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Open AccessArticle

Towards a Unified and Coherent Land Surface Temperature Earth System Data Record from Geostationary Satellites

1
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA
2
NASA Jet Propulsion Laboratory M/S 183-501, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
3
University of Wisconsin—Madison, Space Science and Engineering Center (SSEC) Cooperative Institute for Meteorological Satellite Studies (CIMSS), Madison, WI 53706, USA
4
NASA Marshall Space Flight Center, Huntsville, AL 35808, USA
5
School of Meteorology and School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73019, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(12), 1399; https://doi.org/10.3390/rs11121399
Received: 25 April 2019 / Revised: 31 May 2019 / Accepted: 4 June 2019 / Published: 12 June 2019
(This article belongs to the Special Issue Remote Sensing Monitoring of Land Surface Temperature (LST))
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. View Full-Text
Keywords: Land Surface Temperature (LST); satellite retrievals of LST; LST from GOES satellites Land Surface Temperature (LST); satellite retrievals of LST; LST from GOES satellites
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MDPI and ACS Style

Pinker, R.T.; Ma, Y.; Chen, W.; Hulley, G.; Borbas, E.; Islam, T.; Hain, C.; Cawse-Nicholson, K.; Hook, S.; Basara, J. Towards a Unified and Coherent Land Surface Temperature Earth System Data Record from Geostationary Satellites. Remote Sens. 2019, 11, 1399.

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