The dataset of spatio-temporal water resources distribution in the source regions of Yangtze River and Yellow River (1998-2017)
  • 2019-09-22
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This data is a simulated output data set of 5km monthly hydrological data obtained by establishing the WEB-DHM distributed hydrological model of the source regions of Yangtze River and Yellow River, using temperature, precipitation and pressure as input data, and GAME-TIBET data as verification data. The dataset includes grid runoff and evaporation (if the evaporation is less than 0, it means deposition; if the runoff is less than 0, it means that the precipitation in the month is less than evaporation). This data is a model based on the WEB-DHM distributed hydrological model, and established by using temperature, and precipitation (from itp-forcing and CMA) as input data, GLASS, MODIA, AVHRR as vegetation data, and SOILGRID and FAO as soil parameters. And by the calibration and verification of runoff,soil temperature and soil humidity, the 5 km monthly grid runoff and evaporation in the source regions of Yangtze River and Yellow River from 1998 to 2017 was obtained. If asc can't open normally in arcmap, please delete the blacks space of the top 5 lines of the asc file.

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The daily microwave precipitation dataset of Tibetan Plateau(2015-2017)
  • 2019-09-22
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The strong spatial and temporal changes of precipitation often make it impossible to accurately know the spatial distribution and intensity changes of precipitation during the precipitation observation of conventional foundation stations. Satellite microwave remote sensing can overcome this limitation and achieve global scale precipitation and cloud observation. Compared with infrared/visible light, which can only reflect cloud thickness and cloud height, microwave can penetrate the cloud, and also use the interaction between precipitation and cloud particles in the cloud and microwave to detect the cloud and rain more directly. This data use the surface precipitation, obtained by the DPR double wave band precipitation radar carried by GPM, as the true value, soil temperature/humidity of NDVI, DEM and ERA5 as reference data. And the multi-band passive brightness temperature data of GMI is used to invert the instantaneous precipitation intensity during the warm season (May-September) in Tibetan Plateau, then the result is re-sampled to the spatial resolution of 0.1°and accumulated them to a day.

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Precipitation observation data of Jaggang Snow Mountain (2016-2017)
  • 2019-09-15
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This is the precipitation observation data of the observation point in Jaggang Snow Mountain. It can be used in Glaciology, Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from September 14, 2016 to June 19, 2017. It is measured by automatic rain gauge and a piece of data is recorded every 60 minutes. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.

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WATER: Dataset of CMA operational meteorological stations observations in the Heihe River Basin
  • 2019-09-15
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The dataset of CMA operational meteorological stations observations in the Heihe river basin were provided by Gansu Meteorological Administration and Qinghai Meteorological Administration. It included: (1) Diurnal precipitation, sunshine, evaporation, the wind speed, the air temperature and air humidity (2, 8, 14 and 20 o'clock) in Mazongshan, Yumen touwnship, Dingxin, Jinta, Jiuquan, Gaotai, Linze, Sunan, Zhangye, Mingle, Shandan and Yongchang in Gansu province (2) the wind direction and speed, the temperature and the dew-point spread (8 and 20 o'clock; 850, 700, 600, 500, 400, 300, 250, 200, 150, 100 and 50hpa) in Jiuquan, Zhangye and Mingqin in Gansu province and Golmud, Doulan and Xining in Qinghai province (3) the surface temperature, the dew point, the air pressure, the voltage transformation (3 hours and 24 hours), the weather phenomena (the present and the past), variable temperatures, visibility, cloudage, the wind direction and speed, precipitation within six hours and unusual weather in Jiuquan, Sunan, Jinta, Dingxin, Mingle, Zhangye, Gaotai, Shandan, Linze, Yongchang and Mingqin in Gansu province and Tuole, Yeniugao, Qilian, Menyuan, Xining, Gangcha and Huangyuan in Qinhai province.

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Precipitation observation data on Taerma Township (2016-2017)
  • 2019-09-15
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This is the precipitation observation data of the observation point in Taerma Township. It can be used in Glaciology, Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from September 15, 2016 to August 17, 2017. It is measured by automatic rain gauge and a piece of data is recorded every 60 minutes. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.

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HiWATER: Dataset of flux observation matrix (automatic meteorological station of No.17) of the MUlti-Scale Observation EXperiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)
  • 2019-09-15
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This dataset contains the automatic weather station (AWS) measurements from site No.17 in the flux observation matrix from 12 May to 17 September, 2012. The site (100.36972° E, 38.84510° N) was located in an orchard in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1559.63 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45C; 5 m, towards north), air pressure (PTB110; 2 m), rain gauge (52203; 10 m), wind speed and direction (034B; 10 m, towards north), a four-component radiometer (CNR1; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFP01; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). One of the infrared temperature sensors (IRT_2) was adjusted to a zenith angle of 50° after 6 August. The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_10 m, m/s), wind direction (WD_10 m, °), 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 IR_2, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_100 cm, ℃), and soil moisture profile (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_100 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

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Precipitation observation data of the Qiang-Tang Plateau (2017)
  • 2019-09-15
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This is the rain gauge precipitation observation data along Bange-Ali line in the Qiang-tang Plateau. It can be used to evaluate and improve the quality of satellite precipitation products, thereby improving the estimation accuracy of precipitation in the Qiangtang Plateau. The data is observed from June 19, 2016 to September 24, 2017. And a piece of data is recorded every 60 minutes. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.

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HiWATER: Dataset of flux observation matrix (automatic meteorological station of No.8) of the MUlti-Scale Observation EXperiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)
  • 2019-09-15
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This dataset contains the automatic weather station (AWS) measurements from site No.8 in the flux observation matrix from 14 May to 21 September, 2012. The site (100.37649° E, 38.87254° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1550.06 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed and direction (010C/020C; 10 m, towards north), a four-component radiometer (CNR4; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFP01; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_10 m, m/s), wind direction (WD_10 m, °), 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 IR_2, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_100 cm, ℃), and soil moisture profile (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_100 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

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HiWATER: Dataset of flux observation matrix (automatic meteorological station of No.1) of the MUlti-Scale Observation EXperiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)
  • 2019-09-15
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This dataset contains the automatic weather station (AWS) measurements from site No.1 in the flux observation matrix from 10 June to 17 September, 2012. The site (100.3582° E, 38.8932° N) was located in a cropland (vegetable surface) in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP155; 5 m, towards north), air pressure (PTB110; 2 m), rain gauge (TR525M; 10 m), wind speed and direction (03002; 10 m, towards north), a four-component radiometer (CNR4; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (SM300; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFP01; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). One of the infrared temperature sensors (IRT_2) was adjusted to a zenith angle of 50° after 6 August. The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_10 m, m/s), wind direction (WD_10 m, °), 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 IR_2, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_100 cm, ℃), and soil moisture profile (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_100 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

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HiWATER: Dataset of flux observation matrix (automatic meteorological station of No.10) of the MUlti-Scale Observation EXperiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)
  • 2019-09-15
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This dataset contains the automatic weather station (AWS) measurements from site No.10 in the flux observation matrix from 1 June to 17 September, 2012. The site (100.39572° E, 38.87567° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1534.73 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP155; 5 m, towards north), rain gauge (TE525M; 10 m), wind speed (03001; 10 m, towards north), a four-component radiometer (CNR1; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109ss-L; 0, -0.02, and -0.04 m), soil moisture profile (CS616; 0.02, 0.04 m), and soil heat flux (HFP01; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), precipitation (rain, mm), wind speed (Ws_10 m, m/s), 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 IR_2, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, and Ts_4 cm, ℃), and soil moisture profile (Ms_2 cm and Ms_4 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

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