Land surface temperature (LST), a key
indicator of the Earth surface energy budget, is widely required in applications of hydrology,
meteorology, and climatology. It is of fundamental importance to the net radiation budget at the
Earth surface and to monitoring the state of crops and vegetation, as well as an important indicator
of both the greenhouse effect and the energy flux between the atmosphere and ground.
VIIRS LST is produced from VIIRS satellite S-NPP and NOAA-20, for each non-confidently-cloudy land
pixel observed by the VIIRS sensor. The LST retrieval will rely on data from VIIRS channels M15 and
M16 using split window technique, which corrects for atmospheric absorption, and applies surface
emissivity explicitly in the retrieval. Coefficients of the LST algorithm, which were derived using
an atmospheric radiative transfer model (RTM), are stratified by daytime and nighttime conditions,
multiple levels of viewing geometry and dry and moist atmospheric conditions. The algorithm is then
verified using a RTM simulation dataset and evaluated using S-NPP (NOAA-20) VIIRS dataset and ground
measurements.
The VIIRS LST product is in Netcdf4 format, which includes LST values, associated quality flags as
well as the related emissivity values including the spectral emissivity of the two split window
channels, broadband emissivity and associated emissivity quality flags. To minimize the file size,
the LST value is stored as a scaled value in 16-bit integer type. The emissivity value is stored as
scaled value in 8-bit integer type. Scale factor and offset as well as valid range, fill value etc.
are provide as the data attributes. The quality flags are 2-byte bitwise short integer, which
contains quality information of LST production for each pixel. Upon user request, the viewing
geometry including satellite zenith angle and azimuth angle is also added into the LST
output.
For information on the science algorithms, see the VIIRS Land Surface Temperature Algorithm Theoretical Basic Document (ATBD).
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