Articles | Volume 19, issue 8
https://doi.org/10.5194/tc-19-2913-2025
https://doi.org/10.5194/tc-19-2913-2025
Research article
 | 
06 Aug 2025
Research article |  | 06 Aug 2025

Evaluating sensitivity of optical snow grain size retrievals to radiative transfer models, shape parameters, and inversion techniques

James W. Dillon, Christopher P. Donahue, Evan N. Schehrer, and Kevin D. Hammonds

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Cited articles

Ackroyd, C., Donahue, C. P., Menounos, B., and Skiles, S. M.: Airborne lidar intensity correction for mapping snow cover extent and effective grain size in mountainous terrain, GISci Remote Sens., 61, 2427326, https://doi.org/10.1080/15481603.2024.2427326, 2024. 
Bair, E. H., Stillinger, T., and Dozier, J.: Snow Property Inversion from Remote Sensing (SPIReS): A generalized multispectral unmixing approach with examples from MODIS and Landsat 8 OLI, IEEE T. Geosci. Remote, 59, 7270–7284, 2020. 
Bohn, N., Painter, T. H., Thompson, D. R., Carmon, N., Susiluoto, J., Turmon, M. J., Helmlinger, M. C., Green, R. O., Cook, J. M., and Guanter, L.: Optimal estimation of snow and ice surface parameters from imaging spectroscopy measurements, Remote Sens. Environ., 264, 112613, https://doi.org/10.1016/j.rse.2021.112613, 2021. 
Clark, R. N. and Roush, T. L.: Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications, J. Geophys. Res.-Sol. Ea., 89, 6329–6340, 1984. 
Dang, C., Zender, C. S., and Flanner, M. G.: Intercomparison and improvement of two-stream shortwave radiative transfer schemes in Earth system models for a unified treatment of cryospheric surfaces, The Cryosphere, 13, 2325–2343, https://doi.org/10.5194/tc-13-2325-2019, 2019. 
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Short summary
The optical grain size of snow controls albedo, playing a key role in Earth's energy balance. This parameter varies substantially in time and space; thus, accurate estimates are vital. Reflectance measurements can be used to map grain size, although results differ considerably, depending on the algorithm and model used during retrieval. We perform a novel laboratory comparison to determine the optimal model, shape parameters, and retrieval algorithm for accurately estimating grain size.
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