The DOI matches its Crossref record.
Overview of the Integrated Global Radiosonde Archive
Abstract
This paper provides a general description of the Integrated Global Radiosonde Archive (IGRA), a new radiosonde dataset from the National Climatic Data Center (NCDC). IGRA consists of radiosonde and pilot balloon observations at more than 1500 globally distributed stations with varying periods of record, many of which extend from the 1960s to present. Observations include pressure, temperature, geopotential height, dewpoint depression, wind direction, and wind speed at standard, surface, tropopause, and significant levels. IGRA contains quality-assured data from 11 different sources. Rigorous procedures are employed to ensure proper station identification, eliminate duplicate levels within soundings, and select one sounding for every station, date, and time. The quality assurance algorithms check for format problems, physically implausible values, internal inconsistencies among variables, runs of values across soundings and levels, climatological outliers, and temporal and vertical inconsistencies in temperature. The performance of the various checks was evaluated by careful inspection of selected soundings and time series. In its final form, IGRA is the largest and most comprehensive dataset of quality-assured radiosonde observations freely available. Its temporal and spatial coverage is most complete over the United States, western Europe, Russia, and Australia. The vertical resolution and extent of soundings improve significantly over time, with nearly three-quarters of all soundings reaching up to at least 100 hPa by 2003. IGRA data are updated on a daily basis and are available online from NCDC as both individual soundings and monthly means.
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.
Integrity signals
Registry
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.
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
The Twentieth Century Reanalysis Project
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P., et al. (2011) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.776 · Cited by 3,518
Self-citationDominant control of the South Asian monsoon by orographic insulation versus plateau heating
Boos, W. R., & Kuang, Z. (2010) · Nature · doi:10.1038/nature08707 · Cited by 961
A Deep Hybrid Model for Weather Forecasting
Grover, A., Kapoor, A., & Horvitz, E. (2015) · Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/2783258.2783275 · Cited by 276
Allen, R. J., Sherwood, S. C., Norris, J. R., & Zender, C. S. (2012) · Nature · doi:10.1038/nature11097 · Cited by 256
Strategies for Evaluating Quality Assurance Procedures
Durre, I., Menne, M. J., & Vose, R. S. (2008) · Journal of Applied Meteorology and Climatology · doi:10.1175/2007jamc1706.1 · Cited by 111
Self-citationSurface-based temperature inversions in Alaska from a climate perspective
Bourne, S. M., Bhatt, U. S., Zhang, J., & Thoman, R. (2010) · Atmospheric Research · doi:10.1016/j.atmosres.2009.09.013 · Cited by 83
Increasing potential for intense tropical and subtropical thunderstorms under global warming
Singh, M. S., Kuang, Z., Maloney, E. D., Hannah, W. M., & Wolding, B. O. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707603114 · Cited by 79
Thorne, P. W., Willett, K. M., Allan, R. J., Bojinski, S., Christy, J. R., Fox, N., Gilbert, S., Jolliffe, I., Kennedy, J. J., Kent, E., et al. (2011) · Bulletin of the American Meteorological Society · doi:10.1175/2011bams3124.1 · Cited by 76
Assessing bias and uncertainty in the HadAT-adjusted radiosonde climate record.
McCarthy, M. P., Titchner, H. A., Thorne, P. W., Tett, S. F. B., Haimberger, L., & Parker, D. E. (2008) · Journal of Climate · doi:10.1175/2007jcli1733.1 · Cited by 56
Metadata
- Authors
- Durre, I., Vose, R. S., & Wuertz, D. B.
- Venue
- Journal of Climate
- Publisher
- American Meteorological Society
- Published
- 2006-01-01
- Volume
- 19
- Issue
- 1
- Pages
- 53-68
- ISSN
- 0894-8755 (ISSN-L)
- 1520-0442
- OpenAlex
- W2146598934
- Cited by
- 783
- References
- 0
- FWCI
- 18.30
- Type
- journal article
- Language
- en
- Open access
- closed
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
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.