• A synthetic analysis for spatiotemporal variability of snow cover and snow phenology was performed. • Decline of snow cover over the most of High Mountain Asia (HMA) from the hydrological year 2002–2020 was found. • The spatiotemporal variations of snow phenology have strong altitude dependence. • Air temperature was the dominant factor affecting the interannual variation of snow phenology. Accurate understanding the spatiotemporal variability of snow cover and snow phenology over High Mountain Asia (HMA) is of great interest because of their vital impacts on the hydrological processes, global climate system and regional water resource management. This study investigates the spatiotemporal variability of snow-covered extent (SCE), snow-covered days (SCD), snow onset date (SOD), snow end date (SED) and snow duration days (SDD) of HMA using the daily cloud-free Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products from the hydrological year 2002 to 2020. The vertical difference of the effect of elevation on snow phenology and the response of snow phenology to climate change are explored. The results indicate that the monthly SCE over the whole HMA exhibited a slight decreasing in most months over the study period. The variability of snow cover and snow phenology over the whole HMA generally showed decreased SCD (significant decrease accounts for 15.73%), delayed SOD (significant delay accounts for 14.35%), advanced SED (significant advance accounts for 15.46%) and shortened SDD (significant shorten accounts for 16.01%). It is worth noting that the snow cover in the West Himalaya was enhancing with its increased SCE, increased SCD and lengthened SDD. There is an elevation dependence of snow phenology changes over HMA with the high-altitude mountain ranges generally having a higher SCD, earlier SOD, later SED and longer SDD than low altitude areas. The air temperature of snow accumulation period is the dominant factor affecting the interannual variation of SOD, and the air temperature of snow melt period is the dominant factor affecting the interannual variation of SED. The increase of air temperature leads to the delayed SOD, advanced SED and shortened SDD. 

Satellite observed spatiotemporal variability of snow cover and snow phenology over High Mountain Asia from 2002 to 2021

Snowmelt from the Tibetan Plateau (TP) is the water source of many major Asian rivers, with significant importance for regional water supply and ecosystem services. The spatiotemporal variations of snow cover on the TP and its response to climate change at different altitudes are still unclear because of the lack of in situ observations on the western TP, and limitations of optical remote sensing due to clouds. Using a daily passive microwave remote sensing snow depth dataset from 1979 to 2020 across the TP, this study investigates the spatiotemporal variations of snow depth and snow phenology as well as their responses to climate change. The results showed that during the past 40 years, the maximum snow depth (SDmax) and the snow cover duration days (SCD) on the TP decreased significantly at a rate of 0.6 cm/decade and 2.9 d/decade, respectively. The snow cover starting date (SCS) was delayed at a rate of 1.1 d/decade, whereas the snow cover melt date (SCM) advanced at a rate of 1.1 d/decade. The decrease of SCD was driven by the advance of SCM, which was caused by the decrease of SDmax, whereas the decrease of SDmax was driven by the increase in snow accumulation season temperature (Ta). The TP showed significant elevation-dependent warming (EDW) (0.04 ℃ decade-1 km−1) and elevation-dependent decrease of SDmax (0.12 cm decade-1 km−1) and SCD (4.1 d decade-1 km−1). The EDW explains the elevation-dependent decrease of SDmax (r = −0.72, P < 0.05) and SCD (r = −0.83, P < 0.05). It is expected that the negative feedback effect of SDmax and SCD on EDW may further exacerbate the EDW of the TP, and the earlier snowmelt due to the continuous decrease of snow depth may increase the frequency of droughts and floods. Our findings support the enhancement of EDW on the TP, depletion of solid reservoirs, and intensification of the regional water crisis in a warmer future. 

Climate and elevation control snow depth and snow phenology on the Tibetan Plateau

Change in the elevational pattern of vegetation greenup date across the Tianshan Mountains in Central Asia during 2001–2020

Investigating the spatial and temporal changes in snow cover over mountain areas is significant for understanding the impact of regional climate variability. In this study, using cloud‐removed snow cover data, which are generated based on Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products, the spatiotemporal changes of snow cover fraction (SCF) and its relationship with temperature and precipitation changes from 2002 to 2020 were examined over Altai Mountains, China. The results demonstrate that the distribution and changes of SCF are highly spatiotemporally heterogeneous. Within a year, the maximum SCF occurs in January at 98.6%, and the minimum appears in July at 8.7%. The annual‐mean SCF shows an increasing trend at 0.09%·annum−1, owing to the significantly increasing SCF in the snow accumulation period at 0.5%·annum−1 and the decreasing SCF in the snow melting period at −0.2%·annum−1. The SCF distribution, as well as its interannual change, is greatly influenced by elevation. During the snow cover period, a positive linear correlation between SCF and elevation is found at 0.02%·m−1 (p < .01). The annual‐mean SCF decreases in the area below 1,200 m, whereas it increases in the area above 1,200 m. Accordingly, the elevation‐dependent SCF results in various SCF distributions on different slopes and watersheds. The SCF shows an apparent pattern in different aspects, with similar SCFs between the north and east aspects and between the west and south aspects but a difference between the northeast aspects and the westsouth aspects. The SCF is negatively correlated with air temperature (r = −0.74, p < 0.01) and positively correlated with precipitation (r = 0.74, p < 0.01). In addition, temperature shows a significant and larger correlation with SCF in both the snow accumulation and melting periods, indicating the major factor of temperature for the changes in SCF.

How do snow cover fraction change and respond to climate in Altai Mountains of China?

Seasonal snow is a critical component of the surface energy balance and hydrologic cycle, yet global maps of seasonal snow boundaries are not readily available. Snow persistence (SP), the fraction of a year that snow is present on the ground, is an easily globally observed snow metric that can be used to map snow zones globally. Here we map snow zones across the globe using SP calculated from the MODIS10A2 product; evaluate how SP relates to precipitation, temperature, and climate indices, and examine trends in annual SP for 2001-2016. In the northern hemisphere, intermittent, seasonal, and permanent snow zones occupy a far greater percent (63%) of the land surface than in the southern hemisphere (< 5%) where the low snow zone dominates (> 95%). SP is most variable from year to year near the snow line, which has a relatively consistent decrease in elevation with increasing latitude across all continents. Areas with decreasing SP trends cover 5.8% of snow zone areas, whereas those with increasing trends cover 1.0% of this area. The largest areas of declining SP are in the seasonal snow zones of the northern hemisphere. Trend patterns vary within individual regions, with elevation, and on windward-leeward sides of the mountains. This study supplies a framework for comparing snow between regions, highlights areas with snow changes, and can facilitate analyses of why snow changes vary within and between regions. 1 Department of Geosciences, Colorado State University, Fort Collins, CO, USA 2 Departmento de Ciencias Geográficas, Universidad de Playa Ancha, Valparaíso, Chile 3 Centro de Estudios Avanzados, Universidad de Playa Ancha, Viña del Mar, Chile 4 Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO, USA

Global snow zone maps and trends in snow persistence 2001-2016

Elevation-dependent response of snow phenology to climate change from a remote sensing perspective: A case survey in the central Tianshan mountains from 2000 to 2019

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Elevation-dependent response of snow phenology to climate change from a remote sensing perspective: A case survey in the central Tianshan mountains from 2000 to 2019