A model for sensible heat flux probability density function for near-neutral and slightly-stable atmospheric flows

The probability density function for sensible heat flux was measured above a uniform dry lakebed (Owens lake) in Owens Valley, California. It was found that for moderately stable to near neutral atmospheric stability conditions, the probability density function exhibits well defined exponential tails. These exponential tails are consistent with many laboratory boundarylayer measurements and numerical simulations. A model for the sensible heat flux probability density function was developed and tested. A key assumption in the model derivation was the near Gaussian statistics of the vertical velocity and temperature fluctuations. This assumption was verified from time series measurements of temperature and vertical velocity. The parameters for the sensible heat flux probability density function model were also derived from mean meteorological and surface conditions using surface-layer similarity theory. It was found that the best agreement between modeled and measured sensible heat flux probability density function was at the tails. Finally, a relation between the intermittency parameter, the probability density function, and the mean meteorological conditions was derived. This relation rigorously links the intermittency parameter to mean meteorological conditions.