22 Feb 2023
 | 22 Feb 2023
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Large–Eddy Simulation of Turbulent Flux Patterns over Oasis Surface

Bangjun Cao, Yaping Shao, Xianyu Yang, Xin Yin, and Shaofeng Liu

Abstract. Large-eddy simulation (LES) is widely used for studying surface fluxes over heterogeneous areas, but the parameterizations based on the Monin-Obukhov Similarity Theory (MOST) often used violate the basic assumptions of the very theory and generate inconsistencies with the LES model closures. Experience shows that LES simulated surface fluxes are strongly dependent on model resolution. Here, we propose a novel scheme for turbulent flux estimates in LES models, which computes the fluxes locally using the LES sub-grid closure scheme (here a k-l scheme) and constrained on the macroscopic scale using the MOST. In comparison with several other schemes, the new scheme performs better for various types of land surfaces tested. The surface fluxes estimated with the new scheme are compared with the field measurements over an oasis surface at different height levels. Other quantities related to surface energy balance, including net radiation, ground heat flux and surface skin temperature, simulated using the new scheme are also found to be consistent with the measurements. Sensitivity tests show that the uncertainty of MOST flux vary little with horizontal resolution, while the macroscopic constraint of MOST increases with horizontal resolution.

Bangjun Cao et al.

Status: open (until 26 Apr 2023)

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Bangjun Cao et al.

Bangjun Cao et al.


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Short summary
The scale differences is important for the transfer of knowledge from large eddy simulation (LES) to large-scale model. We propose a new scheme for surface flux calculation applicable to LES models. The scheme first computes fluxes using the eddy viscosity and diffusivity estimated from the closure scheme, then applies a MOST macroscopic constraint such that the fluxes averaged over the LES domain. The new scheme makes the transfer of knowledge from LES to large-scale model plausible.