Contribution de Julien Gazeaux, Deborah Batista & Caspar M. Ammann:

Assimilation techniques for extracting Common Pulse-Like Signals from Multiple Ice Core Time Series.

To understand the nature and cause of natural climate variability, it is important to attribute past climate variations to particular forcing factors. In this work, our main focus is to introduce an automatic assimilation procedure to estimate the magnitude of strong but short-lived perturbations such as large explosive volcanic eruptions in a series of climate/ proxies time series. Our extraction algorithm handles multivariate time series with a common but unknown forcing. This statistical procedure is based on a multivariate multistate space model and a non linear Kalman Filter. It can provide an accurate estimator of the timing and duration of individual pulse-like events from a set of different time series. It not only allows for a more objective estimation of its associated peak amplitude and the subsequent time evolution of the signal, but at the same time it provides a measure of confidence through the posterior probability for each pulse-like event. The flexibility, robustness and limitations of our approach are discussed by applying our method to simulated and real multivariate time series.

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