Heatwave intensity and frequency are predicted to intensify in the coming years and this will bear adverse consequences to the socio-economic fabric of urbanized areas. Urban areas are dominated by built surfaces that increase heat storage and reduce water retention capacity. This parlous combination results in higher near surface air temperature compared to the surrounding rural areas that is commonly referred to as the urban heat-island intensity (UHI). The primary motive of this study is to quantify the interaction of this city-scale UHI with mesoscale heatwave episodes and analyze the factors that contribute toward this interaction. A modified version of the Weather Research and Forecast model (WRF) is utilized to simulate two heatwave episodes in the highly urbanized New York City. To better represent the urban surface-to-atmosphere exchanges the default urban canopy model in WRF is replaced by Princeton urban canopy model that includes sub-facet level representation for surface energy fluxes. Also the dominant approach used to ascertain the land use category in WRF at every grid point is substituted with a mosaic approach that solves for multiple land use categories at every grid point and fractionally averages the resulting fluxes. Our results indicate that during the heatwave episodes the daily averaged UHI in NYC increased by 1.5 K. Most of this amplification occurred in the mid afternoon period when the temperatures peaked. Wind speed and direction, deficit in available energy and moisture availability were found to affect the UHI in a systematic way. While deficit in available energy and wind magnitude affected the UHI on diurnal timescale, the long term trends in UHI and its interaction with heatwave was mainly constrained by moisture availability. During the heatwave episodes, the coastal winds were blocked by the presence of the anticyclonic system and the winds were predominantly from the west. This warm air that advects from the west is amplified as it passes over the industrial zone to the west of the city and has severe implications to UHI in NYC.

Urbanization is an extreme way in which human being changes the land use/land cover of the earth surface, and anthropogenic heat release occurs at the same time. In this paper, the anthropogenic heat release parameterization scheme in the Weather Research and Forecasting model is modified to consider the spatial heterogeneity of the release; and the impacts of land use change and anthropogenic heat release on urban boundary layer structure in the Pearl River Delta, China are studied with a series of numerical experiments. The results show that the anthropogenic heat release contributes nearly 75% to the urban heat island intensity in our studied period. The impact of anthropogenic heat release on near-surface specific humidity is very weak, but that on relative humidity is apparent due to the near-surface air temperature change. The near-surface wind speed decreases after the local land-use is changed to urban type due to the increased land surface roughness, but the anthropogenic heat release leads to increases of the low-level wind speed and decreases above in the urban boundary layer because the anthropogenic heat release reduces the boundary layer stability and enhances the vertical mixing.

The urban heat island (UHI) has been the subject numerous studies worldwide, dating back as far as the 19th century. This phenomenon has been measured in large cities as well as in small villages. However, as of yet simple models to estimate the UHI are lacking. Considering the complexity of the urban environment this is not surprising. Besides internal factors, such as evaporation in a city (through vegetation, soil moisture, or surface water) or thermal properties of the buildings, there are also external factors to consider (e.g. wind speed and direction, cloud fraction or the stability of the atmosphere). Including all relevant factors makes deriving a simple model a complicated task.

With an old method often used to tackle complex physical problems, dimensional analysis, we attempt to derive a formula for the maximum urban canopy heat island. The most important factors influencing the night-time urban heat island are included in this analysis. Using data from 30 measurements stations in and around Wageningen (the Netherlands), a formula for the maximum urban heat island is revealed. This formula will be validated with measurements from other cities.

The scientific evaluation of urban heat islands (UHI) over city clusters is important for the study of the urbanization effects of regional climate and environment. In this paper, UHI and meteorological elements over the Pearl River Delta (PRD),China, are investigated using data measured at 20 meteorological observatories during the period of 1999-2008. A new method is adopted to choose the suburb meteorological observatories for calculating UHI intensities over three zones in PRD. The average UHI intensity is 0.71℃ and the linear trend is 0.29℃/10a. The spatial distribution of UHI presents a tri-pole pattern, in which the UHI intensities in the middle zone of PRD are higher than those in the east and the west zone. The average UHI shows clearly seasonal and diurnal changes, is weakest in spring (0.39℃), strongest in autumn (1.06℃), higher in nighttime (0.91℃) than in daytime (0.53℃). The UHI intensity decreases with increasing low cloud cover, relative humidity, wind speed and precipitation. The results may contribute to city planning and risk zoning of meteorology and environment in PRD.

Impact of thermal inertia for urban heat island circulation is clarified by high spacial and temporal resolution observation in Kyoto City, Japan. The 38 observational stations are located with an average separation of 1 km. The observed meteorological element is temperature and long-wave radiation with time resolution of 1 minute. From the observation it is confirmed that in the daily variation of the heat island intensity (temperature difference of urban and rural areas), two different phases exist: phase A in which the temperature differences increase rapidly after sunset, and phase B in which the difference decreases towards to stable value after phase A, as is mentioned by Haeger-Eugensson & Holmer, 1999. The relation between an amount of long-wave radiation and heat island intensity suggests that the contribution of anthropogenic heat for urban heat island intensity is below half of the influence produced by the difference in thermal response.

When clouds appear, radiation balance will change. The change of radiation balance causes temperature change. We estimate local effective thermal inertia (LETI), which does not include the effect of thermal advection but the effect of sensible heat flux, from long-wave radiation and temperature change in cloud appearance. LETI of urban area is estimated as 4.3-7.9 x 10^3 [W K-1 s-1/2], of rural area as 1.7-3.4 x 10^3 [W K-1 s-1/2]. LETI of urban area is more than two times of estimated by previous works (Carlson et al., 1981; Sugawara et al., 2001; Takemoto & Moriyama, 2002). Thermal inertia estimated in previous works would be smaller than real value for temperature decrease by the influence of thermal advection. The difference of LETI between urban and rural area is consistent with the difference of temperature decrease in phase A.

In phase B, it is implied that advection has a key role of the heat island intensity from analysis of wind data of Kyoto Local Meteorological Office and our temperature data. By applying the argument on Mori & Niino, 2002 to urban heat island phenomenon, it is clarified that the ratio of LETI between urban and rural is important for whether advection will occur or not. When the ratio of LETI is more than twice, the difference of thermal response cause the difference of vertical temperature distribution, and the gravity current (wind advection) is produced by the temperature distribution.

Extreme heat events are projected to increase in both frequency and duration as a consequence of global warming. Understanding their impacts in large urban centers and their neighboring areas has become increasingly important. This study aims to use the multi-level urbanized version of the community mesoscale Weather Research and Forecasting (uWRF) model to investigate the impacts of New York City (NYC) land cover on local and its suburban Long Island (LI) weather and climate during a heat wave event in July 2010. A sensitivity experiment consisted of three simulations: control run using unaltered land use index values, forest run with both modified land use index values and initial condition soil moisture profile, and urbanized run using the Building Energy Parameterization (BEP) and Building Energy Model (BEM) options in uWRF. The control and urbanized simulations were able to successfully capture the observed maximum daily temperatures and heat index values associated with the heat wave event, as well as the strong nighttime urban heat island signal. The model showed the greatest sensitivity in nighttime minimum temperatures, with values in the forest case up to 2°C cooler than the control and urbanized simulations over NYC, and up to 1°C cooler over LI. Peak sensible heat fluxes were 20% higher over the city in the urbanized simulation than in the control run, due to increased anthropogenic heat production from building air conditioning systems. Over LI, the smallest sensible heat fluxes were observed in the forested case, with peak values up to 3% lower than in the other two cases.

The climatology of planetary boundary layer heights (PBLH) have been revisited over ten US sites with contrasting land surface features (inland urban, inland rural, coastal urban and coastal rural), based on long-term (1998-2010), high-resolution (every six seconds) radiosonde observations. The central objective of this study is to investigate the roles of land surface properties/ambient environment in shaping climatological behaviors of PBLH. A new objective approach, which bases on analyzing profiles of virtual potential temperature, is used to determine PBLH for each sounding. The results are further validated by the well-known bulk Richardson number based approach. Both approaches present consistent estimations of PBLH for all selected sites. Preliminary results are: 1) PBLH at morning time (11UTC) does not present distinct seasonal cycles, with shallow boundary layers less than 1 km; 2) Both inland rural and inland urban sites present distinct seasonal cycles at afternoon time (23UTC). PBLH present strong positive dependence on air temperature in inland sites, with the maxima attained in warm seasons (June, July August and September); 3) PBLH at Coastal sites (coastal urban and coastal rural) do not vary significantly across seasons at either morning or afternoon time, possibly related to the advance or retreat of sea/land breeze; 4) Different behaviors of PBLH exist between rainy days and non-rainy days, possibly related to the perturbation of rain cloud existence in the vertical profiles of temperature and humidity, but needs further examination. Attribution analyses on the climatological behaviors of PBLH among sites are underway, and will be presented in full text.

The characteristics of urban atmospheric boundary layer (ABL) height on January, April, July and October 2014 using the gradient method by a ceilometer with a wavelength of 910 nm and an aerosol lidar with a wavelength of 532 and 1064 nm installed at two urban sites (Gwanghwamun and Jungnang) in Korea are analyzed. The Gwanghwamun site located at urban commercial area is 10 km apart from the Jungnang site located at urban residential area. The ABL height is determined by a height with a strong gradient of vertical backscatter intensity. It is found that the ABL height at both sites show a similar pattern and has a strong diurnal variation with a steep increase at 09-12 KST with a maximum in the late afternoon. And it is not determined clearly and the correlation between the ABL height by a ceilometer and that by an aerosol lidar is relatively low in case of high PM10 concentration such as Asian dust, haze and smog. Uncertainty of ABL height is also found to be strongly affected by the weather phenomena such as rain, haze or fog.

The Atmospheric Boundary Layer is a complex system, under permanent transition. The transition from night to day-time and the subsequent rapid growth of the convective boundary layer are periods when the boundary layer flows are non-stationary and poorly understood, especially in the highly complex and heterogeneous urban environment. Nevertheless these periods are important for the initialization of prognostic models, basic understanding of significant meteorological processes (e.g. the evolution of the Low Level Jet) and the dispersion of pollutants.

The present study aims to present a conceptual model for the morning growth of the urban convective boundary layer, using measurements that were taken in the frame of the ACTUAL (Advanced Climate Technology Urban Atmospheric Laboratory) project. Doppler lidars operating in two scanning modes (continuous stare mode and Doppler Beam Swinging mode) and two eddy covariance systems, weather stations and net radiometer systems that were operating at 191m and 19m agl, probed vertical profiles of turbulence and wind speed over London for the period May 2011 – August 2012.

The proposed conceptual model describes the development of the mechanically and thermally generated turbulence in two phases: (a) the morning transition - from sunrise until the onset of the convective boundary layer, when the Mixing Height first reaches 200m and (b) the rapid growth period, from the onset until the fully developed convective boundary layer. Results are compared with those previously obtained for rural sites, and model results obtained from an idealized Large Eddy Simulation run.

The seasonal dependency of the urban heat island (UHI) intensity and its climatic drivers at the mid-latitudes are addressed with model-based sensitivity experiments over Belgium. Hereby, simulations with TERRA_URB is coupled to COSMO-CLM over Belgium are performed for the summer of 2012 and the subsequent winter showing a good agreement of the seasonal, daily and diurnal variability of the UHI intensity of cities in Belgium. It is a common perception that the presence of the urban fabric (UF) characterized by a scarseness in vegetation and the presence of streets and buildings is the overall dominant driver of the UHI intensity. Yet, additional sensitivity experiments with COSMO-CLM coupled to TERRA_URB clearly show that the impact of both the UF, the anthropogenic heat emission (AHE), and the synergy between those two impacts determine the seasonal dependency of the UHI intensity. Remarkably, the averaged contribution of the UF to the nocturnal boundary-layer UHI for the cities in and around Belgium (+0.45 K for Brussels) during winter is smaller than that from the AHE (+1.27 K). Conversely, the contribution of the UF (+1.97 K) dominates that of the AHE (+0.84 K) during summer. The respective contributions counteract each other during summer (−0.33 K), whereas they slightly enhance each other during winter (+0.15 K). Within the general assessment of global climate change projections, land-use change scenarios and urban-climate mitigation and adaptation, we recommend to account for each of these effects and their implications at every season.

Dhaka city is confronted with a significantly high rate of physical and population growth since 1981 (BBS 1997; BBS 2003, BBS 2012), which has created tremendous pressure on urban land, utility services, and other amenities of urban life. We perform a systematic study of Dhaka city in Bangladesh to assess the urban heat island intensities (UHI) by means of remotely sensed land surface temperature data to understand the latest intensity and dynamics of heat-island phenomena in Dhaka by using meteorological parameters from observations and WRF model simulation.

Capital of Bangladesh, mega city Dhaka has grown by leaps and bounds during past 2 - 3 decades and strongly represents tropical climatic conditions where such studies are practically non-existent. Urban heat island effects were found to be most dominant in areas of dense built up infrastructure and intense human activity. The UHI was observed to be higher in magnitude both during afternoon hours and night hours (maximum up to 7.5 ̊C) similar to some recent studies. The four high ranking urban heat island locations in the city are within commercial and/or densely populated areas.

Key words: Urban Heat Island, land-use land-cover, meteorological parameters, WRF model.

Urban climate affected by urban green areas, building and road. To investigate the effect, we observed air temperature, relative humidity, wind speed, wind direction and precipitation using multi sensor(WXT-520, VAISALA) in seoul. Air temperature is lower in green areas than in urban areas. Relative humidity is higher in green areas than in urban areas. Air temperature difference between green areas and urban is 0.4℃ (clear day), 1.0℃ (cloudy day) in daytime (0800~1400). In nighttime (2000~0600) it is 2.0℃ (clear day), 1.2℃ (cloudy day). It can be confirmed that the effect of green areas greatest at nighttime and on clear day. Also, the air temperature difference depend on wind speed. In daytime, the difference is not changed significantly, in nighttime there is the difference is largest.

The urban heat island (UHI) effect is one of the most significant phenomena caused by urbanization. Till 2011, the urbanization rate of China had reached to 51.27%. By 2050, there is a potential that the urbanization rate of China may break through 70%. Therefore, Chinese major cities will maintain their expansions and growths in recent decades. That means if without precise planning and control, the UHI effects will become more and more serious in these cities. Urbanization will not only affect the urban itself on its UHI effect. In our former study, we have discovered that the changes of urban morphology of Wuhan will cause its downwind rural areas’ temperature to rise 0.5 to 1 °C.

The aim of this study is assessing the impact of upwind urbanization on the UHI effect of downwind areas. To achieve that, we selected two areas next to each other along the prevailing wind direction of Wuhan in summer. One is in the upwind position, and the other is in the downwind position. To quantitatively evaluate the impact, we set 3 groups of 15 cases with different building densities, building heights, or green coverage ratios in the upwind area, and used Weather Research and Forecasting model of WRF to simulate each of the cases.

According to the results, the average temperature of upwind area decreased, while the building height of this area is increasing. Oppositely, affected by the building height of upwind area, the average temperature of downwind area increased. We also discovered that, the average surface skin temperature of downwind area increased approximate 7% when the building density of upwind area increased from 25% to 45%. However, the average surface skin temperature of downwind area remained unchanged after the building density of upwind area exceeded 30%. Comparisons among building density, building height, and green coverage ratio of upwind area showed that building density is the key factor contributing to the UHI effect of downwind area.

A 24 hour mobile traverse measurement was conducted in the city of Hong Kong to analyze the effect of urban geometry of the urban air temperature. The vehicle equipped with temperature sensors drive along the fix route for 2 sunny days, September 16 which is a weekend and September 17 which is a week day in 2012. A universal parameter, the sky view factor, is used for characterizing the urban geometry. Six places with distinct urban morphology characteristic are chosen for detailed analysis. The results reveal that although there are many factors such as anthropogenic heat that may influence the measurement results, the urban geometry has significant effect on the urban air temperature. For the compact areas with small sky view factor, the air temperature increase rate is the slowest during the morning. Thus, it experience cooler thermal environment at the daytime. Also, the cooling rate of small sky view factor area is slow after sunset. On the contrary, the daytime air temperature for the area with large sky view factor always very high. The effect of anthropogenic heat emission on the urban thermal environment by vehicles and buildings seems much stronger than urban geometry. There are clearly difference of temperature profile of Sunday and Monday due to the effect of anthropogenic heat. Also, the effect of the vegetation area is very limited, especially for large anthropogenic emission area.

Urban heat islands (UHI) are a clear, well-documented example of an anthropogenic modification to climate that has an atmospheric, biological, and economic impact. This review shows how satellite-based and modeling studies continue to help unravel the factors that are responsible for urban heat island development and are providing a basis for the development and application of sustainable adaptation strategies.

As urban areas continue to expand as a result of land use land cover changes, there is a heightened awareness that scientific knowledge of the urban heat island must be more effectively communicated to architects, engineers, and planners and translated into intelligent urban design.

Green roof technology and greening of urban set up is a case in point. This and other technologies are being slowly adopted, and research published since 2003 suggests that the pace with which many practical applications are put into practice should accelerate.

The study has revealed significant differences of air temperature and relative humidity at four study areas of Dhaka city. Motijheel, the commercial heart of Dhaka City has the highest average temperature at noon (12 pm: 29.0°C) and at evening (6pm: 27.3°C). Little variation of relative humidity is seen among the areas at noon (12pm). All the areas have 49% mean relative humidity for the month of November except Agargaon’s Bangladesh Meteorological Department’s weather station where relative humidity reaches 44%. In the evening this variation becomes significant as in Motijheel and Segunbagicha area mean relative humidity for the month of November remain below 60% and in other two sites Dhaka University area and Agargaon area it reaches above 60% .Motijheel area has the lowest mean air temperature range (1.7°C) and mean relative humidity range 8%. These types of significant differences between Motijheel area and other study areas are not only found but also significant difference are found among other areas. These evidences bring the testimony of urban microclimatic condition and worsening heat environment in Dhaka city. Proper understanding and mitigation strategies are required to improve heat environment and to minimize microclimatic conditions in Dhaka city.

Generally, in situations where the initial ground temperature field is unknown or unsatisfactorily known, numerical simulations must be carried out for several years with an assumed initial ground temperature in order that the system defined by the building and the surrounding soil reaches equilibrium. Note that, equilibrium means that the grid nodes after a certain time point have approximately the same temperatures at the same corresponding hour every year. Sometimes it is of paramount importance to evaluate the thermal performance of a building at a specific location over a long period of time. The same applies for the calculation of soil’s temperature due to the building’s presence.

Usually, an initial ground temperature must be assumed and the model run for a long period (e.g. 4 years), in order to approximate the thermal performance of the earth-contact domain when it reaches equilibrium. The duration of the period that the simulation must be carried out depends on how good the initial ground temperature has been approximated in relation to the meteorological conditions and the location. Basically, when a structure is constructed, the presence of the building in combination with the meteorological conditions tends to drive the ground temperature field below it after the system reaches equilibrium. In the present study, an effort will be carried out in order to predict soil’s temperature due to the interaction between the atmosphere, structural components and ground for several years.

Urbanization negatively impacts the environment mainly by the production of pollution, the modification of the physical and chemical properties of the atmosphere, and the covering of the soil surface. Considered to be a cumulative effect of all these impacts is the Urban Heat Island (UHI) defined as the rise in temperature of any man-made area, resulting in a well defined, distinct "warm island" among the "cool sea" represented by the lower temperature of the areas nearby natural landscape. Though heat islands may form on any rural or urban area, and at any spatial scale, cities are favored, since their surfaces are prone to release large quantities of heat. Nonetheless, the UHI negatively impacts not only residents of urban-related environs, but also humans and their associated ecosystems located far away from cities. In fact, UHIs have been indirectly related to climate change due to their contribution to the greenhouse effect, and therefore, to global warming.Of late Shillong, (the study area) has experienced a progressive replacement of natural surfaces by built-up surfaces through urbanization, which constituted to be the main cause of UHI formation. Built surfaces of the study area is replaced by non-reflective and water-resistant construction materials that tend to absorb a significant proportion of the incident radiation, which is released as heat, therefore, utilizing a relatively large proportion of the absorbed radiation in the evapotranspiration process and release water vapour that contributes to cool the air in their vicinity. The rapid urbanization is the prime concern in the study area, which resulted in the rise of UHI level. The decrease and fragmentation of vegetated areas, inhibits atmospheric cooling due to horizontal air circulation generated by the temperature gradient between vegetated and urbanized areas (i.e. advection). The radiation is ultimately absorbed by the building walls (i.e. reduced sky view factor), thus enhancing the urban heat release. Additional factors such as the scattered and emitted radiation from atmospheric pollutants to the urban area, the production of waste heat from air-conditioning and refrigeration systems, as well as from motorized vehicular traffic (i.e. anthropogenic heat), and the obstruction of rural air flows by the windward face of the built-up surfaces, have been recognized as additional causes of the UHI effect. In the light of the above, the present paper will emphasize on the urban phenomenon particularly the overall urban land use pattern which is primarily responsible for the development of UHI in the study area.

Currently, 53.6% of the world's population is living in urban areas and that figure is predicted to continue to increase (United Nations, Department of Economic and Social Affairs Population Division, Population Estimates and Projections Section, 2014). On the other hand, many cities are facing problems caused by urbanization. The urban heat island phenomenon, one of the urban climate problems, is a typical environmental problem encountered in dense urban areas in summer. The use of the sea breeze to mitigate the urban heat island phenomenon has attracted attention in coastal cities. Some statistics show that about 40% of the world's population lives within 100 km of the coast (World Resources Institute, Fisheries, 2007). Further investigation of the environment in the urban area near the coast is, therefore, important.

Japan is a mountainous island nation, therefore, most of the large cities in Japan are located in coastal areas. In this study, Fukuoka-Kitakyushu metropolitan area is targeted for investigation. Fukuoka-Kitakyushu metropolitan area is the fourth largest behind Tokyo, Osaka and Nagoya. And also, all of these large cities are coastal cities. Within these areas, sea breezes are important factors mitigating the air temperature rise in summer. However, ongoing urbanization could be changing not only the mechanism of the energy balance on the urban surface, but also the sea breeze system in large coastal cities. To clarify the effects of urbanization in Fukuoka-Kitakyushu metropolitan area, a meso-scale meteorological model WRF (Weather Research and Forecasting model) was adopted for analysis. In the WRF model, land use database provided by the U.S. Geological Survey (USGS) is utilized by default. To represent the urbanization process in the targeted area, land use data of the National Land Numerical Information provided by the National Land Information Division, National Spatial Planning and Regional Policy Bureau, Ministry of Land, Infrastructure, Transport and Tourism (MILT) of Japan. USGS global land use data were derived from 1-km Advanced Very High Resolution Radiometer spans a 12-month period from April 1992 to March 1993. On the other hand, MILT land use data were recorded only in Japan, however, published in several years. In this study, land use data in 1976 and 2009 were utilized to investigate the effect of urbanization in Fukuoka-Kitakyushu metropolitan area. These results suggest that the ongoing urbanization process could raise the air temperature and change the sea breeze system in the targeted area.

Rapid uranization in cities of Rawalpindi and Islamabad in Pakistan caused to merge the both cities into one another. Presently, they are commonly known as twin cities. The combined estimated population of twin cities in 2014 is 3,225,000 making them 4th largest urban agglomeration of Pakistan. The objective of the present work is to study the impact of urban evolution on variability of local temperature trends of twin cities. To study the land-cover change of urban area such as built-up area, vegetation cover, water and barren land, LANDSAT images for the years of 1980, 1992, 2000 and 2013 are used for the image processing and classification purposes by using Erdas Imagine. Before classification function, enhancement techniques were used as noise reduction and histogram match to identify the radiometric and visual properties of images. Four classes (built-up area, vegetation, water and barren land) in each image were identified through supervised image classification with maximum likelihood rule and probability surface method. Supervised classification method is commonly used on the bases of known land features and clusters of same feature are separated by statistical or radiometric, spectral and spatial properties. To evaluate the temperature trends, homogenized time series data of daily averaged monthly minimum (Tmin) and maximum (Tmax) temperatures for the period of 1983 to 2013 was analyzed by using the linear regression. The results show that built-up area of twin cities increased from 66 km2 in 1983 to 148 km2 in 2013 with an increase of 120% within 31 years. Due to resulted urbanization, Tmin and Tmax of twin cities have been increasing. Tmin is increased more in Rawalpindi than Islamabad and Tmax is increased more in Islamabad than Rawalpindi. The highest increase in Tmin and Tmax at both stations is observed during spring season.

In recent years, mitigating urban warming that is caused by global warming and urban heat island phenomena is becoming the one of topics in urban planning. Because, it is said that the urban warming causes some influences on comfortable life, health hazards, and energy consumption. Especially, in high-rise urban area, many people gather and they are exposed to severe thermal environment in summer that is strengthened by paved surface and large amount of human activities. On the other, in such urban area, ventilation condition will be better if wind is used effectively, because high-rise buildings can pull down the upper winds. In addition, many cities in Japan are located in coastal area, and sea breeze can be used effectively.

Consequently, in this study, three areas in the downtown area of Yokohama that is the second largest city in Japan and located in coastal area are selected as a study area. Actually, temperature distributions are observed in summer and the distribution patterns are analyzed by using GIS in the areas.

In the beginning, air temperatures and wind directions and speeds are observed at some places in the study area in summer (from August 7 to August 31 in 2014) for understanding the temperature distributions. The study area is divided into three areas based on the height of buildings, building density and land use. As a result, average temperatures are different among the three areas.

This study focus on four factors, wind speed, anthropogenic heat release, land surface, and sky view factor that effect on temperature distributions. As for wind speed, spatial wind speed distributions are simulated by using CFD and the relationship between the simulated wind speed and observed temperatures are analyzed. In high-rise and low density area, negative correlation can be seen, although it cannot be seen in high-rise and high density area. In high-rise and high density area, other factors affect temperature distributions, because the ventilation is insufficient for whole area.

Other factors of temperature distributions are also analyzed. Actually, anthropogenic heat release (from the buildings and cars) map, land surface map, and sky view factor distribution map are made and they are overlaid with temperature distribution. As results some correlations are found.

Finally, by using the multivariate analysis approach (multiple regression analysis), comprehensive effects on temperature distributions are analyzed. Actually, temperature of each observation point is used as an objective variable, and each factor are used as explanatory variables. By using the multiple regression formula, temperature distribution maps in the three areas for day and night are made. And some suitable urban design ideas for each area are proposed based on the results of the multiple regression analysis.

An urban heat island (UHI) is a metropolitan area that is significantly warmer than surrounding rural areas due to human activity. The temperature difference is usually larger at night than during the day. Such UHI effects are most noticeable during the summer and winter.

The present author is a member of the LiveE! Project, which is concerned with independently monitoring weather conditions in various regions using meteorological equipment that gathers weather information and transmits it through an IP network at intervals of several seconds. Of the more than 80 measurement locations around the world, two are in our university campus in central Tokyo. One is on the concrete roof of a building and the other is in an area of greenery.

The purpose of the present study was to determine whether, even within the limited area of a university campus, temperature differences exist that are similar to those produced by the UHI effect. Air-temperature data for the two locations for the period 2010 to 2014 were used, and the values that were compared were the temperature at 4:00, 14:00 and 22:00, the mean temperature, and the maximum and minimum temperatures. The monthly maximum value of the temperature difference and the monthly mean of the difference in the maximum temperature between the two locations were then calculated.

The results indicated that the concrete roof was warmer than the green area, especially during summer and winter, similar to the UHI case. However, the temperature difference was larger during the day than at night, which is opposite to the UHI case. This is thought to be because the concrete roof is well ventilated, being on top of a five-story building that rises approximately 25 m above the ground. In addition, the weather was investigated for days when there were large temperature differences between the two locations, and for days when the temperature difference was larger at night than during the day. It was found that on such days, inclement weather events such as thunderstorms and typhoons had occurred.

Thus, it can be concluded that an effect similar to the UHI effect may occur even within the limited confines of a university campus, if the influence of ventilation is excluded. Further investigations should be carried out to determine the importance of factors such as the height at which the measurements are performed.

Mitigation of community heat island intensity (CHI) is important for mitigation of urban heat island and improving urban environment. The present paper is aimed to conduct field experiments on several communities in hot-humid area of China and study the impacts of buildings layouts and trees on CHI. Several communities in Guangzhou were studied in summer of 2013. Air temperatures were measured at 1.5 m height, on many positions and for a whole day for each community and the change of community air temperature with time was obtained. The CHI was calculated by subtracting air temperature of suburb weather station or nearby urban station. It was found that the method of subtracting air temperature of suburb weather station overestimated significantly CHI and the method of subtracting air temperature of nearby urban station was more appropriate for CHI calculation. The impacts of several parameters, i.e. sky view factor, leaf area index, shadow area ratio, and ground surface character on CHI were analyzed, and accordingly the guideline for community layout plan was proposed.

In this study, the fixed point observation of surface air temperature was carried out during the summer in Kumagaya, Japan. Furthermore, diurnal variation patterns of the heat island intensity were extracted from observed data by a multivariate analysis.

As a result of the observation, the air temperature of the urban area was higher than the surroundings throughout the day (about 1℃), and the difference was the greatest in the night (about 1.5℃). In the suburbs, remarkable low temperature was observed in the paddy field area during the daytime and in the forest area during the nighttime.

In addition, the heat island intensity that subtracted temperature of the suburbs from the urban area was computed to evaluate the urban heat island quantitatively. As a result, the daily maximum of heat island intensity appeared in the daytime (about 4℃) when suburban stations were selected in the paddy field, but in the nighttime (about 3℃)in the case of the forest area. This suggests that the selection of suburb stations can have a strong influence on the interpretation of heat island intensity. In addition, the component referred to the inhomogeneity of diurnal temperature variation in the suburbs was obtained by principal component analysis. Therefore, it became clear that the diurnal variation of the heat island intensity in Kumagaya City greatly depends on the land cover status.

The factors that determine the extent to which an urban climate differs from the climate of the surrounding area are formed by the built environment and the activities that take place there. The Greek cities, regardless of their difference in size, have similar town-planning organization. In addition, the buildings in them have similar and specific architectural and constructional features and operating patterns. For instance, in their common feature they are included the dense construction, the lack of green areas, the relative equal-height structure, the high roughness of the building surfaces, the increased albedo, the burning products and photochemical reactions as the main component of their atmospheric pollution. These facts produce similarities in the basic qualitative characteristics of the urban climate in them. This study identifies and describes the basic characteristics of the Urban Heat Island phenomenon in Greek cities. Based on measurements from relevant studies, it explores the relation between the intensity of the phenomenon and the characteristics of the built environment in which it is measured. A number of conclusions emerging from the study can be utilized in the planning and implementation of measures to improve the overall living conditions in Greek cities.

Urban heat island effect in Delhi has been assessed using Weather Research and Forecasting (WRF v3.5) model based on simulated air temperatures and surface skin temperatures. The estimated heat island intensities for different land use/land cover (LULC) have been compared with in-situ observations of a field campaign which employed numerous micro-meteorological stations spread throughout the extent of the study region. Urban heat island intensities

based on land surface temperature have been compared with those derived from MODIS Terra 8-day average land surface temperature (LST). The model simulates maximum hourly urban heat island intensity of 8.9 °C compared to observed 10.7°C. Statistical parameters have been used to evaluate model performance. The model performs reasonably well for UHI estimation from viewpoint of statistical benchmarks (RMSE=1.9°C, Index of Agreement=0.77 for urban areas). Although, corresponding peaks are not captured in observed and simulated UHIs, top UHI zones are captured in model for both air and land surface temperatures. WRF is able to reproduce trend of UHI for urban areas but shows poor performance for certain non-urban areas where in-situ LULC is not represented in the model. However, top UHI zones are captured in model for both air and land surface temperatures.

The relevance of selecting a reference point for UHI estimation is examined in the context of rapidly growing cities where rural areas are fast getting turned into built areas. In this regard, model sensitivity to selection of reference point (green area within the city vis-a-vis external rural area) for estimation of UHI has been examined.UHI estimated by model with respect to reference rural site (Torni Village) corroborates well with the same using observed in-situ data while UHI estimated with respect to a green area (Sanjay Van) within the city does not compare well with that using in-situ data. This shows that WRF model has potential to be applied for UHI estimations with some improvements. The likely cause of this is lack of higher resolution LULC data within the city. However, the potential of using the reference site within the city still exists which can be explored further.

Spatial variability in simulated UHI compares fairly during nighttime with observed distribution. Daytime comparison is not good indicating greater role of anthropogenic factors which are not being included in model at present. However, there is a scope of improvement in model results with incorporation of high resolution dataset of the urban fabric of the city as well as anthropogenic emissions.

Modern prospects of intensification of socioeconomic activity and building new settlements in Arctic zone requires better understanding of the urban-caused microclimatic features and their behavior in the conditions of arctic and sub-arctic climate. While in moderate and tropical climate zones urban heat island (UHI) seems to have negative effect on people health (Buechley et. al., 1972) and energy consumption rates (Sailor, 2002), for arctic cities positive effect could be expected during long winter, when UHI could mitigate severe climatic conditions within urban areas and provide the economy of fuel for house heating. However, until nowadays knowledge about UHI of polar cities was very poor, the only existing researches considered small towns in Alaska (Magee et. al., 1999), while UHI of the biggest arctic cities, which are located in Russia, remained undiscovered.

In this study, we consider the results of research of the UHI of Norilsk (second biggest city over the Polar Circle with aprox. 180 000 inh.) and Apatity (fifth biggest polar city with aprox. 60 000 inh.), which were obtained during the expedition of Russian Geographic Society during the 2013-2014 winter season. Expedition to Norilsk took place at December, in the middle of polar night, and expedition to Apatity was organizes in the end of January. Field measurements in these cities included installation of several automatic weather stations (AWS) and the net of small temperature sensors (iButton) in the city and surrounding landscape and car-based temperature sounding of the city with AWS. Additional information, such as measurements of MTP-5 temperature profiler and surface temperature data, provided by MODIS remote sensing system, were used for verification and confirmation of the results, obtained by experimental measurements.

Analysis of experimental data and additional information showed existence of significant UHI with the difference between city center and surrounding landscape up to 6-7 ⁰C with mean value about 2⁰C. Such values are rather high as for Apatity, which is, actually, relatively small town, as for Norilsk, where measurements were made in the middle of polar night, when anthropogenic heat flux is the only factor forming the UHI. Measurements in Norilsk shown interesting spatial feature of temperature distribution: the warmest place was discovered not in the center of the city, but at the edge of the city near unfreezing lake, which is used for cooling industrial plants and releases anthropogenic heat to atmosphere. Economic effect of the UHI, connected with economy of fuel for house heating, was roughly estimated by hundreds of thousands - first millions EUR per year, for this assessment a simple statistical model of centralized urban heating system was used.

References:

1. Magee N., Curtis J., Wendler G., The Urban Heat Island Effect at Fairbanks, Alaska// Theor. Appl. Climatol. 1999. V. 64, pp 39-47;

2. Buechley RW, Van Bruggen J and Truppi LE Heat island equals death island?// Environmental Resourses. 1972. V. 5. PP. 85-92.

3. Sailor, D. J. Urban Heat Islands, Opportunities and Challenges for Mitigation and Adap-tation (2002). Sample Electric Load Data for New Orleans, LA (NOPSI, 1995)// North American Urban Heat Island Summit. Toronto, Canada. 1-4 May 2002. Data courtesy Entergy Corporation;

This study was supported by Russian Geographic Society, research projects No. 69/2013-H7 and 27/2013-НЗ.

This paper analyzed the change of heat environment in Seoul metropolitan region of Korea by urbanization during 10 years (2000-2009). For simulations, we used the Weather Research and Forecasting (WRF) coupled with an Urban Canopy Model (UCM). The simulations were composed of three sets: (1) the meteorological condition of Oct. 2000 with land-use data from the Korea Ministry of Environment (KME) in 2000, (2) the meteorological condition of Oct. 2009 with those from KME in 2000 and (3) the meteorological condition of Oct. 2009 with those from KME in 2009.

The urban land-use area in the modeling domain increased by 2.18 percentages between 2000 and 2009. For the three urban land-use categories, the low/high intensity residential areas decreased by 1.26 percentage and commercial/industrial/transportation areas increased by 3.44 percentage over the 10 years.

The simulations showed that there was an increase in near-surface temperature over all of the analyzed stations due to climate changes during 10 years. At the stations where the urban land-use type is changed, the near-surface temperature in night increased highly by combined effect of climate and land-use changes. In addition to, the change of urban land-use contributed to not only the intensification of urban heat island but also the increase of sensible heat flux and decrease of latent heat flux during 10 years.

The urban thermal environment varies not only from its rural surroundings, but also within the urban area due to intra-urban differences in land-use and surface characteristics. Thus, this study aimed to analyze the influence of geourbanos factors in setting the spatial variability of air temperature, at night, at the time of Urban Heat Island (UHI) intensity of 3.5ºC. Therefore, we used multiple linear regression and geostatistical analyzes. The results showed that human factors were prevalent at the time of occurrence of UHI, the proposed model to estimate the air temperature values for the whole city got an r2 of 0.99. It was noted correlation of NDVI and UI (Urbanization Index) of -0.93 and 0.92 respectively. Therefore, the proposed model can be applied if it is adapted to spatialize the air temperature in urban areas.