Spatiotemporal Variability of Monthly and Annual Snow Depths in Xinjiang, China over 1961–2015 and the Potential Effects

Abstract

The spatiotemporal variability of snow depth supplies important information for snow disaster prevention. The monthly and annual snow depths and weather data (from Xinjiang Meteorological Observatory) at 102 meteorological stations in Xinjiang, China over 1961-2015 were used to analyze the spatiotemporal characteristics of snow depths from different aspects. The empirical orthogonal function (EOF), the modified Mann-Kendall method, Morlet wavelet, Daubechies wavelet decomposition and cross wavelet transform were applied to investigate the trend and significance, spatial structure, periods, decomposed series and coherence of monthly and annual snow depths. The results indicated that: (1) The value of EOF first spatial mode (EOF1) of the monthly and annual snow depths in north Xinjiang were larger than south Xinjiang, indicating greater variability of snow depths in north Xinjiang. (2) The change points of annual snow depth mainly occurred during 1969-1979 and 1980-1990. The annual snow depth of most sites showed increasing trends, but with different slope magnitudes. (3) The sites that had main periods of 2-8 and 9-14 years of monthly and annual snow depths (detected by the Morlet wavelet) mainly distributed in northern Xinjiang. The sites that had main periods of 15-20 years of monthly and annual snow depths mainly distributed in southwestern Xinjiang. (4) By using the Daubechies wavelet, the decomposed annual snow depth in entire Xinjiang tended to increase. (5) Through the cross wavelet transform, annual snow depths in entire Xinjiang had good correlations with annual precipitation or relative humidity, and showed a low negative correlation with minimum temperature or sunshine hours. In conclusion, the monthly and annual snow depths had comprehensive spatiotemporal variability but had overall increasing trend during 1961-2015.There have been several research projects on spatial and temporal variation analysis, simulation and remote sensing analysis of snow depth, conducted at daily, monthly, or annual scales and in different parts of the world [7,8]. Liu et al. [9] used wavelet analysis to analyze the periodic characteristics of maximum snow depth in northern Xinjiang over 1961-2008. They found that the maximum snow depth had a main period of 7-11 years in northern Xinjiang. Hu et al. [10] analyzed the correlation coefficient between the annual snow depth and the annual precipitation (or average temperature) in Xinjiang over 1960-2011. The annual snow depth had a good correlation with the annual precipitation, but a low correlation with the average temperature. Xu et al. [11] used a linear model to investigate the spatiotemporal characteristics of daily snow depth and the snow-cover days in the Qinghai-Tibetan Plateau over 1961-2010. They revealed that snow cover was controlled by multiple climate factors rather than a single variable. Ding et al. [6] used the modified Mann-Kendall test to analyze trends and significance of daily snow depth at 105 stations (spread in the whole area) in Xinjiang, China over 19...

Snow depth alteration and its relation with climate variability in China

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