A comprehensive investigation on afternoon transition of the atmospheric boundary layer over a tropical rural site
- 1National Atmospheric Research Laboratory, Gadanki – 517 112, India
- 2Sri Venkateswara University, Department of Physics, Tirupati – 517 502, India
Abstract. The transitory nature of the atmospheric boundary layer (ABL) a few hours before and after the time of sunset has been studied comprehensively over a tropical station, Gadanki (13.45° N, 79.18° E), using a suite of in situ and remote sensing devices. This study addresses the following fundamental and important issues related to the afternoon transition (AT): which state variable first identifies the AT? Which variable best identifies the AT? Does the start time of the AT vary with season and height? If so, which physical mechanism is responsible for the observed height variation in the start time of the transition?
At the surface, the transition is first seen in temperature (T) and wind variance (σ2WS), ~ 100 min prior to the time of local sunset, then in the vertical temperature gradient and finally in water vapor mixing ratio variations. Aloft, both signal-to-noise ratio (SNR) and spectral width (σ) show the AT nearly at the same time. The T at the surface and SNR aloft are found to be the best indicators of transition. Their distributions for the start time of the AT with reference to time of sunset are narrow and consistent in both total and seasonal plots. The start time of the transition shows some seasonal variation, with delayed transitions occurring mostly in the rainy and humid season of the northeast monsoon. Interestingly, in contrast to the general perception, the signature of the transition is first seen in the profiler data, then in the sodar data, and finally in the surface data. This suggests that the transition follows a top-to-bottom evolution. It indicates that other processes, like entrainment, could also play a role in altering the structure of the ABL during the AT, when the sensible heat flux decreases progressively. These mechanisms are quantified using a unique high-resolution data set to understand their variation in light of the intriguing height dependency of the start time of the AT.