Applications of an Adaptive Moving Average Filter to Climate and Air Quality Data

摘要

The Kolmogorov-Zurbenko (KZ) filter used in this study is a low pass, non-parametric filter. The main advantage of the KZ filter is that it can be used to separate different phenomena (short-term, seasonal, and long-term fluctuations) in the time series data. The Kolmogorov-Zurbenko Adaptive (KZA) filter is a modification of the KZ filter and is used to sharpen the location of breaks. This study presents a few applications of the Kolmogorov-Zurbenko (KZ) filters to both climate and ozone air quality data. In this report, previous work is briefly reviewed. A description of the data acquisition and processing is offered, as well as the methodology of the analysis. This includes a description of the filters, estimation of the trends, the development of a regional filter, and the filters application to the ozone data. Finally, results from data analyses are then discussed.