Impacts of submesoscale motions on similarity relationships based on nocturnal observations in the Taklimakan Desert

Abstract

Submesoscale motions may substantially influence similarity relationships within the Stable Boundary Layer (SBL), leading to considerable uncertainty in these relationships. Therefore, we conducted a comparison of similarity relationships within the SBL in the Taklimakan Desert before and after the removal of submesoscale motions, aiming to gain deeper insights into the impacts of submesoscale motions on the similarity relationships. We introduced a method utilizing Discrete Wavelet Transform with orthogonal wavelets to identify and filter out submesoscale motions. By investigating nocturnal observations from June 29 to July 31, 2021, daily from 22:00 to 07:00 local time, we tested and confirmed that submesoscale motions indeed exert a substantial influence on similarity relationships in different ways. After removing submesoscale motions, dimensionless wind velocity standard deviations become more consistent across different averaging periods, with notably higher Correlation Coefficients and lower Root Mean Square Errors. This highlights the effectiveness of the method in eliminating submesoscale motions. Submesoscale motions themselves do not exert a direct and significant influence on the flux–profile relationship for wind speed. It seems the enhanced turbulence intermittency induced by episodic submesoscale motions results in notable deviations from the Businger-Dyer relationship within the strong stable regime. The influence of submesoscale motions on intermittency appears more pronounced as stability increases. Submesoscale motions significantly influence the relationship between turbulence intensity and wind speed. The episodic submesoscale motions appear to be the direct cause for the presence of moderate turbulence intensity at low wind speeds. Horizontal wind velocity variances are mainly influenced by submesoscale motions, while vertical wind variance is predominantly associated with small-scale turbulence. These findings may contribute to a more accurate understanding of the impacts of submesoscale motions on similarity relationships in the SBL and provide genuine and stable similarity relationships of small-scale turbulence for SBL modeling.