Application of shadowing Filter in Weather Predictability

Abstract

The physical meaning of the Ikeda model is analyzed. The influence of the parameters in the model on the \u00a0state \u00a0of \u00a0the \u00a0solution \u00a0is \u00a0discussed. \u00a0The \u00a0change \u00a0process \u00a0of \u00a0the \u00a0solution \u00a0when \u00a0the \u00a0parameters \u00a0are \u00a0taken \u00a0from different values is described, and the sensitivity of the solution to the initial value is studied.The tail filter is used to optimize \u00a0the \u00a0decision \u00a0function \u00a0through \u00a0the \u00a0gradient \u00a0descent \u00a0method, \u00a0filtering \u00a0the \u00a0observation \u00a0error, \u00a0and obtaining the initial field which is closer to the true value.