Rethinking the atmospheric downward longwave radiation: A black-gray body model for accurate estimation

Abstract

Accurately estimating atmospheric downward longwave radiation is critical for applications ranging from radiative cooling to building energy efficiency. The main challenge lies in its spectral variability, which depends strongly on sky conditions such as humidity and cloud cover. In this study, we propose a Black–Gray body atmospheric radiation model that divides the infrared spectrum into three regions, treating the atmosphere as a graybody in the 8–13 μm and a blackbody outside this band. The model integrates locally measured radiative power to dynamically capture temporal and spatial variations. Validation experiments were conducted using radiative cooling processes in three Chinese cities (Hefei, Lhasa, and Haikou) under different climates and weather conditions. The BG model consistently predicted radiative cooling power with high accuracy, with mean absolute percentage errors generally below 10 %, outperforming both the effective sky emissivity method and MODTRAN-based predictions. Furthermore, we introduce the concept of band-resolved atmospheric energy databases, analogous to solar radiation databases, and demonstrate it with a full-year case study in Hefei. This work provides a new modeling framework that enhances precision and enables broader applications in energy systems, climate studies, and environmental design.