Wind regime features and their impacts on the middle reaches of the Yarlung Zangbo River on the Tibetan Plateau, China

The wide valley of the Yarlung Zangbo River is one of the most intense areas in terms of aeolian activity on the Tibetan Plateau,China.In the past,the evaluation of the intensity of aeolian activity in the Quxu–Sangri section of the Yarlung Zangbo River Valley was mainly based on data from the old meteorological stations,especially in non-sandy areas.In 2020,six new meteorological stations,which are closest to the new meteorological stations,were built in the wind erosion source regions(i.e.,sandy areas)in the Quxu–Sangri section.In this study,based on mathematical statistics and empirical orthogonal function(EOF)decomposition analysis,we compared the difference of the wind regime between new meteorological stations and old meteorological stations from December 2020 to November 2021,and discussed the reasons for the discrepancy.The results showed that sandy and non-sandy areas differed significantly regarding the mean velocity(8.3(±0.3)versus 7.7(±0.3)m/s,respectively),frequency(12.9%(±6.2%)versus 2.9%(±1.9%),respectively),and dominant direction(nearly east or west versus nearly north or south,respectively)of sand-driving winds,drift potential(168.1(±77.3)versus 24.0(±17.9)VU(where VU is the vector unit),respectively),resultant drift potential(92.3(±78.5)versus 8.7(±9.2)VU,respectively),and resultant drift direction(nearly westward or eastward versus nearly southward or northward,respectively).This indicated an obvious spatial variation in the wind regime between sandy and non-sandy areas and suggested that there exist problems when using wind velocity data from non-sandy areas to evaluate the wind regime in sandy areas.The wind regime between sandy and non-sandy areas differed due to the differences in topography,heat flows,and their coupling with underlying surface,thereby affecting the local atmospheric circulation.Affected by large-scale circulations(westerly jet and Indian monsoon systems),both sandy and non-sandy areas showed similar seasonal variations in their respective wind regime.These findings provide a credible reference for re-understanding the wind regime and scientific wind-sand control in the middle reaches of the Yarlung Zangbo River Valley.

Distribution of winter-spring snow over the Tibetan Plateau and its relationship with summer precipitationin Yangtze River

The distribution of winter-spring snow cover over the Tibetan Plateau （TP） and its relationship with summer precipitation in the middle and lower reaches of Yangtze River Valley （MLYRV） during 2003-2013 have been investigated with the moderate-resolution imaging spectrometer （MODIS） Terra data （MOD10A2） and precipitation observations. Results show that snow cover percentage （SCP） remains approximately 20% in winter and spring then tails off to below 5% with warmer temperature and snow melt in summer. The lower and highest percentages present a declining tendency while the middle SCP exhibits an opposite variation. The maximum value appears from the middle of October to March and the minimum emerges from July to August. The annual and winter-spring SCPs present a decreasing tendency. Snow cover is mainly situated in the periphery of the plateau and mountainous regions, and less snow in the interior of the plateau, basin and valley areas in view of snow cover frequency （SCF） over the TP. Whatever annual or winter-spring snow cover, they all have remarkable declining tendency during 2003-2013, and annual snow cover presents a decreasing trend in the interior of the TP and increasing trend in the periphery of the TP. Hie multi-year averaged eight-day SCP is negatively related to mean precipitation in the MLYRV. Spring SCP is negatively related to summer precipitation while winter SCP is positively related to summer precipitation in most parts of the MLYRV. Hence, the influence of winter snow cover on precipitation is much more significant than that in spring on the basis of correlation analysis. The oscillation of SCF from southeast to northwest over the TP corresponds well to the beginning,development and cessation of the rain belt in eastern China.

Comparison of precipitation products to observations in Tibet during the rainy season

Precipitation is an important component of global water and energy transport and a major aspect of climate change. Due to the scarcity of meteorological observations, the precipitation climate over Tibet has been insufficiently documented. In this study, the distribution of precipitation during the rainy season over Tibet from 1980 to 2013 is described on monthly to annual time scales with meteorological observations. Furthermore, four precipitation products are compared to observations over Tibet. These datasets include products derived from the Asian Precipitation-Highly-Resolved Observational Data(APHRO), the Global Precipitation Climatology Centre(GPCC), the University of Delaware(UDel), and the China Meteorological Administration(CMA). The error, relative error, standard deviation, root-mean-square error, correlations and trends between these products for the same period are analyzed with in situ precipitation during the rainy season from May to September. The results indicate that these datasets can broadly capture the temporal and spatial precipitation distribution over Tibet. The precipitation gradually increases from northwest to southeast. The spatial precipitation in GPCC and CMA are similar and positively correlated to observations. Areas with the largest deviations are located in southwestern Tibet along the Himalayas. The APHRO product underestimates, while the UDel, GPCC, and CMA datasets overestimates precipitation on the basis of monthly and inter-annual variation. The biases in GPCC and CMA are smaller than those in APHRO and UDel with a mean relative error lower than 10% during the same periods. The linear trend of precipitation indicates that the increase in precipitation has accelerated extensively during the last 30 years in most regions of Tibet. The CMA generally achieves the best performance of these four precipitation products. Data uncertainty in Tibet might be caused by the low density of stations, complex topography between the grid points and stations, and the interpolation methods, which can also produce an obvious difference between the gridded data and observations.

Evaluation of the Climate Prediction System CMA-CPSv3 on Performances of Precipitation and Temperature Prediction over the Tibetan Plateau

In order to evaluate the prediction performances of the climate prediction system developed by the China Meteorological Administration (CMA-CPSv3) over the Tibetan Plateau region, the precipitation and temperature predicted by CMA-CPSv3 at different lead time was evaluated for the period of 2001-2023, by comparing with observations—the monthly precipitation of the CMAP and 2 m temperature data of the NCEP/DOE reanalysis data. The main conclusions were as follows: 1) the forecast skill of the model is very sensitive to the initial conditions and value, and the model forecast capability decreases rapidly as the lead time is extended. 2) CPSv3 performed well in capturing the spatial distribution of precipitation over Tibet in January, August, October, November and December at 0-month lead, and the forecast skill is relatively poor in March and April. CPSv3 has better performance in the east-central part of the land in January, in the central and western part of the region in March, in the whole region in April, in the northern part of Nagchu, northern part of Chamdo and central part of Shigatse in July, in the eastern part of Chamdo, northern part of Nagchu and northern part of Ali in August, in the whole region in September, and in the cities of Shigatse and Shannan in November. 3) At each lead time, the forecast skill for 2-m temperatures was higher than that for precipitation. For 2-m temperature, CPSv3 performed best in January, May, July, August, September, October, and December, while performing relatively poor in March, April, and November. Specifically, the prediction skill is higher in January and December for most of the regions, for Shigatse and Ali in May, for southern Shannan in July, and for northern Nagchu and southern Shannan in August, and there is some prediction skill in March, April and October, while CPSv3 performed poorly in November.

Regionalization and the Method for Risk Grading for Flash Flood Disaster in Tibet Region

Flash flood is one of the major meteorological disasters on the Tibet Plateau (TP). Flash flood risk regionalization based on the theory of flash flood occurrence risk is the essential basis for relative risk management. The flash flood risk regionalization and the high-resolution grid mountain flood risk level in TP is carried out by using ArcGIS with the indicators of rainfall, days of heavy rain, vegetation cover, slope, relative elevation difference, river network density, population density, average GDP and traffic density. The areas with high mountain flood risk are mainly located in the middle and downstream of Yarlung, the Nujiang River Valley, the Jinsha River and Lancang River Basin. Besides, the results of flash flood disaster risk regionalization were tested by using historical flash flood disaster data and calamity census data. The disasters occurred in high-risk and sub-high-risk regions are accounted for 73%. Flash floods that cause casualties and economic losses of more than 100,000 CNY (Chinese Yuan) occurred in high-risk areas. Flash flood risk assessment may provide reference for the prevention and control of geological disasters in TP, improve disaster prevention and mitigation capabilities, reduce the hazards of flash floods to social development.