Using MODIS to Estimate Cloud Contamination of the AVHRR Data Record

Abstract

A study of the improvement in cloud-masking capability of data from a Moderate Resolution Imaging Spectroradiometer (MODIS) relative to data from an Advanced Very High Resolution Radiometer (AVHRR) is performed. MODIS offers significant advances over AVHRR in spatial resolution and spectral information. Three MODIS scenes that present a range of cloudiness, surface type, and illumination conditions are analyzed. AVHRR local area coverage (LAC) and global area coverage (GAC) data were synthesized from the most spectrally comparable MODIS channels. This study explores the benefits to cloud masking offered by MODIS beyond that offered by AVHRR. No global generalization can be inferred from this limited analysis, but this study does attempt to quantify the added benefit of MODIS over AVHRR for three scenes. The sole focus is on the levels of cloud contamination in clear AVHRR pixels; the misclassification of clear pixels as cloudy is not addressed. For the scenes studied, the results of the additional MODIS tests revealed measurable residual cloud contamination in both AVHRR LAC and GAC clear pixels. From this analysis, the contamination of the clear pixels in AVHRR LAC data was between 1% and 3% for the cases studied. The levels of contamination of the clear GAC pixels revealed by MODIS cloud tests ranged from 2% to 4%. MODIS was able to reveal roughly 2% more cloud contamination of clear GAC pixels than was revealed by LAC. This result indicates that the increase in spatial resolution offered by MODIS may be as significant to reducing cloud contamination as is the increase in spectral information. Inclusion of the results of AVHRR spatial uniformity tests applied to MODIS or LAC pixels revealed potentially much more cloud contamination of clear GAC pixels. The larger values of potential cloud contamination revealed by spatial uniformity tests were not apparent in the clear-sky products. An analysis of the derived SST, land surface temperature (LST), and normalized difference vegetation index (NDVI) fields was conducted to explore the impact of the MODIS-inferred cloud contamination on these products. The results indicated minimal effects on the distribution of SST, LST, and NDVI derived from AVHRR LAC data. Errors in the GAC SST and LST had standard deviations of 0.1 and 0.3 K, respectively. The GAC NDVI error distribution has a standard deviation of 0.03 for all scenes. The GAC error distributions showed little bias, indicating that cloud-masking differences between the AVHRR and MODIS should not introduce a discontinuity in the AVHRR/MODIS/Visible Infrared Imaging Radiometer Suite (VIIRS) SST and NDVI data records.