netcdf QTB_corr_1_13640909516982448455 {
dimensions:
y = 7752 ;
x = 7421 ;
time = UNLIMITED ; // (41 currently)
variables:
float temperature(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: -999.0 to 29.999298 ." ;
int time(time) ;
time:units = "seconds since 2019-01-02 04:03:49" ;
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 = "Corrected Surface Temperature Data for 2019-01-02" ;
: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/" ;
:comment = "This dataset contains surface temperature data corrected using a Random Forest Regressor algorithm. \nThe corrected surface temperature is based on 1 remote sensing image. The root mean squared error of the corrected surface air temperature is 1.83degrees Celsius. \nThe standard deviation of the test stations within the training coverage area is 1.73 degrees Celsius. \nThe root mean squared error of the surface temperature derived from thermal infrared remote sensing is 4.40 degrees Celsius. \nThe standard deviation of the surface temperature derived from thermal infrared remote sensing within the training coverage area is 4.25 degrees Celsius. \nThe test stations at the Parlung site include 23 stations: AWS4400, AWS4800, P1_390, P2_390, P3_390, P4_390, P5_390, P6_390, P7_94, P8_94, P9_94, P10_94, P11_94, P12_94, P13_94, P14_94, P15_4, P16_4, P17_4,\tP18_4, P19_4, P20_4, P21_4. \nWhen the 23 test stations at Parlung are used as test set data, they do not participate in the model training, the root mean squared error(RMSE) is 2.23 degrees Celsius, the standard deviation(STD) is 1.97 degrees Celsius. \nScene center time of the 1 remote sensing image is 04:04:09.6773829Z; date_acquired is 2019-01-02." ;
:program = "Single-Channel Algorithm, Random Forest Regressor Algorithm" ;
: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 contains corrected surface air temperature data, which has been processed using meteorological observation data and thermal infrared remote sensing data. \nThe data covers a high-altitude area of the Qinghai-Tibet Plateau, with a spatial resolution of 30 meters. \nThe original temperature data were obtained from multiple sources, including thermal infrared remote sensing data from Landsat 8(L8) and Landsat 9 (L9) Collection 2 (C2) Level 2 (L2) products,as well as ground station measurements from National Tibetan Plateau/Third Pole Environment Data Center. \nL2SP includes Surface Temperature (ST), the L2SP image data are atmospherically corrected, each image band is available in a separate file. \nThe earth’s surface temperature is provided by ST band based on thermal infrared remote sensing information. \nDigital Number (DN) of standard L2SP is stored in a 16-bit unsigned integer format, ST is calculated by the Single Channel algorithm. \nThe value of Multiplicative factor is 0.00341802, which is used to scale the temperature converted by DN. \nThe value of additive factor is 149.0, which is used to scale the temperature converted by DN. \nThe regression algorithms in supervised learning was trained to correct for biases and inaccuracies in updating the spatialized near-surface air temperature. \nThis dataset is suitable for climate research, environmental monitoring, and other applications requiring relatively accurate surface air temperature data. " ;
: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 2024-11-19, using Python netCDF4." ;
:creation_date = "2025-02-14T12:30:00Z" ;
:creator = "Tianyun Wang" ;
:Conventions = "CF-1.8 ATMODAT-3.0" ;
:atmodat = "3.0" ;
:MAP_PROJECTION = "UTM" ;
:Projection_Information = "UTM Zone 47N (WGS84)" ;
:im_GeoTransform = 141765., 30., 0., 3312135., 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" ;
}