Characterization of variability at in situ locations for calibration/validation of satellite-derived land surface temperature data

Abstract

Calibration and validation (cal/val) of data derived from satellite-based instruments is critical to providing accurate global measurements of environmental variables at useful spatial and temporal resolutions. In this letter, statistical models based on linear regressions employing various predictor variables were utilized to elucidate appropriate methods of characterizing variability near ground sites that might be used for calibration and validation. Regressions based on more complex statistics performed no better than those based on easily derived statistics, and the regression relations provided valuable information for assessing the potential quality of satellite-based measures of land surface temperature.

Acknowledgements

This study was partially supported by the NOAA GOES-R Program.