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.
The basic data set of water resources research of Southeast Asian countries and Lancang Mekong basin (1901-2010) collected and sorted out the main hydrometeorological data of Southeast Asian countries and Lancang Mekong basin, including precipitation, average temperature, maximum temperature, minimum temperature, water vapor pressure, etc. the data came from CRU TS v. 4.03 (clinical research unit time series version 4.03), which is widely used in the whole world The format is NC, the time resolution is month by month, and the time length is from January 1901 to December 2018. Hydrological data includes surface runoff and underground runoff simulated by the hydrological model. The data comes from GLDAS (Global Land Data Assimilation System). The data format is NC, the time resolution is month by month, and the time length is from January 1979 to February 2019.
1) Data content (including elements and significance): 21 stations (Southeast Tibet station, Namucuo station, Zhufeng station, mustag station, Ali station, Naqu station, Shuanghu station, Geermu station, Tianshan station, Qilianshan station, Ruoergai station (northwest courtyard), Yulong Xueshan station, Naqu station (hanhansuo), Haibei Station, Sanjiangyuan station, Shenzha station, gonggashan station, Ruoergai station（ Chengdu Institute of biology, Naqu station (Institute of Geography), Lhasa station, Qinghai Lake Station) 2018 Qinghai Tibet Plateau meteorological observation data set (temperature, precipitation, wind direction and speed, relative humidity, air pressure, radiation and evaporation) 2) Data source and processing method: field observation at Excel stations in 21 formats 3) Data quality description: daily resolution of the site 4) Data application results and prospects: Based on long-term observation data of various cold stations in the Alpine Network and overseas stations in the pan-third pole region, a series of datasets of meteorological, hydrological and ecological elements in the pan-third pole region were established; Strengthen observation and sample site and sample point verification, complete the inversion of meteorological elements, lake water quantity and quality, above-ground vegetation biomass, glacial frozen soil change and other data products; based on the Internet of Things technology, develop and establish multi-station networked meteorological, hydrological, Ecological data management platform, real-time acquisition and remote control and sharing of networked data.
This dataset includes the monthly precipitation data with 0.0083333 arc degree (~1km) for China from Jan 1901 to Dec 2017. The data form belongs to NETCDF, namely .nc file. The unit of the data is 0.1 mm. The dataset was spatially downscaled from CRU TS v4.02 with WorldClim datasets based on Delta downscaling method. The dataset was evaluated by 496 national weather stations across China, and the evaluation indicated that the downscaled dataset is reliable for the investigations related to climate change across China. The dataset covers the main land area of China, including Hong Kong, Macao and Taiwan regions, and excluding islands and reefs in South China Sea.
The data include daily precipitation (Precip) amount and daily mean near-surface air temperature (T2M) over the Pan Third Pole region. The data is downscaled by using the Weather Research and Forecasting (WRF) model (3.7.1). The boundary and initial condition come from the fifth-generation global reanalysis product by the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA5. The seasonal cycle and summer mean of precipitation over Tibet is well reproduced in comparison to the in situ observations.
This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since January 2014. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification. Please refer to "waternet data document 20141206. Docx" for details
This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since the end of June 2013. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification.
The meteorological field is located in 2700m grassland in the Pailougou watershed of Qilian Mountain. The date of data recording is from May 2013 to September 2013, including air humidity at 1.5m, air temperature at 3.0m, atmospheric pressure at 2.8m, precipitation at 1.3m, wind speed at 2.2m and total solar radiation at 3.1m. The units are%, ℃, PA, m, m/s and W·m-2, respectively.
This data set is the precipitation characteristic data in the precipitation interception data of alpine shrub in hulugou basin in the upper reaches of Heihe River in 2012. The observation date is from October 2, 2011 to September 24, 2012. The observation contents include precipitation, precipitation duration, precipitation intensity and frequency of throughfall. The observation data are recorded by self recording rain gauge and artificial rain gauge.
The distributed eco hydrological model needs high-precision precipitation spatial distribution information as input. Due to the scarcity of stations, the station interpolation precipitation can not reflect the spatial distribution of precipitation in Heihe mountain area. The regional climate model (RCM) simulation results provide the information of precipitation elevation relationship at different locations. The relationship is corrected according to the observed precipitation elevation gradient of hulugou watershed, and the precipitation elevation gradient at different locations of the watershed is obtained. Based on the gradient and the multi-year average value of precipitation observed at the station, the precipitation climate background field is established to represent the multi-year average spatial distribution of precipitation in the basin. Then, based on the daily precipitation observation data of 16 meteorological stations and 25 hydrological stations, and the precipitation spatial distribution information provided by the precipitation climate background field, the daily grid precipitation data is obtained by interpolation. The interpolation year of this data is 1960-2014, the spatial interpolation precision is 3-km, and the time precision is day by day data (the daily period is from 8:00 a.m. to 8:00 a.m. the next day). The results show that the interpolation precipitation is reliable. The data is stored in ASCII file. The file name of each file is in the form of precyyyymmdd.asc. Yyyy is the year, mm is the month and DD is the day. Each ASCII file represents the grid precipitation data of the day, in mm.