reported a skewness of 0.42 for TD maps. As we see in Section \[secresults\], different filters applied in the spatial domain may result in different values for the skewness.

The fact that the divergence maps have a nonzero skewness suggests that different Fourier components of the divergence field cannot be independent. If they were independent, the data would have zero skewness, just like a random wave field. As the statistical properties of the supergranular divergence field are translation invariant, it is clear that two Fourier components are uncorrelated. As we see in Section \[secBispectrumIntro\], the nonzero skewness of the data can be related to nonzero correlations between three Fourier components, which leads to the definition of the bispectrum. As such correlations between three Fourier components are also present in simple patterns of convection, we now look at these patterns before introducing the bispectrum.

A brief account of convection patterns {#secPatternsIntro}
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We briefly discuss a few patterns used in analytical studies of convection. [[Related to the specific case of solar supergranulation]{}]{}, @Busse2003 [@Busse2004; @Busse2007] studied hexagonal convection cells. This work is based on earlier and more general studies of Boussinesq convection that used convection patterns such as rolls, squares, and 