This dataset contains the flux measurements from the mixed forest station eddy covariance system (EC) in the lower reaches of the Heihe hydrometeorological observation network from 12 July to 31 December, 2013. The site (101.134° E, 41.990° N) was located in the Populus and Tamarix surface, Ejin Banner in Inner Mongolia. The elevation is 874 m. The EC was installed at a height of 22 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 (CSAT3&Li7500) was 0.17 m. The 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 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), as 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), which represent high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened using 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 0.2 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Due to the malfunction of sonic anemometer, data during 16 August to 17 September were missing. 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 *.xls format. 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.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The dataset of ground truth measurement synchronizing with Envisat ASAR was obtained in the arid region hydrological experimental area on Sep. 19, 2007 during the pre-observation period. One scene of Envisat ASAR image was captured on Sep. 19. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:29 BJT. Those provide reliable ground data for remote sensing retrieval and validation of soil moisture from Envisat ASAR image. Observation items included: (1) soil moisture measured by the cutting ring method in Linze reed land, Zhangye farmland, Zhangye gobi, Linze maize land, Linze alfalfa land, Zhangye weather station, and Linze wetland. (2) GPS measured by GARMIN GPS 76 (3) vegetation measurements including the vegetation height, the green weight, the dry weight, the sampling method, and descriptions on the land type, uniformity and dry and wet conditions (4) atmospheric parameters at Daman Water Management office measured by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in .k7 and can be opened by ASTPWin. ReadMetext files (.txt) is attached for detail. Processed data (after retrieval of the raw data) archived as Excel files are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (5) roughness measured by the roughness plate together with the digital camera. The coordinates of the sample would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing (Vol. II). The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each text files (.txt) file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 radius is also included for further checking.
CHE Tao, LI Xin, BAI Yunjie, DING Songchuang, GAO Song, HAN Xujun, HAO Xiaohua, LI Hongyi, LI Zhe, LIANG Ji, PAN Xiaoduo, QIN Chun, RAN Youhua, WANG Xufeng, WU Yueru, YAN Qiaodi, ZHANG Lingmei, FANG Li, LI Hua, Liu Qiang, Wen Jianguang, MA Hongwei, YAN Yeqing, YUAN Xiaolong
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at site No.2 in the flux observation matrix. There were two types of LASs at site No.2: German BLS900 and German BLS450. The observation periods were from 7 June to 19 September, 2012, and 18 June to 19 September, 2012, for the BLS900 and the BLS450, respectively. The north tower is placed with the receiver of BLS900 and the transmitter of BLS450, and the south tower is placed with the transmitter of BLS900 and the receiver of BLS450. The site (north: 100.363° E, 38.883° N; south: 100.362° E, 38.857° N) was located in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 m. The underlying surface between the two towers contains corn, greenhouse, and village. The effective height of the LASs was 33.45 m; the path length was 2841 m. Data were sampled at 1 min intervals. Raw data acquired at 1 min intervals were processed and quality-controlled. The data were subsequently averaged over 30 min periods. The main quality control steps were as follows. (1) The data were rejected when Cn2 was beyond the saturated criterion (Cn2>4.08E-14). (2) Data were rejected when the demodulation signal was small (BLS900: Average X Intensity<1000; BLS450: Minimum X<50). (3) Data were rejected within 1 h of precipitation. (4) Data were rejected at night when weak turbulence occurred (u* was less than 0.1 m/s). The sensible heat flux was iteratively calculated by combining with meteorological data and based on Monin-Obukhov similarity theory. There were several instructions for the released data. (1) The data were primarily obtained from BLS900 measurements; missing flux measurements from the BLS900 were filled with measurements from the BLS450. Missing data were denoted by -6999. (2) The dataset contained the following variables: data/time (yyyy-mm-dd hh:mm:ss), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, W/m^2). (3) 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. 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.
LIU Shaomin, LI Xin, XU Ziwei
The dataset of LAS (Large Aperture Scintillometer, made in Holland) observations was obtained in the Linze grassland station, Linze county (Gansu province), from May 19 to Aug. 31, 2008. The instrument was composed of the transmitter (100°04′10.4″E, 39°15′02.8″N, 9.25m), the receiver (100°03′36.8″E, 39°15′02.8″N, 9.1m) and the data acquisition system. The transmitter and the receiver were 1550m away from each other and the operating altitude was 9.2m. The observation item was natural logarithm of structural parameters of the refractive index (UCn2). The transmitting frequency was 0.5HZ. The data were named after WATER_LAS_Linze_yyyymmdd-yyyymmdd.csv (yyyymmdd-yyyymmdd for observation time). The missing data were marked "None". For more detailed information, please refer to Directions on LAS (Large Aperture Scintillometer) observations.
LIU Shaomin, LI Xin, XU Ziwei
The dataset of meteorological station observations (2008-2009) was obtained at the Yeniugou cold region hydrological station (E99°33'/N38°28', 3320m), Qilian county, Qinghai province. Observation items were multilayer (2m and 10m) of the air temperature and air humidity, the wind speed and direction, the air pressure, precipitation, the global radiation, the net radiation, the multilayer soil temperature (20cm, 40cm, 60cm, 80cm, 120cm and 160cm), soil moisture (20cm, 40cm, 60cm, 80cm, 120cm and 160cm), and soil heat flux. For more details, please refer to the attached Data Directions.
CHEN Rensheng, YANG Yong, Wang Weizhen, LI Xin
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at A’rou Superstation in the hydrometeorological observation network of Heihe River Basin between 14 October, 2012, and 31 December, 2013. There were two types of LASs at A’rou Superstation: German BLS450 and China zzlas. The north tower was set up with the zzlas receiver and the BLS450 transmitter, and the south tower was equipped with the zzlas transmitter and the BLS450 receiver. Zzlas has been in use since 14 October, 2012, and the observation period of BLS450 was from 9 August to 10 December, 2013. The site (north: 100.467° E, 38.050° N; south: 100.450° E, 38.033° N) was located in Caodaban village of A’rou town in Qilian county, Qinghai Province. The underlying surface between the two towers was alpine meadow. The elevation is 3033 m. The effective height of the LASs was 9.5 m, and the path length was 2390 m. The data were sampled at 5 Hz and 1 Hz intervals for BLS450 and zzlas, respectively, and then averaged over 1 min. 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 (BLS450: Cn2>7.25E-14, zzlas: Cn2>7.84E-14). (2) The data were rejected when the demodulation signal was small (BLS450: Average X Intensity<1000; zzlas: Demod>-20 mv). (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 BLS450 and zzlas, respectively. Several instructions were included with the released data. (1) The data were primarily obtained from BLS450 measurements, and missing flux measurements from the BLS450 instrument were substituted with measurements from the zzlas instrument. The missing data were denoted by -6999. Due to the drift of the zzlas signal, data from 10 November to 23 November, 2012, and 14 March to 10 April, 2013, were excluded. Due to the LAS tower’s lean, the data from 10 April to 31 May, 2013, were not collected. (2) The dataset contained the following variables: data/time (yyyy-m-d h:mm), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, 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 *.xls format. 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.
LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
This dataset contains the flux measurements from site No.14 eddy covariance system (EC) in the flux observation matrix from 30 May to 21 September, 2012. The site (100.35310° E, 38.85867° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1570.23 m. The EC was installed at a height of 4.6 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&Li7500) was 0.15 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.
LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the flux measurements from site No.8 eddy covariance system (EC) in the flux observation matrix from 28 May to 21 September, 2012. The site (100.37649° E, 38.87254° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1550.06 m. The EC was installed at a height of 3.2 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&Li7500) was 0.15 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.
LIU Shaomin, LI Xin, XU Ziwei
The dataset of LST (land surface temperature) observed by the thermal camera (ThermaCAM SC2000 and ThermaCAM S60) at 24°×18° was obtained in the Yingke oasis, Huazhaizi desert steppe and Linze grassland foci experimental areas on May 20, 24,28 and 30, Jun. 1, 4, 16 and 29, Jul. 7, 8 and 11, 2008. Meanwhile, the optical photos were acquired in Yingke oasis maize field, Huazhaizi desert No. 1 and 2 plots, Huazhaizi desert maize field and Linze grassland. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, Landsat TM and ASTER.
HE Tao, KANG Guoting, REN Huazhong, YAN Guangkuo, WANG Haoxing, WANG Tianxing, LI Hua, Liu Qiang, XIA Chuanfu, ZHOU Chunyan, ZHOU Mengwei, CHEN Shaohui, YANG Tianfu
This dataset contains the flux measurements from site No.6 eddy covariance system (EC) in the flux observation matrix from 28 May to 21 September, 2012. The site (100.35970° E, 38.87116° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1562.97 m. The EC was installed at a height of 4.6 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 0.15 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.
LI Xin, XU Ziwei
This data set contains the daily values of temperature, air pressure, relative humidity, wind speed, precipitation, and total radiation observed at the Namco station from 1 October 2005 to 31 December 2016. The data set was processed as a continuous time series after the original data were quality controlled. After the systematic error caused by missing data points and sensor failure was eliminated, the data set reaches the accuracy of raw meteorological observation data required by the National Weather Service and the World Meteorological Organization (WMO). The data can provide information for professionals engaged in scientific research and training related to atmospheric physics, atmospheric environment, climate, glaciers, frozen soils and other disciplines. This data set has mainly been applied in the fields of glaciology, climatology, environmental change, cold zone hydrological processes, frozen soil science, etc. The measured parameters had the following units and accuracies: Air temperature, unit: °C, accuracy: 0.1 °C; air relative humidity, unit: %, accuracy: 0.1%; wind speed, unit: m/s, accuracy: 0.1 m/s; wind direction, unit: °, accuracy: 0.1 °; air pressure, unit: hPa, accuracy: 0.1 hPa; precipitation, unit: mm, accuracy: 0.1 mm; total radiation, unit: W/m2, accuracy: 0.1 W/m2.
WANG Yuanwei, WU Guangjian
This dataset contains the flux measurements from the Zhangye wetland station eddy covariance system (EC) in the middle reaches of the Heihe hydrometeorological observation network from 15 September, 2012, to 21 November, 2013. The site (100.446° E, 38.975° N) was located in the desert steppe surface, near Zhangye city in Gansu Province. The elevation is 1460 m. The EC was installed at a height of 5.2 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 (Gill&Li7500A) was 0.25 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/eddy_covariance/software.html), 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), as 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), which represent high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened using 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. Suspicious data were marked in red. Due to the calibration of CO2/H2O gas analyzer and CF card storage problem, data during 28 May to 30 May, and 21 November to 31 December, 2013 were missing. 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 *.xls format. 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.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset includes the emissivity spectrum (8-14 µm) of typical ground objects in Zhangye City, Zhangye airport, desert and farmland at Wuxing experiment area. The data was measured by the BOMEM MR304 FTIR (Fourier Transform Infrared Spectrometer). A. Objective The objective of the thermal infrared (TIR) spectrum measurement lies in: Radiometric calibration for the airborne TIR sensor, land surface emissivity products validation and collecting typical surface spectrum working as priori knowledge in land surface temperature inversion and ecological and hydrological models. B. Instruments and theory Instruments: BOMEM MR304 FTIR, Mikron M340 blackbody, BODACH BDB blackbody, diffused golden plate, Fluke 50-series II thermometer Measurement theory: The target radiance is directly measured by the MR304 FTIR under clear-sky condition while the atmospheric downward radiance is obtained through a diffused golden plate, and emissivity is retrieved by the Iterative Spectrally Smooth Temperature and Emissivity Separation (ISSTES) algorithm C. Experiment site and targets 29-5-2012: Stone bricks, grassland and asphalt, etc at square of Zhangye. 20-6-2012: Roof of the building in Zhangye, water and sand sample collected from the desert, etc. 30-6-2012: Cement road at Zhangye airport, desert around the Zhangye airport. 3-7-2012: Corn leaves, soil and road in the farmland at Wuxing village, Zhangye City. 4-7-2012: Corn leaves, wheat canopy at Xiaoman town, Zhangye City. 10-7-2012: Bricks of Runquanhu park, Zhangye City. 13-7-2012: Corn leaves and other plants at Wuxing village, Zhangye City. D. Data processing The original data collected by BOMEM FTIR is firstly calibrated using the calibration data and get the radiance spectrum of the targets and sky (*.rad), then, the radiance data is converted to the easy readably text file (ASCII format). The time used in this dataset is in UTC+8 Time.
MA Mingguo, XIAO Qing
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at site No.4 in the flux observation matrix. There were two types of LASs at site No.4: German BLS450 and China zzlas. The observation periods were from 2 June to 22 September, 2012 and 11 June to 20 September, 2012, for the BLS450 and the zzlas, respectively. The north tower is placed with the receiver of BLS450 and the transmitter of zzlas, and the south tower is placed with the transmitter of BLS450 and the receiver of zzlas. The site (north: 100.379° E, 38.861° N; south: 100.369° E, 38.847° N) was located in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 m. The underlying surface between the two towers contains corn, greenhouse, and village. The effective height of the LASs was 33.45 m; the path length was 1854 m. Data were sampled at 1 min intervals. Raw data acquired at 1 min intervals were processed and quality-controlled. The data were subsequently averaged over 30 min periods. The main quality control steps were as follows. (1) The data were rejected when Cn2 was beyond the saturated criterion (Cn2>1.01E-13). (2) Data were rejected when the demodulation signal was small (BLS450: Average X Intensity<1000, zzlas: Demod<-40 mv). (3) Data were rejected within 1 h of precipitation. (4) Data were rejected at night when weak turbulence occurred (u* was less than 0.1 m/s). The sensible heat flux was iteratively calculated by combining with meteorological data and based on Monin-Obukhov similarity theory. There were several instructions for the released data. (1) The data were primarily obtained from BLS450 measurements. Missing data were denoted by -6999. (2) The dataset contained the following variables: data/time (yyyy-mm-dd hh:mm:ss), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, W/m^2). (3) 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. 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.
LIU Shaomin, LI Xin, XU Ziwei
The GAME/Tibet project conducted a short-term pre-intensive observing period (PIOP) at the Amdo station in the summer of 1997. From May to September 1998, five consecutive IOPs were scheduled, with approximately one month per IOP. More than 80 scientific workers from China, Japan and South Korea went to the Tibetan Plateau in batches and carried out arduous and fruitful work. The observation tests and plans were successfully completed. After the completion of the IOP in September, 1998, five automatic weather stations (AWS), one Portable Atmospheric Mosonet (PAM), one boundary layer tower and integrated radiation observatory (Amdo) and nine soil temperature and moisture observation stations have been continuously observed to date and have obtained extremely valuable information for 8 years and 6 months consecutively (starting from June 1997). The experimental area is located in Nagqu, in northern Tibet, and has an area of 150 km × 200 km (Fig. 1), and observation points are also established in D66, Tuotuohe and the Tanggula Mountain Pass (D105) along the Qinghai-Tibet Highway. The following observation stations (sites) are set up on different underlying surfaces including plateau meadows, plateau lakes, and desert steppe. (1) Two multidisciplinary (atmosphere and soil) observation stations, Amdo and NaquFx, have multicomponent radiation observation systems, gradient observation towers, turbulent flux direct measurement systems, soil temperature and moisture gradient observations, radiosonde, ground soil moisture observation networks and multiangle spectrometer observations used as ground truth values for satellite data, etc. (2) There are six automatic weather stations (D66, Tuotuohe, D105, D110, Nagqu and MS3608), each of which has observations of wind, temperature, humidity, pressure, radiation, surface temperature, soil temperature and moisture, precipitation, etc. (3) PAM stations (Portable Automated Meso - net) located approximately 80 km north and south of Nagqu (MS3478 and MS3637) have major projects similar to the two integrated observation stations (Amdo and NaquFx) above and to the wind, temperature and humidity turbulence observations. (4) There are nine soil temperature and moisture observation sites (D66, Tuotuohe, D110, WADD, NODA, Amdo, MS3478, MS3478 and MS3637), each of which has soil temperature measurements of 6 layers and soil moisture measurement of 9 layers. (5) A 3D Doppler Radar Station is located in the south of Nagqu, and there are seven encrypted precipitation gauges in the adjacent (within approximately 100 km) area. The radiation observation system mainly studies the plateau cloud and precipitation system and serves as a ground true value station for the TRMM satellite. The GAME-Tibet project seeks to gain insight into the land-atmosphere interaction on the Tibetan Plateau and its impact on the Asian monsoon system through enhanced observational experiments and long-term monitoring at different spatial scales. After the end of 2000, the GAME/Tibet project joined the “Coordinated Enhanced Observing Period (CEOP)” jointly organized by two international plans, GEWEX (Global Energy and Water Cycle Experiment) and CL IVAR (Climate Change and Forecast). The Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau of the Global Coordinated Enhanced Observation Program (CEOP) has been started. The data set contains POP data for 1997 and IOP data for 1998. Ⅰ. The POP data of 1997 contain the following. 1. Precipitation Gauge Network (PGN) 2. Radiosonde Observation at Naqu 3. Analysis of Stable Isotope for Water Cycle Studies 4. Doppler radar observation 5. Large-Scale Hydrological Cycle in Tibet (Link to Numaguchi's home page) 6. Portable Automated Mesonet (PAM) [Japanese] 7. Ground Truth Data Collection (GTDC) for Satellite Remote Sensing 8. Tanggula AWS (D105 station in Tibet) 9. Syamboche AWS (GEN/GAME AWS in Nepal) Ⅱ. The IOP data of 1998 contain the following. 1. Anduo （1） PBL Tower, 2） Radiation, 3） Turbulence SMTMS 2. D66 （1） AWS （2） SMTMS （3） GTDC （4) Precipitation 3. Toutouhe （1） AWS （2） SMTMS （3 ）GTDC 4. D110 （1） AWS （2） SMTMS (3) GTDC (4) SMTMS 5. MS3608 （1） AWS （2） SMTMS （3） Precipitation 6. D105 （1） Precipitation (2) GTDC 7. MS3478(NPAM) （1） PAM （2） Precipitation 8. MS3637 （1） PAM （2） SMTMS （3） Precipitation 9. NODAA （1） SMTMS (2) Precipitation 10. WADD （1） SMTMS （2） Precipitation （3） Barometricmd 11. AQB （1） Precipitation 12. Dienpa (RS2) （1） Precipitation 13. Zuri （1） Precipitation （2） Barometricmd 14. Juze （1） Precipitation 15. Naqu hydrological station （1） Precipitation 16. MSofNaqu （1） Barometricmd 16. Naquradarsite （1）Radar system （2） Precipitation 17. Syangboche [Nepal] （1） AWS 18. Shiqu-anhe （1） AWS （2） GTDC 19. Seqin-Xiang （1） Barometricmd 20. NODA （1）Barometricmd （2） Precipitation （3) SMTMS 21. NaquHY （1） Barometricmd （2） Precipitation 22. NaquFx(BJ) （1） GTDC（2) PBLmd (3) Precipitation 23. MS3543 （1） Precipitation 24. MNofAmdo （1） Barometricmd 25. Mardi （1） Runoff 26. Gaize （1） AWS （2） GTDC （3） Sonde A CD of the data GAME-Tibet POP/IOP dataset cd （vol. 1) GAME-Tibet POP/IOP dataset cd （vol. 2)
MA Yaoming
This dataset contains eddy correlation instrument observation data from the Huyanglin station downstream of the Heihe Hydrological and Meteorological Observation Network from January 1, 2014 to December 31, 2014. The site is located in Sidaoqiao, Ejin Banner, Inner Mongolia, and the underlying surface is Populus euphratica. The latitude and longitude of the observation point is 101.1236E, 41.9928N, and the altitude is 876m. The vortex correlator has a height of 22 m and a sampling frequency of 10 Hz. The ultrasonic orientation is in the north direction, and the distance between the ultrasonic wind speed temperature meter (CSAT3) and the CO2/H2O analyzer (Li7500) is 17 cm. The original observation data of the eddy correlation meter is 10 Hz, and the released data is 30 minutes of data processed by Eddypro software. The main steps of the processing include: outlier removal, time-lag correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. At the same time, the quality evaluation of each flux value is conducted, it mainly contains atmosphere state stability test(Δst) and integrated turbulence characteristic test(ITC). The 30-min flux value output by Eddypro software was also screened: (1) data from the instrument error was eliminated; (2) data 1 h before and after precipitation was removed; (3) data from the deletion rate greater than 10% within every 30 min of the 10 Hz raw data. (4) eliminating observation data of weak turbulence at night (u* less than 0.1 m/s). The average time period of observation data is 30 minutes, 48 data per day, and the missing data is labeled -6999. Abnormal data caused by instrument drift and other reasons are marked in red. From February 21 to March 13, the data is missing due to problems in memory card and wireless transmission module. Published observations include: date/time Date/Time, wind direction Wdir(°), horizontal wind speed Wnd(m/s), lateral wind speed standard deviation Std_Uy(m/s), ultrasonic virtual temperature Tv(°C), water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar (m/s), stability Z/L (dimensionless), sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), sensible heat flux quality identification QA_Hs, latent heat flux quality identification QA_LE, carbon dioxide flux quality identification QA_Fc. The quality identification of sensible heat, latent heat, and carbon dioxide flux is divided into three levels (quality mark 0: (Δst <30, ITC<30); 1: (Δst <100, ITC<100); the rest is 2). The meaning of the data time, such as 0:30 represents an average of 0:00-0:30; the data is stored in *.xls format. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The dataset of ground truth measurement synchronizing with the airborne WiDAS mission was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jun. 1, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data included: (1) The radiative temperature of maize, wheat and the bare land in Yingke oasis maize field and Huazhaizi desert No. 1 plot by ThermaCAM SC2000 (1.2m above the ground, FOV = 24°×18°). The data included raw data (read by ThermaCAM Researcher 2001), recorded data and the blackbody calibrated data (archived in Excel format). (2) The radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 1.0; from Institute of Remote Sensing Applications), observing straight downwards at intervals of 1s in Yingke oasis maize field. Raw data, blackbody calibrated data and processed data were all archived in Excel format. (3) FPAR (Fraction of Photosynthetically Active Radiation) of maize and wheat by SUNSACN and the digital camera in Yingke oasis maize field. FPAR= (canopyPAR－surface transmissionPAR－canopy reflection PAR+surface reflectionPAR) /canopy PAR; APAR=FPAR* canopy PAR. Data were archived in Excel format. (4) The reflectance spectra by ASD in Yingke oasis maize field (350-2500nm , from BNU, the vertical canopy observation and the transect observation), and Huazhaizi desert No. 1 plot (350-2500nm , from Cold and Arid Regions Environmental and Engineering Research Institute, CAS, the NE-SW diagonal observation at intervals of 30m). The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (5) Maize albedo by the shortwave radiometer in Yingke oasis maize field. R =10H (R for FOV radius; H for the probe height). Data were archived in Excel format. (6) The radiative temperature by the handheld radiometer in Yingke oasis maize field (from BNU, the vertical canopy observation, the transect observation and the diagonal observation), Yingke oasis wheat field (only for the transect temperature), and Huazhaizi desert No. 1 plot (the NE-SW diagonal observation). Besides, the maize radiative temperature and the physical temperature were also measured both by the handheld radiometer and the probe thermometer in the maize plot of 30m near the resort. The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (7) Atmospheric parameters on the playroom roof at the resort by CE318 (produced by CIMEL in France). The underlying surface was mainly composed of crops and the forest (1526m high). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in .k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (8) Narrow channel emissivity of the bare land and vegetation by the W-shaped determinator in Huazhaizi desert No. 1 plot. Four circumstances should be considered for emissivity, with the lid plus the au-plating board, the au-plating board only, the lid only and without both. Data were archived in Word.
CHEN Ling, HE Tao, REN Huazhong, REN Zhixing, YAN Guangkuo, ZHANG Wuming, XU Zhen, LI Xin, GE Yingchun, SHU Lele, JIANG Xi, HUANG Chunlin, GUANG Jie, LI Li, LIU Sihan, WANG Ying, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, LIU Xiaocheng, TAO Xin, CHEN Shaohui, LIANG Wenguang, LI Xiaoyu, CHENG Zhanhui, Liu Liangyun, YANG Tianfu
This dataset contains the flux measurements from the Bajitan Gobi station eddy covariance system (EC) in the flux observation matrix from 31 May to 15 September, 2012. The site (100.30420° E, 38.91496° N) was located in Gobi surface, which is near Zhangye, Gansu Province. The elevation is 1562.00 m. The EC was installed at a height of 4.6 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&Li7500) was 0.15 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.
LI Xin, XU Ziwei
This dataset contains the flux measurements from site No.1 eddy covariance system (EC) in the flux observation matrix from 4 June to 17 September 2012. The site (100.35813° E, 38.89322° N) was located in a cropland (vegetable surface) in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 m. The EC was installed at a height of 3.8 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 (Gill&Li7500A) was 0.2 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack 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.
LIU Shaomin, LI Xin, XU Ziwei
This dataset includes the emissivity spectrum of typical ground objects in middle researches of the Heihe river basin. This dataset was acquired in oasis, desert, Gobi and wetland of experiment area. Time range starts from 2012-05-25 to 2012-07-18 (UTC+8). Instrument: MODEL 102F PORTABLE FTIR (Fourier Transform Infrared Spectrometer), Handheld infrared thermometer. Measurement methods: at the first step, measure the thermal radiance of cold blackbody, warm blackbody, sample and gold plate (Downwelling Radiance). The radiance of cold blackbody and warm blackbody was used to calibrate the instrument, and eliminate the “noise” caused by the device itself. The retrieval of emissivity and temperature was then performed using iterative spectrally smooth temperature-emissivity separation (ISSTES) algorithm. The retrieved emissivity spectrum range from 8 to 14 μm, with spectral resolution of 4cm-1. Dataset contains the original recorded spectra (in ASCII format) and the log files (in doc format). The processed data are emissivity curves (ASCII) that ranged from 8 to 14 μm, and the temperatures of samples. Thermal photos of the sample, digital photo of the scene and the object are recorded in some cases.
MA Mingguo
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