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
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
Glacial mass balance is one of the most important glaciological parameters to characterize the accumulation and ablation of glaciers. Glacier mass balance is the link between climate and glacier change, and it is the direct reflection of glacier to the regional climate. Climate change leads to the corresponding changes in the material budget of glaciers, which in turn can lead to changes in the movement characteristics and thermal conditions of glaciers, and then lead to changes in the location, area and ice storage of glaciers. The monitoring method is to set a fixed mark flower pole on the glacier surface and regularly monitor the distance between the glacier surface and the top of the flower pole to calculate the amount of ice and snow melting; In the accumulation area, the snow pits or boreholes are excavated regularly to measure the snow density, analyze the characteristics of snow granular snow additional ice layer, and calculate the snow accumulation; Then, the single point monitoring results are drawn on the large-scale glacier topographic map, and the instantaneous, seasonal (such as winter and summer) and annual mass balance components of the whole glacier are calculated according to the net equilibrium contour method or contour zoning method. The data set is the annual mass balance data of different representative glaciers in the Qinghai Tibet Plateau and Tianshan Mountains, in millimeter water equivalent.
WU Guangjian
Glacier is the supply water source of rivers in the western mountainous area, and it is one of the most basic elements for people to survive and develop industry, agriculture and animal husbandry in the western region. Glaciers are not only valuable fresh water resources, but also the source of serious natural disasters in mountainous areas, such as sudden ice lake outburst flood, glacier debris flow and ice avalanche. Glacier hydrological monitoring is the basis for studying the characteristics of glacier melt water, the replenishment of glacier melt water to rivers, the relationship between glacier surface ablation and runoff, the process of ice runoff and confluence, and the calculation and prediction of floods and debris flows induced by glacier and seasonal snow melt water. Glacial hydrology refers to the water and heat conditions of glacial covered basins (i.e. glacial action areas), that is, the water and heat exchange between glaciers and their surrounding environment, the physical process of water accumulation and flow on the surface, inside and bottom of glaciers, the water balance of glaciers, the replenishment of glacial melt water to rivers, and the impact of water bodies in cold regions on climate change. At present, hydrological monitoring stations are mainly established at the outlet of the river basin to carry out field monitoring《 Glacial water resources of China (1991), hydrology of cold regions of China (2000) and glacial Hydrology (2001) summarize the early studies on glacial hydrology. China has carried out glacier hydrological monitoring on more than 20 glaciers in Tianshan, Karakorum, West Kunlun, Qilian, Tanggula, Nianqing Tanggula, gangrigab, Hengduan and Himalayas. This data set is the monthly runoff data of representative glaciers.
YANG Wei, LI Zhongqin, WANG Ninglian, QIN Xiang
Near-surface air temperature variability and the reliability of temperature extrapolation within glacierized regions are important issues for hydrological and glaciological studies that remain elusive because of the scarcity of high-elevation observations. Based on air temperature data in 2019 collected from 12 automatic weather stations, 43 temperature loggers and 6 national meteorological stations in six different catchments, this study presents air temperature variability in different glacierized/nonglacierized regions and assesses the robustness of different temperature extrapolations to reduce errors in melt estimation. The results show high spatial variability in temperature lapse rates (LRs) in different climatic contexts, with the steepest LRs located on the cold-dry northwestern Tibetan Plateau and the lowest LRs located on the warm-humid monsoonal-influenced southeastern Tibetan Plateau. Near-surface air temperatures in high-elevation glacierized regions of the western and central Tibetan Plateau are less influenced by katabatic winds and thus can be linearly extrapolated from off-glacier records. In contrast, the local katabatic winds prevailing on the temperate glaciers of the southeastern Tibetan Plateau exert pronounced cooling effects on the ambient air temperature, and thus, on-glacier air temperatures are significantly lower than that in elevation-equivalent nonglacierized regions. Consequently, linear temperature extrapolation from low-elevation nonglacierized stations may lead to as much as 40% overestimation of positive degree days, particularly with respect to large glaciers with a long flowline distances and significant cooling effects. These findings provide noteworthy evidence that the different LRs and relevant cooling effects on high-elevation glaciers under distinct climatic regimes should be carefully accounted for when estimating glacier melting on the Tibetan Plateau.
YANG Wei
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.
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 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
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 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
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
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
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
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
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
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.
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 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
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 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
1 High resolution gridded West Antarctic surface mass balance dataset, its project is Polar Stereographic Projection 2. The kriging like interpolation method is used to reconstruct the high‐spatial resolution surface mass balance (SMB) over the West Antarctic Ice Sheet (WAIS) from 1800 to 2010, based on ice core records, the outputs of the European Centre for Medium‐Range Weather Forecasts “Interim” reanalysis (ERA‐Interim) as well as the latest polar version of the Regional Atmospheric Climate Model (RACMO2.3p2). 3. Its accuracy is higher than reanalysis data. 4. Temporal resolution: 1800-2010; Temporal resolution: 1 year; Spatial coverage : the whole West Antarctic Ice Sheet, Spatial resolution: 25km х 25km
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
The data of triode ice core mainly comes from NOAA (National Oceanic and Atmospheric Administration, https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/ice-core). The original data is mainly in text format, which is provided by relevant units and researchers voluntarily. The data mainly includes the original observation data such as oxygen isotope, greenhouse gas concentration, ice core age, etc., as well as the historical temperature, carbon dioxide concentration and methane concentration produced by the researchers according to the observation data. The data are mainly divided into Antarctic, Arctic, Greenland and the third polar region. The database includes drilling address, time, derivative products, corresponding observation site data, references and other elements. Derivative products include product name, type, time and other elements. The space location is divided into the south pole, the north pole and the third pole, including Alaska, Canada, Russia, Greenland and other regions. After sorting and post-processing the collected data, the ice core database is established by using the access database management system of Microsoft office. According to the Antarctic, Arctic, Greenland and the third pole, it is divided into four sub databases. The first table in each database is readme, which contains information and references of each data table.
YE Aizhong
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). 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).
WANG Lei
This project is based on the data of bioactive elements such as Fe in miaergou ice core (94 ° 19 ′ e, 43 ° 03 ′ n, 4518 m) of the East Tianshan Mountains, and rebuilt the metal element history of 1956-2004. Data content: 1956-2004 ice core metal elements (including Fe, CD, Pb, as, Ba, Al, s, Mn, CO and Ni); data source, through ICP-MS test; data quality: blank sample is significantly lower than sample value, with better quality; data application results and prospects: data has been published, see Du, Z., Xiao, C., Zhang, W., Handley, M. J., mayewski, P. A., Liu, Y., & Li, X. (20. 19). Iron record associated with sandstorms in a central Asian shallow ice core spanning 1956-2004. Atmospheric environment, 203, 121-130. It can provide comparative study of other ice cores in Central Asia.
Du Zhiheng
Glaciers are very sensitive to regional and global climate change, so they are often regarded as one of the indicators of climate change, and their relevant parameters are also the key indicators of climate change research. Especially in the comparative study of the three polar environmental changes on the earth, the time and space difference ratio of glacial speed is one of the focuses of climate change research. However, because glaciers are basically located in high altitude, high latitude and high cold areas, the natural environment is poor, and people are rarely seen, and it is difficult to carry out the conventional field measurement of large-scale glacial movement. In order to understand the glacial movement in the three polar areas in a timely, efficient, comprehensive and accurate manner, radar interferometry, radar and optical image pixel tracking are used to obtain the three polar areas. The distribution of surface movement of some typical glaciers in some years from 2000 to 2017 provides basic data for the comparative analysis of the movement of the three polar glaciers. The dataset contains 12 grid files named "glacier movement in a certain period of time in a certain region". Each grid map mainly contains the regional velocity distribution of a typical glacier.
Yan Shiyong
This product is based on multi-source remote sensing DEM data generation. The steps are as follows: select control points in relatively stable and flat terrain area with Landsat ETM +, SRTM and ICESat remote sensing data as reference. The horizontal coordinates of the control points are obtained with Landsat ETM + l1t panchromatic image as the horizontal reference. The height coordinates of the control points are mainly obtained by ICESat gla14 elevation data, and are supplemented by SRTM elevation data in areas without ICESat distribution. Using the selected control points and automatically generated connection points, the lens distortion and residual deformation are compensated by Brown's physical model, so that the total RMSE of all stereo image pairs in the aerial triangulation results is less than 1 pixel. In order to edit the extracted DEM data to eliminate the obvious elevation abnormal value, DEM Interpolation, DEM filtering and DEM smoothing are used to edit the DEM on the glacier, and kh-9 DEM data in the West Kunlun West and West Kunlun east regions are spliced to form products.
ZHOU Jianming
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