Direct Multispectral Satellite Nowcasting of Gridded Surface Solar Radiation

arXiv:2611.12999v1 Announce Type: new Abstract: Surface shortwave radiation (SWR) can change within minutes as clouds evolve, but operational forecasts often trade spatial detail and update frequency for forecast range. We present a numerical-weather-prediction-independent, observation-to-forecast framework that converts sequences of Himawari-8 Level-1 multispectral imagery and solar geometry directly into 24 gridded SWR fields at 10-min intervals for the next 4 h. A controlled six-model experiment separates the effects of satellite information from those of temporal self-attention. In the 0-1 h window, the full-multispectral attention model achieves a mean absolute error of 37.9 W/m2 and a root mean square error of 63.7 W/m2, reductions of 21.0% and 19.5% relative to a historical-SWR baseline. Improvements extend across nine subregions and include weaker spatial bias and better structural consistency. Temporal attention does not improve forecasts from historical SWR alone, but becomes effective when supplied with multispectral cloud and thermodynamic signals. Direct multispectral observations therefore provide the precursor information required for high-frequency, spatially resolved SWR nowcasting.