Impact of Snowpack on the Land Surface Phenology in the Tianshan Mountains, Central Asia

Abstract

The accumulation and ablation processes of seasonal snow significantly affect the land surface phenology in a mountainous ecosystem. However, the ability of snow to regulate the alpine land surface phenology in the arid regions is not well described in the context of climate change. The impact of snowpack changes on land surface phenology and its driving factors were investigated in the Tianshan Mountains using the land surface phenology metrics derived from satellited products and a snow dataset from downscaled regional climate model simulations covering the period from 1983 to 2015. The results demonstrated that the annual mean start of growing season (SOS) and length of growing season (LOS) experienced a significant (p < 0.05) decrease and increase with a rate of −2.45 days/decade and 2.98 days/decade, respectively. The significantly advanced SOS and increased LOS were mainly seen in the Western Tianshan Mountains and Ili Valley regions with elevations from 2500 to 3500 m a.s.l and below 3000 m a.s.l, respectively. During the early spring, the significant decline in snow cover fraction (SCF) could advance the SOS. In contrast, snowmelt amount and annual maximum snow water equivalent (SWE) have an almost equally substantial positive correlation with annual maximum vegetation greenness. In particular, the SOS of grassland was the most sensitive to variations of snow cover fraction during early spring than that of other vegetation types, and their strong relationship was mainly located at elevations from 1500 to 2500 m a.s.l. Its greenness was significantly controlled by the annual maximum snow water equivalent in all elevation bands. Both decreased SCF and increased temperature in the early spring caused a significant advance of the SOS, consequently prolonging the LOS. Meanwhile, more SWE and snowmelt amount could significantly promote vegetation greenness by regulating the soil moisture. The results can improve the understanding of the snow ecosystem services in the alpine regions under climate change.

Reflection of Solar Light from Surface Snow Loaded with Light-Absorbing Impurities: A Case Study of Black Carbon, Mineral Dust, and Ash

“…These findings are consistent with previous model simulations 30 and in situ measurements. 46 The spectral slope of high-level MD snow first shows a significant decrease at 600 nm, making it possible to identify MD-loaded snow using simple mathematical methods such as spectral derivative or change point detection. The impact of ash on snow spectra is more pronounced than that of MD, with its first spectral slope significant decrease point near 700 nm (Figure 7A).…”

An Overview of Remote Sensing for Mountain Vegetation and Snow Cover

“…Thirdly, the studies included in this Special Issue explore the interrelationships between vegetation and snow cover in the context of climate change and intensive human activity. Yang et al [14] investigated the impact of snowpack changes on land surface phenology and its driving factors in the Tianshan Mountains from 1983 to 2015. Snow and vegetation phenology metrics were derived from satellite products and regional climate model simulations.…”

Continued spring phenological advance under global warming hiatus over the Pan-Third Pole

“…For example, over the Tibetan Plateau, a series of research based on satellite data found an advancing trend in spring phenology from 1982 to the mid-1990s, but the advance slowed down after the mid-1990s ( Yu et al., 2010 ; Chen et al., 2011 ; Piao et al., 2011 ; Shen, 2011 ; Shen et al., 2011 ). While a continued advance in spring phenology in the first decades of this century, was found in the western Tianshan Mountains, Ili Valley ( Yang et al., 2022 ), and the northern Alps of European ( Meng et al., 2021 ). What’s more, a significant slowing down of spring phenology during 2000-2011 were found in the lowland of the Pan-Third Pole ( Fu et al., 2014 ), with even slight delaying trends detected in the south-western Tibetan Plateau ( Shen et al., 2022 ) and high altitude (>2500 m) of Tianshan Mountains in central Asia ( Ding et al., 2022 ), and French Alps ( Asse et al., 2018 ).…”