Seasonality and Dependence in Daily Mean USCRN Temperature

14 Pages Posted: 14 Apr 2016 Last revised: 6 Oct 2016

Jamal Munshi

Sonoma State University

Date Written: April 12, 2016

Abstract

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

Suggested Citation

Munshi, Jamal, Seasonality and Dependence in Daily Mean USCRN Temperature (April 12, 2016). Available at SSRN: https://ssrn.com/abstract=2763358 or http://dx.doi.org/10.2139/ssrn.2763358

Jamal Munshi (Contact Author)

Sonoma State University ( email )

1801 East Cotati Avenue
Rohnert Park, CA 94928
United States

Paper statistics

Downloads
219
Rank
111,108
Abstract Views
1,294