi.org/10.5194/acp-13-2045-2013, 2013. a
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson‐Parris, D., Boucher, O., Carslaw, K., Christensen, M., Daniau, A., Dufresne, J., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J., Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D., Myhre, G., Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y., Schulz, M., Schwartz, S., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D., and Stevens, B.: Bounding global aerosol radiative forcing of climate change, Rev. Geophys., 58, e2019RG000660, https://doi.org/10.1029/2019rg000660, 2020. a, b
Download
Short summary
This work reveals that prognostic precipitation significantly reduces the magnitude of aerosol–cloud interactions (ERFaci), mainly due to the collection process associated with snowflakes and underlying cloud droplets. This precipitation-driven buffering effect, which is missing in traditional GCMs, can explain the model–observation discrepancy in ERFaci. These results underscore the necessity for a prognostic precipitation framework in GCMs for more reliable climate simulations.
Altmetrics
Final-revised paper
Preprint