Conclusion

Introduction

Predicting urban dome in the cityXiaoxue Wang, Yuguo Li

Department of Mechanical Engineering, The University of Hong Kong

References

Urban Heat Island Circulation (UHIC), also referred to

as urban dome, influences the transport of heat and

moisture, and air motion in both urban and rural areas.

Detailed simulation of the urban dome is very limited

by either mesoscale or microscale models due to their

own limitations. A modified City-Scale CFD approach

(csCFD) is proposed to simulate it in fine grid (e.g. 20

m).

Ideal 2D cases with or without building clusters’ effect

were simulated by csCFD to find out the influence of

the city in urban dome.

The wind environment around a building during the

evolution of urban dome is also shown.

0

11 ln 1

g z

z R T

Compared with traditional CFD, csCFD

1. The simulated vertical profiles agree reasonably well with other data in literature[4].

The simulated results by csCFD agrees well with other data in literature.

When the city is introduced by porous media, the velocity in the city decreases, the neck of

the plume increases, and multi-upward flows are observed.

Dense city also increases the relative reverse height at the edge of the city.

The wind environment abound a building in the city was simulated simultaneously with the

evolution of urban dome.

Relative reverse height (RRH)=Reverse height

Reference height

Methodology

Results

Porous model

~ 105 m

Porous model

Building details resolved

~ 103 m

~ 101 m

Meso-scale

City-scale

Micro-scale

Figure 2. The structure of csCFD.

-2 -1 0 1 2 30

1

2

3

z/z i

u/UD

Flat city ()

Porous city ()

Porous city (=0.5)

Flat city (Theory)

Flow reverse height

Reference

height

Figure 7. Hourly mean velocity vectors and streamlines near the building at different hours.

Figure 3. Simulated scaled (a) vertical temperature, (b)

horizontal wind speed at the city edge and (c) the vertical

wind speed at the city center with data in the literature.

;z

nw e w

;z

p np e p

Figure 1. The original and transformed height.

Other relations between transformed variables ( )

and the original variables ( ) are[1]:n

;nT T z

)0 1 z

n e

;nu u

;nv v

Not to scale

x

z

Constant heat flux

(city)

50 m

Constant heat flux

(rural)

Figure 4. The sketch of the computational domain. The

grey shadow area is the city area (if needed). The

porosity of the city is set to 0.75 here.

-2 -1.5 -1 -0.5 0 0.5 1 1.5 20

500

1000

1500

2000300 301 302 303 304 305 306 307 308 309 310 311 312

x/D

Hei

ght

(m)

Potential temperature

-2 -1.5 -1 -0.5 0 0.5 1 1.5 20

500

1000

1500

2000300 301 302 303 304 305 306 307 308 309 310 311 312

Potential temperature

x/D

Potential temperature

Hei

ght

(m)

2. City’s effect lead to wider neck of the plume, smaller velocity in the city and multi-upward

flows.

Hei

ght

(m)

x/D

Figure 6. The analytical solution and predicted data of the scaled horizontal velocity at the edge of the city.

Table 2 The RRH value in different cases

Caseϕ=1.0

(Theory)

ϕ=1.0

(Flat city)ϕ=0.75 ϕ=0.5

RRH 39.5% 42.6% 50.3% 51.3%

Figure 5. The contour maps of potential temperature in (a) flat and (b) porous city and vectors in (c) flat and (d)

porous city at quasi-steady state.

Increase

[1] Kristóf, G., Rácz, N. and Balogh, M. (2009) "Adaptation of pressure based CFD solvers for

mesoscale atmospheric problems", Boundary-Layer Meteorology, 131, 85-103.

[2] Durran, D.R. and Klemp, J.B. (1983) "A compressible model for the simulation of moist

mountain waves", Monthly Weather Review, 111, 2341-2361.

[3] Hang, J. and Li, Y. (2010) "Wind conditions in idealized building clusters: macroscopic

simulations using a porous turbulence model", Boundary-Layer Meteorology, 136, 129-159.

[4] Catalano, F., Cenedese, A., Falasca, S., and Moroni, M. (2012). Numerical and

experimental simulations of local winds. In National Security and Human Health Implications

of Climate Change (pp. 199-218). Springer Netherlands.

)1

1 zh e

2) Add mesoscale terms

3) Improve numerical stability by adding

absorbing layer[2]

4) Model city scale effect by adding porous

turbulence model[3]

1) Use KRB coordinate

Basic principle: the pressure gradient in the

reference state in a layer of original and the

transformed height should be the same.

0 2 4 6 8 10

0

2

4

6

8

10

0 2 4 6 8 10

0

2

4

6

8

10

Ori

gin

al h

eig

ht

(z)

(km

)

Horizontal dimension (km)

KR

B c

oo

rdin

ate

hei

gh

t (h

) (k

m)

Horizontal dimension (km)

0 1 2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

-1 0 1 0 10 20 30z/

z i(T-T

a)/T

m

u/uD

(c)(b)(a)

w/WD

This study

Catalano et al. (2012) (Sim1)

Catalano et al. (2012) (Sim2)

Catalano et al. (2012) (Exp1)

Catalano et al. (2012) (Exp2)

Kristof et al. (2009)

Kurbatskii (2001)

Cenedese and Monti (2003)

Lu et al. (1997)

x

Hei

ght

(m)

0 50 100 1500

50

100

1501m/s

(m) x

Hei

ght

(m)

0 50 100 1500

50

100

1501m/s

(m) x

Hei

ght

(m)

0 50 100 1500

50

100

1501m/s

(m) x

Hei

ght

(m)

0 50 100 1500

50

100

1501m/s

(m)

x

Hei

ght

(m)

0 50 100 1500

50

100

1501m/s

(m)

3. When the porosity of the city decreases, the relative reverse height increases.

4. Wind environment around a building in the city was first dominated by the plume generated

by itself, but finally was dominated by the urban dome during the evolution of urban dome .

(a) (b)

(c) (d)

Hei

ght

(m)

x/D

(d)

(a) 7:00 (b) 8:00 (c) 9:00 (d) 10:00 (e) 11:00

Croucher Advanced Study

Institute 2015-2016: Changing

Urban Climate & the Impact

on Urban Thermal

Environment and Urban Living