• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.119-127
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• 2014

A very high resolution weather analysis system (VHRAS) of 50 m horizontal resolution is established based on LAPS. VHRAS utilizes the 3 hourly forecast data of the Unified Model (UM) of the Korea Meteorological Administration (KMA) with the horizontal resolution of 12 km as initial guess fields. The analysis system ingests the automatic weather station (AWS) data as input observations. The analysis system operates every hour for Seoul, Korea region in real time basis. It takes less than 10 minutes for one analysis cycle. The size of grid of the analysis domain is $800{\times}660$, respectively. The analysis results from December 2010 to February 2011 showed that the mean biases of temperature, maximum and minimum temperature were -0.07, 1.6, $0.2^{\circ}C$, respectively. The temperature in the central part of the city revealed relatively higher value than that of the surrounding mountainous areas, which showed a heat island feature. The heat island appears in zonal direction since the central city region is developed along a large river. Along the heat island, the eastern region was warmer than the western region. The warmer temperature in the western part of the heat island was caused by anthropogenic heat change in conjunction with the change of land use. This system will provide more reliable weather data and information in Seoul.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.2
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• pp.55-63
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• 2008

We investigated characteristics of temperature variation in urban and suburban areas(e.g., paddy field, upland, park, residential area) and urban heat island(UHI) during winter(December 2005 to February 2006). The daily maximum air temperature was not significantly different between suburban and urban areas, whereas the daily minimum air temperatures were significantly lower in the suburban areas than that in the residential area. The wind speed in the urban park(0.3 m/s) was much lower than that in the paddy fields(2.3 m/s), likely due to an urban canopy layer formed by high buildings. The UHI intensity was represented by differences in daily minimum temperatures between urban residential and paddy field areas. The UHI intensity($4.1^{\circ}C$) in winter was larger than that($2.6^{\circ}C$) in summer. This may be because a stable boundary layer develops in the winter, and thereby this inhibits diffusion of heat from surface.

• Journal of the Korean Regional Science Association
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• v.35 no.4
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• pp.61-73
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• 2019

Urban development and densification have led to the Urban Heat Island Effect, in which the temperature of urban space is higher than the surrounding areas, and the intensity is increasing with climate change. In addition, when the city's air temperature rises in summer, low-income, elderly population, and socially vulnerable people who have health problems lack the ability to cope with the elevated heat environment. Therefore, this study aimed to identify the urban heat island area of Seoul through Hotspot analysis, which is a spatial statistics technique, and explored physical environments, demographic and socioeconomic characteristics of urban heat island effect areas using logistic regression models. This study performed urban heat island hotspot analysis using the average air temperatures of the 423 administrative dongs in Seoul. Analysis results identified that the urban heat islands were concentrated in Jung-gu, Jongno-gu, Yongsan-gu, and Yeongdeungpo-gu. Logistic regression analysis results indicated that urban heat island areas of Seoul were affected by residential floor area ratio, commercial facility floor area ratio, overall floor area ratio, impervious surface ratio, and normalized difference vegetation index(NDVI). In addition, as a result of analyzing the vulnerable area of thermal environment considering the demographic and socioeconomic characteristics of the heat island area, urban heat island areas of Seoul were significantly associated with the proportion of low-income elderly living alone. The result of this study provided useful insights for urban thermal environmental design and policy development that could improve the thermal environment for the socially disadvantaged urban population.

• Journal of Environmental Impact Assessment
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• v.32 no.3
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• pp.176-186
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• 2023

Urban Heat Island (UHI) is caused by an energy imbalance in urban areas, where building design and land cover contribute to its amplification. To mitigate UHI, increasing green space is one of the well known and the most effective approach. This study aims aimed to identify specific components of green spaces that lower temperatures and demonstrate the cooling effects based on their size and composition. Forests within green spaces have had a greater impact on temperature reduction due to shading and blocking solar radiation. Although lakes also contributed to temperature reduction, the effect to cooling intensity was not significant. The cooling distance does not depended on green space size or composition. The study emphasizes that initial temperature has a strongerinfluence on cooling intensity than green space size, highlighting the importance of vegetation type within green spaces to achieve a cooling effect. These findings provide valuable insights for urban planning and the design of green spaces to mitigate the effects of the urban heat island.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.2
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• pp.119-130
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• 2012

Heat island phenomena in Chuncheon (Korea) were investigated using air temperature measured by automatic weather stations and temperature dataloggers located at rural and urban sites. Numerical simulation of the phenomena was performed using Weather Research and Forecasting Urban Canopy Model (WRF-UCM) and results were compared with the observation. The model was initialized with NCEP/FNL data. The horizontal resolution of the fine domain is 0.33 km. The results of observational analyses show that the intensity of heat island was significantly higher during the nighttime than during the daytime. The highest measured temperature difference between rural and urban site is $3.49^{\circ}C$ and average temperature difference varies between 1.4 and $1.9^{\circ}C$. Good agreement was found between the simulated and observed temperatures. However, significantly overestimated wind speed was found at the urban sites. The linear regression analysis between observed and simulated temperature shows high correlation coefficient 0.96 for urban and 0.94 for rural sites while for wind speed, a very low correlation coefficient was found, 0.30 and 0.55 respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.4
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• pp.303-309
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• 1993

An observational study of urban heat island was carried out using field data obatined during 6 days in May and August 1992 in Chunchon(population size 180.000). Air temperature was measured at 64 points along two sampling ruoutes by themisters attached to cars. Both routes cover urban and rural area and across the cneter of urban area. Continuous observation of air sonde was perfomed to clarify heights of nocturnal boundary layer(NBL) at the center of urban area. Surface meteorological observations were performed at both urban and rural sites. This study showed that heat island phenomena was obviously observed at the urbanized area during the night time with low wind speed. The average NBL heights exteded to about 10 meters, but varied with meteorological conditions. After sunset, the air temperature decreased with time at both sites and cooling rate at the urban site was greater than the rural site. The maximum heat island intensity was 7.5$^{\circ}$C at 21 LST, May 4. Usingthe two meteorological data sets obtained from urban and rural sites, the air pollutant concentration was calculated by Gaussian plume model which can obtain not only horizontal distribution of concentration but also vertical distribution. The result indicated that the concentration resulted from urban meteorological data set was lower than that from rural meteorological data set. It was also calculated that the air pollutant extended to higher level in urban meteorological data set than that in rural meteorological data set.

• Journal of the Korean earth science society
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• v.42 no.2
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• pp.135-148
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• 2021

The purpose of this study was to evaluate the urban heat island (UHI) intensity and the corresponding surface temperature forecast obtained using the local data assimilation and prediction system (LDAPS) of the Korea Meteorological Administration (KMA) against the AWS observation. The observed UHI intensity in Seoul increases during spring and winter, while it decreases during summer. It is found that the diurnal variability of the UHI intensity peaks at dawn but reaches a minimum in the afternoon. The LDAPS overestimates the UHI intensity in summer but underestimates it in winter. In particular, the model tends to overestimate the UHI intensity during the daytime in summer but underestimate it during the nighttime in winter. Moreover, surface temperature errors decrease in summer but increase in winter. The underestimation of the winter UHI intensity appears to be associated with weak forecasting of urban temperature in winter. However, the overestimated summer UHI intensity results from the underestimation of the suburban temperature forecast in summer. In order to improve the predictability of the UHI intensity, an urban canopy model (MORUSES) that considers urban effects was combined with LDAPS and used for simulation for the summer of 2017. The surface temperature forecast for the city was improved significantly by adopting MORUSES, and there were remarkable improvements in urban surface temperature morning forecasts. The urban canopy model produced an improvement effect that weakened the intensity of the UHI, which showed an overestimation during summer.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.253-264
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• 2022

The effect of decreased human activity on the urban heat island intensity (UHII) was analyzed using the observed temperature data of six sites (including one reference area) in Daejeon Metropolitan City from February to May of 2019 to 2021. Depending on the observation site, UHII decreased by approximately 20% in 2020 and 2021 compared to 2019 before COVID-19. The decrease in human activity increased UHII at night and decreased it during the daytime. Consequently, UHII diurnal amplitude increased by approximately 20% in 2020 and 2021 compared to 2019, irrespective of location. The decrease in UHII did not appear to be significantly correlated with natural factors such as wind speed and social distancing steps. In contrast, UHII was correlated with social distancing and significantly reduced air pollutants after COVID-19, with the most significant correlation observed for NO₂.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.1-12
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• 2018

Heat waves during summer cause a qualitative degradation in urban environments and increases the number of patients who suffer from heat-related illnesses, and the urbanization deepens these problems. It is a prerequisite to analyze the current status accurately in order to assess the urban heat island phenomenon. Thus, this study aims to collect weather measurements information at the occurrence of a severe heat wave in Seoul, thereby allowing analysis of information, which will also consider the land use type. The weather measurement information used in the analysis had an advantage, as the gap between measured locations is considerably shorter than before due to the miniaturization of the automatic weather systems (AWS), which are connected through the communication network. Based on the above collected information, a temporal change in the data due to land use type was analyzed. As a result, the difference in temperature change in response to the land use type could be compared, as could the occurrence pattern of the tropical night phenomenon, and the effect on temperature reduction in green belt areas could be identified through the comparison of the intensity of heat island by time and land use. The methods and results derived in this study through the comparative analysis in terms of time and land use, weather information measurements, and mapping can be utilized as foundational data that can be referred to in urban planning to reduce the heat island phenomenon in the future.

• Journal of Environmental Science International
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• v.18 no.2
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• pp.169-176
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• 2009

The present study observed temperature in order to identify factors affecting temperature by zoning and to measure the intensity of their impact on temperature. The empirical results of analyzing observed data are as follows. In order to make up for multicollinearity, a problem in multiple regression analysis, and to give more specific explanations, this study conducted factor analysis and obtained desirable data with adequacy and statistical significance. In the correlation matrix, factors decreasing temperature were planted areas, water surfaces and grasslands, and those increasing temperature were bare grounds, paved areas, and building area. According to land cover patterns, commercial areas had the highest temperature lowering effect. Through the rotated component matrix, we found that factors are grouped into those decreasing temperature, those increasing temperature, and those with low significance in increasing or decreasing temperature. In order to solve the problem of multicollinearity in multiple regression analysis, we performed factor analysis between the land use patterns and temperature and confirmed the usability of factor analysis as a new analysis method in urban heat island.