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The urban-parkland nocturnal temperature interface
Urban Climate 31 (2020) 100585
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Urban Climate journal homepage: www.elsevier.com/locate/uclim
The urban-parkland nocturnal temperature interface ⁎
Roger Claya,b, , Huade Guanb
T
a
School of Physical Sciences, University of Adelaide, South Australia 5005, Australia National Centre for Groundwater Research and Training, College of Science & Engineering, Flinders University, Bedford Park, South Australia 5042, Australia
b
A R T IC LE I N F O
ABS TRA CT
Keywords: Urban heat island Traverse measurements Boundary effects Water vapor
An urban heat island (UHI) study has been made of the transition between an open park area and an urban environment, mainly through the use of night-time mobile traverses concentrating on still nights at cloudless times. The park areas exhibit lower temperatures than the urban areas, with little extension of the effect into the urban area. The boundary transition proves to be quite sharp at times when wind speeds are low. Through additional measurements of water vapor it was found that there is an inverse relationship between specific humidity and screen temperature along traverses. The park areas have higher humidity levels. Measurements at fixed urban locations exhibit a similar effect with evapotranspiration apparently playing a significant role.
1. Introduction The urban heat island (UHI) relates to the increased temperatures within urban environments when compared to surrounding rural temperatures (Oke, 1987; Stewart and Oke, 2012). Those urban temperature excesses vary both spatially and temporally within the urban region and are often reported to reach levels of 5 °C or more. This effect is important since, in climates which require air conditioned cooling, it can add appreciable economic costs (e.g. Guan et al., 2014). It also has appreciable costs in terms of the comfort and health of the local population (e.g. Sharifi et al., 2016). Such considerations are becoming more serious as urban areas expand and climate change results in the increase of intrinsic temperatures in many of our large-scale environments. Whilst the UHI phenomenon is understood, in general ways, to be associated with the physical properties of urban surfaces, buildings, anthropogenic heat release, and sky view factors within urban canyons, detailed studies in particular locations can add to our understanding and, potentially, point to ways of mitigating the effect. The overall thermal climate in an urban area is shaped by both regional winds and the UHI effect (Guan et al., 2016). For a total picture, both need to be considered. When found, the magnitude of the temperature excess has a positive correlation with the fraction of impermeable surface in the urban area (Park, 1986), related to the “built-up ratio” (Bottyán et al., 2005). It also correlates inversely with the sky view factors associated with urban canyons and the level of cloudiness in the sky (Zhu et al., 2013). The effect is strongest when wind speeds are low and is almost lost at wind speeds above about 3 ms−1 (Clay et al., 2016; Park, 1986). In considering how one might mitigate an urban temperature excess, it is important also to know something about its characteristic scale lengths when properties of the built urban environment vary spatially. Those length scales might be expected to depend not only on wind speed and associated turbulence scales but also length scales within the built environment such as the lengths of city blocks (Nichol and Wong, 2008). The importance of horizontal air movement in determining the local urban thermal environment of Taipei city was discussed by Chang and Li, 2014. Park et al., 2017 found evidence for measurable effects of green spaces down to areas of 300 m2 in urban blocks with rather tall
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Corresponding author at: School of Physical Sciences, University of Adelaide, South Australia 5005, Australia. E-mail addresses: [email protected] (R. Clay), huade.guan@flinders.edu.au (H. Guan).
https://doi.org/10.1016/j.uclim.2020.100585 Received 4 April 2019; Received in revised form 8 November 2019; Accepted 6 January 2020 2212-0955/ © 2020 Elsevier B.V. All rights reserved.
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R. Clay and H. Guan
buildings and Lee et al., 2009 noted the effect of tall buildings inhibiting the movement of cool air in the Seoul CBD area. Urban parks are considered to be one efficient urban heat mitigation solution (Bernard et al., 2018). The cooling effect of Chapultepec Park (500 ha) in Mexico City can reach a distance about the same as its width (2 km) (Jauregui, 1991). Measurements in the vicinity of a Beijing park (Yan et al., 2018) indicate that a large park (in their case, containing forest, lakes and wetlands) can influence urban temperatures at distances of up to 2 km from the park. In Leipzig, Jaganmohan et al. (2016) show that the influence range of park cooling varies from tens to hundreds of metres. It seems to be clear that park size is an important factor determining the park cooling effect. This is likely related to the spatial scale for efficient surface and air heat exchange. Guan et al. (2015) showed that the effective heating area for urban Adelaide was ~100 × 100 m2 and Nichol and Wong (2008) noted that small green spaces above ~1 ha in size could produce lowered surface temperatures but, at those small sizes, they do not seem to influence air temperatures along a traverse route. The effects of large parks on the spatial structure of the urban temperature distribution should be considered as they mimic, on a small scale, a rural environment (Yan et al., 2018). To assist with urban planning, the properties of the park boundaries and the dependence of local-scale air temperatures on the dimensions of parkland areas are important topics for study, as is the related extent of the influence of a park into the surrounding urban area. The differing effects of trees and shrubs, when compared to grass, within parks was emphasized by Cao et al., 2010 who proposed a park vegetation and shape index. Wind data were not provided by Yan et al. and wind might also be expected to have an influence on heat transfer in the surroundings of a green space. In the Beijing data, there seems to be a shift of the cooled region to the east of their park area which is otherwise unexplained. The results of screen temperature measurements by Yan et al. (2018) emphasized the conclusions of Du et al. (2017) who used satellite imagery to study the extent of the influence of green space areas outward from parks. This cooling influence was found at the 2 °C level out to several hundred metres from the green space. Physically, urban park cooling is considered to mainly result from surface evapotranspiration. Other factors, such as parks having a larger sky view than street blocks, and better ventilation, may contribute to the cooling effect. In climates where UHI problems are important, open park areas may be watered by the park management. The effect of such watering and vegetation evapotranspiration may be measured by recording humidity and local temperatures and a relationship is known to exist between the two (Acero et al., 2013). However, the process by which this correlation comes about has not been clearly demonstrated. It is generally understood that vegetation transpiration stops after sunset. Thus, evapotranspiration cooling would not be a significant contributor to urban park cooling at night time. However, Holmer et al. (2013) show that surface evapotranspiration continues for a couple of hours into the evening, leading to a lower temperature over the vegetated surface when compared to the surrounding area. Interestingly, this temperature difference persists whilst both surfaces continue to cool radiatively throughout the night. In their study, the sky view effect is secondary in night-time urban air cooling. The overall objective of our study is to examine the nocturnal temperature interface between parkland and urban areas. The paper examines the broad parklands which surround and are enclosed in the central business district (CBD) of the City of Adelaide, South Australia. Specific objectives are (1) to investigate characteristics of the temperature gradient variation through the urban-park interface from outside the CBD, and in parks within the CBD, and (2) determine whether nocturnal evapotranspiration contributes to park cooling. Our initial hypothesis was that the air temperature through the urban-park boundary would vary smoothly with a gradient changing only slowly through the interface, even on calm nights. We shall show that this idea was not supported in our work. The role of nocturnal evapotranspiration in any changes of that gradient was to be examined. 2. Method This study is based both on a large number (approaching 100) of night-time (early morning) traverses through the CBD, out of which a small number were selected to have clear skies and to have wind speeds which could be described as ‘calm’, and on data from an array of static sensors spaced through the area of study. Data which included screen temperatures, relative humidity, and infra-red sky temperatures were recorded. Water vapor is the most important of the greenhouses gases affecting the terrestrial climate and it is also associated with evapotranspiration cooling mechanisms for vegetation. It may well have appreciable concentration variations within a city canopy layer. As part of this work, we have begun a program to study the possible role of water vapor in the UHI. Water vapor is recorded throughout our traverses through measurements of the relative humidity. A knowledge of that parameter plus the screen temperature enables the specific humidity (g/kg) to be calculated. Upward-viewing infra-red radiometers operating at long wavelengths are sensitive to water vapor, although in a column rather than just the local vapor density. They can be used as an indicative cross-check of the variation of the vapor density as derived from the screen temperature and relative humidity data. Over the past year, we have used infra-red radiometers in conjunction with the other instrumentation for our traverses. We use two broad-band long-wave radiometers directed at elevations of 45o, one which covers the water vapor band at ~ 7 μm and an otherwise identical one which does not. The difference between their outputs is a measure of the water vapor column density, integrated, at least, over the atmospheric gases within the city canopy level. The traverse method employed here followed that which was described in some detail by Clay et al. (2016). Vehicular traverses (in the main following the route indicated in that paper) were made with screen temperature (1.5 m above ground), relative humidity, and infra-red temperatures (two radiometers most recently) being logged at 10 s intervals. The screen temperature was calibrated to 0.1 °C and the response time was ~130 ms. This technique introduces a characteristic spatial uncertainty ~50 m in general, although at important spatial points data were usually recorded with better resolution whilst the vehicle was travelling very slowly or was stationary at traffic lights. Traverses took place typically between 4 a.m. and 6 a.m., always well before sunrise. 2
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Fig. 1. Image of the central Adelaide urban area. Parkland (land cover type B, Stewart and Oke, 2012) surrounds a central built area. The southern half of that built area has a local climate zone (LCZ) classification LCZ 3. The north east quadrant, surrounding Hindmarsh Square, is classified LCZ 1. Details of the building heights are shown in the overlay. Red markers are sites of the fixed network used for Figs. 6 and 10. This paper deals particularly with the UHI transition at the point marked for the King William Street-parkland boundary, and the effect on the UHI strength of the marked ‘squares’. The most usual traverse route taken for this paper passes north from the parkland, through Hurtle Square and is shown in Clay et al., 2016. (Background image from Google Earth.) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Traverse data led us to investigate related data from the Adelaide Urban Heat Island Monitoring Network (Guan et al., 2016). This network of static temperature and relative humidity monitoring sites at a height of 4 m is centred on the CBD of Adelaide with significant extensions into the surrounding suburban areas. The central region of the City of Adelaide has an area of approximately 5 km2 and is level within 15 m altitude over a linear distance of order 2 km. It has within it five ‘squares’ with areas ranging from about 2.5–4.0 ha (Fig. 1). That central region is surrounded by ‘parklands' (land cover type B, Stewart and Oke, 2012) with widths of the order of several hundred metres (typically ~ 500 m). There are thus clear boundaries between the city area and the parklands, and at the boundaries of open areas (“squares”) within the city area, which enable us to investigate characteristic distance scales for the extent of the UHI phenomenon. The climate in Adelaide is usually described as “Mediterranean” with mild moist winters and generally hot, dry, summers. Our previous work has showed that spatial temperature structure in the urban heat island (UHI) is washed out for wind speeds above about 3 m.s−1. This work aims to investigate the form of that spatial structure, particularly at the parkland boundary, concentrating on times which are described as ‘calm’, with wind speeds recorded by the local Bureau of Meteorology typically below 1 m.s−1 and under cloudless skies.
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Fig. 2. The result of temperature measurements (‘y’ axis) along traverses from urban area (LCZ 3) to park (Local Climate Zone LCZ B) through the southern city boundary (see Fig. 5c below). The local wind speeds recorded by the Bureau of Meteorology are noted. The built area is left at 0.6 km in every case. The measurements are adjusted by the subtraction of a fixed temperature to agree at 1.3 km.
3. The urban-parkland temperature gradient at the outer boundary of the CBD We wished to examine the boundary of the extensive park area surrounding the central urban area of the City of Adelaide. We wished to know the spatial extent by which temperature changes associated with the boundary were to be found (primarily) within the park area. Fig. 2 shows representative data taken at the boundary (in this case, the King William Street-parkland boundary shown in Fig. 1). In all cases, the boundary is crossed at distance marked as 0.6 km (chosen to show data from each side of the boundary). On cloudless mornings, at times when the wind speed (as noted by the Bureau of Meteorology) is 0 m.s−1 (calm), the beginning of the clear temperature drop into the park area takes place within a characteristic distance of below ~50 m of that boundary. This effect is particularly clear in Fig. 3 for which the transition is from a local climate zone classified as LCZ 1 (Stewart and Oke, 2012). The data in Fig. 2 show a rather sharp transition from the urban CBD (LCZ 2) to the parkland area at distance 0.6 km (photograph Fig. 5c). In cases with wind recorded as “calm” (0 m.s−1), the distances travelled into the southern park areas to reach the lowest temperatures had a mean distance of 300 m. Fig. 3 shows data for a transition out of the CBD (LCZ 1) to the north. In this case, after the boundary there is an appreciable downward slope into the park area (a drop of 40 m in altitude) and we note that the temperature transition extends further for this traverse. The mean reductions in temperature as the parklands are entered are shown in Table 1, at times of no wind, for three exit locations from the built area. There is no strong evidence for an appreciable extension into the city urban area of the cooling due to the parklands. This is in contrast to evidence from Beijing (Yan et al., 2018) and Shanghai (Du et al., 2017) which show effects extending up to 2 km from large parks (with dimensions up to ~2 km in diameter in contrast to our data for the 500 m wide parkland). We note that our clearest UHI effects were for times when the wind speed was very low. This could be inhibiting the extension of the cooling to more central urban areas under the conditions for which our data were acquired. The data from Beijing and Shanghai (Yant et al. 2018 and Du
Fig. 3. As for Fig. 2 but exiting the urban area (Local Climate Zone LCZ 1) to the north into parkland (Local Climate Zone LCZ B) through a downward slope of a total of 40 m over a distance c. 500 m. The built area is left at 0.6 km. 4
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Table 1 Full temperature reductions when transiting from the built area into parklands on clear, still mornings (the magnitude of the UHI boundary). Exiting South
4.2 +/− 0.8 °C
(27 entries)
Exiting West Exiting North
5.5 °C 4.2 +/− 0.4 °C
(1 entry) (4 entries)
Fig. 4. Screen temperatures measured in a traverse through Hindmarsh Square (between distances 0.6 and 0.8 km) at 05:00 11 March 2018. The route passes through an area with relatively low buildings (2 stories) before the Square and then enters a “canyon” region after the Square (see also Fig. 5).
Table 2 Average temperature reductions on passing from the built area into City squares. The reduction to the lowest temperature in each square is shown as a fraction of the reduction found at the parkland boundary for that traverse.
Hindmarsh square Hurtle square Light square Victoria square
Approximate
Fractional
Dimensions
Temperature drop
145 145 120 100
× × × ×
230 230 220 240
m m m m
0.19 ± 0.02 0.10 ± 0.005 0.1 0.056 ± 0.003
(8 (8 (1 (7
entries) entries) entry) entries)
et al., 2017) suggest a transition effect outside the park area of ~2 °C which extends to some hundreds of metres into the urban area. Our data do not show this effect and their transition into the park is quite clear, with a clear change in the gradient of the temperature curve at the interface. Any effect of air temperature variations in the urban area is at a level below 1 °C for times when the wind speeds were very low. As we have noted before (Clay et al., 2016), and to be seen in Fig. 2, data for times when wind speeds are above 2–3 m.s−1 show little transition effect at the boundary. However, it is possible that those higher wind speeds do cause mixing between air in the parkland and the city areas such as may be suggested by the progressive temperature change before the transition at 0.6 km for the dataset in Fig. 2 corresponding to a wind speed of 3 m.s−1.
4. The urban-parkland temperature gradient within city squares The five squares within the Adelaide CBD have dimensions comparable to, or somewhat less than, the spatial scales of temperature change discussed above for transitions extending into the parklands. Four of the squares have been examined within our traverses. Fig. 4 shows one of those traverses, with the route passing through the center of Hindmarsh Square (see location in Fig. 1, LCZ B) at distance 0.7 km. The route travels north through relatively low buildings (LCZ 3) to reach the square at distance 0.6 km and then passes through the Square, entering a high rise “canyon” (LCZ 1) to the west at distance 0.8 km. The average magnitudes of screen temperature reductions for traverses through four squares are presented in Table 2. Whilst the temperature drops in the squares were close to limitations set by the sensor accuracy (as may be seen in Fig. 4), averaged data allow mean temperature reductions to be derived with the uncertainties in Table 2. Those small reductions are in contrast with the five to ten times larger reductions at the urban-parkland boundary. The internal distances to the centers of these squares are no larger than the distance scales found in which the parkland UHI temperatures are reduced by 30%. Given that the parklands have a considerable lateral extent to the side of the traverses, whilst the 5
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Fig. 5. Photographs of (a) Hindmarsh Square, (b) Victoria Square, and (c) the Parkland transition point (King William St and South Terrace). Photo credits: (a), (c) R. Clay; (b) H. Guan. (a) Hindmarsh Square, facing west. (b) Victoria Square, facing south. (c) Parkland transition point (King William St and South Terrace), facing north.
squares have two modest sized dimensions in comparison, it is probably not surprising to find that the temperature reductions in the squares are rather small. On the other hand, there does seem to be a difference in the depth of the temperature drop amongst the squares so it may be that other parameters, such as the surface of the squares, vegetation, and watering patterns are also important. Fig. 5 includes photographs of the Hindmarsh and Victoria squares in which it can be seen that the surface treatment and its likely watering are quite different.
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Fig. 6. Diurnal temperature variations averaged over one month (25 Feb-26 Mar 2015, measured at 4 m above ground) at four fixed sites (blue parkland (345 m from the city boundary); red – boundary between the parkland and the city; yellow and green – progressively further inside the city area). The site locations are shown by red markers in Fig. 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 7. Data from a traverse through parkland into the city area, and then out into parklands. Shown are screen temperature (purple), water vapor density (red, derived from the relative humidity) and an infra-red measure (blue, arb. units) of the water vapor column density. (10 March 2018). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
5. Diurnal variation of the temperature through a parkland-city boundary The data discussed above were taken typically in the time range 04:00 to 06:00 local standard time. The variation of temperatures over full 24 h periods can be extracted from data recorded at fixed city sites by the Adelaide Urban Heat Island Monitoring Network (Guan et al., 2016). An example is shown in Fig. 6. The results corresponding to the traverse data discussed above are in the early morning period (04,00–06:00). The transition from the city area to the parkland (from red to blue lines) is clear at all times, as is the lack of a temperature change between the boundary and the internal city areas (red, green, yellow). The city areas are classified as LCZ 3 with rather little physical reduction in sky view factor (SVF: blue 0.99, red 0.97, yellow 0.84, green 0.91). There is the clearest parkland-city transition at times from late morning to evening when the parkland data (blue) show a substantial reduction in temperature compared to the city. This variation does not seem consistent with a sky view factor effect and we interpret this to be a result of strong evapotranspiration effects in the parkland at the hottest times of day. Holmer et al. (2013) reported a persistent temperature difference between vegetated and surrounding areas whilst cooling through the night (“Phase 2”) following site-dependent cooling around sunset (“Phase 1”) which they relate to evening evapotranspirative cooling (EEC). Phase 2 can be seen clearly in Fig. 6 between 22:00 h and 05:00 h, as can phase 1 which, in our case, persists somewhat longer than found by Holmer et al. 6. Water vapor at the urban-park boundary Fig. 7 shows results from a city (parkland to urban area to parkland) traverse in which the screen temperature (purple) and 7
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Fig. 8. The relationship between specific humidity and temperature for a traverse through parklands and the city area (10 March 2018).
specific humidity (red) data are presented. There is an apparent inverse correlation between these two parameters. Fig. 7 also shows a measure of humidity derived from infra-red radiometer measurements (blue - arbitrary units). The same sort of relationship is found as with a more direct measure of specific humidity except that the infra-red data are noisy (they are the difference of two signals) and their changes at the parklands are not abrupt. The latter is due to the radiometers viewing at an elevation of 45o and so integrating over a substantial lateral distance. This supports the result, from data using the relative humidity sensor, that water vapor density is changing through the urban heat island inversely with screen temperature. This relationship is shown explicitly in Fig. 8. The data show that parkland areas have lower temperatures and higher humidity than the central City areas. A natural assumption is that vegetated areas offer more opportunities for transpiration and evaporation than a (largely) impervious urban environment. We can also see the effect of water vapor using data recorded at fixed locations in the central city area with the Adelaide Urban Heat Island Monitoring Network (Guan et al., 2016). These data are shown in Fig. 9 which shows relationships between screen temperature (measured), and specific humidity (derived from temperature and relative humidity measurements) for three single day subsets of those data. There is again an inverse relationship between temperature and humidity and we note that there is a similar rate of temperature decrease with specific humidity as for the traverse. A naive interpretation might be that evapotranspirational cooling decreases the temperature and leads to an increase in the ambient vapor density, but such cause and effect has not yet been demonstrated. Clear relationships such as those in Fig. 8 are not found in some other days with different synoptic weather conditions. In Fig. 6, we showed temperature data from four fixed sites and speculated that there was an evapotranspiration effect even at an urban site, particularly onwards from late morning. Fig. 10 shows specific humidity data corresponding to the temperature data in Fig. 6 (same four sites, same times). There is clear evidence for an increase in specific humidity for two sites at the times (10:00–16:00) when the parkland temperatures are lowest compared to the temperatures of city locations. However, in this case, we note that the measurements of specific humidity at the boundary follow the parkland humidity rather than that of the city area. This is in contrast with the properties of the boundary temperature which, as we saw, follows the city temperature.
7. Discussion We have examined mainly night-time data at the boundary between parkland and a built city area. Our first objective was to investigate the temperature gradient variation through the urban-park interface. Our initial hypothesis had been that the air temperature would vary smoothly with a gradient which changed only slowly through the interface, even on calm nights. This did not prove to be the case. We find a sharp temperature transition with a break within ~50 m of the boundary (the spatial resolution of our measurements). At times of low wind, from the boundary location and travelling inwards into the city, there is little temperature change (Figs. 2 and 3 for distances below 0.6 km). In the more open parkland area, the temperature reduces with distance from the boundary with a characteristic scale of some hundreds of meters. These low wind speed data are in contrast to observations presented from parks at other sites, which were obtained under less fixed conditions. It appears likely that wind speeds above about 2 m.s−1 do cause mixing through the boundary and may be the source of the apparent discrepancy. The significant scale lengths associated with temperature changes in the parkland area probably result in the lack of substantial temperature reductions in the city open spaces (city squares), which have characteristic dimensions of 100–200 m. It would seem that, to be effective, open spaces need to have dimensions greater than, or the order of, 500 m. Our second objective related to the possible role of nocturnal evapotranspiration in the cooling of parkland. We have shown that 8
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Fig. 9. Three single day measurements relating humidity and screen temperature, made at a location in the central city area.
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Fig. 10. The average 24 h variation in specific humidity, measured at 4 m above ground (25 Feb-26 Mar 2015) at the four sites (red markers in Fig. 1) whose temperatures are shown in Figs. 6. (blue – parkland (345 m from the city boundary); red – boundary between the parkland and the city; yellow and green – progressively further inside the city area). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
the measured temperature variations have an inverse association with the specific humidity in the vicinity of the temperature measurements. This is found both over a short time interval for a range of locations along a traverse, and over an extended period for a fixed location. Thus, we found (Figs. 8 and 9) a quantitative relationship between air temperature and specific humidity which is similar across space and time, showing 3–4 degree cooling with 1 g/kg increase in specific humidity. Although not definite, this relationship supports the possible hypothesis of an effect of surface evaporation cooling, even in night time. Figs. 6 and 10 show particularly large differences in air temperature between park and urban areas at times when there are large specific humidity differences. This would also seem to support the idea that evapotranspiration has a positive effect in mitigating the UHI process. It could be either that surface evapotranspiration adds moisture to the near-surface air, which simultaneously reduces the air temperature, or that the cooler surface in the parkland reduces vertical mixing, leading to higher specific humidity (or a combination of both). However, temperature changes do not perfectly correspond with humidity changes and the understanding of that component of the UHI process remains incomplete. 8. Conclusions The transition at the boundary of the urban heat island of the central urban region of the City of Adelaide, South Australia, has been investigated. There is a rather distinct commencement of the transition in UHI screen temperature at the boundary (within ~50 m) and the screen temperature continues to drop over a distance ~300 m into the park area. We have not been able to support evidence for substantial cooling into the urban area from the parkland under conditions of low wind and in the early morning period. We have shown an inverse relationship between the screen temperature and atmospheric humidity as they vary over traverses through park and urban areas and with time at fixed locations within the urban area. The detailed origin of this relationship is currently unclear but we have suggested that it reflects the role of evapotranspiration in determining local temperatures, even at night time. Acknowledgements We thank our collaborators John Bennett, Cecilia Ewenz, Vinodkumar, and Neville Wild, in particular, for their contributions to our recent studies of the Adelaide Urban Heat Island. This work was funded in part by the “Prospering in a Changing Climate” grants programme of the South Australia State Government and by the South Australian Water Corporation (2014). Declaration of Competing Interest Roger Clay and Huade Guan have no conflicts of interest for this paper. References Acero, J., Arrizabalaga, J., Kupski, S., Katzshner, L., 2013. Urban heat island in a coastal urban area in northern Spain. Theor. Appl. Climatol. 113, 137–154. Bernard, J., Rodler, A., Morille, B., Zhang, X.Y., 2018. How to design a Park and its surrounding urban morphology to optimize the spreading of cool air? Climate 6, 15. Bottyán, Z., Kircsi, A., Szegedi, S., Unger, J., 2005. The relationship between built-up areas and the spatial development of the mean maximum urban heat island in Debrecen, Hungary. Int. J. Climatol. 25, 405–418.
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Urban Climate journal homepage: www.elsevier.com/locate/uclim
The urban-parkland nocturnal temperature interface ⁎
Roger Claya,b, , Huade Guanb
T
a
School of Physical Sciences, University of Adelaide, South Australia 5005, Australia National Centre for Groundwater Research and Training, College of Science & Engineering, Flinders University, Bedford Park, South Australia 5042, Australia
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A R T IC LE I N F O
ABS TRA CT
Keywords: Urban heat island Traverse measurements Boundary effects Water vapor
An urban heat island (UHI) study has been made of the transition between an open park area and an urban environment, mainly through the use of night-time mobile traverses concentrating on still nights at cloudless times. The park areas exhibit lower temperatures than the urban areas, with little extension of the effect into the urban area. The boundary transition proves to be quite sharp at times when wind speeds are low. Through additional measurements of water vapor it was found that there is an inverse relationship between specific humidity and screen temperature along traverses. The park areas have higher humidity levels. Measurements at fixed urban locations exhibit a similar effect with evapotranspiration apparently playing a significant role.
1. Introduction The urban heat island (UHI) relates to the increased temperatures within urban environments when compared to surrounding rural temperatures (Oke, 1987; Stewart and Oke, 2012). Those urban temperature excesses vary both spatially and temporally within the urban region and are often reported to reach levels of 5 °C or more. This effect is important since, in climates which require air conditioned cooling, it can add appreciable economic costs (e.g. Guan et al., 2014). It also has appreciable costs in terms of the comfort and health of the local population (e.g. Sharifi et al., 2016). Such considerations are becoming more serious as urban areas expand and climate change results in the increase of intrinsic temperatures in many of our large-scale environments. Whilst the UHI phenomenon is understood, in general ways, to be associated with the physical properties of urban surfaces, buildings, anthropogenic heat release, and sky view factors within urban canyons, detailed studies in particular locations can add to our understanding and, potentially, point to ways of mitigating the effect. The overall thermal climate in an urban area is shaped by both regional winds and the UHI effect (Guan et al., 2016). For a total picture, both need to be considered. When found, the magnitude of the temperature excess has a positive correlation with the fraction of impermeable surface in the urban area (Park, 1986), related to the “built-up ratio” (Bottyán et al., 2005). It also correlates inversely with the sky view factors associated with urban canyons and the level of cloudiness in the sky (Zhu et al., 2013). The effect is strongest when wind speeds are low and is almost lost at wind speeds above about 3 ms−1 (Clay et al., 2016; Park, 1986). In considering how one might mitigate an urban temperature excess, it is important also to know something about its characteristic scale lengths when properties of the built urban environment vary spatially. Those length scales might be expected to depend not only on wind speed and associated turbulence scales but also length scales within the built environment such as the lengths of city blocks (Nichol and Wong, 2008). The importance of horizontal air movement in determining the local urban thermal environment of Taipei city was discussed by Chang and Li, 2014. Park et al., 2017 found evidence for measurable effects of green spaces down to areas of 300 m2 in urban blocks with rather tall
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Corresponding author at: School of Physical Sciences, University of Adelaide, South Australia 5005, Australia. E-mail addresses: [email protected] (R. Clay), huade.guan@flinders.edu.au (H. Guan).
https://doi.org/10.1016/j.uclim.2020.100585 Received 4 April 2019; Received in revised form 8 November 2019; Accepted 6 January 2020 2212-0955/ © 2020 Elsevier B.V. All rights reserved.
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buildings and Lee et al., 2009 noted the effect of tall buildings inhibiting the movement of cool air in the Seoul CBD area. Urban parks are considered to be one efficient urban heat mitigation solution (Bernard et al., 2018). The cooling effect of Chapultepec Park (500 ha) in Mexico City can reach a distance about the same as its width (2 km) (Jauregui, 1991). Measurements in the vicinity of a Beijing park (Yan et al., 2018) indicate that a large park (in their case, containing forest, lakes and wetlands) can influence urban temperatures at distances of up to 2 km from the park. In Leipzig, Jaganmohan et al. (2016) show that the influence range of park cooling varies from tens to hundreds of metres. It seems to be clear that park size is an important factor determining the park cooling effect. This is likely related to the spatial scale for efficient surface and air heat exchange. Guan et al. (2015) showed that the effective heating area for urban Adelaide was ~100 × 100 m2 and Nichol and Wong (2008) noted that small green spaces above ~1 ha in size could produce lowered surface temperatures but, at those small sizes, they do not seem to influence air temperatures along a traverse route. The effects of large parks on the spatial structure of the urban temperature distribution should be considered as they mimic, on a small scale, a rural environment (Yan et al., 2018). To assist with urban planning, the properties of the park boundaries and the dependence of local-scale air temperatures on the dimensions of parkland areas are important topics for study, as is the related extent of the influence of a park into the surrounding urban area. The differing effects of trees and shrubs, when compared to grass, within parks was emphasized by Cao et al., 2010 who proposed a park vegetation and shape index. Wind data were not provided by Yan et al. and wind might also be expected to have an influence on heat transfer in the surroundings of a green space. In the Beijing data, there seems to be a shift of the cooled region to the east of their park area which is otherwise unexplained. The results of screen temperature measurements by Yan et al. (2018) emphasized the conclusions of Du et al. (2017) who used satellite imagery to study the extent of the influence of green space areas outward from parks. This cooling influence was found at the 2 °C level out to several hundred metres from the green space. Physically, urban park cooling is considered to mainly result from surface evapotranspiration. Other factors, such as parks having a larger sky view than street blocks, and better ventilation, may contribute to the cooling effect. In climates where UHI problems are important, open park areas may be watered by the park management. The effect of such watering and vegetation evapotranspiration may be measured by recording humidity and local temperatures and a relationship is known to exist between the two (Acero et al., 2013). However, the process by which this correlation comes about has not been clearly demonstrated. It is generally understood that vegetation transpiration stops after sunset. Thus, evapotranspiration cooling would not be a significant contributor to urban park cooling at night time. However, Holmer et al. (2013) show that surface evapotranspiration continues for a couple of hours into the evening, leading to a lower temperature over the vegetated surface when compared to the surrounding area. Interestingly, this temperature difference persists whilst both surfaces continue to cool radiatively throughout the night. In their study, the sky view effect is secondary in night-time urban air cooling. The overall objective of our study is to examine the nocturnal temperature interface between parkland and urban areas. The paper examines the broad parklands which surround and are enclosed in the central business district (CBD) of the City of Adelaide, South Australia. Specific objectives are (1) to investigate characteristics of the temperature gradient variation through the urban-park interface from outside the CBD, and in parks within the CBD, and (2) determine whether nocturnal evapotranspiration contributes to park cooling. Our initial hypothesis was that the air temperature through the urban-park boundary would vary smoothly with a gradient changing only slowly through the interface, even on calm nights. We shall show that this idea was not supported in our work. The role of nocturnal evapotranspiration in any changes of that gradient was to be examined. 2. Method This study is based both on a large number (approaching 100) of night-time (early morning) traverses through the CBD, out of which a small number were selected to have clear skies and to have wind speeds which could be described as ‘calm’, and on data from an array of static sensors spaced through the area of study. Data which included screen temperatures, relative humidity, and infra-red sky temperatures were recorded. Water vapor is the most important of the greenhouses gases affecting the terrestrial climate and it is also associated with evapotranspiration cooling mechanisms for vegetation. It may well have appreciable concentration variations within a city canopy layer. As part of this work, we have begun a program to study the possible role of water vapor in the UHI. Water vapor is recorded throughout our traverses through measurements of the relative humidity. A knowledge of that parameter plus the screen temperature enables the specific humidity (g/kg) to be calculated. Upward-viewing infra-red radiometers operating at long wavelengths are sensitive to water vapor, although in a column rather than just the local vapor density. They can be used as an indicative cross-check of the variation of the vapor density as derived from the screen temperature and relative humidity data. Over the past year, we have used infra-red radiometers in conjunction with the other instrumentation for our traverses. We use two broad-band long-wave radiometers directed at elevations of 45o, one which covers the water vapor band at ~ 7 μm and an otherwise identical one which does not. The difference between their outputs is a measure of the water vapor column density, integrated, at least, over the atmospheric gases within the city canopy level. The traverse method employed here followed that which was described in some detail by Clay et al. (2016). Vehicular traverses (in the main following the route indicated in that paper) were made with screen temperature (1.5 m above ground), relative humidity, and infra-red temperatures (two radiometers most recently) being logged at 10 s intervals. The screen temperature was calibrated to 0.1 °C and the response time was ~130 ms. This technique introduces a characteristic spatial uncertainty ~50 m in general, although at important spatial points data were usually recorded with better resolution whilst the vehicle was travelling very slowly or was stationary at traffic lights. Traverses took place typically between 4 a.m. and 6 a.m., always well before sunrise. 2
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Fig. 1. Image of the central Adelaide urban area. Parkland (land cover type B, Stewart and Oke, 2012) surrounds a central built area. The southern half of that built area has a local climate zone (LCZ) classification LCZ 3. The north east quadrant, surrounding Hindmarsh Square, is classified LCZ 1. Details of the building heights are shown in the overlay. Red markers are sites of the fixed network used for Figs. 6 and 10. This paper deals particularly with the UHI transition at the point marked for the King William Street-parkland boundary, and the effect on the UHI strength of the marked ‘squares’. The most usual traverse route taken for this paper passes north from the parkland, through Hurtle Square and is shown in Clay et al., 2016. (Background image from Google Earth.) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Traverse data led us to investigate related data from the Adelaide Urban Heat Island Monitoring Network (Guan et al., 2016). This network of static temperature and relative humidity monitoring sites at a height of 4 m is centred on the CBD of Adelaide with significant extensions into the surrounding suburban areas. The central region of the City of Adelaide has an area of approximately 5 km2 and is level within 15 m altitude over a linear distance of order 2 km. It has within it five ‘squares’ with areas ranging from about 2.5–4.0 ha (Fig. 1). That central region is surrounded by ‘parklands' (land cover type B, Stewart and Oke, 2012) with widths of the order of several hundred metres (typically ~ 500 m). There are thus clear boundaries between the city area and the parklands, and at the boundaries of open areas (“squares”) within the city area, which enable us to investigate characteristic distance scales for the extent of the UHI phenomenon. The climate in Adelaide is usually described as “Mediterranean” with mild moist winters and generally hot, dry, summers. Our previous work has showed that spatial temperature structure in the urban heat island (UHI) is washed out for wind speeds above about 3 m.s−1. This work aims to investigate the form of that spatial structure, particularly at the parkland boundary, concentrating on times which are described as ‘calm’, with wind speeds recorded by the local Bureau of Meteorology typically below 1 m.s−1 and under cloudless skies.
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Fig. 2. The result of temperature measurements (‘y’ axis) along traverses from urban area (LCZ 3) to park (Local Climate Zone LCZ B) through the southern city boundary (see Fig. 5c below). The local wind speeds recorded by the Bureau of Meteorology are noted. The built area is left at 0.6 km in every case. The measurements are adjusted by the subtraction of a fixed temperature to agree at 1.3 km.
3. The urban-parkland temperature gradient at the outer boundary of the CBD We wished to examine the boundary of the extensive park area surrounding the central urban area of the City of Adelaide. We wished to know the spatial extent by which temperature changes associated with the boundary were to be found (primarily) within the park area. Fig. 2 shows representative data taken at the boundary (in this case, the King William Street-parkland boundary shown in Fig. 1). In all cases, the boundary is crossed at distance marked as 0.6 km (chosen to show data from each side of the boundary). On cloudless mornings, at times when the wind speed (as noted by the Bureau of Meteorology) is 0 m.s−1 (calm), the beginning of the clear temperature drop into the park area takes place within a characteristic distance of below ~50 m of that boundary. This effect is particularly clear in Fig. 3 for which the transition is from a local climate zone classified as LCZ 1 (Stewart and Oke, 2012). The data in Fig. 2 show a rather sharp transition from the urban CBD (LCZ 2) to the parkland area at distance 0.6 km (photograph Fig. 5c). In cases with wind recorded as “calm” (0 m.s−1), the distances travelled into the southern park areas to reach the lowest temperatures had a mean distance of 300 m. Fig. 3 shows data for a transition out of the CBD (LCZ 1) to the north. In this case, after the boundary there is an appreciable downward slope into the park area (a drop of 40 m in altitude) and we note that the temperature transition extends further for this traverse. The mean reductions in temperature as the parklands are entered are shown in Table 1, at times of no wind, for three exit locations from the built area. There is no strong evidence for an appreciable extension into the city urban area of the cooling due to the parklands. This is in contrast to evidence from Beijing (Yan et al., 2018) and Shanghai (Du et al., 2017) which show effects extending up to 2 km from large parks (with dimensions up to ~2 km in diameter in contrast to our data for the 500 m wide parkland). We note that our clearest UHI effects were for times when the wind speed was very low. This could be inhibiting the extension of the cooling to more central urban areas under the conditions for which our data were acquired. The data from Beijing and Shanghai (Yant et al. 2018 and Du
Fig. 3. As for Fig. 2 but exiting the urban area (Local Climate Zone LCZ 1) to the north into parkland (Local Climate Zone LCZ B) through a downward slope of a total of 40 m over a distance c. 500 m. The built area is left at 0.6 km. 4
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Table 1 Full temperature reductions when transiting from the built area into parklands on clear, still mornings (the magnitude of the UHI boundary). Exiting South
4.2 +/− 0.8 °C
(27 entries)
Exiting West Exiting North
5.5 °C 4.2 +/− 0.4 °C
(1 entry) (4 entries)
Fig. 4. Screen temperatures measured in a traverse through Hindmarsh Square (between distances 0.6 and 0.8 km) at 05:00 11 March 2018. The route passes through an area with relatively low buildings (2 stories) before the Square and then enters a “canyon” region after the Square (see also Fig. 5).
Table 2 Average temperature reductions on passing from the built area into City squares. The reduction to the lowest temperature in each square is shown as a fraction of the reduction found at the parkland boundary for that traverse.
Hindmarsh square Hurtle square Light square Victoria square
Approximate
Fractional
Dimensions
Temperature drop
145 145 120 100
× × × ×
230 230 220 240
m m m m
0.19 ± 0.02 0.10 ± 0.005 0.1 0.056 ± 0.003
(8 (8 (1 (7
entries) entries) entry) entries)
et al., 2017) suggest a transition effect outside the park area of ~2 °C which extends to some hundreds of metres into the urban area. Our data do not show this effect and their transition into the park is quite clear, with a clear change in the gradient of the temperature curve at the interface. Any effect of air temperature variations in the urban area is at a level below 1 °C for times when the wind speeds were very low. As we have noted before (Clay et al., 2016), and to be seen in Fig. 2, data for times when wind speeds are above 2–3 m.s−1 show little transition effect at the boundary. However, it is possible that those higher wind speeds do cause mixing between air in the parkland and the city areas such as may be suggested by the progressive temperature change before the transition at 0.6 km for the dataset in Fig. 2 corresponding to a wind speed of 3 m.s−1.
4. The urban-parkland temperature gradient within city squares The five squares within the Adelaide CBD have dimensions comparable to, or somewhat less than, the spatial scales of temperature change discussed above for transitions extending into the parklands. Four of the squares have been examined within our traverses. Fig. 4 shows one of those traverses, with the route passing through the center of Hindmarsh Square (see location in Fig. 1, LCZ B) at distance 0.7 km. The route travels north through relatively low buildings (LCZ 3) to reach the square at distance 0.6 km and then passes through the Square, entering a high rise “canyon” (LCZ 1) to the west at distance 0.8 km. The average magnitudes of screen temperature reductions for traverses through four squares are presented in Table 2. Whilst the temperature drops in the squares were close to limitations set by the sensor accuracy (as may be seen in Fig. 4), averaged data allow mean temperature reductions to be derived with the uncertainties in Table 2. Those small reductions are in contrast with the five to ten times larger reductions at the urban-parkland boundary. The internal distances to the centers of these squares are no larger than the distance scales found in which the parkland UHI temperatures are reduced by 30%. Given that the parklands have a considerable lateral extent to the side of the traverses, whilst the 5
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Fig. 5. Photographs of (a) Hindmarsh Square, (b) Victoria Square, and (c) the Parkland transition point (King William St and South Terrace). Photo credits: (a), (c) R. Clay; (b) H. Guan. (a) Hindmarsh Square, facing west. (b) Victoria Square, facing south. (c) Parkland transition point (King William St and South Terrace), facing north.
squares have two modest sized dimensions in comparison, it is probably not surprising to find that the temperature reductions in the squares are rather small. On the other hand, there does seem to be a difference in the depth of the temperature drop amongst the squares so it may be that other parameters, such as the surface of the squares, vegetation, and watering patterns are also important. Fig. 5 includes photographs of the Hindmarsh and Victoria squares in which it can be seen that the surface treatment and its likely watering are quite different.
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Fig. 6. Diurnal temperature variations averaged over one month (25 Feb-26 Mar 2015, measured at 4 m above ground) at four fixed sites (blue parkland (345 m from the city boundary); red – boundary between the parkland and the city; yellow and green – progressively further inside the city area). The site locations are shown by red markers in Fig. 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 7. Data from a traverse through parkland into the city area, and then out into parklands. Shown are screen temperature (purple), water vapor density (red, derived from the relative humidity) and an infra-red measure (blue, arb. units) of the water vapor column density. (10 March 2018). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
5. Diurnal variation of the temperature through a parkland-city boundary The data discussed above were taken typically in the time range 04:00 to 06:00 local standard time. The variation of temperatures over full 24 h periods can be extracted from data recorded at fixed city sites by the Adelaide Urban Heat Island Monitoring Network (Guan et al., 2016). An example is shown in Fig. 6. The results corresponding to the traverse data discussed above are in the early morning period (04,00–06:00). The transition from the city area to the parkland (from red to blue lines) is clear at all times, as is the lack of a temperature change between the boundary and the internal city areas (red, green, yellow). The city areas are classified as LCZ 3 with rather little physical reduction in sky view factor (SVF: blue 0.99, red 0.97, yellow 0.84, green 0.91). There is the clearest parkland-city transition at times from late morning to evening when the parkland data (blue) show a substantial reduction in temperature compared to the city. This variation does not seem consistent with a sky view factor effect and we interpret this to be a result of strong evapotranspiration effects in the parkland at the hottest times of day. Holmer et al. (2013) reported a persistent temperature difference between vegetated and surrounding areas whilst cooling through the night (“Phase 2”) following site-dependent cooling around sunset (“Phase 1”) which they relate to evening evapotranspirative cooling (EEC). Phase 2 can be seen clearly in Fig. 6 between 22:00 h and 05:00 h, as can phase 1 which, in our case, persists somewhat longer than found by Holmer et al. 6. Water vapor at the urban-park boundary Fig. 7 shows results from a city (parkland to urban area to parkland) traverse in which the screen temperature (purple) and 7
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Fig. 8. The relationship between specific humidity and temperature for a traverse through parklands and the city area (10 March 2018).
specific humidity (red) data are presented. There is an apparent inverse correlation between these two parameters. Fig. 7 also shows a measure of humidity derived from infra-red radiometer measurements (blue - arbitrary units). The same sort of relationship is found as with a more direct measure of specific humidity except that the infra-red data are noisy (they are the difference of two signals) and their changes at the parklands are not abrupt. The latter is due to the radiometers viewing at an elevation of 45o and so integrating over a substantial lateral distance. This supports the result, from data using the relative humidity sensor, that water vapor density is changing through the urban heat island inversely with screen temperature. This relationship is shown explicitly in Fig. 8. The data show that parkland areas have lower temperatures and higher humidity than the central City areas. A natural assumption is that vegetated areas offer more opportunities for transpiration and evaporation than a (largely) impervious urban environment. We can also see the effect of water vapor using data recorded at fixed locations in the central city area with the Adelaide Urban Heat Island Monitoring Network (Guan et al., 2016). These data are shown in Fig. 9 which shows relationships between screen temperature (measured), and specific humidity (derived from temperature and relative humidity measurements) for three single day subsets of those data. There is again an inverse relationship between temperature and humidity and we note that there is a similar rate of temperature decrease with specific humidity as for the traverse. A naive interpretation might be that evapotranspirational cooling decreases the temperature and leads to an increase in the ambient vapor density, but such cause and effect has not yet been demonstrated. Clear relationships such as those in Fig. 8 are not found in some other days with different synoptic weather conditions. In Fig. 6, we showed temperature data from four fixed sites and speculated that there was an evapotranspiration effect even at an urban site, particularly onwards from late morning. Fig. 10 shows specific humidity data corresponding to the temperature data in Fig. 6 (same four sites, same times). There is clear evidence for an increase in specific humidity for two sites at the times (10:00–16:00) when the parkland temperatures are lowest compared to the temperatures of city locations. However, in this case, we note that the measurements of specific humidity at the boundary follow the parkland humidity rather than that of the city area. This is in contrast with the properties of the boundary temperature which, as we saw, follows the city temperature.
7. Discussion We have examined mainly night-time data at the boundary between parkland and a built city area. Our first objective was to investigate the temperature gradient variation through the urban-park interface. Our initial hypothesis had been that the air temperature would vary smoothly with a gradient which changed only slowly through the interface, even on calm nights. This did not prove to be the case. We find a sharp temperature transition with a break within ~50 m of the boundary (the spatial resolution of our measurements). At times of low wind, from the boundary location and travelling inwards into the city, there is little temperature change (Figs. 2 and 3 for distances below 0.6 km). In the more open parkland area, the temperature reduces with distance from the boundary with a characteristic scale of some hundreds of meters. These low wind speed data are in contrast to observations presented from parks at other sites, which were obtained under less fixed conditions. It appears likely that wind speeds above about 2 m.s−1 do cause mixing through the boundary and may be the source of the apparent discrepancy. The significant scale lengths associated with temperature changes in the parkland area probably result in the lack of substantial temperature reductions in the city open spaces (city squares), which have characteristic dimensions of 100–200 m. It would seem that, to be effective, open spaces need to have dimensions greater than, or the order of, 500 m. Our second objective related to the possible role of nocturnal evapotranspiration in the cooling of parkland. We have shown that 8
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Fig. 9. Three single day measurements relating humidity and screen temperature, made at a location in the central city area.
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Fig. 10. The average 24 h variation in specific humidity, measured at 4 m above ground (25 Feb-26 Mar 2015) at the four sites (red markers in Fig. 1) whose temperatures are shown in Figs. 6. (blue – parkland (345 m from the city boundary); red – boundary between the parkland and the city; yellow and green – progressively further inside the city area). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
the measured temperature variations have an inverse association with the specific humidity in the vicinity of the temperature measurements. This is found both over a short time interval for a range of locations along a traverse, and over an extended period for a fixed location. Thus, we found (Figs. 8 and 9) a quantitative relationship between air temperature and specific humidity which is similar across space and time, showing 3–4 degree cooling with 1 g/kg increase in specific humidity. Although not definite, this relationship supports the possible hypothesis of an effect of surface evaporation cooling, even in night time. Figs. 6 and 10 show particularly large differences in air temperature between park and urban areas at times when there are large specific humidity differences. This would also seem to support the idea that evapotranspiration has a positive effect in mitigating the UHI process. It could be either that surface evapotranspiration adds moisture to the near-surface air, which simultaneously reduces the air temperature, or that the cooler surface in the parkland reduces vertical mixing, leading to higher specific humidity (or a combination of both). However, temperature changes do not perfectly correspond with humidity changes and the understanding of that component of the UHI process remains incomplete. 8. Conclusions The transition at the boundary of the urban heat island of the central urban region of the City of Adelaide, South Australia, has been investigated. There is a rather distinct commencement of the transition in UHI screen temperature at the boundary (within ~50 m) and the screen temperature continues to drop over a distance ~300 m into the park area. We have not been able to support evidence for substantial cooling into the urban area from the parkland under conditions of low wind and in the early morning period. We have shown an inverse relationship between the screen temperature and atmospheric humidity as they vary over traverses through park and urban areas and with time at fixed locations within the urban area. The detailed origin of this relationship is currently unclear but we have suggested that it reflects the role of evapotranspiration in determining local temperatures, even at night time. Acknowledgements We thank our collaborators John Bennett, Cecilia Ewenz, Vinodkumar, and Neville Wild, in particular, for their contributions to our recent studies of the Adelaide Urban Heat Island. This work was funded in part by the “Prospering in a Changing Climate” grants programme of the South Australia State Government and by the South Australian Water Corporation (2014). Declaration of Competing Interest Roger Clay and Huade Guan have no conflicts of interest for this paper. References Acero, J., Arrizabalaga, J., Kupski, S., Katzshner, L., 2013. Urban heat island in a coastal urban area in northern Spain. Theor. Appl. Climatol. 113, 137–154. Bernard, J., Rodler, A., Morille, B., Zhang, X.Y., 2018. How to design a Park and its surrounding urban morphology to optimize the spreading of cool air? Climate 6, 15. Bottyán, Z., Kircsi, A., Szegedi, S., Unger, J., 2005. The relationship between built-up areas and the spatial development of the mean maximum urban heat island in Debrecen, Hungary. Int. J. Climatol. 25, 405–418.
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