Document Type : Research Paper
Author
Associate professor of climatology, Zanjan University
Abstract
Extended Abstract
Introduction
The planetary boundary layer (PBL) as the lowest part of the troposphere is the most dynamic part of the atmosphere that is directly affected by the interactions of the atmosphere and the surface of the Earth (Stell, 2012 and Gert, 1992). These atmospheric surface interactions occur in short periods of time and play an important role in the development of the boundary layer. The height of this layer is also influenced by atmospheric conditions, topography characteristics, and type of land cover, and is an important parameter for many meteorological phenomena that have various applications such as monitoring air quality, cloud formation and evolution, surface fluids, and atmospheric hydrological cycles (Garrett 1994). Since the height of the boundary layer indicates the depth of turbulent vertical mixing, it is very effective in increasing or decreasing the concentration of pollutants near the surface and is considered as an essential parameter in air quality monitoring (Su and Khan, 2018). In addition, the height of this layer is a key factor in numerical weather forecasts. Since the height of the base of clouds is usually close to the height of the boundary layer, this layer determines the extent of cloud development and causes the transition from shallow convection to deep in the clouds.
Materials
The data used in this study included re-analysis data on the monthly time scale of the planetary boundary layer height for the entire Iranian region with a resolution of 0.25×0.25 which was obtained from the ERA5 version of ECMWF site during the period 1959-2021. In order to analyze the relationship between different climatic variables (mean temperature, mean relative humidity and air pressure), the meteorological data of 187 synoptic weather stations during the statistical period 2000-2022 has been used.
Methods
In this study, in order to prepare the data using programming capabilities in MATLAB software, maps with an average of 62 years old have been prepared and then using ARC GIS software to map the monthly average height of the boundary layer in Iran. In the next step, spatial statistics index of Getis-Ord Gi* was used to analyze the spatial changes in the height of the boundary layer in different months. In order to analyze the effective variables in elevation changes in the boundary layer temperature, relative humidity, soil moisture, etc. Multivariate standard regression method was used.
Conclusion and Discussion
The annual average elevation map of the boundary layer also shows that the maximum height of this layer in Iran is 1600 m which is located in the south of Iran in Kerman province and south of Sistan and Baluchestan province and in general, the southern half of Iran with the exception of a narrow strip of southern coasts is higher than the northern half. The lowest elevation between 520 and 1000 meters is mainly located in the northern half, the eastern part and a narrow strip of southern coast. The average height of the entire boundary layer of Iran during the year is 1131 meters. The height of the boundary layer in different months of the year has significant changes in Iran and in terms of spatial changes it follows severe cluster patterns. Analysis of hot and cold spots showed that the spatial distribution of the height of the boundary layer has completely homogeneous spatial patterns so that the northern half of the country, especially the northwest and northeastern regions of the country, have a high significance as cold spots in most months of the year.
Results
The results of this study showed that the elevation of the boundary layer in Iran during the year has a lot of spatial and temporal changes due to geographical diversity and climatic characteristics in different regions of the country. The existence of diverse topography, expansion in latitude, large differences in relative moisture content and soil moisture content are among the factors that have caused significant changes in the height of the boundary layer at different times and places. The results of multivariate regression analysis showed that the height of this layer is mainly affected by six parameters in particular, temperature and relative humidity.
Keywords
Main Subjects