Articles | Volume 15, issue 3
Atmos. Chem. Phys., 15, 1503–1520, 2015
https://doi.org/10.5194/acp-15-1503-2015
Atmos. Chem. Phys., 15, 1503–1520, 2015
https://doi.org/10.5194/acp-15-1503-2015
Research article
11 Feb 2015
Research article | 11 Feb 2015

Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5)

X. Shi et al.

Related authors

Impacts of the ice-particle size distribution shape parameter on climate simulations with the Community Atmosphere Model Version 6 (CAM6)
Wentao Zhang, Xiangjun Shi, and Chunsong Lu
Geosci. Model Dev., 15, 7751–7766, https://doi.org/10.5194/gmd-15-7751-2022,https://doi.org/10.5194/gmd-15-7751-2022, 2022
Short summary
Effective radiative forcing of anthropogenic aerosols in E3SM version 1: historical changes, causality, decomposition, and parameterization sensitivities
Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
Atmos. Chem. Phys., 22, 9129–9160, https://doi.org/10.5194/acp-22-9129-2022,https://doi.org/10.5194/acp-22-9129-2022, 2022
Short summary
Estimating the potential cooling effect of cirrus thinning achieved via the seeding approach
Jiaojiao Liu and Xiangjun Shi
Atmos. Chem. Phys., 21, 10609–10624, https://doi.org/10.5194/acp-21-10609-2021,https://doi.org/10.5194/acp-21-10609-2021, 2021
Short summary
Impact of aerosols on ice crystal size
Bin Zhao, Kuo-Nan Liou, Yu Gu, Jonathan H. Jiang, Qinbin Li, Rong Fu, Lei Huang, Xiaohong Liu, Xiangjun Shi, Hui Su, and Cenlin He
Atmos. Chem. Phys., 18, 1065–1078, https://doi.org/10.5194/acp-18-1065-2018,https://doi.org/10.5194/acp-18-1065-2018, 2018
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Aerosol–precipitation elevation dependence over the central Himalayas using cloud-resolving WRF-Chem numerical modeling
Pramod Adhikari and John F. Mejia
Atmos. Chem. Phys., 23, 1019–1042, https://doi.org/10.5194/acp-23-1019-2023,https://doi.org/10.5194/acp-23-1019-2023, 2023
Short summary
Machine learning of cloud types in satellite observations and climate models
Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
Atmos. Chem. Phys., 23, 523–549, https://doi.org/10.5194/acp-23-523-2023,https://doi.org/10.5194/acp-23-523-2023, 2023
Short summary
A modeling study of an extreme rainfall event along the northern coast of Taiwan on 2 June 2017
Chung-Chieh Wang, Ting-Yu Yeh, Chih-Sheng Chang, Ming-Siang Li, Kazuhisa Tsuboki, and Ching-Hwang Liu
Atmos. Chem. Phys., 23, 501–521, https://doi.org/10.5194/acp-23-501-2023,https://doi.org/10.5194/acp-23-501-2023, 2023
Short summary
Long-term upper-troposphere climatology of potential contrail occurrence over the Paris area derived from radiosonde observations
Kevin Wolf, Nicolas Bellouin, and Olivier Boucher
Atmos. Chem. Phys., 23, 287–309, https://doi.org/10.5194/acp-23-287-2023,https://doi.org/10.5194/acp-23-287-2023, 2023
Short summary
Equilibrium climate sensitivity increases with aerosol concentration due to changes in precipitation efficiency
Guy Dagan
Atmos. Chem. Phys., 22, 15767–15775, https://doi.org/10.5194/acp-22-15767-2022,https://doi.org/10.5194/acp-22-15767-2022, 2022
Short summary

Cited articles

Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeor., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003.
Andrews, T., Forster, P. M., Boucher, O., Bellouin, N., and Jones, A.: Precipitation, radiative forcing and global temperature change, Geophys. Res. Lett., 37, L14701, https://doi.org/10.1029/2010GL043991, 2010.
Barahona, D. and Nenes, A.: Parameterization of cirrus cloud formation in large-scale models: Homogeneous nucleation, J. Geophys. Res.-Atmos., 113, D11211, https://doi.org/10.1029/2007JD009355, 2008.
Barahona, D. and Nenes, A.: Parameterizing the competition between homogeneous and heterogeneous freezing in ice cloud formation – polydisperse ice nuclei, Atmos. Chem. Phys., 9, 5933–5948, https://doi.org/10.5194/acp-9-5933-2009, 2009.
Barahona, D. and Nenes, A.: Dynamical states of low temperature cirrus, Atmos. Chem. Phys., 11, 3757–3771, https://doi.org/10.5194/acp-11-3757-2011, 2011.
Download
Short summary
The ice nucleation scheme in the Community Atmosphere Model (CAM5) was improved by considering the effects of pre-existing ice crystals and some other modifications. Subsequently, the comparison between different ice nucleation parameterizations is investigated. Experiment using the ice nucleation parameterization of Kärcher et al. (2006) predicts a much smaller anthropogenic aerosol indirect forcing than that using the parameterizations of Liu and Penner (2005) and Barahona and Nenes (2009).
Altmetrics
Final-revised paper
Preprint