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Figure 6.16 shows the same results for 04:00. The COMBINED series again shows a very similar form to the RADIUS series, and all series show a linear reduction in the mean wind speed at 04:00 with the increase in the mean urban land cover. The R 2 values range from 0.98 to 0.99. Mean wind speed at 04:00 am (ms-1) 2.5 2.0 1.5 1.0 0.5 y = -3.1531x + 2.3063 R 2 = 0.9962 y = -2.1346x + 2.0615 R 2 = 0.9833 y = -2.6221x + 2.3512 R 2 = 0.9873 0.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Mean urban land cover fraction COMBINED SERIES RADIUS SERIES DENSITY SERIES Figure 6.16: Mean horizontal wind speed at z = 10 m as a function of the mean urban land cover fraction for the RADIUS, DENSITY and COMBINED series of model runs, at 04:00 of the second day of simulation. For both daytime and night time, the COMBINED series, whilst spanning a much smaller range of land cover fractions, shows a very similar form to the RADIUS series, which suggests that the change in urban land cover density of the COMBINED series compared to the RADIUS series has a less important effect compared to the increase in the radial size of the city. In general the mean wind speed is smaller for the DENSITY series, which represents a larger city size, compared to simulations from the RADIUS series with a similar mean urban land cover fraction. 202
The total reduction in mean wind speed in the DENSITY and COMBINED series, at night time, is 16%, which can be compared to the reduction of 29% in the RADIUS series. During daytime the COMBINED series shows a reduction of 7%, compared to a reduction of 12% for the DENSITY series and of 21% for the RADIUS series shows a reduction of 21%. These % reductions are comparable with those in Klaic et al. (2002), who found an average wind speed reduction of 8% and 18% for two simulations which represented small increases in the urban area by 12.5% and 37.5%. They are also comparable with Wang et al. (2007) who simulated a 20% reduction in wind speed due to urbanisation in the Pearl Delta region, China. 203
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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
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works. In the control simulation th
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characterised by the albedo, therma
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is higher by a similar amount. The
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(a) Potential temperature [K] (c) T
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Figure 4.25 shows the vertical sect
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tests also reproduced well document
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Chapter 5: Evaluation of the urbani
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Fraction of urban land cover [%] Fi
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For the summers of 1995-2000 the an
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Table 5.2: Selected periods of simu
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commonly used as a rural reference
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newly urbanised version of the METR
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adiation trapping in the street can
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the second day of simulation (31 st
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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 and 186: During daytime the shape of the are
Page 187 and 188: The calculation was performed for t
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: to be more linear than the smaller
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
Page 237 and 238: 7.2.3 Wind speed The effect of the
Page 239 and 240: 7.3 Effects of urbanisation for the
Page 241 and 242: mean near surface potential tempera
Page 243 and 244: 7.3.2 Wind speed Changes in the mea
Page 245 and 246: expansion strategies such as the re
Page 247 and 248: should also be considered to avoid
Page 249 and 250: models, for example Martilli et al.
Page 251 and 252: cities (Baker et al. 2002). Already
Page 253 and 254: uses, painting the roofs white to r
Page 255 and 256: The full influence of different met
Page 257 and 258: References Abercrombie, P. (1945).
Page 259 and 260: Bottema, M. (1997). "Urban Roughnes
Page 261 and 262: Craig, K. J. and R. D. Bornstein (2
Page 263 and 264: Grimmond, C. S. B. and T. R. Oke (2
Page 265 and 266: Jin, M. and J. M. Shepherd (2005).
Page 267 and 268:
Lemonsu, A. and V. Masson (2002). "
Page 269 and 270:
Nitis, T., Z. B. Klaic and N. Mouss
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alance in urban areas - Recent adva
Page 273 and 274:
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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