Multi-range fractional model for convective atmospheric surface-layer turbulence

TL;DR

This paper introduces a multi-range fractional model to better understand and simulate the complex turbulent spectrum in the atmospheric surface layer, validated with real observational data at high Reynolds numbers.

Contribution

The paper presents a novel multi-range fractional model that captures multiple self-similar ranges in turbulence spectra and updates existing theories with new quantifications.

Findings

Validated with observational data from Qingtu lake

Identified spectral exponents and transition scales for different variables

Proposed a new expression for vertical velocity variance

Abstract

We develop a multi-range fractional (MRF) model to capture the turbulent spectrum consisting of multiple self-similar ranges impacted by multiple effects. The MRF model is validated using long-term observational atmospheric surface layer data from Qingtu lake with extreme Reynolds numbers up to Re$_\tau\sim O(10^6)$. The spectral exponent in each range and the transition scales between different ranges are solo parameters in the MRF model and are identified for streamwise velocity, vertical velocity, and temperature, and they update the quantifications in the multi-point Monin-Obukhov theory. Therefore, based on the MRF model and considering the consistency between the turbulent spectrum and variance, we propose an expression for the vertical dependence of the streamwise velocity variance that is inadequately described by the Monin-Obukhov similarity theory. The MRF model provides a new method to analyze and quantify turbulent data, and as a time-series model, it enables the generation of synthetic turbulent data.