Time Variability of Surface-Layer Characteristics over a Mountain Ridge in the Central Himalayas During the Spring Season

We present the diurnal variations of surface-layer characteristics during spring (March–May 2013) observed near a mountain ridge at Nainital (29.4∘N,79.5∘E,\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$29.4^{\circ }\mathrm{N},\,79.5^{\circ }\mathrm{E},$$\end{document} 1926 m above mean sea level), a hill station located in the southern part of the central Himalayas. During spring, this region generally witnesses fair-weather conditions and significant solar heating of the surface, providing favourable conditions for the systematic diurnal evolution of the atmospheric boundary layer. We mainly utilize the three-dimensional wind components and virtual temperature observed with sonic anemometers (sampling at 25 Hz) mounted at 12- and 27-m heights on a meteorological tower. Tilt corrections using the planar-fit method have been applied to convert the measurements to streamline-following coordinate system before estimating turbulence parameters. The airflow at this ridge site is quite different from slope flows. Notwithstanding the prevalence of strong large-scale north-westerly winds, the diurnal variation of the mountain circulation is clearly discernible with the increase of wind speed and a small but distinct change in wind direction during the afternoon period. Such an effect further modulates the surface-layer water vapour content, which increases during the daytime and results in the development of boundary-layer clouds in the evening. The sensible heat flux (H) shows peak values around noon, with its magnitude increasing from March (222±46Wm-2)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(222\pm 46\,\mathrm{W\,m}^{-2})$$\end{document} to May (353±147Wm-2).\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(353\pm 147\,\mathrm{W\,m}^{-2}).$$\end{document} The diurnal variation of turbulent kinetic energy (e) is insignificant during March while its mean value is enhanced by 30–50 % of the post-midnight value during the afternoon (1400–1600 IST), delayed by ≈2h\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\approx }2\,\mathrm{h}$$\end{document} compared to the peak in H. This difference between the phase variations of incoming shortwave flux, H and e primarily arise due to the competing effects of turbulent eddies produced by thermals and wind shear, the latter increase significantly with time until nighttime during April–May. Variations of the standard deviations of vertical wind normalized with friction velocity (σw/u∗)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\sigma _\mathrm{w}/u_{*})$$\end{document} and temperature normalized with scaling temperature (σθ/T∗)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\sigma _{\theta }/T_{*})$$\end{document} as functions of stability parameter (z / L) indicate that they follow a power-law variation during unstable conditions, with an index of 1/3 for the former and −1/3 for the latter. The coefficients defining the above variations are found in agreement with those derived over flat as well as complex terrain.