attribution of climate change

Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate

We analyze a time series of global temperature anomaly distributions to identify and estimate persistent features in climate change. Temperature densities from globally distributed data between 1850 and 2012 are treated as a time series of functional observations that change over time. We employ a formal test for the existence of functional unit roots in the time series of these densities. Further, we develop a new test to distinguish functional unit roots from functional deterministic trends or explosive behavior.

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