The data was compiled from "China's 1:100,000 wetland data". "China 1:100,000 wetland data" mainly reflects the information of marshes and wetlands throughout the country in the 2000s, and is represented by geographical coordinates in decimal scale. The main contents include: types of marshes and wetlands, types of water supply, types of soil, types of main vegetation, and geographical regions.The information classification and coding standard of China sustainable development information sharing system was implemented.Data source of this database: 1:20 swamp map (internal version), 1:500 000 swamp map (internal version) of qinghai-tibet plateau, 1:100 000 swamp survey data and 1:400 000 swamp map of China;The processing steps are as follows: data source selection, preprocessing, marshland element digitization and coding, data editing and processing, establishment of topological relationship, edge-to-edge processing, projection transformation, connection with attribute database such as geographical name and acquisition of attribute data.

Based on the Global 1,000,000 Basic Geographic Data (2010) of the Resource and Environment Science Data Center of the Chinese Academy of Sciences, the administrative divisions of Arctic countries (USA, Canada, Russia, Norway (including Greenland and the Faroe Islands), Denmark, Sweden, Finland, and Iceland) at the national and provincial levels are extracted via ArcGIS. The data are stored separately by nation. The data format is the .shp format of ArcGIS, and the projection mode is GCS_WGS_1984. The national data are from http://www.resdc.cn/data.aspx?DATAID=205. The provincial data are from http://www.resdc.cn/data.aspx?DATAID=206.

Digital Elevation Model (DEM) is a kind of solid ground Model that represents the ground Elevation in the form of a set of ordered numerical arrays. The arctic region within 66 ° 34 'refers to the arctic regions and parts of Greenland in the arctic.Elevation data include arctic digital dem and hillshade data in tif format.Range of 66 ° ~ 90 ° N N, the spatial resolution of 0.008 ° x 0.008 °. The data is downloaded from NASA global elevation data DEM describes ground elevation information, which is widely used in surveying and mapping, hydrology, meteorology, geomorphology, geology, soil, engineering construction, communication, military and other fields of national economy and national defense as well as humanities and natural sciences.

This dataset is the population index, which includes the dataset of Qinghai Province and Tibet Autonomous Region. It can be used for the coupling coordination relationship between urbanization and eco-environment in Qinghai-Tibet Plateau. The time span in Tibet Autonomous Region is 1995-2016. Permanent residents is based on the population census and the annual population change sampling survey. In addition to the total permanent population, the data were also calculated by gender and urban and rural areas. The time span is from 1952 to 2015 in Qinghai Province, and the indices are resident population, birth, death and natural increase. All data is from the statistical yearbook.

The third pole 1:100,000 range data set includes:Mountains(Tibet_Mountains)vector space data set and its attribute name:Name(Name)、Countries Name（CNTRY_NAME）、Countries Referred to as（CNTRY_CODE）、Latitude（LATITUDE）、Longitude(LONGITUDE). The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，Data through the topology, into the library，It's comprehensive, up-to-date and seamless geodigital data. The world map coordinate system is latitude and longitude, D_WGS_1984 datum surface

A multi-layer soil particle-size distribution dataset (sand, silt and clay content), based on USDA (United States Department of Agriculture) standard for regional land and climate modelling in China. was developed The 1:1,000,000 scale soil map of China and 8595 soil profiles from the Second National Soil Survey served as the starting point for this work. We reclassified the inconsistent soil profiles into the proper soil type of the map as much as possible because the soil classification names of the map units and profiles were not quite the same. The sand, silt and clay maps were derived using the polygon linkage method, which linked soil profiles and map polygons considering the distance between them, the sample sizes of the profiles, and soil classification information. For comparison, a soil type linkage was also generated by linking the map units and soil profiles with the same soil type. The quality of the derived soil fractions was reliable. Overall, the map polygon linkage offered better results than the soil type linkage or the Harmonized World Soil Database. The dataset, with a 1-km resolution, can be applied to land and climate modelling at a regional scale. Data characteristics： projection：projection Coverage: China Resolution: 0.00833 (about 1 km) Data format: FLT, TIFF Value range: 0%-100% Document describing： Floating point raster files include: Sand1. FLT, clay1. FLT -- surface (0-30cm) sand, clay content. Sand2. FLT, clay2. FLT -- content of sand and clay in the bottom layer (30-100cm). PSD. HDR -- header file: Ncols - the number of columns Nrows- rows Xllcorner - latitude in the lower left corner Yllcorner - longitude of the lower left corner Cellsize - cellsize NODATA_value - a null value byteorder - LSBFIRST, Least Significant Bit First TIFF raster files include: Sand1. Tif, clay1. Tif - surface (0-30cm) sand, clay content. Sand2. Tif, clay2. Tif - bottom layer (30-100cm) sand, clay content.

Snow cover dataset is produced by snow and cloud identification method based on optical instrument observation data, covering the time from 1989 to 2018 (two periods, from January to April and from October to December) and the region of Qinghai-Tibet Plateau (17°N-41°N, 65°E-106°E) with daily product, which takes equal latitude and longitude projection with 0.01°×0.01° spatial resolution, and characterizes whether the ground under clear sky or transparent thin cloud is covered by snow. The input data sources include AVHRR L1 data of NOAA and MetOp serials of satellites, and L1 data corresponding to AVHRR channels taken from TERRA/MODIS. Decision Tree algorithm (DT) with dynamic thresholds is employed independent of cloud mask and its cloud detection emphasizes on reserving snow, particularly under transparency cirrus. It considers a variety of methods for different situations, such as ice-cloud over the water-cloud, snow in forest and sand, thin snow or melting snow, etc. Besides those, setting dynamic threshold based on land-surface type, DEM and season variation, deleting false snow in low latitude forest covered by heavy aerosol or soot, referring to maximum monthly snowlines and minimum snow surface brightness temperature, and optimizing discrimination program, these techniques all contribute to DT. DT discriminates most snow and cloud under normal circumstances, but underestimates snow on the Qinghai-Tibet Plateau in October. Daily product achieves about 95% average coincidence rate of snow and non-snow identification compared to ground-based snow depth observation in years. The dataset is stored in the standard HDF4 files each having two SDSs of snow cover and quality code with the dimensions of 4100-column and 2400-line. Complete attribute descriptions is written in them.

This dataset includes five scenes, covering the artificial oasis eco-hydrology experimental area of the Heihe River Basin, which were acquired on (yy-mm-dd) 2012-04-05, 2012-04-21, 2012-05-07, 2012-06-24, 2012-07-10. The data were all acquired around 11:50 (BJT) with data product of Level 2. Landsat ETM+ dataset was downloaded from http://glovis.usgs.gov/.

This dataset includes one scene acquired on (yy-mm-dd hh:mm, BJT) 2012-07-06 06:30, covering the artificial oasis eco-hydrology experimental area of the Heihe River Basin. This datum was acquired at Stripmap-Quad mode with product level of SLC, and this image includes VV, VH, HH and HV polarization with a spatial resolution of 8 m. Radarsat-2 dataset was acquired from the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences (Courtesy: Dr. Chen Quan).

The data set of 1:100,000 settlements in the Arctic includes all settlements in the North Pole (Arctic_Resident), capital settlements (Arctic_Capitals), Cities_up_to_75K settlements and other vector spatial data and related attribute data: urban name (ENG_NAME), CITY_POP and other properties. The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，It's most comprehensive, current and seamless geographic digital data for the whole earth. The world map coordinate system is latitude and longitude, WGS84 datum surface，Arctic specific projection parameters（North_Pole_Stereographic）.

A gridded ocean temperature dataset with complete global ocean coverage is a highly valuable resource for the understanding of climate change and climate variability. The Institute of Atmospheric Physics (IAP) provides a new objective analysis of historical ocean subsurface temperature since 1990 for the upper 2000m through several innovative steps. The first was to use an updated set of past observations that had been newly corrected for biases (e.g., in XBTs). The XBT bias was corrected by CH14 scheme, which is recommended by the XBT community. The second was to use co-variability between values at different places in the ocean and background information from a number of climate models that included a comprehensive ocean model. The third was to extend the influence of each observation over larger areas, recognizing the relative homogeneity of the vast open expanses of the southern oceans. Then the observations were also used to provide finer scale detail. Finally, the new analysis was carefully evaluated by using the knowledge of recent well-observed ocean states, but subsampled using the sparse distribution of observations in the more distant past to show that the method produces unbiased historical reconstruction. The ocean wind data set is constructed using RSS Version-7 microwave radiometer wind speed data. The input microwave data are processed by Remote Sensing Systems with funding from the NASA MEaSUREs Program and from the NASA Earth Science Physical Oceanography Program. This wind speed product is intended for climate study as the input data have been carefully intercalibrated and consistently processed. Each netCDF file contains: 1) monthly means of wind speed, grid size 360x180xnumber of all months since Jan 1988(increases over time) 2) a 12-month set of climatology wind speed, grid size 360x180, the climatology is an average calculated over the 20-year period 1988-2007 3) monthly anomalies of wind speed derived by subtracting the above climatology maps from the monthly means, grid size 360x180x#months since Jan 1988 (increases over time) 4) a wind speed trend map, grid size 360x180, the trend is calculated from 1988-01-01 to the latest complete calendar year 5) a time-latitude plot (a minimum of 10% of latitude cells is required for valid data), grid size 180x#months since Jan 1988 (increases over time).

The aerosol optical thickness data of the Arctic Alaska station is based on the observation data products of the atmospheric radiation observation plan of the U.S. Department of energy at the Arctic Alaska station. The data coverage time is updated from 2017 to 2019, with the time resolution of hour by hour. The coverage site is the northern Alaska station, with the longitude and latitude coordinates of (71 ° 19 ′ 22.8 ″ n, 156 ° 36 ′ 32.4 ″ w). The source of the observed data is retrieved from the radiation data observed by mfrsr instrument. The characteristic variable is aerosol optical thickness, and the error range of the observed inversion is about 15%. The data format is NC format. The aerosol optical thickness data of Qomolangma station and Namuco station in the Qinghai Tibet Plateau is based on the observation data products of Qomolangma station and Namuco station from the atmospheric radiation view of the Institute of Qinghai Tibet Plateau of the Chinese Academy of Sciences. The data coverage time is from 2017 to 2019, the time resolution is hour by hour, the coverage sites are Qomolangma station and Namuco station, the longitude and latitude coordinates are (Qomolangma station: 28.365n, 86.948e, Namuco station Mucuo station: 30.7725n, 90.9626e). The source of the observed data is retrieved from the radiation data observed by mfrsr instrument. The characteristic variable is aerosol optical thickness, and the error range of the observed inversion is about 15%. The data format is TXT.