Faster Determination of the Intraseasonal Variability of Storm Tracks Using Murakami's Recursive Filter

Abstract

Murakami's recursive filter technique is suitable for computing storm tracks with reduced needs in data length, and it decreases computing time by the factor 3.5. It is shown that the storm tracks differ only slightly from the ones obtained using the conventional Blackmon filtering approach. A problem identified with respect to the exact frequency of the 1.0 response of Murakami's filter appears to be of minor importance.