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at 04:00 is (1.29 ± 0.33) K, and at 12:00 it is (0.75 ± 0.29) K. The conversion of rural land cover to urban land cover has caused an increase in the spatially averaged near surface potential temperature across the domain, both during daytime and night time. During night time 82% of the grid cells show a change greater than 1 K with respect to the rural domain, compared with 20% during daytime. These increases can be compared to results for other numerical studies, for example Lee et al. (2008) found an increase of 1.5 K for the rapid urbanisation over 40 years of the Daegu region in Korea, Wang et al. (2007) also found increases for the 2-d averaged temperature of 1.5 K during night time and 0.8 K during daytime due to urbanisation in the Pearl Delta region on China, and Lamptey et al. (2005) found an increase of more than 1 K over urban sites due to urbanisation in the North- Eastern US. 6.2.2 Diurnal temperature range (DTR) Diurnal temperature range is a meteorological indicator which can be associated with climate change and urbanisation (Easterling et al. 1997; Kalnay et al. 2003). Gallo et al. (1996) found that changes in the predominant land use or land cover conditions could significantly affect the climatological DTR. The DTR was calculated for each grid cell (i,j) in the domain by subtracting the minimum diurnal temperature (Tmin_diurnal) from the maximum diurnal temperature (Tmax_diurnal), as described in Equation 6.2. DTR(i,j) = Tmax_diurnal (i,j) - Tmin_diurnal(i,j) (Equation 6.2) 172
The calculation was performed for the base case with current urban land cover (URB_BASE) and the case with no urban surface (NOURB) for the second day of simulation. The difference in the DTR due to the urban effect was calculated by subtracting the DTR for the urbanised run from that of the rural run for each grid cell. A reduction in the DTR due to the urban area was observed across the entire domain, with an average of (-0.74 ± 0.31) K. The reduction in the DTR is due to changes in both the maximum and minimum diurnal temperatures. In particular an increase in the minimum diurnal temperature was observed across the entire domain, with an average increase of (1.31 ± 0.30) K. The difference in the maximum diurnal temperature showed a smaller variation, with an average increase of (0.57 ± 0.19) K. The main reason for the increase in the minimum diurnal temperature is the increased heat capacity which leads to increased storage during daytime, which leads to increased release of heat at night time. Other reasons could include the lower albedo of urban surface (where applicable – this might not always be the case, and could be offset by greater reflectivity between buildings), which causes greater energy absorption during the day; less surface water which prevents evaporative cooling; lower latent heat compared to rural areas during the night and higher night time sensible heat fluxes due to anthropogenic heat sources. All these are known to contribute to raising minimum night time temperatures, and to the UHI phenomenon. The increase in the maximum diurnal temperature in the urban area is primarily due to the effect of the building geometry on the radiation terms of the surface energy balance 173
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MODELLING THE IMPACT OF URBANISATIO
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Abstract Urban areas have well docu
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Abbreviations aLMo Meteo Swiss oper
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4.2.2 Impact of the urban area on t
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List of figures Figure 2.1: Scales
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Figure 4.21: Diurnal variation of t
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Figure 6.16: Mean horizontal wind s
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Chapter 1: Introduction Urban areas
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with trends derived from a statisti
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scheme, and therefore it was necess
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The effects of future urban expansi
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2.1 Urban climate modification Urba
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latitudes (Taha 1997), and this is
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100 - 200 m 1 - 2 km 10 - 20 km 100
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epresentatively sample the underlyi
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over the city centre, convergent fl
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Cold islands can also occur in urba
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of the atmosphere. For example, it
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amount of solar radiation absorbed
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(Peterson 1969; Changnon 1992; Coll
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2.3 Justification of modelling appr
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Trusilova (2006) carried out a stud
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constant flux surface layer in the
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the vertical distribution of vegeta
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using different building parameters
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Table 2.2: SWOT analysis for the ME
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Fraction of urban land cover [%] Fi
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The built up area of London can cur
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Figure 2.5(a-f): Builtup area of Lo
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• Mainly high density development
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climate of London, and currently on
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For mid-latitude cities, of which L
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warming of 0.04 °C per decade, in
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out differences in the urban heat i
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adopted in previous studies ranges
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y the implementation of a specific
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A prognostic equation is used to re
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At the surface the temperature is c
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The boundary conditions used for th
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are defined in the file m1tini_TAPE
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The terms representing the impact o
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3.2.1 Calculation of dynamical effe
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θ k ∆z / 2 H Siu (Equation 3.12)
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3.3 Implementation of BEP in METRAS
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difficulties in the linking of the
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Table 3.3: Description of how the 2
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3.5.2 Orography data Orography data
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epresenting suburban development a
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Table 3.7 shows a summary of the MI
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3.6 Summary In this PhD study the m
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temperature, air pressure and air d
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Potential temperature [K] Figure 4.
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Wind speed [ms -1 ] Figure 4.2: Ver
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4.2.1 Horizontal cross sections of
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affected, as the flow bends around
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Downwind of the city on the other h
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the city, which is expected since t
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Potential temperature [K] Figure 4.
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simulation this effect is verticall
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differences are expected during day
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tend to cool the surface, but can a
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Figure 4.15 shows the vertical prof
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appropriate value for these paramet
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0.61) and that of conventional grav
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Difference in potential temperature
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educed near surface temperatures of
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fraction was increased in steps of
Page 135 and 136: works. In the control simulation th
Page 137 and 138: characterised by the albedo, therma
Page 139 and 140: is higher by a similar amount. The
Page 141 and 142: (a) Potential temperature [K] (c) T
Page 143 and 144: Figure 4.25 shows the vertical sect
Page 145 and 146: tests also reproduced well document
Page 147 and 148: Chapter 5: Evaluation of the urbani
Page 149 and 150: Fraction of urban land cover [%] Fi
Page 151 and 152: For the summers of 1995-2000 the an
Page 153 and 154: Table 5.2: Selected periods of simu
Page 155 and 156: commonly used as a rural reference
Page 157 and 158: newly urbanised version of the METR
Page 159 and 160: adiation trapping in the street can
Page 161 and 162: the second day of simulation (31 st
Page 163 and 164: Air temperature ( o C) 35 30 25 20
Page 165 and 166: the model. The smaller percentage o
Page 167 and 168: Wind speed (ms -1 ) Wind direction
Page 169 and 170: London Heathrow Airport (LHR) Wind
Page 171 and 172: A full set of hourly wind speed and
Page 173 and 174: contain both roofs exposed to direc
Page 175 and 176: Chapter 6: The effects of urban lan
Page 177 and 178: simulations with two hypothetical s
Page 179 and 180: dependent on the r(i,j), the radial
Page 181 and 182: centre of the domain was more than
Page 183 and 184: 6.2 Effects of the current state of
Page 185: During daytime the shape of the are
Page 189 and 190: ecause finding a rural reference po
Page 191 and 192: development (GLA 2006) and differen
Page 193 and 194: 6.2.4 Wind speed and direction Klai
Page 195 and 196: Wind speed and direction (ms -1 ) F
Page 197 and 198: “urban” cells to be affected by
Page 199 and 200: the urban surface. Many other studi
Page 201 and 202: eason the near surface potential te
Page 203 and 204: Mean potential temperature at 12:00
Page 205 and 206: where A(x) is the area affected by
Page 207 and 208: Table 6.8: REI for the RADIUS, DENS
Page 209 and 210: COMBINED series also show a reducti
Page 211 and 212: for all runs in the series, and cor
Page 213 and 214: The runs are then combined into one
Page 215 and 216: to be more linear than the smaller
Page 217 and 218: The total reduction in mean wind sp
Page 219 and 220: The REI showed that for all the var
Page 221 and 222: Higher temperatures in the urban ar
Page 223 and 224: Over the next ten years the populat
Page 225 and 226: 7.1.1 EXPANSION series The first sc
Page 227 and 228: Another cause of this form of expan
Page 229 and 230: 7.2 Effects of urbanisation for the
Page 231 and 232: Mean near surface potential tempera
Page 233 and 234: UHI intensity (K) 4 3.5 3 2.5 2 1.5
Page 235 and 236: temperature, an increase in the mea
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7.2.3 Wind speed The effect of the
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7.3 Effects of urbanisation for the
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mean near surface potential tempera
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7.3.2 Wind speed Changes in the mea
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expansion strategies such as the re
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should also be considered to avoid
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models, for example Martilli et al.
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cities (Baker et al. 2002). Already
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uses, painting the roofs white to r
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The full influence of different met
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References Abercrombie, P. (1945).
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Bottema, M. (1997). "Urban Roughnes
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Craig, K. J. and R. D. Bornstein (2
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Grimmond, C. S. B. and T. R. Oke (2
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Jin, M. and J. M. Shepherd (2005).
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Lemonsu, A. and V. Masson (2002). "
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Nitis, T., Z. B. Klaic and N. Mouss
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alance in urban areas - Recent adva
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Seaman, N. L. (2000). "Meteorologic
Page 275 and 276:
Therry, G. and P. Lacarrere (1983).
Page 277:
Yague, C., E. Zurita and A. Martine
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