Articles | Volume 10, issue 4
https://doi.org/10.5194/gmd-10-1817-2017
https://doi.org/10.5194/gmd-10-1817-2017
Development and technical paper
 | 
27 Apr 2017
Development and technical paper |  | 27 Apr 2017

An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

Daniel Rothenberg and Chien Wang

Related authors

Impacts on cloud radiative effects induced by coexisting aerosols converted from international shipping and maritime DMS emissions
Qinjian Jin, Benjamin S. Grandey, Daniel Rothenberg, Alexander Avramov, and Chien Wang
Atmos. Chem. Phys., 18, 16793–16808, https://doi.org/10.5194/acp-18-16793-2018,https://doi.org/10.5194/acp-18-16793-2018, 2018
Short summary
The Fifth International Workshop on Ice Nucleation phase 2 (FIN-02): laboratory intercomparison of ice nucleation measurements
Paul J. DeMott, Ottmar Möhler, Daniel J. Cziczo, Naruki Hiranuma, Markus D. Petters, Sarah S. Petters, Franco Belosi, Heinz G. Bingemer, Sarah D. Brooks, Carsten Budke, Monika Burkert-Kohn, Kristen N. Collier, Anja Danielczok, Oliver Eppers, Laura Felgitsch, Sarvesh Garimella, Hinrich Grothe, Paul Herenz, Thomas C. J. Hill, Kristina Höhler, Zamin A. Kanji, Alexei Kiselev, Thomas Koop, Thomas B. Kristensen, Konstantin Krüger, Gourihar Kulkarni, Ezra J. T. Levin, Benjamin J. Murray, Alessia Nicosia, Daniel O'Sullivan, Andreas Peckhaus, Michael J. Polen, Hannah C. Price, Naama Reicher, Daniel A. Rothenberg, Yinon Rudich, Gianni Santachiara, Thea Schiebel, Jann Schrod, Teresa M. Seifried, Frank Stratmann, Ryan C. Sullivan, Kaitlyn J. Suski, Miklós Szakáll, Hans P. Taylor, Romy Ullrich, Jesus Vergara-Temprado, Robert Wagner, Thomas F. Whale, Daniel Weber, André Welti, Theodore W. Wilson, Martin J. Wolf, and Jake Zenker
Atmos. Meas. Tech., 11, 6231–6257, https://doi.org/10.5194/amt-11-6231-2018,https://doi.org/10.5194/amt-11-6231-2018, 2018
Short summary
Effective radiative forcing in the aerosol–climate model CAM5.3-MARC-ARG
Benjamin S. Grandey, Daniel Rothenberg, Alexander Avramov, Qinjian Jin, Hsiang-He Lee, Xiaohong Liu, Zheng Lu, Samuel Albani, and Chien Wang
Atmos. Chem. Phys., 18, 15783–15810, https://doi.org/10.5194/acp-18-15783-2018,https://doi.org/10.5194/acp-18-15783-2018, 2018
Short summary
On the representation of aerosol activation and its influence on model-derived estimates of the aerosol indirect effect
Daniel Rothenberg, Alexander Avramov, and Chien Wang
Atmos. Chem. Phys., 18, 7961–7983, https://doi.org/10.5194/acp-18-7961-2018,https://doi.org/10.5194/acp-18-7961-2018, 2018
Short summary
Uncertainty in counting ice nucleating particles with continuous flow diffusion chambers
Sarvesh Garimella, Daniel A. Rothenberg, Martin J. Wolf, Robert O. David, Zamin A. Kanji, Chien Wang, Michael Rösch, and Daniel J. Cziczo
Atmos. Chem. Phys., 17, 10855–10864, https://doi.org/10.5194/acp-17-10855-2017,https://doi.org/10.5194/acp-17-10855-2017, 2017
Short summary

Related subject area

Atmospheric sciences
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025,https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025,https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025,https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025,https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025,https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary

Cited articles

Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 2. Multiple aerosol types, J. Geophys. Res., 105, 6837, https://doi.org/10.1029/1999JD901161, 2000.
Abdul-Razzak, H. and Ghan, S. J.: Parameterization of the influence of organic surfactants on aerosol activation, J. Geophys. Res.-Atmos., 109, D3, https://doi.org/10.1029/2003JD004043, 2004.
Adams, B. M., Ebeida, M. S., Eldred, M. S., Jakeman, J. D., Swiler, L. P., Stephens, J. A., Vigil, D. M., Wildey, T. M., Bohnhoff, W. J., Dalbey, K. R., Eddy, J. P., Hu, K. T., Bauman, L. E., and Hough, P. D.: DAKOTA, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.0 User's Manual, Tech. rep., Sandia National Laboratories, Albuquerque, New Mexico, 2014.
Albani, S., Mahowald, N. M., Perry, A. T., Scanza, R. A., Zender, C. S., Heavens, N. G., Maggi, V., Kok, J. F., and Otto-Bliesner, B. L.: Improved dust representation in the Community Atmosphere Model, J. Adv. Model. Earth Sys., 6, 541–570, https://doi.org/10.1002/2013MS000279, 2014.
Barahona, D. and Nenes, A.: Parameterization of cloud droplet formation in large-scale models: Including effects of entrainment, J. Geophys. Res., 112, D16206, https://doi.org/10.1029/2007JD008473, 2007.
Download
Short summary
Climate models include descriptions of how cloud droplets form from particles in the atmosphere. We have developed an efficient parameterization of this process by building an emulator of a detailed model, which can accurately predict cloud droplet number concentrations and potentially include additional physics and chemistry. We further show that using different parameterizations could influence droplet number estimates in global models and their aerosol indirect effect on climate.
Share