HiWATER: Dataset of hydrometeorological observation network (an observation system of meteorological elements gradient of A’rou Superstation, 2013)- A Big Earth Data Platform for Three Poles

This dataset includes data recorded by the Hydrometeorological observation network obtained from an observation system of Meteorological elements gradient of A’rou Superstation between 14 October, 2012, and 31 December, 2013. The site (100.464° E, 38.047° N) was located on a cold grassland surface in the Caodaban village, A’rou Town, Qilian County, Qinghai Province. The elevation is 3033 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45C; 1, 2, 5, 10, 15 and 25 m, towards north), wind speed profile (010C; 1, 2, 5, 10, 15 and 25 m, towards north), wind direction profile (020C; 2 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 5 m, towards south), four-component radiometer (CNR4; 5 m, towards south), two infrared temperature sensors (SI-111; 5 m, towards south, vertically downward), photosynthetically active radiation (PAR-LITE; 5 m, towards south, vertically upward), soil heat flux (HFP01SC; 3 duplicates, -0.06 m, 2 m in the south of tower), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m, 2 m in the south of tower), soil temperature profile (109; 0, -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m), and soil moisture profile (CS616; -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m).

The observations included the following: air temperature and humidity (Ta_1 m, Ta_2 m, Ta_5 m, Ta_10 m, Ta_15 m and Ta_25 m; RH_1 m, RH_2 m, RH_5 m, RH_10 m, RH_15 m and RH_25 m) (℃ and %, respectively), wind speed (Ws_1 m, Ws_2 m, Ws_5 m, Ws_10 m, Ws_15 m and Ws_25 m) (m/s), wind direction (WD_2 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/m2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation (PAR) (μmol/(s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm_1, Ts_4 cm_2, Ts_4 cm_3, Ts_6 cm, Ts_10 cm_1, Ts_10 cm_2, Ts_10 cm_3, Ts_15 cm, Ts_20 cm, Ts_30 cm, Ts_40 cm, Ts_60 cm, Ts_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm, Ts_240 cm, Ts_280 cm and Ts_320 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm_1, Ms_4 cm_2, Ms_4 cm_3, Ms_6 cm, Ms_10 cm_1, Ms_10 cm_2, Ms_10 cm_3, Ms_15 cm, Ms_20 cm, Ms_30 cm, Ms_40 cm, Ms_60 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 cm, Ms_240 cm, Ms_280 cm and Ms_320 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 AWS data were averaged over intervals of 30 min before 4 December, 2012 for a total of 48 records per day). The average soil temperature, soil heat flux, soil temperature and soil moisture were missing during 30 November, 2012 and 8 December, 2012, 21 April, 2013 and 31 May, 2013 because of insufficient power supply; Wind speed in 2 m and 5 m were missing during 28 December, 2012 and 28 March, 2012 because of datalogger repairing. 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: 2013-6-10 10:30. (6) the naming rule is: AWS+ site name.

For information of hydrometeorological network or station, please refer to Liu et al.(2018), and for observation data processing, please refer to Liu et al.(2011).

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Liu, S., Li, X., Che, T., Xu, Z., Zhang, Y., Tan, J. (2016). HiWATER: Dataset of hydrometeorological observation network (an observation system of meteorological elements gradient of A’rou Superstation, 2013). A Big Earth Data Platform for Three Poles, DOI: 10.3972/hiwater.175.2014.db. CSTR: 18406.11.hiwater.175.2014.db. (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. 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. (2019). Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China. Earth System Science Data, 11, 1483-1499( View Details | Download | Bibtex)

3. 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.Zhou, J., Li, M.S., Liu, S.M., Jia, Z.Z., &Ma, Y.F. (2015). Validation and performance evaluations of methods for estimating land surface temperatures from ASTER data in the middle reach of the Heihe River Basin, Northwest China. Remote Sensing, 7, 7126-7156. (View Details )

2.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 )

3.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 )

4.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 )

5.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 )

6.Zhang, L., Sun, R., Xu, Z.W., Qiao, C., &Jiang, G.Q. (2015). Diurnal and Seasonal Variations in Carbon Dioxide Exchange in Ecosystems in the Zhangye Oasis Area, Northwest China. PLOS ONE, 10(6). (View Details )

7.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 )

8.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 )

9.Song, L.S., Liu, S.M., William Kustas, P., Zhou, J., &Ma, Y.F. (2015). Using the Surface Temperature-Albedo Space to Separate Regional Soil and Vegetation Temperatures from ASTER Data. Remote Sensing, 7(5), 5828-5848. (View Details | Download )

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.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 )

12.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 )

13.Li Xin, Liu Shaomin, Ma Mingguo, Xiao Qing, Liu Qinhuo, Jin Rui, Che Tao. HiWATER: An Integrated Remote Sensing Experiment on Hydrological and Ecological Processes in the Heihe River Basin. Advances in Earth Science, 2012, 27(5): 481-498. (View Details | Download )

14.Wang, J.M., Zhuang, J.X., Wang, W.Z., Liu, S.M., &Xu, Z.W. (2015). Assessment of uncertainties in eddy covariance flux measurement based on intensive flux matrix of HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 12(2), 259-263. (View Details )

15.Song, L.S., Liu, S.M., Zhang, X., Zhou, J., & Li, M.S. (2015). Estimating and Validating Soil Evaporation and Crop Transpiration During the HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 12(2), 334-338. (View Details | Download )

16.Ge, Y., Liang, Y.Z., Wang, J.H., Zhao, Q.Y., &Liu, S.M. (2015). Upscaling sensible heat fluxes with area-to-area regression kriging. IEEE Geoscience and Remote Sensing Letters, 12(3), 656-660. (View Details )

17.Hu, M.G., Wang, J.H., Ge, Y., Liu, M.X., Liu, S.M., Xu, Z.W., &Xu, T.R. (2015). Scaling Flux Tower Observations of Sensible Heat Flux Using Weighted Area-to-Area Regression Kriging. Atmosphere, 6(8), 1032-1044. (View Details | Download )

18.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 )

19.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. doi:10.1109/LGRS.2014.2356652. (View Details )

20.Xu, T., Liu, S., Xu, L., Chen ,Y., Jia, Z., Xu, Z., &Nielson, J. (2015). Temporal Upscaling and Reconstruction of Thermal Remotely Sensed Instantaneous Evapotranspiration. Remote Sensing, 7(3), 3400-3425. (View Details | Download )

21.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 )

22.Li X, Cheng GD, Liu SM, Xiao Q, Ma MG, Jin R, Che T, Liu QH, Wang WZ, Qi Y, Wen JG, Li HY, Zhu GF, Guo JW, Ran YH, Wang SG, Zhu ZL, Zhou J, Hu XL, Xu ZW. Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific objectives and experimental design. Bulletin of the American Meteorological Society, 2013, 94(8): 1145-1160, 10.1175/BAMS-D-12-00154.1. (View Details )

23.Li, Y., Sun, R., &Liu, S.M. (2015). Vegetation Physiological Parameters Setting in the Simple Biosphere Model 2 (SiB2) for alpine meadows in upper reaches of Heihe River. Science China Earth Sciences, 58(5), 755-769. (View Details | Download )

24.Wang, Binbin, Ma, Yaoming, Chen, Xuelong, Ma, Weiqiang, Su, Zhongbo, Menenti, Massimo. Observation and simulation of lake-air heat and water transfer processes in a high-altitude shallow lake on the Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 2015, 120(24):2015JD023863. doi:10.1002/2015JD023863 (View Details )

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National Natural Science Foundation of China (No:91125002)

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