• Journal of Environmental Science International
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• v.23 no.9
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• pp.1619-1626
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• 2014

We analyzed diurnal variations in the surface air temperature using the high density urban climate observation network in Daegu metropolitan city, the representative basin-type city in Korea, in summer, 2013. We used a total of 28 air temperature observation points data(16 thermometers and 12 AWSs). From the distribution of monthly average air temperature, air temperature at the center of Daegu was higher than the suburbs. Also, the days of daily minimum air temperature more than or equal to $25^{\circ}C$ and daily maximum air temperature more than or equal to $35^{\circ}C$ at the schools near the center of Daegu was more than those at other schools. This tendency appeared more clearly on the days of daily minimum air temperature more than or equal to $25^{\circ}C$. Also, the air temperature near the center of the city was higher than that of the suburbs in the early morning. Thus it was indicated that the air temperature was hard to decrease as the bottom of the basin. From these results, the influence of urbanization to the formation of the daily minimum temperature in Daegu was indicated.

• Journal of Environmental Science International
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• v.22 no.6
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• pp.667-677
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• 2013

This study aims to examine the actual status of the urban heat island in Daegu by analyzing the data of 17 automatic weather stations installed in the Daegu area. And the results can be summarized as follows: First, regarding the temperature distribution in Daegu by summer time zones, for the 31 days(August 1st till 31st), 18 days showed daily maximum temperature over $30^{\circ}C$, and 11 days indicated daily minimum temperature over $25^{\circ}C$. The day that showed the highest daily maximum temperature was August 5th, which indicated $36^{\circ}C$. Second, about the spatial distribution of time ratio exceeding $30^{\circ}C$ and $25^{\circ}C$, the area with the highest time ratio exceeding $30^{\circ}C$ is mostly the downtown(central area), eastern area, and northern area. Meanwhile, regarding the time ratio exceeding $25^{\circ}C$, the downtown area centering around the central area were high as over 70%, and the outskirts were low as under 65%. Third, considering the temporal distribution of daily maximum temperature and daily minimum temperature, daily maximum temperature was shown around 14:00 to 15:00 while the daily minimum temperature was indicated around 17:00 to 18:00. Daily maximum and minimum temperature were appeared at northeast and downtown, respectively. Fourth, regarding the spatial distribution of tropical days and tropical night days, tropical days showed 77% and tropical night days indicated 42% before and after the 24th and also the 13th each. Tropical days were occurred up to 24 days at northeastern area. And the southwestern area of Daegu showed under 22 days. The downtown showed the 14 days of the tropical night. However, the outskirts indicated relatively few days as under 10 days. Fifth, about the spatial distribution of the average daily temperature range (the difference between the highest temperature and lowest temperature), the central area, the central part of the city, showed the smallest as $7.2^{\circ}C$, and as it was closer to the northern area, it became larger, so in the eastern and northern area, it was over $8.8^{\circ}C$ or so.

• Journal of Climate Change Research
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• v.6 no.2
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• pp.87-94
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• 2015

To compare changes in winter temperature over South Korea, 30-year average climate data and climate data of recent 10 years (2014~2014) such as mean temperature, daily maximum temperature and daily minimum temperature were analyzed. Also, we set analysis extreme cold waves frequency related to winter such as freezing days, snow days, days with temperature of below -5, and days with temperature of below -10. This process enabled the comparative analysis of winter temperature changes and extreme cold waves frequency related to winter. This study estimated that winter temperature has gradually increased throughout the last five decades, however, the frequency of extreme weather, such as cold waves has also increased.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.155-160
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• 2012

This study was conducted to develop a practical method for estimating the extremes of minimum air temperature with given return-period based on the frequency distribution of daily minimum air temperature in January. Daily temperature data were collected from 61 meteorological observatories country-wide from 1961 to 2010. Most of daily minimum temperature in January could be represented by a normal-distribution, so it is possible to predict stochastically the lowest temperature by the mean and standard deviation. We developed a quadratic function to estimate standard deviation in terms of daily minimum temperature in January. Also, we introduced a coefficient which can be used to predict an extreme of minimum temperature with mean and standard deviation, and is dependent on return-periods. Using this method, we were able to reproduce the past 30-year extremes with an error of 1.1 on average and 5.3 in the worst case.

• Journal of the Korean association of regional geographers
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• v.17 no.2
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• pp.167-180
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• 2011

This paper investigates the changes of diurnal temperature range (DTR) by season and region in South Korea using daily maximum temperature and daily minimum temperature from 1954 to 2009. It also attempts to find what causes these changes. The daily minimum temperature distinctively increased during the latter half of the research period (1988~2009) than the first half of the year (1954~1987) leading decreases in DTR, while the rise in daily maximum temperature was not distinct during the research period. The DTR shows slightly increasing trend in spring. but decreasing trend in fall. The DTR is decreasing in urban region while it is increasing in rural area. The degree of the DTR decrease is bigger in large urban region than in medium-small urban region. The DTR in urban region is affected by the amount of clouds in spring and tile duration of sunshine in fall. The DTR in rural area is affected by the amount of clouds in spring and the number of days with precipitation in fall.

• Atmosphere
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• v.24 no.1
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• pp.29-38
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• 2014

A characteristic of snowfall and minimum temperature variability in South Korea with respect to the variability of Arctic Oscillation (AO) was investigated. The climatic snowfall regions of South Korea based on daily new fresh snowfall data of 59 Korea Meteorological Administration (KMA) stations data corresponding to the sign of AO index during December to February 1979~2011 were classified. Especially, the differences between snowfalls of eastern regions and that of western regions in South Korea were seen by each mean 1000hPa geopotential height fields, which is one of physical structure, for the selected cases over the East Asia including the Korean Peninsula. Daily minimum temperature variability of 59 KMA station data and daily AO index during the same period were investigated using Cyclo-stationary empirical orthogonal function (CSEOF) analysis. The first CSEOF of wintertime daily AO index and that of minimum temperature of 59 KMA stations explain 33% and 66% of total variability, respectively. Correlation between principal component time series corresponding to the first CSEOF of AO index and that of temperature at the period of 1990s is over about -0.7 when that of AO index leads about 40 days.

• Atmosphere
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• v.17 no.2
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• pp.185-193
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• 2007

This study investigates urbanization effect in warming trend of surface air temperature over Korea. The data used in this study consist of the daily minimum and maximum temperatures during the period of 32 years(1968-1999) from 16 stations of KMA. To calculate magnitude and trend of urbanization effect, stations were classified into urban and rural stations using population statistics. Urban stations were defined as those with population densities greater than 1000 persons per kilometer squared in 1995. The others were defined as rural stations. The urban stations were also subdivided into two groups according to their population totals. For estimates of urban effect magnitude, temperature change was calculated by comparing 16-year mean values between 1968-83 and 1984-99. Then, the difference between each urban station and every rural station was calculated. During the analysis period of 32 years, maximum temperature increase is $1.22^{\circ}C$. In the total temperature increase, urban effect is estimated by 28.7%. For minimum temperature, it becomes larger by about 10% than that in maximum temperature. Therefore, urban effect in an increasing trend of minimum temperature is 38.9% in the change of $1.13^{\circ}C$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.1
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• pp.43-47
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• 2003

Air temperature was continuously measured in hilly pear orchards at 4 sites with elevations of 10, 49, 104 and 253 m above sea level. The mean air temperature, averaged over the 10-month period from August 2001 to June 2002, decreased as the site elevation increased by 0.2$^{\circ}C$ per 100 m. This weak lapse condition was amplified during daytime by sun-slope geometry. But on most days an inversion condition began by sunset and persisted until the next sunrise. During the observation period, daily minimum temperature at the valley bottom was lower than that of the hilltop on 67% of the days, and the average temperature difference was 1.4$^{\circ}C$. Inversion of daily minimum temperature under clear sky conditions was stronger in spring and autumn than in winter with a maximum of 6$^{\circ}C$. Lapse condition was predominant in daily minimum temperature on rainy days, and the lapse rate was strongest in winter.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.9-20
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• 1999

The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

• Journal of the Korean Solar Energy Society
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• v.29 no.5
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• pp.81-87
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• 2009

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design.. Building designers often now predict the performance of buildings simulation programmes that require hourly weather data. However, not all weather stations provide hourly data. Climate prediction models such as HadCM3 also provide the daily average dry bulb temperature as well as the maximum and minimum. Hourly temperature values are available for building thermal simulations that accounts for future changes to climate. In order to make full use of these predicted future weather data in building simulation programmes, algorithms for downscaling daily values to hourly values are required. This paper describes a more accurate method for generating hourly temperature values in the South Korea that uses all three temperature parameters from climate model. All methods were evaluated for accuracy and stability in terms of coefficient of determination and cumulative error. They were compared with hourly data collected in Seoul and Ulsan, South Korea.