toeclim: Time of Emergence of Climate Signals from Internal Variability
Detects when a forced climate change signal emerges from
internal variability ('time of emergence') in annual climate time series
such as temperature or precipitation. The signal is estimated with a
linear, quadratic or locally weighted smoother and compared with noise
estimated from a baseline period. Emergence is defined through
configurable signal-to-noise thresholds and persistence rules.
Uncertainty in the time of emergence is quantified by autoregressive
or moving-block bootstrap resampling. Helpers are provided for
multi-member ensembles, threshold sensitivity, anomaly and annual
aggregation, Mann-Kendall trend tests with trend-free prewhitening,
and synthetic data generation. The approach builds on Hawkins and
Sutton (2012) <doi:10.1029/2011GL050087>, Yue et al. (2002)
<doi:10.1002/hyp.1095> and Sen (1968)
<doi:10.1080/01621459.1968.10480934>.
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