E3SMv1 simulation output from sensitivity study on aerosol process coupling

Wan, Hui; Zhang, Kai

doi:10.25584/2529469

Title: E3SMv1 simulation output from sensitivity study on aerosol process coupling

Dataset
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Abstract

This dataset contains annual mean and 6-hourly output data from a set of E3SMv1 simulations that demonstrates the impact of numerical process coupling on the simulated dust life cycle. The simulations are documented and analyzed in the attached manuscript (pdf file). Publishing the manuscript in a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that. The data files to be uploaded are currently saved on Compy under /compyfs/wanh895/scidac_share/cflx_2023/

Authors:

;

PNNL

Publication Date:: Sun Dec 03 23:00:00 EST 2023

DOE Contract Number:: AC05-76RL01830

Research Org.:: Pacific Northwest National Laboratory 2

Sponsoring Org.:: DOE

OSTI Identifier:: 2529469

DOI:: https://doi.org/10.25584/2529469

Citation Formats


                    Wan, Hui, and Zhang, Kai. E3SMv1 simulation output from sensitivity study on aerosol process coupling.  United States: N. p., 2023. 
        Web.  doi:10.25584/2529469.

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                    Wan, Hui, & Zhang, Kai. E3SMv1 simulation output from sensitivity study on aerosol process coupling.  United States.  doi:https://doi.org/10.25584/2529469

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                    Wan, Hui, and Zhang, Kai. 2023.  
"E3SMv1 simulation output from sensitivity study on aerosol process coupling".  United States.  doi:https://doi.org/10.25584/2529469.  https://www.osti.gov/servlets/purl/2529469. Pub date:Sun Dec 03 23:00:00 EST 2023

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@article{osti_2529469,

  title        = {E3SMv1 simulation output from sensitivity study on aerosol process coupling},

  author       = {Wan, Hui and Zhang, Kai},

  abstractNote = {This dataset contains annual mean and 6-hourly output data from a set of E3SMv1 simulations that demonstrates the impact of numerical process coupling on the simulated dust life cycle. The simulations are documented and analyzed in the attached manuscript (pdf file). Publishing the manuscript in a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that. The data files to be uploaded are currently saved on Compy under /compyfs/wanh895/scidac_share/cflx_2023/},

  doi          = {10.25584/2529469},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Dec 03 23:00:00 EST 2023},

  month        = {Sun Dec 03 23:00:00 EST 2023}

}

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DOI: https://doi.org/10.25584/2529469

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