Identification and correction of systematic error in NOAA AVHRR long-term satellite data record

Abstract

Systematic error in long-term satellite data records resulting from inter-sensor differences or other persistent influences such as satellite orbital drift can greatly affect the use of these data to monitor land surface dynamics and trends. In this research an identification and correction procedure for systematic error is developed and used to evaluate the NOAA AVHRR long-term satellite data record produced by the Canada Center for Remote Sensing (CCRS). The record is composed of observations acquired by seven AVHRR sensors during the period 1985–2011. It includes two types of AVHRR sensor: AVHHR-2 flown onboard NOAA-9, -11, and ‐14, and AVHRR-3 onboard NOAA-16, -17, -18 and ‐19. Systematic error between sensors was identified through evaluation of synchronized nadir overpass (SNO) observations. The first order systematic error correction was derived from SNO comparison and then further optimized using a reference calibration target. Examination showed considerable difference between AVHRR-2 and AVHRR-3 measurements, which are largely attributed to differences in sensor design characteristics, uncertainty in sensor radiometric calibration, and imperfections in data processing. The results also show overall higher consistency between data from missions with AVHRR-3 than with AVHRR-2 sensors. The developed approach for correction of systematic error in time series was validated based on statistical analysis of eight independent pseudo-invariant targets not used for the initial correction development. Trends in these targets largely caused by the difference between AVHRR-2 and ‐3 sensors are shown to be removed or reduced after the correction was applied.