This paper presents a series of validated models for predicting solar radiation components needed for energy system modeling and building design. The models calculate global, direct, and diffuse daylight illuminance, diffuse irradiance, and sky luminance. They are based on hourly or higher frequency direct and global irradiance data, along with surface dew point temperature. The models are "all-weather" short-time-step conversion algorithms with a common structure and input data. They are validated using both hourly and 15-minute data. The models are used to bridge the gap between available solar radiation data and specific user needs. They are applied in various fields, including climatological data preparation and system simulation program modifications. The models are based on three years of experimental data from 10 American and three European sites. The models are validated against data from multiple locations and show high accuracy, with root-mean-square and mean bias errors of less than 3% and 1%, respectively. The models are recommended for use in solar energy and daylighting applications. The paper also discusses the validation of the models and their performance in different climatic conditions. The models are considered a major contribution to solar energy research.This paper presents a series of validated models for predicting solar radiation components needed for energy system modeling and building design. The models calculate global, direct, and diffuse daylight illuminance, diffuse irradiance, and sky luminance. They are based on hourly or higher frequency direct and global irradiance data, along with surface dew point temperature. The models are "all-weather" short-time-step conversion algorithms with a common structure and input data. They are validated using both hourly and 15-minute data. The models are used to bridge the gap between available solar radiation data and specific user needs. They are applied in various fields, including climatological data preparation and system simulation program modifications. The models are based on three years of experimental data from 10 American and three European sites. The models are validated against data from multiple locations and show high accuracy, with root-mean-square and mean bias errors of less than 3% and 1%, respectively. The models are recommended for use in solar energy and daylighting applications. The paper also discusses the validation of the models and their performance in different climatic conditions. The models are considered a major contribution to solar energy research.