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This data set contains the observation data of 10 m tower eddy covariance instrument from January 1, 2017 to December 31, 2017. The site is located in donghuayuan Town, Huailai County, Hebei Province. The longitude and latitude of the observation point are 115.7880e, 40.3491n and 480m above sea level. The acquisition frequency of the eddy correlator is 10Hz, the height of the frame is 5m, the ultrasonic direction is due north, and the distance between the ultrasonic anemometer (csat3) and the CO2 / H2O analyzer (li7500a) is 15cm.

The released data is 30 minutes data obtained by post-processing the original collected 10Hz data by eddypro software. The main processing steps include: outlier value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction. At the same time, the quality evaluation of each flux value is mainly the test of atmospheric stability (Δ st) and turbulence similarity characteristics (ITC). The 30 min flux values output after processing were also screened: (1) the data of instrument error; (2) the data of 1 h before and after precipitation; (3) the data of 10 Hz original data missing more than 10% every 30 min; (4) the observation data of weak turbulence at night (U * less than 0.1 M / s) were eliminated. The average period of observation data is 30 minutes. There are 48 data in a day, and the missing data is marked as - 6999. From May 27 to July 22, the data was missing due to problems with the ultrasonic anemometer.

The observational data released by eddy correlator include date / time, wind direction WDIR (°), horizontal wind speed wnd (M / s) and standard deviation of lateral wind speed STD_ Uy (M / s), ultrasonic virtual temperature TV (k), water vapor density H2O (g / m3), carbon dioxide concentration CO2 (mg / m3), friction velocity ustar (M / s), obuhof length, sensible heat flux HS (w / m2), latent heat flux Le (w / M2), carbon dioxide flux FC (mg / (M2S)), quality identification of sensible heat flux QA_ HS, quality identification of latent heat flux QA_ LE。 The quality identification of sensible heat, latent heat and carbon dioxide flux can be divided into three levels (quality mark 0: (Δ st < 30, ITC < 30); 1: (Δ st < 100, ITC < 100); the rest are 2). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; the data is stored in *. XLS format.

Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing

File naming and required software

File naming method: **** station-####-xx tower-yyyy, where **** * represents the site name, #### # represents the site type, xx represents the tower height (meters), yyyy represents the data observation year
Data usage: this data is tabular data, which can be opened and viewed by WPS, Ecxel and other software

Data Citations Data citation guideline What's data citation?

Liu, S., Xu, Z. (2019). Multi-scale surface flux and meteorological elements observation dataset in the Hai River Basin (Huailai station-eddy covariance system-10m tower, 2017). A Big Earth Data Platform for Three Poles, DOI: 10.3972/haihe.008.2019.db. CSTR: 18406.11.haihe.008.2019.db. (Download the reference： RIS | Bibtex )

1. Liu, S.M., Xu, Z.W., Zhu, Z.L., Jia, Z.Z., &Zhu, M.J. (2013). Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China. Journal of Hydrology, 487, 24-38.( View Details | Bibtex)

2. Guo, A.L., Liu, S.M., Zhu, Z.L., Xu, Z.W., Xiao, Q., Ju, Q., Zhang, Y., & Yang, X.F. (2020). Impact of Lake/Reservoir Expansion and Shrinkage on Energy and Water Vapor Fluxes in the Surrounding Area. Journal of Geophysical Research: Atmospheres, 125, e2020JD032833. https://doi.org/10.1029/2020JD032833.( View Details | Bibtex)

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

References literature

1.Liu, S.M., Lu, L., Mao, D., & Jia, L. (2007). Evaluating parameterizations of aerodynamic resistance to heat transfer using field measurements. Hydrology and Earth System Sciences, 11(2), 769-283. (View Details | Download )

2.Jia, Z.Z., Liu, S.M., Xu, Z.W,, Chen, Y.J., & Zhu, M.J. (2012). Validation of remotely sensed evapotranspiration over the Hai River Basin, China. Journal of Geophysical Research, 117(D13). (View Details | Download )

3.Xu, Z.W., Liu, S.M., Li, X., Shi, S.J., Wang, J.M., Zhu, Z.L., Xu, T.R., Wang, W.Z., &Ma, M.G. (2013). Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE. Journal of Geophysical Research, 118, 13140-13157. (View Details | Download )

4.Liu, S.M., Xu, Z.W., Song, L.S., Zhao, Q.Y., Ge, Y., Xu, T.R., Ma, Y.F., Zhu, Z.L., Jia, Z.Z., &Zhang, F. (2016). Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology, 230-231, 97-113. (View Details | Download )

5.Liu, S.M., Xu, Z.W., Wang, W.Z., Bai, J., Jia, Z., Zhu, M., & Wang, J.M. (2011). A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem. Hydrology and Earth System Sciences, 15(4), 1291-1306. (View Details | Download )

6.Lu, L., Liu, S.M., Xu, Z.W., Yang, K., Cai, X.H., Jia, L., & Wang, J.M. (2009). The characteristics and parameterization of aerodynamic roughness length over heterogeneous surfaces. Advances in atmospheric sciences, 26(1), 180-190. (View Details | Download )

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

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