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  "Title": "Time of Emergence of Climate Signals from Internal Variability",
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  "Authors@R": "person(\"Abul Kashem Faruki\", \"Fahim\", , \"farukifahim@du.ac.bd\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-8554-4730\"))",
  "Description": "Detects when a forced climate change signal emerges from\ninternal variability ('time of emergence') in annual climate\ntime series such as temperature or precipitation. The signal is\nestimated with a linear, quadratic or locally weighted smoother\nand compared with noise estimated from a baseline period.\nEmergence is defined through configurable signal-to-noise\nthresholds and persistence rules. Uncertainty in the time of\nemergence is quantified by autoregressive or moving-block\nbootstrap resampling. Helpers are provided for multi-member\nensembles, threshold sensitivity, anomaly and annual\naggregation, Mann-Kendall trend tests with trend-free\nprewhitening, and synthetic data generation. The approach\nbuilds on Hawkins and Sutton (2012) <doi:10.1029/2011GL050087>,\nYue et al. (2002) <doi:10.1002/hyp.1095> and Sen (1968)\n<doi:10.1080/01621459.1968.10480934>.",
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      "title": "Sensitivity of the time of emergence to threshold choices",
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        "What is time of emergence?",
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        "Ensembles",
        "Preparing real data",
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