Obtaining Meteorologically Significant Surface Divergence Fields Through the Filtering Property of Objective Analysis

Abstract

A method is developed for designing specific filtering properties into a weighted-average interpolation scheme. Both spatial and temporal filtering are simultaneously accomplished, resulting in good time continuity as well as smooth spatial patterns. Both low-pass and band-pass filters are shown, with the band-pass results designed to emphasize details of the fields at the resolution limits for conventional surface data. These filters are applied to surface data on a severe thunderstorm day in Oklahoma. Results suggest that divergence fields calculated from the filtered data are well correlated with severe weather events, which develop only after several hours of preexisting moisture convergence.