Pan-third-polar environmental change and green silk road construction

Brief Introduction: Pan-third-polar environmental change and green silk road construction

Number of Datasets: 1208

  • Meteorological monitoring data of Kara-Batkak glacier in the Western Tianshan Mountains of Kyrgyzstan(2020)

    Meteorological monitoring data of Kara-Batkak glacier in the Western Tianshan Mountains of Kyrgyzstan(2020)

    Kara batkak glacier weather station in Western Tianshan Mountains of Kyrgyzstan (42 ° 9'46 ″ n, 78 ° 16'21 ″ e, 3280m). The observational data include hourly meteorological elements (hourly rainfall (mm), instantaneous wind direction (°), instantaneous wind speed (M / s), 2-minute wind direction (°), 2-minute wind speed (M / s), 10 minute wind direction (°), 10 minute wind speed (M / s), maximum wind direction (°), maximum wind speed (M / s), maximum wind speed time, maximum wind direction (°), maximum wind speed (M / s), maximum wind speed time, maximum instantaneous wind speed within minutes) Direction (°), maximum instantaneous wind speed in minutes (M / s), air pressure (HPA), maximum air pressure (HPA), time of maximum air pressure, time of minimum air pressure (HPA), time of minimum air pressure. Meteorological observation elements, after accumulation and statistics, are processed into climate data to provide important data for planning, design and research of agriculture, forestry, industry, transportation, military, hydrology, medical and health, environmental protection and other departments.

    2022-04-18 2289 1

  • Meteorological observation data of Kunsha Glacier (2015-2017)

    Meteorological observation data of Kunsha Glacier (2015-2017)

    This data set includes the temperature, precipitation, relative humidity, wind speed, wind direction and other daily values in the observation point of Kunsha Glacier. The data is observed from October 3, 2015 to September 19, 2017. It is measured by automatic meteorological station (Onset Company) and a piece of data is recorded every 2 hours. 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.

    2022-04-18 3860 263

  • Glacier inventory of Qilian Mountain Area (2020)

    Glacier inventory of Qilian Mountain Area (2020)

    This dataset contains the glacier outlines in Qilian Mountain Area in 2020. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2020 were used as basic data for glacier extraction. Google images and Map World images were employed as reference data for manual adjusting. The dataset was stored in SHP format and attached with the attributions of coordinates, glacier ID and glacier area. Consisting of 1 season, the dataset has a spatial resolution of 2 meters. The accuracy is about 1 pixel (±2 meter). The dataset directly reflects the glacier distribution within the Qilian Mountain in 2020, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.

    2022-04-18 2413 0

  • Dataset of mass balance  on the Laohugou Glacier No. 12, western Qilian Mountains (2014-2018)

    Dataset of mass balance on the Laohugou Glacier No. 12, western Qilian Mountains (2014-2018)

    1) Dataset: The dataset includes mass balance data during 2010-2015 on the Laohuogou Glacier No. 12. 2) Sourc and methods: the mass balances were measured at each 100 m elevation belt, and every elevation had installed three plastic stick to measure mass balance. The mass balance of entire glacier was mesrued in May and September, the glacier-wide mass balance was calculated following met Area-Average method. 3) Data quality dsecription: data were manually measured following glaciology method, with a good quality.

    2022-04-18 2374 210

  • Distribution data of underground ice in permafrost regions of Qilian Mountains (2013-2015)

    Distribution data of underground ice in permafrost regions of Qilian Mountains (2013-2015)

    This data set is the distribution data of permafrost and underground ice in Qilian Mountains. Based on the existing borehole data, combined with the Quaternary sedimentary type distribution data and land use data in Qilian mountain area, this paper estimates the distribution of underground ice from permafrost upper limit to 10 m depth underground. In this data set, 374 boreholes in Qilian mountain area are used, and the indication function of Quaternary sedimentary type to underground ice storage is considered, so it has certain reliability. This data has a certain scientific value for the study of permafrost and water resources in Qilian Mountains. In addition, it has a certain promotion value for the estimation of underground ice reserves in the whole Qinghai Tibet Plateau.

    2022-04-18 5005 102

  • The 30-m land cover data of Tibetan Plateau (2010)

    The 30-m land cover data of Tibetan Plateau (2010)

    These data contain two data files: GLOBELAND30 TILES (raw data) and TIBET_ GLOBELAND30_MOSAIC (mosaic data). The raw data were downloaded from the Global Land Cover Data website (GlobalLand3) (http://www.globallandcover.com) and cover the Tibetan Plateau and surrounding areas. The raw data were stored in frames, and for the convenience of using the data, we use Erdas software to splice and mosaic the raw data. The Global Land Cover Data (GlobalLand30) is the result of the “Global Land Cover Remote Sensing Mapping and Key Technology Research”, which is a key project of the National 863 Program. Using the American Landsat images (TM5, ETM+) and Chinese Environmental Disaster Reduction Satellite images (HJ-1), the data were extracted by a comprehensive method based on pixel classification-object extraction-knowledge checks. The data include 10 primary land cover types—cultivated land, forest, grassland, shrub, wetland, water body, tundra, man-made cover, bare land, glacier and permanent snow—without extracting secondary types. In terms of accuracy assessment, nine types and more than 150,000 test samples were evaluated. The overall accuracy of the GlobeLand30-2010 data is 80.33%. The Kappa indicator is 0.75. The GlobeLand30 data use the WGS84 coordinate system, UTM projection, and 6-degree banding, and the reference ellipsoid is the WGS 84 ellipsoid. According to different latitudes, the data are organized into two types of framing. In the regions of 60° north and south latitudes, the framing is carried out according to a size of 5° (latitude) × 6° (longitude); in the regions of 60° to 80° north and south latitudes, the framing is carried out according to a size of 5° (latitude) × 12° (longitude). The framing is projected according to the central meridian of the odd 6° band. GLOBELAND30 TILES: The original, unprocessed raw data are retained. TIBET_ GLOBELAND30_MOSAIC: The Erdas software is used to mosaic the raw data. The parameter settings use the default value of the raw data to retain the original, and the accuracy is consistent with that of the downloading site.

    2022-04-18 4952 108

  • The fundamental database of atmospheric boundary layer of the north Tibetan Plateau (1997-2008)

    The fundamental database of atmospheric boundary layer of the north Tibetan Plateau (1997-2008)

    The data set collected long-term monitoring projects from multiple stations for atmosphere, hydrology and soil in the North Tibetan Plateau. The data set consisted of monitoring data obtained from the automatic weather station (AWS) and the atmospheric boundary layer tower (PBL) in the field. The sensors for temperature, humidity and pressure were provided by Vaisala of Finland; the sensors for wind speed and direction were provided by Met One of America, the radiation sensors were provided by APPLEY of America and EKO of Japan; the gas analyzers were provided by Licor of America; the soil water content instrument, ultrasonic anemometers and data collectors were provided by CAMPBELL of America. The observation system was maintained by professionals regularly (2-3 times a year), the sensors were calibrated and replaced, and the collected data were downloaded and reorganized. The data set was processed by forming a time continuous sequence after the raw data were quality-controlled. It met the accuracy level of the original meteorological observation data of the National Weather Service and the World Meteorological Organization (WMO). The quality control included the elimination of the missing data and the systematic error caused by the failure of the sensor.

    2022-04-18 3399 48

  • The Active layer moisture monitoring dataset of Tibet Plateau Beibeihe meteorological station (2017-2018)

    The Active layer moisture monitoring dataset of Tibet Plateau Beibeihe meteorological station (2017-2018)

    The active layer is one of the main characteristics of permafrost. It melts in warm season and freezes in cold season, showing seasonal changes. The change of ground temperature of active layer will directly affect the change of temperature of permafrost, thus affecting the stability of permafrost.The monitoring station of this data set is located at 92 °E, 35 ° N, with an elevation of 4,600 M. The monitoring site is flat, the vegetation type is alpine meadow, and the monitoring instrument is DT500 series data acquisition instrument. The monitoring of ground temperature is carried out at 5 depths below the surface, 10 cm, 20 cm, 40 cm, 80 cm and 160cm respectively. The time interval of this data set is 1 day, which is the average value of data once every 30 minutes.Data are stable and continuous during the period.Scientific subjects such as thermal change process and change mechanism of active layer are carried out by combining data of soil heat flux and soil moisture.

    2022-04-18 1935 230

  • Black carbon dataset of ice cores over the Tibetan Plateau (1950-2006)

    Black carbon dataset of ice cores over the Tibetan Plateau (1950-2006)

    As the “water tower of Asia”, Tibetan Plateau (TP) are the resource of major rivers in Asia. Black carbon (BC) aerosol emitted from surrounding regions can be transported to the inner TP by atmospheric circulation and consequently deposited in snow, which can significantly influence precipitation and mass balance of glaciers. By drilling and sampling ice cores and snow samples and measuring BC concentration, historical record and spatial distribution can be abtained. It can provide basic dataset to study the effects of BC to the environment and climate over the Tibetan Plateau, as well as the pollutants transport.

    2022-04-18 2226 180

  • The lakes larger than 1k㎡ in Tibetan Plateau (V1.0) (1970s, 1990, 2000, 2010)

    The lakes larger than 1k㎡ in Tibetan Plateau (V1.0) (1970s, 1990, 2000, 2010)

    The dataset includes vector map of the lakes larger than 1k㎡ on Tibetan Plateau in 1970s, 1990, 2000, 2010. The lake boundry data was extracted from remote sensing image like Landsat MSS, TM, ETM+, by means of visual interpretation. The data type is vector data, and it's attribute class includes Area (km²). The Projected Coordinate System is Albers Conical Equal Area. It is mainly used in the study of changes in lakes, hydrological and meteorological on the Tibetan Plateau.

    2022-04-18 3217 287

  • Photosynthetically active radiation absorption coefficient dataset in Qinghai Tibet Plateau (2000-2015)

    Photosynthetically active radiation absorption coefficient dataset in Qinghai Tibet Plateau (2000-2015)

    Photosynthetic effective radiation absorption coefficient photosynthetically active radiation component is an important biophysical parameter. It is an important land characteristic parameter of ecosystem function model, crop growth model, net primary productivity model, atmosphere model, biogeochemical model and ecological model, and is an ideal parameter for estimating vegetation biomass. The data set contains the data of photosynthetically active radiation absorption coefficient in Qinghai Tibet Plateau, with spatial resolution of 500m, temporal resolution of 8D, and time coverage of 2000, 2005, 2010 and 2015. The data source is MODIS Lai / FPAR product data mod15a2h (C6) on NASA website. The data are of great significance to the analysis of vegetation ecological environment in the Qinghai Tibet Plateau.

    2022-04-18 4251 151

  • The meteorological observation dataset of Guoluo meadow on the Tibetan Plateau (2005-2009)

    The meteorological observation dataset of Guoluo meadow on the Tibetan Plateau (2005-2009)

    This data set includes meteorological data observed by the carbon flux station in the Guoluo Army Ranch in Qinghai. The temporal coverage is from 2005 to 2009, and the temporal resolution is 1 day. Meteorological and carbon flux data observation methods: vorticity-related observation instruments were used for automatic recording; biomass observation method: harvest method, weighing in a 60-degree oven for 48 hours. Both carbon flux and meteorological data were automatically recorded by the instruments and manually checked. During the data observation process, the operation of the instrument and the selection of the observation objects were in strict accordance with professional requirements, and the data could be applied to plant leaf photosynthetic parameter simulation and productivity estimation. This data contains observation items as follows: Temperature °C Precipitation mm Wind speed m/s Soil temperature at 5 cm depth °C Photosynthetically active radiation µmol/m²s Total radiation W/m²

    2022-04-18 2205 220

  • Dataset of river basins map over the TP(2016)

    Dataset of river basins map over the TP(2016)

    The data set was produced based on the SRTM DEM data collected by Space Shuttle Radar terrain mission in 2016, the reference data such as river, lake and other water system auxiliary data , using the arcgis hydrological model to analyze and extract the river network. There are 12 sub-basins over the Tibet Plateau, including AmuDayra、Brahmaputra、Ganges、Hexi、Indus、Inner、Mekong、Qaidam、Salween、Tarim、Yangtze、Yellow. The outer boundary is based on the 2500-metre contour line and national boundaries.

    2022-04-18 14583 1738

  • Aerosol datasets over the Tibetan Plateau (2006-2019)

    Aerosol datasets over the Tibetan Plateau (2006-2019)

    There are two types of aerosol data in the Tibetan Plateau. Aerosol type data products are the results of aerosol type data fusion by using Meera 2 assimilation data and active satellite CALIPSO products through a series of data preprocessing, quality control, statistical analysis and comparative analysis. The key of the algorithm is to judge the CALIPSO aerosol type. According to CALIPSO aerosol types and quality control, and referring to merra 2 aerosol types, the final aerosol type data (12 kinds) and quality control results were obtained. Considering the vertical and spatial distribution of aerosols, it has high spatial resolution (0.625 ° × 0.5 °) and temporal resolution (month). Aerosol optical depth (AOD) is a visible band remote sensing inversion method developed by ourselves, combined with merra-2 model data and NASA's official product mod04. The data coverage time is from 2000 to 2019, with daily temporal resolution and spatial resolution of 0.1 degree. The retrieval method mainly uses the self-developed APRs algorithm to retrieve the aerosol optical depth over the ice and snow. The algorithm takes into account the BRDF characteristics of the ice and snow surface, and is suitable for the inversion of aerosol optical thickness on the ice and snow. The results show that the relative deviation of the data is less than 35%, which can effectively improve the coverage and accuracy of the polar AOD.

    2022-04-18 2553 228

  • Meteorological Datasets of Xidatan station (XDT) on the Tibetan Plateau in 2014-2018

    Meteorological Datasets of Xidatan station (XDT) on the Tibetan Plateau in 2014-2018

    This dataset is Meteorologic Elements Dataset of XDT on Qinghai-Tibet Plateau 2014-2018. Meteorologic elements including: 2m air temperature(℃), 2m air humidity(%), precipitation(mm), 2m wind speed(m/s), global radiation(w/㎡). The data are from the XiDaTan monitoring site(site code: XDTMS) of Cryosphere Research Station on Qinghai-Tibat Plateau, Chinese Academy of Sciences(CRS-CAS). These daily data was calculated from the original monitoring data(monitoring frequency is 30min). The missing part of the daily data was marked by NAN, which were manually collated and verified. The missing period was from 2017-7-7 to 2017-10-3.

    2022-04-18 2901 250

  • Data set of modern glacier distribution in Hoh Xil area, Qinghai Province (1989-August 1990)

    Data set of modern glacier distribution in Hoh Xil area, Qinghai Province (1989-August 1990)

    The data set is a record of glacier distribution in Hoh Xil region, including three tables: the distribution of modern glaciers in various mountain areas in Hoh Xil region, the distribution of modern glaciers in various river basins in Hoh Xil region, and the distribution of modern glaciers in different mountain height segments in Hoh Xil region. Hoh Xil, located in the hinterland of the Qinghai Tibet Plateau, has an average altitude of more than 5000m and a very cold climate. According to the catalogue of China's glaciers and the author's re statistics on the 1 / 100000 topographic map, 437 modern glaciers are developed in the whole region, covering an area of 1552.39 square kilometers, with ice reserves of 162.8349 cubic kilometers, becoming an important source of water supply for many rivers and lakes in the region. Through this data set, we can know more about the distribution of glaciers in this area.

    2022-04-18 2654 238

  • Vector dataset of glaciers and glacial lakes in the Boqu Basin in Central Himalaya (1976-2010)

    Vector dataset of glaciers and glacial lakes in the Boqu Basin in Central Himalaya (1976-2010)

    This is the 1976, 1991, 2000, and 2010 vector data set of glaciers and glacial lakes in the Boqu Basin in Central Himalaya based on Landsat satellite images. The data source is from Landsat remote images. 1976: LM21510411975306AAA05, LM21510401976355AAA04 1991: LT41410401991334XXX02, LT41410411991334XXX02 2000: LE71410402000279SGS00, LE71400412000304SGS00, LE71410402000327EDC00, LE71410412000327EDC00 2010: LT51400412009288KHC00, LT51410402009295KHC00, LT51410412009311KHC00, LT51410402011237KHC00. The boundaries of glaciers and glacial lakes are extracted manually from the various remote sensing images. The extraction error of the boundaries of glaciers and glacial lakes is estimated to be 0.5 pixels. Data file: Glacial_1976: Glacier vector data in 1976 Glacial_1991: Glacier vector data in 1991 Glacial_2000: Glacier vector data in 2000 Glacial_2010: Glacier vector data in 2010 Glacial_Lake_1976: Glacial lake vector data in 1976年 Glacial_Lake_1991: Glacial lake vector data in 1991 Glacial_Lake_2000: Glacial lake vector data in 2000 Glacial_Lake_2010: Glacial lake vector data in 2010 The glacial lake vector data fields include Number, name, latitude and longitude, altitude, area, orientation, type of glacial lake, length, width, and distance from the glacier.

    2022-04-18 2796 222

  • Annual variation characteristic value of runoff at the major hydrological stations of the Yarlung Zangbo River (1956-2000)

    Annual variation characteristic value of runoff at the major hydrological stations of the Yarlung Zangbo River (1956-2000)

    This dataset contains the annual variation of runoff from the major hydrological stations in the Yarlung Zangbo River (annual average runoff volume, annual extremum ratio, coefficient of variation, etc.). It can be used to study the hydrological characteristics of the Yarlung Zangbo River. The original data are the national hydrological station data, and the quality requirements are the same as the national standards. Spatial Coverage: 4 hydrological stations in the main streams of the Yarlung Zangbo River basin, which are Lazi, Nugesha, Yangcun and Nuxia. This data sheet has five fields. Field 1: Station Name Field 2: Annual average runoff volume Field 3: Annual Extreme Ratio Field 4: Coefficient of variation Field 5: Data Series Length

    2022-04-18 5648 476

  • Yulong snow mountain glacier No.1, 4 506 m altitude the daily average meteorological observation dataset (2014-2018)

    Yulong snow mountain glacier No.1, 4 506 m altitude the daily average meteorological observation dataset (2014-2018)

    1. Data content: air temperature, relative humidity, precipitation, air pressure, wind speed, average total radiation, total net radiation value and daily average water vapor pressure data. 2. Data source and processing method: Observed by American campel high-altitude automatic weather station, air temperature and humidity sensor model HMP155A; wind speed and wind direction model: 05103-45; net radiometer: CNR 4 Net Radiometer four component; atmospheric pressure sensor: CS106; Rain gauge: TE525MM. The automatic weather station automatically collects data every 10 minutes, and collects daily statistical data to obtain daily average weather data. 3. Data quality description: Data is automatically acquired continuously. 4. Data application results and prospects: The weather station is located in the middle of the glacier, and the meteorological data can provide data guarantee for simulating the response of oceanic glacier changes to global climate change in the context of future climate change.

    2022-04-18 2542 21

  • Hydrological data set of surface process and environment observation network in alpine region of China (2019)

    Hydrological data set of surface process and environment observation network in alpine region of China (2019)

    Based on the long-term observation data of the field stations in the alpine network and the overseas stations in the pan third polar region, a series of data sets of meteorological, hydrological and ecological elements in the pan third polar region are established; through the intensive observation and sample plot and sample point verification in key areas, the inversion of meteorological elements, lake water and water quality, aboveground vegetation biomass, glacier and frozen soil change and other data products are completed; based on the Internet of things, the data products are retrieved Network technology, research and establish meteorological, hydrological, ecological data management platform of multi station networking, to achieve real-time data acquisition and remote control and sharing. The hydrological data set of the surface process and environment observation network in China's alpine regions in 2019 mainly collects the measured hydrological (runoff, water level, water temperature, etc.) data at six stations, including Southeast Tibet station, Zhufeng station, Yulong Snow Mountain station, Namco station, Ali station and Tianshan station. Southeast Tibet station: flow data, including 4 times of using M9 to measure flow in 2019, including average velocity, flow and maximum water depth; relative water level data is measured by hobo pressure water level meter, including daily average relative water level and water temperature data in 2019. Namco station: discharge data, including the data measured by domestic ls-1206b hand-held current meter for 4 times in 2019, including river width and flow data. The water level data is measured by hobo pressure water level meter, including the water pressure, water temperature and electricity of the original 1 hour in 2019. The relative water level can be calculated by water pressure; Everest station: rongbuhe river discharge, including river width and discharge data measured by domestic ls-1206b hand-held current meter 13 times from June to September 2019; Ali station: flow data: including 22 times of irregular measurement data by river anchor M9 in 2019, and relative water level data measured by hobo pressure water level meter, including hourly water level and water temperature data of the whole year in 2019; Tianshan station: water level data: including daily average water level of 3 points in 2019 Yulong Xueshan station: including mujiaqiao flow data from January to October in 2019

    2022-04-18 2004 1