“Predicting annual temperatures a year ahead” (Dr Gavin Schmidt at REALCLIMATE)

Dr Schmidt is essentially betting that the trend, seen as a random variable, will regress towards the smooth mean.

I have a post at Nate Silver’s 538 site on how we can predict annual surface temperature anomalies based on El Niño and persistence – including a (by now unsurprising) prediction for a new record in 2016 and a slightly cooler, but still very warm, 2017. The key results are summarized in the figures that show how residual variations in the global temperatures (after detrending) related to the ENSO phase at the beginning …

Source: Predicting annual temperatures a year ahead

About hypergeometric

See http://www.linkedin.com/in/deepdevelopment/ and http://667-per-cm.net
This entry was posted in American Meteorological Association, American Statistical Association, AMETSOC, anomaly detection, Anthropocene, changepoint detection, climate change, climate data, climate disruption, climate education, climate models, ecology, environment, forecasting, geophysics, global warming, Hyper Anthropocene, meteorology, oceanography, physics, regression toward the mean, science, statistics, time series. Bookmark the permalink.

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