SNEEUW, SNEEUW, SNEEUW! Snow, nieve, what a beauty!

We’ve been enjoying abundant snowfall here in the Netherlands, which reminds me so much of my stunning Patagonia… ❄️

What I find ABSOLUTELY FASCINATING about this research study, is how the authors recover physical properties from spectral data.

Dillon, J. W., Donahue, C. P., Schehrer, E. N., & Hammonds, K. D. (2025). Evaluating sensitivity of optical snow grain size retrievals to radiative transfer models, shape parameters, and inversion techniques. The Cryosphere, 19(6), 2913–2933. https://lnkd.in/erez788Y

Snow has unique optical properties that make this possible, specifically, its reflectance and absorbance behaviors in different wavelengths.

Larger grains allow light to penetrate deeper, increasing absorption and reducing reflectance. Smaller grains scatter light more efficiently, leading to higher reflectance.

In this paper, the authors calculate the snow grain radius from HSI data.
How? They first use physical models like TARTES or SNICAR to generate simulated spectra based on various snow grain properties. These create vast libraries of theoretical reflectance curves. Then, they compare real HSI spectra (measured from actual snow samples in a lab) to these simulations, finding the best match via techniques like residual minimization.

They validate these recovered values against ground truth: Direct measurements from micro-computed tomography (micro-CT) scans of real snow samples in the lab. The results show impressive accuracy.

A BEAUTIFUL EXAMPLE of how HSI spectra can reveal the hidden physical properties of snow grains!

Why does this matter? The optical grain size of snow controls its ALBEDO, which in turn determines melting rates, climate dynamics, and water availability.