The data set includes annual mass balance of Naimona’nyi glacier (northern branch) from 2008 to 2018, daily meteorological data at two automatic meteorological stations (AWSs) near the glacier from 2011 to 2018 and monthly air temperature and relative humidity on the glacier from 2018 to 2019. In the end of September or early October for each year , the stake heights and snow-pit features (snow layer density and stratigraphy) are manually measured to derive the annual point mass balance. Then the glacier-wide mass balance was then calculated （Please to see the reference). Two automatic weather stations (AWSs, Campbell company) were installed near the Naimona’nyi Glacier. AWS1, at 5543 m a. s.l., recorded meteorological variables from October 2011 at half hourly resolution, including air temperature (℃), relative humidity (%), and downward shortwave radiation (W m-2) . AWS2 was installed at 5950 m a.s.l. in October 2010 at hourly resolution and recorded wind speed (m/s), air pressure (hPa), precipitation (mm). Data quality: the quality of the original data is better, less missing. Firstly, the abnormal data in the original records are removed, and then the daily values of these parameters are calculated. Two probes (Hobo MX2301) which record air temperature and relative humidity was installed on the glacier at half hour resolution since October 2018. The observed meteorological data was calculated as monthly values. The data is stored in Excel file. It can be used by researchers for studying the changes in climate, hydrology, glaciers, etc.
ZHAO Huabiao
The near surface atmospheric forcing and surface state dataset of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.
PAN Xiaoduo
The field observation platform of the Tibetan Plateau is the forefront of scientific observation and research on the Tibetan Plateau. The land surface processes and environmental changes based comprehensive observation of the land-boundary layer in the Tibetan Plateau provides valuable data for the study of the mechanism of the land-atmosphere interaction on the Tibetan Plateau and its effects. This dataset integrates the 2005-2016 hourly atmospheric, soil hydrothermal and turbulent fluxes observations of Qomolangma Atmospheric and Environmental Observation and Research Station, Chinese Academy of Sciences (QOMS/CAS), Southeast Tibet Observation and Research Station for the Alpine Environment, CAS (SETORS), the BJ site of Nagqu Station of Plateau Climate and Environment, CAS (NPCE-BJ), Nam Co Monitoring and Research Station for Multisphere Interactions, CAS (NAMORS), Ngari Desert Observation and Research Station, CAS (NADORS), Muztagh Ata Westerly Observation and Research Station, CAS (MAWORS). It contains gradient observation data composed of multi-layer wind speed and direction, temperature, humidity, air pressure and precipitation data, four-component radiation data, multi-layer soil temperature and humidity and soil heat flux data, and turbulence data composed of sensible heat flux, latent heat flux and carbon dioxide flux. These data can be widely used in the analysis of the characteristics of meteorological elements on the Tibetan Plaetau, the evaluation of remote sensing products and development of the remote sensing retrieval algorithms, and the evaluation and development of numerical models.
MA Yaoming
This data set includes the monthly average actual evapotranspiration of the Tibet Plateau from 2001 to 2018. The data set is based on the satellite remote sensing data (MODIS) and reanalysis meteorological data (CMFD), and is calculated by the surface energy balance system model (SEBS). In the process of calculating the turbulent flux, the sub-grid scale topography drag parameterization scheme is introduced to improve the simulation of sensible and latent heat fluxes. In addition, the evapotranspiration of the model is verified by the observation data of six turbulence flux stations on the Tibetan Plateau, which shows high accuracy. The data set can be used to study the characteristics of land-atmosphere interaction and the water cycle in the Tibetan Plateau.
HAN Cunbo, MA Yaoming, WANG Binbin, ZHONG Lei, MA Weiqiang*, CHEN Xuelong, SU Zhongbo
Terrestrial actual evapotranspiration (ETa) is an important component of terrestrial ecosystems because it links the hydrological, energy, and carbon cycles. However, accurately monitoring and understanding the spatial and temporal variability of ETa over the Tibetan Plateau (TP) remains very difficult. Here, the multiyear (2000-2018) monthly ETa on the TP was estimated using the MOD16-STM model supported by datasets of soil properties, meteorological conditions, and remote sensing. The estimated ETa correlates very well with measurements from 9 flux towers, with low root mean square errors (average RMSE = 13.48 mm/month) and mean bias (average MB = 2.85 mm/month), and strong correlation coefficients (R = 0.88) and the index of agreement values (IOA = 0.92). The spatially averaged ETa of the entire TP and the eastern TP (Lon > 90°E) increased significantly, at rates of 1.34 mm/year (p < 0.05) and 2.84 mm/year (p < 0.05) from 2000 to 2018, while no pronounced trend was detected on the western TP (Lon < 90°E). The spatial distribution of ETa and its components were heterogeneous, decreasing from the southeastern to northwestern TP. ETa showed a significantly increasing trend in the eastern TP, and a significant decreasing trend throughout the year in the southwestern TP, particularly in winter and spring. Soil evaporation (Es) accounted for more than 84% of ETa and the spatial distribution of temporal trends was similar to that of ETa over the TP. The amplitudes and rates of variations in ETa were greatest in spring and summer. The multi-year averaged annual terrestrial ETa (over an area of 2444.18×103 km2) was 376.91±13.13 mm/year, equivalent to a volume of 976.52±35.7 km3/year. The average annual evapotranspirated water volume over the whole TP (including all plateau lakes, with an area of 2539.49×103 km2) was about 1028.22±37.8 km3/year. This new estimated ETa dataset is useful for investigating the hydrological impacts of land cover change and will help with better management of watershed water resources across the TP.
MA Yaoming, CHEN Xuelong,
The SZIsnow dataset was calculated based on systematic physical fields from the Global Land Data Assimilation System version 2 (GLDAS-2) with the Noah land surface model. This SZIsnow dataset considers different physical water-energy processes, especially snow processes. The evaluation shows the dataset is capable of investigating different types of droughts across different timescales. The assessment also indicates that the dataset has an adequate performance to capture droughts across different spatial scales. The consideration of snow processes improved the capability of SZIsnow, and the improvement is evident over snow-covered areas (e.g., Arctic region) and high-altitude areas (e.g., Tibet Plateau). Moreover, the analysis also implies that SZIsnow dataset is able to well capture the large-scale drought events across the world. This drought dataset has high application potential for monitoring, assessing, and supplying information of drought, and also can serve as a valuable resource for drought studies.
WU Pute, TIAN Lei, ZHANG Baoqing
The matching data of water and soil resources in the Qinghai Tibet Plateau, the potential evapotranspiration data calculated by Penman formula from the site meteorological data (2008-2016, national meteorological data sharing network), the evapotranspiration under the existing land use according to the influence coefficient of underlying surface, and the rainfall data obtained by interpolation from the site rainfall data in the meteorological data, are used to calculate the evapotranspiration under the existing land use according to the different land types of land use According to the difference, the matching coefficient of water and soil resources is obtained. The difference between the actual rainfall and the water demand under the existing land use conditions reflects the matching of water and soil resources. The larger the value is, the better the matching is. The spatial distribution of the matching of soil and water resources can pave the way for further understanding of the agricultural and animal husbandry resources in the Qinghai Tibet Plateau.
DONG Lingxiao
The stable oxygen isotope ratio (δ 18O) in precipitation is a comprehensive tracer of global atmospheric processes. Since the 1990s, efforts have been made to study the isotopic composition of precipitation at more than 20 stations located on the TP of the Tibetan Plateau, which are located at the air mass intersection between westerlies and monsoons. In this paper, we establish a database of monthly precipitation δ 18O over the Tibetan Plateau and use different models to evaluate the climate control of precipitation δ 18O over TP. The spatiotemporal pattern of precipitation δ 18O and its relationship with temperature and precipitation reveal three different domains, which are respectively related to westerly wind (North TP), Indian monsoon (South TP) and their transition.
GAO Jing
1)Data content (including elements and meanings): surface meteorological observation data product of TP in 1979-2016 2)Data source and processing method: In .tif format, can be opened and analysed in arcgis. 3)Data quality description: daily resolution 4)Data application results and prospects: Based on the long-term observation data of the 17 stations of HORN, establish a series of data series of meteorological, hydrological and ecological elements in the Pan-Earth region; Strengthen observation and sample and sample verification, and complete the inversion of meteorological elements, lake water quantity and water quality, aboveground vegetation biomass, glacier and frozen soil changes; based on Internet of Things technology, develop multi-station networked meteorological, hydrological, The ecological data management platform realizes real-time acquisition and remote control and sharing of networked data.
ZHU Liping,
The data set collects the long-term monitoring data on atmosphere, hydrology and soil from the Integrated Observation and Research Station of Multisphere in Namco, the Integrated Observation and Research Station of Atmosphere and Environment in Mt. Qomolangma, and the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The data have three resolutions, which include 0.1 seconds, 10 minutes, 30 minutes, and 24 hours. The temperature, humidity and pressure sensors used in the field atmospheric boundary layer tower (PBL) were provided by Vaisala of Finland. The wind speed and direction sensor was provided by MetOne of the United States. The radiation sensor was provided by APPLEY of the United States and EKO of Japan. Gas analysis instrument was provided by Licor of the United States, and the soil moisture content, ultrasonic anemometer and data collector were provided by CAMPBELL of the United States. The observing system is maintained by professionals on a regular basis (2-3 times a year), the sensors are calibrated and replaced, and the collected data are downloaded and reorganized to meet the meteorological observation specifications of the National Weather Service and the World Meteorological Organization (WMO). The data set was processed by forming a time continuous sequence after the raw data were quality-controlled, and the quality control included eliminating the systematic error caused by missing data and sensor failure.
MA Yaoming
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