Passive radiative cooling spontaneously emits thermal radiation into the cold universe, providing an environment-friendly solution for cooling. Unlike the mature methods for annual performance evaluation of solar energy harvesting, appropriate long-term radiative cooling performance simulation methods that can be used across different cities in the world are still missing. The main reason is that the spectral distribution of atmospheric radiation varies sensitively with sky status (e.g., cloudy, humid, etc.), while the normalized solar radiation spectrum is relatively stable regardless of weather conditions. Currently reported atmospheric radiation models in radiative cooling field, including the effective sky emissivity model and Modtran model, cannot simultaneously meet the spectral, spatial, and temporal requirements. Herein, we propose an accurate long-term radiative cooling simulation method by developing a novel black-gray (BG) body atmospheric radiation model based on the atmospheric spectral properties and the measured atmospheric radiative power. Experimental validation has been performed in cities with different climate styles and results show superior accuracy than reported methods. The proposed radiative cooling simulation method is well-suited for diverse environmental conditions, encompassing different weather conditions, climate styles, and seasons. It is also applicable for both spectral broadband and selective coolers, particularly for recently proposed selective coolers. To further apply the proposed method, we propose a concept of atmospheric spectral energy databases for the first time and provide a demo case study in Hefei, China, which aims to guide the accurate long-term radiative cooling simulation analysis.