final_program_abstracts[1]

11 IMSC Session Program
A change point approach for applications to atmospheric
carbon dioxide time series
Tuesday - Parallel Session 8
Claudie Beaulieu and Jorge L. Sarmiento
Atmospheric and Oceanic Sciences, Princeton University, Princeton, USA
Long-term changes in climate variables can exhibit step-like changes in the mean, in
the variance and/or in the trend. Change point methods allow detecting and
quantifying these changes. Change point methods have been used in atmospheric and
oceanic sciences to detect artificial or natural discontinuities and regime shifts.
Most change point approaches were designed to detect a specific type of shift (e.g.
either a change in the mean, in the variance or in the parameters of a regression
model, but rarely a combination of several types of changes at the same times).
Furthermore, most change point methods rely on the independence hypothesis while
the presence of autocorrelation is a common feature of climate time series (especially
at the short time scales). A positive autocorrelation can lead to the detection of false
shifts if it is not taken into account in the analysis. Recently, several studies have
started to take into account the autocorrelation in change point detection by assuming
that it can be represented by a lag-1 autoregressive model (AR(1)). The
autocorrelation structure in climate time series can be more complex that that.
In this work, the informational approach is used to discriminate between several types
of changes (shift in the mean, shift in the variance, shift in the trend, shift in the
relation with a covariable or a combination of these different types of changes) though
the application of a hierarchy of models. The informational approach is also used to
identify the auto correlation structure in each models (not restricted only to an AR(1))
and it is taken into account in the change point analysis. The usefulness of this
approach to detect change points in atmospheric CO2 concentration, in the growth rate
of atmospheric CO2 and in the sources and sinks of atmospheric CO2 is demonstrated
through applications.
Abstracts 156