[^1]. The main result of this paper demonstrated that in the former case the scale of sparseness is not only actualized well beyond the guaranteed *a priori* bound [@BrFaGr18], but also just beyond the critical bound [@BrFaGr18] sufficient for the diffusion to fully engage (overpowering the nonlinearity) and prevent the further growth of the vorticity magnitude. This result provides numerical confirmation that the aforementioned mathematical framework is capable of accurately detecting the onset of turbulent dissipation, and furnishes a necessary validation of the current theoretical efforts in closing the scaling gap in the NS regularity problem within the framework. In addition, we provide arguments that shed new light on some of the classical work in the computational simulations of *intermittent events* in turbulence. More specifically, based on the theory presented in [@BrFaGr18] we provide–for the first time–a rigorous explanation for the eventual ‘slumps’ in the ‘bursts’ of the vorticity magnitude observed in computational modeling of the Kida vortex-initialized flows [@KM86; @KM87; @BP94].

In the second scenario, we analyze data sampled from the forced isotropic turbulence simulation publicly available from the Johns Hopkins Turbulence Data Base (JHTDB). This data set had previously only been analyzed for spectral scales, and this work 