
On structure of dynamic features of the lower layer of the atmosphere at low cloudiness
Author(s) -
O. N. Hrushevskiy,
O. Ye. Yeshanu,
N. М. Mishchenko
Publication year - 2017
Publication title -
ukraïnsʹkij gìdrometeorologìčnij žurnal
Language(s) - English
Resource type - Journals
eISSN - 2616-7271
pISSN - 2311-0902
DOI - 10.31481/uhmj.18.2016.06
Subject(s) - cloud cover , environmental science , ceiling (cloud) , atmosphere (unit) , meteorology , climatology , atmospheric sciences , cloud computing , geography , computer science , geology , operating system
Low cloudiness is one of the most important factors of a flight meteorological situation determining safety of aircrafts landing. The majority of publications devoted to the problem of stratiform cloudiness focus main attention on either studying of quantitative parameters of heat and moisture advection or typification of synoptic processes leading to its emergence and evolution. Therefore the main goal of the article consists in study of the spatiotemporal structure of dynamic features of the clouds-containing layer. Using the example of weather conditions causing air traffic disruption at Odessa International Airport, the article studies spatiotemporal structure of dynamic features of the lower layer of the atmosphere at the time of low cloudiness formation and its degradation. Complex usage of GFS model data with high resolution and data of actual observations with regard to cloudiness ceiling ensured obtaining conclusions about the nature of circulation conditions during its evolution. In particular, usage of time series helped to determine that vorticity and its features do not significantly affect low cloudiness formation unlike divergence and its vertical gradient. The conclusions obtained are confirmed via drafting of spatial vertical cross sections through the regions with minimum cloudiness ceiling. Quantitative and qualitative assessments of dynamic structure of the lower layer of the atmosphere at the time of low cloudiness formation may be used when developing criteria and parameters for its forecast.