Hats: Field observations to obtain spatially filtered Turbulence fields from crosswind Arrays of sonic anemometers in the atmospheric surface layer

Abstract

The Horizontal Array Turbulence Study (HATS) field program utilized horizontal, crosswind arrays of sonic anemometers to calculate estimates of spatially filtered and subfilter-scale (SFS) turbulence, corresponding to its partitioning in large-eddy simulations (LESs) of atmospheric flows. Measurements were made over a wide range of atmospheric stability and for z/Δf nominally equal to 0.25, 0.5, 1.0, and 2.0, where z is height and Δf is the width of the spatial filter. This paper examines the viability of the crosswind array technique by analyzing uncertainties in the filtered turbulence fields. Aliasing in the crosswind direction, caused by the discrete spacing of the sonic anemometers, is found to be minimal except for the spatially filtered vertical velocity and for SFS second moments. In those cases, aliasing errors become significant when the sonic spacing is greater than the wavelength at the peak in the crosswind spectrum of vertical velocity. Aliasing errors are estimated to be of a similar magnitude for the crosswind gradients of filtered variables. Surrogate streamwise filtering is performed by assuming Taylor's hypothesis and using the mean wind speed U to interpret sonic time series as spatial data. The actual turbulence advection velocity Uc is estimated from the cross correlation between data from HATS sonics separated in the streamwise direction. These estimates suggest that, for near-neutral stratification, the ratio Uc/U depends on the turbulence variable and is typically between 1.0 and 1.2. Analysis of LES turbulence fields for a neutrally stratified boundary layer finds that the correlation between the true spatially filtered SFS stress component τ13 and the same variable obtained with surrogate streamwise filtering exceeds 0.98 for z/Δf > 0.25. Within the limits noted, it is concluded that the horizontal array technique is sufficient for the estimation of resolved and SFS turbulence variables. © 2004 American Meteorological Society.