final_program_abstracts[1]

11 IMSC Session Program
Climate change detected through a Markov chain analysis –
an application to the Iberian Peninsula
Thursday - Poster Session 6
J.A. Freund 1 , S. Mieruch 2 , S. Noël 2 , H. Bovensmann 2 and J.P. Burrows 2
1 Institute for Chemistry and Biology of the Marine Environment, University of
Oldenburg, Germany
2 Institute of Environmental Physics, University of Bremen, Germany
The fingerprint of climate change can be seen in many regions across the globe. In
Europe, the Iberian Peninsula is most susceptible to climate change. Trend studies
indicate that glaciers are melting, droughts and storms are increasing and beaches get
lost. In contrast, significant changes of climate variables are harder to detect on
shorter time scales, e.g. for the last decade being the relevant time range for climate
data acquired by modern satellites. We show how signs of climate change can also be
observed on shorter time scales when analysing the interplay of climate variables. To
this end we describe the interplay using dynamic descriptors such as persistence,
recurrence time and entropy. These descriptors are based on anomaly statistics
derived from a coarse-grained categorical representation of multivariate time series
and a subsequent Markov chain analysis. We apply the method to a multivariate data
set of temperature (GISS), water vapour (GOME/SCIAMACHY) and vegetation
(SPOT), recorded for Europe on a 0.5° by 0.5° grid and spanning the time range from
1999 to 2005. As a result, for the Iberian Peninsula we find a pronounced change in
persistence around the year 2003 and discuss the possibility of a climatic regime shift.
Abstracts 286