Atmospheric Turbulent Intermittency Over the Arctic Sea‐Ice Surface During the MOSAiC Expedition.

Turbulent motions in the Arctic stable boundary layer are characterized by intermittency, but they are rarely investigated due to limited observations, in particular over the sea‐ice surface. In the present study, we explore the characteristics of turbulent intermittency over the Arctic sea‐ice surface using data collected during the Multidisciplinary drifting Observation for the Study of Arctic Climate expedition from October 2019 to September 2020. We first develop a new algorithm, which performs well in identifying the spectral gap over the Arctic sea‐ice surface. Then the characteristics of intermittency are investigated. It is found that the strength of intermittency increases under the conditions of light surface wind speed, small surface wind speed gradient, and strong surface air temperature gradient. The momentum flux, sensible heat flux, and latent heat flux calculated by raw eddy‐covariance fluctuations are overestimated by 3%, 10%, and 24%, respectively, because submesoscale motions are included. Furthermore, the characteristics of the atmospheric boundary layer structure under various intermittency conditions reveal that strong low‐level jets are favorable to surface turbulent motions that result in weak intermittency, while strong temperature inversions above the surface layer suppress surface turbulent motions and lead to strong intermittency. Plain Language Summary: In polar regions, turbulent mixing in the near‐surface layer is weak and is often modulated by strong stable stratification, thus the intermittent state of turbulence is universal. The intermittency might lead to inaccuracy of the Monin‐Obukhov similarity theory, which assumes that turbulence is fully developed. In this study, by using a year of eddy‐covariance observations collected over the Arctic sea‐ice surface, we first develop an automatic algorithm to identify the spectral gap where the Hilbert spectrum presents an abrupt drop in low frequency. Using only high‐frequency turbulent motions, the turbulent data is reconstructed. This algorithm has the potential to quantify the characteristics of turbulence intermittency in polar regions. Based on our analysis, the intermittency results in the greatest relative influence on the latent heat flux compared with the momentum and sensible heat fluxes. Furthermore, we found the following meteorological conditions often lead to the enhancement of intermittency: low surface wind speed and wind speed gradient; strong surface air temperature gradient; weak low‐level jets; and strong temperature inversions above the surface layer. These findings help to improve our understanding of turbulent intermittency over the Arctic sea‐ice surface. Key Points: A new algorithm, which performs well in identifying the spectral gap over the Arctic sea‐ice surface, is proposedThe characteristics of intermittency under different meteorological conditions are revealedThe effects of intermittency on eddy‐covariance fluxes are assessed [ABSTRACT FROM AUTHOR]