Abstract
Our objective is to develop a framework for deriving long term, consistent Land Surface Temperatures (LSTs) from Geostationary (GEO) satellites that is able to account for satellite sensor updates. Specifically, we use the Radiative Transfer for TOVS (RTTOV) model driven with Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) information and Combined ASTER and MODIS Emissivity over Land (CAMEL) products. We discuss the results from our comparison of the Geostationary Operational Environmental Satellite East (GOES-E) with the MODIS Land Surface Temperature and Emissivity (MOD11) products, as well as several independent sources of ground observations, for daytime and nighttime independently. Based on a six-year record at instantaneous time scale (2004–2009), most LST estimates are within one std from the mean observed value and the bias is under 1% of the mean. It was also shown that at several ground sites, the diurnal cycle of LST, as averaged over six years, is consistent with a similar record generated from satellite observations. Since the evaluation of the GOES-E LST estimates occurred at every hour, day and night, the data are well suited to address outstanding issues related to the temporal variability of LST, specifically, the diurnal cycle and the amplitude of the diurnal cycle, which are not well represented in LST retrievals form Low Earth Orbit (LEO) satellites.
Highlights
Land surface temperature is an important climate parameter due to its control of the components of the surface energy budget, such as turbulent heat and moisture fluxes, and upward terrestrial radiation [1]
A new land surface emissivity Earth Science Data Systems (ESDS) product has been developed in support of a NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) project [30,31] Moderate-resolution Imaging Spectroradiometer (MODIS)-ASTER Global Infrared Combined Emissivity product produced from the University Wisconsin Global Infrared Land Surface Emissivity (UWIREMIS) and the ASTER Global Emissivity (GED) Database are known as the Combined ASTER and MODIS Emissivity for Land (CAMEL) and represents a combination of MODIS baseline-fit emissivity database (MODBF)
We will present results of evaluation for UMD Land Surface Temperatures (LSTs) retrievals against MOD11 products, the Baseline Surface Radiation Network (BSRN)/Surface Radiation Budget Network (SURFRAD) network over the USA, the Atmospheric Radiation Measurement (ARM)/SGP C1 site over the Southern Great Plains, and the MESONET network over Oklahoma
Summary
Land surface temperature is an important climate parameter due to its control of the components of the surface energy budget, such as turbulent heat and moisture fluxes, and upward terrestrial radiation [1]. The early effort to retrieve LST from satellites over agricultural land made by Price [3] was done by adopting the Advanced Very High Resolution Radiometer (AVHRR) Sea Surface Temperature (SST) split window algorithm [12,13]. Becker and Li [14] extended the split window method of McMillin [15] for SST to LST and took into account the spectral variability in land surface emissivity This so called “generalized split window” LST algorithm has been widely used. While the principles of retrieval methodologies have not changed drastically over time, the development in auxiliary information, quality of such information, and availability of long term records of satellite observations make it feasible to formulate a homogeneous approach across various satellite sensors that can culminate in climatic records of LST.
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