netcdf GATP_Aru_1_15584414038312380335 {
dimensions:
y = 800 ;
x = 150 ;
Time = 1488 ;
time = UNLIMITED ; // (1488 currently)
variables:
float temperature(Time, y, x) ;
temperature:_FillValue = NaNf ;
temperature:standard_name = "air_temperature" ;
temperature:long_name = "corrected_surface_air_temperature" ;
temperature:units = "degrees Celsius" ;
temperature:FillValue = NaNf ;
temperature:missing_value = NaNf ;
temperature:comment = "Temperature data contains missing values: nan, Actual range: -32.89911 to 4.9999084 ." ;
int time(time) ;
time:units = "minutes since 2019-01-01 00:00:00" ;
time:calendar = "gregorian" ;
time:standard_name = "time" ;
time:long_name = "Time duration" ;
time:axis = "T" ;
float Longitude(y, x) ;
Longitude:standard_name = "longitude" ;
Longitude:long_name = "Longitude" ;
Longitude:units = "degrees_east" ;
float Latitude(y, x) ;
Latitude:standard_name = "latitude" ;
Latitude:long_name = "Latitude" ;
Latitude:units = "degrees_north" ;
float surface_bidirectional_reflectance(y, x) ;
surface_bidirectional_reflectance:grid_cell_size_reflective = 30.f ;
surface_bidirectional_reflectance:units = "percent" ;
surface_bidirectional_reflectance:standard_name = "surface_bidirectional_reflectance" ;
surface_bidirectional_reflectance:long_name = "surface bidirectional reflectance" ;
// global attributes:
:title = "Temperature Data in Aru region for 2019-01" ;
:references = "reference_1: https://doi.org/10.5066/P9OGBGM6\nreference_2: Yang, W. (2021). Temperature data of six glaciers in high altitude area of Qinghai Tibet Plateau (2019). National Tibetan Plateau / Third Pole Environment Data Center. https://doi.org/10.11888/Cryos.tpdc.271916." ;
:institution = "Shenyang University of Technology" ;
:institution_id = "SUT" ;
:institution_url = "https://www.sut.edu.cn/" ;
string :comment = "This dataset contains spatialization of near-surface air temperature in high-elevation glacierized regions in the Qinghai-Tibet Plateau. \nIce-covered study region is Aru Glacier region on the northwestern Tibetan Plateau.An AWS_aru was installed near the collapse fan, with the 4978 m elevation.\nT loggers were deployed on Aru Glacier,with 1 T logger located in front of the terminus moraines and 6 six other T loggers distributed on the glacier surface from 5357 to 6013 m MSL.The latitude and longitude coordinates were derived from a single-subscene remote sensing image acquired on January 8, 2019.The selected observations at Aru include 8 stations: AWS_aru, A1, A2, A3, A4, A5, A6, A7.\nCore Variable: Temperature (half-hourly surface air temperature at 30 m resolution)\nDimensions: (1488, 800, 150)\n1488 → Time steps (2019-01-01 00:00:00 – 2019-01-31 23:30:00, half-hourly) \n800 → Grid rows (latitude/y-axis)\n150 → Grid columns (longitude/x-axis)\nThe data for the Aru Glacier region covers the period from 1 January 2019 to 31 January 2019." ;
:program = "Single-Channel Algorithm, Voronoi-Delaunay triangulation, Gaussian Filter, Mean Filter" ;
:license = "CC-BY 4.0" ;
:keywords_vocabulary = "Global Change Master Directory (GCMD): https://earthdata.nasa.gov/earth-observation-data/find-data/gcmd/gcmd-keywords" ;
:keywords = "GCMD: Earth Science>Atmosphere>Atmospheric Temperature>Surface Air Temperature" ;
:contact = "Tianyun Wang <>" ;
:product_version = "1.0.0" ;
:standard_name_vocabulary = "CF Standard Name Table v27" ;
:realm = "landIce" ;
string :summary = "This dataset provides high-resolution (30 m) spatialized air temperature estimates for the Qinghai-Tibet Plateau,The spatialized air temperature is derived solely from ground-based meteorological station measurements interpolated within a geographic framework defined by Landsat 8 thermal infrared data.The spatial interpolation relies on Voronoi-Delaunay triangulation, using station measurements as anchors while leveraging Landsat precise geospatial coordinates (latitude/longitude) to delineate the interpolation grid boundaries.For simple and fast smoothing of gridded surface temperature data, use the mean filter; for edge-preserving denoising that maintains spatial gradients, choose the Gaussian filter.\nUnlike conventional methods, this approach does not incorporate satellite-derived land surface temperature (LST) values; Instead, it uses Landsat data strictly as a spatial reference to ensure accurate 30 m grid alignment.The resulting product combines the reliability of station observations with the fine-scale spatial structure of satellite data,It is suitable for studies requiring high-precision temperature distribution without the uncertainties associated with remote sensing temperature retrievals.The spatial grid alignment relies on Landsat 8 imagery acquired on January 8, 2019. \nThe study period for the Aru Glacier region spans January 2019 (01–31 January)." ;
:processing_level = "L4" ;
:source = "source_1: Image courtesy of the U.S. Geological Survey, LANDSAT_8 OLI/TIRS, L2SP, FILE_NAME_BAND_ST_B10. \nsource_2: Yang, W. (2021). Temperature data of six glaciers in high altitude area of Qinghai Tibet Plateau (2019). National Tibetan Plateau / Third Pole Environment Data Center. https://doi.org/10.11888/Cryos.tpdc.271916." ;
:source_type = "AER" ;
:frequency = "1hr" ;
:history = "Created on 2025-5-15, using Python netCDF4." ;
:creation_date = "2025-05-15T12:30:00Z" ;
:creator = "Tianyun Wang" ;
:Conventions = "CF-1.8 ATMODAT-3.0" ;
:atmodat = "3.0" ;
:MAP_PROJECTION = "UTM" ;
:Projection_Information = "UTM Zone 47N (WGS84)" ;
:im_GeoTransform = 618915., 30., 0., 3764625., 0., -30. ;
:UTM_ZONE = "44" ;
:img_proj = "PROJCS[\"WGS 84 / UTM zone 44N\",GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563,AUTHORITY[\"EPSG\",\"7030\"]],AUTHORITY[\"EPSG\",\"6326\"]],PRIMEM[\"Greenwich\",0,AUTHORITY[\"EPSG\",\"8901\"]],UNIT[\"degree\",0.0174532925199433,AUTHORITY[\"EPSG\",\"9122\"]],AUTHORITY[\"EPSG\",\"4326\"]],PROJECTION[\"Transverse_Mercator\"],PARAMETER[\"latitude_of_origin\",0],PARAMETER[\"central_meridian\",81],PARAMETER[\"scale_factor\",0.9996],PARAMETER[\"false_easting\",500000],PARAMETER[\"false_northing\",0],UNIT[\"metre\",1,AUTHORITY[\"EPSG\",\"9001\"]],AXIS[\"Easting\",EAST],AXIS[\"Northing\",NORTH],AUTHORITY[\"EPSG\",\"32644\"]]" ;
:geospatial_vertical_resolution = "Undefined" ;
:nominal_resolution = "0.5 km" ;
:geospatial_lat_resolution = "30 m" ;
:geospatial_lon_resolution = "30 m" ;
:crs = "WGS84" ;
:featureType = "point" ;
:further_info_url = "https://swiftbrowser.dkrz.de/tcl_s/C17Xs1bKsPDlGS" ;
:metadata_link = "https://swiftbrowser.dkrz.de/tcl_s/C17Xs1bKsPDlGS/ST_RFR_0124_Naimonanyi" ;
:project = "Heat Island Intensity Prediction in an Intelligent Sponge Urban System in the Qinghai-Tibet Plateau" ;
:grid_mapping_name = "latitude_longitude" ;
}