Inverse Parameter Estimation of the Turbulent Surface Layer from Single-Level Data and Surface Temperature

Abstract

Abstract A simple inverse parameter estimation method is used in a practical diagnostic approach to obtain the surface roughness lengths and surface resistance parameters from a chi-square cost function containing measurements of wind speed and air surface temperature differences in the atmospheric surface layer. The estimated parameters allow the calculation of the turbulent fluxes of momentum and heat and the surface-layer profiles of wind speed temperature and humidity from single-level data of wind speed and variance, air temperature and humidity, surface temperature, and total heat flux (sum of sensible and latent fluxes, estimated as net radiation minus soil heat flux). The procedure, which is potentially applicable when fast response data are not available without the necessity of external parameters (with the exception of the displacement height), is tested over a field dataset in southern Italy.