Frontiers in Remote Sensing (Apr 2022)
Toward a Reliable Correction of NOAA AVHRR Orbital Drift
Abstract
The NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High-Resolution Radiometer) orbital drift prevents the use of its derived land surface temperature (LST) data for global studies of temperature trends, especially for the 80s and 90s over land. In a previous study, we showed how orbital drift correction methods could be validated by simulating a reference and drifted time series from alternative MSG (Meteosat Second Generation) SEVIRI (Spinning Enhanced Visible and InfraRed Imager) data, thanks to their high (15 min) temporal resolution. In this study, we show how these alternative data allow identifying orbital drift effects on different land covers, and how these effects could be mitigated with novel approaches. We also identify two key statistical parameters to assess orbital drift correction performance: the bias between corrected and drifted time series and the trend of their difference. We present two methods and compare their results with an alternative orbital drift correction, validated against in situ data by their authors. Considering an ideal case where the whole influence of the orbital drift is known, our novel approach allows for an almost complete removal of the orbital drift effect (zero bias and 0.05 K/yr difference trend). However, in real cases, when we have only access to the drifted time series, our approach’s performance decreases slightly, mainly through a larger spread of the retrieved statistics. As for the alternative correction method, its performance is poorer, even if it actually succeeds in removing part of the observed orbital drift. These results, as well as the new insights we provide on the orbital drift effect on LST, pave the way toward a reliable correction of NOAA AVHRR orbital drift. We therefore recommend the use of simulated LST time series such as the ones used in this study for the validation of orbital drift correction methods.
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