Articles | Volume 21, issue 21
https://doi.org/10.5194/acp-21-16203-2021
https://doi.org/10.5194/acp-21-16203-2021
Research article
 | 
04 Nov 2021
Research article |  | 04 Nov 2021

Revisiting adiabatic fraction estimations in cumulus clouds: high-resolution simulations with a passive tracer

Eshkol Eytan, Ilan Koren, Orit Altaratz, Mark Pinsky, and Alexander Khain

Related authors

Dynamical regimes of CCN activation in adiabatic air parcels
Manuel Santos Gutiérrez, Mickaël David Chekroun, and Ilan Koren
EGUsphere, https://doi.org/https://doi.org/10.48550/arXiv.2405.11545,https://doi.org/https://doi.org/10.48550/arXiv.2405.11545, 2024
Preprint withdrawn
Short summary
Opposing trends of cloud coverage over land and ocean under global warming
Huan Liu, Ilan Koren, Orit Altaratz, and Mickaël D. Chekroun
Atmos. Chem. Phys., 23, 6559–6569, https://doi.org/10.5194/acp-23-6559-2023,https://doi.org/10.5194/acp-23-6559-2023, 2023
Short summary
Record-breaking statistics detect islands of cooling in a sea of warming
Elisa T. Sena, Ilan Koren, Orit Altaratz, and Alexander B. Kostinski
Atmos. Chem. Phys., 22, 16111–16122, https://doi.org/10.5194/acp-22-16111-2022,https://doi.org/10.5194/acp-22-16111-2022, 2022
Short summary
Deciphering organization of GOES-16 green cumulus through the empirical orthogonal function (EOF) lens
Tom Dror, Mickaël D. Chekroun, Orit Altaratz, and Ilan Koren
Atmos. Chem. Phys., 21, 12261–12272, https://doi.org/10.5194/acp-21-12261-2021,https://doi.org/10.5194/acp-21-12261-2021, 2021
Short summary
Sensitivity of warm clouds to large particles in measured marine aerosol size distributions – a theoretical study
Tom Dror, J. Michel Flores, Orit Altaratz, Guy Dagan, Zev Levin, Assaf Vardi, and Ilan Koren
Atmos. Chem. Phys., 20, 15297–15306, https://doi.org/10.5194/acp-20-15297-2020,https://doi.org/10.5194/acp-20-15297-2020, 2020
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)
Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli
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
Short summary
Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment
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
Short summary
Microphysical processes involving the vapour phase dominate in simulated low-level Arctic clouds
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
Short summary
Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign
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
Short summary
On the sensitivity of aerosol–cloud interactions to changes in sea surface temperature in radiative–convective equilibrium
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
Short summary

Cited articles

Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989. a
Altaratz, O., Koren, I., Reisin, T., Kostinski, A., Feingold, G., Levin, Z., and Yin, Y.: Aerosols' influence on the interplay between condensation, evaporation and rain in warm cumulus cloud, Atmos. Chem. Phys., 8, 15–24, https://doi.org/10.5194/acp-8-15-2008, 2008. a
Baker, M., Corbin, R., and Latham, J.: The influence of entrainment on the evolution of cloud droplet spectra: I. A model of inhomogeneous mixing, Q. J. Roy. Meteor. Soc., 106, 581–598, 1980. a
Bera, S.: Droplet spectral dispersion by lateral mixing process in continental deep cumulus clouds, J. Atmos. Sol.-Terr. Phy., 214, 105550, https://doi.org/10.1016/j.jastp.2021.105550, 2021. a, b
Bolton, D.: The computation of equivalent potential temperature, Mon. Weather Rev., 108, 1046–1053, 1980. a, b
Download
Short summary
Describing cloud mixing processes is among the most challenging fronts in cloud physics. Therefore, the adiabatic fraction (AF) that serves as a mixing measure is a valuable metric. We use high-resolution (10 m) simulations of single clouds with a passive tracer to test the skill of different methods used to derive AF. We highlight a method that is insensitive to the available cloud samples and allows considering microphysical effects on AF estimations in different environmental conditions.
Altmetrics
Final-revised paper
Preprint