Understanding the trends and periodicities in geo- physical processes is imperative for assessing and forecasting their future change. However, it is possible to mistreat parts of cycles as linear trends with sudden breaks when analysing short-term data. We demonstrate this through the analysis of solar irradiance data as well as Northern Hemisphere (NH) and Southern Hemisphere (SH) sea surface temperature (SST) data sets, with emphasis on the (a) analyses of trends in total solar irradiance (TSI) and (b) asso- ciation of trends in SST with solar activity during the period from 1900 to 2017. The trends estimated using singular spectrum anal- ysis together with linear regression revealed statistically significant long periodic non-linear trends in both TSI and SST data. Our results suggest that the appraisal of linear trends to identify their breaks/sudden changes is a biased approach when analysing data sets of shorter periods, when the data are governed by long periodic dynamical processes. Our study concludes that (1) breaks in linear trends are pseudo-attribution of parts of cycles, and (2) the statistically significant trends in NH and SH SST are mainly associated with loadings from trend changes in solar irradiance.
Figure: Trends of northern and southern hemispheric sea surface temperature during the period from 1900 to 2014 (top panel) along with TSI (bottom panel)
Rekappali R. and Tiwari R.K., Pure Appl. Geophys. 177 (2020), 5469–5474 Ó 2020 Springer Nature Switzerland AG https://doi.org/10.1007/s00024-020-02577-y