14 Pages Posted: 14 Apr 2016 Last revised: 6 Oct 2016
Date Written: April 12, 2016
A study of daily mean temperature data from five USCRN stations in the sample period 1/1/2005-3/31/2016 shows that the seasonal cycle can be captured with significantly greater precision by dividing the year into smaller parts than calendar months. The enhanced precision greatly reduces vestigial patterns in the deseasonalized and detrended residuals. Rescaled Range analysis of the residuals indicates a violation of the independence assumption of OLS regression. The existence of dependence, memory, and persistence in the data is indicated by high values of the Hurst exponent. The results imply that decadal and even multi-decadal OLS trends in USCRN daily mean temperature may be spurious.
Keywords: global warming, climate change, USCRN, OLS trends, Hurst exponent, time series
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