Pan-third-polar environmental change and green silk road construction

Brief Introduction: Pan-third-polar environmental change and green silk road construction

Number of Datasets: 625

  • Dataset of high-resolution (3 hour, 10 km) global surface solar radiation (1983-2017)

    Dataset of high-resolution (3 hour, 10 km) global surface solar radiation (1983-2017)

    The dataset is a 34-year (1983.7-2017.6) high-resolution (3 h, 10 km) global SSR (surface solar radiation) dataset, which can be used for hydrological modeling, land surface modeling and engineering application. The dataset was produced based on ISCCP-HXG cloud products, ERA5 reanalysis data, and MODIS aerosol and albedo products with an improved physical parameterization scheme. Validation and comparisons with other global satellite radiation products indicate that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). This SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future.

    2020-01-10 3999 223 View Details

  • Long-term surface soil freeze-thaw states dataset of China using the dual-index algorithm (1978-2015)

    Long-term surface soil freeze-thaw states dataset of China using the dual-index algorithm (1978-2015)

    This dataset uses daily temperature data from SMMR (1978-1987), SSM/I (1987-2009) and SSMIS (2009-2015). It is generated by the dual-index (TB, 37v, SG) freeze-thaw discrimination algorithm. The classification results include the frozen surface, the thawed surface, the deserts and water bodies. The data coverage is the main part of China’s mainland, with a spatial resolution of 25.067525 km via the EASE-Grid projection method, and it is stored in ASCIIGRID format. All the ASCII files in this data set can be opened directly with a text program such as Notepad. Except for the head file, the body content is numerically characterized by the freeze/thaw status of the surface soil: 1 for frozen, 2 for thawed, 3 for desert, and 4 for precipitation. If you want to use the icon for display, we recommend using the ArcView + 3D or Spatial Analyst extension module for reading; in the process of reading, a grid format file will be generated, and the displayed grid file is the graphical expression of the ASCII file. The read method comprises the following. [1] Add the 3D or Spatial Analyst extension module to the ArcView software and then create a new View. [2] Activate View, click File menu, and select the Import Data Source option. When the Import Data Source selection box pops up, select ASCII Raster in the Select import file type box. When the dialog box for selecting the source ASCII file automatically pops up, click to find any ASCII file in the data set, and then press OK. [3] Type the name of the Grid file in the Output Grid dialog box (it is recommended that a meaningful file name is used for later viewing) and click the path to store the Grid file, press OK again, and then press Yes (to select integer data) and Yes (to put the generated grid file into the current view). The generated files can be edited according to the Grid file standard. This completes the process of displaying an ASCII file into a Grid file. [4] In the batch processing, the ASCIGRID command of ARCINFO can be used to write AML files, and then use the Run command to complete the process in the Grid module: Usage: ASCIIGRID <in_ascii_file> <out_grid> {INT | FLOAT}. The production of this data is supported by the following Natural Science Foundation Projects: Environmental and Ecological Science Data Center of West China (90502010), Land Data Assimilation System of West China (90202014) and Active and Passive Microwave Radiation Transmission Simulation and Radiation Scattering Characteristics of the Frozen Soil (41071226).

    2020-01-09 6614 99 View Details

  • Geomorphological map of Nima and Lunpola Basins in Tibetan Plateau

    Geomorphological map of Nima and Lunpola Basins in Tibetan Plateau

    This data set comprises pictures of geological sections and landscape of Nima Basin and Lunpola Basin in the north of Tibetan Plateau which produced on achievement of geological survey in these years. The process of section pictures drawing comprises: measurement of different stratas by hand; identify and description of stratas by experienced geological researcher; picture production with software, based on information collected above. Landscape pictures were drew from satellite maps as base map, then added texts with software. All the pictures are clear, detailed and comprehensive. They are very critical for research on geology, geomorphology of the important localities in the north of Tibetan Plateau, such as Nima Basin and Lunpola Basin, and necessary for paleo-altimetry and uplift of Tibetan Plateau.

    2019-12-18 201 0 View Details

  • Water resources data of the Qinghai Tibet Plateau (1990-2010)

    Water resources data of the Qinghai Tibet Plateau (1990-2010)

    This data set is the water resources data of the Qinghai Tibet Plateau from 1990 to 2010, which is the sum of renewable surface and groundwater resources. The data is in vector format and the spatial resolution is in the scale of prefecture level administrative units. The data is obtained by checking the results of VIC (variable injection capacity) hydrological model. The simulated water resources are the sum of the surface runoff and underground runoff in the output results of hydrological simulation. The simulation results are verified by comparing with the runoff data of the measured stations. According to the statistics of water resources at the provincial level in China water resources bulletin, a correction coefficient α is introduced at the provincial level, so that the product of water resources and α in the hydrological model simulation province is equal to the statistics of water resources. Then the amount of water resources in the administrative unit is the product of the total amount of water resources and α.

    2019-12-06 223 7 View Details

  • Monthly dataset of ERA-Interim based on pressure levels from 1979 to 2018 released from ECMWF

    Monthly dataset of ERA-Interim based on pressure levels from 1979 to 2018 released from ECMWF

    This dataset is derived from the global atmospheric reanalysis dataset, ERA-Interim, based on the 4-dimensional variational analysis (4D-Var) released by the European Centre for Medium-Range Weather Forecasts (ECMWF). ERA-Interim represents a major undertaking by ECMWF (European Centre for Medium-Range Weather Forecasts) to produce a reanalysis with an improved atmospheric model and assimilation system which replaces those used in ERA-40, particularly for the data-rich 1990s and 2000s, and to be continued as an ECMWF Climate Data Assimilation System (ECDAS) until superseded by a new reanalysis. Through systematic increases in computing power, 4-dimensional variational assimilation (4D-Var) became feasible and part of ECMWF operations since 1997. Enhanced computing power also allowed horizontal resolution to be increased from T159 to T255, and the latest Integrated Forecasting System(IFS CY31r1 and CY31r2) to be used, taking advantage of improved model physics. ERA-interim retains the same 60 model levels used for ERA-40 with the highest level being 0.1 hPa. Besides, data assimilation of ERA-Interim also benefits from quality control that draws on experience from ERA-40 and JRA-25, variational bias correction of satellite radiance data, and more extensive use of radiances with an improved fast radiative transfer model. In addition, ERA-Interim uses the new ERS (European Remote Sensing Satellite) altimeter wave heights, EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) reprocessed winds and clear-sky radiances, GOME (Global Ozone Monitoring Experiment) ozone data from the Rutherford Appleton Laboratory, and CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), and COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) GPS radio occultation measurements processed and archived by UCAR (University Corporation for Atmospheric Research).

    2019-12-05 80 0 View Details

  • Palaeogeographic distribution of Early, Middle and Late Triassic lithofacies in Pan-Third Pole area

    Palaeogeographic distribution of Early, Middle and Late Triassic lithofacies in Pan-Third Pole area

    Guided by plate tectonics, palaeogeography, petroleum basin analysis and sedimentary basin dynamics , a large number of data and achievements in recent years of geological and petroleum geology research in Pan-Third Pole have been collected, including basic materials such as strata, sediments, palaeontology, palaeogeography, palaeoenvironments, palaeoclimate, structure, petroleum (sylvine) geology, especially Palaeomagnetism and palaeozoic. On the basis of material, detrital zircon and geochemical data, and combined with the results of typical measured stratigraphic profiles, the lithofacies and climatic palaeogeographic pattern of the Triassic period were restored and reconstructed, and the Palaeogeographic distribution of Early, Middle and Late Triassic lithofacies in Pan-Third Pole area as well as the paleoclimatic distribution maps were obtained, aiming at discussing the control and influence of palaeogeography, palaeostructure and Palaeoclimate on hydrocarbon (potassium-bearing) resources In order to reveal the geological conditions of oil and gas formation and the law of resource distribution, and provide scientific basis and technical support for overseas and domestic oil and gas exploration and deployment in China.

    2019-12-03 142 1 View Details

  • The desertification risk map in Central-Western Asia (2015)

    The desertification risk map in Central-Western Asia (2015)

    The gridded desertification risk data in Central-Western Asia was calculated based on the environmentally sensitive area index (ESAI) methodology. The ESAI approach incorporates soil, vegetation, climate and management quality and is one of the most widely used approaches for monitoring desertification risk. Based on the ESAI framework, fourteen indicators were chosen to consider four quality domains. Each quality index was calculated from several indicator parameters. The value of each parameter was categorized into several classes, the thresholds of which were determined according to previous studies. Then, sensitivity scores between 1 (lowest sensitivity) and 2 (highest sensitivity) were assigned to each class based on the importance of the class’ role in land sensitivity to desertification and the relationships of each class to the onset of the desertification process or irreversible degradation. A more comprehensive description of how the indicators are related to desertification risk and scores is provided in the studies of Kosmas (Kosmas et al., 2013; Kosmas et al., 1999). The main indicator datasets were acquired from the Harmonized World Soil Database of the Food and Agriculture Organization, Climate Change Initiative (CCI) land cover of the European Space Agency and NOAA’s Advanced Very High Resolution Radiometer (AVHRR) data. The raster datasets of all parameters were resampled to 1km and temporally assembled to the yearly values. Despite the difficulty of validating a composite index, two indirect validations of desertification risk were conducted according to the spatial and temporal comparison of ESAI values, including a quantitative analysis of the relationship between the ESAI and land use change between sparse vegetation and grasslands and a quantitative analysis of the relationship between the ESAI and net primary production (NPP). The verification results indicated that the desertification risk data is reliable in Central-Western Asia.

    2019-11-30 135 3 View Details

  • Stable Isotope Dataset of the Sediment Core Retrieved from Lop Nor in the Tarim Basin/Dataset of field investigation and field photos  of the Tibetan Plateau

    Stable Isotope Dataset of the Sediment Core Retrieved from Lop Nor in the Tarim Basin/Dataset of field investigation and field photos of the Tibetan Plateau

    This dataset includes stable carbon and oxygen isotopes of carbonates in a 180 m-long sediment core retrieved from Lop Nor, Tarim Basin. Sedimentary carbon and oxygen isotopes from carbonates are two of the most commonly used proxies in paleoclimatic studies, as they have the potential to record past variations in hydrology and vegetation. The sediment samples were grounded and sieved through a 100 mesh screen, and then directly analyzed using an isotope ratio mass spectrometer (MAT-252) with an automated carbonate preparation device (Kiel Ⅱ). Typical analytical errors are within ±0.06‰ and ±0.08‰ for carbon isotope and oxygen isotope, respectively. Based on the high-resolution stable carbon and oxygen isotope data of core Lop Nor, the evolution history of arid environment in the Taklimakan Desert since the Pleistocene can be reconstructed, allowing further exploring of trends, variability and mechanisms of regional climate change. Field photos dataset of the Tibetan Plateau include photos of the stratigraphic profiles.

    2019-11-29 110 0 View Details

  • MODIS 250-meter forest coverage data over Pan-third 18 key nodes (2000-2016)

    MODIS 250-meter forest coverage data over Pan-third 18 key nodes (2000-2016)

    MODIS 250-meter forest coverage is a key parameter that accurately reflects the overall coverage of forests. Forests serve as special “transformation” roles in lithosphere, biosphere, soil circles and the atmosphere, to assess the global carbon balance of ecosystems and Regional contributions and responses provide the foundation.Currently, MODIS satellite data products are an important source of data for inversion of forest cover.With 18 key nodes as the research area, based on the MOD44B data from 2000 to 2016, the forest coverage data of different regions were tailored and estimated, and the MODIS 250-meter forest coverage data of key nodes in 2000-2016 was obtained.

    2019-11-28 192 1 View Details

  • NDVI 16-Day 250m dataset in Xinjiang provice (2000-2017)

    NDVI 16-Day 250m dataset in Xinjiang provice (2000-2017)

    1. Data source: MODIS/Terra Vegetation Indices 16-day L3 Global 250m SIN Grid V006 products (2000-2017) Download address https://search.earthdata.nasa.gov/ 2. Data name: (1) resize is automatically generated in the batch cropping process, which means that it has been extracted by mask and the data range after processing is xinjiang provice; (2) seven digits represent the time of data acquisition, the first four digits are years, and the last three digits are days of the year.For example, "2000049" means that the year of data acquisition is 2000 and the specific time is the 49th day of that year. (3) 250m represents the ground resolution, i.e. 250 meters; (4) 16_days represents the time resolution, that is, 16 days; (5) NDVI represents data type, namely normalized vegetation index; 3. Data time range: 2000049-2017353, data interval of 16 days; 4..Tif file and.hdr file . Tif file is the original NDVI data with the same name. HDR file is the mask data that supports normal use of. 5. To analyze the ecological effects of cryosphere

    2019-11-28 209 2 View Details

  • Lithology description of a 400 m-thick Paleocene strata borehole in the Xiaojinggu area, Yunnan

    Lithology description of a 400 m-thick Paleocene strata borehole in the Xiaojinggu area, Yunnan

    The most complete Early Cenozoic strata in the Simao Basin are located in Xiaojinggu Town, Jinggu County, which mainly includes the sedimentary strata of the Mengyejing Formation, the Denghei Formation and the Mengla Formation. Due to the tectonic uplifting of the mountain in the late Cenozoic, the syncline structure caused the top of the Mengyejing Formation, the Denghei Formation and the Mengla Formation to be exposed to the surface. However, a complete sedimentary profile containing the middle and lower part of the Mengyejing Formation could not be obtained due to vegetation cover and village construction. The chronological study of sedimentary strata in the Simao Basin is mainly concentrated in the Mengyejing Formation with potassium salt. However, there still has significant controversy about the deposition time of this group at this stage. Recently, a continuous and complete high-resolution sequence (361.86 m in thickness) of the Mengyejing Formation was obtained through the continuous drilling. Among them, the Mengyejing Formation (0-353.3 m) is mainly a set of purple-red muddy silt and mudstone combination, while the underlying Mangang Formation (353.3-361.86 m) is a set of gray-white sandstone.

    2019-11-25 227 0 View Details

  • Lithology description of a 300m-thick Oligocene borehole strata in the Qujing area, Yunnan

    Lithology description of a 300m-thick Oligocene borehole strata in the Qujing area, Yunnan

    The thick Cenozoic sediments deposited in Yunnan are ideal achieves used to explore the history of local deformation process affected by the collision of the Indian-Eurasian plate as well as the evolution of the Indian monsoon in the Cenozoic. However, due to the lack of precise age control, the early Neogene strata in Yunnan are poorly constrained. The Qujing Basin in the northern part of Yunnan Province preserves thick and continuous Cenozoic sediments, which can be divided into the Xiaotun Formation, the Caijiachong Formation and the Ciying Formation from bottom to top. Through the combination of the field outcrop profile and the borehole core, the research team obtained the stratified stratum of the Xiaotun Formation and the Caijiachong Formation with a total thickness of 251 m in the Qujing Basin. The U-Pb geochronology of the top volcanic tuff layer (35.49 ± 0.78 Ma), Caijiachong mammal fossil group (late Eocene) as well as magnetic stratigraphy collectively reveals that the age at the bottom of the Xiaotun Formation is 46.2 Ma, the top of the Caijiachong Formation should be < 36.2 Ma, and the epoch line of the two groups is 41.2 Ma. However, due to the weak influence of tectonic activities in the late Cenozoic and the small deformation of the formation, the terrain in the middle of the basin is relatively flat, resulting in the inability to obtain the top of the continuous Caijiachong Formation and the upper Ciying Formation samples. A total of 320.1 meter core covering the entire Ciying Formation and the Caijiachong Formation was obtained through the continuous drilling mission carried out in the center of the basin. Among them, the overall lithology of the core of the Ciying Formation (0-216.3 m) is dominated by gray mudstone and siltstone, and several layers of coal seams are intercalated; while the lower Caijiachong Formation (216.3-305.5 m) is grayish and grayish green mudstone. The lithology of the Xiaotun Formation (305.5-320.1 m) is mainly dominated by red mudstone.

    2019-11-25 225 1 View Details

  • Glacier temperature dataset of Xiaodong Kemadi (2012-2015)

    Glacier temperature dataset of Xiaodong Kemadi (2012-2015)

    This is the daily temperature observation data set of 6 points in Xiaodong Kemadi, 4 points in Yangbajing, and 4 points in Hariqin during 2012-2015.

    2019-11-22 518 0 View Details

  • Water quality slope data of Co Ngoin Lake (2017)

    Water quality slope data of Co Ngoin Lake (2017)

    The data set includes the vertical profile of water quality and the multi-parameter data of surface water quality of Selincho Lake during the investigation of the sources of rivers and lakes from June to July of 2017. The main water quality parameters measured are dissolved oxygen, conductivity, pH, water temperature, etc. YSI EXO2 water quality multi-parameter measuring instrument is calibrated according to lake surface elevation and local pressure before each measurement. The time interval of measurement is set at 0.25s, and the speed of putting in is slow, so he high continuity of data acquisition is guaranteed. The original data obtained include the measured data exposed to air above the water surface, which are eliminated in the later processing.

    2019-11-22 525 7 View Details

  • None

    2019-11-20 104 1 View Details

  • Dataset of key elements of desertification in typical watershed of Central and Western Asia (Amu River Basin)

    Dataset of key elements of desertification in typical watershed of Central and Western Asia (Amu River Basin)

    Data Set of Key Elements of Desertification in Typical Watershed of Central and Western Asia includes four parts: distribution and change of agricultural land of Amu River Basin, distribution and change of grassland of Amu River Basin, distribution and change of shrub land of Amu River Basin, distribution and change of forests of Amu River Basin. the spatial resolution of data is 30 m. All the data is based on Landsat TM/ETM image data in 1990, 2000 and 2010. The data produced by the key laboratory of remote sensing and GIS, Xinjiang institute of ecology and geography, Chinese Academy of Sciences. Data production Supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Grant No. XDA20030101.

    2019-11-19 199 3 View Details

  • A monthly air temperature and precipitation gridded dataset on 0.025° spatial resolution in China during(1951-2011)

    A monthly air temperature and precipitation gridded dataset on 0.025° spatial resolution in China during(1951-2011)

    Gridded climatic datasets with fine spatial resolution can potentially be used to depict the climatic characteristics across the complex topography of China. In this study we collected records of monthly temperature at 1153 stations and precipitation at 1202 stations in China and neighboring countries to construct a monthly climate dataset in China with a 0.025° resolution (~2.5 km). The dataset, named LZU0025, was designed by Lanzhou University and used a partial thin plate smoothing method embedded in the ANUSPLIN software. The accuracy of LZU0025 was evaluated based on three aspects: (1) Diagnostic statistics from the surface fitting model during 1951–2011. The results indicate a low mean square root of generalized cross validation (RTGCV) for the monthly air temperature surface (1.06 °C) and monthly precipitation surface (1.97 mm1/2). (2) Error statistics of comparisons between interpolated monthly LZU0025 with the withholding of climatic data from 265 stations during 1951–2011. The results show that the predicted values closely tracked the real true values with values of mean absolute error (MAE) of 0.59 °C and 70.5 mm, and standard deviation of the mean error (STD) of 1.27 °C and 122.6 mm. In addition, the monthly STDs exhibited a consistent pattern of variation with RTGCV. (3) Comparison with other datasets. This was done in two ways. The first was via comparison of standard deviation, mean and time trend derived from all datasets to a reference dataset released by the China Meteorological Administration (CMA), using Taylor diagrams. The second was to compare LZU0025 with the station dataset in the Tibetan Plateau. Taylor diagrams show that the standard deviation, mean and time trend derived from LZU had a higher correlation with that produced by the CMA, and the centered normalized root-mean-square difference for this index derived from LZU and CMA was lower. LZU0025 had high correlation with the Coordinated Energy and Water Cycle Observation Project (CEOP) - Asian Monsoon Project, (CAMP) Tibet surface meteorology station dataset for air temperature, despite a non-significant correlation for precipitation at a few stations. Based on this comprehensive analysis, we conclude that LZU0025 is a reliable dataset. LZU0025, which has a fine resolution, can be used to identify a greater number of climate types, such as tundra and subpolar continental, along the Himalayan Mountain. We anticipate that LZU0025 can be used for the monitoring of regional climate change and precision agriculture modulation under global climate change.

    2019-11-18 5036 193 View Details

  • Water level observation data of Selincuo Lake (2016-2017)

    Water level observation data of Selincuo Lake (2016-2017)

    This is the water level observation data of Selincuo Lake. It can be used in Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from September 17, 2016 to February 15,2017. It is measured by automatic water gauge and a piece of data is recorded every 60 minutes. The data includes the water pressure and water temperature of the water level observation point on the east bank of Selincuo Lake.The original data is precise, with the pressure accurate to 0.001kP and the water temperature 0.001℃. The original data forms a continuous time series after quality control. And the daily mean index data is obtained through calculation. The data is stored as an excel file.

    2019-11-18 546 0 View Details

  • Water depth measurement dataset over the Kering Tso Lake (2017)

    Water depth measurement dataset over the Kering Tso Lake (2017)

    This data set includes the water depth measurement data during the Jianghuyuan expedition from June to July 2017 over the Kering Tso Lake. The measurement time is on July 2, 2017. The data was measured by Lowrance HDS-5 sonar sounder. The original data was generated by surfer 13 software and Kriging difference method. The original data contained more invalid depth data, which had been screened out in the later stage of collation. The survey line is reasonable to ensure that the data cover all depth gradients.

    2019-11-18 332 3 View Details

  • Bathymetric data of Co Ngoin Lake (2017)

    Bathymetric data of Co Ngoin Lake (2017)

    This data set comprises the depth measurements of Co Ngoin Lake during the River and Lake Source Investigation from June to July in 2017. The measurements were obtained on June 24, 2017 using a Lowrance HDS-5 sonar depth finder. The original data are made into the isobath map processed by the Surfer 13 software using the Kriging method. The original measured data contain numerous invalid depth data, all of which has been eliminated in the postselection process. The selected measurement line is reasonable, and the data cover various depth gradients.

    2019-11-18 414 4 View Details