E3SMv2 simulation output from sensitivity study on cloud formation

Wan, Hui; Zhang, Kai

doi:10.25584/2481237

Title: E3SMv2 simulation output from sensitivity study on cloud formation

Dataset
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Abstract

This dataset contains E3SMv2 simulation output files discussed in the manuscript approved for IR in PNNL-SA-206024. The dataset was used to examine the occurrences of ultra-low cloud droplet number concentrations in E3SMv2. Submitting the manuscript to a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that.

Authors:

;

PNNL

Publication Date:: Sat Nov 30 23:00:00 EST 2024

DOE Contract Number:: AC05-76RL01830

Research Org.:: Pacific Northwest National Laboratory 2

Sponsoring Org.:: DOE

OSTI Identifier:: 2481237

DOI:: https://doi.org/10.25584/2481237

Citation Formats


                    Wan, Hui, and Zhang, Kai. E3SMv2 simulation output from sensitivity study on cloud formation.  United States: N. p., 2024. 
        Web.  doi:10.25584/2481237.

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                    Wan, Hui, & Zhang, Kai. E3SMv2 simulation output from sensitivity study on cloud formation.  United States.  doi:https://doi.org/10.25584/2481237

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                    Wan, Hui, and Zhang, Kai. 2024.  
"E3SMv2 simulation output from sensitivity study on cloud formation".  United States.  doi:https://doi.org/10.25584/2481237.  https://www.osti.gov/servlets/purl/2481237. Pub date:Sat Nov 30 23:00:00 EST 2024

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@article{osti_2481237,

  title        = {E3SMv2 simulation output from sensitivity study on cloud formation},

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

  abstractNote = {This dataset contains E3SMv2 simulation output files discussed in the manuscript approved for IR in PNNL-SA-206024. The dataset was used to examine the occurrences of ultra-low cloud droplet number concentrations in E3SMv2. Submitting the manuscript to a peer-reviewed journal will require making the model output publicly available. We plan to use DataHub for that.},

  doi          = {10.25584/2481237},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sat Nov 30 23:00:00 EST 2024},

  month        = {Sat Nov 30 23:00:00 EST 2024}

}

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DOI: https://doi.org/10.25584/2481237

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