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Variational quality control
Abstract
We describe the implementation of variational quality control in the operational four‐dimensional variational data assimilation scheme at the European Centre for Medium‐Range Weather Forecasts (ECMWF). the quality control takes place during the iterative solution of the variational analysis problem itself, rather than in a separate step prior to the main analysis. This ensures that the quality control is consistent with the analysis in terms of error statistics, background and model constraints, in particular. All observational data are used and quality‐controlled simultaneously. the probability of gross error is computed for each observation, given the preliminary analysis at each iteration. the weight of each observation is smoothly decreased with increased likelihood for gross error. the formulation, the implementation details and results from data assimilation and forecast experiments are presented.
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Cited by
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., et al. (2020) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.3803 · Cited by 31,882
The ERA‐Interim reanalysis: configuration and performance of the data assimilation system
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., et al. (2011) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.828 · Cited by 24,480
Atmospheric Modeling, Data Assimilation and Predictability
Kalnay, E. (2002) · doi:10.1017/cbo9780511802270 · Cited by 3,391
CERA‐20C: A Coupled Reanalysis of the Twentieth Century
Laloyaux, P., de Boisseson, E., Balmaseda, M., Bidlot, J., Broennimann, S., Buizza, R., Dalhgren, P., Dee, D., Haimberger, L., Hersbach, H., et al. (2018) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2018ms001273 · Cited by 319
Review and assessment of latent and sensible heat flux accuracy over the global oceans.
Bentamy, A., Piollé, J. F., Grouazel, A., Danielson, R., Gulev, S., Paul, F., Azelmat, H., Mathieu, P. P., von Schuckmann, K., Sathyendranath, S., et al. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.08.016 · Cited by 116
Metadata
- Authors
- Anderson, E., & Järvinen, H.
- Venue
- Quarterly Journal of the Royal Meteorological Society
- Publisher
- Wiley
- Published
- 1999-01
- Volume
- 125
- Issue
- 554
- Pages
- 697-722
- ISSN
- 0035-9009 (ISSN-L)
- 1477-870X
- OpenAlex
- W2135622818
- Cited by
- 198
- References
- 0
- FWCI
- 6.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Anderson, E., & Järvinen, H. (1999). Variational quality control. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.49712555416
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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.
