Methods of Sequential Estimation for Determining Initial Data in Numerical Weather Prediction

摘要: Numerical weather prediction (NWP) is an initial-value problem for a system of nonlinear differential equations, in which initial values are known incompletely and inaccurately. Observational data available at the time must therefore be supplemented by prior to time, as meteorological assimilation. A further complication NWP that solutions governing equations evolve on two different scales, fast one slow one, whereas scale motions atmosphere not reliably observed. This leads so called initialization problem: constrained result slowly evolving forecast. The theory estimation stochastic dynamic systems provides natural approach such problems. For linear models, Kalman-Bucy (KB) sequential filter optimal assimilation method, combined assimilation-initialization method modified version KB filter.