Land Surface Temperature
Land surface temperature, 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's 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. Satellite LST can be assimilated into climate and atmospheric and land surface models to estimate sensible heat flux and latent heat flux. It can also be applied for analyzing climate change due to its long-term archive from imagery data of geostationary and polar-orbiting satellites. In the United States of America, demands of satellite LST data are from a variety of government agencies including the National Oceanic and Atmospheric Administration (NOAA, Department of Agriculture (DOA), Environmental Protection Agency (EPA), Department of the Interior (DOI), Department of Defense (DOD), as well as from universities and research institutes.
The Land Surface Temperature (LST) product will be derived from GOES-R ABI longwave infrared spectral channels. Accuracy of the satellite LST measurement is limited by the atmospheric correction, the complexity of surface emission characteristics, and sensor performance. Among those, variation of surface emissivity is the biggest difficulty in the satellite LST measurement.
Improvements and Benefits
GOES-R LST expected to be used in a number of applications in hydrology, meteorology, and climatology. Forecasters will use it to forecast the occurrence of fog and frost. The land surface product is of fundamental importance to the net radiation budget at the Earth's surface and to monitoring the state of crops and vegetation. It is an important indicator of both the greenhouse effect and the energy flux between the atmosphere and ground. Furthermore, it can be assimilated into climate, atmospheric, and land surface models to estimate sensible heat flux and latent heat flux.
Example of the Land Surface Temperature (LST) product as generated by the GOES-R Land Surface Temperature algorithm using Meteoest-9/SEVIRI data on 15 April, 2008 12:45 UTC.
How does it work? - Algorithm
The ABI LST product is based on a split-window technique that corrects for atmospheric absorption, and applies prescribed surface emissivity information. In addition, an atmospheric path length term is applied to further correct for local zenith angle effect (Yu et al., 2009a). Coefficients of the LST algorithm, which were derived using an atmospheric radiative transfer model (RTM), are stratified for daytime and nighttime conditions, as well as for dry and moist atmospheres. The algorithm is then verified using a RTM simulation dataset, and evaluated using proxy dataset and ground measurements.
See the GOES-R ATBD page for all ATBDs.
How are the results compared to existing data? - Calibration and Validation
ABI LST will be validated with ground-based and satellite-based LST products, allowing comparison of satellite to satellite as well as satellite to ground in situ measurements. The in situ measurements will be based on seven operational stations of the Surface Radiation Budget Network (SURFRAD) in the US. The Climate Reference Network (CRN) and Atmospheric Radiation Measurement (ARM), which has over 130 stations in the US provide data with less accuracy. These data will be used as a complementary data resource. Satellite sources include NPP VIIRS and EOS MODIS (if it is still available). The EOS Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) will be used for characterizing ground stations before the GOES-R launch. China's Feng-Yun satellite is also considered a satellite data source. Finally, the ground LSTs may also be collected from field campaigns supported from a variety of domestic and international programs.
A more technical validation presentation, (PDF, 20.71 MB) is also available.