Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of the temperate steppe, 2020- A Big Earth Data Platform for Three Poles

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient from Janurary 1 to December 31 in 2020. The site (100°14'8.99"E, 37°14'49.00"N) was located in Sanjiaocheng sheep breeding farm, Gangcha County, Qinghai Province. The elevation is 3210m.The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5, 10 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; towards north), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -5.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -5.00m).

The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m; RH_3 m, RH_5 m, RH_10 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m) (°), precipitation (rain) (mm), air pressure (press) (hpa), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)), 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), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_400cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_400cm) (%, 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. (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: 2018/8/31 10:30.

File naming and required software

Year+** observatory network+ site+ AWS

Data Citations Data citation guideline What's data citation?

Cite as:

Li, X. (2021). Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of the temperate steppe, 2020. A Big Earth Data Platform for Three Poles, DOI: 10.11888/Meteoro.tpdc.271383. CSTR: 18406.11.Meteoro.tpdc.271383. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Li, X.Y., Yang, X.F., Ma, Y.J., Hu, G.R., Hu, X., Wu, X.C., Wang, P., Huang, Y.M., Cui, B.L., & Wei, J.Q. (2018). Qinghai Lake Basin Critical Zone Observatory on the Qinghai-Tibet Plateau. Vadose Zone Journal, 17(1).( View Details | Bibtex)

2. Li, X.Y., Ma, Y.J., Huang, Y.M., Hu, X., Wu, X.C., Wang, P., Li, G.Y., Zhang, S.Y., Wu, H.W., Jiang, Z.Y., Cui, B.L., & Liu, L. (2016). Evaporation and surface energy budget over the largest high-altitude saline lake on the Qinghai-Tibet Plateau. Journal of Geophysical Research: Atmospheres, 121(18), 10470-10485.( 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.Zhang, S.Y., Li, X.Y., Zhao, G.Q., &Huang, Y.M. (2016). Surface energy fluxes and controls of evapotranspiration in three alpine ecosystems of Qinghai Lake watershed, NE Qinghai-Tibet Plateau. Ecohydrology, 9(2), 267-279. (View Details )

2.Zhang, S.Y., Li, X.Y., Ma, Y.J., Zhao, G.Q., Li, L., Chen, J., Jiang, Z.Y., & Huang, Y.M. (2014). Interannual and Seasonal Variability in Evapotranspiration and Energy Partitioning over the Alpine Riparian ShrubMyricaria SquamosaDesv. on Qinghai-Tibet Plateau. Cold Regions Science and Technology, 102, 8-20. (View Details )

3.Yu, G.R., Zhu, X.J., Fu, Y.L., He, H.L., Wang, Q.F., Wen, X.F., Li, X.R., Zhang, L.M., Zhang, L., Su, W., Li, S.G., Sun, X.M., Zhang, Y.P., Zhang, J.H., Yan, J.H., Wang, H.M., Zhou, G.S., Jia, B.R., Xiang, W.H., Li, Y.N., Zhao, L., Wang, Y.F., Shi, P.L., Chen, S.P., Zhao, F.H., Wang, Y.Y., & Tong, C.L. (2013). Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China. Global Change Biology, 19, 798–810. (View Details )

4.Gu, S., Tang, Y.H., Du, M.Y., Kato, T., Li, Y.N., Cui, X.Y., &Zhao, X.Q. (2003). Short term variation of NEE in relation to environmental controls in an alpine meadow on the Qinghai-Tibetan Plateau, Journal of Geophysical Research, 108(D21), 4670. (View Details )

5.Fu, Y., Zheng, Z., Yu, G., Hu, Z., Sun, X., Shi, P., Wang, Y., & Zhao, X. (2009). Environmental influences on carbon dioxide fluxes over three grassland ecosystems in China. Biogeosciences, 6, 2879–2893. (View Details )

6.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 )

7.Liu, S., Li, X., Xu, Z., Che, T., Xiao, Q., Ma, M., Liu, Q., Jin, R., Guo, J., Wang, L., Wang, W., Qi, Y., Li, H., Xu, T., Ran, Y., Hu, X., Shi, S., Zhu, Z., Tan, J., Zhang, Y., Ren, Z. (2018). The Heihe Integrated Observatory Network: A basin‐scale land surface processes observatory in China. Vadose Zone Journal, 17,180072. https://doi.org/10.2136/vzj2018.04.0072. (View Details )

8.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 )

9.Song, L.S., Kustas WP, Liu, S.M., Colaizzi PD, Nieto H, Xu, Z.W., Ma, Y.F., Li, M.S., Xu, T.R., Agam, N., Tolk, J., & Evett, S. (2016). Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions. Journal of Hydrology, doi:10.1016/j.jhydrol.2016.06.034. (View Details )

10.Zhang, Q., Sun, R., Jiang, G.Q., Xu, Z.W., & Liu, S.M. (2016). Carbon and energy flux from a Phragmites australis wetland in Zhangye oasis-desert area, China. Agricultural and Forest Meteorology, 230-231, 45-57. (View Details )

11.Xu, T.R., Bateni, S.M., & Liang, S.L. (2015). Estimating turbulent heat fluxes with a weak-constraint data assimilation scheme: A case study (HiWATER-MUSOEXE). IEEE Geoscience and Remote Sensing Letters, 12(1), 68-72. (View Details )

12.Su, P.X., Yan, Q.D., Xie, T.T., Zhou,Z.J., & Gao, S. (2012). Associated growth of C3 and C4 desert plants helps the C3 species at the cost of the C4 species. Acta Physiologiae Plantarum, 34(6), 2057-2068. (View Details )

13.Zhu, Z.L., Tan, L., Gao, S.G., &Jiao, Q.S. (2015). Oberservation on soil moisture of irrigated cropland by cosmic-ray probe. IEEE Geoscience and Remote Sensing Letters, 12(3), 472-476. (View Details )

14.Bai, J., Jia, L., Liu, S., Xu, Z., Hu, G., Zhu, M., &Song, L. (2015). Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes. IEEE Geoscience and Remote Sensing Letters, 12(5), 943-947. (View Details | Download )

15.Xu, T.R., Liu, S.M., Xu, Z.W., Liang, S.L., &Xu, L. (2015). A dual-pass data assimilation scheme for estimating surface fluxes with FY3A-VIRR land surface temperature. Science China Earth Science, 58(2), 211-230. (View Details | Download )

16.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 )

17.Gao, S.G., Zhu, Z.L., Liu, S.M., Jin, R., Yang, G.C., Tan, L. (2014). Estimating spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing. International Journal of Applied Earth Observation and Geoinformation, 32, 54-66. doi:10.1016/j.jag.2014.03.003. (View Details )

18.Ma, Y.F., Liu, S.M., Zhang, F., Zhou, J., &Jia, Z.Z. (2015). Estimations of regional surface energy fluxes over heterogeneous oasis-desert surfaces in the middle reaches of the Heihe River during HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 12(3), 671-675. (View Details )

Support Program

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

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

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