On the Interpretation of Running Trends as Summary Statistics for Time Series Analysis
Abstract
In recent years, running trends analysis (RTA) has been widely used in climate applied research as summary statistics for time series analysis. There is no doubt that RTA might be a useful descriptive tool, but despite its general use in applied research, precisely what it reveals about the underlying time series is unclear and, as a result, its interpretation is unclear too. This work contributes to such interpretation in two ways: 1) an explicit formula is obtained for the set of time series with a given series of running trends, making it possible to show that running trends, alone, perform very poorly as summary statistics for time series analysis; and 2) an equivalence is established between RTA and the estimation of a (possibly nonlinear) trend component of the underlying time series using a weighted moving average filter. Such equivalence provides a solid ground for RTA implementation and interpretation/validation.
- Publication:
-
EGU General Assembly Conference Abstracts
- Pub Date:
- April 2016
- Bibcode:
- 2016EGUGA..18.6379V