scholarly journals Combined Effects of Precipitation and Temperature on the Responses of Forest Spring Phenology to Winter Snow Cover Dynamics in Northeast China

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 138950-138962 ◽  
Author(s):  
Dejing Qiao ◽  
Jianmin Zhou ◽  
Shuang Liang ◽  
Xiyou Fu
Keyword(s):  
Snow Cover ◽  
Northeast China ◽  
Combined Effects ◽  
Spring Phenology ◽  
Winter Snow ◽  
Precipitation And Temperature

scholarly journals Effects of Winter Snow Cover on Spring Soil Moisture Based on Remote Sensing Data Product over Farmland in Northeast China

2020 ◽  
Vol 12 (17) ◽  
pp. 2716
Author(s):  
Shuang Liang ◽  
Xiaofeng Li ◽  
Xingming Zheng ◽  
Tao Jiang ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Linear Regression ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regression Models ◽  
Linear Regression Models ◽  
Winter Snow ◽  
The Relationship

Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.

scholarly journals Relationship between Winter Snow Cover Dynamics, Climate and Spring Grassland Vegetation Phenology in Inner Mongolia, China

2019 ◽  
Vol 8 (1) ◽  
pp. 42 ◽  
Author(s):  
Dejing Qiao ◽  
Nianqin Wang
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Terrestrial Ecosystems ◽  
Onset Date ◽  
Vegetation Phenology ◽  
Grassland Vegetation ◽  
Spring Phenology ◽  
Winter Snow

The onset date of spring phenology (SOS) is regarded as a key parameter for understanding and modeling vegetation–climate interactions. Inner Mongolia has a typical temperate grassland vegetation ecosystem, and has a rich snow cover during winter. Due to climate change, the winter snow cover has undergone significant changes that will inevitably affect the vegetation growth. Therefore, improving our ability to accurately describe the responses of spring grassland vegetation phenology to winter snow cover dynamics would enhance our understanding of changes in terrestrial ecosystems due to their responses to climate changes. In this study, we quantified the spatial-temporal change of SOS by using the Advanced Very High Resolution Radiometer (AVHRR) derived Normalized Difference Vegetation Index (NDVI) from 1982 to 2015, and explored the relationships between winter snow cover, climate, and SOS across different grassland vegetation types. The results showed that the SOS advanced significantly at a rate of 0.3 days/year. Winter snow cover dynamics presented a significant positive correlation with the SOS, except for the start date of snow cover. Moreover, the relationship with the increasing temperature and precipitation showed a significant negative correlation, except that increasing Tmax (maximum air temperature) and Tavg (average air temperature) would lead a delay in SOS for desert steppe ecosystems. Sunshine hours and relative humidity showed a weaker correlation.

scholarly journals Trends and variability in snowmelt in China under climate change

2021 ◽  
Author(s):  
Yong Yang ◽  
Rensheng Chen ◽  
Guohua Liu ◽  
Zhangwen Liu ◽  
Xiqiang Wang
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Snow Cover ◽  
Northeast China ◽  
Cmip5 Models ◽  
Historical Period ◽  
The Tibetan Plateau ◽  
Snowmelt Runoff ◽  
The Mean ◽  
Precipitation And Temperature

Abstract. Snowmelt is a major fresh water resource, and quantifying snowmelt and its variability under climate change is necessary for planning and management of water resources. Spatiotemporal changes in snow properties in China have drawn wide attention in recent decades; however, country-wide assessments of snowmelt are lacking. Using precipitation and temperature data with a high spatial resolution (0.5 seconds, approximately 1 km), this study calculated the monthly snowmelt in China for the 1951–2017 period using a simple temperature index model, and the model outputs were validated using snowfall, snow depth, snow cover extent and snow water equivalent. Precipitation and temperature scenarios developed from five CMIP5 models were used to predict future snowmelt in China under three different representative concentration pathways (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5). The results showed that the mean annual snowmelt in China from 1951 to 2017 was 2.41 × 1011 m3. The mean annual snowmelts in Northern Xinjiang, Northeast China, and the Tibetan Plateau – China’s three main stable snow cover regions – were 0.18 × 1011 m3, 0.42 × 1011 m3 and 1.15 × 1011 m3, respectively. From 1951 to 2017, the snowmelt increased significantly in the Tibetan Plateau and decreased significantly in North, Central and Southeast China. In the whole of China, there was a decreasing trend in snowmelt, but this was not statistically significant. The mean annual snowmelt runoff ratios were generally more than 10 % in almost all third-level basins in West China, more than 5 % in third-level basins in North and Northeast China, and less than 2 % in third-level basins in South China. From 1951 to 2017, the annual snowmelt runoff ratios decreased in most third-level basins in China. Under RCP2.6, RCP4.5 and RCP8.5, the projected snowmelt in China in 2030s (2050s, 2090s) may decrease by 13.4 % (16.3 %, 13.8 %), 19.1 % (19.8 %, 22.5 %), 17.1 % (24.7 %, 42.8 %) compared with the historical period (1951–2017), respectively. Most of the projected mean annual snowmelt runoff ratios in third-level basins in different decades (2030s, 2050s and 2090s) were lower than those in the historical period. Low temperature regions can tolerate more warming, and the snowmelt change in these regions is mainly influenced by precipitation; however, the snowmelt change in warm regions is more sensitive to temperature increases. The spatial variability of snowmelt changes may lead to regional differences in the impact of snowmelt on water supply.

Displacement and dispersion of parturient caribou at calving as antipredator tactics

1987 ◽  
Vol 65 (7) ◽  
pp. 1597-1606 ◽  
Author(s):  
A. T. Bergerud ◽  
R. E. Page
Keyword(s):  
Snow Cover ◽  
Rangifer Tarandus ◽  
Forest Cover ◽  
Ursus Arctos ◽  
Early Years ◽  
Stochastic Variation ◽  
Spring Phenology ◽  
Calf Survival ◽  
Searching Ability ◽  
High Elevations

Survival of caribou (Rangifer tarandus) calves until 4 months of age was monitored for 8 years in four herds in northern British Columbia, Canada. The chief cause of mortality was predation by wolves (Canis lupus) and grizzly bears (Ursus arctos) and this mortality was correlated within years between all herds. More calves died in years with late springs when extensive snow patches remained during calving in June than in early springs when larger snow-free areas existed. Before calving and after birth, caribou cows sought to space themselves out on snow-free areas in small aggregations at high elevations above treeline. By placing themselves at high elevations, the females increased the distance between themselves and wolves and bears travelling in the valley bottoms, as well as the main alternate prey, moose (Alces alces), which calved only in forest cover at lower elevations. In addition, the reduced snow in early springs meant that there was more space for dispersion. The variation in calf survival for three herds was negatively correlated with the heterogeneity of the calving area. Snow cover disappeared in smaller patches in more rugged mountains regardless of spring phenology, thereby providing a more constant search area for predators from year to year. More uniform mountains had either extensive areas of snow cover (late years) or brown substrates (early years), thus greatly varying the space that predators had to search between years. As stochastic variation in snow cover at calving time alters the searching ability of predators, the aggregation responses of prey, and the spatial overlap between predators and prey, it promotes short-term stability of the prey and lessens the probability of extinction.

scholarly journals Mapping the Distribution of Buried Glacier Ice – An Example From Lago Delle Locce, Monte Rosa, Italian Alps

1986 ◽  
Vol 8 ◽  
pp. 78-81 ◽  
Author(s):  
W. Haeberli ◽  
F. Epifani
Keyword(s):  
Snow Cover ◽  
Seismic Refraction ◽  
Italian Alps ◽  
Frozen Ground ◽  
Near Surface ◽  
Winter Snow ◽  
Glacier Ice ◽  
Geoelectrical Resistivity ◽  
Monte Rosa

Techniques for mapping the distribution of buried glacier ice are discussed and the results, from a study carried out within the framework of flood protection work in the Italian Alps, are presented. Bottom temperatures of the winter snow cover (BTS) primarily indicate the heat flow conditions in the underlying ground and mainly depend on the presence or absence of an ice layer beneath the surface. Determination of BTS values is therefore an inexpensive method for quickly mapping the near-surface underground ice in areas where there is 1 m or more of winter snow cover. At greater depths, and/or when more detail is required, geoelectrical resistivity soundings and seismic refraction soundings are most commonly used to investigate underground ice. A combination of the two sounding techniques allows the vertical extent and the main characteristics (frozen ground, dead glacier ice) to be determined in at least a semi-quantitative way. Complications mainly arise from irregularity in the horizontal extension of the studied underground ice bodies, and they may have to be overcome by expensive core drillings and borehole measurements. Widespread occurrence of buried glacier ice was observed in morainic deposits, surrounding an ice-dammed lake near Macugnaga, Italy.

scholarly journals Climatic influence on the composition of snow cover at Austre Okstindbreen, Norway, 1989 and 1990

1994 ◽  
Vol 19 ◽  
pp. 1-6 ◽  
Author(s):  
He Yuanqing ◽  
Wilfred H. Theakstone
Keyword(s):  
Snow Cover ◽  
North Atlantic ◽  
Early Summer ◽  
Late Winter ◽  
Crustal Material ◽  
Air Masses ◽  
The North ◽  
Air Temperatures ◽  
Winter Snow ◽  
Marine Source

Winter snow cover at Austre Okstindbreen is influenced strongly by patterns of atmospheric circulation, and by air temperatures during precipitation. Differences of circulation over the North Atlantic and Scandinavia during the winters of 1988–89 and 1989–90 were reflected in the ionic and isotopic composition of snow that accumulated at the glacier. Early summer ablation did not remove, or smooth out, all the initial stratigraphic differences. In the first half of the 1988–89 winter, most air masses took a relatively short route between a marine source and Okstindan; late winter snowfalls were from air masses which had taken a longer continental route. The snow that accumulated in the first half of the 1989–90 winter was associated with air masses which had followed longer continental routes, and so brought higher concentrations of impurities from forests, lakes and crustal material. The ablation season began earlier in 1990 than in 1989, and summer winds and rain supplied more impurities to the snowpack surface.

scholarly journals Assessing Snow Phenology and Its Environmental Driving Factors in Northeast China

2022 ◽  
Vol 14 (2) ◽  
pp. 262
Author(s):  
Hui Guo ◽  
Xiaoyan Wang ◽  
Zecheng Guo ◽  
Siyong Chen
Keyword(s):  
Snow Cover ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Water Cycle ◽  
Water Source ◽  
Driving Factors ◽  
Change Rate ◽  
Mean Temperature ◽  
Forested Areas

Snow cover is an important water source and even an Essential Climate Variable (ECV) as defined by the World Meteorological Organization (WMO). Assessing snow phenology and its driving factors in Northeast China will help with comprehensively understanding the role of snow cover in regional water cycle and climate change. This study presents spatiotemporal variations in snow phenology and the relative importance of potential drivers, including climate, geography, and the normalized difference vegetation index (NDVI), based on the MODIS snow products across Northeast China from 2001 to 2018. The results indicated that the snow cover days (SCD), snow cover onset dates (SCOD) and snow cover end dates (SCED) all showed obvious latitudinal distribution characteristics. As the latitude gradually increases, SCD becomes longer, SCOD advances and SCED delays. Overall, there is a growing tendency in SCD and a delayed trend in SCED across time. The variations in snow phenology were driven by mean temperature, followed by latitude, while precipitation, aspect and slope all had little effect on the SCD, SCOD and SCED. With decreasing temperature, the SCD and SCED showed upward trends. The mean temperature has negatively correlation with SCD and SCED and positively correlation with SCOD. With increasing latitude, the change rate of the SCD, SCOD and SCED in the whole Northeast China were 10.20 d/degree, −3.82 d/degree and 5.41 d/degree, respectively, and the change rate of snow phenology in forested areas was lower than that in nonforested areas. At the same latitude, the snow phenology for different underlying surfaces varied greatly. The correlations between the snow phenology and NDVI were mainly positive, but weak correlations accounted for a large proportion.

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