S2S Hindcast TC Tracks

This dataset contains tropical cyclone (TCs) tracks in the CESM2 S2S reforecasts for the period of 2002 - 2019. We use the TempestExtremes tracking algorithm to detect and track TCs (or TC-like disturbances) on the CESM2 CAM6 native grid, utilizing all 11 ensemble members and 6-hourly output of near-surface winds, sea level pressure, and geopotential thickness between 200 and 500 hPa. D

To Access Resource:

Questions? Email Resource Support Contact:

  • Teagan King
    tking@ucar.edu
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  2002-01
    End:  2019-10

Keywords

Resource Type dataset
Temporal Range Begin 2002-01
Temporal Range End 2019-10
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links N/A
Additional Information N/A
Resource Format NetCDF (Binary)
Standardized Resource Format NetCDF
Asset Size 0.00 MB
Legal Constraints

Creative Commons Attribution 4.0 International License
Access Constraints None
Software Implementation Language N/A

Resource Support Name Teagan King
Resource Support Email tking@ucar.edu
Resource Support Organization UCAR/NCAR - Research Data Archive
Distributor NCAR Research Data Archive
Metadata Contact Name N/A
Metadata Contact Email rdahelp@ucar.edu
Metadata Contact Organization NCAR Research Data Archive

Author Li, Hui
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 2025-07-01
Digital Object Identifier (DOI) Not Assigned
Alternate Identifier d651062
Resource Version N/A
Topic Category climatologyMeteorologyAtmosphere
Progress completed
Metadata Date 2025-07-01T18:05:03Z
Metadata Record Identifier edu.ucar.rda::d651062
Metadata Language eng; USA
Suggested Citation Li, Hui. (2025). S2S Hindcast TC Tracks. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://rda.ucar.edu/datasets/d651062/. Accessed 20 August 2025.

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