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Remote Sensing
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30 November 2025

Improvement of Snow Albedo Simulation Considering Water Content

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State Key Laboratory of Climate System Prediction and Risk Management (CPRM), School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Remote Sens.2025, 17(23), 3899;https://doi.org/10.3390/rs17233899 
(registering DOI)
This article belongs to the Special Issue Remote Sensing Modelling and Measuring Snow Cover and Snow Albedo

Abstract

By combining the Maxwell–Garnett mixing rule, Mie scattering, and the four-stream discrete ordinates adding method, a snow albedo model with explicit consideration of water content was constructed, and the influence of snow water content on snow albedo simulation was systematically analyzed. The results indicate that liquid water content is the key factor contributing to significant changes in albedo in the near-infrared band. The albedo of snow with small particle sizes is more sensitive to water content. The water content in the surface layer of snow has a more pronounced effect on reducing albedo. The actual measurement cases at the stations on the Tibetan Plateau, Xinjiang, and Northeast China show that the model established here provides a good simulation of albedo accuracy, with a bias of −0.0069 and a Root Mean Square Error (RMSE) of 0.0583 compared to the observations. This indicates that the model has a strong ability to express physical mechanisms and performs stably in complex environments, thereby demonstrating good regional applicability. This model can also be applied to wet snow containing impurities in the future.

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