Impact of Built-up Areas Surrounding the International Baghdad Airport on Aviation Meteorology

The surrounding land – and boundaries of airspace – around airports must remain free of obstacles for aircraft to perform their operations safely at the airport; the airport cannot be used if there is a proliferation of obstacles in those areas. The impact of escalating extreme weather conditions or high-impact weather occurrences in these areas will also be significant; for example, extreme air temperatures and heat waves, and the negative health effects associated with them, are more frequent [Wahab et al. 2022]. Neglecting variations in urban density and potential urban intensification may result in an underestimation of an urban heat island's scale, particularly in a city's densest areas. Intensified urbanization has the potential to elevate temperatures in some of the city's hottest areas, and future research should strive to include more realistic urban expansion scenarios, for example, by using government plans in the design of scenarios [e.g. Nichol et al. 2013; Chapman et al. 2017].

Urban expansion is defined as the physical extension of the geographical footprint of towns, cities, and metropolitan areas into the surrounding countryside, which impacts aircraft during takeoff or landing. It also causes turbulence, which can cause aviation accidents that lead to material and human losses [Kreuz et al. 2017].

Air temperature also has an important influence on the formation of meteorological dangers. In the areas of fuel capacity and interpretation, it also has a direct impact on airplane safety. In nonstop intercontinental travel, because fuels expand as air temperature rises, the outside temperature at the airport during fueling may have an impact on an aircraft's fuel storage capacity [Chevron 2006]. Fuels may also gel or freeze in extremely low temperatures [Keel et al. 2000]. Because there is a positive relationship between expanding urbanization and air temperature, as well as an inverse relationship between said urbanization and solar radiation and wind speed, the growth of green areas without adequate coordination will have an impact on the local ecosystem [Abdulrahman et al. 2020; Al-Jiboori et al. 2020]. Replacing vegetation with impermeable surfaces results in warming, which will alter the local urban climate and change ecological conditions [Dong et al. 2014].

Weather is a primary contributing factor in 23% of all aviation accidents. The total global economic impact of weather, in terms of accidents, damage and injuries, delays, and unexpected operating costs, is estimated to be $3 billion [Kulsea 2002]. Many meteorological parameters, such as heavy precipitation, lightning, turbulence, dust or sand storms, heat waves, and wind, influence aviation, impacting operational performance, the infrastructure of airports and aircraft, and working conditions at outdoor aviation activities [International Civil Aviation Organization 2005].

In the present study, the latter two parameters, which are particularly sensitive to changes in surface properties, are examined as to how they are affected by urban expansion in Baghdad, in terms of air temperature and low-altitude wind shear. Wind shear is a change in wind speed and/or direction that can occur either horizontally or vertically and is most often associated with frontal activity, thunderstorms, temperature inversions or surface obstructions [Federal Aviation Administration 2008]. Wind shear can also occur at high or low altitudes; here we only discuss low-altitude vertical wind shear, which tends to have the most serious effect on an aircraft.

There are many studies about aviation meteorology. For example, Hahn [1989] studied the effect of wind shear on flight safety. The study found that wind shear affects the flight performance as well as the aircraft motion, especially low-level wind shear during landing and take-off. Schultz et al. [2018] showed that airport performance scores could be used in comprehensive air traffic network simulations to evaluate the impact across the network of weather-induced local performance deterioration. Wind shear was significantly observed at higher wind speed conditions (³ 6 ms⁻¹) [Hon, Chan 2022] and complex terrain [Xu, Niu 2019]. Recently, Chan et al. [2023] have applied large-eddy simulation around the Hong Kong International Airport, which proved to be a reasonable method of capturing low-level wind shear in the springtime.

There has also been some research on changes in land cover change in Baghdad specifically. For example, Al-Saadi et al. [2020] studied the varieties of urban vegetation cover and their impact on minimum and maximum heat islands. The study demonstrated that maintaining and expanding plant cover in semiarid urban contexts is the most effective technique for lowering the possibility of thermal impacts and heat stress, which are worsened by regional and global warming. Ali and Al-Ramahi [2020] also studied the influence of urbanization on annual evaporation rates in Baghdad City using remote sensing and showed that vegetation plays a key role in lowering temperatures and minimizing urban heat islands.

The main contribution of this paper is to document the effect of urbanization expansion surrounding airports on aviation meteorology and air traffic at lower elevations. Urban expansion in Iraq, especially in the areas surrounding the International Baghdad Airport (IBA), has brought with it urban land changes, such as an increase in built-up surfaces, roads, bridges and other impermeable surfaces. This has been considered a random expansion resulting from population growth, as well as political conditions and military operations in the country. However, there is very little understanding about the relationship between the growth of urban areas and meteorological parameters. The parameters most related to this subject are vertical changes in the air temperature and winds over a long-term period. The objectives of this study are to 1) determine the annual variations in built-up areas surrounding Baghdad International Airport (IBA); 2) analyze monthly means for both temperature and wind shear for only July over eight years; and 3) establish empirical relationships correlating urban expansion around IBA with these parameters. The structure of the paper is organized as follows: section 2 provides the details of study area and data collection sources. Section 3 presents the analysis procedure with a flow diagram. In the following section, descriptions of the built-up index, climate factors, and their combined effects are discussed. Finally, a summary of main conclusions is reported in section 5.

First, in order to assess the random and continuous development and expansion of Baghdad City, we adopted the Built up Index (BUI) proposed by Zha et al. [2003] to quantify the changes between urban built-up areas and other land-cover types. BUI is the spectral index for analyzing urban patterns based on the difference between normalized difference building and vegetation indexes. It can calculate using the following equation (1): BUI=(MIR+NIRMIR−NIR)−(NIR−REDNIR+RED) {\rm{BUI}} = \left( {{{{\rm{MIR}} + {\rm{NIR}}} \over {{\rm{MIR}} - {\rm{NIR}}}}} \right) - \left( {{{{\rm{NIR}} - {\rm{RED}}} \over {{\rm{NIR}} + {\rm{RED}}}}} \right) where MIR is the Middle Infrared = Band 5 for Landsat-5 and 7 and = Band 6 for Landsat-8; NIR is the Near Infrared = Band 4 in Landsat-5 and 7 and = Band 5 for Landsat-8; and RED is Red = Band 3 in Landsat-5 and 7 and = Band-4 in Landsat-8.

This advantage of this method is its unique spectral response to build up area and its ability to automatically quantify a spatial pattern. The output binary image shows positive pixels for builtup and barren areas, and the rest of pixel for all other covers [Zha et al. 2003; Tawfeek et al. 2020]. The binary image, with only higher positive value indicating built-up and barren areas, used in ArcGIS program, version 10.7, allows the BUI to map the built-up area automatically. For more details, preand post-processing of satellite images, such as clipping, compositing, mosaic bands and extraction of the study area, are explained by Zeina and Al-Jiboori [2023].

The second part of our methodology was the analysis of daily climate data of the two factors of air temperature and wind shear. Wind shear is a change in wind speed and/or direction over a short distance. It can occur either horizontally or vertically, and is most often associated with strong temperature inversions or density gradients [Al-Ghrybawi, Al-Jiboori 2019]. In this study, this was only calculated for July of each year. This month was selected to coincide with the satellite images analyzed in this study. The air temperature (°C) at 2 m, during the period between 01/7/1985 and 31/07/2020, and wind speed, measured at two heights 10 (U₁₀) and 50 m (U₅₀), during the period between 01/01/1985 and 01/09/2020, were used. “Monthly” means these data were calculated only for the July of each year for this study. From the mean wind speed, the mean wind shear was calculated in (s⁻¹) using the equation (2): Wind shear=U¯50−U¯10Z50−Z10=U¯50−U¯1040 {\rm{Wind}}\,{\rm{shear}} = {{{{\overline {\rm{U}}}_{50}} - {{\overline {\rm{U}}}_{10}}} \over {{{\rm{Z}}_{50}} - {{\rm{Z}}_{10}}}} = {{{{\overline {\rm{U}}}_{50}} - {{\overline {\rm{U}}}_{10}}} \over {40}} where Ū₅₀ is the mean wind speed at the height of 50 m (Z₅₀) and is the Ū₅₀ mean wind speed at 10 m (Z₁₀).

In third part of the study, the built-up indexes, average air temperatures, and wind shear values were projected on two charts using the Origin 9.2 program, showing the extent to which the air temperatures are proportional to the BUI of the area, as well as to wind shear. These were analyzed using the linear regression equation (3): Y=δ+ε*X {\rm{Y}} = \delta + \varepsilon *{\rm{X}} where Y is the air temperature, wind shear, or any dependent variable, and X is the built-up area, time, or any independent variable. The constant a is the intercept and b represents the slope. The values of a and b were derived from the experimental data above.

Finally, the statistical parameter R² was used to measure of the goodness of fit of a real point data, which when close to 1 indicates that the regression predictions perfectly fit the data. According to the discussion above, the methodology of this study can be summarized in the flowchart shown in Figure 2.

Figure 2.

In this study a statistical method was presented to determine the impact of the urban expansion on aviation micrometeorology around International Baghdad Airport between 1985 and 2020. The changes in land cover showed that there is an impact on the local climate, and the following conclusions can be drawn: -

The mean air temperature was continuously increasing, with the highest temperatures recorded in 2020. It is possible that this is related to decreases in the amount of vegetation cover as a result of the conversion of agricultural and open land to populated and commercial areas and commercial usage. Aside from that, there are also some random settlements.