Scale‐Dependent Estimability of Turbulent Flux in the Unstable Surface Layer for Land Surface Modeling

• Published in: Journal of advances in modeling earth systems Vol. 15; no. 8
• Main Authors: Liu, Shaofeng, Zeng, Xubin, Dai, Yongjiu, Yuan, Hua, Wei, Nan, Wei, Zhongwang, Lu, Xingjie, Zhang, Shupeng, Li, Xian‐Xiang
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.08.2023; American Geophysical Union (AGU)
• Subjects: Boundary layer height; Boundary layers; Earth; Earth surface; Equilibrium; Experiments; Fluctuations; Height; Heterogeneity; land surface modeling; large eddy simulation; Large eddy simulations; Modelling; Oceanic eddies; Simulation; Sparsity; Surface boundary layer; surface flux estimation; Surface fluxes; Surface layers; Turbulent flow; turbulent fluctuation; Turbulent fluxes; Wind shear
• ISSN: 1942-2466; 1942-2466
• DOI: 10.1029/2022MS003567

Surface flux estimation is essential to land surface modeling in earth system models. In practice, parameterizations of surface turbulent fluxes are almost all based on the similarity theory. That is, the grid or subgrid mean surface‐layer flow is assumed at equilibrium with the underlying earth surface, and therefore some empirical relations can be used to estimate surface fluxes. In this paper, scale‐dependent estimability of turbulent flux in the unstable surface layer is systematically investigated based on high‐resolution large‐eddy simulation data over a flat and homogeneous domain, representing a typical land surface modeling grid. It is found that turbulent flow in the unstable surface layer inherently fluctuates over a wide range of scales. This kind of fluctuation affects the steady‐state relations between mean atmospheric quantities and underlying earth surface, and hence affects the estimability of surface fluxes. Sensitivity tests show that the relative root mean square error of the estimated surface friction velocity for a subdomain generally increases as the subdomain becomes smaller. The error can be as high as 35% as the subdomain size decreases to the order of the surface layer height. To achieve an error of 10% for all cases, the subdomain size should be at least on the order of the boundary layer height. These findings imply that estimability‐based strategies may be needed for representing subgrid heterogeneity for surface flux estimation in land surface modeling. Plain Language Summary Flux‐related land surface modeling involves much the representation of subgrid land surface. Land Cover Type (LCT) and Plant Functional Type (PFT) are the two main subgrid land surface representation approaches applied by modern land surface models. The two approaches both use some sort of subgrid “tiling” system. Tiles are defined as spatially aggregation of the area belonging to a land surface type (or category). Applying a novel analysis approach developed in this study and based on high‐resolution large‐eddy simulation data over an ideal domain, representing a typical land surface modeling grid, we find that the multiscale fluctuation of turbulent flow in the unstable surface layer makes the estimability of surface fluxes scale dependent. A subdomain with larger size or sparser distribution tends to achieve higher estimability. It is indicated that to reduce the estimation error to 10% for land surface modeling, the subgrid size should be at least on the order of the boundary layer height. This implies that aggregating small patches into a larger subgrid tile may introduce errors and traditional strategies, such as the LCT and PFT mosaic approaches, are probably not applicable to surface flux estimation. Estimability‐based strategies may need to be developed. Key Points Multiscale turbulent fluctuations affect local equilibrium in the unstable surface layer Fluctuation‐related nonequilibrium in the surface layer yields scale‐dependent surface turbulent flux Uncertainty of surface flux is quantified based on equilibrium‐based classical theory