Articles | Volume 12, issue 9
https://doi.org/10.5194/gmd-12-3863-2019
https://doi.org/10.5194/gmd-12-3863-2019
Development and technical paper
 | 
03 Sep 2019
Development and technical paper |  | 03 Sep 2019

Improved tropospheric and stratospheric sulfur cycle in the aerosol–chemistry–climate model SOCOL-AERv2

Aryeh Feinberg, Timofei Sukhodolov, Bei-Ping Luo, Eugene Rozanov, Lenny H. E. Winkel, Thomas Peter, and Andrea Stenke

Related authors

The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): Mercury modeling to support international environmental policy
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Terry Keating, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-65,https://doi.org/10.5194/gmd-2024-65, 2024
Preprint under review for GMD
Short summary
A fully coupled solid particle microphysics scheme for stratospheric aerosol injections within the aerosol-chemistry-climate-model SOCOL-AERv2
Sandro Vattioni, Rahel Weber, Aryehe Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
EGUsphere, https://doi.org/10.5194/egusphere-2024-444,https://doi.org/10.5194/egusphere-2024-444, 2024
Short summary
Influences of sources and weather dynamics on atmospheric deposition of Se species and other trace elements
Esther S. Breuninger, Julie Tolu, Iris Thurnherr, Franziska Aemisegger, Aryeh Feinberg, Sylvain Bouchet, Jeroen E. Sonke, Véronique Pont, Heini Wernli, and Lenny H. E. Winkel
Atmos. Chem. Phys., 24, 2491–2510, https://doi.org/10.5194/acp-24-2491-2024,https://doi.org/10.5194/acp-24-2491-2024, 2024
Short summary
Accelerating models for multiphase chemical kinetics through machine learning with polynomial chaos expansion and neural networks
Thomas Berkemeier, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger
Geosci. Model Dev., 16, 2037–2054, https://doi.org/10.5194/gmd-16-2037-2023,https://doi.org/10.5194/gmd-16-2037-2023, 2023
Short summary
Atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0: description and evaluation
Timofei Sukhodolov, Tatiana Egorova, Andrea Stenke, William T. Ball, Christina Brodowsky, Gabriel Chiodo, Aryeh Feinberg, Marina Friedel, Arseniy Karagodin-Doyennel, Thomas Peter, Jan Sedlacek, Sandro Vattioni, and Eugene Rozanov
Geosci. Model Dev., 14, 5525–5560, https://doi.org/10.5194/gmd-14-5525-2021,https://doi.org/10.5194/gmd-14-5525-2021, 2021
Short summary

Related subject area

Atmospheric sciences
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024,https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024,https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024,https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
RoadSurf 1.1: open-source road weather model library
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024,https://doi.org/10.5194/gmd-17-4837-2024, 2024
Short summary
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024,https://doi.org/10.5194/gmd-17-4755-2024, 2024
Short summary

Cited articles

Allen, R. J. and Landuyt, W.: The vertical distribution of black carbon in CMIP5 models: Comparison to observations and the importance of convective transport, J. Geophys. Res.-Atmos., 119, 4808–4835, https://doi.org/10.1002/2014jd021595, 2014. a
Andres, R. and Kasgnoc, A.: A time-averaged inventory of subaerial volcanic sulfur emissions, J. Geophys. Res., 103, 25251–25261, https://doi.org/10.1029/98jd02091, 1998. a
Arfeuille, F., Luo, B. P., Heckendorn, P., Weisenstein, D., Sheng, J. X., Rozanov, E., Schraner, M., Brönnimann, S., Thomason, L. W., and Peter, T.: Modeling the stratospheric warming following the Mt. Pinatubo eruption: uncertainties in aerosol extinctions, Atmos. Chem. Phys., 13, 11221–11234, https://doi.org/10.5194/acp-13-11221-2013, 2013. a
Ayers, G., Gillett, R., and Gras, J.: On the vapor pressure of sulfuric acid, Geophys. Res. Lett., 7, 433–436, https://doi.org/10.1029/GL007i006p00433, 1980. a
Baran, A. and Foot, J.: New application of the operational sounder HIRS in determining a climatology of sulphuric acid aerosol from the Pinatubo eruption, J. Geophys. Res., 99, 25673–25679, https://doi.org/10.1029/94jd02044, 1994. a
Download
Short summary
We have improved several aspects of atmospheric sulfur cycling in SOCOL-AER, an aerosol–chemistry–climate model. The newly implemented features in SOCOL-AERv2 include interactive deposition schemes, improved sulfur mass conservation, and expanded tropospheric chemistry. SOCOL-AERv2 shows better agreement with stratospheric aerosol observations and sulfur deposition networks compared to SOCOL-AERv1. SOCOL-AERv2 can be used to study impacts of sulfate aerosol on climate, chemistry, and ecosystems.