Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2601.07672

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

Christophe Perron·Bastian Raulier·Philippe Massicotte·Martin Vancoppenolle·Marcel Babin
View original source ↗Read source document ↗Export metadata ↓

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.

Explore related subjects

physics.ao-phphysics.optics

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Christophe Perron, Bastian Raulier, Philippe Massicotte, Martin Vancoppenolle, Marcel Babin. 2026-01-12. Inversion of Sea Ice Spectral Albedo to Estimate Under-Ice Transmittance. https://arxiv.org/abs/2601.07672

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Conservation Constraints and Distributed Advective Memory in a Reduced Model of Atlantic Overturning Hysteresis

Interbasin exchange through the Indo-Pacific gateway supplies salt to the Atlantic and is widely invoked as a control on the stability of the Atlantic overturning circulation. We ask whether that control can act on the equilibrium structure of a conceptual thermohaline model. A closed five-box model with an exact salt invariant is constructed, comprising North Atlantic, upper-limb, Indian, Pacific, and deep reservoirs, with the return flow split between a warm route through the Indian reservoir and a cold route, together with an Indonesian Throughflow branch and an Agulhas retroflection. Adding the steady-state budgets of the gateway reservoirs shows that every internal exchange cancels, so the salt they export to the Atlantic is fixed by the net Atlantic freshwater export alone. This holds independently of the warm-route fraction, the throughflow, the retroflection, and how the export is apportioned among gateway reservoirs; across a parameter sweep the largest departure is of order ten to the minus eleven. The gateway therefore enters as a purely additive forcing and cannot renormalize the salt-advection feedback. Replacing the discrete transit lag by a gamma memory kernel leaves the equilibria unchanged but yields a closed-form threshold for oscillatory instability depending only on kernel shape. Broad memory is strongly stabilizing, and a discrete lag is the least stable member of the family. Because the instantaneous feedback vanishes at the fold, oscillatory instability always precedes the saddle-node, over an interval widening more than tenfold as memory sharpens. Gateways therefore appear to act on transient rather than equilibrium dynamics

physics.ao-ph↗
arXiv2026

Forecasting threshold exceedance of atmospheric variables at a specific location

Accurate short-term forecasting of extreme weather events is important for early warning and risk mitigation. We compare two approaches for predicting site-specific threshold exceedances of weather variables: direct binary probabilistic models trained on thresholded outcomes and full-distribution parametric models trained on the continuous target. Using an analytically tractable Gaussian random-location model, in which the distribution is predictably shifted by the covariates, we quantify the consequences of the information loss induced by thresholding and derive the rare-event behavior of prediction errors and forecast skill. The analysis predicts an increasing relative advantage of the full-distribution approach as event probability decreases, because binarization progressively discards information contained in the continuous response. We then compare the two approaches to forecast wind speed and accumulated rainfall at various weather station sites over southeastern France using the same hybrid neural-network architecture. Although wind speed and rainfall depart from the toy-model assumptions, its main qualitative predictions are recovered for both variables: the relative advantage of distributional modeling increases toward rarer thresholds. This agreement further suggests that a substantial fraction of the forecastable signal associated with extreme events arises from predictable shifts in the conditional distribution. For the reasonably suitable parametric families examined, the results show limited sensitivity to the selected class of distribution. Overall, the results highlight the statistical advantage of training on continuous observations rather than on thresholded binary outcomes when forecasting rare threshold exceedances.

physics.ao-ph↗
arXiv2026

Blinded Evaluation of Oceanic Sound Source Locations via Sequential Bound Estimation

A non-linear, non-Bayesian method called sequential bound estimation (SBE) derived 100% confidence intervals of location (CIL) for 219 explosions in the ocean from measurements of their time differences of arrivals among five widely-spaced time-unsynchronized receivers on the ocean bottom. The explosion's locations were measured with the global positioning system. A blind evaluation revealed all 219 explosions were within their CIL. The probability this could happen by chance is $4 \times 10^{-116}$. The explosions were detonated in shallow water on the eastern continental shelf of the U.S. over the so-called New England Mud Patch.

physics.ao-ph↗