This session is positioned at the interface between statistics and climatology. Climate time series analysis takes into account the uncertainties in the climate system, measurements, proxy quality and dating. It provides confidence intervals and error bars of estimates, or it gives p-values of hypothesis tests. The challenge is to develop methods and obtain results that are robust and reliable also in the presence of following difficulties:
We welcome novel contributions that address those difficulties, show a sound statistical basis of the methodology and demonstrate the feasibility of the method in real-world climatological applications. Methods may include, but are not restricted to:
(3) spectral analysis,
(5) nonlinear dynamical system analysis
(6) extreme value analysis.