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Abstract

Changes in maximum and minimum temperature (Tmax and Tmin) are analysed to assess the regional extent of global warming in Xinjiang autonomous region, China, for the period of 1961-2015. Two nonlinear, non-stationary signal-processing methods - the Bernaola-Galván algorithm and the ensemble empirical mode decomposition method - are applied on daily time series of observations from 53 meteorological stations. Statistically significant abrupt change points are identified in 1996 in both annual Tmax and Tmin time series averaged for the whole province, while another one is identified in 1976 in the annual Tmin time series only. At local scale, most stations experience one abrupt change point in annual Tmax in the 1990s, but two or three change points in annual Tmin, mainly in the 1980s and 1990s. After the abrupt change points, the frequency and probability density of Tmax in summer and Tmin in winter are skewed towards the hotter part of the probability distribution. It is found that the hot temperature extremes in summer occur concurrently with El Niño events. Further results suggest that anomalies in geopotential height at 500hPa can be associated with the hottest and coldest months. The key regions of the anomalies are over the east of the Ural Mountains and the North Atlantic, while the geopotential height anomalies over Greenland and the east of the Ural Mountains are closely related to the hot and cold spells. © 2017 Royal Meteorological Society.