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1886 JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY VOLUME 53

Moderation of Summertime Heat Island Phenomena via Modiﬁcation of the Urban Form in the Tokyo Metropolitan Area

,1 # @ SACHIHO A. ADACHI,* FUJIO KIMURA,* HIROYUKI KUSAKA, MICHAEL G. DUDA, 11 ## YOSHIKI YAMAGATA,** HAJIME SEYA,** KUMIKO NAKAMICHI, AND TOSHINORI AOYAGI * Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan # Center for Computational Sciences, University of Tsukuba, Tsukuba, Japan @ National Center for Atmospheric Research,& Boulder, Colorado ** National Institute for Environmental Studies, Tsukuba, Japan 11 National Institute for Environmental Studies, Tsukuba, Japan, Tokyo Institute of Technology, Meguro, Japan ## Meteorological Research Institute, Tsukuba, Japan

(Manuscript received 7 June 2013, in ﬁnal form 17 February 2014)

ABSTRACT

This study investigated the moderation of the urban heat island via changes in the urban form in the Tokyo metropolitan area (TMA). Two urban scenarios with the same population as that of the current urban form were used for sensitivity experiments: the dispersed-city and compact-city scenarios. Numerical experiments using the two urban scenarios as well as an experiment using the current urban form were conducted using a regional climate model coupled with a single-layer urban canopy model. The averaged nighttime surface air temperature in TMA increased by ;0.348C in the dispersed-city scenario and decreased by ;0.18C in the compact-city scenario. Therefore, the compact-city scenario had signiﬁcant potential for moderating the mean areal heat-island effect in the entire TMA. Alternatively, in the central part of the TMA, these two urban-form scenarios produced opposite effects on the surface air temperature; that is, severe thermal conditions worsened further in the compact-city scenario because of the denser population. This result suggests that the compact-city form is not always appropriate for moderation of the urban-heat-island effect. This scenario would need to combine with other mitigation strategies, such as the additional greening of urban areas, especially in the central area. This study suggests that it is important to design a plan to adapt to higher urban temperatures, which are likely to ensue from future global warming and the urban heat island, from several perspectives; that is, designs should take into account not only climatological aspects but also impacts on urban inhabitants.

1. Introduction people were hospitalized for heat stroke between July and September of 2010 (Fire and Disaster Management Most regions of Japan experienced record heat levels in Agency 2010), and 621 people died of heat stroke over the the summer of 2010. In August of 2010 the Tokyo me- full year (Ministry of Health Labor and Welfare 2011). teorological station observed the highest monthly-mean Heat stroke tends to develop frequently in the daytime surface air temperature (29.68C) on record (between 1876 when high temperatures are experienced. In the sum- and 2012). In the Tokyo metropolitan area (TMA), 16 477 mer of 2010, however, about one-half of the people who died of heat stroke in Tokyo died during the night, and

1 many were single elderly people (Tokyo Metropolitan Current afﬁliation: Advanced Institute for Computational Sci- Government Bureau of Social Welfare and Public Health ence, RIKEN, Kobe, Japan. & The National Center for Atmospheric Research is sponsored 2010). Heat-related health issues during the night, in- by the National Science Foundation. cluding heat stroke and sleep disruption, in addition to those during the day, are becoming a signiﬁcant social issue in the TMA, especially in the central area, where Corresponding author address: Sachiho A. Adachi, Advanced Institute for Computational Science, RIKEN, 7-1-26 Minatojima- high nighttime temperatures can be experienced. minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan. The summertime climate in the TMA is characterized E-mail: [email protected] by conditions of high temperature and humidity that

DOI: 10.1175/JAMC-D-13-0194.1

Ó 2014 American Meteorological Society Unauthenticated | Downloaded 10/05/21 05:00 PM UTC AUGUST 2014 ADACHI ET AL. 1887 lead to discomfort for the inhabitants. The climate in this (2012) estimated the urban-heat-island intensity (UHII) in region is significantly affected by two stationary high the TMA by replacing urban areas with grassland in pressure systems: the Bonin high and the Okhotsk high. a numerical model. The sensitivity experiment indicated The appearance in Japan of an active Bonin high, which is that the average UHII in August in the TMA was ap- a subtropical anticyclone located in the south of the proximately 18C in the 1990s. Papangelis et al. (2012) country, blocks typhoons and prevents disturbances from conducted numerical experiments and estimated the passing through Japan, which brings fine weather in the cooling effect of replacing the industrial/commercial area TMA (Ueda et al. 1995; Yasunaka and Hanawa 2006). with a large green park in Athens, Greece. They indicated Conversely, an intensified Okhotsk high over the Okhotsk that the introduction of a large urban park had a cooling Sea generates a cold northeasterly wind in the northern effect of more than 58C at nighttime when compared with part of Japan and causes cold summer weather with the original industrial/commercial land use. The nighttime cloudy conditions (Yasunaka and Hanawa 2006). The hot cooling effect expanded to the surrounding area and in- summer of 2010 was reported to be caused by the fol- duced cooling of between 0.58 and 1.28C in the area around lowing conditions, typical of a hot summer: 1) midtropo- the park’s borders. Coutts et al. (2008) developed a mod- spheric warming, which seemed to be affected by the end ified air-pollution model to assess the impact of urban of El Niño and the beginning of La Niña; 2) intensification planning on local climate. They also estimated the UHII in of the Bonin high; and 3) weakening of the Okhotsk Melbourne in the present day and the 2030s using the high (Japan Meteorological Agency 2011). Note also that modified air-pollution model. Their results indicated that the long-term warming trend has also been implicated in the maximum intensity of the UHII in the 2030s would not the hot summers experienced in recent years, including the increase from that of the present-day urban area but that summer of 2010. The surface air temperature in August in high-temperature areas were projected to expand. In their Tokyo increased by about 1.48C during the 80 years from study, they demonstrated that regional urban modeling is 1931to2010(Japan Meteorological Agency 2011), which a powerful tool for evaluating the climatological effects of is associated with local urbanization and global warming various urban scenarios and that the results from the due to the increased emission of anthropogenic green- model are likely to be valuable to urban planners, as also house gases (e.g., Fujibe 2009). The frequency of hot has been reported in previous studies (e.g., Manins 1995). summers, such as that of 2010, is projected to increase in Previous studies have indicated changes in the UHII Japan in the future because of global climate change that are due to historical urbanization, different urban- (Solomon et al. 2007; Japan Meteorological Agency planning scenarios, and the cooling effects of greening the 2005; Kusaka et al. 2012). Thus, countermeasures against city. Most of these studies implicitly assume a population hot humid summer conditions in the TMA are required. change in association with land-use change, and most Moderation of the urban heat island is a potential permit large-scale alteration of land use. Large-scale al- method to improve uncomfortable summer conditions in terations are very difficult to undertake in high-density urban areas. Moreover, such moderation is expected to urban areas such as the TMA, however. In addition, to become part of an adaptation strategy for global climate determine the appropriate urban form to counter an change because urban-heat-island mitigation should be uncomfortable thermal environment, it is necessary to mostly implemented by local governments (Coutts et al. assess the urban scenarios from the perspective of in- 2008; Adachi et al. 2012). Many methods have been habitants. This study uses the current urban situation and proposed to mitigate urban-heat-island effects, such as two projected urban scenarios with the same population changes in the urban form (Oke 1984; Scherer et al. 1999), as the current urban situation: the dispersed-city and greening of parking lots and building walls (Onishi et al. compact-city scenarios. The levels of social and economic 2010; Takebayashi and Moriyama 2009), increasing activity in the two projected scenarios are assumed to roof albedo (e.g., Takebayashi and Moriyama 2007; remain unchanged. The model then investigates how Krayenhoff and Voogt 2010; Oleson et al. 2010), and differences in the urban form moderate nighttime ther- changes in pavement materials (Takebayashi and mal conditions in the TMA from the perspective of in- Moriyama 2012). Of these possible measures, this study habitants as well as from a climatological perspective. focused on changes in the urban form. The model setting and urban scenarios are described Many previous studies have reported the effects of in sections 2 and 3. Section 4 presents the results in terms land-use changes on urban heat islands in relation to of the impacts of different urban forms on thermal the expansion and reduction of the urban area in sev- conditions in the TMA. In section 5, the differences in eral urban cities, including the TMA (e.g., Kimura and urban form are discussed from the perspective of an Takahashi 1991; Kusaka et al. 2000; Van Weverberg et al. adaptation strategy to global warming in urban areas. 2008; Miao et al. 2009; Aoyagi et al. 2012). Adachi et al. Section 6 provides the conclusions and further remarks.

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FIG. 1. (a) Simulation domains of WRF. The dot-outlined squares indicate the second and third domains. (b) The analysis area, which is shown as a thick-lined square in (a). Stars and black dots indicate the locations of AMeDAS observation stations. White and black stars indicate the locations of the Tokyo and Ryugasaki AMeDAS stations, respectively. The gray color indicates the topography. The red and blue shaded areas are deﬁned as region i and region ii, which are located within 15 and 25 km of the Tokyo AMeDAS station, respectively. The other areas are deﬁned as region iii.

2. Model descriptions urban and the other was the most dominant land use in a grid cell, excluding urban (hereinafter LU_dom). The The numerical model used in this study was the heat and moisture fluxes from each grid cell were calcu- Weather Research and Forecasting Model, version 3.1.1 lated from an area-weighted average of the fluxes from (hereinafter WRF; Skamarock et al. 2008). The model the two subtiles in the grid cell (Chen et al. 2011), as shown was used to calculate meteorological conditions in the in Eq. (A6) of appendix A, below. These fluxes were cal- TMA during August of 2010. The model domains are culated by the UCM for urban tiles and by the ‘‘Noah’’ a nested system with three grids. The outermost, middle, land surface model for other land-use tiles. The method and inner domains are covered by 162 3 150, 251 3 231, used to diagnostically estimate surface air temperature at and 203 3 201 grid cells with horizontal spatial resolu- 2 m was also modified, as described in appendix A. Table 1 tions of 20, 4, and 2 km, respectively (Fig. 1a). A total of lists the other settings of the physical scheme options. 31 vertical model levels were used, and the height of the Observed data from a series of Automated Meteoro- lowest level was set at approximately 30 m above ground logical Data Acquisition Systems (AMeDAS) were used to level. The initial and boundary conditions for WRF were evaluate the model performance. There are 57 AMeDAS provided from the National Centers for Environmental stations located at altitudes lower than 200 m above sea Prediction–National Center for Atmospheric Research level in the TMA (Fig. 1b). (NCEP–NCAR) reanalysis data (Kalnay et al. 1996). The simulation period was from 25 July to 1 September 2010, and the results for August were used for analysis. 3. Urban scenarios and experimental design The WRF–Urban Canopy Model (UCM) was modi- a. Urban parameters for the current urban scenario fied to incorporate the gridded urban fraction and the gridded sensible and latent anthropogenic heat fluxes in This study assumed a current urban scenario and two the single-layer UCM. In the original WRF, land-use other urban scenarios, the dispersed-city and compact- type in a grid cell is defined by the most dominant land- city scenarios, which were introduced by Yamagata et al. use category in the grid cell. Urban areas in the model (2011) to estimate the moderation of the urban heat is- are limited to densely urbanized areas. A vegetation type land by differences in urban form. The land-use data for in an urban area is fixed to one type of vegetation that the current urban scenario were classified into seven is arbitrarily defined in a parameter table. In this study, all categories as follows: forest, cropland, paddy, grassland, grid cells had two kinds of land-use subtiles: one was bare, water area, and urban. Each land-use category was

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TABLE 1. The schemes chosen for each physical option used in WRF.

Physical options Schemes Cloud microphysics WRF single-moment 6-class graupel scheme Convective parameterization Kain–Fritsch (new Eta) scheme Radiation scheme Rapid Radiative Transfer Model (GCM application version) radiation scheme Boundary layer Mellor–Yamada–Janjic turbulent kinetic energy scheme Surface layer Monin–Obukhov (Janjic) scheme Land surface model Noah land surface model (Chen and Dudhia 2001) Urban model Single-layer UCM (Kusaka et al. 2001)

estimated by applying the improved subspace method the national population census in 2005 and published by (Bagan and Yamagata 2010) using Landsat images and the MIC, were used to determine the nighttime pop- is presented as the fraction of data on a 1-km square ulation density in the current urban scenario. The maps of mesh. The fractions of urban and LU_dom in a model urban fraction, daily mean AH, and population for the grid cell were calculated from the 1-km mesh fraction current urban scenario are shown in Figs. 2a, 2f, and 2k, (Fig. 2a). respectively. The urban area was distributed along the The sensible and latent anthropogenic heat fluxes railway. A larger AH was determined closer to the cen- (AH) for the current urban scenario were estimated as tral area. follows: 1) The AH from residential and commercial b. Urban scenarios for the dispersed city and compact buildings was calculated by multiplying the floor area by city the AH consumption rate per unit area for each building type reported in Fukami et al. (2003). The floor-area The dispersed-city and compact-city scenarios were dataset was created on the basis of reported fixed-asset produced using a spatially explicit land-use model tax rolls (FATR) published by the Ministry of Internal (Yamagata et al. 2011). The model is a land-use equi- Affairs and Communications (MIC) in 2005. 2) The AH librium model entirely based on urban economic theory. from road transport was calculated from carbon dioxide The land-use model considers three different agents

(CO2) emission data from road transport (Kannari et al. (i.e., households, developers, and absentee landlords) 2007), CO2 emission coefficients, and the calorific value of and determines the location of housing to maintain gasoline (Ministry of the Environment 2012). 3) The total a balance between utility maximization for households number of AH data per 1-km mesh cell was obtained as and profit maximization by developers and absentee the sum of AH from buildings and transport. The diurnal landlords. Therefore, the distribution of residential variations in sensible and latent AH emissions were based buildings changes depending on the demand for land on values for August reported in National Institute for and housing under given conditions, whereas the dis- Resources and Environment (1997), as shown in Fig. 3. tribution of offices and commercial buildings is fixed The diurnal cycle was assumed to be horizontally uni- to that of the current urban situation. The details of form in this study, although it is likely to be spatially this spatially explicit land-use model are described in inhomogeneous. The number of building levels aver- Yamagata and Seya (2013) and Yamagata et al. (2013). aged in a grid cell was calculated by dividing floor area To show the possible range of changes in the urban form by land area, and the floor-area and land-area data were in the TMA, the following conditions were assumed in obtained from the FATR report. The building level was the land-use model. The strategy for the dispersed-city used only to define the urban category for each grid cell scenario was automobile dependent and included 1) free in this study because it is difficult to estimate the buil- purchase costs for a car, 2) no fuel cost for a car, and 3) ding height, roof width, and road width for each grid cell toll-free expressways. Alternatively, the compact-city even though they are important parameters for the scenario assumed 1) a reduction in the land available for UCM. Areas with building levels of eight floors or more residential buildings in areas more than 1 km away from and fewer than four floors were defined as urban cate- train stations and 2) the prohibition of car use. gories UC1 and UC3, respectively, and the other areas The urban fractions in the dispersed-city and compact- were defined as UC2 (Fig. 4). The urban parameters ex- city scenarios were determined by the land-use model cept for the urban fraction and AH were given specific according to the above assumptions. The increased/ values according to the urban category in each grid cell, decreased portion in the urban area was balanced by as shown in Table 2. The population data, provided by changing the LU_dom area in a grid cell. The distributions

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22 FIG. 2. Distribution of urban parameters: (a)–(c) urban-area ratio, (f)–(h) daily mean anthropogenic heat emission (W m ), and (k)–(m) population per square kilometer in the (left) current urban situation, (center) dispersed-city scenario, and (right) compact-city scenario. Differences in the urban-area ratio and anthropogenic heat ﬂux from the current urban situation are shown in (d) and (i), respectively, for the dispersed-city scenario and in (e) and (j), respectively, for the compact-city scenario.

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FIG. 3. Diurnal cycle of sensible and latent anthropogenic heat emissions. The value indicates the multiplication coefficient applied to the daily average heat emissions shown in Fig. 2. of AH and population were estimated in accordance with the increase or decrease in households. Previous studies have reported that AH varies depending on outside air temperature, as a result of a positive feedback between air temperature and air-conditioning energy demand (e.g., FIG. 4. Distribution of the urban category defined by the building Kikegawa et al. 2003). This feedback was not considered in levels in the current urban situation. this study, however. Changes in AH emission from buildings in the two urban scenarios were only dependent on the changes in floor area relative to the current situa- the same as CTL_o, but land use, AH, and urban category tion. The urban category was defined according to the were different from the current urban situation and rep- number of building levels, calculated in the same way as in resented the dispersed-city and compact-city scenarios, the current urban situation using the modified floor and respectively. In addition, sensitivity experiments were land areas. The distribution of the urban category in conducted to estimate the contribution of anthropogenic the dispersed-city and compact-city scenarios was almost heat emissions and land-use changes to changes in surface the same as in the current urban situation (not shown in the air temperature. The CTL_o_noAH, URB_d_noAH, figures). The ratios of building height to road width in the and URB_c_noAH simulations used the same settings as dispersed-city and compact-city scenarios were assumed to CTL_o, URB_d, and URB_c but without the AH emis- be the same as in the current urban situation. The distri- sion. The contributions of land-use changes were ob- butions of urban parameters in the two urban scenarios are tained from the differences between URB_d_noAH or illustrated in Fig. 2. The residential area expands to the URB_c_noAH and CTL_o_noAH. The contributions of suburbs, with a lower cost of commuting in the dispersed city (Figs. 2b,d). The AH also increases in suburban areas because of frequent car use and the expansion of resi- TABLE 2. Urban parameters for each urban category. The urban dential areas. In contrast, the pattern of the urban distri- category in a grid cell is defined by the gridded building levels in the $ , bution in the compact city is similar to the current urban grid cell. The grid cells with building levels 8 floors and 4 floors were defined as UC1 and UC3, respectively, and the other areas situation (Fig. 2c), and the AH is enhanced in the central were defined as UC2. part of the TMA because of the concentration of people and the increase in floor area in that area (Figs. 2h,j). Urban category UC1 UC2 UC3 c. Experimental design Building height used in UCM (m) 16 10 6 Roof width used in UCM (m) 9 9 9 The numerical experiments listed in Table 3 were Road width used in UCM (m) 11 11 11 conducted to evaluate the effect of moderation of the Sky-view factor 0.3 0.45 0.65 Displacement height (m) 4.8 3 1.8 urban form on the urban heat island. The simulation Roughness length for momentum (m) 2.4 1.5 0.9 CTL_o was a control simulation for 2010 using the Roughness length for heat (m) 0.24 0.15 0.09 2 2 2 current urban situation. URB_d and URB_c were sim- Building heat conductivity (J m 1 s 1 K 1) 2.28 2.28 2.28 ulations to estimate the impact of changes in the urban Emissivity 0.97 0.97 0.97 form on urban climate. These simulations were otherwise Surface albedo of roof/wall/ground 0.2 0.2 0.2

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TABLE 3. Experimental design.

Run name Expt description Boundary data Land use AH CTL_o Hindcast simulation NCEP–NCAR reanalysis Current urban AH of current data in 2010 situation (original) urban situation URB_d Impact of urban NCEP–NCAR reanalysis Dispersed-city scenario AH of dispersed-city scenario data in 2010 scenario URB_c Impact of urban NCEP–NCAR reanalysis Compact-city scenario AH of compact-city scenario data in 2010 scenario CTL_o_noAH Sensitivity experiment NCEP–NCAR reanalysis Current urban 0 data in 2010 situation (original) URB_d_noAH Sensitivity experiment NCEP–NCAR reanalysis Dispersed-city scenario 0 data in 2010 URB_c_noAH Sensitivity experiment NCEP–NCAR reanalysis Compact-city scenario 0 data in 2010

the differences in AH were estimated from the difference Saitama, and Gunma prefectures. These areas all have in the AH impact on surface air temperature between the a higher urban-area ratio (shown in Fig. 2a). Compared two scenarios and the current urban scenario. The AH with these areas, the eastern parts of the TMA, Ibaraki, impact for each scenario was obtained from the differ- and Chiba prefectures displayed relatively lower surface ence between the simulations with and without AH under air temperatures because of the limited urban area. The the corresponding urban scenario. nighttime temperature simulated in CTL_o agreed well with the observations (Fig. 5b). The mean bias of nighttime temperature averaged over the 57 observation 4. Results points was 20.078C, and the root-mean-square error The control simulation (CTL_o) was compared with (RMSE) was 0.858C. The temperature in Chiba and observations to validate the model. The observed Ibaraki was underestimated by about 18C. The reason monthly-mean nighttime surface air temperature be- for this temperature underestimation was related to the tween 0100 and 0500 Japan standard time (JST) (here- underestimation of the number of small settlements in inafter, nighttime temperature) in August is shown in mountainous regions in the urban-fraction data, espe- Fig. 5a. The temperature in the central part of the TMA cially in the southern part of Chiba (not shown in the exceeded 278C. Areas with high temperatures (.268C) ﬁgure). The simulated magnitude of the nighttime wind were found in Tokyo and the eastern parts of Kanagawa, speed also agreed well with the observation. The mean

FIG. 5. Distribution of monthly nighttime surface air temperatures averaged between 0100 and 0500 JST in August 2010: (a) observed data and (b) model results for the CTL_o simulation. The gray color in (a) illustrates the topography, which is the same as that shown in Fig. 1b.

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FIG. 6. The differences in monthly nighttime surface air temperature averaged between 0100 and 0500 JST in August 2010 between the current urban situation (CTL_o) and (a) the dispersed-city scenario (URB_d) and (b) the compact-city scenario (URB_c). bias of wind speed averaged over all of the observation nighttime temperature was ;0.038C, which was almost 2 2 points was 0.86 m s 1, and the RMSE was 1.17 m s 1. the same amplitude as projected in URB_d. These re- The changes in nighttime temperature due to modiﬁ- sults indicate that the compact-city scenario had the cation of the urban form are indicated in Fig. 6. A surface potential to reduce the intensity of the urban heat island air temperature increase was predicted throughout most in the whole of the TMA. of the TMA in the URB_d, with the exception of the central part (Fig. 6a). Warming of more than 0.68Cwas simulated in the Chiba and Ibaraki prefectures because of the large expansion of urban area in the region (as shown in Fig. 2d). The developed urban area in Tokyo, Kanagawa, and Saitama was projected to experience at most about a 0.38C temperature increase. In the central part of Tokyo, however, nighttime temperature was projected to decrease by about 0.18C. The change in area-averaged nighttime temperature over the TMA is illustrated in Fig. 7. In the URB_d simulation, a temperature increase of 0.348C was projected. Of this increase, 0.318C was caused by land-use changes and 0.038C was derived from the increase in AH. Therefore, the temperature increase in the dispersed-city scenario was mainly attributed to land-use changes associated with urban expansion. The inﬂuence of AH was also not negligible because it generated a 12% enhance- ment in the effect of AH on surface air temperature FIG. 7. The area-averaged nighttime surface air temperature relative to the current urban situation. differences between the dispersed-city or compact-city scenarios In the URB_c simulation, the response of nighttime and the current urban situation. White bars show the temperature differences between the URB_d or URB_c and CTL_o simula- temperatures to changes in the urban form was opposite tions. Gray bars indicate the contribution of land-use changes to that projected in the URB_d simulation. The nighttime the temperature differences, which were obtained from the dif- temperature was reduced by about 0.18C over a large ferences between the URB_d_noAH or URB_c_noAH and area of the TMA, except for the central part, where the CTL_o_noAH simulations. Black bars indicate the contribution of temperature increased by about 0.18C(Fig. 6b). The area- AH emissions, which were estimated by the differences in the ; 8 impact of AH between either of the two urban scenarios and the averaged surface air temperature decreased by 0.09 C current urban situation. The impact of AH for each urban scenario because of the concentration of urban area (Fig. 7). The was calculated by the differences between simulations with and impact of the reduction of AH on the change in without the AH emission.

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FIG. 8. Diurnal variations of ground surface temperature at (a) Ryugasaki and (b) Tokyo. The two broken lines show the difference in surface temperature from the current situation in the dispersed-city and compact-city scenarios. Also shown for (left) Ryugasaki and (right) Tokyo is (c),(d) the current urban energy budget and changes in the energy budget from the current situation in the (e),(f) dispersed-city and (g),(h) compact-city scenarios.

To clarify the causes of surface air temperature changes dispersed-city scenario and decreased to 0.187 in the in detail, the changes in surface skin temperature and compact-city scenario, whereas in Tokyo it changed from energy budget at Ryugasaki and Tokyo are shown in 0.826 to 0.809 in the dispersed-city scenario and 0.828 in Fig. 8. These locations are a rural area and a central area, the compact-city scenario. The reason for the small respectively, as shown in Fig. 1b. The illustrated values of change in the urban ratio between the current urban and temperature and fluxes are averaged in nine grid cells the compact-city scenario in Tokyo is that the urban area centered on the nearest grid cell from each AMeDAS expanded vertically in the central area. station. The urban-area ratio at Ryugasaki increased The upward latent heat flux is greater than the sensi- from 0.197 in the current situation to 0.249 in the ble heat flux in the daytime in Ryugasaki, because the

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FIG. 9. The relationship between monthly-mean daily minimum surface air temperature and the population for a certain grid cell. The daily minimum surface air temperature was defined as the minimum temperature between 0100 JST and 0500 JST. Regions i–iii indicate where people live, and their locations are defined in Fig. 1b. urban area is limited and irrigated cropland and pasture was larger than in a rural area (Fig. 8d). In the dispersed- dominate in the current urban situation (Fig. 8c). During city scenario, the nighttime surface temperature was the night, the ground heat flux is negative as a result of the projected to reduce by approximately 0.48C in Tokyo conduction of heat from the warm ground to the cooler (Fig. 8b). The main cause of the temperature reduction surface. The release of stored heat as longwave radiation was a decrease in anthropogenic sensible heat emission by 2 results in a cooling of the ground surface. Figures 8e and 8g approximately 13 W m 2, although several changes oc- 2 display the differences in the fluxes between the current curred in the ground heat flux of about 3 W m 2 (Fig. 8f). urban and the dispersed-city or compact-city scenarios, In contrast, the surface temperature in Tokyo was pro- respectively. In the dispersed-city scenario, the nighttime jected to rise by approximately 0.388C in the compact-city surface temperature was projected to increase by ap- scenario (Fig. 8b). The changes in the latent heat flux and proximately 0.548C in Ryugasaki (Fig. 8a). The sensible the ground heat flux were minimal during the night and latent heat fluxes increased slightly during the night as (Fig. 8h). Therefore, the increase in surface air temper- a result of the increase in anthropogenic heat emissions. ature was mainly due to the growth of anthropogenic heat The released ground heat flux was enhanced during the fluxes in Tokyo in the compact-city scenario (Fig. 8h). night with the increase in surface temperature. The surface The reduction in nighttime temperature is important in temperature was higher than for the current urban situa- terms of sleep disruption and heatstroke. The compact- tion during the night, however, because of the increased city scenario resulted in a reduced nighttime temperature heat storage associated with the expansion of the urban in the TMA, as shown in Figs. 6 and 7. On the other hand, area. Therefore, the reduced effect of radiative cooling nighttime temperature increased in the central part of the induces the elevation of nighttime surface air temperature TMA, which has a very dense population. Figure 9 shows in the dispersed-city scenario in addition to the increase of the population in different areas classified by tempera- anthropogenic sensible heat emissions. In the compact-city ture category, as defined by the monthly mean of daily scenario, the nighttime surface temperature was projected minimum nighttime temperature (Tminave). The daily to be reduced by about 0.148CinRyugasaki(Fig. 8a). This minimum nighttime temperature was defined as the min- is a result of the reduction of the heat capacity associated imum temperature between 0100 JST and 0500 JST. The with the slightly downsized urban areas. population in each temperature category from I to IX was In Tokyo, the diurnal variations of heat fluxes dis- calculated by summing the population in the grid cells that played characteristics typical of an urban area. The sen- met the conditions of Tminave. sible heat flux prevailed throughout the day over the In the lower temperature categories (from VI to IX), latent heat flux, and the amplitude of the ground heat flux the population increased in both the URB_d and URB_c

Unauthenticated | Downloaded 10/05/21 05:00 PM UTC 1896 JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY VOLUME 53 simulations. Conversely, the population decreased in the higher temperature categories (II and III) when compared with that in the current urban situation. This resulted in a tendency for nighttime temperatures affecting citizens to improve in both urban scenarios. This happened because either people would move into the surrounding areas (region iii in Fig. 1b) where temperatures were lower in the dispersed-city scenario, or the nighttime temperature would be reduced throughout much of the TMA in the compact-city scenario, as shown in Fig. 6b.Note, however, that the population increased by about one million in the highest temperature category (I) in the URB_c simulation. Most people in category I live in the central area of the TMA (i.e., region i). This resulted in FIG. 10. (a) The change in monthly-mean per capita CO2 emis- further deterioration in nighttime thermal conditions in sions averaged in the Tokyo metropolitan area relative to the the central part of the TMA in the compact-city scenario. current urban situation, and (b) the differences in daily minimum surface air temperature from the current urban situation in the vicinity of the Tokyo AMeDAS station (the averaged value in the 5. Discussion area within 5 km of the Tokyo AMeDAS station). Gray and dark gray bars indicate the results of the dispersed-city and compact-city Moderation of the urban-heat-island effect is likely to scenarios, respectively. become an adaptation to global warming. In addition, it is important to reduce the emission of greenhouse gases The monthly-mean daily minimum surface air tem- so as to mitigate future global warming. Urban areas perature (Tminave) increased in the central area as contribute 67% of global energy consumption and 71% a result of the high population density in the compact- of global CO2 emissions (International Energy Agency urban scenario, as shown in Figs. 6b and 9. The nighttime 2008). One of the advantages of the compact urban form thermal environment deteriorated further in the central is the efficiency of energy use that results from down- area (Fig. 10b). This finding suggests that the adoption of sizing the city area and increasing the active use of public a compact-city strategy alone may not always reduce the transportation systems (Newman and Kenworthy 1999; increase in temperature due to global warming in Taniguchi et al. 2008; Nakamichi et al. 2012). densely urbanized areas such as the TMA, although it is The change in per capita CO2 emission when com- appropriate for the mitigation of global climate change pared with the current situation is shown in Fig. 10a. The from the perspective of energy consumption. method used to calculate CO2 emissions for each urban The Tminave in the central area was projected to in- scenario is described in appendix B. The per capita CO2 crease by up to 0.268C in the compact-city scenario. emission is 242 kg CO2 per month in the TMA in the Fujibe (2013) investigated the relationship between current urban situation. The emission increased by mortality due to excessive heat and surface air temper- about 80 kg CO2 in the dispersed-city scenario, corre- ature averaged over July and August from 1909 to 2011 sponding to a level about 1.3 times that in the current in Japan. A regression analysis was applied to inter- urban situation. This is because of the increase in energy annual variations in mortality rate and daily minimum use associated with the expansion of floor area and ag- surface air temperature and revealed that the regression gressive vehicle use. In contrast, the CO2 emission in the coefficient of the mortality rate to minimum surface air 2 compact-city scenario slightly decreased when com- temperature is approximately 40%–60% 8C 1. This pared with the current urban situation, despite the fact finding suggests that the estimated warming of nighttime that the efficiency of energy consumption per unit area surface air temperature has a nonnegligible impact on was not considered in this study. Therefore, the the elevation of the mortality rate in the central area of compact-city scenario with lower energy consumption the TMA. seems more likely to mitigate the effects of global warming than does the dispersed-city scenario, although 6. Conclusions and remarks the reduction in CO2 emissions was very small in the TMA (Fig. 10a). The reason for the small reduction in This study investigated the moderation of nighttime

CO2 emissions in the compact-city scenario seems to be surface air temperatures in the TMA through simulations that the TMA developed along the railroad lines and of dispersed-city and compact-city scenarios at the cur- already had some features of a compact city. rent population level. The area-averaged nighttime

Unauthenticated | Downloaded 10/05/21 05:00 PM UTC AUGUST 2014 ADACHI ET AL. 1897 temperature in the TMA increased by about 0.348Cin Acknowledgments. The authors are grateful to the dispersed-city scenario and decreased by about Dr. Hiroaki Kondo for providing their anthropogenic 0.18C in the compact-city scenario when compared heat data to estimate the diurnal variation of AH. This with the current urban situation. The area-averaged study was supported by the Global Environment Research thermal environment during the night tended to de- Fund (S-5-3) of the Ministry of the Environment of Japan teriorate in the dispersed-city scenario and to improve and the Research Program on Climate Change Adapta- in the compact-city scenario. In contrast, each urban tion (RECCA) Fund by Ministry of Education, Culture, scenario had the opposite impact on the nighttime Sports, Science and Technology (MEXT) of Japan. surface air temperature in the central part of the TMA, with a temperature increaseinthecompact-citysce- nario and a decrease in the dispersed-city scenario. As APPENDIX A a result, the number of people living in the area with higher nighttime temperatures (more than 27.88C) Method for the Diagnostic Calculation of Surface Air increased by about one million in the compact-city Temperature at 2 m scenario when compared with the current urban situation. Therefore, the severe high-temperature con- The method for estimating surface air temperature at ditions worsened in the city center in the compact-city 2 m above ground level was modified from the original scenario. method in WRF V3.1.1 as follows. The surface air The adoption of a compact-city scenario is expected temperature at 2 m was estimated diagnostically from air not only to moderate the urban-heat-island effect but also temperature at the first atmospheric model level by as- to act as an adaptation strategy for global warming in suming the Monin–Obukhov similarity theory. The di- urban areas because it would reduce energy consumption mensionless potential temperature gradient is expressed through more frequent use of public transport systems as (e.g., Arya 2001) and efficient energy use. The results of this study suggest ›u that the compact-city scenario is not always appropriate kz 5 f z u › h , (A1) for the moderation of the urban heat island, however, * z L especially in the central part of the TMA. To avoid a deterioration of the thermal environment in the central where k is the von Kármán constant (50.4), L is the area, the temperature increase needs to be compensated u f Obukhov length, * is the temperature scale, and h is for by other strategies, such as the greening of urban the basic universal similarity function. The temperature areas. In combination with other strategies, a compact profile is written by integrating Eq. (A1) with respect to city has the potential to be useful not only as an adapta- height as tion to the higher temperatures associated with global warming in the urban area but also as an overall mitiga- u 1 * z z0 z tion technique for global warming as a result of reducing u 2 u 5 ln 2 c , (A2) 0 k z h L greenhouse-gas emissions. This study indicates that it is 0 important to evaluate an adaptation plan for higher ur- u ban temperatures from several perspectives, that is, not where z0 is the roughness length, 0 is the extrapolated c only taking climatological aspects into consideration but temperature at the height of zT, and h is the integrated f also its impacts on urban inhabitants. similarity function for heat related to h as The aggravation of thermal conditions estimated in ð (z1z )/L this study is likely to be underestimated in the central z 0 dz c 5 [1 2 f (z)] , (A3) part of a city in the compact-city scenario because the h L h z z0/L growth of energy demand for air conditioning, due to the increased nighttime temperature, was not considered. where z 5 z/L. To determine the c function, the em- The further concentration of the urban area into the city h pirical forms of f given below were used to simplify the center leads to the verticalization of buildings in the h process, although more suitable similarity functions compact-city scenario. The wind and temperature fields were recently discussed in Jiménez et al. (2012): are affected by the increased roughness length and the enhanced shield effect of radiation as a result of the 2 f 5 (1 2 16z) 1/2 , for unstable conditions (z , 0) vertical extension of building height. Further research is h . f 5 (1 1 7z), for stable conditions (0 # z) required to evaluate these effects, because they were not h directly addressed in this study. (A4)

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TABLE B1. Parameters for calculation of CO2 emission.

HV EC Ratio (%)*

21 21 Transport Gasoline 34.6 (MJ L ) 2.32 (kg CO2 L )— 21 21 Building Electricity 3.60 [MJ (kW h) ]** 0.375 [kg CO2 (kW h) ] 44.1 3 21 3 21 City gas 44.8 [MJ (N m ) ] 2.23 [kg CO2 (N m ) ] 36.3 21 21 Heating oil 36.7 (MJ L ) 2.49 (kg CO2 L ) 9.9 21 21 LPG 50.8 (MJ kg ) 3.00 (kg CO2 kg ) 9.7

* Values estimated from the total energy consumption in the Tokyo metropolitan area. ** Heat value due to power consumption.

Corresponding to Eq. (A3) and (A4), the integrated APPENDIX B similarity function for heat was obtained as

The Procedure for Calculating CO2 Emissions z y 1 1 c 5 ln 1 2ln T , for unstable conditions, and h z y 1 1 The monthly CO2 emissions were calculated from the T anthropogenic heat emission data as follows. In the calculation, the energy coefficient and energy allocation z c 527 , for stable conditions, of energy sources were assumed to remain unchanged in h L the different urban scenarios. The CO2 emissions 22 1/2 1/2 (kg CO2 m ) from transportation were calculated as where y 5 (1 2 16z) , yT 5 (1 2 16zT) ,andzT 5 zT/L. The temperature at 2 m used for analysis was di- CO emission from transport agnosed using the integrated dimensionless equation of 2 u 5 EC 3 AH from transport 3 TOHV. Eq. (A2) and by assuming that * was constant with height. The temperature at 2 m u2m was obtained by 22 subtracting Eq. (A1) for the temperature ua at the first The AH from transport (W m ) was available for each model level from Eq. (A1) for u2m: grid cell. Here, T is the number of seconds in a month (60 3 60 3 24 3 31). The values for gasoline shown in u 1 Table B1 (Ministry of the Environment 2012) were used 2 z0 2 u 5 u 1 * ln 2 c 21 2m a k z h L for the heating value HV (J L ) and CO2 emission 0 21 1 coefficient EC (kg CO2 L ). za z0 zz 2 ln 2 c , (A5) The CO2 emissions from residential and commercial z h L 0 buildings were obtained by summing the CO2 emissions from four main energy sources: electricity, city gas, where za is the first model level. The Obukhov length, heating oil, and liquefied petroleum gas (LPG). The defined as L 5 u2 u /(kgu ), and the temperature scale, * a * CO2 emissions from each energy source were calculated u 52 r defined as * H/( acpu*), were obtained from the using the proportion of each energy source in the final grid average of the sensible heat flux H and the friction energy consumption and the CO2 emission coefficient r 5 velocity u* in a grid cell; a is density at z za, and cp is for each energy source. The proportion of each energy the specific heat of air at constant pressure. The grid source in the final energy consumption (Ratio) was ap- averages of H and u* were obtained as follows (Chen plied to the value in the TMA (Agency for Natural et al. 2011): Resources and Energy 2012):

5 1 CO emisssion from buildings H FurbHurb FvegHveg and (A6) 2 4 5 å (EC 3 AH from buildings 3 Ratio 3 TOHV ). 5 2 1 2 1/2 i i i u* (Furbu*urb Fvegu*veg) , (A7) i51

where Furb and Fveg are the fractional coverage of For HV and EC, the values reported in Ministry of the urban and dominant land use except for urban Environment (2012) were used except for the HV (LU_dom), respectively. Also, Hurb and u*urb are the value for electricity, which was taken from Kainou sensible heat ﬂux and the friction velocity for the subtile (2012). The total CO2 emissions in the TMA were of urban, while Hveg and u*veg represent the subtile of calculated from the emissions from transportation and LU_dom. buildings.

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