Shao (2026) Estimating snow albedo from satellite

Identification

• Journal: Elsevier eBooks
• Year: 2026
• Date: 2026-01-01
• Authors: Donghang Shao
• DOI: 10.1016/b978-0-323-85242-5.00082-8

Research Groups

Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences

Short Summary

This chapter provides a concise overview of fundamental methods for estimating snow albedo, detailing remote sensing retrieval, forward simulation, and land surface model schemes, along with their respective advantages and disadvantages.

Objective

• To describe and compare the basic methods for obtaining snow albedo, specifically focusing on remote sensing retrieval, forward simulation, and snow albedo estimation schemes within land surface process models.

Study Configuration

• Spatial Scale: Global to regional (methods are applicable across various scales for snow cover monitoring).
• Temporal Scale: Continuous time series (methods aim to provide this, with varying capabilities regarding data gaps).

Methodology and Data

• Models used: Remote sensing retrieval algorithms (e.g., look-up table, BRDF model-based, Lambert Assumption-based, GLASS albedo), forward radiative transfer models, and snow albedo estimation schemes integrated into land surface process models.
• Data sources: Satellite remote sensing data, ground-level meteorological observations, and snow physical properties.

Main Results

• Remote sensing retrieval methods offer large-scale, real-time snow albedo products independent of meteorological observations, but are susceptible to cloud cover data gaps.
• Forward simulation methods provide continuous time series by modeling radiative transfer based on ground-level meteorological conditions and snow properties, and can be integrated with land surface models.
• The chapter systematically outlines the principles, advantages, and disadvantages of both remote sensing and forward simulation approaches for snow albedo estimation.

Contributions

• Provides a comprehensive synthesis and comparison of the primary methods for snow albedo estimation, including remote sensing retrieval, forward simulation, and land surface model schemes.
• Highlights the strengths and limitations of each method, offering guidance for their application in cryospheric and climate studies.
• Serves as a foundational reference for understanding snow albedo acquisition techniques and their implications for climate and hydrological modeling.

Funding

Not specified in the provided text.

Citation

@article{Shao2026Estimating,
  author = {Shao, Donghang},
  title = {Estimating snow albedo from satellite},
  journal = {Elsevier eBooks},
  year = {2026},
  doi = {10.1016/b978-0-323-85242-5.00082-8},
  url = {https://doi.org/10.1016/b978-0-323-85242-5.00082-8}
}