Current Browsing: Cryosphere


Geodetic Glacier mass changes in Naimo'Nanyi area in 1974-2000 and 2000-2013 (V1.0)

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.

2022-04-18

The third polar area glacier surface elevation change data product v1.0

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.

2022-04-18

Glacier thickness data in the third polar region (2018-2021)

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.

2022-04-18

Meteorological data of typical glacier front, river water level data and observation data of typical lake area (2021)

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.

2022-04-18

AWS data from typical glacier (2019-2020)

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.

2022-04-18

Distribution data of permafrost in the source area of the Yellow River (2013-2015)

The distribution data of permafrost in the source area of the Yellow River is established based on the annual average ground temperature model of permafrost in the source area of the Yellow River. The annual average ground temperature of 0 ℃ is taken as the standard and boundary for dividing seasonal frozen soil and permafrost. Compared with the available permafrost maps of the source region of the Yellow River (1:3 million) and the permafrost background survey project of the Qinghai Tibet Plateau (1:1 million), the data set is based on the measured data of the Yellow River source area, which has higher consistency with the measured data, and the simulation accuracy of the permafrost distribution map is the highest. The data set can be used to verify the distribution of permafrost in the source area of the Yellow River, as well as to study the frozen soil environment.

2022-04-18

Glacier inventory of Qilian Mountain Area (2020)

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

2022-04-18

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

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

2022-04-18

Data from automatic weather station at the end of glacier in Qinghai-Tibet Plateau (2019-2020)

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.

2022-04-18

In-situ water quality parameters of the lakes on the Tibetan Plateau (2009-2020)

This dataset provides the in-situ lake water parameters of 124 closed lakes with a total lake area of 24,570 km2, occupying 53% of the total lake area of the TP.These in-situ water quality parameters include water temperature, salinity, pH,chlorophyll-a concentration, blue-green algae (BGA) concentration, turbidity, dissolved oxygen (DO), fluorescent dissolved organic matter (fDOM), and water clarity of Secchi Depth (SD).

2022-04-18