Another scanning test of trend change in regression coefficients applied to monthly temperature on global land and sea surfaces

Two algorithms has been proposed in this paper. One is another scanning t -test of trend change-points in regression slope-coefficients in two phases, along with a coherency analysis of changes between two time series. It is different from the previously published scanning F max test of trend changes in two-phase regressions. The second is a fuzzy weighted moving average (FWMA). Then the algorithms were applied to two series of monthly temperature over global land and ocean surfaces for 1850–2018. The applied results show that significant changes in segment trends appeared into two gradations on inter-decadal and intra-decadal scales. All subsample regression models were found to fit well with that data. Global warming got started in April 1976 with a good coherency of warming trends between land and sea. The global warming ‘hiatus’ mainly occurred in the sea cooling from November 2001 to April 2008, but not evinced over land. The ‘land/sea warming contrast’ was detected only in their anomaly series. It disappeared in their standardized differences. We refer to the anomalies in distribution N(0,s) as ‘perceptual’ indicators, while refer to the standardized differences in distribution N(0,1) as ‘net’ indexes.