Hybrid Spin-Orbit Tomography for Earth-like Planets: Simultaneous Mapping of Static Surfaces and Dynamic Clouds from Multicolor Light Curves

Photometric variability of directly imaged exoplanets encodes information on both persistent surface features and time-variable phenomena such as clouds. We present Hybrid Spin-Orbit Tomography, a method that simultaneously retrieves multiple static components and a single dynamic component, together with their reflection spectra, from multiband photometric variability. The method integrates spectral unmixing and dynamic spin-orbit tomography by introducing a time-dependent component into the forward model. We employ sparse regularization for static surface distributions, volume regularization for reflection spectra, and a Kronecker-sum kernel regularization for the dynamic component. Applying the method to a toy Earth model, we successfully recover static surface distributions together with a single time-dependent cloud component. Furthermore, we apply the method to DSCOVR/EPIC observations of Earth and retrieve a dynamic component consistent with real cloud distributions, together with components broadly interpretable as oceans, vegetation, and land surfaces. Relative to static spin-orbit unmixing, the hybrid model substantially reduces the residual scatter of the multiband light curves, demonstrating that explicit treatment of dynamic components improves global mapping from color variability. These results provide a step toward the simultaneous retrieval of static and dynamic planetary components, while highlighting the need for more physical cloud-surface masking models and uncertainty quantification.