Articles | Volume 8, issue 3
https://doi.org/10.5194/gmd-8-631-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-631-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
20 Mar 2015
Development and technical paper |
| 20 Mar 2015
Evaluation of the global aerosol microphysical ModelE2-TOMAS model against satellite and ground-based observations
Y. H. Lee
CORRESPONDING AUTHOR
Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
P. J. Adams
Department of Civil and Environmental Engineering and Department of Engineering Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA
D. T. Shindell
Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
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- Interactive nature of climate change and aerosol forcing L. Nazarenko et al. https://doi.org/10.1002/2016JD025809
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- Cloud condensation nuclei over the Southern Ocean: wind dependence and seasonal cycles J. Gras & M. Keywood https://doi.org/10.5194/acp-17-4419-2017
- Effect of model errors in ambient air humidity on the aerosol optical depth obtained via aerosol hygroscopicity in eastern China in the Atmospheric Chemistry and Climate Model Intercomparison Project datasets W. CHANG https://doi.org/10.1080/16742834.2019.1588063
- Climate and health impacts of US emissions reductions consistent with 2 °C D. Shindell et al. https://doi.org/10.1038/nclimate2935
- Evaluation of observed and modelled aerosol lifetimes using radioactive tracers of opportunity and an ensemble of 19 global models N. Kristiansen et al. https://doi.org/10.5194/acp-16-3525-2016
- On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models S. Zhang et al. https://doi.org/10.5194/acp-16-2765-2016
- Global fine-mode aerosol radiative effect, as constrained by comprehensive observations C. Chung et al. https://doi.org/10.5194/acp-16-8071-2016
- Bounding Global Aerosol Radiative Forcing of Climate Change N. Bellouin et al. https://doi.org/10.1029/2019RG000660
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20 citations as recorded by crossref.
- Quantifying organic aerosol single scattering albedo over the tropical biomass burning regions J. Chu & K. Ha https://doi.org/10.1016/j.atmosenv.2016.09.069
- Interactive nature of climate change and aerosol forcing L. Nazarenko et al. https://doi.org/10.1002/2016JD025809
- Measurement report: Cloud processes and the transport of biological emissions affect southern ocean particle and cloud condensation nuclei concentrations K. Sanchez et al. https://doi.org/10.5194/acp-21-3427-2021
- Evaluating the skill of high-resolution WRF-Chem simulations in describing drivers of aerosol direct climate forcing on the regional scale P. Crippa et al. https://doi.org/10.5194/acp-16-397-2016
- Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation G. Fanourgakis et al. https://doi.org/10.5194/acp-19-8591-2019
- Potential impact of a US climate policy and air quality regulations on future air quality and climate change Y. Lee et al. https://doi.org/10.5194/acp-16-5323-2016
- A parameterization for the light scattering enhancement factor with aerosol chemical compositions Y. Yu et al. https://doi.org/10.1016/j.atmosenv.2018.08.016
- Cloud condensation nuclei over the Southern Ocean: wind dependence and seasonal cycles J. Gras & M. Keywood https://doi.org/10.5194/acp-17-4419-2017
- Effect of model errors in ambient air humidity on the aerosol optical depth obtained via aerosol hygroscopicity in eastern China in the Atmospheric Chemistry and Climate Model Intercomparison Project datasets W. CHANG https://doi.org/10.1080/16742834.2019.1588063
- Climate and health impacts of US emissions reductions consistent with 2 °C D. Shindell et al. https://doi.org/10.1038/nclimate2935
- Evaluation of observed and modelled aerosol lifetimes using radioactive tracers of opportunity and an ensemble of 19 global models N. Kristiansen et al. https://doi.org/10.5194/acp-16-3525-2016
- On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models S. Zhang et al. https://doi.org/10.5194/acp-16-2765-2016
- Global fine-mode aerosol radiative effect, as constrained by comprehensive observations C. Chung et al. https://doi.org/10.5194/acp-16-8071-2016
- Bounding Global Aerosol Radiative Forcing of Climate Change N. Bellouin et al. https://doi.org/10.1029/2019RG000660
- IAP-AACM v1.0: a global to regional evaluation of the atmospheric chemistry model in CAS-ESM Y. Wei et al. https://doi.org/10.5194/acp-19-8269-2019
- An aerosol classification scheme for global simulations using the K-means machine learning method J. Li et al. https://doi.org/10.5194/gmd-15-509-2022
- Fungal treatment for liquid waste containing U(VI) and Th(IV) E. Ghoniemy et al. https://doi.org/10.1016/j.btre.2020.e00472
- The Global Spatial Pattern of Aerosol Optical, Microphysical and Chemical Properties Derived from AERONET Observations Y. Zhang et al. https://doi.org/10.3390/rs17213624
- Recovery of uranium from solutions using Aspergillus nidulans isolated from monazite mineral S. Mansour Abozaid et al. https://doi.org/10.1080/03067319.2021.1939022
- Global aerosol modeling with MADE3 (v3.0) in EMAC (based on v2.53): model description and evaluation J. Kaiser et al. https://doi.org/10.5194/gmd-12-541-2019
Saved (final revised paper)
Latest update: 01 Nov 2026
Short summary
We have implemented the TwO-Moment Aerosol Sectional (TOMAS) microphysics model in NASA GISS ModelE2, called “ModelE2-TOMAS”. We compared global budgets of ModelE2-TOMAS to other global aerosol models and evaluated the model with various observations such as aerosol precursor gas, aerosol mass, number concentrations, and aerosol optical depth. We found that ModelE2-TOMAS agrees with observations reasonably and that its predictions are within the range of other global aerosol model predictions.
We have implemented the TwO-Moment Aerosol Sectional (TOMAS) microphysics model in NASA GISS...
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