Interpolation and Filtering of Spatial Observations Using Successive Corrections and Gaussian Filters

Abstract

Abstract This paper describes a simple empirical analysis system based on Bratseth's method of successive corrections applied to detrended field data, which approximates an optimal interpolation of fields with a spatially variable mean sampled within a limited domain by scattered observations. As in other empirical interpolation schemes, the influence function that determines the weights applied to increment variables is chosen such that unresolvable scales tend to be strongly damped, even if the contribution from observation error is not represented in a formally equivalent correlation model for observed increment variables. Unlike most empirical successive correction schemes, the number of iterations is not necessarily considered as a prescribed analysis parameter. Instead, the number of iterations can be chosen on a judgemental, posterior basis such that the analysis approximates the observed field to within some acceptable limit. The analysis generated by this form of successive corrections can be rep...