next-order generalization of the power spectrum [e.g., @Priestley1981 Section 11.5.1]. Just as the power spectrum describes the variance as a function of scale, the bispectrum describes the skewness as a function of two coupling scales [e.g., @Watkinson2017]. Measuring the bispectrum of supergranular divergence maps would therefore be useful to characterize the skewness as a function of scale. Furthermore, the bispectrum is directly related to hexagonal patterns because a hexagon has a specific signature in the bispectrum. The bispectrum characterizes the coupling of two wave vectors to a third wave vector, which appears similarly in the nonlinearities in the Navier-Stokes equations. Such nonlinearities are present in the modal equations of convection studied using horizontal patterns [e.g., @Chandrasekhar1961; @Gough1975; @Busse2007].

To clarify the results obtained in this paper, it is necessary to clarify what we mean by linear and nonlinear. By linear, we mean the hypothesis that the time-evolution of supergranular divergence maps was given by a linear partial differential equation (PDE) and a stochastic forcing term with independent Gaussian Fourier components. In this case, the dynamics at the Fourier components of the solution would also be independent. By nonlinear, we mean the hypothesis that the dynamics of supergranular divergence maps was 