On the performance of surface renewal analysis to estimate sensible heat flux over two growing rice fields under the influence of regional advection

High-frequency temperature data were recorded at one height and they were used in Surface Renewal (SR) analysis to estimate sensible heat flux during the full growing season of two rice fields located north–northeast of Colusa, CA (in the Sacramento Valley). One of the fields was seeded into a flooded paddy and the other was drill seeded before flooding. To minimize fetch requirements, the measurement height was selected to be close to the maximum expected canopy height. The roughness sub-layer depth was estimated to discriminate if the temperature data came from the inertial or roughness sub-layer. The equation to estimate the roughness sub-layer depth was derived by combining simple mixing-length theory, mixing-layer analogy, equations to account for stable atmospheric surface layer conditions, and semi-empirical canopy–architecture relationships. The potential for SR analysis as a method that operates in the full surface boundary layer was tested using data collected over growing vegetation at a site influenced by regional advection of sensible heat flux. The inputs used to estimate the sensible heat fluxes included air temperature sampled at 10 Hz, the mean and variance of the horizontal wind speed, the canopy height, and the plant area index for a given intermediate height of the canopy. Regardless of the stability conditions and measurement height above the canopy, sensible heat flux estimates using SR analysis gave results that were similar to those measured with the eddy covariance method. Under unstable cases, it was shown that the performance was sensitive to estimation of the roughness sub-layer depth. However, an expression was provided to select the crucial scale required for its estimation.