Evaluation of empirical mode decomposition and maximal overlap discrete wavelet transform approaches in trend analysis of meteorological variables

In this study, the effect of empirical mode decomposition (EMD) and maximal overlap discrete wavelet transform (MODWT) approaches in the processing of average temperature, wind speed and precipitation annual, monthly and single month time scales were evaluated. The selected study stations were Ramsar, Kermanshah, Hamadan, Semnan, Mashhad, Shiraz, Ardabil,Urmia, Zanjan, Yazd, Tabriz, Maragheh and Mianeh. In the time series decomposition using EMD, the trend of combined sub-series and in MODWT, the trend of sub-series was consistent with the Mann-Kendall test values of observed data time series, although, it can also be affected with the value and sign of of Mann-Kendall statistic. The significance level of The Mann-Whitney test in comparison of main annual observed time series with subseries of both approaches was more than 0.05, which indicates the acceptable performance of EMD and MODWT. In general, the comparisons of the sub-series of two approach with the main time series in each station, showed that the corresponding significance level for MODWT approach is higher than EMD. Also, the average of significance level for temperature series greater than those of precipitation and wind speed series. The LSD test at the 95% confidence level indicates good agreement of the observed data time series and combined sub-series.