Articles | Volume 16, issue 18
https://doi.org/10.5194/acp-16-12059-2016
https://doi.org/10.5194/acp-16-12059-2016
Research article
 | 
27 Sep 2016
Research article |  | 27 Sep 2016

Parameterizing cloud condensation nuclei concentrations during HOPE

Luke B. Hande, Christa Engler, Corinna Hoose, and Ina Tegen

Related authors

Partitioning the primary ice formation modes in large eddy simulations of mixed-phase clouds
Luke B. Hande and Corinna Hoose
Atmos. Chem. Phys., 17, 14105–14118, https://doi.org/10.5194/acp-17-14105-2017,https://doi.org/10.5194/acp-17-14105-2017, 2017
Short summary
Seasonal variability of Saharan desert dust and ice nucleating particles over Europe
L. B. Hande, C. Engler, C. Hoose, and I. Tegen
Atmos. Chem. Phys., 15, 4389–4397, https://doi.org/10.5194/acp-15-4389-2015,https://doi.org/10.5194/acp-15-4389-2015, 2015
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Modeling impacts of dust mineralogy on fast climate response
Qianqian Song, Paul Ginoux, María Gonçalves Ageitos, Ron L. Miller, Vincenzo Obiso, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 7421–7446, https://doi.org/10.5194/acp-24-7421-2024,https://doi.org/10.5194/acp-24-7421-2024, 2024
Short summary
Uncertainties in laboratory-measured shortwave refractive indices of mineral dust aerosols and derived optical properties: a theoretical assessment
Senyi Kong, Zheng Wang, and Lei Bi
Atmos. Chem. Phys., 24, 6911–6935, https://doi.org/10.5194/acp-24-6911-2024,https://doi.org/10.5194/acp-24-6911-2024, 2024
Short summary
Diagnosing uncertainties in global biomass burning emission inventories and their impact on modeled air pollutants
Wenxuan Hua, Sijia Lou, Xin Huang, Lian Xue, Ke Ding, Zilin Wang, and Aijun Ding
Atmos. Chem. Phys., 24, 6787–6807, https://doi.org/10.5194/acp-24-6787-2024,https://doi.org/10.5194/acp-24-6787-2024, 2024
Short summary
Role of atmospheric aerosols in severe winter fog over the Indo-Gangetic Plain of India: a case study
Chandrakala Bharali, Mary Barth, Rajesh Kumar, Sachin D. Ghude, Vinayak Sinha, and Baerbel Sinha
Atmos. Chem. Phys., 24, 6635–6662, https://doi.org/10.5194/acp-24-6635-2024,https://doi.org/10.5194/acp-24-6635-2024, 2024
Short summary
Long-term variability in black carbon emissions constrained by gap-filled absorption aerosol optical depth and associated premature mortality in China
Wenxin Zhao, Yu Zhao, Yu Zheng, Dong Chen, Jinyuan Xin, Kaitao Li, Huizheng Che, Zhengqiang Li, Mingrui Ma, and Yun Hang
Atmos. Chem. Phys., 24, 6593–6612, https://doi.org/10.5194/acp-24-6593-2024,https://doi.org/10.5194/acp-24-6593-2024, 2024
Short summary

Cited articles

Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation: 2. Multiple aerosol types, J. Geophys. Res.-Atmos., 105, 6837–6844, 2000.
Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 3. Sectional representation, J. Geophys. Res.-Atmos., 107, AAC 1-1–AAC 1-6, https://doi.org/10.1029/2001JD000483, 2002.
Abdul-Razzak, H., Ghan, S. J., and Rivera-Carpio, C.: A parameterization of aerosol activation: 1. Single aerosol type, J. Geophys. Res.-Atmos., 103, 6123–6131, 1998.
Bellouin, N., Mann, G. W., Woodhouse, M. T., Johnson, C., Carslaw, K. S., and Dalvi, M.: Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model, Atmos. Chem. Phys., 13, 3027–3044, https://doi.org/10.5194/acp-13-3027-2013, 2013.
Birmili, W., Stratmann, F., and Wiedensohler, A.: Design of a DMA-based size spectrometer for a large particle size range and stable operation, J. Aerosol Sci., 30, 549–553, 1999.
Download
Short summary
An aerosol model was used to simulate the concentration of natural and anthropogenic aerosols over Germany. Using a detailed parameterization of CCN activation, which includes information of aerosol chemical and physical properties, CCN concentrations were calculated. Using these results, a series of best fit functions were used to define a new parameterization, which is a simple function of vertical velocity and pressure. The new parameterization is easy to implement in models.
Altmetrics
Final-revised paper
Preprint