ABLE Automatic Weather Station (AWS) Data

This data set contains 1-minute resolution surface meteorological data from the Atmospheric Boundary Layer Experiment (ABLE) operated by the Argonne National Laboratory in the Walnut River Watershed in Butler County Kansas. The ABLE Automated Weather Station (AWS) Network consists of five stations. Data cover the period from 13 May to 25 June 2002. The data are in columnar ASCII format. Consult the README for more information.

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Temporal Range

  • Begin:  2002-05-13T00:00:00Z
    End:  2002-06-25T23:59:00Z

Keywords

Resource Type dataset
Temporal Range Begin 2002-05-13T00:00:00Z
Temporal Range End 2002-06-25T23:59:00Z
Temporal Resolution N/A
Bounding Box North Lat 41.00000
Bounding Box South Lat 34.00000
Bounding Box West Long -105.00000
Bounding Box East Long -92.00000
Spatial Representation grid
Spatial Resolution N/A
Related Links

Documentation #1 : ABLE_AWS.htm

Additional Information N/A
Resource Format ASCII: ASCII Text (text/plain)
Standardized Resource Format ASCII
Asset Size 24 MB
Legal Constraints

none


Access Constraints none
Software Implementation Language N/A

Resource Support Name EOL Data Support
Resource Support Email datahelp@eol.ucar.edu
Resource Support Organization UCAR/NCAR - Earth Observing Laboratory
Distributor UCAR/NCAR - Earth Observing Laboratory
Metadata Contact Name EOL Data Support
Metadata Contact Email datahelp@eol.ucar.edu
Metadata Contact Organization UCAR/NCAR - Earth Observing Laboratory

Author Richard L. Coulter
Publisher UCAR/NCAR - Earth Observing Laboratory
Publication Date 2007-10-24T20:48:48
Digital Object Identifier (DOI) https://doi.org/10.26023/YK5J-DJMD-M01
Alternate Identifier 77.027
Resource Version 1.0
Topic Category climatologyMeteorologyAtmosphere
Progress completed
Metadata Date 2024-02-07T22:46:01Z
Metadata Record Identifier edu.ucar.eol::77.027
Metadata Language eng; USA
Suggested Citation Richard L. Coulter. (2007). ABLE Automatic Weather Station (AWS) Data. 1.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.26023/YK5J-DJMD-M01. Accessed 28 November 2024.

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