Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 492

The DOI matches its Crossref record.

The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea level pressure, and station pressure data

Open access
Vose, R, Schmoyer, R, Steurer, P, Peterson, T, Heim, R, Karl, T, Eischeid, J·1992

Abstract

Interest in global climate change has risen dramatically during the last several years. In a similar fashion, the number of data sets available to study global change has also increased. Unfortunately, these data sets have been compiled by many different organizations/researchers, making it confusing and time consuming for individual researchers to acquire the ``best`` data. In response to this rapid growth in the number of global data sets, the Carbon Dioxide Information Analysis Center (CDIAC) and the National Climatic Data Center (NCDC) commenced the Global Historical Climatology Network (GHCN) project. The purpose of this project is to compile an improved global base-line data set of long-term monthly mean temperature, precipitation, sea level pressure, and station pressure for a dense network. of worldwide meteorological stations. Specifically, the GHCN project seeks to consolidate the numerous preexisting national-, regional-, and global-scale data sets into a single global climate data base that can be updated, enhanced, and distributed at regular intervals. The first version of the GHCN data base was completed during the summer of 1992. It contains 6039 temperature, 7533 precipitation, 1883 sea level pressure, and 1873 station pressure stations. All stations have at least 10 years of data, 40% have more than 50 years of data, and 10% have more than 100 years of data. Spatial coverage is good over most of the globe, particularly for the United States and central Europe. In comparison to other major global data sets, dramatic improvements are evident over South America, Africa, and Asia. The GHCN data base is available as a Numeric Data Package (NDP) from CDIAC. The NDP consists of this document and two magnetic tapes that contain machine-readable data files and accompanying retrieval codes. This document describes, in detail, both the GHCN data base and the contents of the magnetic tap

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2172/10178730

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 492

Metadata

Authors
Vose, R., Schmoyer, R., Steurer, P., Peterson, T., Heim, R., Karl, T., & Eischeid, J.
Published
1992-07-01
OpenAlex
W4234492793
Cited by
492
References
0
Type
report
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea level pressure, and station pressure data. https://app.cochat.ai/papers/10.2172/10178730
The paper
Vose, R., Schmoyer, R., Steurer, P., Peterson, T., Heim, R., Karl, T., & Eischeid, J. (1992). The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea level pressure, and station pressure data. https://doi.org/10.2172/10178730

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.