Statistics of clustered vortices in the inverse energy cascade of two-dimensional turbulence

Abstract

Strong, long-lived vortices play a prominent role in two-dimensional (2D) turbulent flows, and understanding their statistics is key to unravelling 2D turbulence. Here it is shown that clustered same-sign vortices in forced 2D turbulence have a scale-invariant distribution of areas and are described by a mean-field theory. Larger clusters come apart more quickly, and the flow surrounding the remaining clusters becomes progressively more randomized and neutral, while vortex merger concentrates coherent enstrophy into a smaller and smaller fraction of the domain.