Nonlinear and linear evolution of initial forecast errors

Abstract

The hypothesis that the short-time evolution of forecast errors originating from initial data uncertainties can be approximated by linear model solutions is investigated using a realistic prognostic model. A tangent linear limited-area model based on a state of the art mesoscale numerical forecast model is developed. The results demonstrate that the initial error evolution is well represented by the tangent model for periods of 1-1.5 days duration. The linear model solutions based on the time-dependent basic state are also good approximations of the real-error evolutions, providing the prognostic fields are not changing rapidly in time. -from Author