U.S. Surface Monthly Station Normals and Sequential Data

This dataset contains 30-year normals of temperature and precipitation for U.S. stations. Also included are the sequential temperature and precipitation data that were used to compute the normals.

To Access Resource:

Questions? Email Resource Support Contact:

  • Bob Dattore
    dattore@ucar.edu
    UCAR/NCAR - Research Data Archive

Temporal Range

  • Begin:  1941-01
    End:  1990-12

Keywords

Resource Type dataset
Temporal Range Begin 1941-01
Temporal Range End 1990-12
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 ASCII
Standardized Resource Format ASCII
Asset Size 166.00 MB
Legal Constraints

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

Resource Support Name Bob Dattore
Resource Support Email dattore@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 National Climatic Data Center, NESDIS, NOAA, U.S. Department of Commerce
Publisher Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory
Publication Date 1983-09-13
Digital Object Identifier (DOI) https://doi.org/10.5065/08K2-WD63
Alternate Identifier d574000
Resource Version N/A
Topic Category climatologyMeteorologyAtmosphere
Progress completed
Metadata Date 2024-08-04T02:11:16Z
Metadata Record Identifier edu.ucar.rda::d574000
Metadata Language eng; USA
Suggested Citation National Climatic Data Center, NESDIS, NOAA, U.S. Department of Commerce. (1983). U.S. Surface Monthly Station Normals and Sequential Data. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/08K2-WD63. Accessed 25 November 2024.

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