• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.56-61
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• 2021

This study was conducted to determine the possibility of estimating the daily mean temperature for a specific location based on the climatic data collected from the nearby Automated Synoptic Observing System (ASOS) and Automated Weather System(AWS) to improve the accuracy of the climate data in forage yield prediction model. To perform this study, the annual mean temperature and monthly mean temperature were checked for normality, correlation with location information (Longitude, Latitude, and Altitude) and multiple regression analysis, respectively. The altitude was found to have a continuous effect on the annual mean temperature and the monthly mean temperature, while the latitude was found to have an effect on the monthly mean temperature excluding June. Longitude affected monthly mean temperature in June, July, August, September, October, and November. Based on the above results and years of experience with climate-related research, the daily mean temperature estimation was determined to be possible using longitude, latitude, and altitude. In this study, it is possible to estimate the daily mean temperature using climate data from all over the country, but in order to improve the accuracy of daily mean temperature, climatic data needs to applied to each city and province.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.6
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• pp.832-841
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• 2007

Rectal Temperature;Thermoregulation;Sows;Breed;The effects of season (hot vs. warm) in a tropical humid climate, parity (primiparous vs. multiparous) and breed (Creole: CR, Large White: LW) on rectal temperature (RT) were studied for a total of 222 lactations obtained in 85 sows (43 CR and 42 LW; 56 primiparous and 166 multiparous) over a 28-d lactation, between June 2002 and April 2005. Mean daily ambient temperature was higher during the hot season than during the warm season (26.0 vs. $24.1^{\circ}C$) and relative humidity was high and similar in both seasons (89% on average). At farrowing, BW was lower (172 vs. 233 kg) and backfat thickness was higher (37 vs. 21 mm) in CR than in LW sows (p<0.01). During the hot season, the reduction of average daily feed intake (ADFI) was more pronounced in LW than in CR sows (-920 vs. -480 g/d, p<0.05). Rectal temperature was higher at 1200 than at 0700hr, which coincides with the maximum and the minimum values of daily ambient temperature. The daily RT increased ($+0.9^{\circ}C$; p<0.01) between d -3 and d 7 (d 0: farrowing day), remained constant between d 7 and d 25 and decreased (p<0.01) thereafter (i.e. $-0.6^{\circ}C$ between d 25 and d 32). The average daily RT was significantly higher during the hot than during the warm season (38.9 vs. $38.6^{\circ}C$; p<0.01). It was not affected by breed, but the difference in RT between the hot and warm seasons was more pronounced in LW than in CR sows (+0.4 vs. $+0.2^{\circ}C$; p<0.05). Parity influenced the RT response; it was greater in primiparous than in multiparous sows (38.9 vs. $38.7^{\circ}C$; p<0.01). This study suggests that thermoregulatory responses to heat stress can differ between breeds and between parities.

• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.184-186
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• 2000

This paper proposes the introduction of TAR(Threshold Autoregressive) model for short-term load forecasting including temperature variable. TAR model is a piecewise linear autoregressive model. In the scatter diagram of daily peak load versus daily maximum or minimum temperature, we can find out that the load-temperature relationship has a negative slope in lower regime and a positive slope in upper regime due to the heating and cooling load, respectively. In this paper, daily peak load was forecasted by applying TAR model using this load-temperature characteristic in these regimes. The results are compared with those of linear and quadratic regression models.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.399-399
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• 2001

This paper proposes TAR(Threshold Autoregressive) model for short-term load forecasting including temperature variable. In the scatter diagram of daily peak load versus daily high or low temperature, we can find out that the load-temperature relationship has a negative slope in the lower regime and a positive slope in the upper regime due to the heating and cooling load, respectively. TAR model is adequate for analyzing these phenomena since TAR model is a piecewise linear autoregressive model. In this paper, we estimated and forecasted one day-ahead daily peak load by applying TAR model using this load-temperature characteristic in these regimes. The results are compared with those of linear and quadratic regression models.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.309-405
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• 2001

This paper proposes TAR(Threshold Autoregressive) model for short-term load forecasting including temperature variable. In the scatter diagram of daily peak load versus daily high or low temperature, we can find out that the load-temperature relationship has a negative slope in the lower regime and a positive slope in the upper regime due to the heating and cooling load, respectively. TAR model is adequate for analyzing these phenomena since TAR model is a piecewise linear autoregressive model. In this paper, we estimated and forecasted one day-ahead daily peak load by applying TAR model using this load-temperature characteristic in these regimes. The results are compared with those of linear and quadratic regression models.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.3
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• pp.304-307
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• 1997

Rectal temperature (Tr), skin surface temperatures (Ts), and heart rate (HR) were measured continuously from birth (day 1) till day 7, while resting heat production (HP) was measured in a chamber on days 1, 3, 5 and 7, in order to study the characteristic variation of Tr in newborn calves by heat balance methods. Despite constant levels of milk being given to the newborn calves each day, daily mean resting HP was lowest on the day of birth, then increased to peak on day 3 and then decreased slightly thereafter. Daily mean HR was higher on days 2, 3 and 4, than on other days. Tr exhibited diurnal rhythms and daily mean Tr was low on day 1, high on day 3, and then decreased slightly after day 3. Daily average mean skin temperature (mTs) was similar on all days. Mean body temperature (Tb) exhibited diurnal rhythms and had a similar range between days, suggesting that heat balance and thermoregulation were carried out effectively on each day. The variation of Tb appeared to be synchronized with that of HP and suggested that newborn calves might use variations in the levels of Tb to facilitate the body's required levels of heart loss.

• Journal of the Korean Solar Energy Society
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• v.28 no.4
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• pp.50-55
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• 2008

The Storage efficiency of concentric evacuated tube solar collector is tested for one year from January 1st to December 31st under the real sun condition. The testing equipment is operated continuously for three days without cooling the storage tank. Daily storage efficiency is obtained from dividing stored energy in the storage tank by solar insolation on the solar collector for each day. Daily averaged temperature of the storage tank is lowest in January and highest in August. Monthly averaged storage efficiency is also lowest in November and highest in June. Therefore, it can be said that the storage temperature and the storage efficiency are roughly proportional to outdoor temperature. Furthermore, the daily storage efficiency is reversely proportional to $(T_s-T_a)/I_c$ where $T_s$ and $T_a$ are daily averaged storage temperature and outdoor temperature from sunrise to sunset, and $I_c$ is total insolation on the solar collector for a day.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.2
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• pp.163-174
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• 2021

Heatwaves are one of the most common phenomena originating from changes in the urban thermal environment. They are caused mainly by the evapotranspiration decrease of surface impermeable areas from increases in temperature and reflected heat, leading to a dry urban environment that can deteriorate aspects of everyday life. This study aimed to calculate daily maximum ground surface temperature affecting heatwaves, to quantify the effects of urban thermal environment control through water cycle restoration while validating its feasibility. The maximum surface temperature regression equation according to the impermeable area ratios of urban land cover types was derived. The estimated values from daily maximum ground surface temperature regression equation were compared with actual measured values to validate the calculation method's feasibility. The land cover classification and derivation of specific parameters were conducted by classifying land cover into buildings, roads, rivers, and lands. Detailed parameters were classified by the river area ratio, land impermeable area ratio, and green area ratio of each land-cover type, with the exception of the rivers, to derive the maximum surface temperature regression equation of each land cover type. The regression equation feasibility assessment showed that the estimated maximum surface temperature values were within the level of significance. The maximum surface temperature decreased by 0.0450℃ when the green area ratio increased by 1% and increased by 0.0321℃ when the impermeable area ratio increased by 1%. It was determined that the surface reduction effect through increases in the green area ratio was 29% higher than the increasing effect of surface temperature due to the impermeable land ratio.

• 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.

• Atmosphere
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• v.17 no.2
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• pp.171-183
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• 2007

Trends of daily maximum and minimum temperatures in major cities of South Korea (Seoul, Busan, Incheon, Daegu, and Ulsan) during the past 40 years (1961-2000) were investigated. Temperature records for the Chupungryeong station were compared with those of the large cities because of the rural environment of the station. There were distinct warming trends at all stations, although the warming rates depend on each station's local climate and environment. The warming rates in Korea are much greater than the global warming trends, by a factor of 3 to 4. The most increasing rate in daily maximum temperature was at Busan with $0.43^{\circ}C$ per decade, the most increasing rate in daily minimum temperature was at Daegu with $0.44^{\circ}C$ per decade. In general, the warming trends of the cities were most pronounced in winter season with an increasing rate of $0.5^{\circ}C$/decade at least. Diurnal temperature range shows positive or negative trends according to the regional climate and environmental change. The frequency distribution of the daily temperatures for the past 40 years at Seoul and Chupungryeong shows that there have been reductions in cold day frequencies at both stations. The results imply that the impacts on human health might be positive in winter and adverse in summer if the regional warming scenario by the current regional climate model reflects future climate change in Korea.