THE USE OF BRED VECTORS IN THE NCEP GLOBAL 3D VARIATIONAL ANALYSIS SYSTEM

The errors in the first-guess (forecast field) of an analysis system v ary from day to day, but, as in all current operational data assimilat ion systems, forecast error covariances are assumed to be constant in time in the NCEP operational three-dimensional variational analysis sy stem (known as a spectral statistical interpolation or SSI). This stud y focuses on the impact of modifying the error statistics by including effects of the ''errors of the day'' on the analysis system. An estim ate of forecast uncertainty, as defined from the bred growing vectors of the NCEP operational global ensemble forecast, is applied in the NC EP operational SSI analysis system. The growing vectors are used to es timate the spatially and temporally varying degree of uncertainty in t he first-guess forecasts used in the analysis. The measure of uncertai nty is defined by a ratio of the local amplitude of the growing vector s, 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 syste m show positive impact of this virtually cost-free method on the quali ty of the analysis and medium-range weather forecasts, encouraging fur ther tests for operational use. The results of a 45-day parallel run, and a discussion of other methods to take advantage of the knowledge o f the day-to-day variation in forecast uncertainties provided by the N CEP ensemble forecast system, are also presented in the paper.