Articles | Volume 13, issue 9
https://doi.org/10.5194/acp-13-4963-2013
https://doi.org/10.5194/acp-13-4963-2013
Research article
 | 
14 May 2013
Research article |  | 14 May 2013

Evaluating and constraining ice cloud parameterizations in CAM5 using aircraft measurements from the SPARTICUS campaign

K. Zhang, X. Liu, M. Wang, J. M. Comstock, D. L. Mitchell, S. Mishra, and G. G. Mace

Related authors

The AeroCom evaluation and intercomparison of organic aerosol in global models
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895, https://doi.org/10.5194/acp-14-10845-2014,https://doi.org/10.5194/acp-14-10845-2014, 2014
Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models
H. Wan, P. J. Rasch, K. Zhang, Y. Qian, H. Yan, and C. Zhao
Geosci. Model Dev., 7, 1961–1977, https://doi.org/10.5194/gmd-7-1961-2014,https://doi.org/10.5194/gmd-7-1961-2014, 2014
Influence of surface morphology on the immersion mode ice nucleation efficiency of hematite particles
N. Hiranuma, N. Hoffmann, A. Kiselev, A. Dreyer, K. Zhang, G. Kulkarni, T. Koop, and O. Möhler
Atmos. Chem. Phys., 14, 2315–2324, https://doi.org/10.5194/acp-14-2315-2014,https://doi.org/10.5194/acp-14-2315-2014, 2014
Numerical issues associated with compensating and competing processes in climate models: an example from ECHAM-HAM
H. Wan, P. J. Rasch, K. Zhang, J. Kazil, and L. R. Leung
Geosci. Model Dev., 6, 861–874, https://doi.org/10.5194/gmd-6-861-2013,https://doi.org/10.5194/gmd-6-861-2013, 2013

Related subject area

Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Estimating the concentration of silver iodide needed to detect unambiguous signatures of glaciogenic cloud seeding
Jing Yang, Jiaojiao Li, Meilian Chen, Xiaoqin Jing, Yan Yin, Bart Geerts, Zhien Wang, Yubao Liu, Baojun Chen, Shaofeng Hua, Hao Hu, Xiaobo Dong, Ping Tian, Qian Chen, and Yang Gao
Atmos. Chem. Phys., 24, 13833–13848, https://doi.org/10.5194/acp-24-13833-2024,https://doi.org/10.5194/acp-24-13833-2024, 2024
Short summary
Ice-nucleating particle concentration impacts cloud properties over Dronning Maud Land, East Antarctica, in COSMO-CLM2
Florian Sauerland, Niels Souverijns, Anna Possner, Heike Wex, Preben Van Overmeiren, Alexander Mangold, Kwinten Van Weverberg, and Nicole van Lipzig
Atmos. Chem. Phys., 24, 13751–13768, https://doi.org/10.5194/acp-24-13751-2024,https://doi.org/10.5194/acp-24-13751-2024, 2024
Short summary
Numerical simulation of aerosol concentration effects on cloud droplet size spectrum evolutions of warm stratiform clouds in Jiangxi, China
Yi Li, Xiaoli Liu, and Hengjia Cai
Atmos. Chem. Phys., 24, 13525–13540, https://doi.org/10.5194/acp-24-13525-2024,https://doi.org/10.5194/acp-24-13525-2024, 2024
Short summary
The impact of aerosol on cloud water: a heuristic perspective
Fabian Hoffmann, Franziska Glassmeier, and Graham Feingold
Atmos. Chem. Phys., 24, 13403–13412, https://doi.org/10.5194/acp-24-13403-2024,https://doi.org/10.5194/acp-24-13403-2024, 2024
Short summary
The presence of clouds lowers climate sensitivity in the MPI-ESM1.2 climate model
Andrea Mosso, Thomas Hocking, and Thorsten Mauritsen
Atmos. Chem. Phys., 24, 12793–12806, https://doi.org/10.5194/acp-24-12793-2024,https://doi.org/10.5194/acp-24-12793-2024, 2024
Short summary

Cited articles

Barahona, D. and Nenes, A.: Parameterization of cirrus cloud formation in large-scale models: homogeneous nucleation, J. Geophys. Res., 113, D11211, https://doi.org/10.1029/2007JD009355, 2008.
Barahona, D. and Nenes, A.: Parameterizing the competition between homogeneous and heterogeneous freezing in cirrus cloud formation – monodisperse ice nuclei, Atmos. Chem. Phys., 9, 369–381, https://doi.org/10.5194/acp-9-369-2009, 2009{a}.
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{b}.
Bretherton, C. S. and Park, S.: A new moist turbulence parameterization in the Community Atmosphere Model, J. Climate, 22, 3422–3448, https://doi.org/10.1175/2008JCLI2556.1, 2009.
Chen, J.-P., Hazra, A., and Levin, Z.: Parameterizing ice nucleation rates using contact angle and activation energy derived from laboratory data, Atmos. Chem. Phys., 8, 7431–7449, https://doi.org/10.5194/acp-8-7431-2008, 2008.
Download
Altmetrics
Final-revised paper
Preprint