Authors: Juan Carlos Palacios (Florida Institute of Technology), Sofiane Bourouaine (Johns Hopkins University), Jean Carlos Perez (Florida Institute of Technology)

In this work we investigate the dependency with scale of the empirical probability distribution functions (PDFs) of Elsasser increments using large sets of WIND data (collected between 1995 and 2017) near 1 au. The empirical PDFs are compared to the ones obtained from the high-resolution numerical simulations of steadily driven, homogeneous Reduced MHD turbulence on a 2048^3 rectangular mesh. A large statistical sample of Alfvenic increments is obtained by using conditional analysis based on the solar wind average properties. The PDF tails obtained from observations and numerical simulations are found to have exponential behavior in the inertial range, with a decrement that satisfies power-laws with exponents around 0.2 for observations and 0.4 for simulations. PDF tails were extrapolated assuming their exponential behavior extends to arbitrarily large increments in order to determine structure function scaling laws at very high orders. Our results points to potentially universal scaling laws governing the PDF of Elsasser increments and to an alternative methodology to investigate high-order statistics in solar wind observations.