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Part of the book series: Applied Mathematical Sciences ((AMS,volume 36))

Abstract

For a given situation, our knowledge about the state of the atmosphere is given by a large number of actual and recent observations, irregularly distributed in space and time. The procedure of combining these observed data to make conclusions about the total variation of the meteorological variables within the area of interest, has generally been called meteorological analysis. The term “objective analysis” has been used for analysis as a numerical procedure by the aid of a computer to distinguish from the manual or “subjective” analysis procedure. In my opinion, the term “objective analysis” is too pretentious, a more relevant terminology is “numerical analysis” versus “manual analysis”.

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List of References

  • Alaka, M.A. and Elvander, R.C.: Optimum interpolation from observations of mixed quality. Monthly Weather Review, Vol. 100, No. 8, pp. 612–624.

    Google Scholar 

  • Atkins, M., 1974: The objective analysis of relative humidity. Tellus, Vol. 26, NO. 6, pp. 663–671.

    Article  Google Scholar 

  • Bengtsson, L. and Gustafsson, N., 1972: Assimilation of non-synoptic observations. Tellus, Vol. 24, pp. 383–399.

    Article  Google Scholar 

  • Bengtsson, L., 1975: 4-dimensional assimilation of meteorological observations, GARP Publication Series No. 15.

    Google Scholar 

  • Bengtsson, L., 1980: On the use of a time sequence of surface pressures in four-dimensional data assimilation. Tellus, Vol. 32, pp. 189–197.

    Article  Google Scholar 

  • Bergman, K.H., 1979: Multivariate analysis of temperatures and winds using optimum interpolation. Monthly Weather Review, Vol. 107, pp. 1423–1444.

    Article  Google Scholar 

  • Bergthorsson, P. and Döös, B.R., 1955: Numerical weather map analysis. Tellus, Vol. 7, pp. 329–340.

    Article  Google Scholar 

  • Bertoni, E. and Lund, T.A., 1963: Space correlations of the height of constant pressure surfaces. J. Appl. Meteor., Vol. 2, MO 4.

    Google Scholar 

  • Buell, E., 1972: Correlation functions of the height of constant pressure surfaces. J. Appl. Meteor., Vol. 11, pp. 51–59.

    Article  Google Scholar 

  • Cats, G.J., 1980: Construction of correlation matrices for the ECMWF analysis scheme. ECMWF working paper.

    Google Scholar 

  • Cressman, G.P., 1959: An operational objective analysis system. Monthly Weather Review, Vol. 87, pp. 367–374.

    Article  Google Scholar 

  • Dixon, R., 1976: An objective analysis system using orthogonal polynomials. GARP WGNE Report No. 11, pp. 73–85.

    Google Scholar 

  • Eliassen, A., 1954: Provisional report on calculation of spatial covariance and autocorrelation of the pressure field. Inst. Weather and Climate Res., Acad. Sci. Oslo, Rept. No. 5.

    Google Scholar 

  • Flattery, T., 1971: Spectrql models for global analysis and forecasting. Proc. Sixth AWS Technical Exchange Conference. Air Weather Service Techn. Rep. 242, pp. 42–54.

    Google Scholar 

  • Gandin, L.S., 1963: Objective analysis of meteorological fields. Leningrad. Hydromet. Press.

    Google Scholar 

  • Gandin, L.S. and Tarasyuk, V.V., 1971: A complex method of checking the upper-air information. Meteorologija i Gidrologija, 1971, No. 5, pp. 3–9.

    Google Scholar 

  • Ghil, M. and Balgovind, R., 1980: A Langevin equation for large-scale atmospheric flow. GARP WGNE Report No. 20, pp. 31–33.

    Google Scholar 

  • Gilchrist, B. and Cressman, G.P., 1954: An experiment in objective analysis. Tellus, Vol. 6, pp. 97–101.

    Article  Google Scholar 

  • Hayden, C.M., 1976: Satellite reference level experiments with VTRR and the NMC global spectral analyses. GARP WGNE Report No. 11, pp. 57–72.

    Google Scholar 

  • Hollett, S.R., 1975: Three-dimensional spatial correlations of PE forecast errors. M.S. thesis, Dept of Meteorology, McGill University.

    Google Scholar 

  • Kaestner, 1974: Ein Verfahren zur numerischen Analyse der relativen Feuchte. Arch. Met. Geph. Biokl., Ser. A, Vol. 23,

    Google Scholar 

  • Van Maanen, J., 1980: Objective analysis of the humidity field by the optimum interpolation method. GARP WGNE Report No. 20, pp. 38–40.

    Google Scholar 

  • Panofsky, H.A., 1949: Objective weather map analysis. J. Met., Vol. 6, No.6, pp. 386–392.

    Article  Google Scholar 

  • Richardson, L.F., 1922: Weather prediction by numerical process. Dover Publ. Ins., New York 1965.

    Google Scholar 

  • Rutherford, I.D., 1976: An operational three-dimensional multivariate statistical objective analysis scheme. GARP WGNE Report No. 11, pp. 98–121.

    Google Scholar 

  • Sasaki, Y., 1958: An objective analysis based on the variational method. J. of Met. Soc. Japan, Vol. 36, pp. 77–88.

    Google Scholar 

  • Thiebaux, H.J., 1975: Experiments with correlation representations for objective analysis. Mon. Wea. Rev., Vol. 103, pp. 617–627.

    Article  Google Scholar 

  • Thiebaux, H.J., 1976: Anisotropic correlation functions for objective analysis. Mon. Wea. Rev., Vol. 104, pp. 994–1002.

    Article  Google Scholar 

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© 1981 Springer-Verlag New York, Inc.

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Gustafsson, N. (1981). A Review of Methods for Objective Analysis. In: Bengtsson, L., Ghil, M., Källén, E. (eds) Dynamic Meteorology: Data Assimilation Methods. Applied Mathematical Sciences, vol 36. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-5970-1_2

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  • DOI: https://doi.org/10.1007/978-1-4612-5970-1_2

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-90632-4

  • Online ISBN: 978-1-4612-5970-1

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