Dataset of Heihe integrated observatory network (eddy covariance system of Dashalong station, 2025)

English name

CSTR

CSTR:11738.11.ncdc.heihe.db7611.2026

DOI

10.12072/ncdc.heihe.db7611.2026

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Category

Meteorology

Contributors

Liu shaomin , Xu ziwei , Che Tao , Zhang Yang , Tan Junlei , Ren zhiguo

Datasets description

This dataset contains the flux measurements from the Dashalong station eddy covariance system (EC) in the upstream reaches of the Heihe integrated observatory network from January 1 to December 30 in 2025. The site (98.9406° E, 38.8399° N) was located in the Qilian County in Qinghai Province. The elevation is 3739 m. The EC was installed at a height of 4.5 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&Li7500RS) 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 -9999. 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. (2018) and Che et al. (2019).

Base information

collect time	2025/01/01 - 2025/12/30
collect place	Dashalon Station upstream of the Comprehensive Observation Network of Surface Processes in the Heihe River Basin
altitude	3739.0m - 3739.0m
data size	1.9 MiB
data format	*.xlsx
Data spatial resolution (/ M)	--
Data time resolution	30 min

Data source description

Dashalong station in the upper stream of the Heihe integrated observatory network.

Project information

#	number	name	type
1	XDA20100101	Pan-Third Pole Environmental Change and Green Silk Road Construction Special Project (XDA20100101)

Citations and annotations

In order to protect the rights and interests of the platform's scientific and technological resources, expand the services of the platform center, and enhance the application potential of scientific and technological resources, resource users are requested to mark and quote the research results (including published papers, treatises, data products, unpublished research reports, data products, etc.) generated by the use of resources in the following manner.

For the achievements published in English, please refer to the following specifications： The dataset is provided by National Cryosphere Desert Data Center. (https://www.ncdc.ac.cn).

Data reference

Liu shaomin, Xu ziwei, Che Tao, Zhang Yang, Tan Junlei, Ren zhiguo. Dataset of Heihe integrated observatory network (eddy covariance system of Dashalong station, 2025). National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2026. https://cstr.cn/CSTR:11738.11.ncdc.heihe.db7611.2026.
Liu shaomin, Xu ziwei, Che Tao, Zhang Yang, Tan Junlei, Ren zhiguo. Dataset of Heihe integrated observatory network (eddy covariance system of Dashalong station, 2025). National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2026. https://www.doi.org/10.12072/ncdc.heihe.db7611.2026.

EndnoteEN BibtexEN RISEN

Papers to be cited

Che T, Li X, Liu S, Li H, Xu Z, Tan J, Zhang Y, Ren Z, Xiao L, Deng J, Jin R, Ma M, Wang J, Yang X. Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China[J/OL]. Earth System Science Data, 2019, 11(3): 1483-1499. DOI: 10.5194/essd-11-1483-2019.

Reference format： Endnote Bibtex RIS
Liu Shaomin, Li Xin, Xu Ziwei, Che Tao, Xiao Qing, Ma Mingguo, Liu Qinhuo, Jin Rui, Guo Jianwen, Wang Liangxu, Wang Weizhen, Qi Yuan, Li Hongyi, Xu Tongren, Ran Youhua, Hu Xiaoli, Shi Shengjin, Zhu Zhongli, Tan Junlei, Zhang Yang, Ren Zhiguo. [J].

Reference format： Endnote Bibtex RIS

license agreement

This work is licensed under CC BY 4.0 (Creative Commons Attribution 4.0 International License).

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#	title	file size
1	2025年黑河流域地表过程综合观测网大沙龙站EC-ok.xlsx	1.9 MiB

#	category	title	author	year
1	paper	Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China	T,Che,X,Li,S,Liu,H,Li,Z,Xu,J,Tan,Y,Zhang,Z,Ren,L,Xiao,J,Deng,R,Jin,M,Ma,J,Wang,X,Yang	2019
2	paper	The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China	Shaomin,Liu,Xin,Li,Ziwei,Xu,Tao,Che,Qing,Xiao,Mingguo,Ma,Qinhuo,Liu,Rui,Jin,Jianwen,Guo,Liangxu,Wang,Weizhen,Wang,Yuan,Qi,Hongyi,Li,Tongren,Xu,Youhua,Ran,Xiaoli,Hu,Shengjin,Shi,Zhongli,Zhu,Junlei,Tan,Yang,Zhang,Zhiguo,Ren	2018