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.
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.
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).
Freezing (thawing) index refers to the sum of all temperatures less than (greater than) 0 ℃ in a year. Surface freezing (thawing) index is an important parameter to measure the time and capacity of surface freezing (thawing), which can reflect the characteristics of regional freezing and thawing environment. Based on the modis-lst data product, which comes from the national Qinghai Tibet Plateau science data center, the data in the Sanjiang River Basin are read by MATLAB language, and combined with the calculation of freezing (thawing index) formula, the spatial distribution data set of surface freezing and thawing index of dynamic environmental factors outside the Sanjiang River basin (average from 2003 to 2015) is obtained. This data set can better reflect the ability of surface freezing and thawing in the Sanjiang River Basin, so as to reflect the characteristics of regional freezing and thawing environment, It provides important external dynamic environmental factors for the development of freeze-thaw landslide.
The Antarctic ice sheet elevation data were generated from radar altimeter data (Envisat RA-2) and lidar data (ICESat/GLAS). To improve the accuracy of the ICESat/GLAS data, five different quality control indicators were used to process the GLAS data, filtering out 8.36% unqualified data. These five quality control indicators were used to eliminate satellite location error, atmospheric forward scattering, saturation and cloud effects. At the same time, dry and wet tropospheric, correction, solid tide and extreme tide corrections were performed on the Envisat RA-2 data. For the two different elevation data, an elevation relative correction method based on the geometric intersection of Envisat RA-2 and GLAS data spot footprints was proposed, which was used to analyze the point pairs of GLAS footprints and Envisat RA-2 data center points, establish the correlation between the height difference of these intersection points (GLAS-RA-2) and the roughness of the terrain relief, and perform the relative correction of the Envisat RA-2 data to the point pairs with stable correlation. By analyzing the altimetry density in different areas of the Antarctic ice sheet, the final DEM resolution was determined to be 1000 meters. Considering the differences between the Prydz Bay and the inland regions of the Antarctic, the Antarctic ice sheet was divided into 16 sections. The best interpolation model and parameters were determined by semivariogram analysis, and the Antarctic ice sheet elevation data with a resolution of 1000 meters were generated by the Kriging interpolation method. The new Antarctic DEM was verified by two kinds of airborne lidar data and GPS data measured by multiple Antarctic expeditions of China. The results showed that the differences between the new DEM and the measured data ranged from 3.21 to 27.84 meters, and the error distribution was closely related to the slope.
The DEMs of the typical glaciers on the Tibetan Plateau were provided by the bistatic InSAR method. The data were collected on November 21, 2013. It covered Puruogangri and west Qilian Mountains with a spatial resolution of 10 meters, and an elevation accuracy of 0.8 m which met the requirements of national 1:10 000 topographic mapping. Considering the characteristics of the bistatic InSAR in terms of imaging geometry and phase unwrapping, based on the TanDEM-X bistatic InSAR data, and adopting the improved SAR interference processing method, the surface DEMs of the two typical glaciers above were generated with high resolution and precision. The data set was in GeoTIFF format, and each typical glacial DEM was stored in a folder. For details of the data, please refer to the Surface DEMs for typical glaciers on the Tibetan Plateau - Data Description.
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.
This data includes the soil microbial composition data in permafrost of different ages in Barrow area of the Arctic. It can be used to explore the response of soil microorganisms to the thawing in permafrost of different ages. This data is generated by high through-put sequencing using the earth microbiome project primers are 515f – 806r. The region amplified is the V4 hypervariable region, and the sequencing platform is Illumina hiseq PE250; This data is used in the articles published in cryosphere, Permafrost thawing exhibits a greater influence on bacterial richness and community structure than permafrost age in Arctic permafrost soils. The Cryosphere, 2020, 14, 3907–3916, https://doi.org/10.5194/tc-14-3907-2020https://doi.org/10.5194/tc-14-3907-2020 . This data can also be used for the comparative analysis of soil microorganisms across the three poles.
First of all, the data of ice cover elevation change is obtained by using the data of glas12 in 2004 and 2008. In ideal case, each track is strictly repeated. However, due to the track deviation, it can not be guaranteed that the track is strictly repeated according to the design. The deviation varies from several meters to several hundred meters. The grid of 500m * 500m is taken, and the point falling in the same grid is considered as the weight of the repeated track. The elevation change in 2004-2008 is obtained by subtraction of complex points, and the annual elevation change is obtained. Ice sheet elevation change data
The medium-resolution MODIS river and lake ice phenology data set in the high latitudes of the northern hemisphere from 2002 to 2019 is based on the Normalized Difference Snow Index (NDSI) data of the Moderate Resolution Imaging Spectroradiometer(MODIS). Daily lake iceextent and coverage under clear-sky conditions was examined byemploying the conventional SNOWMAP algorithm, and thoseunder cloud cover conditions were re-determined using the temporal and spatial continuity of lake surface conditions througha series of steps.The lake ice phenology information obtained in this dataset was highly consistent with that from passive microwave data at an average correlation coefficient of 0.91 and an RMSE value varying from 0.07 to 0.13.
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LinksNational Tibetan Plateau Data Center
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