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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Inventory dataset of glacial lakes in Himachal Pradesh, India (2004)
  • 2019-09-15
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This glacial lake inventory receives joint support from the International Centre for Integrated Mountain Development (ICIMOD) and United Nations Environment Programme/Regional Resource Centre, Asia and the Pacific (UNEP/RRC-AP). 5. This glacial lake inventory referred to Landsat 4/5 (MSS and TM), SPOT(XS), IRS-1C/1D(LISS-III) and other remote sensing data. It reflects the current situation of glacial lakes with areas larger than 0.01 km2 in 2004. 6. Glacial Lake Inventory Coverage: Yamuna basin, Ravi basin, Chenab basin, Satluj River Basin and others. 7. The Glacial Lake Inventory includes glacial lake inventory, glacial lake type, glacial lake width, glacial lake orientation, glacial lake length from the glacier and other attributes. 8. Projection parameter: Projection: Albers Equal Area Conic Ellipsoid: WGS 84 Datum: WGS 1984 False easting: 0.0000000 False northing: 0.0000000 Central meridian: 82° 30’E Central parallel: 0° 0’ N Latitude of first parallel: 20° N Latitude of second parallel: 35° N For a detailed data description, please refer to the data file and report.

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Surface DEM for typical glaciers on the Tibetan Plateau (Version 1.0) (2003)
  • 2019-09-15
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The DEMs of the typical glaciers on the Tibetan Plateau were provided by the bistatic InSAR method. The data were collected on November 21, 2013. It covered Puruogangri and west Qilian Mountains with a spatial resolution of 10 meters, and an elevation accuracy of 0.8 m which met the requirements of national 1:10 000 topographic mapping. Considering the characteristics of the bistatic InSAR in terms of imaging geometry and phase unwrapping, based on the TanDEM-X bistatic InSAR data, and adopting the improved SAR interference processing method, the surface DEMs of the two typical glaciers above were generated with high resolution and precision. The data set was in GeoTIFF format, and each typical glacial DEM was stored in a folder. For details of the data, please refer to the Surface DEMs for typical glaciers on the Tibetan Plateau - Data Description.

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Dataset of typical glacier changes on Tibetan Plateau and Its surrounding areas (2005-2016)
  • 2019-09-15
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This is the data set of typical glacier changes on the Tibetan Plateau and its surrounding areas, which includes the Qiangyong Glacier near Yamdrog Yumtso, the Palong Glacier in the Palongzangbu River Basin, the Xiaodongkemadi Glacier on Tanggula Mountain in the central Tibetan Plateau, the No. 2 Anglong Glacier in the Ngari Prefecture in the western Tibetan Plateau, the Aerqieteke Glacier in the Muztagata region, the No. 15 Glacier, the Qiaodumake Glacier, and the Qiyi Glacier in the Qilian Mountains on the northeastern Tibetan Plateau. It can be used to study the response of typical glaciers in typical areas of the plateau to climate change. On the ice surface of a typical glacier in a typical area, a steam drill is used to set a length rod. The height of the rod is measured at a fixed time every year and combined with snow pit observations to observe the glacier mass balance. Marks are set on the ground near the terminus of the glacier, and the distance between the marker and the terminus of the glacier is measured to observe changes in the position of the terminus of the glacier. Among the glaciers, there are terminus change data for the Qiaodumake Glacier and No. 94 Palong Glacier. In the data set processing method, a continuous sequence of time and space is formed after the quality control of the original data. It conforms to the accuracy of conventional glacier monitoring and research in China and the world, and it meets the requirements of the comparative study of glacier changes and related climate change records.

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Oxygen isotope, dust, anion and accumulation data from the Guliya ice core (1992)
  • 2019-09-15
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This data set contains the oxygen isotope, dust, anion and accumulation data obtained from the deep ice core drilled in 1992 in the Guliya ice cap, which is located in the west Kunlun Mountains on the Tibetan Plateau. The length of the ice core was 308.6 m. The ice core was cut into samples, 12628 of which were used to measure the oxygen isotope values, 12480 of which were used to measure the dust concentrations, and 9681 of which were used to measure the anion concentrations. Data Resource: National Centers for Environmental Information(http://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/ice-core). Processing Method: Average. The data set contains 4 tables, namely: oxygen isotope, dust and anion data from different depths in the Guliya ice core, 10-year mean data of oxygen isotopes, dust, anions and net accumulation in the Guliya ice core, 400-year mean data of oxygen isotopes, dust and anions in the Guliya ice core, and chlorine-36 data from different depths. Table 1: Data on oxygen isotopes, dust and anion concentrations at different depths in the Guliya ice core. a. Name explanation Field 1: Depth Field 2: Oxygen isotope value Field 3: Dust concentration (diameter 0.63 to 20 µm) Field 4: Cl- Field 5: SO42- Field 6: NO3- b. Dimensions (unit of measure) Field 1: m Field 2: ‰ Field 3: particles/mL Field 4: ppb Field 5: ppb Field 6: ppb Table 2: 10-year mean oxygen isotope, dust, anion and net accumulation data for the Guliya ice core (0-1989) a. Name explanation Field 1: Start time Field 2: End time Field 3: Oxygen isotope value Field 4: Dust concentration (diameter 0.63 -20 µm) Field 5: Cl- Field 6: SO42- Field 7: NO3- Field 8: Net accumulation b. Dimensions (unit of measure) Field 1: Dimensionless Field 2: Dimensionless Field 3: ‰ Field 4: particles/mL Field 5: ppb Field 6: ppb Field 7: ppb Field 8: cm/year Table 3: 400-year mean oxygen isotope, dust and anion data for the Guliya ice core. a. Name explanation Field 1: Time Field 2: Oxygen isotope Field 3: Dust concentration (diameter 0.63-20 µm) Field 4: Cl- Field 5: SO42- Field 6: NO3- b. Dimensions (unit of measure) Field 1: Millennium Field 2: ‰ Field 3: particles/mL Field 4: ppb Field 5: ppb Field 6: ppb Table 4: Chlorine-36 data at different depths a. Name explanation Field 1: Depth Field 2: 36Cl Field 3: 36Cl error Field 4: Year b. Dimensions (unit of measure) Field 1: m Field 2: 104 atoms g-1 Field 3: % Field 4: Millennium

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Oxygen Isotope, dust, anion and accumulation data from the Dunde Ice Core (1987)
  • 2019-09-15
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This data set contains data from the three ice cores drilled from the Dunde ice cap in the northern Tibetan Plateau in 1987. Core D-1 has a length of 139.8 m and is divided into 3585 samples for isotope analysis. Core D-3 has a length of 138.4 m, and the upper 56 m was cut into several samples on site and stored in bottles after melting, while the remaining length was frozen and preserved. The data set contains three data tables, namely, 10-year mean oxygen isotope data for the Dunde ice core (520-1987 A.D.), 5-year mean water equivalent accumulation data for Dunde ice core and 10-year mean dust data for the Dunde ice core. Data source: National Centers for Environmental Information (http://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/ice-core). Processing method: Average. Table 1: 10-year mean oxygen isotope data for core D-3 (520 - 1987 A.D.) a. Name explanation Field 1: Start time Field 2: End time Field 3: Oxygen isotope value b. Dimensions (units of measure) Field 1: Dimensionless Field 2: Dimensionless Field 3: ‰ Data Table 2: 5-year mean water equivalent accumulation data for core D-1 (1606-1984) a. Name explanation Field 1: Start time Field 2: End time Field 3: Accumulation b. Dimensions (units of measure) Field 1: Dimensionless Field 2: Dimensionless Field 3: m Data Sheet 3: 10-year mean dust data for core D-3 (520 - 1987 A.D.) a. Name explanation Field 1: Start time Field 2: End time Field 3: Dust (diameter 0.63-16 µm) Field 4: Dust (diameter 2.00-60 µm) Field 5: Cl- Field 6: SO42- Field 7: NO3- b. Dimensions (units of measure) Field 1: Dimensionless Field 2: Dimensionless Field 3: Particles/mL Field 4: Particles/mL Field 5: ppb Field 6: ppb Field 7: ppb

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Glacier data product in Tibetan Plateau (1976)
  • 2019-09-15
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The Tibetan Plateau Glacial Data Product-TPG1976 is a glacial attribute product of the Tibetan Plateau around 1976. It was generated by remote sensing visual interpretation method adopting Landsat MSS multispectral data. The temporal coverage of the data were from 1972 to 1979. 61% of the remote sensing data were from 1976 to 1977. The data covered the Tibetan Plateau with a spatial resolution of approximately 60 m. Considering the large error of automatic remote sensing extraction method caused by the impact of cloud, shadow and seasonal snow on glacier area, the remote sensing inversion method adopted manual visual interpretation. By comparing the results of automatic methods and visual interpretation of glacier boundaries based on experts’ experiences, we know that the manual interpretation based on remote sensing images is still the most accurate method to obtain the glacier vector boundary at present. When selecting remote sensing images, the minimum effects of cloud and seasonal snow were mainly considered. Images of summer and cold season were both selected (different from the principle applied in selecting remote sensing image data source for China's second glacier inventory). At the same time, considering the differences in discriminant standards between different interpreters, the comparison of multiple typical regions showed that the relative deviation of manual visual interpretation was less than 4%. Based on the Arc map software platform, the abovementioned remote sensing images were geometrically corrected, and the final glacier vector boundary data were obtained by visual interpretation. According to the format and requirements of the second glacier inventory in China, the glacier code and area statistics were collected, and the elevation attribute data of each glacier was obtained based on the SRTM DEM data, and finally the 1976 glacial data product of the Tibetan Plateau was obtained.

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Inventory data of glacial lake in west China (2015)
  • 2019-09-15
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This data set is based on China's second inventory data, Landsat series optical image data with a spatial resolution of 30 meters and cloud coverage of less than 10% and SRTM and other data using ArcGIS, ENVI, Google Earth and other processing software and extracting the glacial lake boundary within 10 km of the glacier boundary by artificial visual interpretation. In addition, the data set adds attributes such as glacial lake type, the mountain range, the province, and the basin to the data as well as quality checking and accuracy verification for the interpreted data. The spatial resolution is 30 meters. It consists of two parts: the glacial lake distribution area vector file and the Inventory Data set of glacial lakes in west China in 2015. It can provide reference data for glacial lake-glacier coupling, water resource utilization and management in west China and can also be used as basic data for regional climate change and cryospheric studies.

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The observation dataset of glacial hydrological stations in the Namco Basin (2006-2008)
  • 2019-09-14
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This data set comprises the observed runoff data of the glacial hydrological stations in the Namco Basin in Tibet from 2006 to 2008. It contains monthly mean runoff data from four regions: the Niyaqu river, Qugaqie river, Zhadang river, and Angqu river. The data were used to study the regional hydrology and water resources. Measurement instrument: propeller flow velocity meter (LS1206B), Hobo water level meter. Spatial location: Niyaqu, East Namco (the road near the lake outlet): 90.2969E, 31.0342N, elevation: 4730 m; Qugaqie, South Namco (road into the lake outlet): 90.6361E, 30.8175N, elevation: 4780 m; End of the Zhadang Glacier: 90.7261E, 30.6878N, elevation: 5400 m; Angqu (bridge near Deqing Town): 90.2839E, 30.6525N, elevation: 4780 m.

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Data on glacial lakes in the TPE (V1.0) (1990, 2000, 2010)
  • 2019-09-14
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There are three types of glacial lakes: supraglacial lakes, lakes attached to the end of the glacier and lakes not attached to the end of the glacier. Based on this classification, the following properties are studied: the variation in the number and area of glacial lakes in different basins in the Third Pole region, the changes in extent in terms of size and area, distance from glaciers, the differences in area changes between lakes with and without the supply of glacial melt water runoff, the characteristics of changes in the glacial lake area with respect to elevation, etc. Data source: Landsat TM/ETM+ 1990, 2000, 2010. The data were visually interpreted, which included checking and editing by comparing the original image with Google Earth images when the area was greater than 0.003 square kilometres. The data were applied to glacial lake changes and glacial lake outburst flood assessments in the Third Pole region. Data type: Vector data. Projected Coordinate System: Albers Conical Equal Area.

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