Interaction of Submeso Motions in the Antarctic Stable Boundary Layer
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Submeso motions add complexities to the structure of the stable boundary layer. Such motions include horizontal meandering and gravity waves, in particular when the large-scale flow is weak. The coexistence and interaction of such submeso motions is investigated through the analysis of data collected in Antarctica, in persistent conditions of strong atmospheric stratification. Detected horizontal meandering is frequently associated with temperature oscillations characterized by similar time scales (30 min) at all levels (2, 4.5 and 10 m). In contrast, dirty gravity waves superimposed on horizontal meandering are detected only at the highest level, characterized by time scales of a few minutes. The meandering produces an energy peak in the low-frequency spectral range, well fitted by a spectral model previously proposed for low wind speeds. The coexistence of horizontal and vertical oscillations is observed in the presence of large wind-direction shifts superimposed on the gradual flow meandering. Such shifts are often related to the variation of the mean flow dynamics, but also to intermittent events, localized in time, which do not produce a variation in the mean wind direction and that are associated with sharp decreases in wind speed and temperature. The noisy gravity waves coexisting with horizontal meandering persist only for a few cycles and produce bursts of turbulent mixing close to the ground, affecting the exchange processes between the surface and the stable boundary layer. The results confirm the importance of sharp wind-direction changes at low wind speed in the stable atmosphere and suggest a possible correlation between observed gravity waves and dynamical instabilities modulated by horizontal meandering.
KeywordsGravity waves Horizontal meandering Intermittent turbulence Stable boundary layer Wind-direction variability
This work was supported by PNRA (Progetto Nazionale di Ricerche in Antartide). We would like to acknowledge the collaboration with the Marche Region, and in particular the “Environmental assessments and authorizations, air quality and natural protection” section. We thank Dr. Karl Lapo and the three anonymous reviewers for their constructive comments that contributed to improve the quality of this manuscript.
- Bates DM, Chambers JM (1992) Nonlinear models. In: Chambers JM, Hastie TJ (eds) Chapter 10 of statistical models in S. Wadsworth & Brooks/Cole, BerlinGoogle Scholar
- Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows. Oxford University Press, New York, p 289Google Scholar
- Kolmogorov AN (1941) The local structure of turbulence in incompressible viscous fluid for very large Reynolds number. Dokl. Akad. Nauk. SSSR 30:9–13Google Scholar
- Mahrt L (2014) Stably stratified atmospheric boundary layers. Annu Rev Fluid Mech 46:23–45. https://doi.org/10.1146/annurev-fluid-010313-141354 CrossRefGoogle Scholar
- Nappo CJ (2002) An introduction to atmospheric gravity waves. Academic Press, New YorkGoogle Scholar
- Pasquill F (1974) Atmospheric diffusion. Wiley, London, p 429Google Scholar
- R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/
- Sun J, Nappo CJ, Mahrt L, Belušic D, Grisogono B, Stauffer DR, Pulido M, Staquet C, Jiang O, Pouquet A, Yagüe C, Galperin B, Smith RB, Finnigan JJ, Mayor SD, Svensson G, Grachev AA, Neff WD (2015a) Review of wave-turbulence interactions in the stable atmospheric boundary layer. Rev Geophys 53:956–993. https://doi.org/10.1002/2015RG000487 CrossRefGoogle Scholar
- Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteorol Soc 79:61–78. https://doi.org/10.1175/1520-0477(1998)079%3c0061:APGTWA%3e2.0.CO;2 CrossRefGoogle Scholar