Retrieval of Sea Surface Skin Temperature from FY-3C/VIRR Data in the Arctic

Abstract

Arctic sea surface temperature is an important parameter for the research of climate change monitoring. Satellite remote sensing provides an important means of sea surface temperature (SST) observation, especially when there are few buoy and ship data in the Arctic. The Visible and Infrared Scanning Radiometer (VIRR) onboard the Fengyun-3C (FY-3C) can be used to observe SST. In this paper, intercalibration between VIRR and MODIS is performed to obtain corrected brightness temperature (BT) via double difference method, then Bayesian cloud detection and optimal estimation algorithms based on VIRR corrected BT are used to obtain Arctic VIRR SST. In this paper, only the data in March 2016 are processed, the bias of matchups between VIRR SST and AVHRR SST is -0.24°C, the standard deviation is 0.57°C, the robust standard deviation is 0.45°C. In the future, the data of long time series will then be processed for a complete assessment.