A Critical Analysis of the Surface Renewal Method for Scalar Flux Estimation

Surface renewal is an inexpensive micrometeorological method to measure scalar fluxes, so it is employed as an alternative to the widely used eddy covariance technique. Despite its usefulness and the simplicity of its theory and field deployment, it has not been used extensively by the micrometeorological community, partially because refinements are needed to have an independent and more robust method. The surface renewal method takes advantage of a sawtooth-like patterns in high-frequency scalar traces, for example, temperature or water vapor. This pattern is created by the interaction of turbulent coherent structures with the surface or canopy (Paw U et al., 1992). To characterize the pattern, structure functions of different order are frequently used, allowing the estimate of geometrical attributes of the pattern (amplitude and repetition duration). In reality, the geometry of the pattern is close to a sawtooth-like shape but it is not always well-defined or clear. Moreover, at different heights inside a tall canopy, the pattern can display slightly different forms due to differential heating, cooling, or saturation rates, governed by thermodynamic, physiologic, or mechanical constraints. Our methodology, using synthetic data has shown discrepancies between the classic surface renewal method (Paw U et al., 1995; Snyder et al., 1996) and variations of it (Chen et al., 1997a, b). These differences arise primarily due to the different geometrical shapes of the pattern and the order of the structure functions used in each method. Here, we report preliminary results of a critical analysis of the surface renewal method basics and explore the consequences of varying pattern shapes and methodologies on estimating scalar fluxes. In addition, we show how a novel combination of structure functions of different orders is suitable for characterizing surface renewal patterns. We build on the analysis of synthetically constructed ramps by applying our results to experimental field data.