Qilian Mountains integrated observatory network: cold and arid research network of Lanzhou university (eddy covariance system of Guazhou station, 2018)

Qilian Mountains integrated observatory network: cold and arid research network of Lanzhou university (eddy covariance system of Guazhou station, 2018)


This dataset contains the flux measurements from the Guazhou station eddy covariance system (EC) in the middle reaches of the Heihe integrated observatory network from September 24 to December 31 in 2018. The site (95.673E, 41.405N) was located in a desert in Liuyuan Guazhou, which is near Jiuquan city in Gansu Province. The elevation is 2016 m. The EC was installed at a height of 4.0 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 0.17 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. 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/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). 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. (2011) for data processing) in the Citation section.


File naming and required software

Year+** observatory network+ site no + EC.


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Cite as:

Zhang, R. (2019). Qilian Mountains integrated observatory network: cold and arid research network of Lanzhou university (eddy covariance system of Guazhou station, 2018). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Meteoro.tpdc.270800. CSTR: 18406.11.Meteoro.tpdc.270800. (Download the reference: RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.


Support Program

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)

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License: This work is licensed under an Attribution 4.0 International (CC BY 4.0)


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Keywords
Geographic coverage
East: 180.00 West: 180.00
South: 41.41 North: 41.41
Details
  • Temporal resolution: Hourly
  • File size: 0.6 MB
  • Views: 6249
  • Downloads: 603
  • Access: Open Access
  • Temporal coverage: 2018-01-19 To 2019-01-18
  • Updated time: 2021-04-19
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: ZHANG Renyi  

Distributor: A Big Earth Data Platform for Three Poles

Email: poles@itpcas.ac.cn

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