The DOI matches its Crossref record.
The Meteorological Office analysis correction data assimilation scheme
Abstract
A major revision is described to the analysis component of the Meteorological Office data assimilation scheme for both the global and the regional numerical weather prediction models. Initialization by repeated insertion of data and divergence damping is retained but a more flexible modified successive‐correction scheme replaces optimum interpolation for the analysis step. The scheme is derived as an approximate iterative solution to a general equation for the optimal analysis. Within iterations, the analyses of each model variable are performed sequentially and multivariate increment fields are derived for dynamical balance at intermediate stages. The horizontal influence area of data is substantially increased, giving a beneficial impact in data‐sparse regions. All data contribute to the analysis at each gridpoint within their radius of influence. The observation weights are recalculated every model time‐step, allowing asynoptic data to be used at their true valid time, though this feature is found to have only slight impact on forecasts. Each analysis is factorized into a vertical step, then into a horizontal step. The structure of each is described in detail, with system parameters listed in appendices. Results of two kinds are presented. Sensitivity experiments highlight the effects of some individual constituents of the scheme; operational trials against the old scheme reveal the impact of the whole system. The new analyses are better balanced and lead to a better short‐period forecast, especially for the wind field. Medium‐range impact is clearly beneficial in the southern hemisphere but ambiguous in the northern hemisphere. Precipitation forecasts in the regional model are improved.
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
Atmospheric Modeling, Data Assimilation and Predictability
Kalnay, E. (2002) · doi:10.1017/cbo9780511802270 · Cited by 3,391
The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system
Donlon, C. J., Martin, M., Stark, J., Roberts-Jones, J., Fiedler, E., & Wimmer, W. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2010.10.017 · Cited by 1,394
Good, S., Fiedler, E., Mao, C., Martin, M. J., Maycock, A., Reid, R., Roberts-Jones, J., Searle, T., Waters, J., While, J., et al. (2020) · Remote Sensing · doi:10.3390/rs12040720 · Cited by 585
The Met. Office global three‐dimensional variational data assimilation scheme
Lorenc, A. C., Ballard, S. P., Bell, R. S., Ingleby, N. B., Andrews, P. L. F., Barker, D. M., Bray, J. R., Clayton, A. M., Dalby, T., Li, D., et al. (2000) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.49712657002 · Cited by 478
Self-citationNimrod: a system for generating automated very short range forecasts
Golding, B. W. (1998) · Meteorological Applications · doi:10.1017/s1350482798000577 · Cited by 369
Metadata
- Authors
- Lorenc, A. C., Bell, R. S., & Macpherson, B.
- Venue
- Quarterly Journal of the Royal Meteorological Society
- Publisher
- Wiley
- Published
- 1991-01
- Volume
- 117
- Issue
- 497
- Pages
- 59-89
- ISSN
- 0035-9009 (ISSN-L)
- 1477-870X
- OpenAlex
- W2112958117
- Cited by
- 224
- References
- 0
- FWCI
- 6.17
- 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 Meteorological Office analysis correction data assimilation scheme. https://app.cochat.ai/papers/10.1002/qj.49711749704
- The paper
- Lorenc, A. C., Bell, R. S., & Macpherson, B. (1991). The Meteorological Office analysis correction data assimilation scheme. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.49711749704
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.