Normalized innovative trend analysis model and Mann-Kendall test for solar data

It is common knowledge that trends occur in meteorological and hydrological measurements and their detections are possible by convenient trend analysis approaches. In this paper, Şen’s innovative trend analysis (ITA) methodology is considered, because it provides even visual identification of trends without assumptions. Based on ITA methodology, the normalized innovative trend analysis (N-ITA) model is proposed in this research that offers comparison opportunity between several different data series on the same graph. For such a purpose, one of the basic principles of the N-ITA method is necessary to apply normalization procedure to all data, which confines the data values between 0 and 1, inclusive. Therefore, applications using interrelated monthly measurements of solar radiation, sunshine duration, and temperature reveal four important interpretation possibilities on a single graph. These information sources are concerned with the time series trend comparisons relative to each other. The data from the Turkish State Meteorological Service (TSMS) at Adana, Bozova (Şanlıurfa), and Mardin stations are subjected to N-ITA procedure application. The potential contribution of the proposed N-ITA method is illustrated through comparisons with the ITA approach and Mann-Kendall test for each station.