VALIDATION OF A SKILL PREDICTION METHOD

A large experiment is performed to validate two predictors for the qua lity of ECMWF forecasts over Western Europe. One predictor yields the spread of the probability distribution for the error in the predicted 500 hPa geopotential height. It is determined by the trace of the cova riance matrix for the geographically local forecast error. In addition the spread for the 500 hPa vorticity error at a location near the Net herlands is computed. The local covariance matrix, necessary for deter mining both predictors, is computed for 607 days, using the tangent li near and an adjoint version of a quasi-geostrophic 3-level model with truncation T21. We assume linear error growth and the absence of model errors. The forward reference orbit is obtained by interpolating actu al ECMWF forecasts with the 3-level model. Small values of the predict or imply small error growth, and therefore accurate forecasts. Large v alues may or may not be associated with large actual forecast errors, depending on whether the initial error strongly projects on the fastes t growing modes. How the uncertainty in the structure of the initial e rror influences the performance of the skill predictor is studied by c onsidering three different covariance matrices for the initial error. Validation of the predicted variance with the 2-day and 3-day ECMWF fo recast error shows that for all initial covariance matrices, both pred ictors provide significant information about the quality of the foreca st. In case of small and large predicted variance, the probabilities f or small and large prediction errors are 10% higher than the climatolo gical probabilities. Projection of the observed forecast error onto th e eigenvectors of the local covariance matrix indicates that a few eig envectors already describe a large portion of the forecast error.