Editorial Type:
Article
Article Type:
Research Article

The Use of Bred Vectors in the NCEP Global 3D Variational Analysis System

Zhao-Xia Pu Environmental Modeling Center, National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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Eugenia Kalnay Environmental Modeling Center, National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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David Parrish Environmental Modeling Center, National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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Wanshu Wu Environmental Modeling Center, National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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Zoltan Toth Environmental Modeling Center, National Centers for Environmental Prediction, NWS/NOAA, Washington, D.C.

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Print Publication:
01 Sep 1997
DOI:
https://doi.org/10.1175/1520-0434(1997)012<0689:TUOBVI>2.0.CO;2
Page(s):
689–695
Restricted access

Abstract

The errors in the first-guess (forecast field) of an analysis system vary from day to day, but, as in all current operational data assimilation systems, forecast error covariances are assumed to be constant in time in the NCEP operational three-dimensional variational analysis system (known as a spectral statistical interpolation or SSI). This study focuses on the impact of modifying the error statistics by including effects of the “errors of the day” on the analysis system. An estimate of forecast uncertainty, as defined from the bred growing vectors of the NCEP operational global ensemble forecast, is applied in the NCEP operational SSI analysis system. The growing vectors are used to estimate the spatially and temporally varying degree of uncertainty in the first-guess forecasts used in the analysis. The measure of uncertainty is defined by a ratio of the local amplitude of the growing vectors, relative to a background amplitude measure over a large area. This ratio is used in the SSI system for adjusting the observational error term (giving more weight to observations in regions of larger forecast errors). Preliminary experiments with the low-resolution global system show positive impact of this virtually cost-free method on the quality of the analysis and medium-range weather forecasts, encouraging further tests for operational use. The results of a 45-day parallel run, and a discussion of other methods to take advantage of the knowledge of the day-to-day variation in forecast uncertainties provided by the NCEP ensemble forecast system, are also presented in the paper.

* Current affiliation: UCAR Visiting Scientist, NCEP, Washington, D.C.

Current affiliation: General Sciences Corporation, Laurel, Maryland.

Corresponding author address: Zhao-Xia Pu, EMC/NCEP2, WWB, Room 207, 5200 Auth Road, Camp Springs, MD 20746.

Email: wdzøzp@sun1.wwb.noaa.gov

Abstract

The errors in the first-guess (forecast field) of an analysis system vary from day to day, but, as in all current operational data assimilation systems, forecast error covariances are assumed to be constant in time in the NCEP operational three-dimensional variational analysis system (known as a spectral statistical interpolation or SSI). This study focuses on the impact of modifying the error statistics by including effects of the “errors of the day” on the analysis system. An estimate of forecast uncertainty, as defined from the bred growing vectors of the NCEP operational global ensemble forecast, is applied in the NCEP operational SSI analysis system. The growing vectors are used to estimate the spatially and temporally varying degree of uncertainty in the first-guess forecasts used in the analysis. The measure of uncertainty is defined by a ratio of the local amplitude of the growing vectors, relative to a background amplitude measure over a large area. This ratio is used in the SSI system for adjusting the observational error term (giving more weight to observations in regions of larger forecast errors). Preliminary experiments with the low-resolution global system show positive impact of this virtually cost-free method on the quality of the analysis and medium-range weather forecasts, encouraging further tests for operational use. The results of a 45-day parallel run, and a discussion of other methods to take advantage of the knowledge of the day-to-day variation in forecast uncertainties provided by the NCEP ensemble forecast system, are also presented in the paper.

* Current affiliation: UCAR Visiting Scientist, NCEP, Washington, D.C.

Current affiliation: General Sciences Corporation, Laurel, Maryland.

Corresponding author address: Zhao-Xia Pu, EMC/NCEP2, WWB, Room 207, 5200 Auth Road, Camp Springs, MD 20746.

Email: wdzøzp@sun1.wwb.noaa.gov

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  • Derber, J., and W.-S. Wu, 1996: The use of cloud-cleared radiances in the NCEP’s SSI analysis system. Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 236–237.

  • ——, D. Parrish, and S. J. Lord, 1991: The new global operational analysis system at the National Meteorological Center. Wea. Forecasting,6, 538–547.

    • Crossref
    • Export Citation

  • ——, ——, W.-S. Wu, Z.-X. Pu, and S. Rizvi, 1994: Improvements to the operational SSI global analysis system. Preprints, 10th Conf. on Numerical Weather Prediction, Portland, OR, Amer. Meteor. Soc., 149–150.

  • Iyengar, G., Z. Toth, E. Kalnay, and J. Woollen, 1996: Are the bred vectors representative of analysis error? Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., J64–J66.

  • Kalnay, E., and Z. Toth, 1994: Removing growing errors in the analysis. Preprints, 10th Conf. Numerical Weather Prediction, Portland OR, Amer. Meteor. Soc., 212–215.

  • Lorenc, A. C., 1986: Analysis methods for numerical weather prediction. Quart. J. Roy. Meteor. Soc.,112, 1177–1194.

    • Crossref
    • Export Citation

  • Pan, H.-L., J. Derber, D. Parrish, W. Gemmill, S.-Y. Hong, and P. Caplan, 1995: Changes to the 1995 NCEP operational MRF model analysis/forecast system. National Weather Service Tech. Procedures Bull. 428, 30 pp. [Available from NCEP/NWS/NOAA, 5200 Auth Rd., Camp Springs, MD 20746.].

  • Parrish, D. F., and J. Derber, 1992: The National Meteorological Center’s spectral statistical interpolation analysis system. Mon. Wea. Rev.,120, 1747–1763.

    • Crossref
    • Export Citation

  • ——, ——, J. Purser, W. Wu, and Z. Pu, 1997: The NCEP Global Analysis system: Recent improvements and future plans. J. Meteor. Soc. Japan,75, 359–365.

    • Crossref
    • Export Citation

  • Pu, Z.-X., E. Kalnay, J. Derber, and J. Sela, 1997: Using forecast sensitivity patterns to improve the future forecast skill. Quart. J. Roy. Meteor. Soc.,123, 1035–1054.

    • Crossref
    • Export Citation

  • Purser, R. J., D. F. Parrish, Z. Toth, and E. Kalnay, 1994: Numerical filtering applied to the enhancement of pre-analysis corrections of background errors expressible as rapidly amplifying modes. Preprints, 10th Conf. on Numerical Weather Prediction, Portland, OR, Amer. Meteor. Soc., 243–244.

  • Toth, Z., and E. Kalnay, 1993: Ensemble forecasting at NMC: The generation of initial perturbation. Bull. Amer. Meteor. Soc.,74, 2317–2330.

    • Crossref
    • Export Citation

  • ——, and ——, 1995: Ensemble forecasting at NCEP and the breeding method. NCEP Office Note 407, 55 pp. [Available from NCEP, 5200 Auth Rd., Camp Springs, MD 20746.].

  • Wahba, G., D. R. Johnson, F. Gao, and J. Gong, 1995: Adaptive tuning of numerical weather prediction model: Randomized GCV in three- and four-dimensional data assimilation. Mon. Wea. Rev.,123, 3358–3369.

    • Crossref
    • Export Citation

  • Zhu, Y., G. Iyengar, Z. Toth, S. Tracton, and T. Marchok, 1996: Objective evaluation of the NCEP global ensemble forecasting system. Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., J79–J82.

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