Improving Sea Ice Concentration Estimates by Blending Visible/Infrared and Passive Microwave Retrievals

Abstract:

This work aims to improve satellite-derived Sea Ice Concentration (SIC). We present a new, experimental product that provides SIC under all-weather conditions through an optimal blending of high spatial resolution Visible Infrared Imaging Radiometer Suite (VIIRS) ice concentration with ice concentration from the passive microwave Advanced Microwave Scanning Radiometer-2 (AMSR2).

Validation of VIIRS and passive microwave-derived SIC has been done using high-resolution Landsat data from the U.S. Geological Survey (USGS). Bias and root-mean-square errors of VIIRS and AMSR2 SIC are derived relative to SIC from Landsat with surface temperature below and above melting point using Ice Surface Temperature (IST) from VIIRS. After both VIIRS and AMSR2 images are remapped into a 1-km EASE grid, the validation statistics are applied to the Best Linear Unbiased Estimator (BLUE) to derive the final ice concentration under clear sky conditions.

It was found that the higher-resolution VIIRS data provides beneficial information to improve upon AMSR2 SIC under clear sky conditions. Furthermore, VIIRS SIC is particularly important during the summer melt season when AMSR2 SIC has a consistent negative bias in above melting point IST environments.