  3D convective cloud images form via two intertwined radiative diffusion
processes. Sunlight starts in the anti-solar direction and ends in
toward-sensor ones, but repeated forward-peaked scattering smears the
well-collimated beams across_direction_ space. This loss of directional memory
in the cloud's "outer shell" (OS) is modeled as a random walk (RW) on the
sphere. We show that, for typical cloud phase functions, 5 or 6 scatterings
suffice for severe degrading of directionality. Simultaneously, a RW unfolds
in_standard_ 3D space where steps are angularly-correlated, hence a drift in
the original direction and an associated lateral dispersion. Any distinctive
cloud image "feature" originates in the OS, and the shallower the better. That
is also why we previously found that the optical depth of the "veiled core"
(VC) is ~5. Significant amounts of sunlight thus arrive at the VC as a diffuse
irradiance, and leave it even more isotropic. The diffusion limit of 3D
radiative transfer (RT) is therefore valid inside the VC. Consequently, the
underlying RW in the VC unfolds in 3D space, now with isotropic steps since
extinction is scaled back to account for forward scattering. We show that the
VC optical thickness controls cloud-scale brightness contrast between the
illuminated and self-shaded sides of the cloud. Full cloud image formation thus
involves diffusions (i.e., RWs) in both Euclidian and spherical/direction
spaces. 3D cloud tomography based on MISR and MODIS multi-angle/-spectral data
is an emerging technique in passive VNIR-SWIR sensing that will make judicious
use this spatial separation of RT regimes to accelerate forward modeling
without significant loss in accuracy.
