The dataset of survey at the poplar sampling plot was obtained in the Linze station foci experimental area. Observation items included: (1) soil profile moisture and temperature (0-5cm, 0-5cm, 10-20cm, 20-40cm and 40-60cm) with photos measured twice by the cutting ring method (50cm^3, each layer), once by ML2X Soil Moisture Tachometer and the probe thermometer (15cm, twice each layer) on Jun. 3, 2008. Data were archived as Excel files. (2) shallow layer soil moisture (0-5cm) measured once by the cutting ring method (50cm^3, once each point) and twice by ML2X Soil Moisture Tachometer on Jun. 4, 2008. 13 points were selected and data were archived as Excel files. (3) LAI by TRAC on Jul. 20, 2008. Data were archived as Excel files. (4) roughness measured by the roughness plate together with the digital camera. 18 points were selected and data were archived in JPG format format. (5) forest investigation of Populus gansuensis from Jun. 5-13, 2008: coordinates, the diameter at breast height and the crown size by the measuring tape, full height by TruPulse200. 408 trees were selected and data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.

On 2 August 2012, Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS) carried by the Harbin Y-12 aircraft was used in a visible near Infrared thermal Dual-mode airborne remote sensing experiment, which is located in the artificial oasis eco-hydrology experimental area (30×30 km). WIDAS includes a CCD camera with a spatial resolution of 0.26 m, a visible near Infrared multispectral camera with five bands scanner (an maximum observation angle 48° and spatial resolution 1.3 m), and a thermal image camera with a spatial resolution of 6.3 m. The CCD camera data are recorded in DN values processed by mosaic and orthorectification.

The data set includes the trends of annual average temperature and rainfall changes at the three meteorological stations in the permafrost section of the Qinghai-Tibet Engineering Corridor over the past 50 years. According to the recorded data, the annual average temperature is experiencing a gradually rising process. The annual average temperature change over the past 56 years in Wudaoliang and Tuotuohe has a good correlation (r2=0.83). In 1957, the average annual temperatures of Wudaoliang and Tuotuohe were -6.6 °C and -5.1 °C, respectively. By 2012, the temperatures of the two stations were -4.6 and -3.1 °C, and the total temperature has risen by approximately 2 °C. The annual average temperature rises by 0.03-0.04 °C. The annual average temperature changes over the past 47 years in Wudaoliang and Anduo also have a good correlation (r2=0.84). In 1966, the average annual temperature in Anduo was -3.0 °C. By 2012, the temperature has risen to -1.8 °C, corresponding to a total temperature rise of approximately 1.2 °C and an annual average temperature rise of 0.02-0.03 °C. The annual average temperature in Wudaoliang and Tuotuohe rose slightly faster than that in Anduo. However, the change in rainfall was more volatile than that of temperature. The correlation between the rainfall change in Wudaoliang and Tuotuohe over the past 56 years is relatively poor (r2=0.60). In 1957, the annual rainfall amounts in Wudaoliang and Tuotuohe were 302 and 309 mm, respectively. By 2012, the annual rainfall amounts at the two stations were 426 and 332 mm. Thus, the rainfall in Wudaoliang had increased by 124 mm, with an annual rainfall increase of approximately 2 mm. In contrast, the annual rainfall in Tuotuohe only increased by 0.4 mm. The correlation between the rainfall change in Wudaoliang and Anduo over the past 47 years is also poor (r2=0.35). In 1966, and 2012, the annual average rainfall amounts in Anduo were 354 and 404 mm. The total increase was approximately 50 mm, and the annual average increase was 1 mm. The annual rainfall in Wudaoliang increased the fastest. The observation data from the three meteorological stations reveal climate changes in the permafrost sections of the Qinghai-Tibet Engineering Corridor. Judging from the overall trend of temperature and rainfall changes, the temperature in the northern and central parts of the corridor has increased rapidly over the past 50 years, exceeding the global average of 0.02 °C/a (IPCC). The rainfall increase in the northern part of the corridor is also obvious, especially the rate of rainfall increase at the Wudaoliang meteorological station. Increases in both temperature and rainfall have a great impact on accelerating the spatial variation in permafrost, and they are the leading cause of permafrost degradation on the Tibetan Plateau.

The dataset of Antarctic mountains(1:1000000) includes vector spatial distribution data and some related attribute data: Name, Country name of the mountains , Country abbreviation, Latitude、 Longitude The data comes from the ADC World Map（1:1000000） global dataset, the data is topological, and it is the comprehensive, latest and seamless geographic digital data. The world map coordinate system is the latitude and longitude, WGS84 datum, and the Antarctic data set is the South Pole Stereographic.

The data set contains the observation data of meteorological elements from the Huyanglin Station, which is located along the lower reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2015 to December 31, 2015. The station is located in Sidaoqiao, Dalaihubu Town, Ejina Banner, Inner Mongolia, the underlying surface is Populus euphratica forest and Tamarisk. The latitude and longitude of the observation point is 101.1239E, 41.9932N, and the altitude is 876m. The air temperature and relative humidity sensor s are erected 28 meters above the ground, facing North; the wind speed sensor is set at 28m, facing north; the four-component radiometer is installed 24 meters above the ground, facing South; two infrared thermometers are installed 24 meters above the ground, facing South, and the probe orientation is vertical downward; two photosynthetically active radiometers are installed 24 meters above the ground, facing South, and the two probes are vertically upward and downward respectively; the soil temperature probes are buried respectively at 0cm on the ground surface, 2cm and 4cm under the ground, they are located 2 meters from the meteorological tower in the North. The soil moisture sensors are buried 2cm and 4cm under the ground, 2 meters from the meteorological tower in the South. The soil heat flow boards (3 pieces) are buried 6cm under the ground, 2 meters from the meteorological tower in the South. Observed items include: air temperature and humidity (Ta_28m, RH_28m) (unit: Celsius, percentage), wind speed (WS_28m) (unit: m/s), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watt / square meter), surface radiation temperature (IRT_1, IRT_2) (unit: Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts / square meter), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm) (unit : Celsius), soil moisture (Ms_2cm, Ms_4cm) (unit: volumetric water content, percentage), up and down photosynthetically active radiation (PAR_up, PAR_down) (unit: micromoles / square meter second). Processing and quality control of observation data: (1) Ensure 144 data per day (every 10 minutes), if there is missing data, it is marked as -6999. Due to instrument adjustment, data between April 22 to April 27 of 2015 is missing. Soil heat flux data between June 19 to September 5 is missing due to sensor failure. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2015-9-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Sidaoqiao populus forest station between 10 July, 2013, and 31 December, 2013. The site (101.124° E, 41.993° N) was located on a populous and tamarix forest (Populus euphratica Olivier. and Tamarix chinensis Lour.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 876 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 28 m, north), wind speed profile (010C; 28 m, north), two four-component radiometer (CNR4; 6 m and 24 m, south), two infrared temperature sensors (SI-111; 24 m, south, vertically downward), two photosynthetically active radiation (PQS-1; 24 m, south, one vertically upward and one vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), and soil temperature profile (109ss-L; 0, -0.02 and -0.04 m). The observations included the following: air temperature and humidity (Ta_28 m; RH_28 m) (℃ and %, respectively), wind speed (Ws_28 m) (m/s), 24 m four-component radiation (DR_1, incoming shortwave radiation; UR_1, outgoing shortwave radiation; DLR_Cor_1, incoming longwave radiation; ULR_Cor_1, outgoing longwave radiation; Rn_2, net radiation) (W/m^2), 6 m four-component radiation (DR_2, incoming shortwave radiation; UR_2, outgoing shortwave radiation; DLR_Cor_2, incoming longwave radiation; ULR_Cor_2, outgoing longwave radiation; Rn_2, net radiation) (W/m^2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), and soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm and Ts_100 cm) (℃). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Data during 16 July, 2013 and 17 July, 2013 were missing during the malfunction of datalogger. The soil heat flux (G3) was missing during 20 November, 2013 and 8 December, 2013 because the wire was break by the sheep. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.

The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in the Linze grassland foci experimental area on Jul. 11, 2008. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:26 BJT. Observations were carried out in the reed plot A, the saline plots B and C, the alfalfa plot D and the barley plot E, which were divided into 6×6 subsites, with each one spanning a 120×120 m2 plot. Soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by using the cutting ring, the mean soil temperature from 0-5cm by the probe thermometer, and the canopy temperature and the land surface temperature by the hand-held infrared thermometer were measured in A, B and C; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the canopy temperature and the land surface temperature by the hand-held infrared thermometer in D and E. Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.

The dataset of airborne LiDAR mission at the super site in the Dayekou watershed flight zone on Jun. 23, 2008 included peak pulse data (*.LAS), full waveform data (.lgc), CCD photos, DEM, DSM and DOM. The flight routes were as follows: {| ! flight route ! startpoint lat ! startpoint lon ! endpoint lat ! endpoint lon ! altitude (m) ! length (km) ! photos |- | 1 || 38°31′59.71″ || 100°14′54.02″ || 38°31′43.04″ || 100°15′44.28″ || 3550 || 1.3 || 7 |- | 2 || 38°32′01.21″ || 100°14′54.82″ || 38°31′44.53″ || 100°15′45.08″ || 3550 || 1.3 || 7 |- | 3 || 38°32′02.70″ || 100°14′55.62″ || 38°31′46.03″ || 100°15′45.88″ || 3550 || 1.3 || 7 |- | 4 || 38°32′04.20″ || 100°14′56.42″ || 38°31′47.52″ || 100°15′46.69″ || 3550 || 1.3 || 7 |- | 5 || 38°32′05.69″ || 100°14′57.23″ || 38°31′49.01″ || 100°15′47.49″ || 3550 || 1.3 || 6 |}

Arctic 1:100,000 airport distribution data set includes vector space data and related attribute data of airports (Arctic_Airport) and airport runway (Arctic_Airport_runways) in the arctic range: airport Name, airport country Name, airport country abbreviation (CNTRY_CODE), LATITUDE and LONGITUDE. The data comes from the 1:100,000 ADC_WorldMap global data set, which is a comprehensive, up-to-date and seamless geographic digital data after the data quality inspection of topology, warehousing and other data. The world map coordinate system is latitude and longitude, WGS84 datum surface, and the arctic data set is the special projection parameter for the arctic (North_Pole_Stereographic).

This dataset contains the automatic weather station (AWS) measurements from site No.3 in the flux observation matrix from 3 June to 18 September, 2012. The site (100.37634° E, 38.89053° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1543.05 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP155; 5 m, towards north), rain gauge (TR525; 10 m), wind speed (010C; 10 m, towards north), a four-component radiometer (NR01; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (AV-10T; 0, -0.02, -0.04 m), soil moisture profile (CS616; -0.02, -0.04 m), and soil heat flux (HFP01; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), precipitation (rain, mm), wind speed (Ws_10 m, m/s), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation; W/m^2), infrared temperature (IRT_1 and IR_2, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, ℃), soil moisture profile (Ms_2 cm, Ms_4 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

This dataset contains data on river water level and flow velocity at No.8 in the intensive runoff observation in the middle reaches of Heihe River runoff from January 1, 2014 to December 31, 2014. The observation point is located at Heihe Bridge, Gaotai County, Zhangye City, Gansu Province. The riverbed is sediment and the section is stable. The latitude and longitude of the observation point is N39°23'22.93", N 99°49'37.29", the altitude is 1347 meters, and the river channel width is 210 meters. The water level observation is measured by SR50 ultrasonic range finder with a frequency of 30 minutes. The data  declaration includes the following two parts: Water level observation, observation frequency 30 minutes, unit (cm); data covering time period from January 1, 2014 to December 31, 2014; Flow observation, unit (m3); monitoring flow and obtaining water level flow curve according to different water levels. The process of the runoff changing is obtained by observing the water level process. The No. 8 point-Gaotaiqiao section only monitored the water level because the water body of the wetland park basically stopped flowing. The missing data is uniformly represented by the string -6999. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to He et al. (2016).

This dataset contains the flux measurements from the No.13 site eddy covariance system (EC) in the flux observation matrix from 27 May to 20 September, 2012. The site (100.37852° E, 38.86074° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1550.73 m. The EC was installed at a height of 5 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500A) was 0.18 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. Moreover, the observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day; the missing data were replaced with -6999. Moreover, suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.