netcdf GATP_Parlung_1_16490707824659338161 {
dimensions:
y = 150 ;
x = 80 ;
Time = 7295 ;
time = UNLIMITED ; // (7295 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: -25.41365 to 19.235931 ." ;
int time(time) ;
time:units = "minutes since 2019-01-01 00:59:00" ;
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:
string :title = "Monthly Temperature Data in Parlung 4 Region January–October 2019" ;
: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 Parlung region located in the upper stream area of the Parlung Zangbu River basin on the southeastern Tibetan Plateau. \nIn this catchment, Parlung 4 glacier area have been monitored for air temperature.\nA total of 7 T loggers were deployed near/on the glacier. \nThe latitude and longitude coordinates were derived from a single-subscene remote sensing image acquired on January 2, 2019. \nThe selected observations at Parlung 4 include 7 stations: P15_4, P16_4, P17_4, P18_4, P19_4, P20_4 and P21_4. \nObservational data from stations P15_4–P21_4 cover the following months: Jan., Feb., Mar., Apr., May, Jun., Jul., Aug., Sep., Oct. \nCore Variable: Temperature (hourly surface air temperature at 30 m resolution)\nDimensions: (7296, 100, 600)\n7296 → Time steps (2019-01-01 00:59:00 – 2019-10-31 22:59:00, hourly) \n100 → Grid rows (latitude/y-axis)\n600 → Grid columns (longitude/x-axis)\nThe data for the Parlung 4 region covers the period from 1 January 2019 to 31 October 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. \nThe spatialized air temperature is derived solely from ground-based meteorological station measurements interpolated within a geographic framework defined by Landsat 8 thermal infrared data. \nThe 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. \nFor 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. \nInstead, it uses Landsat data strictly as a spatial reference to ensure accurate 30 m grid alignment. \nThe resulting product combines the reliability of station observations with the fine-scale spatial structure of satellite data. \nIt is suitable for studies requiring high-precision temperature distribution without the uncertainties associated with remote sensing temperature retrievals. \nThe spatial grid alignment relies on Landsat 8 imagery acquired on January 2, 2019. \nThe study period covers January to October 2019 (1 January – 31 October)." ;
: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 2025-5-19, using Python netCDF4." ;
:creation_date = "2025-05-19T12:30:00Z" ;
:creator = "Tianyun Wang" ;
:Conventions = "CF-1.8 ATMODAT-3.0" ;
:atmodat = "3.0" ;
:MAP_PROJECTION = "UTM" ;
:Projection_Information = "UTM Zone 47N (WGS84)" ;
:im_GeoTransform = 298185., 30., 0., 3240525., 0., -30. ;
:UTM_ZONE = "44" ;
:img_proj = "PROJCS[\"WGS 84 / UTM zone 47N\",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\",99],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\",\"32647\"]]" ;
: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" ;
}