• 典型年三极土壤微生物后处理产品(2005,2006,2015)

    The three pole soil microbial post-treatment products in typical years collected the distribution and analysis results of soil samples from the north and south polar regions from 2005 to 2006 and the distribution and analysis results of soil samples from the Qinghai Tibet Plateau in 2015. Through sorting and summarizing, the post-processing data products of soil microorganisms in the three pole region are obtained. The data format is excel, which is convenient for users to view. Among them, the collection time of samples from the north and south polar regions was from December 13, 2005 to December 8, 2006, including 52 samples from three regions in the Arctic (Spitsbergen slijeringa, Spitsbergen vestpynten, and Alexandra fjord Highlands), and 171 samples from five regions in the Antarctic (Mitchell Peninsula, Casey station main power house, Robinson ridge, herring Island, browning Peninsula); The Qinghai Tibet Plateau was collected from July 1 to July 15, 2015, including meadow, grassland and desert ecosystems. There were 18 sampling points in total, and the number of samples at each sampling point was 3-5. The precipitation, air temperature and drought degree of the sampling point are estimated from the meteorological information for reference. The soil surface samples were collected and stored in liquid nitrogen, then transported back to the Sydney Laboratory for extraction by fastprep DNA kit. The extracted DNA samples were amplified with the 16S rRNA gene fragment using 27F (5'-gagttttgatcntggctca-3') and 519r (5'-gtnttacngcgckctg-3'). The amplified fragments were sequenced by 454 method, and the original data were analyzed by mothur software. The sequences with poor sequencing quality were first removed, and then the chimeric sequences were sequenced and removed. After that, the similarity between sequences is calculated. Sequences with a similarity of more than 97% are clustered into one OTU, and OTU representative sequences are defined. The OTU representative sequences were aligned with the Silva database, and were identified to belong to the first level when the reliability was greater than 80%.

    0 2022-08-20

  • 典型年三极冰雪微生物后处理产品(2010-2018)

    The microbial reprocessing products of polar ice and snow in typical years collected the analysis results of bacteria sampled from glaciers, Glacial Snow and ice in the polar regions and the Qinghai Tibet Plateau from 2010 to 2018. Through sorting, summarizing and summarizing, the post-processing data products of soil microorganisms in the three pole region are obtained, and the data format is excel, which is convenient for users to view. Among them, the prokaryotes of Glacial Snow and ice in the polar regions and Qinghai Tibet Plateau are the sequences of bacterial 16S ribosomal RNA gene collected by teacher Liu Yongqin's experimental group from NCBI database from 2010 to 2018. The collected sequences calculate the similarity between sequences by using dotour software. Sequences with a similarity of more than 97% are clustered into an OTU, and OTU representative sequences are defined. OTU representative sequences were compared with RDP database through "Classifier" software, and were identified to the first level when the reliability was greater than >80%; The glaciers on the Qinghai Tibet Plateau were collected from 2010 to 2018, including the bacterial 16S ribosomal RNA gene sequence of seven glaciers on the Qinghai Tibet Plateau (East Rongbu glacier on Mount Everest, Tianshan No. 1 glacier, Guliya glacier, Laohugou glacier, muzitang glacier, July 1st glacier and yuzhufeng glacier) isolated by teacher Liu Yongqin's experimental group, Malan glacier isolated by teacher Xiang Shurong and ruogangri glacier isolated by teacher Zhang Xinfang. Glacier samples were collected and brought back to the ecological Laboratory of the Institute of Qinghai Tibet Plateau Research in Beijing and the Lanzhou cryosphere National Laboratory. After coating the plate, it was cultured at different temperatures (4-25 ℃) for 20-90 days, and a single colony was picked for purification. The isolated bacteria extracted DNA, amplified 16S ribosomal RNA gene fragments with 27f/1492r primers, and sequenced with Sanger method. 16S ribosomal RNA gene sequence was compared with RDP database through "Classifier" software, and was identified to the first level when the reliability was greater than >80%.

    0 2022-09-01

  • 北极两大河流域历史水循环关键变量数据集(1998-2017)

    This product provides the data set of key variables of the water cycle of Arctic rivers (North America:Mackenzie, Eurasia:Lena) from 1998 to 2017, including 7 variables: precipitation, evapotranspiration, surface runoff, underground runoff, glacier runoff, snow water equivalent and three-layer soil humidity, which are numerically simulated by the land surface model vic-cas developed by the project team. The spatial resolution of the data set is 50km and the temporal resolution is month. This data set can be used to analyze the change of water balance in the Arctic River Basin under climate change, and can also be used to compare and verify remote sensing data products and the simulations of other models.

    0 2022-09-01

  • 北极两大河流域入海径流(各径流成分)数据集(1971-2018)

    The data set includes the observed and simulated runoff into the sea and the composition of each runoff component (total runoff, glacier runoff, snowmelt runoff, rainfall runoff) of two large rivers in the Arctic (North America: Mackenzie, Eurasia: Lena), with a time resolution of months. The data is a vic-cas model driven by the meteorological driving field data produced by the project team. The observed runoff and remote sensing snow data are used for correction. The Nash efficiency coefficient of runoff simulation is more than 0.85, and the model can also better simulate the spatial distribution and intra/inter annual changes of snow cover. The data can be used to analyze the runoff compositions and causes of long-term runoff change, and deepen the understanding of the runoff changes of Arctic rivers.

    0 2022-09-01

  • 北极主要大河流域10km未来水循环关键要素预估数据集(2018-2065)

    This product provides the monthly runoff, evapotranspiration and soil water of major Arctic river basins in 2018-2065 based on the land surface model Vic. The spatial accuracy is 10km. Major Arctic river basins include Lena, Yenisey, ob, Kolyma, Yukon and Mackenzie basins. According to the rcp2.6 (low emission intensity) and rcp8.5 (high emission intensity) scenario results provided by the ipsl-cm5a-lr model in cmip5 in the fifth assessment report of IPCC, the future climate scenario driving data applicable to the Arctic region of 0.1 ° is obtained through statistical downscaling. Using the calibrated land surface hydrological model Vic on a global scale, based on the future climate scenario driven data of 0.1 °, the monthly time series of runoff, soil water and evapotranspiration of the Arctic River Basin in the middle of this century under future climate change are estimated.

    0 2022-09-01

  • 过去500年南北半球环状模数据

    (1) Data content: the annual mean Northern Annular mode index and the Northern Annular mode index from 1500 to 2000; (2) Data source and processing method: this data is independently produced by the author. It is based on PAGES2k data set and reconstructed by machine learning model (random forest, extreme tree, Light GBM and catboost). (3) Data quality description: the data set has high consistency with multiple instrumental data during the observed period, and the reconstruction is better. The data can be used to study the change and mechanism of the main atmospheric circulation in the northern and southern hemispheres on multiple time scales (interannual, interdecadal and multidecadal).

    0 2022-08-30

  • 过去千年青藏高原和北极夏季地表气温时间序列

    We utilized 12 datasets covering the period 900–1999 CE, including two summer temperature gridded datasets from the Qinghai–Tibetan Plateau, two summer temperature series from the Arctic, a summer temperature gridded dataset from the Arctic, six global gridded annual temperature reconstruction datasets, and a last millennium reanalysis dataset with seasonal resolution. We used the optimal information extraction method to reconstruct the summer temperature anomalies in the Qinghai-Tibet Plateau and the Arctic over the past millennium (900–1999 CE) with annual resolution. The range of the Qinghai-Tibetan Plateau is 27°N–36°N, 77°E–106°E, and the range of the Arctic is 60°N–90°N. The reconstruction target is the summer (June–August) temperature anomalies (with respect to 1961–1990 CE period) in the instrumental CRUTEM4v dataset. The data can be used to study the mechanism of temperature variability in the Qinghai-Tibetan Plateau and Arctic over the past millennium.

    0 2022-08-30

  • 过去200年南极海冰范围重建序列

    (1) Data content: data set of Antarctic sea ice extent (Northernmost Latitude of Sea Ice Edge (NLSIE) [°N]) in the past 200 years; (2) Data source and processing method: the data is generated based on the statistical model using six annual resolution proxies (ice core MSA, accumulation rate, etc.); (3) Data quality description: annual resolution; Areas: Indian and western Pacific sector of the Southern Ocean (50 ° – 150 ° E, indwpac), Ross Sea (160 ° E – 140 ° W, RS), Amundsen Sea (90 ° – 140 ° W, as), Bellingshausen Sea (50 ° – 90 ° W, BS), Weddell Sea (50 ° W – 20 ° E, WS); (4) It can be used to study the interdecadal variability of Antarctic sea ice.

    0 2022-08-30

  • 青藏高原及其周边地区潜在冰湖分布

    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.

    0 2022-04-15

  • 青藏高原重点河湖研究区国产高分2-50m融合正射验证数据集(2015-2020)

    Data content: this data set is the historical archived satellite data of the domestic high score series (GF1 / 2 / 3 / 4) in the key river and lake research areas of the Qinghai Tibet Plateau from 2015 to 2020, which can cover the typical river and lake areas for effective monitoring. The time range of the data is from 2015 to 2020. Data source and processing method: the data are level 1 products. After equalizing radiation correction, the changes affecting the sensors are corrected by the equalizing functions of different detectors. Some data are based on the Landsat 8 images in the same period as the base map, and control points are selected for geometric correction of the images. Then, orthophoto correction is carried out based on DEM data, and band fusion processing is carried out for the corresponding data. Data quality description: the Gaofen series satellites are processed by the China Resources Satellite Application Center. There are raw data received by the satellite ground receiving station of the Chinese Academy of Sciences and processed products at all levels. Among them, level 1a (pre-processing level radiometric correction image product): image data processed by data analysis, uniform radiometric correction, noise removal, MTFC, CCD splicing, band registration, etc; And provide RPC files for satellite direct attitude orbit data production. Refer to the data website of China Resources Satellite Application Center for details. Data application achievements and prospects: the data are domestic high-resolution data with high resolution, which can be used to monitor the changes of the Qinghai Tibet Plateau as a water tower in Asia and the generated images, and test the accuracy of other data in the region

    0 2022-08-29