Inversion of Sea Ice Spectral Albedo to Estimate Under-Ice Transmittance

TL;DR

This paper presents a novel spectral albedo inversion method based on Monte-Carlo simulations to accurately estimate under-ice transmittance without relying on snow depth data, improving remote sensing of under-ice radiation.

Contribution

The paper introduces a new inversion technique using spectral albedo to estimate under-ice transmittance, overcoming limitations of current methods that depend on snow depth products.

Findings

Spectral albedo inversion provides more precise transmittance estimates than existing methods.

The approach implicitly accounts for variability in snow scattering properties.

Method enhances satellite-based assessment of under-ice photosynthetically available radiation.

Abstract

Sunlight radiation under snow-covered sea ice obtained from remote sensing could help assess under-ice primary production at pan-Arctic scale. Yet, the current remote sensing methods to estimate sunlight transmittance under sea ice is limited by its reliance on imprecise snow depth products and its inability to sense microstructure-driven variations in snow and ice light scattering properties. Based on Monte-Carlo simulations of radiative transfer, we developed an inversion method relying solely on spectral albedo to estimate transmittance under snow-covered sea ice. The method analyses albedo spectral information to derive the vertically resolved scattering properties of snow and sea ice above the freeboard. Assuming fixed columnar ice physical and optical properties, transmittance is then estimated. At ground level, our spectral albedo inversion method is more precise than the current approaches. We argue this is because it implicitly accounts for the variability in snow scattering properties. This method could significantly improve the satellite estimation of photosynthetically available radiation under sea ice, especially because it does not need snow depth.