Partial trend identification by change-point successive average methodology (SAM)

Abstract

There are different trend identification methodologies in the literature, but almost all are for monotonic trend searches within a given hydro-meteorological time series partially at equal epochs or holistically over the whole record duration. The most important question is how to identify within the same time series successive trends of different durations and slopes. For this purpose, successive arithmetic average methodology (SAM) is proposed in this paper, first for a set of trends visual inspection and then their quantitative duration and slope calculations. This method provides to identify peak and valley change-points years, trends durations and slopes. The most significant benefit from SAM is that there is no need for preliminary assumptions and trends identifications are straight forward. The only limitation of the method is short length time series. Absolute relative percentage error control is suggested as +/- 10% for separation of successive partial trend differences. The application of SAM methodology is presented for more than seventy-year duration total annual rainfall records from seven geographic and climate regions in Turkey. It has been calculated that both increasing and decreasing trend durations have at the maximum 4.5-year duration. According to the calculations, except at one meteorology station almost all the trend slopes are negative, which may be an initial signal for climate change impact indicating the rainfall decreases in recent years over Turkey.