The data involved two periods of geodetic glacier mass storage change of Naimona’Nyi glaciers in the western of Himalaya from 1974-2013 (unit: m w.e. a-1). It is stored in the ESRI vector polygon format. The data sets are composed of two periods of glacier surface elevation difference between 1974-2000 and 2000-2013, i.e. DHSRTM2000-DEM1974（DH2000-1974）、DHTanDEM2013-SRTM2000（DH2013-2000）. DH2000-1974 was surface elevation change between SRTM2000 and DEM1974, i.e. the earlier historical DEM (DEM1974, spatial resolution 25m) was derived from 1:50,000 topographic maps in October 1974(DEM1974,spatial resolution 25m). The uncertainty in the ice free areas of DH2000-1974 was ±0.13 m a-1. The surface elevation difference between 2000-2013 (DH2000-2013, by DinSAR techniques from SRTM DEM2000 and TSX/TDX data on Oct.17th in 2013) The uncertainty in the ice free areas of DH2013-2000 was ±0.04 m a-1. Glacier-averaged annual mass balance change (m w.e.a-1) was averaged annually for each glacier, which was calculated by DH2000-1974/DH2013-2000, glacier coverage area and ice density of 850 ± 60 kg m−3. The attribute data includes Glacier area by Shape_Area (m2), EC74_00, EC00_13, i.e. Glacier-averaged surface elevation change in 1974-2000 and 2000-2013(m a-1), MB74_00, MB00_13 i.e. Glacier-averaged annual mass balance in 1974-2000 and 2000-2013 (m w.e.a-1), and MC74_00, MC00_13, Glacier-averaged annual mass change in 1974-2000 and 2000-2013 (m3 w.e.a-1), Uncerty_MB, is the uncertainty of glacier-averaged annual mass balance（m w.e. a-1）， Uncerty_MC, is the Maximum uncertainty of glacier-averaged annual mass change（m3 w.e. a-1）. The data sets could be used for glacier change, hydrological and climate change studies in the Himalayas and High Mountain Asia.
YE Qinghua
The recent glacial changes in the third polar region have become the focus of the governments of the surrounding countries because of their important significance to the downstream water supply. Based on SRTM acquired in 2000 and aster stereo image pairs before and after 2015, more than 40 Typical Glaciers in the third polar region were selected to estimate the glacial surface elevation in corresponding period. This product estimates the surface elevation changes of more than 14000 glaciers in the third polar region in 2000-2015s, and the investigated area accounts for about 25% of the total glaciers in the third polar region. The data covers the whole third pole area except Altai mountain, with a spatial resolution of 30m.
CHEN An‘an
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
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
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
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
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
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 set includes the temperature, precipitation, relative humidity, wind speed, wind direction and other daily values in the observation point of Kunsha Glacier. The data is observed from October 3, 2015 to September 19, 2017. It is measured by automatic meteorological station (Onset Company) and a piece of data is recorded every 2 hours. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.
ZHANG Yinsheng
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
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
1) Dataset: The dataset includes mass balance data during 2010-2015 on the Laohuogou Glacier No. 12. 2) Sourc and methods: the mass balances were measured at each 100 m elevation belt, and every elevation had installed three plastic stick to measure mass balance. The mass balance of entire glacier was mesrued in May and September, the glacier-wide mass balance was calculated following met Area-Average method. 3) Data quality dsecription: data were manually measured following glaciology method, with a good quality.
LIU Yushuo
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
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
This is the 1976, 1991, 2000, and 2010 vector data set of glaciers and glacial lakes in the Boqu Basin in Central Himalaya based on Landsat satellite images. The data source is from Landsat remote images. 1976: LM21510411975306AAA05, LM21510401976355AAA04 1991: LT41410401991334XXX02, LT41410411991334XXX02 2000: LE71410402000279SGS00, LE71400412000304SGS00, LE71410402000327EDC00, LE71410412000327EDC00 2010: LT51400412009288KHC00, LT51410402009295KHC00, LT51410412009311KHC00, LT51410402011237KHC00. The boundaries of glaciers and glacial lakes are extracted manually from the various remote sensing images. The extraction error of the boundaries of glaciers and glacial lakes is estimated to be 0.5 pixels. Data file: Glacial_1976: Glacier vector data in 1976 Glacial_1991: Glacier vector data in 1991 Glacial_2000: Glacier vector data in 2000 Glacial_2010: Glacier vector data in 2010 Glacial_Lake_1976: Glacial lake vector data in 1976年 Glacial_Lake_1991: Glacial lake vector data in 1991 Glacial_Lake_2000: Glacial lake vector data in 2000 Glacial_Lake_2010: Glacial lake vector data in 2010 The glacial lake vector data fields include Number, name, latitude and longitude, altitude, area, orientation, type of glacial lake, length, width, and distance from the glacier.
WANG Weicai
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 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
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
The data set of ice core-snow black carbon content on the Tibetan plateau (1950-2006) contains five (5) tables: 1 Xu et al. 2006 AG, 2 Xu et al. 2009 PNAS_Conc., 3 Xu et al. 2009 PNAS_flux, 4 Xu et al. 2012 ERL, 5 Wang et al. 2015 ACP. The data collection sites include the Meikuang glacier, Dongkemadi, Qiangyong, Kangwure, Naimona’nyi, Muztagata, Rongbuk, Tanggula Mountain, Ningjin Gangsang, Zuoqipu, and Glacier No. 1 at the headwaters of the Ürüqi River. The latitudes and longitudes of the collection locations, elevations and other information are marked in the data. The main indicators of the data are location, time, organic carbon (OC), elemental carbon (EC), black carbon (BC) content and flux. Location: latitude and longitude Time: year or date OC: organic carbon EC: elemental carbon BC: Black carbon Conc.: content, unit: ng g-1 Flux: flux, unit: mg m-2a-1 The data come from the following subjects. 1. National Program on Key Basic Research Project (973 Program)：Temporal and Spatial Characteristics and Remote Sensing Modeling of Global Change Sensitive Factors; Person in charge: Baiqing Xu; Unit: Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Supported by the Ministry of Science and Technology. 2. National Key Basic Research Program: The Response of Formation and Evolution on the Tibetan Plateau to Global Changes and Adaptation Strategy; Person in charge: Tandong Yao; Unit: Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Supported by the Ministry of Science and Technology. 3. The General Program of National Natural Science Foundation of China: High-resolution Carbon Black Recording in Snow Ice of the Tibetan Plateau; Person in charge: Baiqing Xu; Unit: Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Supported by the National Natural Science Foundation of China (NSFC). 4. The General Program of the National Natural Science Foundation of China: Extraction of Climate and Environment Information from Ice Core Encapsulated Gas on the Tibetan Plateau; Person in charge: Baiqing Xu; Unit: Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Supported by the National Natural Science Foundation of China (NSFC). 5. National Natural Science Foundation of China for Distinguished Young Scholars: Snow and Ice-Atmospheric Chemistry and Environmental Changes on the Tibetan Plateau; Person in charge: Baiqing Xu; Unit: Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Supported by the National Natural Science Foundation of China (NSFC). 6. National Natural Science Foundation of China for Distinguished Young Scholars: Study on the Changes of Aerosol Emissions and Combustion in Human Activities in South Asia in the Past 100 Years; Person in charge: Mo Wang; Unit: Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Supported by the National Natural Science Foundation of China (NSFC). Observation methods: two-step heating method, thermal/optical carbon analysis method, and single-particle black carbon aerosol photometer.
XU Baiqing
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
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
