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Bruno Bavassano is a solar wind researcher whose publications connect spacecraft observations with the statistical behavior of magnetohydrodynamic turbulence. A 2003 study with Roberto Bruno, Vincenzo Carbone and Luca Sorriso-Valvo compared velocity and magnetic field fluctuations between $0.3$ and $1$ astronomical unit from the Sun. It separated fast from slow solar wind, and changes in field magnitude from changes in field direction.^[ref]

The diagnostic was scale-dependent kurtosis. For a fluctuation $X$ with mean zero, $K=\mathbb{E}[X^4]/\mathbb{E}[X^2{]}^2$ weights rare large events strongly. A Gaussian distribution has $K=3$; a rising value as the separation shrinks indicates that small-scale changes are becoming more unevenly distributed. The study found stronger intermittency in compressive magnetic fluctuations than in the corresponding velocity fluctuations, and a radial increase in fast-wind intermittency.^[ref]

For intuition, replacing one ordinary increment by an increment ten times larger multiplies its contribution to the fourth moment by $10^4$, rather than $10^2$ for its squared contribution. This is why a sparse set of sharp changes can matter even when most samples look modest.

Luca Sorriso-Valvo is a physicist who studies turbulence in space plasmas, particularly the solar wind. His CNR institutional profile lists these specialties and publications connecting spacecraft observations to the statistical transfer of energy between scales.^[ref]

His 1999 first-authored paper examined the probability density functions of solar wind speed and magnetic field increments. Small-scale fluctuations departed strongly from a Gaussian distribution. The team fitted a model that mixes Gaussian distributions whose variances follow a log-normal distribution; a scale-dependent width then quantified how the distribution changed.^[ref]

The idea has a simple interpretation. Many quiet intervals mixed with occasional highly variable intervals can produce a distribution with more extreme events than one Gaussian predicts. A good fit does not uniquely prove the underlying mechanism, but following its parameter across scales makes intermittency quantitatively testable. Together with his later work on the energy cascade, this connects the visible irregularity of a time series to specific statistical questions about the flow.

By Luca Sorriso-Valvo, Raffaele Marino, Vincenzo Carbone, Fabio Lepreti, Pierluigi Veltri, Alain Noullez, Roberto Bruno, Bruno Bavassano, Ermanno Pietropaolo.

Physical Review Letters 99, 115001 (2007), DOI doi.org/10.1103/PhysRevLett.99.115001 . Primary byline as listed in the archive. Abstract and mixed third-order structure functions: Ulysses velocity/magnetic observations and evidence of a magnetohydrodynamic inertial energy cascade.