This data set comes from the Land use data of Zhangye city in 2005 completed by YAN Changzhen and others from Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The data was generated by manual interpretation based on Landsat TM and ETM remote sensing data around 2005. This data uses a hierarchical land cover classification system. There are six first-class classifications (cultivated land, woodland, grassland, waters, urban and rural areas, industrial and mining, residential land and unused land), and 25 second-class classifications covering five counties and one district of Zhangye City, Gansu Province. The land use classification criteria used by the Chinese Academy of Sciences since 1986 are adopted in this data. The data type is vector polygon, stored in Shape format, and the data range covers Zhangye City.
The dataset of surface roughness measurements was obtained in No. 1 and 2 quadrates of the E’bao foci experimental area during the pre-observation period. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. With the roughness board 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively.
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 calculated based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II.
The original photos of each sampling point, surface height standard deviation (cm) and correlation length (cm) were archived. 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 .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 needles is also included for further validation.
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at site No.1 in the flux observation matrix. There were two types of LASs at site No.1: German BLS900 and China zzlas. The observation periods were from 7 June to 19 September, 2012, and 16 June to 19 September, 2012, for the BLS900 and the zzlas, respectively. The north tower is placed with the receiver of BLS900 and the transmitter of zzlas, and the south tower is placed with the transmitter of BLS900 and the receiver of zzlas. The site (north: 100.352° E, 38.884° N; south: 100.351° E, 38.855° 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 3256 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>3.05E-14). (2) Data were rejected when the demodulation signal was small (BLS900: 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 BLS900 measurements; missing flux measurements from the BLS900 were filled with measurements from the zzlas. 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.
This dataset contains the flux measurements from the Sidaoqiao superstation eddy covariance system (EC) in the downstream reaches of the Heihe integrated observatory network from January 1 to December 31 in 2018. The site (101.1374° E, 42.0012° N) was located in the Ejina Banner in Inner Mongolia Autonomous Region . The elevation is 873 m. The EC was installed at a height of 3.2 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 (CSAT3&Li7500A) was 0.15 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 10% of the 30 min raw record. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Latent heat flux during November 9 to 21, 2018 were missing due to the sensor malfunction of CO2/H2O gas analyzer.
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/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (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). 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.
For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.
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