The data set includes carbon isotope data of different regions of the Tibetan Plateau and different environmental (carbon isotope data of black carbon and organic carbon in aerosols from 10 typical stations of the Qinghai Tibet Plateau, carbon isotope data of black carbon and water insoluble organic carbon in 11 snow pits in different years, and carbon isotope data of water-soluble organic carbon in monsoon precipitation from 11 stations of the Qinghai Tibet Plateau and its surrounding areas), All samples were collected at each site, and the content and δ 13C and Δ 14C data, which can be used to accurately assess the contribution proportion of atmospheric carbon aerosols, carbon particles deposited on glaciers and water-soluble organic carbon in precipitation from fossil fuels and biomass fuels.
LI Chaoliu
This data set includes the light absorption data of carbon components in the atmosphere and precipitation at typical stations on the Tibetan Plateau (Ranwu (2018-2021), Namco (2013-2016), Everest (2013-2016), Lulang (2015-2016)). All samples were collected on the spot from various sampling points. The concentrations of black carbon and water-soluble organic carbon, as well as the light absorption data were measured, using the index (MAC value) representing the light absorption capacity, The MAC values of light absorption of water-soluble organic carbon and black carbon are calculated. This data is of great significance for evaluating the radiative forcing of carbon particles in the atmosphere, and is an important basic data input for model simulation.
LI Chaoliu
The extraction of glacier surface movement is of great significance in the study of glacier dynamics and material balance changes. In view of the shortcomings of the current application of autonomous remote sensing satellite data in glacier movement monitoring in China, the SAR data covering typical glaciers in alpine areas of the Qinghai Tibet Plateau from 2019 to 2020 obtained under the GF-3 satellite FSI mode was used to obtain the glacier surface velocity distribution in the study area with the help of a parallel offset tracking algorithm. With its good spatial resolution, GF-3 image has significant advantages in extracting glacier movement with small scale and slow movement, and can better reflect the details and differences of glacier movement. This study is helpful to analyze the movement law and spatio-temporal evolution characteristics of glaciers in the Qinghai Tibet Plateau under the background of climate change.
YAN Shiyong
The Antarctic McMurdo Dry Valleys ice velocity product is based on the Antarctic Ice Sheet Velocity and Mapping Project (AIV) data product, which is post-processed with advanced algorithms and numerical tools. The product is mapped using Sentinel-1/2/Landsat data and provides uniform, high-resolution (60m) ice velocity results for McMurdo Dry Valleys, covering the period from 2015 to 2020.
JIANG Liming JIANG Liming JIANG Liming
Based on the monthly precipitation data of 262 rain gauges, WRF and ERA5 precipitation data in the Yarlung Zangbo River basin, the daily precipitation data with a resolution of 10km from 1951 to 2020 in the Yarlung Zangbo River basin and seven sub basins are reconstructed using random forest learning algorithm. This data has been verified by the single point of the station and performs well in terms of annual and seasonal changes. And the data has been reverse evaluated by the hydrological model, which is used to drive the VIC hydrological model to simulate the runoff change of Yajiang River basin and each sub basin, and verified by the measured runoff, MODIS and glacier cataloging data. On the basis of the original first edition, this data has considered the spatial distribution characteristics of precipitation, which can better describe the precipitation characteristics in alpine regions.
SUN He
This data is generated based on meteorological observation data, hydrological station data, combined with various assimilation data and remote sensing data, through the preparation of the Qinghai Tibet Plateau multi-level hydrological model system WEB-DHM (distributed hydrological model based on water and energy balance) coupling snow, glacier and frozen soil physical processes. The time resolution is monthly, the spatial resolution is 5km, and the original data format is ASCII text format, Data types include grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation in the month). If the asc cannot be opened normally in arcmap, please top the first 5 lines of the asc file.
WANG Lei, CHAI Chenhao
This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation), simulated and output through the WEB-DHM distributed hydrological model of the Indus River basin, with temperature, precipitation, barometric pressure, etc. as input data.
WANG Lei, LIU Hu
Both a decrease of sea ice and an increase of surface meltwater, which may induce ice-flow speedup and frontal collapse, have a significant impact on the stability of the floating ice shelf in Greenland. However, detailed dynamic precursors and drivers prior to a fast-calving process remain unclear due to sparse remote sensing observations. Here, we present a comprehensive investigation on hydrological and kinematic precursors before the calving event on 26 July 2017 of Petermann Glacier in northern Greenland, by jointly using remote sensing observations at high-temporal resolution and an ice-flow model. Time series of ice-flow velocity fields during July 2017 were retrieved with Sentinel-2 observations with a sub-weekly sampling interval. The ice-flow speed quickly reached 30 m/d on 26 July (the day before the calving), which is roughly 10 times quicker than the mean glacier velocity.
JIANG Liming
Glaciers are sensitive to climate change. With global warming, the melting of glaciers continues to accelerate all over the world. Surging glaciers are glaciers with intermittent and periodic acceleration, which is a sensitive indicator of climate change. Based on Landsat and Sentinel satellite images from 1980s to 2020, the study area images were obtained by filtering, stitching, and cropping. Among them, the L1GS level images collected by Landsat TM sensor were geo-registered using a second-order polynomial, and the error of the geo- registered images was less than one pixel. After image template matching with an orientation correlation algorithm, this data set provides the surface ice flow velocity of a typical surging glacier in the Greenland ice sheet, Sortebræ Glacier in different period from 1980s to 2020. It is expected to contribute to the research on the surging process of Sortebræ Glacier and the discussion on the mechanism of glacier surging in the context of global warming.
QIAO Gang , SUN Zixiang , YUAN Xiaohan
According to the characteristics of terrain data related to different glacier regions, the elevation data of glacier regions are extracted using the established glacier elevation extraction method. The technical route mainly includes:, Using multi-source elevation difference correction method, DEMs registration and elevation correlation deviation correction are realized through Matlab programming, and finally the glacier elevation change from 1970 to 2000 is calculated; (2) Extracting glacier elevation change based on ICEsat data: First, convert GLA14 binary format data into ASCII text data using IDL Readers tool provided by NSIDC, then conduct saturation correction and post-processing of slope and cloud error elimination through Matlab programming, and use multi-source elevation difference correction method to achieve ICEsat and SRTM data registration and elevation related deviation correction, Finally, the annual change trend regression fitting method is used to obtain the elevation change of glaciers from 2003 to 2009; (3) According to two different types of glacier terrain data, the glacier elevation change is extracted.
ZHOU Jianmin
According to the characteristics of terrain data related to different glacier regions, the elevation data of glacier regions are extracted using the established glacier elevation extraction method. The technical route mainly includes:, Using multi-source elevation difference correction method, DEMs registration and elevation correlation deviation correction are realized through Matlab programming, and finally the glacier elevation change from 1970 to 2000 is calculated; (2) Extracting glacier elevation change based on ICEsat data: First, convert GLA14 binary format data into ASCII text data using IDL Readers tool provided by NSIDC, then conduct saturation correction and post-processing of slope and cloud error elimination through Matlab programming, and use multi-source elevation difference correction method to achieve ICEsat and SRTM data registration and elevation related deviation correction, Finally, the annual change trend regression fitting method is used to obtain the elevation change of glaciers from 2003 to 2009; (3) According to two different types of glacier terrain data, the glacier elevation change is extracted.
ZHOU Jianmin
The data include three files on the spatial variation of surface elevation of endorheic glaciers in the Tibetan Plateau from 1975-2000 (100m), the mean elevation change values of glaciers in each sub-basin of the endorheic region from 1975-2020, and the basin boundaries and zoning. The glacier surface elevation changes from 1975-2000 were obtained based on 32 pairs of KH-9 data and NASADEM, where the results for the Muzetag and Puruogangri areas were obtained from Zhou et al. (2018) and Bhattacharya et al. (2021) respectively The average elevation change results for each 5-year period from 1995-2020 for the respective basins were obtained based on data published by Huggonet et al. (2021), and here it is assumed that the glacier thickness changes from 1995-2000 are similar to those from 2000-2005. Due to the limitation of KH-9 data quality and the glacier characteristics in the instream area, there are many null areas, and it is recommended to combine the zoning and calculate the change results for each elevation zone first, and then project them to each sub-basin.
CHEN Wenfeng, ZHANG Guoqing
Pine Island Glacier, Swett Glacier, etc. are distributed in the basins of the Antarctic Ice Sheet 21 and 22, which is one of the areas with the most severe melting in the Southwest Antarctica. This dataset first uses Cryosat-2 data (August 2010 to October 2018) to establish a plane equation in each regular grid, taking into account terrain items, seasonal fluctuations, backscattering coefficients, wave front width, lifting rails and other factors, and calculates the elevation change of ice cover surface in the grid through least square regression. In addition, we used ICESat-2 data (October 2018 to December 2020) to calculate the surface elevation change during the two periods by obtaining the elevation difference at the intersection of satellite lifting orbits in each regular grid. The spatial resolution of surface elevation change data in two periods is 5km × 5km, the file format is GeoTIFF, the projection coordinate is polar stereo projection (EPSG 3031), and it is named by the name of the satellite altimetry data used. The data can be opened using ArcMap, QGIS and other software. The results show that the average elevation change rate of the region from 2010 to 2018 is -0.34 ± 0.08m/yr, which belongs to the area with severe melting. The annual average elevation change rate from October 2018 to November 2020 is -0.38 ± 0.06m/yr, which is in an intensified state compared with CryoSat-2 calculation results.
YANG Bojin , HUANG Huabing , LIANG Shuang , LI Xinwu
Continued global warming and degradation of the cryosphere are raising concerns about adaptation to environmental instability in mountain areas. In recent decades, glacier-related slope failures, such as ice avalanches and rock avalanches on glaciers, have been frequently documented. In this study, we create a global inventory of glacier-related landslides to examine their distribution, trends, fractures, and relationship to climate change. During the period 1901-2019, 737 glacier-related landslides were recorded, including 156 ice avalanches, 89 ice-rock avalanches, 26 glacier slides, and 466 supraglacial rock avalanches. The Pacific Northwest had the most recorded cases (N = 440, 60%), with supraglacial rockfalls being the most dominant. In addition, the currently published list of glacial lake outburst floods of regional or global nature is integrated and refined, and moraine lake outburst flood events are separated separately. 380 moraine lake outburst flood events were counted between 1901 and 2020, making it the most complete list available on a global scale.
ZHANG Taigang, WANG Weicai
The data is an excel file, which includes four tables named as follows: Altay Snow DOC Time Series, Altay Snow Pit Data, Altay Snow MAC (absorption section) and Central Asia Mos Island Glacier BC, OC, DUST Data. Altay snow DOC table includes seven columns including sample number, sampling date, sampling time, sampling depth, DOC-PPM, BC-PPb and TN-PPM, and 47 sample data. Altay snow pit table includes 8 columns including snow pit number, sample number, sampling date, sampling time, sampling depth, DOC-PPM, BC-PPb and TN-PPM, and 238 sample data. Altay snow MAC table includes: sampling time, MAC and AAE, a total of three columns, and 46 sample data. The BC, OC and DUST data tables of glaciers in Central Asia's Muse Island include 8 columns: code no (sample number), Latitude (latitude), Longitude (longitude),/m a.s.l (altitude), snow type (snow type), BC, OC and DUST, which are analyzed by sampling time. There are 105 rows of data in total. Abbreviation explanation: DOC: Dissolved Organic Carbon MAC: mass absorption cross section BC: black carbon DUST: Dust OC: Organic carbon TN: Total Nitrogen PPM: ug g-1 (microgram per gram) PPb: ng g-1 (nanogram per gram)
ZHANG Yulan
The alpine region of Asia is the third pole in the world, and it is called the "Asian water tower". Affected by climate warming, glaciers continue to lose money, which has profoundly changed the supply-demand relationship of glacial water resources. In order to systematically understand the response of glaciers to climate change, the project reveals the relationship between the change of glacier material balance and climate factors through the sensitivity of glacier material balance. The data includes two maps: the sensitivity distribution map of material balance to temperature and precipitation and the climate sensitivity zoning. In the past 70 years, there have been significant differences in the evolution sequence of glacier material balance among mountain systems in the high mountain region of Asia. The glaciers in the Karakoram and West Kunlun regions have shown a stable state, and the material balance is a weak positive balance, while the Himalayas, Tianshan and Qilian Mountains have shown an accelerated trend after 1990. This is mainly due to the sensitivity of material balance to temperature and precipitation. The monthly scale material balance model is driven by 0.5 ° resolution era5 temperature and precipitation data, and the material balance calibration parameters of 43 monitored glaciers are 1 ° from 2000 to 2016 × The parameters are spatially constrained by the 1 ° aster material balance data, and the material balance sequences of 95085 glaciers in the high mountain region of Asia from 1951 to 2020 are reconstructed by using the method of extrapolation of spatial parameters. The sensitivity of glacier material balance to temperature (± 0.5K, ± 1K, ± 1.5k) and precipitation (± 10%, ± 20%, ± 30%) is analyzed, In combination with the influencing factors of glacier material balance (distribution of summer temperature, ratio of summer precipitation, distribution of glacier types, distribution of clear sky solar radiation in summer, etc.), the glacial climate sensitivity in the high mountain region of Asia is classified and divided into four categories, as shown in Fig. 4: the main control area of air temperature: the temperature is the main control factor of glacier material balance change, and precipitation occupies a secondary position; Precipitation control area: the glacier is mainly controlled by precipitation, and the temperature in the glacier area is lower than 0 ° C throughout the year; Temperature and precipitation control area of accumulated glacier in winter: refers to that the glacier is mainly supplied by precipitation in winter, and the change of material balance of the glacier is the result of the joint action of temperature and precipitation; Summer cumulative glacier temperature and precipitation control area: refers to the supply mode of glacier is summer precipitation, and the material balance of glacier is the result of the joint action of temperature and precipitation.
SHANGGUAN Donghui
1) The data content is the exposure age of the Cosmogenic Nuclide 10Be of the moraine left by the glaciers around the Muztagh Ata peak in the Holocene, including the sampling location, 10Be concentration, calculation results, etc. 2) 10Be concentration data are from published literature. Referring to the latest 10Be yield in the world, three different yield correction methods are used to calculate the exposure age of moraine samples. 3) Compared with the chronological data of the original published literature, this data is more accurate, and the chronological results given by the three methods can be compared with each other, with better concentration within the error range. 4) The data can be used to understand the Holocene change law of glaciers in Pamir region and provide data support for chronological comparison of glacial evolution in the northwest of the plateau.
XU Xiangke, XU Baiqing
1) The data include annual scale oxygen isotope and accumulation records of ice cores from 1900 to 2011, which respectively reflect the temperature and precipitation changes in the study area; 2) For analysis, the ice core samples were first measured using Picaro δ 18O and as per δ The seasonal variation characteristics of 18O determine the age of ice core; The accumulation of ice cores is calculated according to the density of ice cores, the length of ice cores per year and the glacier flow model; 3) Professional laboratory personnel and front-line scientific research personnel operate and maintain the instrument to ensure the reliability of analysis data; 4) The data can be used to analyze the climate and environmental changes in the typical westerly region of the Qinghai Tibet Plateau over the past 100 years, and can be used to explore the evolution of glaciers in this period, providing scientific reference for predicting the future evolution of glaciers, changes in hydrology and water resources and their impact on human activities.
XU Baiqing
Glacier surface albedo is a key parameter in the process of glacier mass and energy balance. The data include annual mean glacier surface albedo and annual minimum glacier surface albedo for each year of the 2000-2020 ablation period (June-August) in the High Mountain Asia. Based on the MODIS 500m resolution daily snow albedo products (including MOD10A1 and MYD10A1), firstly, mean-synthesis was applied to the morning star data MOD10A1 and afternoon star data MYD10A1, followed by interpolation and null-filling using mean-filtering for data within a ±2 day window, and finally based on the minimum and mean methods to obtain the annual mean albedo and annual minimum albedo for glaciers in High Mountain Asia were obtained based on the minimum and mean methods. Compared to the original data, the accuracy and coverage of the data are greatly improved. It can provide ice surface albedo input data for studying the relationship between glacier albedo and matss balance and for glacier models.
XIAO Yao
In recent years, with the acceleration of the melting of the Antarctic ice sheet, a large amount of ice melt has formed on the surface of the ice sheet from 2000 to 2019. It is of great significance to study the material balance of the Antarctic ice sheet to deeply understand the spatial-temporal distribution and dynamic changes of the melt water on the Antarctic ice sheet. This data set is based on Landsat7 and landsat8 images with 30 m spatial resolution from 2000 to 2019. By using normalized water body index, Gabor filtering and morphological path opening operations, the ice melt grid data set is generated, and the grid water body mask is converted into vector data in ArcGIS. This data set is based on the 250m ice surface melt water data set of the Antarctic ice sheet melting area (Alexander Island, Antarctic Peninsula) from 2000 to 2019 extracted from Landsat images. The time is concentrated from December to February (Southern Hemisphere summer)
YANG Kang
We propose an algorithm for ice fissure identification and detection using u-net network, which can realize the automatic detection of ice fissures of Typical Glaciers in Greenland ice sheet. Based on the data of sentinel-1 IW from July and August every year, in order to suppress the speckle noise of SAR image, the probabilistic patch based weights (ppb) algorithm is selected for filtering, and then the representative samples are selected and input into the u-net network for model training, and the ice cracks are predicted according to the trained model. Taking two typical glaciers in Greenland (Jakobshavn and Kangerdlussuaq) as examples, the average accuracy of classification results can reach 94.5%, of which the local accuracy of fissure area can reach 78.6%, and the recall rate is 89.4%.
LI Xinwu , LIANG Shuang , YANG Bojin , ZHAO Jingjing
We propose an algorithm for ice crack identification and detection using u-net network, which can realize the automatic detection of Antarctic ice cracks. Based on the data of sentinel-1 EW from January to February every year, in order to suppress the speckle noise of SAR image, the probabilistic patch based weights (ppb) algorithm is selected for filtering, and then representative samples are selected and input into the u-net network for model training, and the ice cracks are predicted according to the trained model. Taking five typical ice shelves（Amery、Fimbul、Nickerson、Shackleton、Thwaiters) in Antarctica as an example, the average accuracy of classification results can reach 94.5%, of which the local accuracy of fissure area can reach 78.6%, and the recall rate is 89.4%.
LI Xinwu , LIANG Shuang , YANG Bojin , ZHAO Jingjing
Global solar radiation and diffuse horizontal solar radiation at Dome C (Antarctica) are measured by radiation sensors (pyranometers CM22, Kipp & Zonen Inc., The Netherlands), and water vapor pressure (hPa) at the ground are obtained from the IPEV/PNRA Project “Routine Meteorological Observation at Station Concordia”, http://www.climantartide.it. This dataset includes hourly solar radiation and its absorbing and scattering losses caused by the absorbing and scattering atmospheric substances (MJ m-2, 200-3600 nm), and the albedos at the top of the atmosphere and the surface. The above solar radiations are calculated by using an empirical model of global solar radiation (Bai, J.; Zong, X.; Lanconelli, C.; Lupi, A.; Driemel, A.; Vitale, V.; Li, K.; Song, T. 2022. Long-Term Variations of Global Solar Radiation and Its Potential Effects at Dome C (Antarctica). Int. J. Environ. Res. Public Health, 19, 3084. https://doi.org/10.3390/ijerph19053084). The observed global solar radiation and meteorological parameters are available at https://doi.org/10.1594/PANGAEA.935421. The data set can be used to study solar radiation and its attenuation at Dome C, Antarctica.
BAI Jianhui
Global solar radiation at Qomolangma station (The Tibetan Plateau) is measured by radiation sensor (pyranometers CM22, Kipp & Zonen Inc., The Netherlands), and water vapor pressure (hPa) at the ground is measured by HMP45C-GM (Vaisala Inc., Vantaa, Finland). This dataset includes hourly solar radiation and its absorbing and scattering losses caused by the absorbing and scattering atmospheric substances (MJ m-2, 200-3600 nm), and the albedos at the top of the atmosphere and the surface. The above solar radiations are calculated by using an empirical model of global solar radiation (Bai, J.; Zong, X.; Ma, Y.; Wang, B.; Zhao, C.; Yang, Y.; Guang, J.; Cong, Z.; Li, K.; Song, T. 2022. Long-Term Variations in Global Solar Radiation and Its Interaction with Atmospheric Substances at Qomolangma. Int. J. Environ. Res. Public Health, 19, 8906. https://doi.org/10.3390/ijerph19158906). The observed global solar radiation and meteorological variables are available at https://data.tpdc.ac.cn/zh-hans/data/b9ab35b2-81fb-4330-925f-4d9860ac47c3/. The data set can be used to study solar radiation and its attenuation at Qomolangma region.
BAI Jianhui
The data product of ice flow velocity field of Rayner Glacier in East Antarctica in 1963 based on ARGON historical remote sensing images. Using two declassified satellite images taken in 1963 with an interval of two months, the early ice flow velocity field of the Reina Glacier in eastern Antarctica is estimated by hierarchical matching based on parallax decomposition. The accuracy of the estimated velocity map can reach 70 m/year. A method for estimating the surface velocity of cooperative glaciers based on the parallax decomposition of optical stereo images. First, the image to be matched generates the core image and the pyramid of the core image; Next, the ice flow area mask is used to divide the image into ice flow area and non ice flow area for matching respectively. In addition to the normal matching steps, the ice flow area also needs to perform parallax demarcation to distinguish the impact of ice flow movement on terrain parallax. Finally, through layer by layer matching, we can get the DTM and ice flow diagram of the object side at the bottom. This data is of great significance for reconstructing the early surface morphology and ice flow velocity of Rayner Glacier in East Antarctica.
LI Rongxing , QIAO Gang , YE Wenkai
The data set includes the observed and simulated runoff into the sea and the composition of each runoff component (total runoff, glacier runoff, snowmelt runoff, rainfall runoff) of two large rivers in the Arctic (North America: Mackenzie, Eurasia: Lena), with a time resolution of months. The data is a vic-cas model driven by the meteorological driving field data produced by the project team. The observed runoff and remote sensing snow data are used for correction. The Nash efficiency coefficient of runoff simulation is more than 0.85, and the model can also better simulate the spatial distribution and intra/inter annual changes of snow cover. The data can be used to analyze the runoff compositions and causes of long-term runoff change, and deepen the understanding of the runoff changes of Arctic rivers.
ZHAO Qiudong, WU Yuwei
This product provides the data set of key variables of the water cycle of major Arctic rivers (North America: Mackenzie, Eurasia: Lena from 1971 to 2017, including 7 variables: precipitation, evapotranspiration, surface runoff, underground runoff, glacier runoff, snow water equivalent and three-layer soil humidity, which are numerically simulated by the land surface model vic-cas developed by the project team. The spatial resolution of the data set is 0.1degree and the temporal resolution is month. This data set can be used to analyze the change of water balance in the Arctic River Basin under long-term climate change, and can also be used to compare and verify remote sensing data products and the simulation results of other models.
ZHAO Qiudong, WANG Ninglian, WU Yuwei
This product provides the data set of key variables of the water cycle of Arctic rivers (North America：Mackenzie, Eurasia：Lena) from 1998 to 2017, including 7 variables: precipitation, evapotranspiration, surface runoff, underground runoff, glacier runoff, snow water equivalent and three-layer soil humidity, which are numerically simulated by the land surface model vic-cas developed by the project team. The spatial resolution of the data set is 50km and the temporal resolution is month. This data set can be used to analyze the change of water balance in the Arctic River Basin under climate change, and can also be used to compare and verify remote sensing data products and the simulations of other models.
ZHAO Qiudong, WANG Ninglian, WU Yuwei
Mountain glaciers are important freshwater resources in Western China and its surrounding areas. It is at the drainage basin scale that mountain glaciers provide meltwater that humans exploit and utilize. Therefore, the determination of glacierized river basins is the basis for the research on glacier meltwater provisioning functions and their services. Based on the Randolph glacier inventory 6.0, Chinese Glacier Inventories, China's river basin classifications (collected from the Data Centre for Resources and Environmental Sciences, Chinese Academy of Sciences), and global-scale HydroBASINS (www.hydrosheds.org), the following dataset was generated by the intersection between river basins and glacier inventory: (1) Chinese glacierized macroscale and microscale river basins; (2) International glacierized macroscale river basin fed by China’s glaciers; (3) Glacierized macroscale river basin data across High Mountain Asia. This data takes the common river basin boundaries in China and the globe into account, which is poised to provide basic data for the study of historical and future glacier water resources in China and its surrounding areas.
SU Bo
This dataset contains the glacier outlines in Qilian Mountain Area in 2015. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2018 were used as basic data for glacier extraction. Sentinel-2 images, 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 2018, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia Li Jia LI Jia LI Jia
This dataset contains the glacier outlines in Qilian Mountain Area in 2019. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2019 were used as basic data for glacier extraction. Sentinel-2 images, 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 2019, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia Li Jia LI Jia LI Jia
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. Sentinel-2 images, 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.
Li Jia Li Jia LI Jia LI Jia
This dataset contains the glacier outlines in Qilian Mountain Area in 2021. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2021 were used as basic data for glacier extraction. Sentinel-2 images, 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 2021, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia Li Jia LI Jia LI Jia
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
This dataset includes the glacier elevation change data in the High Mountain Asia (HMA) region from 2018 to 2020 derived from Ice, Cloud and land Elevation Satellite (ICESat-2) data. The glacial elevation changes in the High Mountain Asia region were calculated using ICESat-2 data (2018-2020) and SRTM DEM data in 2000, taking into account the inhomogeneity of glacier changes and area distribution at different elevations and slopes (weighted average of glacier area of elevation and slope bins in 1°×1° grid ). The dataset can provide the annual change information of glacier elevation in the High Mountain Asia region from 2018 to 2020 relative to 2000. These data can be used for studies of climate change in the High Mountain Asia.
SHEN Cong , JIA Li
This dataset includes the glacier elevation change data in the High Mountain Asia (HMA) region from 2003 to 2008 derived from Ice, Cloud and land Elevation Satellite (ICESat-1) data. The glacial elevation changes in the High Mountain Asia region were calculated using ICESat-1 data (2003-2008) and SRTM DEM data in 2000, taking into account the inhomogeneity of glacier changes and area distribution at different elevations and slopes (weighted average of glacier area of elevation and slope bins in 1°×1° grid ). The dataset can provide the annual change information of glacier elevation in the High Mountain Asia region from 2003 to 2008 relative to 2000. These data can be used for studies of climate change in the High Mountain Asia.
SHEN Cong , JIA Li
1) The data included the thickness, coordinates and elevation of Xiaodongkemadi glacier and was measured from July 26 to 28, 2021; 2) The data was measured by the ground penetrating radar with working frequency of 100MHz developed by China Institute of Water Resources and Hydropower Research. The thickness of the glacier was obtained through the processing and analysis of the radar echo image. The dielectric constant of the ice was 3.2, and the coordinates and elevation of the measuring points were measured by the RTK system; 3) The data can be used to study the changes of glacier thickness, mass balance , runoff and so on.
FU Hui
Glacier thickness variation is a key parameter for glacier change monitoring. Historical high-resolution KH-9 images (1974), SRTM DEM data products (2000), TanDEM-X dual-station interferometric SAR data (2011-2014) and SPOT-7 images (2015) data were used to generate multi-temporal digital elevation models of the Yanong Glacier in southeastern Tibet based on optical photogrammetry and radar interferometry techniques, respectively. For the TanDEM-X radar data, the geometric positioning errors in the glacier area were removed during the data processing, and the outliers in the snow cover area in the KH-9 DEM were removed. Subsequently, the inter-decadal and inter-annual thickness variation datasets of Yalong glacier during 1975-2015 were finally generated after X-band and C-band radar wave penetration depth corrections. The spatial resolution of this data set is 30m, which can be further used for calibration of glacier evolution model parameters and analysis of glacier future changes.
ZHOU Yushan , LI Xin, ZHENG Donghai, LI Zhiwei
1) Data content: Glacier elevation change in the Southeastern Tibetan Plateau in the past two decades, including time series during 2000 and 2020 and glacier elevation change from 2000 to 2019 at 0.5° grid scale. 2) Data sources and processing methods: Time series during 2000 and 2020 were generated from glacier monitoring methods integrating satellite altimetry (ICESat, CryOSat-2, ICESAT-2), topographic data (DEM derived from ASTER L1A images in 2014), and satellite gravity (GRACE and GLDAS). The grid-scale glacier elevation changes were calculated by ICESAT-2 and NASADEM. 3) Description of data quality: This data is consistent with UAV derived DSM results, GPS observations, and reported results. The temporal resolution and spatial resolution of this data have been significantly improved. 4) Data application results and prospects: This data can be used to calibrate glacial / hydrological model. The data can also be compared with future studies.
ZHAO Fanyu, LONG Di, LI Xingdong, HUANG Qi, HAN Pengfei
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
The data include K, Na, CA, Mg, F, Cl, so 4 and no 3 in the glacier runoff of zhuxigou, covering most of the inorganic dissolved components. The detection limit is less than 0.01 mg / L and the error is less than 10%; The data can be used to reflect the contribution of chemical weathering processes such as sulfide oxidation, carbonate dissolution and silicate weathering to river solutes in zhuxigou watershed, and then accurately calculate the weathering rates of carbonate and silicate rocks, so as to provide scientific basis for evaluating the impact of glaciation on chemical weathering of rocks and its carbon sink effect.
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
This data is the simulated data of glacier distribution in the alpine region of Asia since the last glacial maximum, It includes the annual resolution glacier area change sequence of typical regions (High mountain Asia, Tianshan Mountains, Himalayas and Pamir Plateau) and typical periods (LGM (20000 ~ 19000ka), HS1 (17000 ~ 16000ka), BA (~ 14900 ~ 14350ka), yd (12900 ~ 12000ka), eh (9500 ~ 8500ka), MH (6500 ~ 5500ka), LH (3500 ~ 2500ka) and modern (1951 ~ 1990)) 1 km resolution glacier distribution in High Mountain Asia. This data are created by taking the trace full forcing simulation based on ccsm3 climate model as the external forcing field to drive the 1 km resolution PISM ice sheet model. This data can be used to study the changes of glacier distribution in the alpine region of Asia since the last glacial maximum and its impact on environmental and climatic factors such as lake water level, runoff and landform.
YAN Qing
Qiangyong glacier: 90.23 °E, 28.88° N, 4898 m asl. The surface is bedrock. The record contains data of absolute pressure and water temperature. Data from the automatic water gauge was collected using USB equipment at 12:00 on June 15, 2021, with a recording interval of one hour, and data was downloaded at 12:00 on Nov. 2, 2021. There is no missing data. Jiagang glacier: 88.69°E, 30.82°N, 5362 m asl. The surface is rubble and weeds. The record contains data of absolute pressure and water temperature. Data from the automatic water gauge was collected using USB equipment at 20:00 on June 19, 2021, with a recording interval of one hour, and data was downloaded at 11:00 onSept 18 , 2021. There is no missing data.
ZHANG Dongqi
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
This is a comprehensive dataset on microbial abundance, dissolved organic carbon (DOC), and total nitrogen (TN) for glaciers on the TP based on extensive field sampling from 2010. The dataset comprises 5,409 microbial abundance records of ice cores and snow pits from 12 glaciers and 2,532 DOC and TN records of five habitats, including ice core, snow pit, surface ice, surface snow, and proglacial runoff, from 38 glaciers. These glaciers covered broad areas and diverse climate conditions with a multiyear average temperature ranging from -13.4 ℃ (the Guliya glacier) to 2.9 ℃ (the Zhuxigou glacier) and multiyear average precipitation ranging from 76.9 mm (the No.15 glacier) to 927.8 mm (the 24K glacier), which makes this dataset suitable for studies across the entire TP. To the best of our knowledge, this is the first dataset of microbial abundance and TN in glaciers on the TP, and also the first dataset of DOC in ice cores on the TP. These new data could provide valuable information for researches on the glacier carbon and nitrogen cycle and assessing the potential impacts of glacier retreat due to global warming on downstream ecosystems.
LIU Yongqin
The mass loss of the Greenland ice sheet has been the main contributor to global sea level rise in recent decades. Under the trend of global warming, the Greenland ice sheet is melting faster. It is of great scientific significance to explore the causes of mass loss and its response to climate change. Based on the MEaSUREs Greenland groundingline and the basin boundaries, we discretize the groundingline, combine the MEaSUREs annual ice velocity data from 1985 to 2015 with the BedMachine v3 ice thickness data, and vectorially calculate the ice discharge at each flux gate of the groundingline. We use the surface mass balance data of RACMO2.3p2 model to spatially calculate the surface mass balance of each basin, and combined it with the ice discharge results to obtain the Greenland ice sheet mass balance data set (1985-2015). The data set includes the mass balance results of each basin of the Greenland ice sheet in the year 1985, 2000 and 2015, and the annual ice velocity data, ice thickness and annual ice discharge corresponding to the location of each flux gate. The data set realizes the fine evaluation of ice flux at the groundingline, and reflect the changes and spatial distribution characteristics of the mass balance of each basin of the Greenland ice sheet in recent 30 years. It provides basic data for the subsequent fine change evaluation and prediction of the mass balance of the Greenland ice sheet and the exploration of the mechanism of ice sheet loss.
LIN Yijing, CHENG Xiao
The Antarctic ice sheet is one of the largest potential sources of global sea level rise. Accurately determining the mass budget of the ice sheet is the key to understand the dynamic changes of the Antarctic ice sheet. It is very important to understand the evolution process of the ice sheet and accurately predict the future global sea level rise. Based on the MEaSUREs Antarctic groundingline and the basin boundaries, we discretize the groundingline, combine the MEaSUREs and RAMP annual ice velocity data from 1985 to 2015 with the BedMachine ice thickness data, and vectorially calculate the ice discharge at each flux gate of the groundingline. We use the surface mass balance data of RACMO2.3p2 model to spatially calculate the surface mass balance of each basin, and combined it with the ice discharge results to obtain the Antarctic ice sheet mass balance data set (1985-2015). The data set includes the mass balance results of each basin of the Antarctic ice sheet in the year 1985, 2000 and 2015, and the annual ice velocity data, ice thickness and annual ice discharge corresponding to the location of each flux gate. The data set realizes the fine evaluation of ice flux at the groundingline, and reflect the changes and spatial distribution characteristics of the mass balance of each basin of the Antarctic ice sheet in recent 30 years. It provides basic data for the subsequent fine change evaluation and prediction of the mass balance of the Antarctic ice sheet and the exploration of the mechanism of ice sheet loss.
LIN Yijing, CHENG Xiao
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
Geladandong region is an important and typical source region of great rivers and lakes in the Qinghai Tibet Plateau. This data set provides DEM covering glaciers in the source region of the Yangtze River and Selin Co with different time scales and resolutions to calculate the seasonal and decadal changes of glacier surface elevation in the source region. This data set includes seven 5-meter resolution TanDEM-X data from July 2016 to 2017, which can be used to calculate the seasonal change of glacier surface elevation; it includes one KH-9 DEM with a resolution of 30m in 1976, five TanDEM-X with a resolution of 30m in 2011, one TanDEM-X in 2014 and three TanDEM-X in 2017 with a resolution of 30m. The data can be used to calculate the change of glacier surface elevation during 1976-2000, 2000-20112011-2017. At the same time, Landsat ETM data are used to extract the glacier outline in 1976and we divide it according to the RGI6.0; The right figure shows the spatial and temporal coverage information of the data set, and the base figure is the orthophoto corrected kh-9 image.
CHEN Wenfeng
The surface elevation of the ice sheet is very sensitive to climate change, so the elevation change of the ice sheet is considered as an important variable to evaluate climate change. The time series of long-term ice sheet surface elevation change has become a fundamental data for understanding climate change. The longest time series of ice sheet surface elevation can be established by combining the observation records of radar satellite altimetry missions. However, the previous methods for correcting the intermission bias still have error residue when cross-calibrating different missions. Therefore，we modify the commonly used plane-fitting least-squares regression model by restricting the correction of intermission bias and the ascending–descending bias at the same time to ensure the self-consistency and coherence of surface elevation time series across different missions. Based on this method, we use Envisat and CryoSat-2 data to construct the time series of Antarctic ice sheet elevation change from 2002 to 2019. The time series is the monthly grid data, and the spatial grid resolution is 5 km×5 km. Using airborne and satellite laser altimetry data to evaluate the results, it is found that compared with the traditional method, this method can improve the accuracy of intermission bias correction by 40%. Using the merged elevation time series, combining with firn densification-modeled volume changes due to surface processes, we find that ice dynamic processes make the ice sheet along the Amundsen Sea sector the largest volume loss of the Antarctic ice sheet. The surface processes dominate the volume changes in Totten Glacier sector, Dronning Maud Land, Princess Elizabeth Land, and the Bellingshausen Sea sector. Overall, accelerated volume loss in the West Antarctic continues to outpace the gains observed in the East Antarctic. The total volume change during 2002–2019 for the AIS was −68.7 ± 8.1 km3/y, with an acceleration of −5.5 ± 0.9 km3/y2.
ZHANG Baojun, WANG Zemin, YANG Quanming, LIU Jingbin, AN Jiachun, LI Fei, GENG Hong
This data set includes the average concentrations of chemical species (Na+, K+, Mg2+, Ca2+ and TDS) in meltwater runoff draining 77 glaciers worldwide, annual glacial runoff from eight mountain ranges in Asia, and the mineral compositions of glacial deposits in some typical glacial catchments within Asia. This data set comes from the field monitoring of 19 glaciers in Asia by the data set provider, the previous published data worldwide, and the data shared by the authors of published papers. This data set can be used to evaluate the impact of climate warming on glacier erosion process and chemical weathering process, and the impact of glacier melt caused by climate warming on downstream ecosystems and element cycles.
LI Xiangying
In recent years, the melting of the Antarctic ice sheet has accelerated, and a large amount of surface melt water has appeared on the surface of the Antarctic ice sheet. Understandings of the spatial distribution and dynamics of surface melt water on the Antarctic ice sheet is of great significance for the study of the mass balance of the Antarctic ice sheet. This dataset is 2000-2020 surface melt water dataset of Antarctica Ice Sheet typical melting area (Prydz bay) based on 10-30m Landsat-7, 8 and Sentinel-2 images. The projections are polar azimuthal projections in vector format (ESRI Shapefile) and raster format (GeoTIFF) and the time is Southern Hemisphere summer (December-to-February).
YANG Kang
This dataset contains the glacier outlines in Qilian Mountain Area in 2019. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2019 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 2019, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia Li Jia LI Jia LI Jia
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.
Li Jia Li Jia LI Jia LI Jia
The data include K, Na, CA, Mg, F, Cl, so 4 and no 3 in the glacier runoff of zhuxigou, covering most of the inorganic dissolved components. The detection limit is less than 0.01 mg / L and the error is less than 10%; The data can be used to reflect the contribution of chemical weathering processes such as sulfide oxidation, carbonate dissolution and silicate weathering to river solutes in zhuxigou watershed, and then accurately calculate the weathering rates of carbonate and silicate rocks, so as to provide scientific basis for evaluating the impact of glaciation on chemical weathering of rocks and its carbon sink effect.
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
Glacier surface micrometeorology is to observe the wind direction, wind speed, temperature, humidity, air pressure, four component radiation, ice temperature and precipitation at a certain height of the glacier surface. Glacier surface micrometeorology monitoring is one of the important contents of glacier monitoring. It is an important basic data for the study of energy mass balance, glacier movement, glacier melt runoff, ice core and other related model simulation, which lays a foundation for exploring the relationship between climate change and glacier change. Automatic monitoring is mainly carried out by setting up Alpine weather stations on the glacier surface, and portable weather stations can also be used for short-term flow monitoring. In recent years, more than 20 glacier surfaces in Tianshan, West Kunlun, Qilian, Qiangtang inland, Tanggula, Nianqing Tanggula, southeastern Tibet, Hengduan and Himalayas have been monitored. The data set is monthly meteorological data of glacier area and glacier end.
YANG Wei
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
High resolution pollen records from ice cores can indicate the relationship between seasonal vegetation changes and climate indicators. High resolution sporopollen analysis was carried out on the 32 m ice core sediments of Zuopu ice core in Qinghai Tibet Plateau. 117 SPOROPOLLEN ASSEMBLAGES were obtained. All the data are sporopollen percentage data, which are arranged in order of depth.
LV Houyuan
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
The dataset of of potential glacial lakes (PGLs) distribution in the Tibetan Plateau and its surrounding (TPS) are vector data (. SHP). The data set contains the ID, area, perimeter, volume and elevation of each PGL. The TPS region was divided into 17 subregions based on the river basins’ borders, including 8 outflow river basins, i.e., the Yellow, Yangtze, Mekong, Salween, Brahmaputra, Ganges, Indus, and Ob river basins, and 9 exorheic river basins, i.e., the Qiangtang, Hexi, Tarim, Qiadam, Junggar, Yili, Syr Darya, Amu Darya, and Mongolia river basins. This data is processed from theGlacier ice thickness distribution dataset (provided by Farinotti et al. (2019)). The grid difference between the initial DEM and the glacier ice thickness distribution was used to produce the DEM without glaciers. The overdeepenings were detected via two steps. First, we filled the depressions of the DEM without glaciers using a hydrology tool in the ArcGIS software. Second, using the filled DEM to subtract the DEM without glaciers, we ascertained the PGLs’ locations, areas, depths, and volumes. The quality of this data set depends on the quality of the original glacier thickness data, and the quality of the ice thickness dataset is the best of all similar data at present. The dataset of of potential glacial lakes distribution in the Tibetan Plateau and its surroundings can provide a new perspective from which to understand the future formation and evolution of glacial lakes in the TPS. It is anticipated that approximately 16,000 PGLs areas of greater than 0.02 km2 will be formed in the TPS, covering an area of 2253.95 ± 1291.29 km2 and holding a water volume of 60.49 ± 28.94 km3, which would contribute to a 0.16 ± 0.08 mm equivalent sea-level rise.
ZHANG Taigang, WANG Weicai, YAO Tandong, GAO Tanguang, AN Baosheng
This dataset includes data of glacier elevation changes in 2000‒2013 and 2000‒2017 at high spatial resolution (5 m). The specific areas are Namco area in the west section of Nyainqentangula Mountains (WNM) and Kangri Karpo area in the east section of Nyainqentangula Mountains (ENM). Glacier boundary refers to Randolph Glacier Inventory Version 4.0 (RGI 4.0). The glacier elevation changes were calculated from the DEM data generated by ZiYuan-3 Three-Line-Array (ZY-3 TLA) stereo images in 2013 and 2017 and SRTM DEM data in 2000, respectively. The data in the WNM include three periods, i.e., 2000‒2013, 2013‒2017 and 2000‒2017. The data in the ENM include one period, i.e., 2000‒2017. The spatial resolution of the dataset is 5 meters, the unit is m a^−1, the data format is GeoTIFF, the data type is floating-point, and the projection mode is UTM 46N for the west segment and UTM 47N for the east segment. The glacier elevation change can be transformed into the glacier mass balance (unit: w.e. a^−1) of corresponding temporal intervals by multiplying the average density of the glacier. This dataset can provide the details of the spatial patterns of glacier elevation changes to support modeling studies of glacier mass balance in this region.
REN Shaoting, JIA Li
Radar penetration correction is essential for accurately estimating glacier mass balance when using the geodetic methods based on the radar-derived Digital Elevation Model (DEM). Due to heterogeneous snow distribution and snowpack properties, the radar penetration depth varies by region and is basically dependent on the altitudes. Therefore, this data set gives the result of the penetration depth difference of SRTM C/X-band radar on 1°×1° grid of High Mountain Asia Glaciers. The data set contains 214 1°×1° grids SRTM X-band and C-band penetration depth difference in HMA, and a linear fitting expression for each grid. According to the geodetic method, the 30 m SRTM X-band and C-band DEM are used to obtain the results of the penetration depth difference between the SRTM X-band and C-band of the 1°×1° high grid in HMA, and obtain the relationship between the SRTM X-C-band penetration depth difference and the elevation in the glacier area (for specific methods, please refer to references). The data is stored in excel files. Observational data can provide important basic data for studying the glacier mass balance in HMA, and can be used by scientific researchers studying climate, hydrology and glaciers.
JIANG Liming JIANG Liming JIANG Liming
In the discussion of glacial deposition process, formation conditions and evolution, the analysis and study of Quaternary glacial sediment structure, gravel fabric, grain size characteristics, clastic minerals, clay minerals and chemical composition of moraines are of certain significance for understanding the depositional environment of moraines, the scale of glacial activities and the number of glacial periods. The results of X-ray diffraction analysis of clay minerals show that the clay mineral assemblages of all kinds of moraines are dominated by hydrated phlogopite. The composition of this clay mineral is characterized by glaciation and formation in a special environment. For example, the hydrated phlogopite in the moraine clay minerals (glacial mud) is particularly rich, which can form hydrated phlogopite clay rock. According to the results of chemical composition analysis of five moraine samples from different ages (Table 2), the highest content of SiO2 is 53.9%, followed by Al2O3, which accounts for 13.59%, followed by Cao, MgO, FeO, K2O, Fe2O3, Na2O, etc. According to analysis, the chemical composition of moraine is closely related to bedrock. However, due to the action of glaciers and water, its chemical composition changes greatly.
PENG Buzhuo, YANG Yichou, NIAN Yanyun
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
Qiangyong glacier: 90.23 °E, 28.88° N, 4898 m asl. The surface is bedrock. The record contains data of 1.5 m temperature, 1.5 m humidity, 2 m wind speed, 2 m wind orientation, surface temperature, etc. Data from the automated weather station was collected using USB equipment at 19:10 on August 6, 2019, with a recording interval of 10 minutes, and data was downloaded on December 20, 2020. There is no missing data but a problem with the wind speed data after 9:30 on July 14, 2020 (most likely due to damage to the wind vane). Jiagang glacier: 88.69°E, 30.82°N, 5362 m asl. The surface is rubble and weeds. The records include 1.5 meters of temperature, 1.5 meters of humidity, 2 meters of wind speed, 2 meters of wind direction, surface temperature, etc. The initial recording time is 15:00 on August 9, 2019, and the recording interval is 1 minute. The power supply is mainly maintained by batteries and solar panels. The automatic weather station has no internal storage. The data is uploaded to the Hobo website via GPRS every hour and downloaded regularly. At 23:34 on January 5, 2020, the 1.5 meter temperature and humidity sensor was abnormal, and the temperature and humidity data were lost. The data acquisition instrument will be retrieved on December 19, 2020 and downloaded to 19:43 on June 23, 2020 and 3:36 on September 25, 2020. Then the temperature and humidity sensors were replaced, and the observations resumed at 12:27 on December 21. The current data consists of three segments (2019.8.9-2020.6.30; 2020.6.23-2020.9.25; 2020.12.19-2020.12.29), Some data are missing after inspection. Some data are duplicated in time due to recording battery voltage, which needs to be checked. The meteorological observation data at the front end of Jiagang mountain glacier are collected by the automatic weather station Hobo rx3004-00-01 of onset company. The model of temperature and humidity probe is s-thb-m002, the model of wind speed and direction sensor is s-wset-b, and the model of ground temperature sensor is s-tmb-m006. The meteorological observation data at the front end of Jianyong glacier are collected by the US onset Hobo u21-usb automatic weather station. The temperature and humidity probe model is s-thb-m002, the wind speed and direction sensor model is s-wset-b, and the ground temperature sensor model is s-tmb-m006.
ZHANG Dongqi
According to the color satellite photos, some topographic maps and some actual investigation data, the area of modern glaciers in Namjagbarwa peak area is 1004.20 square kilometers only in wucuoyuan, gangrigab mountain to the west of Galongla, galabailei and the main peak area of Namjagbarwa peak. If there are no glaciers in the vicinity of Longzhu and maladang, plus 1200 square kilometers. Based on the thickness data of some actual observations during the investigation period, and according to some data and field investigation results, some major glaciers are counted and described, including glacier type, glacier orientation, glacier altitude, glacier length, glacier width and glacier area.
PENG Buzhuo, YANG Yichou
The data in the form of .xlsx store the meteorological varialbes observed on the East Rongbuk glacier from May to July. Two sheets, named "Surface_energy_budget" and "Cycle", respectivley, are included. In the sheet of "surface_energy_budget", the meteorological variables are as follows: Four-component radiations (incident solar radiation, reflected shortwave radiation, incoming longwave radiation, outgoing longwave radiation)、wind speed and direction, air temperature and relative humidity, cloud index, south Asian summer monsoon and albedo. In addition, net shortwave radiation, net longwave radiation, net radiation, sensible heat, latent heat and subsurface heat are also included. Energy fluxes are in unit of W m-2. The sheet of "Cycle" stores the diurnal cycle of the meteorological variables mentioned above. In the first line, the prefixes of "1"、"2" and “3” indicate three observational periods, i.e., "1" represents days from 1 - 28 May, "2" represents the period between 29 May 16 June and "3" indicates time episode from 17 June to 22 July.
LIU Weigang
This data set is the physical property data of Hengduan Mountain Glacier, reflecting the temperature condition of Hengduan Mountain Glacier. It was observed on Baishui No.1 glacier on the east slope of Yulong Mountain and dagongba glacier on the west slope of Gongga Mountain by the comprehensive scientific investigation team of Qinghai Tibet Plateau of Chinese Academy of Sciences from 1982 to 1984. The temperature field location, altitude, drilling information, ice surface condition, sampling time, sampling depth and measured temperature of Baishui No. 1 glacier on the east slope of Yulong and dagongba glacier on the west slope of Gongga are recorded in detail in the data, which are obtained from field investigation and calculation. At the same time, the velocity data of dagongba glacier and the surface strain rate, normal strain rate and its error and principal strain rate at 4700m of Baishui No.1 glacier in Yulongshan are available. This data is of great significance to the study of temperature and movement of glacial active layer in Hengduan Mountain area.
LI Jijun
The melting observation of Hengduan Moutain glacier is mainly carried out on Hailuogou Glacier on the east slope of Gongga and the large and small Gongba glacier on the west slope of Gongga. In addition, some ablation observations have been made on Baishui 1 glacier on the east slope of Yulong. According to the melting observation of the four glaciers in the above two mountains, there are some regional representativeness, which makes them reflect the basic situation of melting glaciers in Hengduan Mountain. This data set records the glacier ablation data of different time and different places: from June to August 1982, the Glacier No. 1 in Baishui on the east slope of Yulong mountain was observed at the altitude of 4200m, 4600m and 4800m. From August 27, 1982 to the end of August 1983, the annual measured data of different heights of Hailuogou Glacier tongue on the east slope of Gongga Mountain were collected. From July 12, 1982 to August 6, 1983, the observation data of Gongba glacier melting on the west slope of Gongga Mountain were recorded.
LI Jijun
This data is the statistics of the glaciers and their types in Hengduan Mountain area, the information of each glacier, and the data of some glacier snow lines and related parameters in China. The data includes eight tables, which are glacier Statistics (measured data) of Hengduan Mountains, glacier Statistics (measured data) of Hengduan Mountains, glacier types (measured data), basic characteristics (measured data) of some glacier recharge areas in Gongga Mountain, AAR value and avalanche area (measured data) of some glaciers in Gongga mountain, and ice field in Gongga mountain Data statistics of Sichuan (measured data), thickness measurement statistics of 4 glaciers in Gongga Mountain (measured data), snow line data of some glaciers in China and related parameters (data statistics).
LI Jijun
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.
LI Bingyuan
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
This data set includes daily, annual and multi-year surface mass balance data from Antarctic ice cap poles, ice (snow) cores / snow pits, automatic weather station altimeters and ground penetrating radar observations. The data come from published literature, data reports and international data sharing platform. After quality control, the most perfect data set of daily, annual and multi-year resolution of surface mass balance of Antarctic ice sheet has been formed. Its middle-aged resolution data span the past 1000 years. The data set is mainly used in glaciology, climatology, hydrology and other disciplines, especially in the quantitative analysis of the temporal and spatial changes of Antarctic surface mass balance, climate model validation, driving ice sheet model and snow granulation model, etc.
WANG Yetang
1) These data main included the GPR-surveyed ice thickness of six typical various-sized glaciers in 2016-2018; the GlabTop2-modeled ice thickness of the entire UIB sub-basins, discharge data of the hydrological stations, and related raw & derived data. 2) Data sources and processing methods: We compared the plots and profiles of GPR-surveyed ice bed elevation with the GlabTop2-simulated results and selected the optimal parametric scheme, then simulated the ice thickness of the whole UIB basin and assessed its hydrological effect. These processed results were stored as tables and tif format， 3) Data quality description: The simulated ice thickness has a spatial resolution of 30 m, and has been verified by the GPR-surveyed ice thickness for the MD values were less than 10 m. The maximum error of the GPR-measured data was 230.2 ± 5.4 m, within the quoted glacier error at ± 5%. 4) Synthesizing knowledge of the ice thickness and ice reserves provides critical information for water resources management and regional glacial scientific research, it is also essential for several other fields of glaciology, including hydrological effect, regional climate modeling, and assessment of glacier hazards.
ZHANG Yinsheng
This dataset includes annual mosaics of Antarctic ice velocity derived from Landsat 8 images between December, 2013 and April, 2019, which was updated in 2020 in order to produce multi-year annual ice velocity mosaics and improve the quality of products including non-local means (NLM) filter, and absolute calibration using rock outcrops data. The resulting Version 2 of the mosaics offer reduced local errors, improved spatial resolution as described in the README file.
SHEN Qiang SHEN Qiang
This dataset includes the Antarctica ice sheet mass balance estimated from satellite gravimetry data, April 2002 to December 2019. The satellite measured gravity data mainly come from the joint NASA/DLR mission, Gravity Recovery And Climate Exepriment (GRACE, April 2002 to June 2017), and its successor, GRACE-FO (June 2018 till present). Considering the ~1-year data gap between GRACE and GRACE-FO, we extra include gravity data estimated from GPS tracking data of ESA's Swarm 3-satellite constellation. The GRACE data used in this study are weighted mean of CSR, GFZ, JPL and OSU produced solutions. The post-processing includes: replacing GRACE degree-1, C20 and C30 spherical harmonic coefficients with SLR estimates, destriping filtering, 300-km Gaussian smoothing, GIA correction using ICE6-G_D (VM5a) model, leakage reduction using forward modeling method and ellipsoidal correction.
C.K. Shum
The data are collected from the automatic weather station (AWS, Campbell company) in the moraine area of the 24K glacier in the Southeast Tibet Plateau, Chinese Academy of Sciences. The geographic coordinates are 29.765 ° n, 95.712 ° E and 3950 m above sea level. The data include daily arithmetic mean data of air temperature (℃), relative humidity (%), wind speed (M / s), net radiation (w / m2), water vapor pressure (kPa) and air pressure (mbar). In the original data, an average value was recorded every 30 minutes before October 2018, and then an average value was recorded every 10 minutes. The temperature and humidity are measured by hmp155a temperature and humidity probe. The net radiation probe is nr01, the atmospheric pressure sensor probe is ptb210, and the wind speed sensor is 05103. These probes are 2 m above the ground. Data quality: the data has undergone strict quality control. The original abnormal data of 10 minutes and 30 minutes are removed first, and then the arithmetic mean of each hour is calculated. Finally, the daily value is calculated. If the number of hourly data is less than 24, the data is removed, and the corresponding date data in the data table is empty. In addition to the lack of some parameter data due to the thick snow and low temperature in winter and spring, the data can be used by scientific researchers who study climate, glacier and hydrology through strict quality control.
Luo Lun
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 ages of glacial traces of the last glacial maximum, Holocene and little ice age in the Westerlies and monsoon areas were determined by Cosmogenic Nuclide (10Be and 26Al) exposure dating method to determine the absolute age sequence of glacial advance and retreat. The distribution of glacial remains is investigated in the field, the location of moraine ridge is determined, and the geomorphic characteristics of moraine ridge are measured. According to the geomorphic location and weathering degree of glacial remains, the relationship between the new and the old is determined, and the moraine ridge of the last glacial maximum is preliminarily determined. The exposed age samples of glacial boulders on each row of moraine ridges were collected from the ridge upstream. This data includes the range of glacier advance and retreat in Karakoram area during climate transition period based on 10Be exposure age method.
XU Xiangke
Among many indicators reflecting climate and environmental change, the stable isotope index of ice core is an indispensable parameter in the study of ice core record, and is one of the most reliable and effective ways to recover the past climate change. Ice core accumulation is a direct record of precipitation on glaciers, and high resolution ice core records ensure the continuity of precipitation records. Therefore, ice core records provide an effective means to recover precipitation changes. The isotope and accumulation of ice cores drilled from the Qinghai Tibet Plateau can be used to reconstruct the changes of temperature and precipitation, which is a good record of climate and environment. This data set provides stable isotope records of hushe ice core in Karakoram area and provides data support for the study of climate change in Qinghai Tibet Plateau.
XU Baiqing,
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 involved three periods of geodetic glacier mass storage change of three Rongbuk glaciers and its debris-covered ice in the Rongbuk Catchment from 1974-2016 (unit: m w.e. a-1). It is stored in the ESRI vector polygon format. The data sets are composed of three periods of glacier surface elevation difference between 1974-2000，2000-2016 and 1974-2006, i.e. DHPRISM2006-DEM1974（DH2006-1974）、DHSRTM2000-DEM1974（DH2000-1974）、DHASTER2016-SRTM2000（DH2016-2000）. DH2006-1974 was surface elevation change between ALOS/PRISMDEM(PRISM2006) and DEM1974, i.e. the DEM1974 was subtracted from PRISM2006, DH2006-1974 =PRISM2006 – DEM1974. The PRISM2006 was generated from stereo pairs of ALOS/PRISM on 4 Dec. 2006. 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 DHPRISM2006-DEM1974 was ±0.24 m a-1. DHSRTM2000-DEM1974（DH2000-1974）was surface elevation change between SRTM DEM(SRTM2000) and DEM1974. The uncertainty in the ice free areas of DHSRTM2000-DEM1974 was ±0.13 m a-1. DHASTER2016-SRTM2000（DH2016-2000）was the surface elevation change between ASTER DEM2016 and SRTM DEM(SRTM2000). The uncertainty in the ice free areas of DHASTER2016-SRTM2000 was ±0.08 m a-1. Glacier-averaged annual mass balance change (m w.e.a-1) was averaged annually for each glacier, which was calculated by DH2006-1974/DH2000-1974/DH2016-2000, glacier coverage area and ice density of 850 ± 60 kg m−3. The attribute data includes Glacier area by Shape_Area (m2), EC2000-1974/EC2016-2000/EC2006-1974, i.e. Glacier-averaged surface elevation change in each period(m a-1), MB2000-1974/ MB2016-2000/MB2006-1974, i.e. Glacier-averaged annual mass balance in each period (m w.e.a-1), and MC2000-1974/ MC2016-2000/MC2006-1974,Glacier-averaged annual mass change in each period(m3 w.e.a-1), Uncerty_EC is the maximum uncertainty of glacier surface elevation change（m a-1）、Uncerty_MB, is the maximum uncertainty of glacier mass balance（m w.e. a-1），Uncerty_MC, is the maximum uncertainty of glacier mass change（m3w.e. a-1）。 MinUnty_EC，is the minimum uncertainty of glacier surface elevation change，MinUnty_MB，is the minimum uncertainty of glacier mass balance（m w.e. a-1），MinUnty_MC is the minimum uncertainty of glacier 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 involved geodetic glacier mass change of 71pieces of glaciers during 2000-2014 in the east of the Yigongzangbu, Southeast Tibetan Plateau. It is stored in the ESRI vector polygon format.Glacier-averaged mass balance (m w.e.a-1) was calculated by the surface elevation difference between 2000-2014 ( Dh2000-2014)、glacier coveraged vector data (CGI2/TPG1976/RGI6.0) and ice density of 850 ± 60 kg m−3. Dh2000-2014 is obtained from surface elevation change by D-InSAR technique from a pair of TSX / TDx SAR images on February 7, 2014 and SRTM DEM. CGI2/TPG1976/RGI6.0 were used to extract glacier boundary and GLIMS-ID. SRTM DEM is the reference DEM and datum DEM with spatial resolution 30m. The attribute data includes GLIMS-ID, Area,EC_m_a-1,,MB_m w.e.a-1, MC_m3 w.e.a-1, MC_Gt.a-1, Uncerty_EC, Uncerty_MB, UT_MCm3w.e. a-1. Respectively, EC_m_a-1,,is the glacier-averaged annual elevation change during 2000-2014(m a-1),MB_m w.e.a-1, is glacier-averaged annual mass balance during 2000-2014(m w.e.a-1), MC_m3 w.e.a-1, is glacier-averaged annual mass change during 2000-2014 (m3 w.e.a-1), MC_Gt.a-1,is glacier-averaged annual mass change during 2000-2014 (Gt.a-1)Uncerty_EC is the uncertainty of glacier surface elevation change（±m a-1）、Uncerty_MB ,is the uncertainty of glacier mass balance（±m w.e. a-1），UT_MCm3w.e. a-1, is the uncertainty of glacier mass change（±m3w.e. a-1）。The data sets could be used for glacier change, hydrological and climate change studies in the southeast of Tibetan Plateau.
YE Qinghua
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 set involved geodetic annual glacier-averagedmass balance and mass change data at the Ponkar area in Nepal on the Southern slope of the Himalayas from 1974 to 2014. 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 2000-2014 (DH2000-2014,by DinSAR techniques from SRTM DEM2000 and TSX/TDX data in 2014). 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, the glacier_area（m2）、Area（km2）, the glacier name, EC74_2000, the surface elevation change rate from 1974 to 2000(m a-1), EC00_2014, the surface elevation change rate from 2000 to 2014 (m a-1), MB74_2000, the geodetic glacier mass balance between 1974 and 2000（m w.e. a-1），MB00_2014, the geodetic glacier mass balance between 2000 and 2014（m w.e. a-1）.MC74_2000, the geodetic glacier mass change from 1974 to 2000 (m3w.e. a-1), MC00_2014, the geodetic glacier mass change from 2000 to 2014(m3w.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_14，is the uncertainty of glacier surface elevation change in 2000-2014（m a-1），Ut_MB00_14，is the uncertainty of glacier mass balance for each glacier in 2000-2014（m w.e. a-1），Ut_MC00_14 is the uncertainty of glacier mass change for each glacier in 2000-2014（m3 w.e. a-1）. This data set is used for the study glaciers melting and its hydrological effects in Ponkar area in Nepal in the Southern slope of the Himalayas. It also could be used in studies of climatic change and disasters research in the Himalayas.
YE Qinghua
Based on ICESat r633 altimetry data from February 2004 to October 2008, the elevation changes of Lambert Glacier / Amery ice shelf system in Antarctica are obtained by using the repeated orbit plane fitting method. The GIA correction and projection area deformation correction are carried out with ij05 R2 model, and then 30km * 30km is obtained The surface elevation change rate of resolution is converted into material change by the grain snow density model, and compared with the Antarctic material change obtained by grace gravity satellite time-varying model.
XIE Huan, LI Rongxing
In recent years, the Antarctic Ice Sheet experiences substantial surface melt, and a large amount of meltwater formed on the ice surface. Observing the spatial distribution and temporal evolution of surface meltwater is a crucial task for understanding mass balance across the Antarctic Ice Sheet. This dataset provides a 30 m surface meltwater coverage, extracted from Landsat images, in the typical ablation zone of the ice sheet (Alexandria Island, Antarctic Peninsula) from 2000 to 2019. The projection of this dataset is South Polar Stereographic. The formats of the dataset are vector (.shp) and raster (.tif).
YANG Kang
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
Based on GRACE Level-1b satellite gravity data, a time series of mass change over Greenland for the period 2002 to 2016, with a spatial resolution of 1 degree × 1 degree and a time resolution of one month was developed by the satellite gravity team led by Professor Shen Yunzhong from Tongji University. The reference time of this time series is the mean time span between January 2004 and December 2009. During data processing, ICE5G model was used to reduce the effect of GIA, and the contribution of GAD was added back by using AOD1B RL06 from GFZ
SHEN Yunzhong
This dataset contains the glacier outlines in Qilian Mountain Area in 2019. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2019 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 2018, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia, Li Jia, LI Jia, LI Jia, WANG Yingzheng, LI Jianjiang, LI Xin, LIU Shaomin
This data set includes 2002/04-2019/12 Greenland ice sheet mass changes derived from satellite gravimetry measurements. The satellite gravimetry data come from the joint NASA/DLR Gravity Recovery And Climate Experiment mission twin satellites (GRACE, 2002/04 to 2017/06) and its successor, GRACE Follow-On (GRACE-FO, 2018/06 to present). In order to fill the data gap between GRACE and GRACE-FO, we further utilize gravity field solutions derived from high-low GNSS tracking data of ESA's Swarm 3-satellite constellation whose primary scientific objective is geomagnetic surveying. The data set is provided in Matlab data format, the ice sheet mass changes are transformed to equivalent water height in meters, expressed on 0.25°x0.25° grid with monthly temporal resolution. This data set can be used to study the characteristics of Greenland ice sheet mass changes in recent two decades and their relation with the global climate change.
C.K. Shum
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
Snow is a significant component of the ecosystem and water resources in high-mountain Asia (HMA). Therefore, accurate, continuous, and long-term snow monitoring is indispensable for the water resources management and economic development. The present study improves the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites 8 d (“d” denotes “day”) composite snow cover Collection 6 (C6) products, named MOD10A2.006 (Terra) and MYD10A2.006 (Aqua), for HMA with a multistep approach. The primary purpose of this study was to reduce uncertainty in the Terra–Aqua MODIS snow cover products and generate a combined snow cover product. For reducing underestimation mainly caused by cloud cover, we used seasonal, temporal, and spatial filters. For reducing overestimation caused by MODIS sensors, we combined Terra and Aqua MODIS snow cover products, considering snow only if a pixel represents snow in both the products; otherwise it is classified as no snow, unlike some previous studies which consider snow if any of the Terra or Aqua product identifies snow. Our methodology generates a new product which removes a significant amount of uncertainty in Terra and Aqua MODIS 8 d composite C6 products comprising 46 % overestimation and 3.66 % underestimation, mainly caused by sensor limitations and cloud cover, respectively. The results were validated using Landsat 8 data, both for winter and summer at 20 well-distributed sites in the study area. Our validated adopted methodology improved accuracy by 10 % on average, compared to Landsat data. The final product covers the period from 2002 to 2018, comprising a combination of snow and glaciers created by merging Randolph Glacier Inventory version 6.0 (RGI 6.0) separated as debris-covered and debris-free with the final snow product MOYDGL06*. We have processed approximately 746 images of both Terra and Aqua MODIS snow containing approximately 100 000 satellite individual images. Furthermore, this product can serve as a valuable input dataset for hydrological and glaciological modelling to assess the melt contribution of snow-covered areas. The data, which can be used in various climatological and water-related studies, are available for end users at https://doi.org/10.1594/PANGAEA.901821 (Muhammad and Thapa, 2019).
SHER Muhammad
On the basis of RGI6.0, we use remote sensing and geographic information system technology to update the glacier inventory data in Alaska. The updated glacier inventory uses a data source for 2018 Landsat OLI spatial resolution 15m remote sensing image, and the method used is manual interpretation. The results show that the Alaska Glacier inventory includes 27043 glaciers with a total area of 81285km2. The uncertiany of this data is 4.3%. The data will provide important data support for the study of glacier change in Alaska and the regional and global impact of glacier change in the context of global change.
SHANGGUAN Donghui,
The data set integrated glacier inventory data and 426 Landsat TM/ETM+/OLI images, and adopted manual visual interpretation to extract glacial lake boundaries within a 10-km buffer from glacier terminals using ArcGIS and ENVI software, normalized difference water index maps, and Google Earth images. It was established that 26,089 and 28,953 glacial lakes in HMA, with sizes of 0.0054–5.83 km2, covered a combined area of 1692.74 ± 231.44 and 1955.94 ± 259.68 km2 in 1990 and 2018, respectively.The current glacial lake inventory provided fundamental data for water resource evaluation, assessment of glacial lake outburst floods, and glacier hydrology research in the mountain cryosphere region
WANG Xin, GUO Xiaoyu, YANG Chengde, LIU Qionghuan, WEI Junfeng, ZHANG Yong, LIU Shiyin, ZHANG Yanlin, JIANG Zongli, TANG Zhiguang
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
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
