Development of Seasonal BRDF Models to Extend the Use of Deep Convective Clouds as Invariant Targets for Satellite SWIR-Band Calibration

Abstract

Tropical deep convective clouds (DCC) are an excellent invariant target for vicarious calibration of satellite visible (VIS) and near-infrared (NIR) solar bands. The DCC technique (DCCT) is a statistical approach that collectively analyzes all identified DCC pixels on a monthly basis. The DCC reflectance in VIS and NIR spectrums is mainly a function of cloud optical depth, and provides a stable monthly statistical mode. However, for absorption shortwave infrared (SWIR) bands, the monthly DCC response is found to exhibit large seasonal cycles that make the implementation of the DCCT more challenging at these wavelengths. The seasonality assumption was tested using the SNPP-VIIRS SWIR bands, with up to 50% of the monthly DCC response temporal variation removed through deseasonalization. In this article, a monthly DCC bidirectional reflectance distribution function (BRDF) approach is proposed, which is found to be comparable to or can outperform the effects of deseasonalization alone. To demonstrate that the SNPP-VIIRS DCC BRDF can be applied to other JPSS VIIRS imagers in the same 13:30 sun-synchronous orbit, the VIIRS DCC BRDF was applied to Aqua-MODIS. The Aqua-MODIS SWIR band DCC reflectance natural variability is reduced by up to 45% after applying the VIIRS-based monthly DCC BRDFs.