Abstract
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.
Highlights
Introduction and motivationNumerical weather prediction (NWP) modeling is a maturing technology for the monitoring and prediction of weather and climate conditions on a wide continuum of timescales (e.g., Kalnay, 2003)
As discussed in the rest of this study, with these features, Simulated Weather Imagery (SWIm) occupies a niche for the versatile visualization and validation of NWP analyses and forecasts as well as for the assimilation of color-imagery observations aimed at improved NWP initialization and nowcasting applications
The SWIm package has run on a variety of NWP modeling systems including the Local Analysis and Prediction System (LAPS; Toth et al, 2014), Weather Research and Forecasting Model (WRF), Regional Atmospheric Modeling System (RAMS), High Resolution Rapid Refresh (HRRR) (Benjamin et al, 2016), and NAVGEM
Summary
Numerical weather prediction (NWP) modeling is a maturing technology for the monitoring and prediction of weather and climate conditions on a wide continuum of timescales (e.g., Kalnay, 2003). High-resolution color imagery provides a unique window into fine-scale land surface, aerosol, and cloud processes that are critical for both the monitoring and nowcasting of convective and other severe weather events as well as for the assessment and refinement of modeled energy balance relationships that are crucial for climate forecasting. Utilizing an adjoint or ensemble-based inverse of the forward operator or another minimization procedure, the first-guess forecast variables are adjusted to minimize the difference between the simulated and real observations. In case of visible light measurements, observations can be considered to be in the form of color (or multispectral visible) imagery Beyond their expanding use in DA applications, the simulation of color imagery from model variables via forward operators has another important purpose: the visualization of 4D NWP analysis and forecast fields.
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