Quantifying the Influence of Random Errors in Turbulence Measurements on Scalar Similarity in the Atmospheric Surface Layer

Abstract

The influence of random errors in turbulence measurements on scalar similarity for temperature, water vapour, CO 2 , and NH 3 is investigated using two eddy-covariance datasets collected over a lake and a cattle feedlot. Three measures of scalar similarity, namely, the similarity constant in the flux-variance relationship, the correlation coefficient between two scalars and the relative transport efficiency, are examined. The uncertainty in the similarity constant C s in the flux-variance relationship resulting from random errors in turbulence measurements is quantified based on error propagation analyses and a Monte-Carlo sampling method, which yields a distribution instead of a single value for C s . For different scalars, the distributions of C s are found to significantly overlap, implying that scalars are transported similarly under strongly unstable conditions. The random errors in the correlation coefficients between scalars and the relative transport efficiencies are also quantified through error propagation analyses, and they increase as the atmosphere departs from neutral conditions. Furthermore, the correlation coefficients between three scalars (water vapour, CO 2 , and NH 3 ) are statistically different from unity while the relative transport efficiencies are not, which highlights the difference between these two measures of scalar similarity. The results suggest that uncertainties in these measures of scalar similarity need to be quantified when using them to diagnose the existence of dissimilarity among different scalars.

The k−1 scaling of air temperature spectra in atmospheric surface layer flows

“…In addition, the turbulence intensity has to be smaller than 0.5 to justify the use of Taylor's hypothesis (Stull, ) when inferring wavenumbers from time. In addition, similar to Sun et al (), highly non‐stationary segments were excluded using the quality control described by Foken and Wichura ().…”

Caracterização observacional da turbulência na superfície da Região Metropolitana de São Paulo

“…Este procedimento depende muito da incerteza conceitual (definição, método de estimativa etc.) e observacional de d (Toda & Sugita, 2003;Zilitinkevich et al, 2008) e L (Sun et al, 2015). Utilizando constantes típicas encontradas em estudos rurais, Toda e Usualmente, esta decomposição é feita através da técnica da Transformada Rápida de Fourier (FFT) (e.g., Kaimal et al, 1972;Verma & Anderson, 1984;Oikawa & Meng, 1995;Feigenwinter et al, 1999;Larsén et al, 2021) (Figura 1.2a).…”

“…(2.24) possa ser significativo(Zilitinkevich et al, 2008), não é claro como ele pode ser estimado para cada bloco de 30 min. Assumindo que cov(d, L) ≈ 0(Saleski & Chamecki, 2012;Sun et al, 2015), a incerteza de 𝜙 pode ser reescrita como…”