Applying Big Data Techniques, New Study Finds Most Recent Warming Could Be Natural
Myron Ebell • August 26, 2017
John Abbot and Jennifer Marohasy have published a study in GeoResJ titled, “The application of machine learning for evaluating anthropogenic versus natural climate change.” The study, which is available here and in pdf form here, is highly technical. Fortunately, Marohasy has summarized its findings on her blog:
After deconstructing 2,000-year old proxy-temperature series back to their most basic components, and then rebuilding them using the latest big data techniques, John Abbot and I show what global temperatures might have done in the absence of an industrial revolution. The results from this novel technique, just published in GeoResJ, accord with climate sensitivity estimates from experimental spectroscopy but are at odds with output from General Circulation Models.
https://cei.org/blog/applying-big-data-techniques-new-study-finds-most-recent-warming-could-be-natural