Abstract. Solar radiation is the ultimate source of energy flowing through the
atmosphere; it fuels all atmospheric motions. The visible-wavelength range of
solar radiation represents a significant contribution to the earth's energy
budget, and visible light is a vital indicator for the composition and
thermodynamic processes of the atmosphere from the smallest weather scales to the
largest climate scales. The accurate and fast description of light
propagation in the atmosphere and its lower-boundary environment is
therefore of critical importance for the simulation and prediction of
weather and climate. Simulated Weather Imagery (SWIm) is a new, fast, and physically based visible-wavelength three-dimensional radiative transfer model. Given the location and
intensity of the sources of light (natural or artificial) and the
composition (e.g., clear or turbid air with aerosols, liquid or ice clouds, precipitating rain, snow, and ice hydrometeors) of the atmosphere, it
describes the propagation of light and produces visually and physically
realistic hemispheric or 360∘ spherical panoramic color images of
the atmosphere and the underlying terrain from any specified vantage point
either on or above the earth's surface. Applications of SWIm include the visualization of atmospheric and land
surface conditions simulated or forecast by numerical weather or climate
analysis and prediction systems for either scientific or lay audiences.
Simulated SWIm imagery can also be generated for and compared with observed
camera images to (i) assess the fidelity and (ii) improve the performance
of numerical atmospheric and land surface models. Through the use
of the latter in a data assimilation scheme, it can also (iii) improve the estimate of
the state of atmospheric and land surface initial conditions for situational
awareness and numerical weather prediction forecast initialization purposes.
Production of solar radiation bankable datasets from high-resolution solar irradiance derived with dynamical downscaling Numerical Weather prediction model
