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Järvinen, Heikki; Andersson, Erik; Bouttier, François (2011)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
Subjects:
Assimilation of observations from frequently reporting surface stations with a four-dimensionalvariational assimilation system (4D-Var) is described. A model for the serial observation errorcorrelation is applied to observed time sequences of surface pressure observations, whereby therelative weight of the mean information over the temporal variations is decreased in the assimilation.Variational quality control is performed jointly for each time sequence of observations soas to either keep or reject all observations belonging to a time sequence. The operationalpractice at ECMWF has previously been to use just one pressure datum from each stationwithin each 6-h assimilation time window. The increase of observational information used inthese assimilation experiments results in a small but systematic increase in the short-rangeforecast accuracy. The r.m.s. of the analysis increments is decreased in the experiments, whichmeans there is an improved consistency between the background and the observations. A studyof a rapidly developing small-scale synoptic system (the Irish Christmas Storm in 1997) showedthat both the background and the analysis became more accurate when more frequent observationswere assimilated. Single-observation experiments showed that a surface pressure timesequenceof data from a single surface station can intensify the analysis of a mid-latitudebaroclinic system, that was underestimated in the background, when used in a 6-h 4D-Var. Themethod to assimilate time sequences presented in this paper has been implemented into theECMWF operational 4D-Var assimilation system.DOI: 10.1034/j.1600-0870.1999.t01-4-00002.x
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Andersson, E., Pailleux, J., The´paut, J-N., Eyre, J., McNally, A. P., Kelly, G. and Courtier, P. 1994. Use of cloud-cleared radiances in three/four-dimensional variational data assimilation. Q. J. R. Meteorol. Soc. 120, 627-653.
    • Andersson, E., Haseler, J., Unde´n, P., Courtier, P., Kelly, G., Vasiljevic, D., Brankovic, C., Cardinali, C., GaVard, C., Hollingsworth, A., Jakob, C., Janssen, P., Klinker, E., Lanzinger, A., Miller, M., Rabier, F., Simmons, A., Strauss, B., The´paut, J-N. and Viterbo, P. 1998. The ECMWF implementation of three dimensional variational assimilation (3D-Var). Part III: Experimental results. Q. J. R. Meteorol. Soc. 124, 1831-1860.
    • Andersson, E. and Ja¨rvinen, H. 1999. Variational quality control. Q. J. R. Meteorol. Soc. 125, 697-722.
    • Bengtsson, L. 1980. On the use of a time sequence of surface pressures in four-dimensional data assimilation. T ellus 32, 189-197.
    • Courtier, P., The´paut, J-N. and Hollingsworth, A. 1994. A strategy for operational implementation of 4D-Var using an incremental approach. Q. J. R. Meteorol. Soc. 120, 1367-1387.
    • Courtier, P., Andersson, E., Heckley, W., Pailleux, J., Vasiljevic, D., Hamrud, M., Hollingsworth, A., Rabier, F. and Fisher, M. 1998. The ECMWF implementation of three dimensional variational assimilation (3D-Var). Part I: Formulation. Q. J. R. Meteorol. Soc. 124, 1783-1808.
    • Daley, R. 1992. The eVect of serially correlated observation and model error on atmospheric data assimilation. Mon. Wea. Rev. 120, 164-177.
    • Derber, J. and Bouttier, F. 1999. A reformulation of the background error covariance in the ECMWF global data assimilation system. T ellus, 51A, 195-221.
    • Hollingsworth, A., Shaw, D., L o¨nnberg, P., Illari, L., Arpe, K. and Simmons, A. 1986. Monitoring of observation and analysis quality by a data-assimilation system. Mon. Wea. Rev. 114, 1225-1242.
    • Ide, K., Courtier P., Ghil, M. and Lorenc, A. 1997. Unified notations for data assimilation: operational, sequential and variational. J. Met. Soc. Japan 75, 181-189.
    • Ingleby, N. B. and Lorenc, A. C. 1993. Bayesian quality control using multivariate normal distributions. Q. J. R. Meteorol. Soc. 119, 1195-1225.
    • Ja¨rvinen, H. and Unde´n, P. 1997. Observation screening and first guess quality control in the ECMW F 3D-Var data assimilation system. ECMWF Tech. Memo. 236. Available from ECMWF.
    • Le Dimet, F.-X. and Talagrand, O. 1986. Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. T ellus 38A, 97-110.
    • Lorenc, A. C. 1981. A global three-dimensional multivariate statistical interpolation scheme. Mon. Wea. Rev. 109, 701-721.
    • Lorenc, A. C. 1986. Analysis methods for numerical weather prediction. Q. J. R. Meteorol. Soc. 112, 1177-1194.
    • Lo¨ nnberg, P. 1988. Developments in the ECMWF analysis system. Proc. ECMWF seminar on Data assimilation and the use of satellite data, Reading, 5-9 November 1988, Vol. 1, 75-120. Published by ECMWF, Shinfield Park, Reading, RG2 9AX, UK.
    • Parrish, D. F. and Derber, J. C. 1992. The National Meteorological Center's spectral statistical interpolation analysis system. Mon. Wea. Rev. 120, 1747-1763.
    • Phalippou, L. 1996. Variational retrieval of humidity profile, wind speed and cloud liquid-water path with the SSM/I: Potential for numerical weather prediction. Q. J. R. Meteorol. Soc. 122, 327-355.
    • Rabier, F., The´paut, J-N. and Courtier, P. 1998a. Extended assimilation and forecast experiments with a four-dimensional variational assimilation system. Q. J. R. Meteorol. Soc. 124, 1861-1887.
    • Rabier, F., McNally, A., Andersson, E., Courtier, P., Unde´n, P., Eyre, J., Hollingsworth, A. and Bouttier, F. 1998b. The ECMWF implementation of three dimensional variational assimilation (3D-Var). Part II: Structure functions. Q. J. R. Meteorol. Soc. 124, 1809-1829.
    • Rabier, F., Ja¨rvinen, H., Klinker, E., Mahfouf, J-F. and Simmons, A. 1999. The ECMWF operational implementation of four dimensional variational assimilation. Part I: Experimental results with simplified physics. Q. J. R. Meteorol. Soc., submitted.
    • The´paut, J.-N., HoVman, R. N. and Courtier, P. 1993. Interactions of dynamics and observations in a fourdimensional variational assimilation. Mon. Wea. Rev. 121, 3393-3414.
    • The´paut, J.-N., Courtier, P., Belaud, G. and Lemaˆıtre, G. 1996. Dynamical structure functions in four-dimensional variational assimilation: A case study. Q. J. R. Meteorol. Soc. 122, 535-561.
    • StoVelen, A. and Anderson, D. 1997. Ambiguity removal and assimilation of scatterometer data. Q. J. R. Meteorol. Soc. 123, 491-518.
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