• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.6
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• pp.44-53
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• 1999

The statistical characteristics of the factors related to the daily rainfall prediction model are analyzed . Records of daily precipitation, mean air temperature, relative humidity , dew-point temperature and air pressure from 1973∼1998 at 8 meteorological sttions in south-western part of Korea were used. 1. Serial correlatino of daily precipitaiton was significant with the lag less than 1 day. But , that of other variables were large enough until 10 day lag. 2. Crosscorrelation of air temperature, relative humidity , dew-point temperature showed similar distribution wiht the basin contrours and the others were different. 3. There were significant correlation between the meteorological variables and precipitation preceded more than 2 days. 4. Daily preciption of each station were treated as a truncated continuous random variable and the annual periodic components, mean and standard deviation were estimated for each day. 5. All of the results could be considered to select the input variables of regression model or neural network model for the prediction of daily precipitation and to construct the stochastic model of daily precipitation.

• Journal of Biosystems Engineering
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• v.24 no.5
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• pp.445-452
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• 1999

This study was conducted to develop a searching algorithm for optimal daily temperature setpoint greenhouse. An algorithm using crop growth and energy models was developed to determine optimum crop growth environment. The results of this study were as follows: 1. Mathematical models for crop growth and energy consumption were derived to define optimal daily temperature setpoint. 2. Optimum temperature setpoint, which could maximize performance criterion, was determined by using Pontryagin maximum principle. 3. Dynamic control of daily temperature using the developed algorithm showed higher performance criterion than static control with fixed temperature setpoint. Performance criteria for dynamic control models were with simulated periodic weather data and with real weather data, increased by 48% and 60%, respectively.

• Solar Energy
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• v.12 no.2
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• pp.1-8
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• 1992

Identifying characteristics of heating and cooling systems requires estimation of thermal load of specific time interval, especially in cases that its system is operated intermittently, by using thermal storage, of in a partial load condition. Estimating the thermal load, however, needs to forecast hourly weather data variation. Hence, this paper attempts to examine characteristics of hourly ourdoor temperature variation as a preliminary research for the mathematical modeling of the hourly weather variation. Speculating characteristics of daily minimum and maximum temperature occurances, hourly outdoor temperature variation, and daily temperature differences in the increasing range ($07h{\sim}15h$) and decreasing range($15h{\sim}07h$), we were able to analyze changing patterns of daily temperature differences in each range in terms of daily solar amount, cloud ratio, and other weather data. Results from the multiple regression analysis enables us to conclude that daily differences in the increasing range are strongly affected last night temperature itself while the other range's differences are influenced by many weather data, which are solar amount, the variation of cloud, and the maximum temperature of the previous day.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.185-191
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• 2009

Few studies have attempted to analyze variations of daily maximum temperature in the summer whereas many studies have analyzed warming trends in other seasons with respect to greenhouse gases or urban heat islands. We analyzed daily maximum temperature data for the summer season (June to August) at 18 locations in South Korea from 1983 to 2007. Compared to the climatic normal (from 1971 to 2000), an average increase of $0.1^{\circ}C$ was found for the summer daily maximum temperature along with an increase of $0.61MJ\;m^{-2}$ in daily solar radiation. Approximately 65% of the annual variations of the summer daily maximum temperature could be explained by the solar radiance alone. Higher atmospheric transmittance due to lower aerosol concentration (especially of sulfur dioxide) is believed to have caused the recent increase in solar irradiance. Daily maximum temperature of the summer is expected to keep rising if the clean air activities are maintained in the future.

• Environmental and Resource Economics Review
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• v.29 no.4
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• pp.419-442
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• 2020

The majority of the natural gas demand in South Korea is mainly determined by the heating demand. Accordingly, there is a distinct seasonality in which the gas demand increases in winter and decreases in summer. Moreover, the degree of sensitiveness to temperature on gas demand has changed over time. This study firstly introduces changing temperature response function (TRF) to capture effects of changing seasonality. The temperature effect (TE), estimated by integrating temperature response function with daily temperature density, represents for the amount of gas demand change due to variation of temperature distribution. Also, this study presents an innovative way in forecasting daily temperature density by employing functional principal component analysis based on daily max/min temperature forecasts for the five big cities in Korea. The forecast errors of the temperature density and gas demand are decreased by 50% and 80% respectively if we use the proposed forecasted density rather than the average daily temperature density.

• Journal of Environmental Science International
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• v.25 no.2
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• pp.295-310
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• 2016

In this study, changes in daily temperature range were investigated using daily maximum and minimum temperatures of Busan and Daegu for last 81 years (1934-2014), and also characteristics of daily temperature range and seasonal fluctuations by urbanization were examined. First, elapsing changes showed a lower decreasing trend in Busan ($0.32^{\circ}C$) than Daegu ($1.28^{\circ}C$) for last 81 years. Daily temperature range showed the highest rise in winter in both Busan and Daegu. Second, daily temperature range due to urbanization showed that Busan had a pronounced decreasing trend before urbanization meanwhile Daegu showed the same trend after urbanization. On seasonal changes, the results of Busan showed a decreasing trend in summer before urbanization, and in autumn after urbanization. For Daegu, the results showed a decreasing trend in spring before urbanization, and in winter after urbanization. Seasonal fluctuations of Busan showed little difference in the pre and post-urbanization, except in winter and summer. There was large difference in daily temperature range in winter after urbanization, and in summer before the urbanization. The results in Daegu showed that there was decreasing trend of daily temperature range in all seasons after urbanization.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.1
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• pp.25-31
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• 2008

Information on daily maximum air temperature is important in predicting the status of plants and insects, but the uneven and sparse distribution of weather stations prohibits timely access to the data in regions with complex topography. Since cumulative solar irradiance plays a critical role in determining daily maximum temperature on any sloping surfaces, derivation of a quantitative relationship between cumulative solar irradiance and the resultant daily maximum temperature is a prerequisite to development of such estimation models. Air temperatures at 8 sideslope locations with similar elevation and slope angle but aspect, circumventing a cone-shaped, grass-covered parasitic volcano (c.a., 570 m diameter for the bottom circle and 90m bottom-to-top height), were measured from June to December in 2007. Daily maximum temperatures from each location were compared with the average of 8 locations (assumed to be the temperature measured at a "horizontal reference" position). The temperature deviation at all locations increased with the day of year (or sun elevation) from summer solstice to winter solstice. Averaged over the entire period, the south facing location was warmer by $1^{\circ}C$ in daily maximum temperature than "horizontal reference" and the north facing location was cooler by $0.8^{\circ}C$ than the reference, resulting in the year round average south-north temperature difference of $1.8^{\circ}C$. In November, both south and north facing slopes showed the greatest deviation of $+2.0^{\circ}C$ and $-1.3^{\circ}C$, respectively in daily maximum temperature at monthly scale. On a daily scale, the greatest deviation was +3.8 and $2.7^{\circ}C$ at the south and north slope, respectively. The cumulative solar irradiance (on the slope for 4 hours from 11:00 to 15:00 TST) explained >60% of the variance in daily maximum temperature deviations among 8 locations, suggesting a feasibility of developing an estimation model for daily maximum temperature over complex topography at landscape scales.

• Korean Journal of Human Ecology
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• v.20 no.1
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• pp.195-203
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• 2011

The purpose of this study was to define the effects of the finger temperature response according to the daily life of college student. For this study, 31 healthy female college students were taken as a subject group. To define the effects of the finger temperature response, housing style, subjective thermal sensations during daily life in the house and domestic working time were surveyed. The finger temperature response items were measured. The results were as follows. Strong, normal and weak group members were divided according to their cold resistance index(RI) 3, 8, 20 people, repectively. Subjective thermal sensations during daily life in the house affects the cold resistance index(p<.01). The cold resistance index(RI) got higher as domestic working time was increased(p<.05, F-value=3.927). The percentage wearing protective gloves during domestic work in the weak group was higher than the normal or strong groups. Subjective sensations during daily life and domestic working time effected the local cold tolerance, living in a comfortable environment continuously can weaken one's cold tolerance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.539-547
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• 1997

This study was carried out to identify how soybean seed protein concentration is influenced by climatic factors. Twelve lines selected for seed protein concentration were studied in 13 environments of North Carolina. Sensitivity of seed protein concentration, total seed protein, and seed yield to climatic variables was investigated using a linear regression model. Best response models were determined using two stepwise selection methods, Maximum R-square and Stepwise Selection. There were wide climatic effects in seed protein concentration, total protein and seed yield. The highest protein concentration environment was characterized by the most high temperature days(HTD) and the smallest variance of average daily temperature range (VADTRg), while the lowest protein concentration environment was distinguished by the fewest HTD and the largest VADTRg. For protein concentration, all lines responded positively to average maximum daily temperature(MxDT), HTD, and average daily temperature range(ADTRg) and negatively to ADRa, while they responded positively or negatively to average daily temperature(ADT), variance of average minimum daily temperature (VMnDT), and VADTRg, indicating that genotypes may greatly differ in degrees of sensitivity to each climatic variable. Eleven lines seemed to have best response models with 2 or 3 variables. Exceptionally, NC106 did not show a significant sensitivity to any climatic variable and thus did not have a best response model. This indicates that it may be considered phenotypically more stable. For total seed protein and seed yield, all the lines responded negatively to both ADTRg and VADRa, suggesting that synthesis of seed components may increase with less daily temperature range and less variation in daily rainfall.

• 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.