GFDL SEASAT Scatterometer Derived Winds

SEASAT scatterometer derived wind speed and direction, global coverage, July-October 1978, approximately 50 km resolution, objectively dealiased by Robert Atlas at GSFC.

To Access Resource:

Questions? Email Resource Support Contact:

  • Chi-Fan Shih
    chifan@ucar.edu
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  1978-07
    End:  1978-10

Keywords

Resource Type dataset
Temporal Range Begin 1978-07
Temporal Range End 1978-10
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 Binary
Standardized Resource Format N/A
Asset Size 199.81 MB
Legal Constraints

Use of this dataset is subject to UCAR's Terms of Use, except that commercial use is generally not prohibited.
Access Constraints Registration on the RDA web site is a requirement for access to the data.
Software Implementation Language N/A

Resource Support Name Chi-Fan Shih
Resource Support Email chifan@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 Program Office, Earth Observing System, Goddard Space Flight Center, NASA
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 1988-05-06
Digital Object Identifier (DOI) https://doi.org/10.5065/QCAT-0A04
Alternate Identifier ds726.0
Resource Version N/A
Topic Category oceans
Progress completed
Metadata Date 2021-09-16T16:05:01-07:00
Metadata Record Identifier edu.ucar.rda::ds726.0
Metadata Language eng; USA
Suggested Citation Program Office, Earth Observing System, Goddard Space Flight Center, NASA. (1988). GFDL SEASAT Scatterometer Derived Winds. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/QCAT-0A04. Accessed 08 June 2023.

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