Comprehensive observation system for carbon dioxide isotopes during soil biochemistry process: multichannel and dual-cycle observation system for soil CO2 and δ13C fluxes (2019-2020)

Soil respiration is the second most important carbon flux, which is only lower than that of photosynthesis in terrestrial ecosystems. The production and transport of CO2 and its δ13C by soil biochemical processes are the limiting factors for the magnitude and process evaluation of soil respiration. According to the characteristics of CO2 gas generation and transportation in soil biochemical process, based on stable isotope infrared spectroscopy technology, the nonlinear on-line calibration technology, multi-channel double-cycle efficient gas circulation path, efficient gas circulation path with pre-reduced gas concentration, and variable temperature technology that can simulate the freezing and thawing process were independently developed. On account of the gas exchange process in soil and air interface, vertical migration process of CO2 in soil profile and the process of soil organic matter decomposition, we develop a comprehensive observation system for measuring the isotope composition of carbon dioxide during soil biochemistry processes. The observation systems were placed in the ecologically fragile areas and measured the concentration and flux of soil CO2 and its δ13C, which effectively solved the comprehensive monitoring problem in generation, migration and release of CO2 during soil biochemical process. (1) a multichannel and dual-cycle observation system for soil CO2 and δ13C fluxes at the soil-atmosphere interface: We developed an online calibration system for the nonlinear response of CO2 and its δ13C analyzer at multiple concentrations to ensure the accuracy and accuracy of the instrument. By controlling the circuit switch, the instrument can automatically switch and collect circular observations between multiple channels. By controlling the premixing of gas in the channel while waiting to collect an observation, the instrument can decrease the observation time required for every channel and increase the efficiency and frequency of observation collection. By premixing the gas in the channel to be monitored, the instrument can eliminate the “dead gas” disturbances in the observation results and improve the accuracy of the observations. Based on the simulation flux verification system test, the simulated flux of CO2 and δ13C is better than 0.32 μmol m-2 s-1 @ 10 μmol m-2 s-1 (CO2) and 0.52‰ @ 10 μmol m-2 s-1 (CO2), which is better than the core technical index requirements of the project. The average domestication rate of the equipments is more than 80%, which has been used in the automatic monitoring of forest, grassland and farmland ecosystems, realizing the independent innovation and upgrading of ecological monitoring technology in China, and can be extended to CERN, CFERN, CNERN and similar field stations in other related departments. It is helpful to greatly improve China's R&D capability, level and international influence on ecological monitoring and assessment, effectively support China's terrestrial ecosystem carbon sequestration rate and potential assessment and certification, and provide technical support for national ecological civilization construction, carbon peak, carbon neutrality and ecological security regulation.

0 2021-11-17

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of Alpine meadow and grassland ecosystem Superstation, 2020)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Alpine meadow and grassland ecosystem Superstation from Janurary 1 to December 31 in 2020. 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 installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 10m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 m) (°), precipitation (rain) (mm), air pressure (press) (hpa), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)), 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), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_400cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_400cm) (%, 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. (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: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

0 2021-06-08

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of Subalpine shrub, 2020

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Subalpine shrub from Janurary 1to December 31, 2020. The site (100°6'3.62"E, 37°31'15.67") was located in the subalpine shrub ecosystem, near the Gangcha County, Qinghai Province. The elevation is 3495m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5 and 10 m, towards north), wind speed and direction profile (windsonic; 3, 5 and 10 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 2 m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, and Ta_10 m; RH_3 m, RH_5 m, and RH_10 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, and Ws_10 m) (m/s), wind direction (WD_3 m, WD_5 m and WD_10 m) (°), precipitation (rain) (mm), air pressure (press) (hpa), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)), 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), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_500cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_500cm) (%, 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. (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: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

0 2021-06-08

Vegetation environmental research data set in key areas of Asian water tower area of Qinghai Tibet Plateau (2019-2020)

This data set includes six data files, which are: (1) soil temperature and moisture data of alpine meadow elevation gradient_ Dangxiong, Tibet (2019-2020). This data is the hourly observation data of temperature and water content at different soil depths (5cm and 20cm) of the alpine meadow at 4400m, 4500m, 4650m, 4800m, 4950m and 5100m above sea level in Dangxiong, Tibet during 2019-2020. (2) Meteorological environment data of Sejila Mountain Forest line_ Linzhi, Tibet (2019), the data is the hourly meteorological environment (including wind speed, air temperature 1 m away from the surface, relative humidity 1 m away from the surface, air temperature 3 m away from the surface, relative humidity 3 m away from the surface, atmospheric pressure, total radiation, net radiation, photosynthetically active radiation, 660 nm) of the forest line of Sejila Mountain in Linzhi, Tibet in 2019 Hourly observation data of red light radiation, 730nm infrared radiation, surface temperature, atmospheric long wave radiation, surface long wave radiation, underground 5cm-20cm-60cm heat flux, underground 5cm-20cm-60cm soil temperature and humidity, rainfall and snow thickness, among which some observation data are missing due to equipment power failure in plateau area, which has been explained in the data. (3) NDVI of vegetation at major meteorological stations_ In the Qinghai Tibet Plateau (2020), NDVI survey data and average values of vegetation near 25 meteorological stations are included. (4) Land use survey data set_ Along the Sichuan Tibet Railway (2019), including 35 survey points along the Sichuan Tibet railway land use survey data, including survey time, location, latitude and longitude, altitude, slope aspect, main vegetation types and dominant species. (5) Leaf area index survey data_ The leaf area index (LAI) of main vegetation types along Sichuan Tibet Railway (2019) was measured by SunScan canopy analyzer and lai-2200. (6) Survey data of soil temperature and humidity_ Along the Sichuan Tibet Railway (2019), including 34 survey points along the Sichuan Tibet Railway: location, longitude and latitude, altitude, soil surface temperature, soil moisture at 30cm, the data were recorded as 3 repeated measurements at each survey point. The data set can be used to analyze and study the change law of vegetation environment in Qinghai Tibet Plateau.

0 2021-04-20

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of meteorological elements gradient of Alpine meadow and grassland ecosystem superstation, 2018)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Alpine meadow and grassland ecosystem Superstation from August 31 to December 24, 2018. 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 installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 10m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 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_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_400cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_400cm) (%, volumetric water content), 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: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

0 2020-07-25

Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (an observation system of meteorological elements gradient of Sidaoqiao superstation, 2018)

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, 2018. 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. The precipitation data was wrong during January to June because of the sensor problem; the air pressure data was wrong during July to October because of sensor line broken. 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: 2018-9-10 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.

0 2020-07-25

Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (an observation system of meteorological elements gradient of A’rou Superstation, 2018)

This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of A’rou Superstation from January 1 to December 31, 2018. The site (100.464° E, 38.047° N) was located on a cold grassland surface in the Caodaban village, A’rou Town, Qilian County, Qinghai Province. The elevation is 3033 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45C; 1, 2, 5, 10, 15 and 25 m, towards north), wind speed profile (010C; 1, 2, 5, 10, 15 and 25 m, towards north), wind direction profile (020C; 2 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 5 m, towards south), four-component radiometer (CNR4; 5 m, towards south), two infrared temperature sensors (SI-111; 5 m, towards south, vertically downward), photosynthetically active radiation (PAR-LITE; 5 m, towards south, vertically upward), soil heat flux (HFP01SC; 3 duplicates, -0.06 m, 2 m in the south of tower), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m, 2 m in the south of tower), soil temperature profile (109; 0, -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m), and soil moisture profile (CS616; -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m). The observations included the following: air temperature and humidity (Ta_1 m, Ta_2 m, Ta_5 m, Ta_10 m, Ta_15 m and Ta_25 m; RH_1 m, RH_2 m, RH_5 m, RH_10 m, RH_15 m and RH_25 m) (℃ and %, respectively), wind speed (Ws_1 m, Ws_2 m, Ws_5 m, Ws_10 m, Ws_15 m and Ws_25 m) (m/s), wind direction (WD_2 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/m2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation (PAR) (μmol/(s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm_1, Ts_4 cm_2, Ts_4 cm_3, Ts_6 cm, Ts_10 cm_1, Ts_10 cm_2, Ts_10 cm_3, Ts_15 cm, Ts_20 cm, Ts_30 cm, Ts_40 cm, Ts_60 cm, Ts_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm, Ts_240 cm, Ts_280 cm and Ts_320 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm_1, Ms_4 cm_2, Ms_4 cm_3, Ms_6 cm, Ms_10 cm_1, Ms_10 cm_2, Ms_10 cm_3, Ms_15 cm, Ms_20 cm, Ms_30 cm, Ms_40 cm, Ms_60 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 cm, Ms_240 cm, Ms_280 cm and Ms_320 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 average soil temperature was rejected during February 16 to March 31 and April 15 to May 20 because of broken of the sensor line; Soil heat flux were wrong occasionally during November to December. 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: 2018-9-10 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.

0 2020-07-25

The monitoring data of soil and groundwater temperature in Hulugou Watershed from 2016 May to 2016 September

The data includes the county-level data of characteristic agriculture distribution in the Qinghai Tibet Plateau, which lays the foundation for the spatial distribution and development of characteristic agriculture in the Qinghai Tibet Plateau.

0 2020-06-07

Soil temperature and moisture observation data of the Selincuo Lake Basin (2017)

This is the soil temperature and moisture observation data set in the runoff fields of the east bank of Selincuo Lake. It can be used in Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from August 19, 2017 to September 8, 2017. It is measured by soil temperature and moisture probe (5TE)and a piece of data is recorded every 60 minutes. The original data is precise, with the soil moisture accurate to 0.01% and the soil temperature 0.01℃. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The data is stored as an excel file.

0 2020-06-03

Observation of water and heat flux in alpine meadow ecosystem —automatic weather station of E’bao station (2015-2016)

The data set contains the meteorological element observation data of ebao station in the upper reaches of heihe hydrometeorological observation network on January 1, 2015 and December 31, 2016.The station is located in ebao town, qilian county, qinghai province.The longitude and latitude of the observation point are 100.9151E, 37.9492N, and the altitude is 3294m.The air temperature and relative humidity sensor is set up at 5m, facing due north.The barometer is installed in the anti-skid box on the ground;The tipping bucket rain gauge is installed at 10m;The wind speed and direction sensor is mounted at 10m, facing due north;The four-component radiometer is installed at 6m, facing due south;Two infrared thermometers are installed at 6m, facing south, with the probe facing vertically downward;The soil temperature probe is buried at the surface of 0cm and underground of 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm, 2m south of the meteorological tower.The soil moisture probe is buried underground at 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm, 2m south of the meteorological tower.The soil heat flow plates (3 pieces) are successively buried 6cm underground, 2m south of the meteorological tower. Observation projects are: air temperature and humidity (Ta_5m, RH_5m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:C), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: wattage/m2), soil temperature (Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: water content by volume, percentage). Processing and quality control of observation data :(1) 144 data per day (every 10min) should be ensured.The four-component radiation and infrared temperature were between October 11, 2015 and November 5, 2015.The instrument of the observation tower was re-adjusted between 11.1 and 11.5, and the data was missing;(2) eliminate the moments with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letters in the data is questionable data;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: 2015-9-10 10:30;(6) naming rules: AWS+ site name. For information of hydrometeorological network or site, please refer to Li et al. (2013), and for data processing, please refer to Liu et al. (2011).

0 2020-06-01