Analysed data for numerical prediction can be effectively initialized by means of a digital filter. Computation time is reduced by using an optimal filter. The construction of optimal filters involves the solution of a nonlinear minimization problem using an iterative procedure. In this paper we describe a simple filter based on the Dolph-Chebyshev window, which has properties similar to those of an optimal filter: it is shown to be optimal for an appropriate choice of parameters. It has an explicit analytical expression and is easily implemented. Its effectiveness is demonstrated by application to Richardson's forecast: the initial pressure tendency is reduced from 145 hPa/6 h to -0.9 hPa/6 h. Use of the filter is not restricted to initialization; it may also be applied as a weak constraint in four-dimensional data assimilation.