scholarly journals Assessments and corrections of GLDAS2.0 forcing data in four large transboundary rivers in the Tibetan Plateau and Northeast China

2021 ◽  
Author(s):  
Wei Qi ◽  
Junguo Liu ◽  
Hong Yang ◽  
Deliang Chen ◽  
Lian Feng
Keyword(s):  
Tibetan Plateau ◽  
Northeast China ◽  
The Tibetan Plateau ◽  
Transboundary Rivers

The n-alkanol paleoclimate records in two peat deposits: a comparative study of the northeastern margin of the Tibetan Plateau and Northeast China

2010 ◽  
Vol 63 (1) ◽  
pp. 135-143 ◽  
Author(s):  
Yanhong Zheng ◽  
Weijian Zhou ◽  
Zhao Liu ◽  
Xiaomin Liu
Keyword(s):  
Tibetan Plateau ◽  
Comparative Study ◽  
Northeast China ◽  
The Tibetan Plateau ◽  
Peat Deposits ◽  
Paleoclimate Records

scholarly journals Snow cover variations across China from 1951–2018

2020 ◽  
Author(s):  
Xiaodong Huang ◽  
Changyu Liu ◽  
Zhaojun Zheng ◽  
Yunlong Wang ◽  
Xubing Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regional Differences ◽  
Meteorological Factors ◽  
Onset Date ◽  
The Tibetan Plateau ◽  
Maximum Snow Depth ◽  
The Postponement

Abstract. Based on a snow depth dataset retrieved from meteorological stations, this experiment explored snow indices, including snow depth (SD), snow covered days (SCDs), and snow phenology variations, across China from 1951 to 2018. The results indicated that the snow cover in China exhibits regional differences. The annual mean SD tended to increase, and the increases in mean and maximum snow depth were 0.04 cm and 0.1 cm per decade, respectively. SCDs tended to increase by approximately 0.5 days per decade. The significant increases were concentrated at latitudes higher than 40° N, especially in Northeast China. However, in the Tibetan Plateau, the SD and SCDs tended to decrease but not significantly. Regarding the snow phenology variations, the snow duration days in China decreased, and 25.2 % of the meteorological stations showed significant decreasing trends. This result was mainly caused by the postponement of the snow onset date and the advancement of the snow end date. Geographical and meteorological factors are closely related to snow cover, especially the change in temperature, which will lead to significant changes in snow depth and phenology.

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.

scholarly journals Snow cover variations across China from 1952–2012

2019 ◽  
Author(s):  
Xiaodong Huang ◽  
Changyu Liu ◽  
Yunlong Wang ◽  
Qisheng Feng ◽  
Tiangang Liang
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regional Differences ◽  
Onset Date ◽  
The Tibetan Plateau ◽  
Increasing Trend ◽  
Main Period ◽  
The Postponement

Abstract. Based on a snow depth (SD) dataset retrieved from meteorological stations, this experiment explored snow indices including SD, snow covered days (SCDs), and snow phenology variations in China from 1952 to 2012. The results indicated that the snow in China exhibits regional differences, and the snow cover is mainly concentrated in three snow cover areas in Northeast China, northern Xinjiang and the Tibetan Plateau. In China, the annual average SD showed an increasing trend, and the increases in the average snow depth (SDaverage), cumulative snow depth (SDoverall) and maximum snow depth (SDmax) reached 0.04 cm, 0.05 cm and 0.07 cm per decade, respectively. The significant increases were mainly concentrated in areas higher than 40° N latitude, especially in Northeast China. The SDaverage, SDoveralland SDmax jump points are mainly in 1956, 1957, 1978, and 1987. In the first main period, the SDoverall oscillation in China is relatively stable, and its average period is approximately 13 years. The SCDs showed an increasing trend, with an increase of 0.5 days per decade. The significant increases in SCDs were also concentrated in areas higher than 40° N latitude, especially in Northeast China.However, in the Tibetan Plateau, the decrease in the SCDs reached 0.1 days per decade. In snow phenology, the snow duration days (SDDs) of China decreased, and 17.4 % of the meteorological stations showed significant decreasing trends. This result is mainly caused by the postponement of the snow onset date (SOD) and the advancement of the snow end date (SED). Geographical factors, including latitude, longitude and altitude, affect snow cover distribution directly and indirectly. The squared multiple correlations of SDDs and SCDs are greater than 0.9. Among the effects of SDDs and SCDs, the largest standardized total effect is from altitude on the SDDs, and the effect reaches 0.8.

Geology: Crustal flow of the Tibetan Plateau

Nature China ◽  
2010 ◽  
Author(s):  
Felix Cheung
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau
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