Land Surface Temperature (LST) Retrieval from GOES Satellite Observations - Satellite-based Applications on Climate Change - page 286

Due to the lack of ground observations, all relevant sources of information on
surface skin temperature, directly, including the skin temperature observation from
the Atmospheric Radiation Measurement (ARM) and Mesonet networks, and
indirectly, such as the surface upwelling and downwelling longwave radiation,
and even soil temperature observations, had been used in the evaluations of
retrieved LSTs from GOES by Sun and Pinker ( 2003 , 2004 , 2006 a, b, 2007) and
Yu et al. ( 2009a , b , c ).
19.2 LST Retrieval from Geostationary Satellites
Most surface temperature retrievals from satellites are based on polar orbiters.
Surface temperature, especially land surface temperature, has a strong diurnal
cycle, which cannot be captured at the temporal resolution (approximately two
views per day) of such satellites. Geostationary satellites with high temporal
resolution, on the other hand, provide good diurnal coverage, making them attrac-
tive for deriving information on the diurnal LST cycle and diurnal temperature
range (DTR) (Sun et al. 2006), which is an important climate change index (Karl
et al. 1993 ).
Satellite retrievals of LST have been conducted for over 40 years from a variety
of polar-orbiting and geostationary satellites. For producing an LST climate data
record from those programs, consistency of the LST products from different
satellite mission is of importance. The GOES-Imager LST algorithm should have
a good historical heritage for consistency among other satellite products.
The GOES imager is a multichannel instrument designed to sense emitted and
reflected energy from sampled areas of the Earth. The multielement spectral
channels simultaneously sweep east-west and west-east along a north to south
path using a two-axis mirror scan system.
Accuracy of the satellite LST measurement is limited by the atmospheric
correction, the complexity of surface emission characteristics, and sensor perfor-
mance. Among those, variation of surface emissivity is the biggest difficulty in the
satellite LST measurement.
Currently, surface emissivity variation is still the biggest impediment in satellite
LST retrieval. The remote sensing community has been working for years to obtain
a time series of accurate global land surface emissivity maps (e.g., Borbas et al.
2008 ). The GOES-Imager LST algorithm should potentially benefit from such
improvement of emissivity measurement.
19.2.1 GOES Instrument Characteristics
The Geostationary Operational Environmental Satellite (GOES) system, operated by
the United States National Environmental Satellite, Data, and Information Service