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. Analysing palaeoclimate proxy time series using windowed recurrence network analysis (wRNA) has beenshown to provide valuable information on past climate variability. In turn, it has also been foundthat the robustness of the obtained results differs among proxies from different palaeoclimatearchives. To systematically test the suitability of wRNA for studying different types of palaeoclimateproxy time series, we use the framework of forward proxy modelling. For this, we create artificialinput time series with different properties and compare the areawise significant anomalies detectedusing wRNA of the input and the model output time series.Also, taking into account results for general filtering of different time series, we find that thevariability of the network transitivity is altered for stochastic input time series while being ratherrobust for deterministic input.In terms of significant anomalies of the network transitivity, we observe that these anomalies may bemissed by proxies from tree and lake archives after the non-linear filtering by thecorresponding proxy system models.For proxies from speleothems, we additionally observe falsely identifiedsignificant anomalies that are not present in the input time series. Finally, for proxies from icecores, the wRNA results show the best correspondence to those for the input data.Our results contribute to improve the interpretation of windowedrecurrence network analysis results obtained from real-world palaeoclimate time series.

Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis