2.3.4. Methods for Spatial and Temporal Trend Analysis

In this study, Morlet wavelet analysis was used to study the significant cycle changes in *ET*<sup>0</sup> time series at different time scales, which has significant advantages in revealing the multiscale configuration and main climate change cycle [51]. Empirical orthogonal function (EOF) analysis produces a set of orthogonal spatial and temporal patterns in the order of explained variance, reducing the dimensionality of the analyzed system and finding relatively few independent variables that can provide comprehensive information about the variability of the raw data [52]. EOF analysis, supplemented by the North test [53], was used to study the spatial and temporal patterns of the *ET*<sup>0</sup> climate field in the YRB. In addition, spatial changes in the near-, mid-, and long-term future relative to the historical period were estimated by comparing historical long-term (1901–2014) annual *ET*<sup>0</sup> averages for different emission scenarios of *ET*0.
