Sea-Surface Temperature, NOAA Geo-polar Blended Analysis Diurnal Correction (Day+Night), GHRSST, Near Real-Time, Global 5km, 2019-Present, Daily

Analysed blended sea surface temperature over the global ocean using day and night input data. An SST estimation scheme which combines multi-satellite retrievals of sea surface temperature datasets available from polar orbiters, geostationary InfraRed (IR) and microwave sensors into a single global analysis. This global SST ananlysis provide a daily gap free map of the foundation sea surface temperature at 0.05o spatial resolution.
acknowledgement=NOAA/NESDIS
cdm_data_type=Grid
comment=The Geo-Polar Blended Sea Surface Temperature (SST) Analysis combines multi-satellite retrievals of sea surface temperature into a single analysis of SST
Conventions=CF-1.6, Unidata Observation Dataset v1.0, COARDS, ACDD-1.3
Easternmost_Easting=179.975
gds_version_id=2.0
geospatial_lat_max=89.975
geospatial_lat_min=-89.975
geospatial_lat_resolution=0.049999999999999996
geospatial_lat_units=degrees_north
geospatial_lon_max=179.975
geospatial_lon_min=-179.975
geospatial_lon_resolution=0.049999999999999996
geospatial_lon_units=degrees_east
history=NESDIS geo-SST L1 to L2 processor, NESDIS Advanced Clear-Sky Processor for Oceans (ACSPO), NESDIS Geo-Polar 1/20th degree Blended SST Analysis
id=Geo_Polar_DABlended-OSPO-L4-GLOB-v1.0
infoUrl=https://podaac.jpl.nasa.gov/dataset/Geo_Polar_DABlended-OSPO-L4-GLOB-v1.0
institution=NOAA NESDIS CoastWatch
keywords_vocabulary=GCMD Science Keywords
metadata_link=https://podaac.jpl.nasa.gov/ws/metadata/dataset?format=iso&shortName=Geo_Polar_DABlended-OSPO-L4-GLOB-v1.0
naming_authority=gov.noaa.coastwatch
Northernmost_Northing=89.975
platform=goes-16, goes-18, himawari-9, metop-b, metop-c, meteosat-9, meteosat-10, NOAA-20, NOAA-21,
processing_level=L4
project=Group for High Resolution Sea Surface Temperature
references=Fieguth,P.W. et al. "Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm", J. Atmos. Ocean Tech, 15 (2): 535-546, 1998. Fieguth, P. Multiply-Rooted Multiscale Models for Large-Scale Estimation, IEEE Image Processing, 10(11), 1676-1686, 2001. Khellah, F., P.W. Fieguth, M.J. Murray and M.R. Allen, "Statistical Processing of Large Image Sequences", IEEE Transactions on Geoscience and Remote Sensing, 12 (1), 80-93, 2005.
sensor=abi, abi, ahi, avhrr, avhrr, severi, severi, viirs, viirs,
source=OSPO_acspoSST_GOES16_ABI, OSPO_acspoSST_GOES18_ABI, STAR_acspoSST_HIMAWARI-9_AHI, OSPO_acspoSST_METOPB_AVHRR, OSPO_acspoSST_METOPC_AVHRR, OSPO_geoSST_METEOSAT9_severi, OSPO_geoSST_METEOSAT10_severi, OSPO_acspoSST_NOAA20_VIIRS, OSPO_acspoSST_NOAA21_VIIRS,
sourceUrl=(local files)
Southernmost_Northing=-89.975
spatial_resolution=0.05 degree
standard_name_vocabulary=CF Standard Name Table v29
testOutOfDate=now-4days
time_coverage_end=2024-12-10T12:00:00Z
time_coverage_start=2019-07-22T12:00:00Z
Westernmost_Easting=-179.975

本数据集通过对全球海洋的日夜输入数据进行融合分析，得出了全球海洋的混合海表温度。该海表温度估算方案综合了来自极地轨道卫星、地球静止红外（IR）和微波传感器的多颗卫星海表温度数据集，并形成一个单一的全局分析。该全球海表温度分析提供了每日无空隙的0.05度空间分辨率的基准海表温度地图。