Snow is involved in and influences water–energy processes at multiple scales. Studies on land surface snow phenology are an important part of cryosphere science and are a hot spot in the hydrological community. In this study, we improved a statistical downscaling method by introducing a spatial probability distribution function to obtain regional snow depth data with higher spatial resolution. Based on this, the southern Gansu Plateau (SGP), an important water source region in the upper reaches of the Yellow River, was taken as a study area to quantify regional land surface snow phenology variation, together with a discussion of their responses to land surface terrain and local climate, during the period from 2003 to 2018. The results revealed that the improved downscaling method was satisfactory for snow depth data reprocessing according to comparisons with gauge-based data. The downscaled snow depth data were used to conduct spatial analysis and it was found that snow depth was on average larger and maintained longer in areas with higher altitudes, varying and decreasing with a shortened persistence time. Snow was also found more on steeper terrain, although it was indistinguishable among various aspects. The former is mostly located at high altitudes in the SGP, where lower temperatures and higher precipitation provide favorable conditions for snow accumulation. Climatically, factors such as precipitation, solar radiation, and air temperature had significantly singular effectiveness on land surface snow phenology. Precipitation was positively correlated with snow accumulation and maintenance, while solar radiation and air temperature functioned negatively. Comparatively, the quantity of snow was more sensitive to solar radiation, while its persistence was more sensitive to air temperature, especially extremely low temperatures. This study presents an example of data and methods to analyze regional land surface snow phenology dynamics, and the results may provide references for better understanding water formation, distribution, and evolution in alpine water source areas.
For a better understanding of the precipitable water in the arid northwestern China (NWC), we surveyed the water vapour variability on both sides of the alpine range crests based on the Tropical Rainfall Measuring Mission monthly precipitation data (TRMM 3B43). There were 12 target zones and 23 subzones in six mountain systems representatively selected according to alpine hydrogeomorphology. They were used for comparative analyses in time and space. Comparisons between the two sides of the range crests revealed that there is more precipitable water on the south slopes of the Qilian, Altun, Kunlun, and Altai Mountains, on the north slope of the Tian Mountains, and on the east slope of Helan Mountains. High correlations were detected between precipitable water for both sides of the range crests in target zones, while low correlations were found among precipitable water separately averaged in the Kunlun, Tian, and Qilian Mountains including both sides of the range crests. The proportion of precipitable water during the rainy season gradually increased from west to east along the mountains. Temporally, precipitation presented synchronous increases or decreases on the two sides of the range crests in most of the target zones during the time period from 1998 to 2016, and an overall increase in alpine annual precipitable water was found in the area, except for the decrease in the Altun and western Tian Mountains. The summer decay dominated the decrease in these two target zones, while strengthened conveyance was observed in other seasons, especially in spring and autumn, which compensated for, and led to, total increases in precipitable water in most of the target zones. All of the above findings were indicative of differences in vapour transport from outside areas into diverse alpine systems in the arid NWC, which could be schematically evidenced by the spatial patterns of monthly and annual water vapour conveyance retrieved from the TRMM precipitation data.
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