Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5015-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-5015-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Nov 2024
Research article |
| 06 Nov 2024
| 06 Nov 2024
Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements
Brenton A. Wilder
Department of Geosciences, Boise State University, Boise, ID, USA
Joachim Meyer
Department of Geosciences, Boise State University, Boise, ID, USA
Josh Enterkine
Department of Geosciences, Boise State University, Boise, ID, USA
Department of Geosciences, Boise State University, Boise, ID, USA
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Short summary
Remotely sensed properties of snow are dependent on accurate terrain information, which for a lot of the cryosphere and seasonal snow zones is often insufficient in accuracy. However, as we show in this paper, we can bypass this issue by optimally solving for the terrain by utilizing the raw radiance data returned to the sensor. This method performed well when compared to validation datasets and has the potential to be used across a variety of different snow climates.
Remotely sensed properties of snow are dependent on accurate terrain information, which for a...
