Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 228

The DOI matches its Crossref record.

The ECMWF implementation of three‐dimensional variational assimilation (3D‐Var). II: Structure functions

Rabier, F., McNally, A., Andersson, E., Courtier, P., Undén, P., Eyre, J., Hollingsworth, A., Bouttier, F.·1998·Quarterly Journal of the Royal Meteorological Society

Abstract

Structure functions for the 3D‐Var assimilation scheme of the European Centre for Medium‐Range Weather Forecasts are evaluated from statistics of the differences between two forecasts valid at the same time. Results compare satisfactorily with those reported in the existing literature. Non‐separability of the correlation functions is a pervasive feature. Accounting for non‐separability in 3D‐Var is necessary to reproduce geostrophic characteristics of the statistics, such as the increase of length‐scale with height for the horizontal correlation of the mass variable, sharper vertical correlations for wind than for mass and shorter horizontal length‐scales for temperature than for mass. In our non‐separable 3D‐Var, the vertical correlations vary with total wave‐number and the horizontal correlation functions vary with vertical level.

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 · 10.1002/qj.49712455003

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 228

Metadata

Authors
Rabier, F., McNally, A., Andersson, E., Courtier, P., Undén, P., Eyre, J., Hollingsworth, A., & Bouttier, F.
Venue
Quarterly Journal of the Royal Meteorological Society
Publisher
Wiley
Published
1998-07
Volume
124
Issue
550
Pages
1809-1829
ISSN
  • 0035-9009 (ISSN-L)
  • 1477-870X
OpenAlex
W2134928158
Cited by
228
References
0
FWCI
11.88
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

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 ECMWF implementation of three‐dimensional variational assimilation (3D‐Var). II: Structure functions. https://app.cochat.ai/papers/10.1002/qj.49712455003
The paper
Rabier, F., McNally, A., Andersson, E., Courtier, P., Undén, P., Eyre, J., Hollingsworth, A., & Bouttier, F. (1998). The ECMWF implementation of three‐dimensional variational assimilation (3D‐Var). II: Structure functions. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.49712455003

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.