SolarSpecNet: Phase-Guided Structure–Intensity Modeling for Short-Term Solar Radiation Field Forecasting

Short-term solar-radiation forecasting is essential for photovoltaic integration, power scheduling, and environmental analysis. However, most current methods either focus on station-level time-series prediction or treat gridded radiation fields as generic image sequences. Consequently, they fail to explicitly model two tightly coupled aspects of future radiation-field evolution. 1) Where will regions of high and low radiation emerge? 2) How will the radiation intensity at each location change over time? To address this limitation, we propose SolarSpecNet, which explicitly disentangles these two aspects for specialized modeling while preserving their interaction through spectral-spatial fusion. Specifically, a Structural Evolution Branch exploits Fourier phase information to forecast the spatial evolution of radiation patterns, while a Radiative Energy Branch captures radiation-intensity dynamics from both spatial-domain field values and frequency-domain representations. Then, a Spectral-Spatial Fusion Module integrates these complementary predictions through spectral recombination and spatial refinement to produce the final radiation-field forecast. Experiments on gridded radiation fields show that SolarSpecNet consistently improves multi-step forecasting over representative statistical, recurrent, convolutional, spectral, and foundation time-series baselines. Additional visualizations show that its forecasts evolve smoothly, retain clear day–night boundaries, and preserve the main radiation patterns over time. Codes are attached.