Effect of Urban Heat Island on Growth Rate of the Convective Boundary Layer Over Baghdad City

Abstract


Introduction
The layer of the atmosphere known as the boundary layer (BL) is directly impacted by the surface of the earth.The surface's influence on the convective boundary layer (CBL) is felt by rising, buoyant air currents (Strunin et al., 2004).CBL is a turbulent layer, it defines the vertical mixing of contaminates emitted from the surface by convective and mechanical turbulence.Convective boundary layer (CBL) is affected by Frictional drag, evapotranspiration and sensible heat flux variations (Solanki et al., 2019).
Surface temperature and convective boundary layer (CBL) are closely connected.In particular, in the canopy layer, which is nearest to the surface, surface temperatures have a large but indirect impact on air temperatures.The effect of surface temperature on the earth's atmosphere is significant, at sunset, metropolitan areas stay heated for a longer time until slowly cooling.This was discovered to be caused by absorbent surfaces in cities that collect and store heat throughout the day before releasing it into the atmosphere at night.(Tzavali et al., 2015).Surface heterogeneities and roughness have an impact on the microscale and mesoscale circulations in the convective boundary layer (CBL).The capacity of the surface to transfer the radiative energy absorbed from the sun and the atmosphere into sensible and latent heat fluxes has a significant impact on turbulent surface fluxes.
Urban heat islands can be produced by surface heterogeneities, which leads to regional variability in surface heat fluxes (UHI) (Courault et al., 2007).Such phenomena are known to contribute significantly to energy and matter transfer (Bastin and Drobinski, 2006).The urban heat island (UHI) influences the CBL which appears in all the constituents are well mixed throughout the layer and being homogenous with a murky haze appearance by greater thermal and mechanical turbulent density that is capped from above by an inversion layer (Oke, 1995).In general, many previous studies have dealt with CBL growth rate height and change with time through daily and hourly solar radiation received, and with location, because these changes in surface properties structure are resulted from UHI.
One of these studies plotted hourly boundary layer height (BLH) through 10 years over Baghdad city and its correlation with total column carbon monoxide (TCCO), results show that when BLH in maximum value TCCO have low values, seasonal variation of BLH also implemented, winter has low BLH while summer has large values because of high rate of surface heating during this season (Ali and Hassoon, 2020).Another study explained that urban heat island has a major effect in increasing the surface temperature by comparing the temperatures for two different areas in Baghdad City in the same year from satellite images ( Yaseen et al., 2014).
Hasoon and Ali demonstrated that surface temperature of Baghdad city has increased in a noticeable way manner about 2.5 ºC in 15 years due to the development of municipal areas (Hassoon and Ali, 2021).Hassoon and Ibraheem use satellite images and radiosonde that may be used as well tools to demonstrate how changes in physical properties of the ground surface affect the height of the radix layer (the lowest 1/5 of the convective atmospheric boundary layer) (Hassoon and Ibraheem, 2022).The goal of this article is to show the influence of the expansion in inner-city areas of Baghdad city detected by Landsat images upon the convective and boundary layer height resulting from growth rate that observed by ECMWF and ERA5 model.

Location
The study is at Baghdad City, the capital of Iraq, it lies between longitude 44.2 ºE and 44.5 °E and latitude 33.2 ºN and 33.49ºN, with 34 m elevation above sea level, with an area of 894.3 km 2 (Abbas and Monim, 2019) (Fig. 1a).Tigris river passes through Baghdad City and dividing it into two halves: Rasafa side (Eastern part) and Karkh side (Western part) (Hamiza et al., 2021), as shown in Fig. (1b).

Data from Satellite Images
Two scenes for Baghdad site at Path 168/ Row 37 were taken by Landsat 5 for 1994 and Landsat 9 for 2022 to obtain images processed in order to monitor the urban expansion during the period of 28 years in summer (July), Table 1, shows details of satellite images that used in this study such as sensors, bands and resolution.July was selected among other months due to its high temperatures, so the (UHI) will be in its maximum effect.Landsat 5 was in service from March, 1984, to November 2011, this is out of the study scope, and thus images from Landsat 9 were obtained with Landsat 5, in the same month.Images were downloaded from United States Geological Survey (USGS) website (Usgs. gov 2022).

Data from ECMWF
Reanalysis data product from ERA5 is considered one of recent modern models to archive atmospheric data resulting from European Centre for Medium-Range Weather Forecasts (ECMWF).ERA5 is an enhanced version of ERA model, its reflect as the fifth development for ECMWF reanalysis (reanalysis delivers a global picture of the climate and weather of the past as close to the reality as possible by using models and the laws of physics) for the global climate and weather for the past 4 to 7 decades (Hersbach et al., 2020).Since 1979, ERA5 provides hourly intervals of higher resolution data on a 31 km grid than the ERA Interim (Yang et al., 2022).It provides a wide range of data for several variables, the dataset such as temperature and wind speed at several levels pressure (from 10~1000) mb (Al Senafi et al., 2019).In this study hourly data obtained as NetCDF files for all days of July for both 1994 and 2022, was used with a high resolution of 0.25º × 0.25º grid data over Baghdad.All these grids have pressure levels from 1000 to 700 mb.All atmospheric pressure levels transformed to height in meter units by using hydrostatical equation, as in forma equation ( 1) (Ahrens 2014).
(1) : Height in meter, : temperature measured at that level height, : constant value equal to 0.0342k/m, : pressure at specified, pressure at sea level.

Detected urban expansion by Supervised Classification
True and false color bands are qualified to detect urban areas.This can be done through composite of bands, for example, Landsat 5 and 9 can produce a natural color images by composite bands 1, 2, and 3 and bands 2, 3, and 4 respectively.In composite images bands, municipal areas (areas of human activity) will be in dark blue color according to these merged bands, thus combination images bands are active method to exhibit details modification that happened in any place in land used, specifically exposure vegetation area, land used and expansion of urban municipal zones.Composite imageries given the best image, where the image will be ready to other processes such as supervised and unsupervised classification (Ali et al., 2019;Hassoon and Ibraheem, 2022;Bety, 2013).Supervised classification is the kind of machine learning in which training samples are specified and based on training samples the classification process is applied.In supervised classification, the user has to choose an area of interest which acts as a classifier in a map, and pixels of the whole image are classified depending on a zone for the study area (Enderle and Weihjr, 2005).Supervised classification depends on, the maximum likelihood classification algorithm, which exercised in a single pixel-based supervised classification technique (Bety, 2013) .

Detected Urban Expansion by the Spectral NDBI Index
Normalized difference built up index (NDBI) considers one of spectral indices used to identify built-up area from remote sensing images.It works to separate the built-up area from all types of land cover (such as soil, vegetation, water,.. etc.).Using NDBI is very necessary to determine various builtup kinds of the study area (Vigneshwaran and Kumar, 2018).This index produces accurate results and requires only clear satellite images.NDBI rate is estimated by calculating the ratio between the short wave infrared (SWIR) and near-infrared (NIR) to observe the built-up area changes for Landsat 9 and Landsat 5 data.Built-up Index (NDBI) has been Extracted using the equation (2) as shown below (Zha et al., 2003;Hassoon and Ali, 2021): (2) Where SWIR: is short wave infrared is band 6 in Landsat 9 and 5 in Landsat 5. NIR: near infrared is band 5 in Landsat 9 and 4 in Landsat 5. RED: infrared radiation is band 4 for Landsat 9 and 3 for Landsat 5. (Hassoon and Ibraheem, 2022).

Growth Rate of Convective Boundary Layer (CBL)
The boundary layer depth in the daytime can be referred to as (zi) or convective boundary layer (CBL) consider as the elevation of bottom inversion above surface in daytime.In contrast to zi, the boundary layer elevation (h) is given by the lowermost inversion's base altitude above sea level.The difference between h and zi is the terrain's height, which is normally ignored in low-level terrain.(Kossmann et al., 1998).The changes in zi or CBL height can be determined using a variety of indirect methods, based on profile measurements made with radiosonde, sodar, radar, LiDAR, ceilometers, etc.In addition to some calculation parameterization (Hassoon et al., 2021), or based on some atmospheric parameters such as surface sensible heat flux can be used to infer (CBL) height (Mehson, 2019;Haeffelin et al., 2012 ).The growth rate of the CBL is constructed by the entrained air from the free atmosphere to the entrainment zone that sperate boundary layer from the free atmosphere, the growth rate can be calculated by Stull (2015); Kossmann et al. (1998); Lee (2018). (3)

Where
: represent the progress rate of CBL, is the mean vertical rate at the altitude zi, produced by extensive lifting or dropping.
: is the entrainment rapidity (the speed of entraining free air into the convective mixing layer).This velocity defines the intensification in (CBL) triggered by solar heating of the Earth's surface and intercourse of air from upward to down into the CBL produced by thermals that enter the inversion cover or wind shear.Deardorff in 1974 developed formula to calculate in laboratory and simulate data from observations (Driedonks 1982) can be taken in equation ( 4). (4) Where is the friction velocity, is the Coriolis parameter, is the gravity acceleration, is the potential temperature near the surface, is the vertical gradient of potential temperature just above , is the convective vertical scaling velocity, and is the vertical kinematic sensible heat flux in the surface layer.

Calculate Baghdad City Urban Expansion Area
One of the most recent popular methods of estimating the amount of change in urban expansion is by satellite images and remote sensing.Urban progress needs a large duration period, to determine trends of urban expansion that may be extended to more than 30 years.In this study two images were taken by Landsat 5 and 9, because none of these satellites' sensors contain large periods over 28 years and proceeds to recent years.Two images are compared in detail acquired in one month (July) from years 1994 and 2022, to determine changes in land cover land use.The first step is by composite bands 3, 2, 1 consider for Landsat 5 and bands 4, 3, and 2 for Landsat 9 images.
Combination bands will display natural false color of these images (Figs.2a, and 3b) About more than 700 samples were taken from each image pixel to do supervised classification for these two visible images.Land cover according to this classification is divided to five categories, one of these categories is buildings class (Figs.2b, and 3b).Comparison thematic maps resulted from supervised classification for image scene in 1994 and image scene in 2022 in July shows that there is a change in areas of the categories classes for land cover water, vegetation, open area, roads, and buildings Table 2.For example, most land cover area decreases by about 1.37%, 2.34%, 16.61% and 2.63% for water, vegetation, open area and road classes respectively, Table 2.While buildings increase by rate 22.95% and area increases from 300.249km 2 in 1994 to 505.45km 2 in 2022.The second method to state and explain urban expansion is by NDBI, you can review paragraph 4.2.NDBI for Landsat 5 image in 1994 have range values from -0.64 to 0.51, while Landsat 9 image in 2022, its values vary from -0.450 to 0.480 the decrease in the high value for NDBI is because of another land cover is increasing while the increase in the low value indicates that the building area is more intense (Fig. 4).This figure shows that the orange and red colors have large distribution in 2022 image, although it doesn't have large values as stated in legend in (Fig. 4a), but frequency of this range is very large.Blue color distribution in Landsat image in 1994 is large, although there is clear graduation in color of this image from blue to red, (Fig. 4b), return also to references to known results accuracy of Baghdad classification (Hassoon and Ali, 2021;Tawfeek and Al-Jiboori, 2020).

Air Surface Temperature Trends
The urban expansion in Baghdad center affects the heat budget near the earth surface and the net heat flux released from ground, this will increase surface temperature and air temperature near the earth surface.As we explain in the recent paragraph from this research, this phenomenon can be clearly explained by plotting Air temperature at 2m that the data were downloaded from ERA5 at grid point lat.33.28º, and log.44.25º near to Baghdad Center with time.Time series selected to plot is the same time images scene in the same hour at 9 AM and made as a monthly July average for 28 years, from 1994 to 2022.Results show there is an increase in air temperature about 1.25Cº, where air temperature raised from 42.45Cº in 1994 to 43.698Cº in 2022 (Fig. 5).Thus, there is an increase rate of temperature with area of expansion about 5.5446*10 -2 Cº/km 2 through period of 28years, and about 1.94522*10 -3 Cº/km 2 for each year.

Effect of Urban Expansion on Wind and Temperature Profile through CBL
Transforming land cover land use to buildings area may change heat budget for regions near the earth surface which will increase heat absorption and increased heat released by these areas as a result.These natural responses will affect the nature of the air near the surface, and lastly on Boundary layer growth height and its physical properties.This study will focus on the conclusion of the modification in surface by municipal expansion on the boundary layer elevation and in special case on the convective boundary layer CBL that constructed at daytime.Information for upper layer and boundary layer profile is acquired from ERA5 as raw data distributed vertically in a specified pressure level such as wind speed and temperature.This raw data is downloaded as a NetCDF file, processed by MATLAB program marked for this purpose to transform it to an excel sheet.Pressure levels was converted to height in meters by hydrostatic equation, equation 1, on other hand, temperature also converted to potential temperature.
Potential temperature commonly used in vertical profile because it remains constant as the air parcel undrafted in upper air, in this parcel there is no adiabatic change due to pressure level change, also vertical gradient of potential temperature determines dry static stability of the atmosphere.Excel sheet file also has columns for two horizontal components wind speed u in x-axis and v in y-axis.All these vertical profile elements data were done on hourly average for July 1994 and 2022 respectively, this was considered for the time of satellite images implemented.(Fig. 6) shows average vertical wind and temperature profile through CBL at 9 AM for past and recent years.In this case, potential temperature profile decreases with height, until 2500 meters height, where temperature tends to be constant with height due to the capping inversion layer and the free atmosphere above, see (Fig. 6a).
Concerning case 2022, potential temperature profile also decreases with height, but inversion layer (capping layer) doesn't extend to 2500 meters, but it goes higher that makes the boundary layer deeper and the capping inversion layer will be extended at approximately 3000 meters.This considers a highly significant index to refer to the effect of land cover change, where urban areas increase the height of boundary layer height according to potential temperature parameter.This study also compared two wind speed profiles before and after the formation of urban expansion area and increases to about 23% through the period between 1994 and 2022.Before urban expansion wind profile at several hundred meters near the surface is large compared with wind profile in 2022, because the roughness length has small value compared to 2022 case, represent after urban expansion.The case conditions change at about 1800 meters, there is an opposite case for behavior of wind speed distribution with height, see Fig. (6b).Wind profile behavior differs in upper layer because it's far from the effect of surface friction, while the influence will come from pressure difference for this case, in addition to synoptic systems and wind direction that may be responsible for wind speed changes.
Generally, in Fig. ( 6b), we note similar behaviors for the two cases concerning capping inversion layer, where there is a decrease in wind speed with height although wind speed is high in 2022 above mixing layer over 3200meter, see (Fig. 6b).Atmospheric stable boundary layer (Capping inversion layer) can be determined from the change in behavior of wind speed and potential temperature, thus this study can determine mixed layer as 2300meter before urban expansion and about 3200meter after that, see Fig. ( 6).The change in potential temperature near the surface is very large, about 4.6 C° between 1994 and 2022, because of the change in land cover, but this difference decreases with height through the boundary layer.In other hand urban expansion will be reflected on wind speed flow at surface layer, it is lower than 2.5 to 3.5 m/s for 2022 but higher for 1994 with values of 3.5 m/s at surface layer to more than 8m/s in boundary layer height.

Effect of Urban Expansion on Growth Rate of CBL
Convective boundary layer height and boundary layer height at nighttime can be affected by the nature of land cover land use or the nature of the surface, this effect can be explained considering change in the wind speed and temperature vertical profiles in boundary layer before and after urban expansion.The change in CBL is resulted from the change in growth rate of boundary layer and entrainment of air from free atmosphere to the mixing layer at daytime, this contributed to enhanced buoyant thermal updraft.The processes will be active to increase CBL height.The change in land cover land use will affect heat budget and heat exchange that will have effect on growth rate and CBL.Growth rate for CBL is plotted depending on many atmospheric parameters.From July hourly average data for 2022 and 1994, its noted that there are extreme values for growth rate at 7 AM after sunrise, its large before and after urban expansion as in Fig. (7a), that shows the difference growth rate of 0.0883 m/s.Maximum growth rate at daytime is at 10 AM for 2022 reached 0.25244 m/s.In the nighttime growth rate neglected and have negative sign because of thermal disappearance and downdraft direction at these hours.Overall, there is also a difference in night growth rate between 1994 and 2022, but the difference is very small due to the large difference of heat budget at daytime, and larger rates of absorbing solar radiation at these hours of the day, (Fig. 7a).Fig. (7b) illustrates the differences in mixing height at daytime hours for both years before and after urban expansion that resulted from difference in growth rate of mixing height due to urban expansion and the increase in heat energy absorbed.The difference increases with the increase of the heat energy absorbed and solar radiation income from the sun to the earth surface, it is maximum at 10 AM where mixing height increases to about 620 m after urban extended to a rate of 23%.In other hours convective boundary layer height is also increased to heights 339,612,492,441,376,304,and 164 for hours 8,9,11,12 ,13,14,and 15 respectively,see (Fig. 7b).

Conclusions
Two satellite images in July for 1994 and 2022 and the spectral processes done on them, it is noted that the vegetation has decreased, and the buildings area increased, while the vegetation is decreased by 2.34%, the buildings area is increased by 22.94% of Baghdad area this due to the urban expansion.This urban increases area in 28 years has an effect on air temperature it has an increase of 1.24 Cº which has an effect upon the growth rate of mixing layer depth where there is a difference in the vertical profile of potential temperature about 800m in depth, this depth difference is obvious by the growth rate, it's very large in the first hours of sunrise, where the surface heating starts by sunlight, the largest growth rate is at 7 AM, where it records a value about 0.252 m/s as a monthly average in July/ 2022, this values decreases about 0.0883m/s compared to 1994.The difference in growth rate for mixing height will result in an increase in CBL of about 620 m, but it will be after two hours from maximum growth rate.

Fig. 5 .
Fig. 5. Time series of average air temperatures at July 9:00 AM for 28 years.

Fig. 7 .
Fig. 7. Hourly average for July in 1994 and 2022 shows (a) change boundary layer height at daytime and nighttime; (b) Hourly growth rate for boundary layer at 24 hours.

Table 2 .
The area of each category class according to supervised classification.