by Sachin Philip Kakkanattu, Sanjay Kumar Mehta, D. Bala Subrahamanyam, V. Rakesh and Amit P. Kesarkar
Abstract
The thermodynamic structure of the atmospheric boundary layer for contrasting sky conditions over Chennai, a coastal station in the Indian subcontinent, is investigated through conserved variable analysis of equivalent potential temperature and specific humidity. Simultaneous radiosonde and micropulse lidar measurements undertaken in 2018 constitute the primary database in this investigation. One of the most prominent features of this analysis is a consistent occurrence of a double mixed layer structure during the clear-sky and cloudy conditions throughout the year. The occurrence frequency of the double mixing lines is higher during the pre-monsoon season compared with the winter and northeast (NE) monsoon seasons. The advection mainly dominates the formation of double mixing lines during the winter and pre-monsoon seasons. In contrast, convection and advection dominate during the southwest (SW) and NE monsoon seasons. The frequent double mixing lines over Chennai occur mainly from the restratification of the convective boundary layer (CBL) due to the sea-breeze onset and the cloud layer. Occasionally, a triple mixing line structure is also observed during the fair-weather boundary layer (FWBL) of the pre-monsoon and SW monsoon seasons. Among the 355 total observations collected during 2018, the first, second, and third mixing lines occurred 100%, 70%, and 14%, respectively. The thermal internal boundary layer (TIBL), CBL, and FWBL occur ~50%, ~97%, and ~ 30%, respectively. The first mixing line is represented by both the TIBL and CBL, and CBL and FWBL represent the second mixing line, whereas the third mixing line is represented solely by the FWBL. The first and second mixing line shows strong seasonal variations with lower altitudes during the pre-monsoon season and higher altitudes in the SW monsoon season, almost in the same phase as the CBL variation but in the opposite phase of the TIBL variations. The CBL height attains a minimum during the winter season and maximum during the SW monsoon season, while TIBL becomes minimum during the pre-monsoon and SW monsoon seasons and maximum during winter and NE monsoon seasons.
Source: https://doi.org/10.1016/j.atmosres.2023.106915
by S Lenka, Krushna Chandra Gouda, Rani Devi and C M Joseph
Abstract
There is a need to understand the onset of monsoon dynamics as the date of onset of monsoon (DOM) is an important parameter in framing all the policy for the imminent season like crop choice, sowing schedule, disaster management, power distribution etc It is observed that the interannual variability of the DOM in India is about 7–8 days, making it more challenge to predict this at long lead. The MJO phases are linked with the different convection centres and hence, influences the global circulation process and the rainfall. In this paper the dynamical influence of the different phases of MJO are being quantified on DOM and its progress in continental India by using the multi-source atmospheric and oceanic parameters like wind structure, outgoing longwave radiation (OLR), sea surface temperature (SST). The linkage of the active and inactive phases of MJO along with the favourable conditions for DOM is obtained by using the pentad analysis of associated parameters in different clusters for both the wet and dry phases of MJO along with the strength for the period 1980–2018. Also the dynamics are studied for the early, normal and late onset years separately to understand the relation better. It is inferred that the wet (dry) phase leads to early (late) monsoon onset over Kerala (MOK) in India. To address the progress of monsoon the DOM in Rajasthan (MOR) is considered and the rainfall anomalies during MOK-MOR period are linked to the MJO phases. It is inferred that the wet MJO phase with negative OLR anomaly triggers the fast progress of monsoon over India. This understanding will surely help operational researchers and the NWP modellers for improving the methodologies for the advanced and accurate prediction of DOM.
Source: https://iopscience.iop.org/article/10.1088/2515-7620/acde3a
