  Serial multiscale methods are not effective when the different scales are strongly coupled together. When the different scales interact strongly to produce the observed behavior, what is required is an approach that simulates each region simultaneously. This is called parallel multiscale modeling. Parallel multiscale modeling is the foundation of a nearly ubiquitous simulation method: so called “sub-grid” modeling. Sub-grid modeling refers to the representation of important small-scale physical processes that occur at length-scales that cannot be adequately resolved on the grid size of a particular simulation. (Remember that many simulations discretize continuous equations, so they have a relatively arbitrary finite “grid size.”) In the study of turbulence in fluids, for example, a common practical strategy for calculation is to account for the missing small-scale vortices (or eddies) that fall inside the grid cells. This is done by adding to the large-scale motion an eddy viscosity that characterizes the transport and dissipation of energy in the smaller-scale flow—or any such feature that occurs at too small a scale to be captured by the grid.