Application of non-linear time-alignment and integration methods to environmental time series

This article presents methods for the analysis of environmental time series in cases where non-linear time alignment is anticipated. First, we present simple, robust propagation methods for cases where data are archived as event lists rather than standard time series. Then, we describe alignment and analysis methods based on procedures that are traditionally associated with laboratory-instrument-data time series, namely correlation optimized warping and classical chromatographic peak integration. We provide examples to illustrate routine operation and current limitations of these methods. We also discuss possible future applications of these methods.