Articles | Volume 21, issue 3
https://doi.org/10.5194/acp-21-1861-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-1861-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Simulation of radon-222 with the GEOS-Chem global model: emissions, seasonality, and convective transport
National Institute of Aerospace, Hampton, Virginia, USA
National Institute of Aerospace, Hampton, Virginia, USA
James H. Crawford
NASA Langley Research Center, Hampton, Virginia, USA
Gao Chen
NASA Langley Research Center, Hampton, Virginia, USA
T. Duncan Fairlie
NASA Langley Research Center, Hampton, Virginia, USA
Scott Chambers
Australian Nuclear Science and Technology Organization, Kirrawee, New South Wales, Australia
Chang-Hee Kang
Department of Chemistry, Jeju National University, Jeju, Republic of Korea
Alastair G. Williams
Australian Nuclear Science and Technology Organization, Kirrawee, New South Wales, Australia
Kai Zhang
Pacific Northwest National Laboratory, Richland, Washington, USA
David B. Considine
NASA Headquarters, Washington D.C., USA
Melissa P. Sulprizio
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Robert M. Yantosca
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Data sets
Simulation of radon-222 with the GEOS-Chem global model: Emissions, seasonality, and convective transport Bo Zhang, Hongyu Liu, James H. Crawford, Gao Chen, T. Duncan Fairlie, Scott Chambers, Chang-Hee Kang, Alastair G. Williams, Kai Zhang, David B. Considine, Melissa P. Sulprizio, and Robert M. Yantosca https://doi.org/10.5281/zenodo.3942287
Short summary
We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn emissions and characterize convective transport in the model. We demonstrate the potential of a customized global 222Rn emission scenario to improve simulated surface 222Rn concentrations and seasonality. We assess convective transport using observed 222Rn vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn...
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