A study of the Urban Heat Island of Granadahera.ugr.es/doi/15001647.pdf · Although Granada is not an industrial zone, we must take into account its intense automobile traffic. In

INTERNATIONAL JOURNAL OF CLIMATOLOGY

Int. J. Climatol. 20: 899–911 (2000)

A STUDY OF THE URBAN HEAT ISLAND OF GRANADAJUAN P. MONTAVEZ*, ANTONIO RODRIGUEZ and JUAN I. JIMENEZ

Grupo de Climatologıa Urbana y Cambio Climatico, Departamento de Fısica Aplicada, Facultad de Ciencias,Uni6ersidad de Granada, Granada, Spain

Recei6ed 4 February 1998Re6ised 22 February 1999Accepted 1 March 1999

ABSTRACT

In this study we examine the Urban Heat Island (UHI) of Granada. First, we perform a study of the evolution ofthe recorded temperatures at a meteorological station over the last century. In this record, the minimum temperaturesincrease while the maximum temperatures decrease. We also compare both rural and urban temperature records,obtaining the UHI fluctuations on a smaller time scale. The results show that the UHI phenomenon is stronger inwinter, and the maximum difference occurs in early morning when temperatures are at their daily minimum. Then,we examine the geographical distribution of temperature in the urban region and obtain the dependence of UHI formon meteorological conditions, urban geometry and time scale. Urban geometry plays a particular role in the UHIform. The formation of UHI phenomena depends mainly on weather conditions and on time of night. Finally, werelate both UHI form and intensity with the observed trends in the urban time series. Copyright © 2000 RoyalMeteorological Society.

KEY WORDS: Granada; Urban Heat Island; temperature trends

1. INTRODUCTION

The process of urbanization produces radical changes in the surface and atmospheric properties of aregion. All of these changes induce a modification in the climatic balance, creating a new climate calledthe urban climate (Landsberg, 1981; Wanner and Hertig, 1984; Oke, 1987; Oke et al., 1992). This newclimate must be understood as a local perturbation of the regional climate. However, all urban climatespresent several common characteristics. Of all features, the Urban Heat Island (UHI) is the mostcommonly studied (Landsberg, 1981; Oke, 1987; Yague et al., 1991; Lopez et al., 1993; Moreno-Garcıa,1994). This phenomenon is characterized by a temperature difference between the city and its outskirts.It appears with highest intensity principally at night when the sky is cloudless and the winds are weak.When the UHI occurs, urban temperature is higher than rural temperature. If we plot an isotherm mapof such a situation, the city will appear as an ‘island’ in the background of rural temperature.

We can relate the above-mentioned observed temperature changes directly to the urbanization processand take the background temperature as non-urbanized temperature. Some authors define the back-ground rural temperature prior to urbanization, but doing so neglect any information related to a possibleregional warming (Jones et al., 1990; Esteban-Parra et al., 1995; Karaca et al., 1995).

When the UHI occurs there are temperature gradients in the city closely associated with the features ofeach urban zone. We find a strong temperature gradient at the edge of the city (cliff). Inside the city,depending on the zone, there are weaker temperature gradients (Plateau), reaching a maximum oftemperature (peak) in the most urbanized areas. Therefore, depending on the modifications present ineach zone, different temperature differences, DTu−r=Tu−Tr (where Tu is the urban temperature and Tr

is the rural temperature), will be observed. According to some authors (Oke, 1981; Oke et al., 1991;

* Correspondence to: Grupo de Climatologıa Urbana y Cambio Climatico, Departamento de Fısica Aplicada, Facultad de Ciencias,Universidad de Granada, E-18071 Granada, Spain. Tel.: +34 58 243206; e-mail: [email protected]

Copyright © 2000 Royal Meteorological Society

J.P. MONTAVEZ ET AL.900

Swaid, 1993), of all the modifications produced by the urbanization process, canyon geometry andthermal properties (with their effects on radiation and storage heat release) are the most important factorsin the UHI formation. These results are confirmed by our experiments.

The intensity of the UHI phenomenon depends on several factors. The most important factor is thetime of day: while the phenomenon is very striking at night, it is virtually non-existent during the day. Asecond factor is weather conditions; when the atmosphere has cloudless skies and light winds conditions(CSLW), the intensity is higher. The geometry of the city and topography of the land play an importantrole, but principally in the spatial distribution of temperatures in the city (Eliasson, 1996; Kuttler et al.,1996; Yamashita, 1996). Finally the emission of anthropogenic heat, pollution, etc., affects the UHIintensity but its impact is weaker and it depends on the season (Oke et al., 1991; Stanhill and Kalma,1995).

To study this modification of local climate, several methods have been used: (1) comparison of ruralagainst urban stations. To carry out such an analysis of rural stations they must be in close proximity tothe city and have similar climatic features (Nasrallah et al., 1990; Moreno-Garcıa, 1994; Karaca et al.,1995); (2) taking temperatures at several points in the city by moving observations around the city(Moreno-Garcıa, 1994; Yamashita, 1996); (3) studying the temporal series of temperature of stations thatare engulfed by the city as it grows (Jones et al., 1990; Yague et al., 1991; Esteban-Parra et al., 1995;Karaca et al., 1995); and (4) satellite observations (Lee, 1984; Gallo et al., 1993). All of these methods areuseful but only when used in combination can they give full information about the UHI phenomenon.

In the first part of this study, we examine a long temperature series of a station in the city thatdemonstrates the impact of urban growth on temperature. Second, we do a statistical analysis oftemperature differences between one of the warmer zones of the city and a rural station, obtaining theUHI intensity and its temporal distribution. Next we construct maps of the geographical distribution ofnight time temperature to study the relation between temperature fields on both meteorological conditionsand time of night. In addition, we aim to study the dependence of temperature distribution on variousurban features. Finally, we relate this typical shape of the temperature field to the evolution oftemperature time series.

2. DESCRIPTION OF DATA AND URBAN REGION

Granada is a medium-sized city situated in southeastern Spain (37°11%N, 3°36%W) at an altitude ofapproximately 700 m above mean sea level. It has an area of 22 km2 and a population of about 300 000.Recently, its outer belt has experienced rapid growth. Its climate is characterized by strong daily andseasonal variations of temperature. While it has an annual precipitation of around 450 mm, insummertime there is practically no rain. With regard to topography, Granada is located at the limit of thefertile lowland of the Genil River and Sierra Nevada mountains, the highest of the Iberian Peninsula. Thecity is crossed by four rivers, but none is large enough to affect the temperature field. However, there isa cold air canyon associated with the Darro River. As we will see, it plays an important role in the UHIform of Granada. Although Granada is not an industrial zone, we must take into account its intenseautomobile traffic. In addition, due to their large seasonal thermal variations, many houses in Granadahave air conditioners.

Regarding the database, we have taken four different sources of data:

1. The annual temperature series of the Observatory of Cartuja (1901–1990).2. The urban network of stations. It belongs to the AMA of Andalusia (Agencia del Medio Ambiente),

and provides us with hourly meteorological data.3. The military airdrome of Armilla. It offers several forms of meteorological data. This station is located

4 km from Granada, and its altitude and topographical conditions are quite similar to those of thecity. The nearest runway is 1 km from the meteorological station, the area is open, there are no treesaround it and the surrounds are fertile lowlands.

Copyright © 2000 Royal Meteorological Society Int. J. Climatol. 20: 899–911 (2000)

GRANADA’S URBAN HEAT ISLAND 901

4. Instantaneous temperature data at 84 points around the city. These data were obtained by means oftwo mobile units, equipped with digital thermohygrometric probes covering almost all of the city andsome points of the outskirts. The temperatures taken around the city were calculated for the samehour (central hour of the transect) using a function of temporal temperature evolution that weconstructed. For the fitting we used both the temperature differences obtained at several points of thetransects (crossing points) and the fixed stations.

The quality and homogeneity of all sources of data were verified. Although the temperature data arenot taken at the same distance from the ground, the height of the observations taken are: 1.70 m fortransects, 2.50 m for AMA stations and 1.5 m for Cartuja and Armilla stations. The resulting errors dueto this are negligible. Also, all temperature recordings of all sources are unaspirated. The locations ofstations and points where instantaneous temperatures were measured are shown in Figure 1.

3. TEMPERATURE EVOLUTION IN THE LAST CENTURY

Like many other cities, Granada has experienced spectacular growth in the last century. This growth mayexplain the trend in temperature. To study this relationship, the time series of temperature at Cartujastation, recorded from the beginning of this century, are analysed by statistical methods. We proved thehomogeneity of data by testing several variances (Rodrıguez et al., 1996). The significance of the trendsin annual minimum and maximum temperatures was studied by means of the Mann–Kendall test(sequential version), commonly used by several authors (Yague et al., 1991; Esteban-Parra et al., 1995;Karaca et al., 1995), and recommended by the WMO (Sneyers, 1990).

Figure 1. Points of data. The square indicates the position of the Cartuja Station in Granada city. The three circles show the AMAstation positions. One of them is marked with a star and will be used as an urban station in comparisons. The triangles indicate thepoints of measurement during the transects. The situation of the Armilla airdrome is indicated by an arrow. This base map showsthe proxy edges and the zones with different morphology, the rivers which cross the city and the principal traffic roads of Granada

(see Figure 7)



Table I. Observed trends and Mann–Kendall results for annual time series of maximumand minimum temperatures (Rodrıguez et al., 1996)

Linear trend Significance year Change point

Maximum −0.9°C/century 1970 1968Minimum 1.6°C/century 1938 1950

In addition to the significance of the trend, this non-parametric test may be used to obtain otherparameters such as change points and significance years. The curves plotted in Figure 2 denote the resultsfor the series and the retrogade one. The change points are given by the intersection of both curves, andthe significance year is when the series reaches one of the values 91.96 (which points out that the serieshas a positive or negative trend with 95% confidence level).

The results are shown in Table I and Figure 2.Our results are similar to those obtained by many other authors studying other urban areas: the

temperature series show a notable positive trend in minimum temperatures, while maximum temperaturestend to decrease over time.

lt remains unclear how much of these trends is due to the urban effect and how much is attributableto regional warming. Thus the study of time series affected by urbanization is not valid for studyingregional or global warming. The dependence of this trend on several factors, such as the growth of theurban area, the location of the station within the city, and local and regional climates will be discussedlater.

4. COMPARISON OF A PAIR OF METEOROLOGICAL STATIONS

A second way to study the modification of temperatures in the city is by comparing urban and ruralstations with similar topographic features. If the stations are near enough to one another, then theassumption may be made that their temperatures would be the same as if there were no human influence.

We have suitable stations for such a comparison. We choose one of the AMA stations as the urbanstation, and the station located at the Armilla military airdrome as the site uninfluenced by urbanization(see Figure 1). The AMA site, as will be shown, is located in one of the warmer zones in the city.

Studying the daily temperature evolution at both the rural and urban sites, we observe that the urbanthermal wave amplitude is smaller than that of the rural site (Figure 3). The most notable feature is thereduced cooling in the urban area in the late afternoon and evening resulting in a higher nocturnalminimum temperature in the city. This effect is closely related to the thermal properties and morphologyof the city. Thus there is a large difference between the minimum temperatures at the two stations;however, the maximum temperatures tend to be quite similar.

The UHI intensity is defined (Oke, 1987) as the temperature difference DTu−r between the ‘city peak’and the rural background temperature for nocturnal, cloudless skies and light wind conditions (maximumphenomena conditions). We extend this concept by calculating DTu−r for all meteorological conditions atthose points which give maximum differences for these maxima phenomena conditions.

4.1. Temperature difference and its temporal distribution

Using the time series of temperature differences, a study of the daily maximum and minimum DTu−r

was made for annual and seasonal periods. The results are shown in Table II. The maximum differencesoccur during winter months. They are always greater than 3°C, and sometimes reach values greater than7°C. On the other hand, the minimum differences are largest in autumn and lower in summer, with thecity being warmer by a small amount. The differences are always smaller than 0.5°C, and often the




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Figure 3. (a) Urban and rural daily temperature evolution. (b) Daily UHI intensity. The data used for these results was thetemperature differences between the Armilla station and one of the AMA stations mentioned before (see Figure 1)

opposite phenomenon to UHI occurs: the ‘urban heat sink’, i.e., the city is cooler than its outskirts,reaching DTu−r#−2°C.

In addition, the hour of the maximum and minimum DTu−r is studied. Looking at Figure 3 one cannote that the greatest differences occur during night time and the least occur during day time. The hourswhen DTu−r are most probable to be maxima and minima can be seen in Table II. We observe that whileminimum DTu−r fit to a normal distribution centred between 3 or 4 h after noon, the maximum ones donot fit to a normal distribution. The temporal distribution of maxima temperature differences ischaracterized by a first relative maximum around 5 h after sunset and a absolute maximum at the latesthours of night, coinciding with minimum temperature.

4.2. Intensity of UHI in different weather conditions

We define two kinds of weather situations: CSLW and NCSLW; then all possible meteorologicalconditions are classified in one of these two groups. In the first group all situations characterized bycloudless skies and light winds conditions (CSLW) have been included. The second group includes allother cases (NCSLW). For the CSLW situations, the maximum differences are higher while the minimumones reach negative values. While under NCSLW situations the city is always warmer than rural areas, at

Table II. DTu−r average, maximum and minimum, for seasonal and annual periods

Maximum MinimumAverage

p DTu−r s TIH pDTu−r s DTu−r s TIH% °C °C LST %°C °C °C °C LST

15–170.570.25404–70.86 443.71.12.0Annual0.64 15–17Winter 482.5 1.2 4.1 0.90 6–8 30 0.14

Spring 1.7 1.0 3.4 0.87 4–6 37 0.10 0.56 16–17 370.823.60.91.8Summer 4217–180.4360 0.204–7

15–17 500.54366–80.703.71.02.0 0.54Autumn

s is the S.D., TIH is the time interval when the probability is maxima, all of them are in degreesand p is the probability (in 100) that it occurs in such intervals. The data used were: one of theurban stations, (which is located in the warmest place of the city and mentioned before, see Figure1) and Armilla station. Local standard time is used (GMT in our case) for TIH.



Figure 4. Temperature differences for CSLW and NCSLW situations. In this figure only the differences for February of 1995 areshown. The data used for the study was mentioned in Figure 1

night time DTu−r are smaller and in the day time DTu−r are higher, decreasing the oscillation amplitudeof the temperature difference time series (see Figure 4).

5. STUDY OF THE TEMPERATURE FIELD

In this section the spatial distribution of temperature in the city is studied. The spatial prediction modelused is the ordinary version of the Kriging method (the assumption that air temperature variations aresmall is made) (Eliasson, 1996). We used several kinds of variogram models and obtained the best resultsfor spherical and exponential models. Detailed descriptions of these models are given in Cressie (1991)and Montavez et al. (1996a,b). Then, the values of temperature at each point of a rectangular 60×100grid were calculated, thus obtaining a spatial series for each transect. The description of some of thetransects (those described in point four of the ‘Description of data and urban region’ section) can be seen

Table III. Description of some transects

Gradient SituationN UHIIDate ho

CSLW0.9023:00 5.016/01117/02 23:00 0.50 NCSLW 2.02

3.0NCSLW0.2523:3025/013CSLW 4.00.8420/02 24:004

5 03:30 0.50 CSLWa 5.021/026 08/03 23:00 4.0CSLW0.72

CSLW 4.00.4203:0009/0370.48 CSLW 3.58 09/03 06:00

01:009 0.90 CSLW 4.024/03

N is the number assigned to each transect, ho is the centre of transect time used to carry out allinstantaneous measurements. Gradient shows the negative range of change of temperature in timeobtained from our fit, in °C/h. UHII is the UHI intensity at time ho in °C.a Light breeze.



Figure 5. Isotherm (on the left side) and error surfaces (on the right side) for various transects. The numbers correspond to thenumbers of the transects given in Table III



Figure 5 (Continued)

in Table III. In Figure 5, an isotherm map for such transects is presented, as well as the errors for a 95%level of confidence.

To establish the relation of UHI form to various parameters the following cross-correlation matrix hasbeen constructed:



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denotes the correlation coefficient of i with j transects listed in Table III. Note that all correlationcoefficients are significant at the 95% level of confidence.

5.1. Relation between UHI form and meteorological parameters

Comparing the results of correlation coefficients of NCSLW situations with all others, CSLW andNCSLW, we see that they are never larger than 0.4. In addition to the intensity decrease associated withNCSLW conditions, there is not a defined form of the UHI, having only a small peak in the centre of thecity (see Figure 5a.2). This is due to the fact that in cloudy and windy situations the most importantfactors that contribute to the intensification of the phenomenon are strongly reduced.

Another interesting feature is the behaviour of the UHI when wind begins to blow but wind speeds arestill small. Under these conditions, a strong gradient of windward temperature and a light gradient of leetemperature are formed. Due to turbulence, the temperature field becomes inhomogeneous creating some‘little islands’ (see Figure 5a).

5.2. E6olution of UHI during the night

Now the CSLW situations are compared to each other. The Mij values are sensitive to the hour whenthe transect was made. For transects at different hours, which have differences of central transect timegreater than 2 h, MijB0.6, while a comparison of transects at very different hours, which have differencesof central transect time greater than 5 h, give values of MijB0.4. However, transects made atapproximately the same number of hours after sunset result in Mij\0.5. In addition, when comparedtransects are at the beginning of the night (about 3 or 5 h after dusk), Mij\0.75. These results reveal thatthere is a strong relation between UHI form and the hour of night. This is due to the fact that for a givenhour of the night geometrical, topographical and traffic features play a very important role in the UHIform. But in the course of the night due to advective mixing, temperature becomes homogenized showinglarger gradients in the city edge. Three cross-sections of the UHI of Granada during the same night atdifferent hours (transects 6, 7, 8) are shown in Figure 6. In addition, an important factor in the form ofthe UHI of Granada is the cold air injection from the Darro River. These katabatic winds occur early inthe night, giving Granada’s UHI a peculiar form (opposite results to Kuttler et al., 1996) (see Figure 5a,b).

5.3. Typical UHI form and its relation to urban factors

Therefore, for CSLW situations at the same hour, the UHI has a characteristic form, which is closelyrelated to topographical and geometrical features of the city. From Figure 7, it is apparent that thetemperature peak is in urban zones built around 1960s. These areas are characterized by a lack of openareas and have buildings with eight to ten floors with narrow streets. In general, higher intensity of theUHI phenomena occurs in areas with a large value of the ratio H/W where H is the height of buildings



Figure 6. Cross-sections of UHI of Granada during at three different times of the same night. The cross-section is drawn in Figure7. The thickness coincides with the black circles marked on the cross-section line. A and B are the initial and final point plot inFigure 7. The distance between thickness is 1 km and labels on the horizontal axis indicate distance from point A. It can be observedthat the absolute minimum temperatures coincide with the city edges and the relative minimum which disappears during the night

correspond to a park located within the city

and W is the street width. However, this ratio is only true for H values are approximately higher than twofloors. None of the rivers that cross the city is large enough to have any influence on the surroundingtemperature. But as mentioned above, one of them has a cold air canyon associated with it that dividesGranada’s UHI into two parts and makes some places colder than the outlying areas at nearly nighthours. Also the green areas of the city are associated with small cold sub-islands which disappear duringthe course of the night. By looking at Figure 7 the relationship between geometry and usual form of theUHI is shown (for CSLW situations and between 3 and 5 h after dusk).

Figure 7. Relationship between urban morphology and nocturnal temperature field. (A) Seven to ten floors, very broad streets. (B)Old quarter: two to four floors, very narrow streets, cobblestone paving. (C) Nine to ten floors, broad streets. (D) Gardens and areaswith few builds. (E) Building from seven to ten floors, very broad street. (F) Principal traffic roads. The ‘rural’ areas are shaded in

white.



6. COMMENTS AND CONCLUSIONS

The results obtained in this work show that long temperature series are affected by local climatemodifications. The growth of the city has resulted in a large increase in minimum temperatures and asmall decrease in maximum temperatures. In addition, the results from our study of UHI form lead us tobelieve that the observed trends are a function of the site in the city where the meteorological station islocated, as well as the regional and local climate. If Cartuja station were situated, e.g., in the warmest partof the city, then the observed trend would be larger. Thus, in order to measure the overall warming of aregion that contains an urban area it is necessary to have a meteorological station that is not affected byUHI. In addition, when considering the relationship between temperature and other parameters such asthe number of inhabitants, city size, fuel consumption, etc. (Antunes et al., 1996) the location of themeteorological station must always be taken into account. As a second result, the average temperature ofthe city is always warmer than its outskirts. These differences increase during night time and CSLWsituations. During day time the opposite phenomenon sometimes occurs, giving negative temperaturesdifferences. In NCSLW situations, the differences are smaller and are also similar during both day andnight time. As for the hourly distribution, the maximum differences do not follow a normal distribution.There is higher probability that it occurs in two different intervals of the night, the first around 5 h afterdusk and the second at dawn coinciding with absolute minimum temperatures. The second interval has ahigher probability than the first. Comparing our results with those obtained by other authors, it is likelythat the different results obtained in this study stem from the differing placement of urban and ruralstations. In addition, our results could be influenced by the cold air injection from the Darro River.Regarding the form of the UHI, the dependence on meteorological conditions and hour into the night isvery strong. However, our results show that for CSLW situations the form of UHI is the same at a givenhour. This form is closely related to the geometry and topographic conditions of the city. During the nightwe document the larger cooling of rural zones and the homogeneity of the temperature field in the city.

ACKNOWLEDGEMENTS

We would like to thank AMA and Grupo de Atmosfera from University of Granada, for providing uswith some of the data used in this study; also to CETURSA for use of mobile measurement equipment.Special thanks to Dr A. Sarsa for helping us solve some programming problems and to Dr Alex Hall(Princeton University) for advice on and correction of the text.

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A study of the Urban Heat Island of Granadahera.ugr.es/doi/15001647.pdf · Although Granada is not an industrial zone, we must take into account its intense automobile traffic. In