Global Historical Climatology Network - Daily (GHCN-Daily), Version 3

Metadata Updated: February 8, 2018

The Global Historical Climatology Network - Daily (GHCN-Daily) dataset integrates daily climate observations from approximately 30 different data sources. Version 3 was released in September 2012 with the addition of data from two additional station networks. Changes to the processing system associated with the version 3 release also allowed for updates to occur 7 days a week rather than only on most weekdays. Version 3 contains station-based measurements from well over 90,000 land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. Over 25,000 stations are regularly updated with observations from within roughly the last month. The dataset is also routinely reconstructed (usually every week) from its roughly 30 data sources to ensure that GHCN-Daily is generally in sync with its growing list of constituent sources. During this process, quality assurance checks are applied to the full dataset. Where possible, GHCN-Daily station data are also updated daily from a variety of data streams. Station values for each daily update also undergo a suite of quality checks.

Access & Use Information

Downloads & Resources


Metadata Date October 24, 2017
Metadata Created Date September 26, 2015
Metadata Updated Date February 8, 2018
Reference Date(s) September 24, 2012 (publication)
Frequency Of Update daily

Metadata Source

Harvested from NOAA CSW Harvest Source

Graphic Preview

Map of GHCN-Daily stations

Additional Metadata

Resource Type Dataset
Metadata Date October 24, 2017
Metadata Created Date September 26, 2015
Metadata Updated Date February 8, 2018
Reference Date(s) September 24, 2012 (publication)
Responsible Party DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce (Point of Contact)
Contact Email
Access Constraints Cite this dataset when used as a source: Menne, Matthew J., Imke Durre, Bryant Korzeniewski, Shelley McNeal, Kristy Thomas, Xungang Yin, Steven Anthony, Ron Ray, Russell S. Vose, Byron E.Gleason, and Tamara G. Houston (2012): Global Historical Climatology Network - Daily (GHCN-Daily), Version 3. [indicate subset used]. NOAA National Climatic Data Center. doi:10.7289/V5D21VHZ [access date]., Publications citing this dataset should also cite the following article: Matthew J. Menne, Imke Durre, Russell S. Vose, Byron E. Gleason, and Tamara G. Houston, 2012: An Overview of the Global Historical Climatology Network-Daily Database. J. Atmos. Oceanic Technol., 29, 897-910. doi:10.1175/JTECH-D-11-00103.1., NCEI cannot assume liability for any damages caused by any errors or omissions in the data, nor as a result of the failure of the data to function on a particular system. NCEI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives.
Bbox East Long 180.0
Bbox North Lat 83.0
Bbox South Lat -90.0
Bbox West Long -180.0
Coupled Resource
Frequency Of Update daily
Graphic Preview Description Map of GHCN-Daily stations
Graphic Preview File
Graphic Preview Type PNG
Guid gov.noaa.ncdc:C00861
Harvest Object Id 3395d11a-0390-4026-a8d2-e7199ce07bca
Harvest Source Id 2aed8e29-fc5b-4cde-aa66-fb1118fd705e
Harvest Source Title NOAA CSW Harvest Source
Licence The dataset cannot be used to quantify all aspects of climate variability and change without any additional processing. In general, the stations providing daily observations were not managed to meet the desired standards for climate monitoring. Rather, the stations were deployed to meet the demands of agriculture, hydrology, weather forecasting, aviation, etc. GHCN-Daily data have not been homogenized to account for the potential artifacts associated with the various reporting practices at stations. Users must consider whether the potential for changes in systematic bias might be important for their particular application.
Metadata Language
Metadata Type geospatial
Progress onGoing
Spatial Data Service Type
Spatial Reference System
Spatial Harvester True
Temporal Extent Begin 1880-01-01

Didn't find what you're looking for? Suggest a dataset here.