Pan-third-polar environmental change and green silk road construction

Brief Introduction: Pan-third-polar environmental change and green silk road construction

Number of Datasets: 1212

  • Daily 0.05°×0.05° land surface soil moisture dataset of Qilian Mountain area  (2019,SMHiRes,V2)

    Daily 0.05°×0.05° land surface soil moisture dataset of Qilian Mountain area (2019,SMHiRes,V2)

    This dataset contains daily 0.05°×0.05° land surface soil moisture products in Qilian Mountain Area in 2019. The dataset was produced by utilizing the optimized wavelet-coupled-RF downscaling model (RF-OWCM) to downscale the “AMSR-E and AMSR2 TB-based SMAP Time-Expanded Daily 0.25°×0.25° Land Surface Soil Moisture Dataset in Qilian Mountain Area (SMsmapTE, V1)”. The auxiliary datasets participating in the downscaling model include GLASS Albedo/LAI/FVC, Thermal and Reanalysis Integrating Medium-resolution Spatial-seamless LST – Tibetan Plateau (TRIMS LST-TP) by Ji Zhou and Lat/Lon information.

    2021-06-04 334 13

  • Cold and Arid Research Network of Lanzhou University (an  observation system of Meteorological elements gradient of Dunhuang Station, 2020)

    Cold and Arid Research Network of Lanzhou University (an observation system of Meteorological elements gradient of Dunhuang Station, 2020)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Dunhuang Station from January 1 to December 31, 2020. The site (93.708° E, 40.348° N) was located on a wetland in the Dunhuang west lake, Gansu Province. The elevation is 990 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4m and 8 m, towards north), wind speed and direction profile (windsonic; 4m and 8 m, towards north), air pressure (1 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), soil heat flux (-0.05 and -0.1m ), soil soil temperature/ moisture/ electrical conductivity profile (below the vegetation in the south of tower, -0.05 and -0.2 m), photosynthetically active radiation (4 m, towards south), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_4 m, Ta_8 m; RH_2 m, RH_4 m, RH_8 m) (℃ and %, respectively), wind speed (Ws_4 m, Ws_8 m) (m/s), wind direction (WD_4 m, WD_8 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_0.05m, Ts_0.2m) (℃), soil moisture (Ms_0.05m, Ms_0.2m) (%, volumetric water content), soil conductivity (Ec_0.05m, Ec_0.2m)(μs/cm), sun time(h). 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 and missing records were denoted by -6999.. (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.

    2021-06-04 308 23

  • Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Minqin Station, 2020)

    Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Minqin Station, 2020)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Minqin Station from August 16 to December 31, 2020. The site (103.668E, 39.208N) was located on a alpine meadow in the Wuwei, Gansu Province. The elevation is 1020 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4 and 8 m, towards north), wind speed and direction profile (windsonic; 4, and 8 m, towards north), air pressure (1.5 m), rain gauge (4 m), four-component radiometer (4 m, towards south), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil soil temperature/ moisture/ electrical conductivity profile (-0.2 and -0.4 m in south of tower), sunshine duration sensor (4 m, towards south). The observations included the following: air temperature and humidity (Ta_4 m, and Ta_8 m; RH_4 m, and RH_8 m) (℃ and %, respectively), wind speed (Ws_4 m, and Ws_8 m) (m/s), wind direction (WD_4 m, and WD_8 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s/m^2)), soil heat flux (Gs_5 cm, Gs_10cm) (W/m^2), soil temperature (Ts_10 cm, Ts_20 cm) (℃), soil moisture (Ms_10 cm, Ms_20 cm) (%, volumetric water content), soil water potential (SWP_10cm , SWP_20cm)(kpa) , soil conductivity (Ec_10cm, Ec_20cm)(μs/cm), sun time (h). 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 and missing records 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.

    2021-06-04 276 32

  • Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Xiyinghe Station, 2020)

    Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Xiyinghe Station, 2020)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Xiyinghe Station from January 1 to December 31, 2020. The site (101.853E, 37.561N) was located on a alpine meadow in the Menyuan, Qinghai Province. The elevation is 3639 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (2, 4, and 8 m, towards north), wind speed and direction profile (windsonic; 2, 4, and 8 m, towards north), air pressure (1.5 m), rain gauge (4 m), four-component radiometer (4 m, towards south), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil soil temperature/ moisture/ electrical conductivity profile (-0.2 and -0.4 m in south of tower), sunshine duration sensor (4 m, towards south). The observations included the following: air temperature and humidity (Ta_2 m, Ta_4 m, and Ta_8 m; RH_2 m, RH_4 m, and RH_8 m) (℃ and %, respectively), wind speed (Ws_2 m, Ws_4 m, and Ws_8 m) (m/s), wind direction (WD_2 m, WD_4 m, and WD_8 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s/m^2)), soil heat flux (Gs_5 cm, Gs_10cm) (W/m^2), soil temperature (Ts_20 cm, Ts_40 cm) (℃), soil moisture (Ms_20 cm, Ms_40 cm) (%, volumetric water content), soil water potential (SWP_20cm , SWP_40cm)(kpa) , soil conductivity (Ec_20cm, Ec_40cm)(μs/cm), sun time (h). 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 and missing records 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.

    2021-06-04 319 36

  • Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Sidalong Station, 2020)

    Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Sidalong Station, 2020)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Sidalong Station from January 1 to April 12, 2020. The site (38.430°E, 99.931°N) was located on a forest in the Kangle Sunan, which is near Zhangye city, Gansu Province. The elevation is 3059 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (0.5, 3, 13, 24, and 48 m), wind speed and direction profile (windsonic; 0.5, 3, 13, 24, and 48 m), air pressure (1.5 m), rain gauge (24 m), infrared temperature sensors (4 m and 24m, vertically downward), photosynthetically active radiation (4 m and 24m), soil heat flux (-0.05 m and -0.1m), soil temperature/ moisture/ electrical conductivity profile -0.05, -0.1m, -0.2m, -0.4m and -0.6mr), four-component radiometer (24 m, towards south), sunshine duration sensor(24 m, towards south). The observations included the following: air temperature and humidity (Ta_0.5 m, Ta_3 m, Ta_13 m, Ta_24 m, and Ta_48 m; RH_0.5 m, RH_3 m, RH_13 m, RH_24 m, and RH_48 m) (℃ and %, respectively), wind speed (Ws_0.5 m, Ws_3 m, Ws_13 m, Ws_24 m, and Ws_48 m) (m/s), wind direction (WD_0.5 m, WD_3 m, WD_13 m, WD_24 m, and WD_48 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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_A, IRT_B) (℃), photosynthetically active radiation (PAR_A, PAR_B) (μmol/ (s m^2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_5 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, and Ts_60 cm) (℃), soil moisture (Ms_5 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, and Ms_60 cm) (%, volumetric water content),soil water potential (SWP_5cm, SWP_10cm, SWP_20cm, SWP_40cm, and SWP_60cm)(kpa), soil conductivity (Ec_5cm, Ec_10cm, Ec_20cm, Ec_40cm, and Ec_60cm)(μs/cm), sun time (h). 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 and missing records 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.

    2021-06-04 298 30

  • Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Suganhu Station, 2020)

    Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Suganhu Station, 2020)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Suganhu Station from November 27 to December 31, 2020. The site (93.708° E, 40.348° N) was located on a wetland in the Suganhu west lake, Gansu Province. The elevation is 990 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4m and 8 m, towards north), wind speed and direction profile (windsonic; 4m and 8 m, towards north), air pressure (1 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), soil heat flux (-0.05 and -0.1m ), soil soil temperature/ moisture/ electrical conductivity profile (below the vegetation in the south of tower, -0.05 and -0.2 m), photosynthetically active radiation (4 m, towards south), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_4 m, Ta_8 m; RH_4 m, RH_8 m) (℃ and %, respectively), wind speed (Ws_4 m, Ws_8 m) (m/s), wind direction (WD_4 m, WD_8 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_0.1m, Ts_0.2m, Ts_0.4m) (℃), soil moisture (Ms_0.1m, Ms_0.2m, Ms_0.4m) (%, volumetric water content), soil conductivity (Ec_0.1m, Ec_0.2m, Ec_0.4m)(μs/cm), sun time(h). 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 and missing records 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.

    2021-06-04 300 41

  • Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Linze Station, 2020)

    Cold and Arid Research Network of Lanzhou university (an observation system of Meteorological elements gradient of Linze Station, 2020)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Linze Station from January 1 to December 31, 2020. The site (100.060° E, 39.237° N) was located on a cropland (maize surface) in the Guzhai Xinghua, which is near Zhangye city, Gansu Province. The elevation is 1400 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4 and 8 m, towards north), wind speed and direction profile (windsonic; 4 and 8 m, towards north), air pressure (1 m), rain gauge (4 m), four-component radiometer (4 m, towards south), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (2 duplicates below the vegetation; -0.05 and -0.1m in south of tower), soil soil temperature/ moisture/ electrical conductivity profile (-0.2 and -0.4m), sunshine duration sensor (4 m, towards south). The observations included the following: air temperature and humidity (Ta_4 m, Ta_8 m; RH_3 m, RH_4 m, RH_8 m) (℃ and %, respectively), wind speed (Ws_4 m, Ws_8 m) (m/s), wind direction (WD_4 m, WD_8 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing long wave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), soil heat flux (Gs_5cm, Gs_10cm) (W/m^2), soil temperature (Ts_5 cm, Ts_10 cm) (℃), soil moisture (Ms_5 cm, Ms_10 cm) (%, volumetric water content), soil water potential(SWP_5cm, SWP_10cm), soil conductivity (Ec_5cm,Ec_10cm) (μs/cm), sun time(h). 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 and missing records were denoted by -6999.The precipitation and the air humidity data were rejected due to program error. (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.

    2021-06-04 263 16

  • Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (Cosmic-ray observation system of soil moisture of Daman Superstation, 2020)

    Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (Cosmic-ray observation system of soil moisture of Daman Superstation, 2020)

    This dataset includes data recorded by the Heihe integrated observatory network obtained from a Cosmic-ray Soil Moisture Observing System of soil moisture of Daman Superstation from January 1 to December 31, 2020. The site (100.372° E, 38.856° N) was located on a cropland (maize surface) in the Daman irrigation, which is near Zhangye city, Gansu Province. The elevation is 1556 m. The bottom of the probe was 0.5 m above the ground; the sampling interval was 1 hour. The raw COSMOS data include the following: battery (Batt, V), temperature (T, C), relative humidity (RH, %), air pressure (P, hPa), fast neutron counts (N1C, counts per hour), thermal neutron counts (N2C, counts per hour), sample time of fast neutrons (N1ET, s), and sample time of thermal neutrons (N2ET, s). The distributed data include the following variables: Date, Time, P, N1C, N1C_cor (corrected fast neutron counts) and VWC (volume soil moisture, %), which were processed as follows: 1) Data were removed and replaced by -6999 when (a) the battery voltage was less than 11.8 V, (b) the relative humidity was greater than 80% inside the probe box, (c) the counting data were not of one-hour duration and (d) neutron count differed from the previous value by more than 20%; 2) An air pressure correction was applied to the quality-controlled raw data according to the equation contained in the equipment manual; 3) After the quality control and corrections were applied, soil moisture was calculated using the equation in Zreda et al. (2012), where N0 is the neutron counts above dry soil and the other variables are fitted constants that define the shape of the calibration function. Here, the parameter N0 was calibrated using the in situ observed soil moisture by SoilNET within the footprint; 4) Based on the calibrated N0 and corrected N1C, the hourly soil moisture was computed using the equation from the equipment manual. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Zhu et al. (2015) for data processing) in the Citation section.

    2021-06-02 335 16

  • Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (Large aperture scintillometer of Sidaoqiao Superstation, 2020)

    Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (Large aperture scintillometer of Sidaoqiao Superstation, 2020)

    This dataset contains the flux measurements from the large aperture scintillometer (LAS) at Sidaoqiao Superstation in the Heihe integrated observatory network from January 1 to December 31 in 2020. There were BLS900, BLS450 and RR-RSS460 at Sidaoqiao Superstation. The north towers were set up with these instruments’ receivers and the south towers were transmitters. The site (north: 101.137° E, 42.008° N; south: 101.131° E, 41.987 N) was located in Ejinaqi, Inner Mongolia. The underlying surfaces between the two towers were tamarisk, populus, bare land and farmland. The elevation is 873 m. The effective height of the LAS was 25.5 m, and the path length was 2350 m. The data were sampled 1 minute. The raw data acquired at 1 min intervals were processed and quality controlled. The data were subsequently averaged over 30 min periods, in which sensible heat flux was iteratively calculated by combining Cn2 with meteorological data according to the Monin-Obukhov similarity theory. The main quality control steps were as follows: (1) The data were rejected when Cn2 exceeded the saturated criterion (BLS900&BLS450:Cn2>7.25E-14,RR-RSS460:Cn2>7.84 E-14). (2) The data were rejected when the demodulation signal was small (BLS900&BLS450:Average X Intensity<1000;RR-RSS460:Demod>-20mv). (3) The data were rejected when collected during precipitation. (4) The data were rejected if collected at night when weak turbulence occurred (u* was less than 0.1 m/s). In the iteration process, the universal functions of Thiermann and Grassl (1992) and Andreas (1988) were selected for BLS900 and RR-RSS460, respectively. Detailed can refer to Liu et al. (2011, 2013). Due to instrument adjustment and inadequate power supply, the date of missing data for the large aperture scintillator is: 2020.02.13-2020.02.14;2020.05.18-2020.15.19。 Several instructions were included with the released data. (1) The las data are firstly from BLS900, followed by BLS450, and finally the final missing data was marked with-6999. (2) The dataset contained the following variables: Date/time (yyyy/m/d h:mm), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H, W/m^2). In this dataset, a time of 0:30 corresponds to the average data for the period between 0:00 and 0:30, and the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) (for data processing) in the Citation section.

    2021-06-02 370 11

  • Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (Large aperture scintillometer of Daman Superstation, 2020)

    Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (Large aperture scintillometer of Daman Superstation, 2020)

    This dataset contains the flux measurements from the large aperture scintillometer (LAS) at Daman Superstation in the Heihe integrated observatory network from January 1 to December 6 in 2020. There were two types of LASs at Daman Superstation: BLS900 and RR-RSS460, produced by Germany. The north tower was set up with the BLS900 receiver and the RR-RSS460 transmitter, and the south tower was equipped with the BLS900 transmitter and the RR-RSS460 receiver. The site (north: 100.379° E, 38.861° N; south: 100.369° E, 38.847° N) was located in Daman irrigation district, which is near Zhangye, Gansu Province. The underlying surfaces between the two towers were corn, orchard, and greenhouse. The elevation is 1556 m. The effective height of the LASs was 24.1 m, and the path length was 1854 m. The data were sampled 1 minute at both BLS900 and RR-RSS460. The raw data acquired at 1 min intervals were processed and quality controlled. The data were subsequently averaged over 30 min periods, in which sensible heat flux was iteratively calculated by combining Cn2 with meteorological data according to the Monin-Obukhov similarity theory. The main quality control steps were as follows: (1) The data were rejected when Cn2 exceeded the saturated criterion (BLS900:Cn2>7.25E-14,RR-RSS460:Cn2>7.84 E-14). (2) The data were rejected when the demodulation signal was small (BLS900:Average X Intensity<1000;RR-RSS460:Demod>-20mv). (3) The data were rejected when collected during precipitation. (4) The data were rejected if collected at night when weak turbulence occurred (u* was less than 0.1 m/s). In the iteration process, the universal functions of Thiermann and Grassl (1992) and Andreas (1988) were selected for BLS900 and RR-RSS460, respectively. Detailed can refer to Liu et al. (2011, 2013). Due to instrument adjustment and inadequate power supply, the date of missing data for the large aperture scintillator is: 2020.06.21-2020.06.23;2020.09.21-2020.10.14. Several instructions were included with the released data. (1) The data were primarily obtained from BLS900 measurements, and missing flux measurements from the BLS900 instrument were substituted with measurements from the RR-RSS460 instrument. The missing data were denoted by -6999. (2) The dataset contained the following variables: Date/time (yyyy/m/d h:mm), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H, W/m^2). In this dataset, a time of 0:30 corresponds to the average data for the period between 0:00 and 0:30, and the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) (for data processing) in the Citation section.

    2021-06-02 351 20

  • Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (eddy covariance system of the temperate steppe, 2020)

    Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (eddy covariance system of the temperate steppe, 2020)

    This dataset contains the flux measurements from the temperate steppe eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to December 31 in 2020, but instrument failure and COVID-2019 resulted in lack of data from April 13 to July 20. The site (100°14'8.99"E, 37°14'49.00"N) was located in Sanjiaocheng sheep breeding farm, Gangcha County, Qinghai Province. The elevation is 3210sm. The EC was installed at a height of 2.5 m, and 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 (CSAT3A &EC150) was about 0.17 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the 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. 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): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). 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 collected 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, and the missing data were replaced with -6999. Data during December 18 to December 24, 2018 were missing due to the data collector failure. The released data contained the following variables: DATE/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/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), 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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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 *.xls format. Detailed information can be found in the suggested references.

    2021-06-01 260 13

  • Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (eddy covariance system of Alpine meadow and grassland ecosystem Superstation, 2020

    Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (eddy covariance system of Alpine meadow and grassland ecosystem Superstation, 2020

    This dataset contains the flux measurements from the Alpine meadow and grassland ecosystem Superstation superstation eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 1 to December 31 in 2020,but instrument failure and COVID-2019 resulted in lack of data from February 1 to June 27. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. The EC was installed at a height of 4.5 m, and 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 (CSAT3A &EC150) was about 0.17 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the 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. 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): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). 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 collected 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, and the missing data were replaced with -6999. Data during December 18 to December 24, 2018 were missing due to the data collector failure. The released data contained the following variables: DATE/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/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), 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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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 *.xls format. Detailed information can be found in the suggested references.

    2021-06-01 295 19

  • Cold and Arid Research Network of Lanzhou university (an observation system of meteorological elements gradient of Dayekou Station, 2020)

    Cold and Arid Research Network of Lanzhou university (an observation system of meteorological elements gradient of Dayekou Station, 2020)

    This dataset includes data recorded by Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Dayekou Station from January 1 to December 31, 2020. The site (100.285° E, 38.555° N) was located on a glassland in the Dayekou, which is near Zhangye city, Gansu Province. The elevation is 2694 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (8 m), air pressure (2 m), rain gauge (2 m), infrared temperature sensors (2 m, towards south, vertically downward), soil heat flux (below the vegetation, -0.05 m; towards south), soil soil temperature/moisture/electrical conductivity profile (-0.05 m) photosynthetically active radiation (2 m, towards south), four-component radiometer (2 m, towards south), sunshine duration sensor(2 m, towards south). The observations included the following: air temperature and humidity (Ta_8m; RH_3m, RH_5 m, RH_8m) (℃ and %, respectively), wind speed (Ws_8m) (m/s), wind direction (WD_8m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 (℃), photosynthetically active radiation (PAR) (μmol/ (s m^2)), soil heat flux (Gs_5 cm) (W/m^2), soil temperature (Ts_5cm)(℃), soil moisture (Ms_5cm)(%, volumetric water content), photosynthetically active radiation (μmol/ (s m^2)), soil water potential (Swp_5cm)(kpa), soil conductivity (Ec_5cm)(μs/cm), sun time(h). 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 and missing records 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.

    2021-06-01 259 16

  • Cold and Arid Research Network of Lanzhou university (an observation system of meteorological elements gradient of Guazhou Station, 2020)

    Cold and Arid Research Network of Lanzhou university (an observation system of meteorological elements gradient of Guazhou Station, 2020)

    This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of meteorological elements gradient of Guazhou Station from January 1 to December 31, 2020. The site (95.673E, 41.405N) was located on a desert in the Liuyuan Guazhou, which is near Jiuquan city, Gansu Province. The elevation is 2016 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (2, 4, 8, 16, 32, and 48 m, towards north), wind speed and direction profile (windsonic; 2, 4, 8, 16, 32, and 48 m, towards north), air pressure (1.5 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil soil temperature/ moisture/ electrical conductivity profile -0.05, -0.1m, -0.2m, -0.4m, -0.6m and -0.8m in south of tower), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_2 m, Ta_4 m, Ta_8 m, Ta_16 m, Ta_32 m, and Ta_48 m; RH_2 m, RH_4 m, RH_8 m, RH_16 m, RH_32 m, and RH_48 m) (℃ and %, respectively), wind speed (Ws_2 m, Ws_4 m, Ws_8 m, Ws_16 m, Ws_32 m, and Ws_48 m) (m/s), wind direction (WD_2 m, WD_4 m, WD_8 m, WD_16 m, WD_32 m, and WD_48 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s m^2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_5 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_80 cm) (℃), soil moisture (Ms_5 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_80 cm) (%, volumetric water content),soil water potential (SWP_5cm, SWP_10cm, SWP_20cm, SWP_40cm, SWP_60cm, and SWP_80cm)(kpa), soil conductivity (Ec_5cm, Ec_10cm, Ec_20cm, Ec_40cm, Ec_60cm, and Ec_80cm)(μs/cm), sun time (h). 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 and missing records 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.

    2021-06-01 284 22

  • Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of Zhangye wetland station, 2020)

    Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of Zhangye wetland station, 2020)

    This dataset includes data recorded by the Heihe integrated observatory network obtained from the automatic weather station (AWS) at the observation system of Zhangye wetland station from January 1 to December 31, 2020. The site (100.4464° E, 38.9751° N) was located on a wetland (reed surface) in Zhangye National Wetland Park, Gansu Province. The elevation is 1460 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 5 and 10 m, north), wind speed profile (03002; 5 and 10 m, north), wind direction profile (03002; 10 m, north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (SI-111; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2 and -0.4 m), and four photosynthetically active radiation (PQS-1; two above the plants, 6 m, south, one vertically downward and one vertically upward; two below the plants, 0.25 m, south, one vertically downward and one vertically upward). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m; RH_5 m and RH_10 m) (℃ and %, respectively), wind speed (Ws_5 m and Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 IRT_2) (℃), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm and Ts_40 cm) (℃), on the plants photosynthetically active radiation of upward and downward (PAR_U_up and PAR_U_down) (μmol/ (s m^-2)), and below the plants photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m^-2)). 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. 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: 2019-6-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.

    2021-05-31 443 49

  • Land Surface Temperature Dataset of Typical Stations in Middle Reaches of Heihe River Basin Based on UAV Remote Sensing(2020,V1)

    Land Surface Temperature Dataset of Typical Stations in Middle Reaches of Heihe River Basin Based on UAV Remote Sensing(2020,V1)

    Land Surface temperature is one of the important parameters of surface energy balance. This dataset is the monthly land surface temperature data of typical stations in Heihe River Basin from June to October in 2020; In flight, DJI M600 Pro UAV was equipped with the WIRIS Pro sc thermal imager. taking SD station in the wetland, DM station in the oasis and Hz station in the desert as the center, the land surface temperature was observed, and the surface brightness temperature image was obtained. The flying height of the UAV was about 300m, the pixel of the thermal imager was 336x256, and the spatial resolution of the image was 0.4m. The surface temperature retrieval algorithm is an improved single channel algorithm, which is applied to the surface brightness temperature data obtained by UAV thermal imager, and finally the land surface temperature data with 0.4 m spatial resolution is obtained.

    2021-05-31 303 0

  • Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of Yakou station, 2020)

    Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of Yakou station, 2020)

    This dataset includes data recorded by the Heihe integrated observatory network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Yakou station from January 1 to December 31, 2020. The site (100.2421°E, 38.0142°N) was located on an alpine meadow surface, which is near west of Qilian county, Qinghai Province. The elevation is 4148 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45C; 5 m, north), wind speed and direction profile (010C/020C; 10 m, north), air pressure (PTB110; in the tamper box on the ground), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (SI-111; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109ss-L; 0, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and soil moisture profile (CS616; -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_5 m; RH_5 m) (℃ and %, respectively), wind speed (Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), and soil moisture (Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content). 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. The missing data were denoted by -6999. Due to the sensor malfunction, the four-component radiation was wrong intermittently. Due to the power loss, data during February 2 to April 25 were missing. (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: 2020-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.

    2021-05-31 485 57

  • NDVI Dataset of Typical Stations in Midstream of Heihe River Basin Based on UAV Remote Sensing (2020, V1)

    NDVI Dataset of Typical Stations in Midstream of Heihe River Basin Based on UAV Remote Sensing (2020, V1)

    NDVI is a very important vegetation index for the research of vegetation growth and land cover classification. This dataset provides the monthly normalized differential vegetation index (NDVI) of UAV remote sensing with a spatial resolution of 0.2 m from June to October in 2020. It was measured in the midstream of Heihe River Basin over typical stations. The Pix4D mapper software was used for image mosaic and NDVI calculation.

    2021-05-31 308 0

  • Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (an observation system of Meteorological elements gradient of Sidaoqiao Superstation, 2020)

    Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (an observation system of Meteorological elements gradient of Sidaoqiao Superstation, 2020)

    This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of Sidaoqiao Superstation from January 1 to December 31, 2020. The site (101.137° E, 42.001° N) was located on a tamarix (Tamarix chinensis Lour.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 873 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HC2S3; 5, 7, 10, 15, 20 and 28 m, towards north), wind speed profile (010C; 5, 7, 10, 15, 20 and 28 m, towards north), wind direction profile (020C; 15 m, towards north), air pressure (CS100; in waterproof box), rain gauge (TE525M; 28 m, towards south), four-component radiometer (CNR4; 10 m, towards south), two infrared temperature sensors (SI-111; 10 m, towards south, vertically downward), two photosynthetically active radiation (PQS-1; 10 m, towards south, one vertically upward and one vertically downward), soil heat flux (HFP01SC; 3 duplicates with G1 below the tamarix; G2 and G3 between plants, -0.06 m), a TCAV averaging soil thermocouple probe (installed on 17 July, 2013, TCAV; -0.02, -0.04 m), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, -1.6, -2.0 m), and soil moisture profile (install on 7 December, 2013, ML2X; -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, -1.6, -2.0 m). The observations included the following: air temperature and humidity (Ta_5 m, Ta_7 m, Ta_10 m, Ta_15 m, Ta_20 m and Ta_28 m; RH_5 m, RH_7 m, RH_10 m, RH_15 m, RH_20 m and RH_28 m) (℃ and %, respectively), wind speed (Ws_5 m, Ws_7 m, Ws_10 m, Ws_15 m, Ws_20 m and Ws_28 m) (m/s), wind direction (WD_15 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 cm) (%, volumetric water content). 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 of wind speed at 20 m height during January to April, and infrared temperature 2 during January to May were wrong because of the sensor problem; the soil temperature and moisture was occasionally wrong during January 1 to 14 because of datalogger problem. 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: 2020-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.

    2021-05-31 396 39

  • Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of Jingyangling station, 2020)

    Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of Jingyangling station, 2020)

    This dataset includes data recorded by the Heihe integrated observatory network obtained from the automatic weather station (AWS) at the Jingyangling station from January 1 to December 31, 2020. The site (101.116° E, 37.838° N) was located on a cold meadow surface in the Jingyangling, Qilian County, Qinghai Province. The elevation is 3750 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (5 m, north), wind speed and direction (10 m, north), air pressure (in the tamper box on the ground), rain gauge (10 m), four-component radiometer (6 m, south), two infrared temperature sensors (6 m, south, vertically downward), soil heat flux (3 duplicates, -0.06 m), soil temperature profile (0, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and soil moisture profile (-0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_5 m; RH_5 m) (℃ and %, respectively), wind speed (Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), and soil moisture (Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content). 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. The missing data were denoted by -6999. Due to the snow cover the solar panel causing insufficient power supply, data during March 14-April 25 were missing; due to the sensor malfunction, there were some NAN invalid values of the wind speed and direction; incorrect data of upward shortwave radiation occasionally; (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: 2020-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.

    2021-05-31 455 40