期刊
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY
卷 30, 期 12, 页码 2868-2884出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/JTECH-D-13-00051.1
关键词
Surface temperature; Remote sensing; Satellite observations; Surface observations
资金
- NOAA Climate Data Record (CDR) Program
- NOAA/Office of Systems Development (OSD)
- NOAA/Center for Satellite Applications and Research (STAR)
Because of spectral shifts from instrument to instrument in the operational NOAA satellite imager longwave infrared channels, the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) has developed a single-channel land surface temperature (LST) algorithm based on the observed 11-m radiances, numerical weather prediction data, and radiative transfer modeling that allows for consistent results from the Geostationary Operational Environmental Satellite-I/L (GOES-I/L), GOES-M-P, and Advanced Very High Resolution Radiometer (AVHRR)/1 through 3 sensor versions. This approach is implemented in the real-time NESDIS processing systems [GOES Surface and Insolation Products (GSIP) and Clouds from AVHRR Extended (CLAVR-x)], and in the Pathfinder Atmospheres-Extended (PATMOS-x) climate dataset. An analysis of the PATMOS-x LST against that derived from the upwelling broadband longwave flux at each Surface Radiation Network (SURFRAD) site showed that biases in PATMOS-x were approximately 1 K or less. The standard deviations of the PATMOS-x minus SURFRAD LST biases are generally 2.5 K or less at all sites for all sensors. Using the PATMOS-x minus SURFRAD LST distributions to validate the PATMOS-x cloud detection, the PATMOS-x cloud probability of correct detection values were shown to meet the GOES-R specifications for all sites.
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