Sea ice concentration estimates from ICESat-2 linear ice fraction-Part 2: Gridded data comparison and bias estimation

Abstract

Sea ice coverage is a key indicator of changes in the global climate. Estimates of sea ice area and extent are primarily derived from satellite measurements of surface microwave emissions, from which local sea ice concentration (SIC) is derived. Passive microwave (PM) satellite sensors remain the sole global product for understanding SIC variability but may be sensitive to consistent biases. In Part I we explored these in a multi-sensor intercomparison of optical, passive microwave, and lidar data, showing that a new SIC product, the linear ice fraction (LIF), derived from ICESat-2 (IS2) laser altimetry, could be used to quantify and understand PM SIC biases. Here in Part II, we develop and assess the reliability of larger-scale estimates of SIC from IS2 LIF. We develop an LIF emulator that samples optical imagery using the distribution of possible orientation angles for IS2 to understand the limitations of this one-dimensional product. We find that the error qualities of the LIF product are improved when combining multiple IS2 tracks and discuss intrinsic but correctable biases that emerge in the combination of multiple IS2 measurements. We use these to develop a monthly LIF product, covering up to 46 % of the Arctic sea ice cover, which has similar or better error qualities compared to PM data, subject to uncertainties in surface-Type classification associated with surface melting and differences between IS2's weak and strong beams. We then discuss pathways to improving LIF and enhancing PM-SIC data in the future.