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Calculation of wind in a Tokyo urban area with a mesoscale model including a multi-layer urban canopy model
ARTICLE IN PRESS
Journal of Wind Engineering and Industrial Aerodynamics 96 (2008) 1655–1666 www.elsevier.com/locate/jweia
Calculation of wind in a Tokyo urban area with a mesoscale model including a multi-layer urban canopy model Hiroaki Kondoa,, Takayuki Tokairinb, Yukihiro Kikegawac a
National Institute of Advanced Industrial Science and Technology, Research Institute for Environmental Management Technology, AIST-west, 16-1, Onogawa, Tsukuba 305-8569, Japan b Toyohashi University of Technology, 1-1, Hibarigaoka, Tempaku-cho, Aichi, Japan c Meisei University, 2-1-1, Hodokubo, Hino, Tokyo, Japan Available online 18 April 2008
Abstract The wind velocity in an urban area calculated with a mesoscale meteorological model without an urban canopy model is often overestimated, even when a large value of aerodynamic roughness is specified on the surface. In this paper, the results of a mesoscale model combined with a multi-layer urban canopy model are compared to those of a model without an urban canopy model and with observations. The mesoscale model used here is the AIST-MM. The model is twice-nested, and a 2 km grid is used in the inner model. The model was applied in the vicinity of Tokyo, Japan, and a multi-layer canopy model was combined into 145 grids of the 23-ward area of Tokyo in the inner model. The wind velocity calculated with the urban canopy model is significantly improved near the tops of high buildings and near ground level in residential areas. r 2008 Elsevier Ltd. All rights reserved. Keywords: Mesoscale model; Urban surface wind; Multi-layer urban canopy model; Tokyo; Automated meteorological data acquisition system
Corresponding author. Tel.: +81 29 861 8305; fax: +81 29 861 8358.
E-mail address: [email protected] (H. Kondo). 0167-6105/$ - see front matter r 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jweia.2008.02.022
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1. Introduction Many meteorological models have been developed to analyze the mesoscale and local meteorology in urban areas, and the target scale of such models has become progressively smaller. To analyze the fine structure of the wind and temperature field, it is necessary to resolve the fine structure of the bottom boundary of the model. Since urban areas have a complex surface morphology, the study of the wind near the surface may require more information than can be provided from a mesoscale model including only a slab-type surface-boundary condition. It is usually difficult to compare model results with those obtained from observations because the level of the ground, which should be the base of the comparison, is not always clearly defined in the urban area. In the analysis of urban climatology with a mesoscale meteorological model, the wind velocity at the bottom boundary (not ground level, but somewhere above it) is often specified as a very small value, or a zero value, in order to fit the calculated wind velocity with the results of observations near the surface (e.g., Kimura and Takahashi, 1991; Urano et al., 1999; Kusaka et al., 2000). Since the concentration of air pollutants is estimated to be inversely proportional to the wind velocity (e.g., Pasquill and Smith, 1983), its value is important in an urban environment. To obtain better results in an urban area with mesoscale numerical models, many urban canopy models (more than 30) have been developed, and Grimmond et al. (2007) summarized them. However, most of these were not multi-layered models, and their focus was the temperature in urban areas and not the wind velocity. Among them, Martilli (2002) applied his model to a mesoscale model and investigated wind velocity in an urban area; however, he did not apply his model to any observed data in an actual city. Recently, Kondo et al. (2005) developed a multi-layer urban canopy model and combined it with a mesoscale meteorological model (AIST-MM: Kondo, 1990, 1995) in Tokyo. Their model uses GIS data of the Tokyo metropolitan area, in which the area of the floor, number of floors, and type and use of individual buildings are recorded. Primarily, Kondo et al. (2005) compared the performance of the air temperature with the observation; here, we compare the results concerning the wind with the observation. Tokairin et al. (2006) compared the results of the calculated wind obtained from the mesoscale model including an urban canopy model with the observations only for a few days in summer. In the present paper, the period of the comparison in summer is extended, and a winter comparison is added.
2. Models The mesoscale model used here is the AIST-MM (Kondo, 1990, 1995), and the domain of the calculation is shown in Fig. 1. The AIST-MM is a hydrostatic and Boussinesqapproximated model without cloud generation. The model is twice-nested; the outer domain covers approximately 600 km 600 km with a 10 km grid interval, which is driven with the Grid Point Value (GPV)-Mesoscale Spectrum Model (MSM) data of the Japan Meteorological Agency (JMA, 2006). The inner domain is approximately 160 km 160 km with a 2 km grid interval. The multi-layer urban canopy model (Kondo et al., 2005) is introduced in the grids of the 23-ward area of Tokyo. The canopy model is introduced into 145 grids in the mesoscale model (Fig. 2). The averaged height and sky-view factor, which
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Fig. 1. Domain of the calculation. The right top is the outer domain, and the right bottom is the inner domain of the mesoscale model.
were calculated with the method described in Kondo et al. (2005) in each grid, are shown in Fig. 2. The canopy model consists of a one-dimensional diffusion equation of momentum with the consideration of the drag due to buildings, potential temperature, and humidity. pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi qu 1 q qu ¼ Km m (1) cauð u2 þ v2 Þ qt m qz qz pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi qv 1 q qv ¼ Km m cavð u2 þ v2 Þ qt m qz qz m¼1
b2 Pb ðzÞ ðd þ bÞ2
(2)
(3)
Here, u and v are the wind velocity components in the east–west and north–south directions, respectively. b and d are the averaged width and distance between buildings, respectively, in the considered grid, which are calculated from the GIS data of the Tokyo metropolitan government. c is a parameter depending on l ¼ b2/(d+b2), and the value is obtained from Maruyama (1991) wind tunnel experiments with a fourth-order curve-fitted equation for l. c¼
1 46:8l 353:2l2 þ 1204:2l3 1524:1l4 2
(4)
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Fig. 2. The grids for the urban canopy model are installed. (a) Averaged height of buildings, (b) averaged skyview factor for each grid. The number of grids is shown in parentheses.
a is given by the following equation; here, we consider the building floor density distribution Pb(z) in a vertical direction: a¼
b Pb ðzÞ ðb þ dÞ2 b2 Pb ðzÞ
(5)
The drag force becomes weaker at a high level, where the buildings are very sparse. Km in Eqs. (1) and (2) are the turbulent diffusion coefficients; the original form was given by
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Gambo (1978) and modified on the basis of an idea presented by Watanabe and Kondo (1990) for forest canopies (Kondo et al., 2005). The equations for potential temperature and specific humidity are qy 1 q qy 1 ¼ Kh m Q ðz; tÞ (6) þ qt m qz qz cp r AS qqv 1 q qqv 1 Kq m ¼ (7) þ QAL ðz; tÞ m qz lr qt qz where y, qv, QAS, and QAL are the potential temperature, specific humidity, anthropogenic sensible heat, and anthropogenic latent heat, respectively. Here, QAL is assumed to be zero. Sensible anthropogenic heat is given with the database (NIRE, 1997). cp is the specific heat of air, r, the air density, and l, the latent heat of vaporization. Kh and Kq are the diffusivity for heat and specific humidity, which are assumed to be equal and given in a similar manner to Km from Gambo (1978). The effect of the sky-view factor and the shadow of buildings are simply considered in the radiative transfer in the canopy model. The reflection of the short-wave radiation is considered only twice, and a detailed radiative process is shown in Kondo et al. (2005). The canopy model can consider three different surfaces on each level of the building surface and the ground surface. The parameters used for the buildings and ground (the same in all the grids in which canopy model is applied) are shown in Table 1. The ratio of the vegetation area in each grid is given by the NDVI analysis of Hirano et al. (2004). The conductance of water vapor is specified to be 20 mm s1 in a vegetation area. The canopy model is applied for the buildings but not for the forest in the urban area. The canopy and mesoscale models are interactively calculated. The top of the canopy model was set at 270 m above the ground, and the height was divided into 42 levels. The grid interval between the ground and 30 m is 3 m except for the lowest two layers, which are 1 and 3 m above the ground. The interval is 5 m between 30 and 100 m and 10 m above 100 m. The grid levels of the mesoscale model of the lowest eight levels are approximately 10, 30, 60, 100, 140, 180, 225, and 275 m. Both the mean value and fluxes are handed over from the canopy model to the mesoscale model at the top boundary of the canopy model. The level of the grid point in the vertical direction is not the same in the two models. The same method as that of Martilli et al. (2002) is used for the data transfer from a mesoscale Table 1 Parameters of the surfaces used for the calculation Surfaces
Albedo
Volumetric heat capacity (J m3 K1)
Thermal conductivity (J m1 s1 K1)
Ground 0–36 cm 36–144 cm
0.1 –
2.06 106 1.74 106
0.73 1.00
Wall and roof 16–20 cm 0–16 cm
– 0.2
0.06 106 2.01 106
0.04 2.28
Window (30% of wall)
0.4
–
–
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model to a canopy model. However, we interpolate the temperature or wind itself from the canopy grid levels to the mesoscale grid level. 3. Comparison of the model results with the observations In this paper, we compare the results of the wind values from the combined model with those obtained from observations. The calculated wind is compared with two points in the Tokyo metropolitan area (the 23-ward area) in winter and summer. The first point is Ootemachi, a business district in central Tokyo, and the anemometer, which is used in the comparison, is mounted 76 m above the ground. The anemometer belongs to the JMA and is designed to avoid the effects of obstacles nearby. However, the point is surrounded by 8–15-story buildings. Another point is Nerima, in the northwest part of the 23-ward area in Tokyo; it is in a residential area of two- or three-story houses. This is one of the Automated Meteorological Data Acquisition System (AMeDAS) observatories of the 30 Vobs Vcal
Wind Velocity (ms-1)
25 20 15 10 5 0 5.15h
7.15h
9.15h 11.15h 13.15h DATE, TIME
15.15h
360 315 Wind Direction (degree)
270 225 180 135 90 WDobs WDcal
45 0 5.15h
7.15h
9.15h 11.15h 13.15h DATE, TIME
15.15h
Fig. 3. Comparison of the wind velocity and wind direction at 850 hPa at Tateno in winter, January 5–17, 2004. The top is the wind velocity, and the bottom is the wind direction.
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JMA, and the anemometer is mounted 6 m above the ground. The periods of the comparison were in winter, January 5–18, 2004, and in summer, July 23 to August 1, 2004. First, the calculated results at the 1500 m level were compared to the observed wind at the 850 hPa level, near the top of the boundary layer, obtained with re-win sonde at Tateno, which is 50 km northeast of Tokyo (Fig. 1). In this comparison, the model performance was checked for non-disturbed wind by the urban buildings. The results of the comparison in winter and summer are shown in Figs. 3 and 4, respectively. There was little discrepancy; the observations and calculations agree well with each other in both periods. Since a typhoon (T0410 NAMTHEUN) was approaching the main island of Japan from 27 to 29 July, an easterly wind was dominant at Tateno. Two calculations were conducted for each period. The urban canopy model was included in the first case, and no urban canopy was included in the second case. In the second case, the aerodynamic surface roughness was calculated according to Kondo et al. (2001) using land use data of the Ministry of Land Infrastructure and Transport of Japan. One meter in the area of high buildings and 0.5 m in the area of low buildings were 16
Wind Velocity (ms-1)
14
Vobs Vcal
12 10 8 6 4 2 0 25.09h
29.09h 27.09h DATE, TIME
31.09h
360 WDobs WDcal
Wind Direction (degree)
315 270 225 180 135 90 45 0 25.09h
27.09h 29.09h DATE, TIME
31.09h
Fig. 4. The same as Fig. 3 but for summer, July 23–August 1, 2004.
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specified for the roughness parameter. The wind velocity and direction of both cases, and the observation at Ootemachi in winter are shown (Fig. 5). Fig. 6 is the same figure as Fig. 5 but at Nerima. As shown in Fig. 3, three strong wind periods are seen in the winter period of the calculation. The most frequent wind direction was NNW, and the wind velocity calculated without the canopy model was overestimated by more than twice. At the Nerima observatory, the wind velocity was given every 1 m s1. The wind velocity, even with the urban canopy model, was overestimated at Nerima. This may be due to the difference of the level in the calculation (10 m above the ground in the model) and the location of Nerima in the model. Nerima is located near the northwest boundary of the urban area, where the urban canopy model is introduced. The most frequent wind direction is northwest to north there, and the effect of the urban canopy was insufficiently affected for the wind to be reduced due to relatively short fetch of the area, where the canopy model is applied in this direction.
20
20 canopy obs. no canopy
18 Wind velocity (ms-1)
16
18 16
14
14
12
12
10
10
8
8
6
6
4
4
2
2 0
0
Wind Direction (degree)
6
7
8
9
10 11 12 13 14 DATE (Jan., 2004)
15
16
17
360
360
315
315
270
270
225
225
180
180
135
135 canopy obs. no canopy
90 45
90 45
0
0 6
7
8
9
10 11 12 13 14 DATE (Jan., 2004)
15
16
17
Fig. 5. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Ootemachi in winter. The top is the wind velocity, and the bottom is the wind direction.
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16 canopy obs. no canopy
Wind Velocity (ms-1)
14 12
14 12
10
10
8
8
6
6
4
4
2
2
0
0 6
Wind Direction (degree)
1663
7
8
9
10 11 12 13 14 DATE (JAN, 2004)
15
16
17
360
360
315
315
270
270
225
225
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180
135
135 90
90 canopy obs no cabopy
45
45 0
0 6
7
8
9
10 11 12 13 14 DATE (JAN, 2004)
15
16
17
Fig. 6. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Nerima in winter. The top is the wind velocity, and the bottom is the wind direction.
Fig. 7 shows the same comparison at Ootemachi in summer. The wind velocity has a clear daily variation. The wind velocity is strong in the late afternoon and weak before sunrise. The wind velocity calculated without canopy model is also overestimated. The results including the urban canopy model are overestimated from 30 July to 1 August, when the wind direction was SSE. In the winter cases, most of the wind velocities calculated with the urban canopy model were slightly overestimated. This small difference between the observed wind and that calculated with the urban canopy model might be caused by the inhomogeneity of the spatial height distribution of the buildings around the Ootemachi observatory. The averaged building height of the area north of the observatory is rather low, but that to the south and southeast is rather high. The results of Tokairin et al. (2006) are added in the top figure of Fig. 7 from July 26 to 29 and shown with an open circle (case T). The difference between the present cases and case T is that the observed solar insolation was used in case T. In the present cases, the effect of clouds was calculated
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12
12 obs canopy no canopy case T
Wind Velocity (ms-1)
10
10
8
8
6
6
4
4
2
2
0
0 24
25
27 28 29 30 26 DATE (JUL–AUG, 2004)
31
1
360
360 obs canopy no canopy
Wind Direction (degree)
315 270
315 270
225
225
180
180
135
135
90
90
45
45
0
0 24
25
26 27 28 30 29 DATE (JUL–AUG, 2004)
31
1
Fig. 7. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Ootemachi in summer. The top is the wind velocity, and the bottom is the wind direction. The results of the case T is added in the top figure (open circle).
according to the results of the GPV data of the JMA numerical products, and the cloud amount was not accurately predicted (Tokairin et al., 2006). The wind velocity calculated with actual solar insolation may slightly improve the results because solar insolation is one of the dominant energy sources driving local winds. The calculated wind at Nerima (Fig. 8) is approximately three times the observed wind. As shown in the Ootemachi results, the daily variation of the wind velocity is very clear in the calculated results. The wind calculated with the urban canopy model is also overestimated, even when the calculated wind direction is south; however, the difference becomes smaller than that in the winter case. 4. Conclusions The performance of the mesoscale meteorological model including a multi-layer urban canopy model was compared with observational data in the winter and summer of 2004.
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8 obs canopy no canopy
Wind Velocity (ms-1)
7
7
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6
5
5
4
4
3
3
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2
1
1 0
0 24
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315 Wind Direction (degree)
1665
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225
225
180
180
135
135
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90
45
45
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0 24
25
26 27 28 30 29 DATE (JUL–AUG, 2004)
31
1
Fig. 8. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Nerima in summer. The top is the wind velocity, and the bottom is the wind direction.
The canopy model is vertically one-dimensional and introduced into a mesoscale model in the 23-ward area of Tokyo. The canopy model considers the averaged building width, distance between buildings, and sky-view factor, in addition to the vertical floor density distribution of the buildings in the considered grid area. First, the calculation was compared at an 850 hPa level wind at Tateno with a re-win sonde observation to check the values near the top of boundary layer of an urban area of Tokyo. The results of the calculation were then compared with two observational data at Ootemachi, a business district in the center of Tokyo, and at a residential area of Nerima. The calculated periods were from January 5 to 18 for winter, when the dominant wind direction is northerly, and from July 23 to August 1 for summer, when a south to easterly wind is dominant. In all calculations, the wind direction coincided relatively well with the observation results. The wind velocity calculated with no canopy often resulted in overestimations, and the ratio of the overestimation was bigger near the ground. In the residential area in Nerima, the wind velocity, even with the urban canopy model, was slightly overestimated. This may be
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because Nerima is located near the northwest boundary of the 23-ward area of Tokyo, where the urban canopy model was introduced. In Ootemachi, the discrepancy between the observed wind and that calculated with the urban canopy model depends somewhat on the wind direction. This may be because the canopy structure inside a grid is assumed to be homogeneous in the model; however, the actual canopy structure around the observation point is not homogeneous with each wind direction. Acknowledgment This study was supported by the Ministry of the Environment, Japan. References Gambo, K., 1978. Notes on the turbulence closure model for atmospheric boundary layers. J. Meteorol. Soc. Jpn. 56, 466–480. Grimmond, C.S.B., Best, M., Barlow, J., 2007. Progress on an urban surface energy balance model comparison study /http://ensembles-eu.metoffice.com/cost/Exeter_Workshop/Presentations/Sue_Grimmond.ppt#291,1S. Hirano, Y., Yasuoka, Y., Ichinose, T., 2004. Urban climate simulation by incorporating satellite-derived vegetation cover distribution into a mesoscale meteorological model. Theor. Appl. Climatol. 79, 175–184. JMA, 2006. Numerical Weather Prediction of JMA, available from /http://www.jma.go.jp/jma/jma-eng/ jma-center/nwp/nwp-top.htmS. Kimura, F., Takahashi, S., 1991. The effects of land-use and anthropogenic heating on the surface temperature in the Tokyo metropolitan area: a numerical experiment. Atmos. Environ. 25B, 155–164. Kondo, H., 1990. A numerical experiment of the extended sea breeze over the Kanto plain. J. Meteorol. Soc. Jpn. 68, 419–434. Kondo, H., 1995. The thermally induced local wind and surface inversion over the Kanto plain on calm winter nights. J. Appl. Meteorol. 34, 1439–1448. Kondo, H., Saigusa, N., Murayama, S., Yamamoto, S., Kannari, A., 2001. A numerical simulation of the daily variation of CO2 in the central part of Japan -summer case-. J. Meteorol. Soc. Jpn. 79, 11–21. Kondo, H., Genchi, Y., Kikegawa, Y., Ohashi, Y., Yoshikado, H., Komiyama, H., 2005. Development of a multilayer urban canopy model for the analysis of energy consumption in a big city: structure of the urban canopy model and its basic performance. Boundary-Layer Meteorol. 116, 395–421. Kusaka, H., Kimura, F., Hirakuchi, H., Mizutori, M., 2000. The effects of land-use alteration on the sea breeze and daytime heat island in the Tokyo metropolitan area. J. Meteorol. Soc. Jpn. 78, 405–420. Martilli, A., 2002. Numerical study of urban impact on boundary layer structure: sensitivity to wind speed, urban morphology, and rural soil moisture. J. Appl. Meteorol. 41, 1247–1266. Martilli, A., Clippier, A., Rotach, M.W., 2002. An urban surface exchange parameterization for mesoscale models. Boundary-Layer Meteorol. 104, 261–304. Maruyama, T., 1991. Numerical simulation of turbulent boundary layer over complicated surfaces such as urban areas. J. Wind Eng. 47, 81 (in Japanese). NIRE, 1997. Comprehensive assessment of measures mitigating heat island phenomena in urban areas. Technical Report No. 1, Environmental Assessment Department, National Institute for Resources and Environment (in Japanese). Pasquill, F., Smith, F.B., 1983. Atmospheric Diffusion, third ed. Ellis Horwood Ltd., West Sussex. Tokairin, T., Kondo, H., Yoshikado, H., Genchi, Y., Ihara, T., Kikegawa, Y., Hirano, Y., Asahi, K., 2006. Numerical study on the effect of buildings on temperature rise in urban and sub-urban areas in Tokyo. J. Meteorol. Soc. Jpn. 84, 921–937. Urano, A., Ichinose, T., Hanaki, K., 1999. Thermal environment simulation for three-dimensional replacement of urban activity. J. Wind Eng. Ind. Aerodyn. 81, 197–210. Watanabe, T., Kondo, J., 1990. The influence of the canopy structure and density upon the mixing length within and above vegetation. J. Meteorol. Soc. of Jpn. 68, 227–235.
Journal of Wind Engineering and Industrial Aerodynamics 96 (2008) 1655–1666 www.elsevier.com/locate/jweia
Calculation of wind in a Tokyo urban area with a mesoscale model including a multi-layer urban canopy model Hiroaki Kondoa,, Takayuki Tokairinb, Yukihiro Kikegawac a
National Institute of Advanced Industrial Science and Technology, Research Institute for Environmental Management Technology, AIST-west, 16-1, Onogawa, Tsukuba 305-8569, Japan b Toyohashi University of Technology, 1-1, Hibarigaoka, Tempaku-cho, Aichi, Japan c Meisei University, 2-1-1, Hodokubo, Hino, Tokyo, Japan Available online 18 April 2008
Abstract The wind velocity in an urban area calculated with a mesoscale meteorological model without an urban canopy model is often overestimated, even when a large value of aerodynamic roughness is specified on the surface. In this paper, the results of a mesoscale model combined with a multi-layer urban canopy model are compared to those of a model without an urban canopy model and with observations. The mesoscale model used here is the AIST-MM. The model is twice-nested, and a 2 km grid is used in the inner model. The model was applied in the vicinity of Tokyo, Japan, and a multi-layer canopy model was combined into 145 grids of the 23-ward area of Tokyo in the inner model. The wind velocity calculated with the urban canopy model is significantly improved near the tops of high buildings and near ground level in residential areas. r 2008 Elsevier Ltd. All rights reserved. Keywords: Mesoscale model; Urban surface wind; Multi-layer urban canopy model; Tokyo; Automated meteorological data acquisition system
Corresponding author. Tel.: +81 29 861 8305; fax: +81 29 861 8358.
E-mail address: [email protected] (H. Kondo). 0167-6105/$ - see front matter r 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jweia.2008.02.022
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1. Introduction Many meteorological models have been developed to analyze the mesoscale and local meteorology in urban areas, and the target scale of such models has become progressively smaller. To analyze the fine structure of the wind and temperature field, it is necessary to resolve the fine structure of the bottom boundary of the model. Since urban areas have a complex surface morphology, the study of the wind near the surface may require more information than can be provided from a mesoscale model including only a slab-type surface-boundary condition. It is usually difficult to compare model results with those obtained from observations because the level of the ground, which should be the base of the comparison, is not always clearly defined in the urban area. In the analysis of urban climatology with a mesoscale meteorological model, the wind velocity at the bottom boundary (not ground level, but somewhere above it) is often specified as a very small value, or a zero value, in order to fit the calculated wind velocity with the results of observations near the surface (e.g., Kimura and Takahashi, 1991; Urano et al., 1999; Kusaka et al., 2000). Since the concentration of air pollutants is estimated to be inversely proportional to the wind velocity (e.g., Pasquill and Smith, 1983), its value is important in an urban environment. To obtain better results in an urban area with mesoscale numerical models, many urban canopy models (more than 30) have been developed, and Grimmond et al. (2007) summarized them. However, most of these were not multi-layered models, and their focus was the temperature in urban areas and not the wind velocity. Among them, Martilli (2002) applied his model to a mesoscale model and investigated wind velocity in an urban area; however, he did not apply his model to any observed data in an actual city. Recently, Kondo et al. (2005) developed a multi-layer urban canopy model and combined it with a mesoscale meteorological model (AIST-MM: Kondo, 1990, 1995) in Tokyo. Their model uses GIS data of the Tokyo metropolitan area, in which the area of the floor, number of floors, and type and use of individual buildings are recorded. Primarily, Kondo et al. (2005) compared the performance of the air temperature with the observation; here, we compare the results concerning the wind with the observation. Tokairin et al. (2006) compared the results of the calculated wind obtained from the mesoscale model including an urban canopy model with the observations only for a few days in summer. In the present paper, the period of the comparison in summer is extended, and a winter comparison is added.
2. Models The mesoscale model used here is the AIST-MM (Kondo, 1990, 1995), and the domain of the calculation is shown in Fig. 1. The AIST-MM is a hydrostatic and Boussinesqapproximated model without cloud generation. The model is twice-nested; the outer domain covers approximately 600 km 600 km with a 10 km grid interval, which is driven with the Grid Point Value (GPV)-Mesoscale Spectrum Model (MSM) data of the Japan Meteorological Agency (JMA, 2006). The inner domain is approximately 160 km 160 km with a 2 km grid interval. The multi-layer urban canopy model (Kondo et al., 2005) is introduced in the grids of the 23-ward area of Tokyo. The canopy model is introduced into 145 grids in the mesoscale model (Fig. 2). The averaged height and sky-view factor, which
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Fig. 1. Domain of the calculation. The right top is the outer domain, and the right bottom is the inner domain of the mesoscale model.
were calculated with the method described in Kondo et al. (2005) in each grid, are shown in Fig. 2. The canopy model consists of a one-dimensional diffusion equation of momentum with the consideration of the drag due to buildings, potential temperature, and humidity. pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi qu 1 q qu ¼ Km m (1) cauð u2 þ v2 Þ qt m qz qz pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi qv 1 q qv ¼ Km m cavð u2 þ v2 Þ qt m qz qz m¼1
b2 Pb ðzÞ ðd þ bÞ2
(2)
(3)
Here, u and v are the wind velocity components in the east–west and north–south directions, respectively. b and d are the averaged width and distance between buildings, respectively, in the considered grid, which are calculated from the GIS data of the Tokyo metropolitan government. c is a parameter depending on l ¼ b2/(d+b2), and the value is obtained from Maruyama (1991) wind tunnel experiments with a fourth-order curve-fitted equation for l. c¼
1 46:8l 353:2l2 þ 1204:2l3 1524:1l4 2
(4)
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Fig. 2. The grids for the urban canopy model are installed. (a) Averaged height of buildings, (b) averaged skyview factor for each grid. The number of grids is shown in parentheses.
a is given by the following equation; here, we consider the building floor density distribution Pb(z) in a vertical direction: a¼
b Pb ðzÞ ðb þ dÞ2 b2 Pb ðzÞ
(5)
The drag force becomes weaker at a high level, where the buildings are very sparse. Km in Eqs. (1) and (2) are the turbulent diffusion coefficients; the original form was given by
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Gambo (1978) and modified on the basis of an idea presented by Watanabe and Kondo (1990) for forest canopies (Kondo et al., 2005). The equations for potential temperature and specific humidity are qy 1 q qy 1 ¼ Kh m Q ðz; tÞ (6) þ qt m qz qz cp r AS qqv 1 q qqv 1 Kq m ¼ (7) þ QAL ðz; tÞ m qz lr qt qz where y, qv, QAS, and QAL are the potential temperature, specific humidity, anthropogenic sensible heat, and anthropogenic latent heat, respectively. Here, QAL is assumed to be zero. Sensible anthropogenic heat is given with the database (NIRE, 1997). cp is the specific heat of air, r, the air density, and l, the latent heat of vaporization. Kh and Kq are the diffusivity for heat and specific humidity, which are assumed to be equal and given in a similar manner to Km from Gambo (1978). The effect of the sky-view factor and the shadow of buildings are simply considered in the radiative transfer in the canopy model. The reflection of the short-wave radiation is considered only twice, and a detailed radiative process is shown in Kondo et al. (2005). The canopy model can consider three different surfaces on each level of the building surface and the ground surface. The parameters used for the buildings and ground (the same in all the grids in which canopy model is applied) are shown in Table 1. The ratio of the vegetation area in each grid is given by the NDVI analysis of Hirano et al. (2004). The conductance of water vapor is specified to be 20 mm s1 in a vegetation area. The canopy model is applied for the buildings but not for the forest in the urban area. The canopy and mesoscale models are interactively calculated. The top of the canopy model was set at 270 m above the ground, and the height was divided into 42 levels. The grid interval between the ground and 30 m is 3 m except for the lowest two layers, which are 1 and 3 m above the ground. The interval is 5 m between 30 and 100 m and 10 m above 100 m. The grid levels of the mesoscale model of the lowest eight levels are approximately 10, 30, 60, 100, 140, 180, 225, and 275 m. Both the mean value and fluxes are handed over from the canopy model to the mesoscale model at the top boundary of the canopy model. The level of the grid point in the vertical direction is not the same in the two models. The same method as that of Martilli et al. (2002) is used for the data transfer from a mesoscale Table 1 Parameters of the surfaces used for the calculation Surfaces
Albedo
Volumetric heat capacity (J m3 K1)
Thermal conductivity (J m1 s1 K1)
Ground 0–36 cm 36–144 cm
0.1 –
2.06 106 1.74 106
0.73 1.00
Wall and roof 16–20 cm 0–16 cm
– 0.2
0.06 106 2.01 106
0.04 2.28
Window (30% of wall)
0.4
–
–
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model to a canopy model. However, we interpolate the temperature or wind itself from the canopy grid levels to the mesoscale grid level. 3. Comparison of the model results with the observations In this paper, we compare the results of the wind values from the combined model with those obtained from observations. The calculated wind is compared with two points in the Tokyo metropolitan area (the 23-ward area) in winter and summer. The first point is Ootemachi, a business district in central Tokyo, and the anemometer, which is used in the comparison, is mounted 76 m above the ground. The anemometer belongs to the JMA and is designed to avoid the effects of obstacles nearby. However, the point is surrounded by 8–15-story buildings. Another point is Nerima, in the northwest part of the 23-ward area in Tokyo; it is in a residential area of two- or three-story houses. This is one of the Automated Meteorological Data Acquisition System (AMeDAS) observatories of the 30 Vobs Vcal
Wind Velocity (ms-1)
25 20 15 10 5 0 5.15h
7.15h
9.15h 11.15h 13.15h DATE, TIME
15.15h
360 315 Wind Direction (degree)
270 225 180 135 90 WDobs WDcal
45 0 5.15h
7.15h
9.15h 11.15h 13.15h DATE, TIME
15.15h
Fig. 3. Comparison of the wind velocity and wind direction at 850 hPa at Tateno in winter, January 5–17, 2004. The top is the wind velocity, and the bottom is the wind direction.
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JMA, and the anemometer is mounted 6 m above the ground. The periods of the comparison were in winter, January 5–18, 2004, and in summer, July 23 to August 1, 2004. First, the calculated results at the 1500 m level were compared to the observed wind at the 850 hPa level, near the top of the boundary layer, obtained with re-win sonde at Tateno, which is 50 km northeast of Tokyo (Fig. 1). In this comparison, the model performance was checked for non-disturbed wind by the urban buildings. The results of the comparison in winter and summer are shown in Figs. 3 and 4, respectively. There was little discrepancy; the observations and calculations agree well with each other in both periods. Since a typhoon (T0410 NAMTHEUN) was approaching the main island of Japan from 27 to 29 July, an easterly wind was dominant at Tateno. Two calculations were conducted for each period. The urban canopy model was included in the first case, and no urban canopy was included in the second case. In the second case, the aerodynamic surface roughness was calculated according to Kondo et al. (2001) using land use data of the Ministry of Land Infrastructure and Transport of Japan. One meter in the area of high buildings and 0.5 m in the area of low buildings were 16
Wind Velocity (ms-1)
14
Vobs Vcal
12 10 8 6 4 2 0 25.09h
29.09h 27.09h DATE, TIME
31.09h
360 WDobs WDcal
Wind Direction (degree)
315 270 225 180 135 90 45 0 25.09h
27.09h 29.09h DATE, TIME
31.09h
Fig. 4. The same as Fig. 3 but for summer, July 23–August 1, 2004.
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specified for the roughness parameter. The wind velocity and direction of both cases, and the observation at Ootemachi in winter are shown (Fig. 5). Fig. 6 is the same figure as Fig. 5 but at Nerima. As shown in Fig. 3, three strong wind periods are seen in the winter period of the calculation. The most frequent wind direction was NNW, and the wind velocity calculated without the canopy model was overestimated by more than twice. At the Nerima observatory, the wind velocity was given every 1 m s1. The wind velocity, even with the urban canopy model, was overestimated at Nerima. This may be due to the difference of the level in the calculation (10 m above the ground in the model) and the location of Nerima in the model. Nerima is located near the northwest boundary of the urban area, where the urban canopy model is introduced. The most frequent wind direction is northwest to north there, and the effect of the urban canopy was insufficiently affected for the wind to be reduced due to relatively short fetch of the area, where the canopy model is applied in this direction.
20
20 canopy obs. no canopy
18 Wind velocity (ms-1)
16
18 16
14
14
12
12
10
10
8
8
6
6
4
4
2
2 0
0
Wind Direction (degree)
6
7
8
9
10 11 12 13 14 DATE (Jan., 2004)
15
16
17
360
360
315
315
270
270
225
225
180
180
135
135 canopy obs. no canopy
90 45
90 45
0
0 6
7
8
9
10 11 12 13 14 DATE (Jan., 2004)
15
16
17
Fig. 5. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Ootemachi in winter. The top is the wind velocity, and the bottom is the wind direction.
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16 canopy obs. no canopy
Wind Velocity (ms-1)
14 12
14 12
10
10
8
8
6
6
4
4
2
2
0
0 6
Wind Direction (degree)
1663
7
8
9
10 11 12 13 14 DATE (JAN, 2004)
15
16
17
360
360
315
315
270
270
225
225
180
180
135
135 90
90 canopy obs no cabopy
45
45 0
0 6
7
8
9
10 11 12 13 14 DATE (JAN, 2004)
15
16
17
Fig. 6. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Nerima in winter. The top is the wind velocity, and the bottom is the wind direction.
Fig. 7 shows the same comparison at Ootemachi in summer. The wind velocity has a clear daily variation. The wind velocity is strong in the late afternoon and weak before sunrise. The wind velocity calculated without canopy model is also overestimated. The results including the urban canopy model are overestimated from 30 July to 1 August, when the wind direction was SSE. In the winter cases, most of the wind velocities calculated with the urban canopy model were slightly overestimated. This small difference between the observed wind and that calculated with the urban canopy model might be caused by the inhomogeneity of the spatial height distribution of the buildings around the Ootemachi observatory. The averaged building height of the area north of the observatory is rather low, but that to the south and southeast is rather high. The results of Tokairin et al. (2006) are added in the top figure of Fig. 7 from July 26 to 29 and shown with an open circle (case T). The difference between the present cases and case T is that the observed solar insolation was used in case T. In the present cases, the effect of clouds was calculated
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12
12 obs canopy no canopy case T
Wind Velocity (ms-1)
10
10
8
8
6
6
4
4
2
2
0
0 24
25
27 28 29 30 26 DATE (JUL–AUG, 2004)
31
1
360
360 obs canopy no canopy
Wind Direction (degree)
315 270
315 270
225
225
180
180
135
135
90
90
45
45
0
0 24
25
26 27 28 30 29 DATE (JUL–AUG, 2004)
31
1
Fig. 7. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Ootemachi in summer. The top is the wind velocity, and the bottom is the wind direction. The results of the case T is added in the top figure (open circle).
according to the results of the GPV data of the JMA numerical products, and the cloud amount was not accurately predicted (Tokairin et al., 2006). The wind velocity calculated with actual solar insolation may slightly improve the results because solar insolation is one of the dominant energy sources driving local winds. The calculated wind at Nerima (Fig. 8) is approximately three times the observed wind. As shown in the Ootemachi results, the daily variation of the wind velocity is very clear in the calculated results. The wind calculated with the urban canopy model is also overestimated, even when the calculated wind direction is south; however, the difference becomes smaller than that in the winter case. 4. Conclusions The performance of the mesoscale meteorological model including a multi-layer urban canopy model was compared with observational data in the winter and summer of 2004.
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8 obs canopy no canopy
Wind Velocity (ms-1)
7
7
6
6
5
5
4
4
3
3
2
2
1
1 0
0 24
25
26 27 28 29 30 DATE (JUL–AUG, 2004)
31
1
360
360 obs canopy no canopy
315 Wind Direction (degree)
1665
270
315 270
225
225
180
180
135
135
90
90
45
45
0
0 24
25
26 27 28 30 29 DATE (JUL–AUG, 2004)
31
1
Fig. 8. Comparison of the calculated wind with an urban canopy model (canopy), the observation (obs.), and the calculated wind without an urban canopy model (no canopy) at Nerima in summer. The top is the wind velocity, and the bottom is the wind direction.
The canopy model is vertically one-dimensional and introduced into a mesoscale model in the 23-ward area of Tokyo. The canopy model considers the averaged building width, distance between buildings, and sky-view factor, in addition to the vertical floor density distribution of the buildings in the considered grid area. First, the calculation was compared at an 850 hPa level wind at Tateno with a re-win sonde observation to check the values near the top of boundary layer of an urban area of Tokyo. The results of the calculation were then compared with two observational data at Ootemachi, a business district in the center of Tokyo, and at a residential area of Nerima. The calculated periods were from January 5 to 18 for winter, when the dominant wind direction is northerly, and from July 23 to August 1 for summer, when a south to easterly wind is dominant. In all calculations, the wind direction coincided relatively well with the observation results. The wind velocity calculated with no canopy often resulted in overestimations, and the ratio of the overestimation was bigger near the ground. In the residential area in Nerima, the wind velocity, even with the urban canopy model, was slightly overestimated. This may be
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because Nerima is located near the northwest boundary of the 23-ward area of Tokyo, where the urban canopy model was introduced. In Ootemachi, the discrepancy between the observed wind and that calculated with the urban canopy model depends somewhat on the wind direction. This may be because the canopy structure inside a grid is assumed to be homogeneous in the model; however, the actual canopy structure around the observation point is not homogeneous with each wind direction. Acknowledgment This study was supported by the Ministry of the Environment, Japan. References Gambo, K., 1978. Notes on the turbulence closure model for atmospheric boundary layers. J. Meteorol. Soc. Jpn. 56, 466–480. Grimmond, C.S.B., Best, M., Barlow, J., 2007. Progress on an urban surface energy balance model comparison study /http://ensembles-eu.metoffice.com/cost/Exeter_Workshop/Presentations/Sue_Grimmond.ppt#291,1S. Hirano, Y., Yasuoka, Y., Ichinose, T., 2004. Urban climate simulation by incorporating satellite-derived vegetation cover distribution into a mesoscale meteorological model. Theor. Appl. Climatol. 79, 175–184. JMA, 2006. Numerical Weather Prediction of JMA, available from /http://www.jma.go.jp/jma/jma-eng/ jma-center/nwp/nwp-top.htmS. Kimura, F., Takahashi, S., 1991. The effects of land-use and anthropogenic heating on the surface temperature in the Tokyo metropolitan area: a numerical experiment. Atmos. Environ. 25B, 155–164. Kondo, H., 1990. A numerical experiment of the extended sea breeze over the Kanto plain. J. Meteorol. Soc. Jpn. 68, 419–434. Kondo, H., 1995. The thermally induced local wind and surface inversion over the Kanto plain on calm winter nights. J. Appl. Meteorol. 34, 1439–1448. Kondo, H., Saigusa, N., Murayama, S., Yamamoto, S., Kannari, A., 2001. A numerical simulation of the daily variation of CO2 in the central part of Japan -summer case-. J. Meteorol. Soc. Jpn. 79, 11–21. Kondo, H., Genchi, Y., Kikegawa, Y., Ohashi, Y., Yoshikado, H., Komiyama, H., 2005. Development of a multilayer urban canopy model for the analysis of energy consumption in a big city: structure of the urban canopy model and its basic performance. Boundary-Layer Meteorol. 116, 395–421. Kusaka, H., Kimura, F., Hirakuchi, H., Mizutori, M., 2000. The effects of land-use alteration on the sea breeze and daytime heat island in the Tokyo metropolitan area. J. Meteorol. Soc. Jpn. 78, 405–420. Martilli, A., 2002. Numerical study of urban impact on boundary layer structure: sensitivity to wind speed, urban morphology, and rural soil moisture. J. Appl. Meteorol. 41, 1247–1266. Martilli, A., Clippier, A., Rotach, M.W., 2002. An urban surface exchange parameterization for mesoscale models. Boundary-Layer Meteorol. 104, 261–304. Maruyama, T., 1991. Numerical simulation of turbulent boundary layer over complicated surfaces such as urban areas. J. Wind Eng. 47, 81 (in Japanese). NIRE, 1997. Comprehensive assessment of measures mitigating heat island phenomena in urban areas. Technical Report No. 1, Environmental Assessment Department, National Institute for Resources and Environment (in Japanese). Pasquill, F., Smith, F.B., 1983. Atmospheric Diffusion, third ed. Ellis Horwood Ltd., West Sussex. Tokairin, T., Kondo, H., Yoshikado, H., Genchi, Y., Ihara, T., Kikegawa, Y., Hirano, Y., Asahi, K., 2006. Numerical study on the effect of buildings on temperature rise in urban and sub-urban areas in Tokyo. J. Meteorol. Soc. Jpn. 84, 921–937. Urano, A., Ichinose, T., Hanaki, K., 1999. Thermal environment simulation for three-dimensional replacement of urban activity. J. Wind Eng. Ind. Aerodyn. 81, 197–210. Watanabe, T., Kondo, J., 1990. The influence of the canopy structure and density upon the mixing length within and above vegetation. J. Meteorol. Soc. of Jpn. 68, 227–235.