Asymmetric filters for analyzing time series of atmospheric constituent data

Abstract

We consider the design of asymmetric digital filters for extracting estimates of long-term trends and seasonal cycles from monthly mean values of atmospheric constituent data. It is possible to reduce the amount of data lost from the end of the records at the expense of a relatively small increase in the mean-square error in the estimated signals.