Changes in Snow Phenology from 1979 to 2016 over the Tianshan Mountains, Central Asia

Abstract

Snowmelt from the Tianshan Mountains (TS) is a major contributor to the water resources of the Central Asian region. Thus, changes in snow phenology over the TS have significant implications for regional water supplies and ecosystem services. However, the characteristics of changes in snow phenology and their influences on the climate are poorly understood throughout the entire TS due to the lack of in situ observations, limitations of optical remote sensing due to clouds, and decentralized political landscapes. Using passive microwave remote sensing snow data from 1979 to 2016 across the TS, this study investigates the spatiotemporal variations of snow phenology and their attributes and implications. The results show that the mean snow onset day (Do), snow end day (De), snow cover duration days (Dd), and maximum snow depth (SDmax) from 1979 to 2016 were the 78.2nd day of hydrological year (DOY), 222.4th DOY, 146.2 days, and 16.1 cm over the TS, respectively. Dd exhibited a spatial distribution of days with a temperature of <0 °C derived from meteorological station observations. Anomalies of snow phenology displayed the regional diversities over the TS, with shortened Dd in high-altitude regions and the Fergana Valley but increased Dd in the Ili Valley and upper reaches of the Chu and Aksu Rivers. Increased SDmax was exhibited in the central part of the TS, and decreased SDmax was observed in the western and eastern parts of the TS. Changes in Dd were dominated by earlier De, which was caused by increased melt-season temperatures (Tm). Earlier De with increased accumulation of seasonal precipitation (Pa) influenced the hydrological processes in the snowmelt recharge basin, increasing runoff and earlier peak runoff in the spring, which intensified the regional water crisis.

Recent Changes in Water Discharge in Snow and Glacier Melt-Dominated Rivers in the Tienshan Mountains, Central Asia

“…The gridded precipitation dataset is obtained from the Global Precipitation Climatology Centre (GPCC), which is operated by Deutscher Wetterdienst under the auspices of the World Meteorological Organization (WMO). It has higher accuracy with its spatial resolution of 0.25 • and should, therefore, perform better with regard to real amounts of precipitation in mountain regions with complex topography [85]. Other data include monthly gridded surface temperature (two-meter air temperature) from the ERA-Interim dataset, which is downloaded from the European Center for Medium-Range Weather Forecasts.…”

“…By comparing the MODIS SCA in winter, the mean accuracy of this passive microwave remote-sensing data is 86% [89], with relative biases decreasing from 66.18% to −1.5% [87]. This approach has been widely used in the Tibetan Plateau, the Tienshan Mountains, and the plains and mountain regions of China [59,75,85,90].…”

“…In this study, a Mann-Kendall trend test was adopted to identify the trends of temperature, precipitation, SCA, SD, and streamflow [92,93]. This is a non-parametric test and considered to be more objective for the trends of time series, a method that has been widely used in the trend analysis of hydrological and climatic variables [85,94]. Additionally, linear regression was applied to analyze changing rates in temperature, precipitation, SCA, SD, and streamflow during each period in 1979-2015.…”

Variations in Sediment Grain Size from a Lake in the Tianshan Mountain of Central Asia: Implications for Paleoprecipitation Reconstruction

“…The Tian Shan comprises the largest mountain range in Central Asia, traversing the central part of Xinjiang in China, Kyrgyzstan, and Uzbekistan, and extending into four countries including Kazakhstan at the western end. Major rivers in Central Asia such as the Ili, Syr Darya, Amu Darya, Tarim, and Chu rivers all have their headwaters in the Tian Shan [14]. Within the context of global change, important changes in the climate and hydrology of the Tian Shan have occurred [2,4,11,[14][15][16].…”

“…Major rivers in Central Asia such as the Ili, Syr Darya, Amu Darya, Tarim, and Chu rivers all have their headwaters in the Tian Shan [14]. Within the context of global change, important changes in the climate and hydrology of the Tian Shan have occurred [2,4,11,[14][15][16]. In particular, owing to the lack of weather monitoring stations in high-altitude areas such as the Tian Shan, there is a major knowledge gap regarding temperature and precipitation trends, and available data are typically poor and often unreliable, which has a negative impact on the ability to predict the occurrence and intensity of extreme weather events [17].…”