The dataset includes three high-resolution DSM data as well as Orthophoto Maps of Kuqionggangri Glacier, which were measured in September 2020, June 2021 and September 2021. The dataset is generated using the image data taken by Dajiang Phantom 4 RTK UAV, and the products are generated through tilt photogrammetry technology. The spatial resolution of the data reaches 0.15 m. This dataset is a supplement to the current low-resolution open-source topographic data, and can reflect the surface morphological changes of Kuoqionggangri Glacier from 2020 to 2021. The dataset helps to accurately study the melting process of Kuoqionggangri Glacier under climate change.
LIU Jintao
Glacial mass balance is one of the most important glaciological parameters to characterize the accumulation and ablation of glaciers. Glacier mass balance is the link between climate and glacier change, and it is the direct reflection of glacier to the regional climate. Climate change leads to the corresponding changes in the material budget of glaciers, which in turn can lead to changes in the movement characteristics and thermal conditions of glaciers, and then lead to changes in the location, area and ice storage of glaciers. The monitoring method is to set a fixed mark flower pole on the glacier surface and regularly monitor the distance between the glacier surface and the top of the flower pole to calculate the amount of ice and snow melting; In the accumulation area, the snow pits or boreholes are excavated regularly to measure the snow density, analyze the characteristics of snow granular snow additional ice layer, and calculate the snow accumulation; Then, the single point monitoring results are drawn on the large-scale glacier topographic map, and the instantaneous, seasonal (such as winter and summer) and annual mass balance components of the whole glacier are calculated according to the net equilibrium contour method or contour zoning method. The data set is the annual mass balance data of different representative glaciers in the Qinghai Tibet Plateau and Tianshan Mountains, in millimeter water equivalent.
WU Guangjian
Glacier is the supply water source of rivers in the western mountainous area, and it is one of the most basic elements for people to survive and develop industry, agriculture and animal husbandry in the western region. Glaciers are not only valuable fresh water resources, but also the source of serious natural disasters in mountainous areas, such as sudden ice lake outburst flood, glacier debris flow and ice avalanche. Glacier hydrological monitoring is the basis for studying the characteristics of glacier melt water, the replenishment of glacier melt water to rivers, the relationship between glacier surface ablation and runoff, the process of ice runoff and confluence, and the calculation and prediction of floods and debris flows induced by glacier and seasonal snow melt water. Glacial hydrology refers to the water and heat conditions of glacial covered basins (i.e. glacial action areas), that is, the water and heat exchange between glaciers and their surrounding environment, the physical process of water accumulation and flow on the surface, inside and bottom of glaciers, the water balance of glaciers, the replenishment of glacial melt water to rivers, and the impact of water bodies in cold regions on climate change. At present, hydrological monitoring stations are mainly established at the outlet of the river basin to carry out field monitoring《 Glacial water resources of China (1991), hydrology of cold regions of China (2000) and glacial Hydrology (2001) summarize the early studies on glacial hydrology. China has carried out glacier hydrological monitoring on more than 20 glaciers in Tianshan, Karakorum, West Kunlun, Qilian, Tanggula, Nianqing Tanggula, gangrigab, Hengduan and Himalayas. This data set is the monthly runoff data of representative glaciers.
YANG Wei, LI Zhongqin, WANG Ninglian, QIN Xiang
Near-surface air temperature variability and the reliability of temperature extrapolation within glacierized regions are important issues for hydrological and glaciological studies that remain elusive because of the scarcity of high-elevation observations. Based on air temperature data in 2019 collected from 12 automatic weather stations, 43 temperature loggers and 6 national meteorological stations in six different catchments, this study presents air temperature variability in different glacierized/nonglacierized regions and assesses the robustness of different temperature extrapolations to reduce errors in melt estimation. The results show high spatial variability in temperature lapse rates (LRs) in different climatic contexts, with the steepest LRs located on the cold-dry northwestern Tibetan Plateau and the lowest LRs located on the warm-humid monsoonal-influenced southeastern Tibetan Plateau. Near-surface air temperatures in high-elevation glacierized regions of the western and central Tibetan Plateau are less influenced by katabatic winds and thus can be linearly extrapolated from off-glacier records. In contrast, the local katabatic winds prevailing on the temperate glaciers of the southeastern Tibetan Plateau exert pronounced cooling effects on the ambient air temperature, and thus, on-glacier air temperatures are significantly lower than that in elevation-equivalent nonglacierized regions. Consequently, linear temperature extrapolation from low-elevation nonglacierized stations may lead to as much as 40% overestimation of positive degree days, particularly with respect to large glaciers with a long flowline distances and significant cooling effects. These findings provide noteworthy evidence that the different LRs and relevant cooling effects on high-elevation glaciers under distinct climatic regimes should be carefully accounted for when estimating glacier melting on the Tibetan Plateau.
YANG Wei
The data set of light absorbing impurities in snow and ice in and around the Qinghai Tibet Plateau include black carbon and dust concentration data and their mass absorption cross sections from 9 glaciers (Urumqi glacier No.1, Laohugou glacier No.12, xiaodongkemadi glacier, renlongba glacier, Baishui River glacier No.1, and golubin glacier, Abramov glacier, syekzapadniyi glacier and No. 354 glacier in Pamir region) . The black carbon data is obtained by DRI 2015 model thermo-optical carbon analyzer, and the dust data is obtained by weighing method. The sampling and experimental processes are carried out in strict accordance with the requirements. The data can be used for the study of snow ice albedo and climate effect.
KANG Shichang
From 2015 to 2020, physicochemical properties of glacial snow and ice of NO.15 glacier (NO.15), 24K glacier (24K), Azha glacier(AZ), Cuopugou glacier(CPG), Demula glacier (DML), Dongrongbu glacier (DRB), Dongkemadi glacier (DKMD), Dunde glacier (DD), Guliya glacier (GLY), Hongqi Lapu glacier (HQLP), Kangxiwa River glacier (KXW), Kangwure glacier (KWR), Kuoqionggangri glacier (KQGR), Langadingri glacier (LADR), Mengdagangri glacier (MDGR), Mugagangqiong glacier (MGGQ), Muji glacier (MJ), Mushtag glacier (MSTG), Namunani glacier (NMNN), Nima glacier (NM), Nujiangyuantou (NJYT), Palung 4 glacier (PL4), Qiangtang No.1 glacier (QT), Qiangyong glacier (QY), Quma glacier (QM), Seqila glacier (SQL), Tanggula longxiazailongba glacier (LXZ), Xiagangjiang glacier (XGJ), Yala glacier (YL), Zepugou glacier (ZPG), Zhuxigou glacier (ZXG) on the Tibetan plateau, including DOC The samples were analyzed by 0.45 µm molecular membranes. Samples were filtered through 0.45 micron molecular membranes and tested using a Shimadzu TOC-L instrument, while ion concentrations were measured by ion chromatography. The unit of the indicator is mg/L. "n.a." means below the detection limit of the instrument, and "\" means missing value. Sheet1 in the table is "Physicochemical properties of glaciers and snow ice on the Tibetan Plateau (2015-2020)", and sheet2 is "Basic information of glaciers".
LIU Yongqin
Glacier is the supply water source of rivers in the western mountainous area, and it is one of the most basic elements for people to survive and develop industry, agriculture and animal husbandry in the western region. Glaciers are not only valuable fresh water resources, but also the source of serious natural disasters in mountainous areas, such as sudden ice lake outburst flood, glacier debris flow and ice avalanche. Glacier hydrological monitoring is the basis for studying the characteristics of glacier melt water, the replenishment of glacier melt water to rivers, the relationship between glacier surface ablation and runoff, the process of ice runoff and confluence, and the calculation and prediction of floods and debris flows induced by glacier and seasonal snow melt water. Glacial hydrology refers to the water and heat conditions of glacial covered basins (i.e. glacial action areas), that is, the water and heat exchange between glaciers and their surrounding environment, the physical process of water accumulation and flow on the surface, inside and bottom of glaciers, the water balance of glaciers, the replenishment of glacial melt water to rivers, and the impact of water bodies in cold regions on climate change. At present, hydrological monitoring stations are mainly established at the outlet of the river basin to carry out field monitoring《 Glacial water resources of China (1991), hydrology of cold regions of China (2000) and glacial Hydrology (2001) summarize the early studies on glacial hydrology. China has carried out glacier hydrological monitoring on more than 20 glaciers in Tianshan, Karakorum, West Kunlun, Qilian, Tanggula, Nianqing Tanggula, gangrigab, Hengduan and Himalayas. This data set is the monthly runoff data of representative glaciers.
YANG Wei, LI Zhongqin, WANG Ninglian, QIN Xiang
Glacial mass balance is one of the most important glaciological parameters to characterize the accumulation and ablation of glaciers. Glacier mass balance is the link between climate and glacier change, and it is the direct reflection of glacier to the regional climate. Climate change leads to the corresponding changes in the material budget of glaciers, which in turn can lead to changes in the movement characteristics and thermal conditions of glaciers, and then lead to changes in the location, area and ice storage of glaciers. The monitoring method is to set a fixed mark flower pole on the glacier surface and regularly monitor the distance between the glacier surface and the top of the flower pole to calculate the amount of ice and snow melting; In the accumulation area, the snow pits or boreholes are excavated regularly to measure the snow density, analyze the characteristics of snow granular snow additional ice layer, and calculate the snow accumulation; Then, the single point monitoring results are drawn on the large-scale glacier topographic map, and the instantaneous, seasonal (such as winter and summer) and annual mass balance components of the whole glacier are calculated according to the net equilibrium contour method or contour zoning method. The data set is the annual mass balance data of different representative glaciers in the Qinghai Tibet Plateau and Tianshan Mountains, in millimeter water equivalent.
WU Guangjian
Glacier thickness is the vertical distance between the glacier surface and the glacier bottom. The distribution of glacier thickness is not only controlled by glacier scale and subglacial topography, but also varies with different stages of glacier response to climate. The data include longitude and latitude, elevation, single point thickness, total ice reserves and instrument type of glacier survey line. The glacier thickness mainly comes from drilling and ground penetrating radar (GPR). The drilling method is to drill holes on the ice surface to the bedrock under the ice, so as to obtain the thickness of the glacier at a single point; Glacier radar thickness measurement technology can accurately measure the continuous distribution of glacier thickness on the survey line, and obtain the topographic characteristics of subglacial bedrock, so as to provide necessary parameters for the estimation of glacier reserves and the study of glacier dynamics The accuracy of glacier drilling data reaches decimeter level. The accuracy of thickness measurement by GPR radar is between 5% and 15% in theory due to the difference of glacier properties and radar signal strength of bottom interface. Glacier thickness is a prerequisite for obtaining information of subglacial topography and glacier reserves. In the numerical simulation and model study of glacier dynamics, glacier thickness is an important basic input parameter. At the same time, glacier reserve is the most direct parameter to characterize glacier scale and glacier water resources. It is not only very important for accurate assessment, reasonable planning and effective utilization of glacier water resources, but also has important and far-reaching significance for regional socio-economic development and ecological security.
WU Guangjian
Mercury is a global pollutant.The Qinghai-Tibet Plateau is adjacent to South Asia, which currently has the highest atmospheric mercury emissions, and could be affected by long-distance transport.The history of atmospheric mercury transport and deposition can be well reconstructed using ice cores and lake cores. The history of atmospheric mercury deposition since the industrial revolution was reconstructed based on 8 lake cores and 1 ice core from the Tibetan Plateau and the southern slope of the Himalayas.This data set contains 8 lake core data from Namtso, Bangongtso, Linggatso, Guanyong Lake, Tanggula Lake, Gosainkunda Lake, Gokyo Lake and Phewa Lake, and 1 ice core data .The resolution of ice core data is 1 year, lake core data is 2~20 years, and the data include mercury concentration and flux.
KANG Shichang
The data set includes annual mass balance of Naimona’nyi glacier (northern branch) from 2008 to 2018, daily meteorological data at two automatic meteorological stations (AWSs) near the glacier from 2011 to 2018 and monthly air temperature and relative humidity on the glacier from 2018 to 2019. In the end of September or early October for each year , the stake heights and snow-pit features (snow layer density and stratigraphy) are manually measured to derive the annual point mass balance. Then the glacier-wide mass balance was then calculated （Please to see the reference). Two automatic weather stations (AWSs, Campbell company) were installed near the Naimona’nyi Glacier. AWS1, at 5543 m a. s.l., recorded meteorological variables from October 2011 at half hourly resolution, including air temperature (℃), relative humidity (%), and downward shortwave radiation (W m-2) . AWS2 was installed at 5950 m a.s.l. in October 2010 at hourly resolution and recorded wind speed (m/s), air pressure (hPa), precipitation (mm). Data quality: the quality of the original data is better, less missing. Firstly, the abnormal data in the original records are removed, and then the daily values of these parameters are calculated. Two probes (Hobo MX2301) which record air temperature and relative humidity was installed on the glacier at half hour resolution since October 2018. The observed meteorological data was calculated as monthly values. The data is stored in Excel file. It can be used by researchers for studying the changes in climate, hydrology, glaciers, etc.
ZHAO Huabiao
The data set contains the stable oxygen isotope data of ice core from 1864 to 2006. The ice core was obtained from Noijinkansang glacier in the south of Southern Tibetan Plateau, with a length of 55.1 meters. Oxygen isotopes were measured using a MAT-253 mass spectrometer (with an analytical precision of 0.05 ‰) at the Key Laboratory of CAS for Tibetan Environment and Land Surface Processes, China. Data collection location: Noijinkansang glacier (90.2 ° e, 29.04 ° n, altitude: 5950 m)
GAO Jing
The coverage time of glacier runoff data set in the five major river source areas of the Qinghai Tibet Plateau is from 1971 to 2015, and the time resolution is year by year, covering the source areas of five major rivers (Yellow River source, Yangtze River source, Lancang River source, Nu River source, Yarlung Zangbo River source). The data is based on multi-source remote sensing and measured data. The glacier runoff data is simulated by using the daily scale meteorological data of five major river source areas and their surrounding meteorological stations, the global vegetation products of umd-1km, the igbp-dis soil database, the first and second glacier catalogue data, and the distributed hydrological model vic-cas coupled with the glacier module is used to simulate the glacier runoff data. The simulation results are verified by the site measured data to enhance the quality control. Data indicators include: Glacier runoff (rate of glacier runoff:%), total runoff (mm / a), snow runoff (rate of snow runoff:%), and rainfall runoff rate (rainfall runoff rate:%).
WANG Shijin
The data set involved geodetic annual glacier-averaged mass balance and mass change data atMt.Xixiabangma areasin the Himalayas from 1974 to 2017. It is stored in the ESRI vector polygon format and is composed of two periods, which includes surface elevation difference between 1974-2000 (DH1974-2000, from KH-9 DEM1974 and SRTM DEM2000), surface elevation difference between 2000-2017(DH2000-2017, by DinSAR techniquesfrom SRTM DEM2000 and TSX/TDX data in 2017). KH-9 DEM is a DEM of the study area in 1974, which was generated from three scenes of optical stereo pairs from KH-9. Geodetic glacier mass change was calculated by DH above, glacier cover vector data from TPG1976/CGI2/RGI6.0 with ice density of 850 ± 60 kg m−3. The attribute data included: GLIMSId means the glacier code from GLIMS data base, Area（km2）is the glacier area by km2, area_m2 is glacier area by (m2）, the glacier name, EC74_2000, the surface elevation change rate from 1974 to 2000(m a-1), EC00_2017, the surface elevation change rate from 2000 to 2017 (m a-1), MB74_2000, the geodetic glacier mass balance between 1974 and 2000（m w.e. a-1），MB00_2017, the geodetic glacier mass balance between 2000 and 2017（m w.e. a-1）.MC74_2000, the geodetic glacier mass change from 1974 to 2000 (m3w.e. a-1), MC00_2017, the geodetic glacier mass change from 2000 to 2017(m3 w.e. a-1). Ut_EC74_00 is the uncertainty of glacier surface elevation change（m a-1） in 1974-2000、Ut_MB74_00, is the uncertainty of glacier mass balance for each glacier（m w.e. a-1）in 1974-2000，Ut_MC74_00, is the uncertainty of glacier mass change for each glacier（m3w.e. a-1）in 1974-2000. Ut_EC00_17，is the uncertainty of glacier surface elevation change in 2000-2017（m a-1），Ut_MB00_17，is the uncertainty of glacier mass balance for each glacier in 2000-2017（m w.e. a-1），Ut_MC00_17 is the uncertainty of glacier mass change for each glacier in 2000-2017（m3 w.e. a-1）.This data set is used for the study glaciers melting and its hydrological effects in the Central Himalayas.It also could be used in studies of climatic change and disasters research in the Himalayas.
YE Qinghua
The data involved two periods of geodetic glacier mass storage change of Naimona’Nyi glaciers in the western of Himalaya from 1974-2013 (unit: m w.e. a-1). It is stored in the ESRI vector polygon format. The data sets are composed of two periods of glacier surface elevation difference between 1974-2000 and 2000-2013, i.e. DHSRTM2000-DEM1974（DH2000-1974）、DHTanDEM2013-SRTM2000（DH2013-2000）. DH2000-1974 was surface elevation change between SRTM2000 and DEM1974, i.e. the earlier historical DEM (DEM1974, spatial resolution 25m) was derived from 1:50,000 topographic maps in October 1974(DEM1974,spatial resolution 25m). The uncertainty in the ice free areas of DH2000-1974 was ±0.13 m a-1. The surface elevation difference between 2000-2013 (DH2000-2013, by DinSAR techniques from SRTM DEM2000 and TSX/TDX data on Oct.17th in 2013) The uncertainty in the ice free areas of DH2013-2000 was ±0.04 m a-1. Glacier-averaged annual mass balance change (m w.e.a-1) was averaged annually for each glacier, which was calculated by DH2000-1974/DH2013-2000, glacier coverage area and ice density of 850 ± 60 kg m−3. The attribute data includes Glacier area by Shape_Area (m2), EC74_00, EC00_13, i.e. Glacier-averaged surface elevation change in 1974-2000 and 2000-2013(m a-1), MB74_00, MB00_13 i.e. Glacier-averaged annual mass balance in 1974-2000 and 2000-2013 (m w.e.a-1), and MC74_00, MC00_13, Glacier-averaged annual mass change in 1974-2000 and 2000-2013 (m3 w.e.a-1), Uncerty_MB, is the uncertainty of glacier-averaged annual mass balance（m w.e. a-1）， Uncerty_MC, is the Maximum uncertainty of glacier-averaged annual mass change（m3 w.e. a-1）. The data sets could be used for glacier change, hydrological and climate change studies in the Himalayas and High Mountain Asia.
YE Qinghua
The data set includes the mass balances of Hailuogou Glacier, Parlung No.94 Glacier, Qiyi glacier, Xiaodongkemadi Glacier, Muztagh No.15 Glacier, Meikuang Glacier and NM551 Glacier in the Qinghai Tibet Plateau from 1975 to 2013. Based on several mass balance observations collected from World Glacier Inventory (https://nsidc.org/data/g10002/versions/1) and The Third Pole Environment Database (http://en.tpedatabase.cn/, doi:10.11888/GlaciologyGeocryology.tpe.96.db) by Tandong Yao and the meteorological data obtained from Global Land Assimilation System (GLDAS) (meteorological variables, including precipitation, air temperature, net radiation, evaporation on snow surface, and snow depth, in the central grid of each glacier are extracted from GLDAS data set shown in meteo.xlsx), the mass balances of the above seven glaciers from 1975 to 2013 are reconstructed by using the glacier material balance calculation formula. This reconstruction data is based on the published glacier material balance data to calibrate the parameters in the glacier material balance formula, and to reconstruct the long-time series material balance by using the glacier material balance formula, in which the parameter calibration results and the reconstruction results of the long-time series data are compared with the relevant research results, demonstrating the rationality of the data results Please refer to the following papers. The data can be used to study the change of water resources in the glacial region, expand the data set of Glacier Mass Balance in the Qinghai Tibet Plateau, and provide reference for the future research of Glacier Mass Balance reconstruction.
LIU Xiaowan
The Tibetan Plateau Glacier Data –TPG2017 is a glacial coverage data on the Tibetan Plateau from selected 210 scenes of Landsat 8 Operational Land Imager (OLI) images with 30-m spatial resolution from 2013 to 2018, among of which 90% was in 2017 and 85% in winter. Therefore, 2017 was defined as the reference year for the mosaic image. Glacier outlines were digitized on-screen manually from the 2017 image mosaic, relying on false-colour image composites (RGB by bands 654), which allowed us to distinguish ice/snow from cloud. Debris-free ice was distinguished from the debris and debris-covered ice by its higher reflectance. Debris-covered ice was not delineated in this data. The delineated glacier outlines were compared with band-ratio (e.g. TM3/TM5) results, and validated by overlapping them onto Google Earth imagery, SRTM DEM, topographic maps and corresponding satellite images. For areas with mountain shadows and snow cover, they were verified by different methods using data from different seasons. For glaciers in deep shadow, Google EarthTM imagery from different dates was used as the reference for manual delineation. Steep slopes or headwalls were also excluded in the TPG2017. Areas that appeared in any of these sources to have the characteristics of exposed ground/basement/bed rock were manually delineated as non-glacier, and were also cross-checked with CGI-1 and CGI-2. Steep hanging glaciers were included in TPG2017 if they were identifiable on images in all other three epochs (i.e. TPG1976, TPG2001, and TPG2013). The accuracy of manual digitization was controlled within one half-pixel. All glacier areas were calculated on the WGS84 spheroid in an Albers equal-area map projection centred at (95°E, 30°N) with standard parallels at 15°N and 65°N. Our results showed that the relative deviation of manual interpretation was less than 3.9%.
YE Qinghua
The data of triode ice core mainly comes from NOAA (National Oceanic and Atmospheric Administration, https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/ice-core). The original data is mainly in text format, which is provided by relevant units and researchers voluntarily. The data mainly includes the original observation data such as oxygen isotope, greenhouse gas concentration, ice core age, etc., as well as the historical temperature, carbon dioxide concentration and methane concentration produced by the researchers according to the observation data. The data are mainly divided into Antarctic, Arctic, Greenland and the third polar region. The database includes drilling address, time, derivative products, corresponding observation site data, references and other elements. Derivative products include product name, type, time and other elements. The space location is divided into the south pole, the north pole and the third pole, including Alaska, Canada, Russia, Greenland and other regions. After sorting and post-processing the collected data, the ice core database is established by using the access database management system of Microsoft office. According to the Antarctic, Arctic, Greenland and the third pole, it is divided into four sub databases. The first table in each database is readme, which contains information and references of each data table.
YE Aizhong
Glaciers are very sensitive to regional and global climate change, so they are often regarded as one of the indicators of climate change, and their relevant parameters are also the key indicators of climate change research. Especially in the comparative study of the three polar environmental changes on the earth, the time and space difference ratio of glacial speed is one of the focuses of climate change research. However, because glaciers are basically located in high altitude, high latitude and high cold areas, the natural environment is poor, and people are rarely seen, and it is difficult to carry out the conventional field measurement of large-scale glacial movement. In order to understand the glacial movement in the three polar areas in a timely, efficient, comprehensive and accurate manner, radar interferometry, radar and optical image pixel tracking are used to obtain the three polar areas. The distribution of surface movement of some typical glaciers in some years from 2000 to 2017 provides basic data for the comparative analysis of the movement of the three polar glaciers. The dataset contains 12 grid files named "glacier movement in a certain period of time in a certain region". Each grid map mainly contains the regional velocity distribution of a typical glacier.
Yan Shiyong
This product is based on multi-source remote sensing DEM data generation. The steps are as follows: select control points in relatively stable and flat terrain area with Landsat ETM +, SRTM and ICESat remote sensing data as reference. The horizontal coordinates of the control points are obtained with Landsat ETM + l1t panchromatic image as the horizontal reference. The height coordinates of the control points are mainly obtained by ICESat gla14 elevation data, and are supplemented by SRTM elevation data in areas without ICESat distribution. Using the selected control points and automatically generated connection points, the lens distortion and residual deformation are compensated by Brown's physical model, so that the total RMSE of all stereo image pairs in the aerial triangulation results is less than 1 pixel. In order to edit the extracted DEM data to eliminate the obvious elevation abnormal value, DEM Interpolation, DEM filtering and DEM smoothing are used to edit the DEM on the glacier, and kh-9 DEM data in the West Kunlun West and West Kunlun east regions are spliced to form products.
ZHOU Jianming
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