Simulation of Spectral Albedo and Bidirectional Reflectance over Snow-Covered Urban Canyon: Model Development and Factor Analysis

Author:

Chen Qi-Xiang1,Gao Zi-Yi1,Huang Chun-Lin1,Dong Shi-Kui1ORCID,Lin Kai-Feng2

Affiliation:

1. School of Energy Science and Engineering, Harbin Institute of Technology, No.92 Xidazhi Street, Harbin 150001, China

2. School of Chemistry and Chemical Engineering, Harbin Institute of Technology, No.92 Xidazhi Street, Harbin 150001, China

Abstract

A critical comprehension of the impact of snow cover on urban bidirectional reflectance is pivotal for precise assessments of energy budgets, radiative forcing, and urban climate change. This study develops a numerical model that employs the Monte Carlo ray-tracing technique and a snow anisotropic reflectance model (ART) to simulate spectral albedo and bidirectional reflectance, accounting for urban structure and snow anisotropy. Validation using three flat surfaces and MODIS data (snow-free, fresh snow, and melting snow scenarios) revealed minimal errors: the maximum domain-averaged BRDF bias was 0.01% for flat surfaces, and the overall model-MODIS deviation was less than 0.05. The model’s performance confirmed its accuracy in reproducing the reflectance spectrum. A thorough investigation of key factors affecting bidirectional reflectance in snow-covered urban canyons ensued, with snow coverage found to be the dominant influence. Urban coverage, building height, and soot pollutant concentration significantly impact visible and infrared reflectance, while snow grain size has the greatest effect on shortwave infrared. The bidirectional reflectance at backward scattering angles (0.5–0.6) at 645 nm is lower than forward scattering (around 0.8) in the principal plane as snow grain size increases. These findings contribute to a deeper understanding of snow-covered urban canyons’ reflectance characteristics and facilitate the quantification of radiation interactions, cloud-snow discrimination, and satellite-based retrieval of aerosol and snow parameters.

Funder

China Postdoctoral Science Foundation

Publisher

MDPI AG

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