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Figure 3.6: Locations of Met Office weather stations in the South-East of England (taken from www.metoffice.gov.uk) No data on the energy balance was found to use to validate the model results. Data from the Heathrow MIDAS station was also analysed in order to select the case studies during summer i.e. June-July-August (JJA) and winter i.e. December-January- February (DJF) to be simulated for the model evaluation (see Chapter 5). 84
3.6 Summary In this PhD study the mesoscale model METRAS is used together with the urban canopy parameterisation scheme (BEP) developed by Martilli et al. (2002) in order to simulate the effects of urban land cover for the city of London. This Chapter presents an overview of the mesoscale model METRAS. The model equations are described, and the boundary conditions used in this study are presented. The initialisation process for setting up model simulations is also explained. The Martilli urban scheme (BEP) computes both the dynamic and thermodynamic effects of the urban surface. The scheme and its implementation are described in this Chapter, together with an analysis of the computational demand of the new METRAS+BEP modelling system. A number of different data sources were used to set up the domains for simulation and to initialise and run the model. Land cover data from the CEH Land Cover Map 2000, and orography data from the US Geological Survey, were used to set up model domains for the simulations. UK Met Office meteorological data from radiosondes and weather stations was used to initialise the model and to validate model results respectively. Urban parameters derived from the literature were used as an input to the BEP urban canopy scheme. Any additional information which is specific to the simulations presented in each of the Results Chapters is contained therein for reasons of clarity. 85
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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
Page 47 and 48: the vertical distribution of vegeta
Page 49 and 50: using different building parameters
Page 51 and 52: Table 2.2: SWOT analysis for the ME
Page 53 and 54: Fraction of urban land cover [%] Fi
Page 55 and 56: The built up area of London can cur
Page 57 and 58: Figure 2.5(a-f): Builtup area of Lo
Page 59 and 60: • Mainly high density development
Page 61 and 62: climate of London, and currently on
Page 63 and 64: For mid-latitude cities, of which L
Page 65 and 66: warming of 0.04 °C per decade, in
Page 67 and 68: out differences in the urban heat i
Page 69 and 70: adopted in previous studies ranges
Page 71 and 72: y the implementation of a specific
Page 73 and 74: A prognostic equation is used to re
Page 75 and 76: At the surface the temperature is c
Page 77 and 78: The boundary conditions used for th
Page 79 and 80: are defined in the file m1tini_TAPE
Page 81 and 82: The terms representing the impact o
Page 83 and 84: 3.2.1 Calculation of dynamical effe
Page 85 and 86: θ k ∆z / 2 H Siu (Equation 3.12)
Page 87 and 88: 3.3 Implementation of BEP in METRAS
Page 89 and 90: difficulties in the linking of the
Page 91 and 92: Table 3.3: Description of how the 2
Page 93 and 94: 3.5.2 Orography data Orography data
Page 95 and 96: epresenting suburban development a
Page 97: Table 3.7 shows a summary of the MI
Page 101 and 102: temperature, air pressure and air d
Page 103 and 104: Potential temperature [K] Figure 4.
Page 105 and 106: Wind speed [ms -1 ] Figure 4.2: Ver
Page 107 and 108: 4.2.1 Horizontal cross sections of
Page 109 and 110: affected, as the flow bends around
Page 111 and 112: Downwind of the city on the other h
Page 113 and 114: the city, which is expected since t
Page 115 and 116: Potential temperature [K] Figure 4.
Page 117 and 118: simulation this effect is verticall
Page 119 and 120: differences are expected during day
Page 121 and 122: tend to cool the surface, but can a
Page 123 and 124: Figure 4.15 shows the vertical prof
Page 125 and 126: appropriate value for these paramet
Page 127 and 128: 0.61) and that of conventional grav
Page 129 and 130: Difference in potential temperature
Page 131 and 132: educed near surface temperatures of
Page 133 and 134: 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
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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
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the model. The smaller percentage o
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Wind speed (ms -1 ) Wind direction
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London Heathrow Airport (LHR) Wind
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A full set of hourly wind speed and
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contain both roofs exposed to direc
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Chapter 6: The effects of urban lan
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simulations with two hypothetical s
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dependent on the r(i,j), the radial
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centre of the domain was more than
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6.2 Effects of the current state of
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During daytime the shape of the are
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The calculation was performed for t
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ecause finding a rural reference po
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development (GLA 2006) and differen
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6.2.4 Wind speed and direction Klai
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Wind speed and direction (ms -1 ) F
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“urban” cells to be affected by
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the urban surface. Many other studi
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eason the near surface potential te
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Mean potential temperature at 12:00
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where A(x) is the area affected by
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Table 6.8: REI for the RADIUS, DENS
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COMBINED series also show a reducti
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for all runs in the series, and cor
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The runs are then combined into one
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to be more linear than the smaller
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The total reduction in mean wind sp
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The REI showed that for all the var
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Higher temperatures in the urban ar
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Over the next ten years the populat
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7.1.1 EXPANSION series The first sc
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Another cause of this form of expan
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7.2 Effects of urbanisation for the
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Mean near surface potential tempera
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UHI intensity (K) 4 3.5 3 2.5 2 1.5
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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
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Therry, G. and P. Lacarrere (1983).
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Yague, C., E. Zurita and A. Martine
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