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Qilian mountains integrated observatory network: Dataset of Heihe integrated observatory network (large aperture scintillometer of A'rou superstation, 2018)

This dataset contains the flux measurements from the large aperture scintillometer (LAS) at Arou Superstation in the Heihe integrated observatory network from January 1 to December 31 in 2018. There were two types of LASs at Arou Superstation: BLS450 and zzlas, produced by Germany and China, respectively. 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. The site (north: 100.471° E, 38.057° N; south: 100.457° E, 38.038° 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 1 minute at both BLS450 and zzlas. 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: Mininum X Intensity<50; zzlas: 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 BLS450 and zzlas, respectively. Detailed can refer to Liu et al. (2011, 2013). 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 problems of storing and wireless transmission, data from 5 July to 24 August, were not collected. (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_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 *.xlsx format. 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.

2020-07-25

Qilian mountains integrated observatory network: Dataset of Heihe integrated observatory network (Phenology camera observation dataset of Arou superstation, 2018)

The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.

2020-07-25