Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of mixed forest station, 2018)

Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of mixed forest station, 2018)


This dataset includes data recorded by the Heihe integrated observatory network obtained from the automatic weather station (AWS) at the Sidaoqiao mixed forest station from January 1 to December 31, 2018. The site (101.134° E, 41.990° N) was located on a tamarix and populous forest (Tamarix chinensis Lour. and Populus euphratica Olivier.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 874 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (28 m, north), wind speed and direction profile (28 m, north), air pressure (in tamper box), rain gauge (28 m, south), four-component radiometer (24 m, south), two infrared temperature sensors (24 m, south, vertically downward), two photosynthetically active radiation (24 m, south, one vertically upward and one vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, -1.0, -1.6, -2.0, -2.4 m), and soil moisture profile (-0.02, -0.04, -0.1, -0.2, -0.4, -0.6, -1.0, -1.6, -2.0, -2.4 m).

The observations included the following: air temperature and humidity (Ta_28 m; RH_28 m) (℃ and %, respectively), wind speed (Ws_28 m) (m/s), wind direction (WD_28 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, Ts_100, Ts_160, Ts_200, Ts_240 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, Ms_100, Ms_160, Ms_200, Ms_240 cm) (%, volumetric water content).

The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. Due to the power loss of datalogger, there were occasionally data missing during January 1 to 9, and November 10 to December 14; (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. 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.


File naming and required software

Year+** observatory network+ site+ AWS


Data Citations Data citation guideline What's data citation?
Cite as:

Liu, S., Li, X., Che, T., Xu, Z., Ren, Z., Tan, J. (2019). Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (automatic weather station of mixed forest station, 2018). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Meteoro.tpdc.270771. CSTR: 18406.11.Meteoro.tpdc.270771. (Download the reference: RIS | Bibtex )

Related Literatures:

1. Liu, S.M., Li, X., Xu, Z.W., Che, T., Xiao, Q., Ma, M.G., Liu, Q.H., Jin, R., Guo, J.W., Wang, L.X., Wang, W.Z., Qi, Y., Li, H.Y., Xu, T.R., Ran, Y.H., Hu, X.L., Shi, S.J., Zhu, Z.L., Tan, J.L., Zhang, Y., & Ren, Z.G. (2018). The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China. Vadose Zone Journal, 17(1), 180072. doi:10.2136/vzj2018.04.0072.( View Details | Download | Bibtex)

2. 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 | Bibtex)

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


References literature

1.Xu, Z.W., Ma, Y.F., Liu, S.M., Shi, S.J., &Wang, J.M. (2017). Assessment of the energy balance closure under advective conditions and its impact using remote sensing data. Journal of Applied Meteorology and Climatology, 56, 127-140. (View Details | Download )

2.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 )

3.Song, L.S., Liu, S.M., Kustas, W.P., Zhou, J., Xu, Z.W., Xia, T., & Li, M.S. (2016). Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures. Agricultural and Forest Meteorology, 230-231, 8-19. (View Details | Download )

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Keywords
Geographic coverage
East: 101.13 West: 101.13
South: 41.99 North: 41.99
Details
  • Temporal resolution: Hourly
  • File size: 18 MB
  • Views: 10064
  • Downloads: 210
  • Access: Requestable
  • Temporal coverage: 2018-07-17 To 2019-07-16
  • Updated time: 2021-04-19
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