dataset · Global
NOAA Global Historical Climatology Network Daily (GHCN-D)
<br /> UPDATE TO GHCN PREFIXES - The NODD team is working on improving performance and access to the GHCNd data and will be implementing an updated prefix structure. For more information on the prefix changes, please see the "[READ ME on the NODD Github](https://github.com/NOAA-Big-Data-Program/bdp-data-docs/tree/main/GHCN-D)". If you have questions, comments, or feedback, please reach out to nodd@noaa.gov with GHCN in the subject line. <br /> <br > Global Historical Climatology Network - Daily
Visit source ↗Source details
Licence: NOAA data disseminated through NODD is made available under the [Creative Commons 1.0 Universal Public Domain Dedication (CC0-1.0) license](https://creativecommons.org/publicdomain/zero/1.0/?ref=choos
Evidence quality: 55.3
Listed in aws-odr public catalogue API on 2026-10-16; relevance/value screened (haiku).
Metadata checked: 2026-10-14T13:20:00.000Z
What's in it
- Data offered docs-verified
- daily precipitation (about two thirds of stations measure precipitation only) · daily maximum temperature · daily minimum temperature · temperature at time of observation · snowfall · snow depth
- Coverage docs-verified
- Global land areas (land-based stations worldwide) · 1763 to present
- Resolution docs-verified
- Daily; station-based point measurements
- Update frequency docs-verified
- Daily
- Formats docs-verified
- CSV
- Access docs-verified
- Free and open; CC0-1.0 public domain dedication (no restrictions on use). Public S3 bucket, no AWS account needed for CLI access.
Useful for
- Use cases llm-inferred
- Long-run rainfall and temperature baseline from nearest GHCN station for FRA or drainage design context · Snow depth and snowfall history for cold-weather construction or civils risk assessment · Temperature trend context for ecological or habitat baseline reports
- Audience llm-inferred
- flood consultants · hydrologists · drainage engineers · environmental consultants · climate analysts
Limitations
- Constraints llm-inferred
- Station-based point data, not gridded; coverage density varies by location · About two thirds of stations record precipitation only, so other variables are sparser · Data is a composite from numerous sources, so consistency varies over time · Data is delivered as one CSV file per year, with no native API · NODD is changing the prefix structure, so scripts relying on current S3 paths may need updating
Evidence
- arn:aws:s3:::noaa-ghcn-pds, arn:aws:sns:us-east-1:123901341784:NewGHCNObject
- https://registry.opendata.aws/noaa-ghcn/
Check upstream coverage, uncertainty and licence before use. Station observations are not forecasts or design levels.