Abstract. We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized (

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

Time-lag effects of climatic change and drought on vegetation dynamics in an alpine river basin of the Tibet Plateau, China

Climate-driven changes in hydrological and hydrodynamic responses in the Yarlung Tsangpo River

In the context of global warming, relevant studies have shown that China will experience the largest temperature rise in the Qinghai–Tibet Plateau and northwestern regions in the future. Based on MOD10A2 and MYD10A2 snow products and snow depth data, this study analyzes the temporal and spatial evolution characteristics of the snow cover fraction, snow depth, and snow cover days in the three stable snow cover areas in China, and combines 15 modes in CMIP6 snow cover data in four different scenarios with three kinds of variables, predicting the spatiotemporal evolution pattern of snow cover in China’s three stable snow cover areas in the future. The results show that (1) the mean snow cover fraction, snow depth, and snow cover days in the snow cover area of Northern Xinjiang are all the highest. Seasonal changes in the snow cover areas of the Qinghai–Tibet Plateau are the most stable. The snow cover fraction, snow depth, and snow cover days of the three stable snow cover areas are consistent in spatial distribution. The high values are mainly distributed in the southeast and west of the Qinghai–Tibet Plateau, the south and northeast of Northern Xinjiang, and the north of the snow cover area of Northeast China. (2) The future snow changes in the three stable snow cover areas will continue to decline with the increase in development imbalance. Snow cover fraction and snow depth decrease most significantly in the Qinghai–Tibet Plateau and the snow cover days in Northern Xinjiang decrease most significantly under the SSPs585 scenario. In the future, the southeast of the Qinghai–Tibet Plateau, the northwest of Northern Xinjiang, and the north of Northeast China will be the center of snow cover reduction. (3) Under the four different scenarios, the snow cover changes in the Qinghai–Tibet Plateau and Northern Xinjiang are the most significant. Under the SSPs126 and SSPs245 scenarios, the Qinghai–Tibet Plateau snow cover has the most significant change in response. Under the SSPs370 and SSPs585 scenarios, the snow cover in Northern Xinjiang has the most significant change.

/pdf/snow-cover-in-the-three-stable-snow-cover-areas-of-china-and-296efrdy.pdf

Snow Cover in the Three Stable Snow Cover Areas of China and Spatio-Temporal Patterns of the Future

A perception of the nexus "resistance, recovery, resilience" of vegetations responded to extreme precipitation pulses in arid and semi-arid regions: A case study of the Qilian Mountains Nature Reserve, China.

Vertical influence of temperature and precipitation on snow cover variability in the Yarlung Zangbo River basin, China

The timing of the cessation of Meiyu is closely connected to the amount of Meiyu rainfall and the commencement of the rainy season in North China. Accurately forecasting the Meiyu withdrawal date (MWD) over the Yangtze–Huaihe River basin (YHRB) has significant implications for the prevention and mitigation of flooding in eastern China. This study observed an intimate out-of-phase relationship between MWD variations and early spring (March and April) Arctic Sea ice area (SIA) anomalies to the north of the Chukchi and Beaufort Seas, as well as SIA anomalies to the north of the Queen Elizabeth Islands (75° N–82° N, 170° E–130° W and 82° N–86° N, 130° W–80° W, respectively) on the interannual timescale. As such, these can be considered key Arctic Sea ice domains connected to Meiyu cessation in the YHRB. The Arctic SIA anomalies in the key domains persist from early spring to early summer (May and June), thus exerting a lag modulation effect on year-to-year changes in Meiyu cessation, which can be demonstrated through observational analysis and results from the Community Earth System Model Large Ensemble Numerical Simulation (CESM-LENS) project. Specifically, the preceding negative SIA anomalies in the key domains are linked to a planetary-scale Rossby wave-like pattern emanating over areas to the northwest of the Chukchi Sea. This tele-connected wave-like pattern is conducive to the generation and maintenance of a quasi-barotropic “north-low–south-high” meridional see-saw pattern over the East Asian–Western North Pacific sector in July, which is a pivotal circulation pattern responsible for delayed Meiyu termination. Furthermore, the situation is the opposite in response to increased sea ice in these key domains within the Arctic. This study proposes a significant cryospheric forcing indicator for Meiyu cessation over the YHRB, which may provide helpful information for operational forecasting of the withdrawal timing of the Meiyu over the YHRB.

/pdf/possible-impact-of-early-spring-arctic-sea-ice-on-meiyu-1waqrvgv.pdf

Possible Impact of Early Spring Arctic Sea Ice on Meiyu Cessation over the Yangtze–Huaihe River Basin

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Vertical influence of temperature and precipitation on snow cover variability in the Yarlung Zangbo River basin, China

Possible Impact of Early Spring Arctic Sea Ice on Meiyu Cessation over the Yangtze–Huaihe River Basin