• Title/Summary/Keyword: daily average temperature

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Computing Procedure of Daily Average Air Temperature using Field Data and Frost Index Calibration for Anti-Frost Heave Layer Design (현장계측 데이터를 이용한 일평균 대기온도 산정방법과 동상방지층 설계를 위한 동결지수 보정)

  • Cho, Myung-Hwan;Kim, Nakseok;Shim, Jaepill
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.3D
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    • pp.433-439
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    • 2011
  • The frost depth(frost penetration) is used to install anti-frost heave layers in pavement designs. The freezing index is calculated by an annual accumulated value of multiplying the period of time with temperatures below zero, and the corresponding temperature. Therefore, the DAAT(daily average air temperature) calculation method may play an effect on the FI(freezing index). The Weather Observatory used to supply 4 average air temperatures per day, but currently supplies 8 per day. With this study, we divided the southern part(below FI=$350^{\circ}C{\cdot}day$) of the Korean peninsula into 6 areas according to site conditions(low embankment, embankment-cutting slope, and the cutting slope) and established a field measurement system for 15 positions to check the effects on the result of FI according to differing DAAT calculation methods. The air temperatures obtained by the field measurement system was used to calculate and compare the FI. As a result, the freezing index calculated based on the $DAAT_4(T_4)$ is normally greater by 3% than the one on $DAAT_8(T_8)$. In addition, the calibration equation for the freezing index using air temperatures was proposed through the research.

Estimating milk production losses by heat stress and its impacts on greenhouse gas emissions in Korean dairy farms

  • Geun-woo, Park;Mohammad, Ataallahi;Seon Yong, Ham;Se Jong, Oh;Ki-Youn, Kim;Kyu-Hyun, Park
    • Journal of Animal Science and Technology
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    • v.64 no.4
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    • pp.770-781
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    • 2022
  • Meteorological disasters caused by climate change like heat, cold waves, and unusually long rainy seasons affect the milk productivity of cows. Studies have been conducted on how milk productivity and milk compositions change due to heat stress (HS). However, the estimation of losses in milk production due to HS and hereby environmental impacts of greenhouse gas (GHG) emissions are yet to be evaluated in Korean dairy farms. Dairy milk production and milk compositions data from March to October 2018, provided by the Korea Dairy Committee (KDC), were used to compare regional milk production with the temperature-humidity index (THI). Raw data for the daily temperature and relative humidity in 2018 were obtained from the Korea Meteorological Administration (KMA). This data was used to calculate the THI and the difference between the maximum and minimum temperature changing rate, as the average daily temperature range, to show the extent to which the temperature gap can affect milk productivity. The amount of milk was calculated based on the price of 926 won/kg from KDC. The results showed that the average milk production rate was the highest within the THI range 60-73 in three regions in May: Chulwon (northern region), Hwasung (central region), and Gunwi (southern region). The average milk production decreased by 4.96 ± 1.48% in northern region, 7.12 ± 2.36% in central region, and 7.94 ± 2.57% in southern region from June to August, which had a THI range of 73 or more, when compared to May. Based on the results, the level of THI should be maintained like May. If so, the farmers can earn a profit of 9,128,730 won/farm in northern region, 9,967,880 won/farm in central region, and 12,245,300 won/farm in southern region. Additionally, the average number of cows raised can be reduced by 2.41 ± 0.35 heads/farm, thereby reducing GHG emissions by 29.61 ± 4.36 kg CO2eq/day on average. Overall, the conclusion suggests that maintaining environmental conditions in the summer that are similar to those in May is necessary. This knowledge can be used for basic research to persuade farmers to change farm facilities to increase the economic benefits and improve animal welfare.

Lactation in Cross- and Purebred Friesian Cows in Northern Thailand and Analyses on Effects of Tropical Climate on their Lactation

  • Pongpiachan, P.;Rodtian, P.;Ota, K.
    • Asian-Australasian Journal of Animal Sciences
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    • v.13 no.9
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    • pp.1316-1322
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    • 2000
  • Data were compiled and statistically analyzed on the lactation of 50% and 75% Thai native-Friesian crossbred and purebred Friesian cows that were fed at a national institute in Chiang Mai, Thailand. More than 30% higher milk production was obtained in the 75% crossbred compared with that in the 50%, but this amount of milk production in the upgraded breed was still about half that of purebred Friesians; 2,138 kg, least squares means during an average lactation period of 279 days in the 50% crossbred, 2,847 kg during 277 days in the 75% crossbred and 5,585 kg during 308 days in the purebred. Environmental stress due to tropical climate was alleviated by the use of electric fans and water sprinklers in the feeding house during the hot season, and improved diet seemed to enable purebred Friesians to keep their ability to produce a milk quantity of more than 6,500 kg per year. This special care was not given to crossbreds and significantly negative correlations were found between daily minimum temperature and humidity during the initial 100 days of lactation and total milk production and average daily milk yield in the 75% crossbreds. However, these correlations were not found in the 50% crossbreds.

The Influences of Meteorological Factors, Discount rate, and Weekend Effect on the Sales Volume of Apparel Products (기상요인, 가격할인 및 주말효과가 의류상품 판매량에 미치는 영향)

  • Hwangbo, Hyunwoo;Kim, Eun Hie;Chae, Jin Mie
    • Fashion & Textile Research Journal
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    • v.19 no.4
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    • pp.434-447
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    • 2017
  • This study investigated the effects of influencing factors on the sales volume of apparel products. Based on previous studies, weekend effect, discount rate, and meteorological factors including daily average temperature, rainfall, sea level pressure, and fine dust were selected as independent variables to calculate their effects on sales quantity of apparel products. The daily sales data during 2015 - 2016 were collected from casual brands and outdoor brands which "A" apparel manufacturing company had operated. The actual data of "A" company were analyzed using SAS(R) 9.4 and SAS(R) Enterprise Miner 14.1. The results of this study were as follows: First, the influencing factors on total sales volume of apparel products were proved to be the weekend effect, discount rate, and fine dust. Second, the analysis of influencing factors on sales volume of apparel products according to season showed: 1) In casual brands, the average temperature had a significant influence on the sales volume of spring/summer products, and the sea level pressure affected the sales volume of summer/fall/winter products significantly. 2) In outdoor brands, the average temperature and the fine dust had a significant influence on the sales volume of all season's products. The sea level pressure affected the sales volume of summer/fall/ winter products significantly. The weekend effect and the discount effect affected the sales volume of apparel products partly. Third, the effect of rainfall was not proven significant, which was different from the results of past studies.

Trend of Climatic Growing Season using Average Daily Temperature (1971~2013) in Suwon, Korea (일평균기온(1971~2013)을 이용한 수원지역의 기후학적 식물생육기간의 변화 경향)

  • Jung, Myung-Pyo;Shim, Kyo-Moon;Kim, Yong-Seok;Choi, In-Tae;So, Kyu-Ho
    • Journal of Climate Change Research
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    • v.5 no.4
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    • pp.285-289
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    • 2014
  • The extension of growing season (GS) across the Northern Hemisphere have been linked to increasing temperature, related with global warming. Therefore, in this study, The start, end, and length of GS in Suwon, Korea from 1971 to 2013 based on observed daily mean air temperature are examined using three indices. The GS starts on average after $98.598.5{\pm}1.42$ Julian days and ends after $318.7{\pm}1.08$ Julian days. The average length of GS is $220.2{\pm}2.09$ Julian days. The length of GS in Suwon from 1971 to 2013 has been extended by 6.8 days/decade with an earlier onset of the GS (-4.1 days/decade) and later end of the GS (2.7 days/decade). This change may be due to an advanced start of the GS in spring rather than later end of the GS. In further study, it is necessary to select an index carefully to find the most suitable one for Korea.

Analysis of Optimal Index for Heat Morbidity (온열질환자 예측을 위한 최적의 지표 분석)

  • Sanghyuck Kim;Minju Song;Seokhwan Yun;Dongkun Lee
    • Journal of Environmental Impact Assessment
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    • v.33 no.1
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    • pp.9-17
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    • 2024
  • The purpose of this study is to select and predict optimal heatwave indices for describing and predicting heat-related illnesses. Regression analysis was conducted using Heat-related illness surveillance system data for a number of heat-related illnesses and meteorological data from the Korea Meteorological Administration's Automatic Weather Station (AWS) for the period from 2021 to 2023. Daily average temperature, daily maximum temperature, daily average Wet Bulb Globe Temperature (WBGT), and daily maximum WBGT values were calculated and analyzed. The results indicated that among the four indicators, the daily maximum WBGT showed the highest suitability with an R2 value of 0.81 and RMSE of 0.98, with a threshold of 29.94 Celsius. During the entire analysis period, there were a total of 91 days exceeding this threshold, resulting in 339 cases of heat-related illnesses. Predictions of heat-related illness cases from 2021 to 2023 using the regression equation for daily maximum WBGT showed an accuracy with less than 10 cases of error annually, demonstrating a high level of precision. Through continuous research and refinement of data and analysis methods, it is anticipated that this approach could contribute to predicting and mitigating the impact of heatwaves.

Analysis of the Long-term Trend of PM10 Using KZ Filter in Busan, Korea (KZ 필터를 이용한 부산지역 PM10의 장기 추세 분석)

  • Do, Woo-gon;Jung, Woo-Sik
    • Journal of Environmental Science International
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    • v.26 no.2
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    • pp.221-230
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    • 2017
  • To determine the effect of air pollution reduction policies, the long-term trend of air pollutants should be analyzed. Kolmogorov-Zurbenko (KZ) filter is a low-pass filter, produced through repeated iterations of a moving average to separate each variable into its temporal components. The moving average for a KZ(m, p) filter is calculated by a filter with window length m and p iterations. The output of the first pass subsequently becomes the input for the next pass. Adjusting the window length and the number of iterations makes it possible to control the filtering of different scales of motion. To break down the daily mean $PM_{10}$ into individual time components, we assume that the original time series comprises of a long-term trend, seasonal variation, and a short-term component. The short-term component is attributable to weather and short-term fluctuations in precursor emissions, while the seasonal component is a result of changes in the solar angle. The long-term trend results from changes in overall emissions, pollutant transport, climate, policy and/or economics. The long-term trend of the daily mean $PM_{10}$ decreased sharply from $59.6ug/m^3$ in 2002 to $44.6ug/m^3$ in 2015. This suggests that there was a long-term downward trend since 2005. The difference between the unadjusted and meteorologically adjusted long-term $PM_{10}$ is small. Therefore, we can conclude that $PM_{10}$ is unaffected by the meteorological variables (total insolation, daily mean temperature, daily mean relative humidity, daily mean wind speed, and daily mean local atmospheric pressure) in Busan.

A Study on Clothes Sales Forecast System using Weather Information: Focused on S/S Clothes (기상정보를 활용한 의류제품 판매예측 시스템 연구: S/S 시즌 제품을 중심으로)

  • Oh, Jai Ho;Oh, Hee Sun;Choi, Kyung Min
    • Fashion & Textile Research Journal
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    • v.19 no.3
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    • pp.289-295
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    • 2017
  • This study aims to develop clothing sales forecast system using weather information. As the annual temperature variation affects changes in daily sales of seasonal clothes, sales period can be predicted growth, peak and decline period by changes of temperature. From this perspective, we analyzed the correlation between temperature and sales. Moving average method was applied in order to indicate long-term trend of temperature and sales changes. 7-day moving average temperature at the start/end points of the growth, peak, and decline period of S/S clothing sales was calculated as a reference temperature for sales forecast. According to the 2013 data analysis results, when 7-day moving average temperature value becomes $4^{\circ}C$ or higher, the growth period of S/S clothing sales starts. The peak period of S/S clothing sales starts at $17^{\circ}C$, up to the highest temperature. When temperature drops below $21^{\circ}C$ after the peak temperature, the decline period of S/S clothing sales is over. The reference temperature was applied to 2014 temperature data to forecast sales period. Through comparing the forecasted sales periods with the actual sales data, validity of the sales forecast system has been verified. Finally this study proposes 'clothing sales forecast system using weather information' as the method of clothing sales forecast.

Unsteady heat exchange at the dry spent nuclear fuel storage

  • Alyokhina, Svitlana;Kostikov, Andrii
    • Nuclear Engineering and Technology
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    • v.49 no.7
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    • pp.1457-1462
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    • 2017
  • Unsteady thermal processes in storage containers with spent nuclear fuel were modeled. The daily fluctuations of outer ambient temperatures were taken into account. The modeling approach, which is based on the solving of conjugate and inverse heat transfer problems, was verified by comparison of measured and calculated temperatures in outer channels. The time delays in the reaching of maximal temperatures for each spent fuel assembly were calculated. Results of numerical investigations show that daily fluctuation of outer temperatures does not have a large influence on the maximal temperatures of stored spent fuel, so that fluctuation can be neglected and only daily average temperature should be considered for safety estimation using the "best estimation" approach.

기후변화의 위험헷지와 기온파생상품

  • Son, Dong-Hui;Im, Hyeong-Jun;Jeon, Yong-Il
    • Environmental and Resource Economics Review
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    • v.21 no.3
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    • pp.465-491
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    • 2012
  • Climate change, a result of increasing global warming, has been receiving more public attention due to its serious impact upon many industries. In this study we consider sustainable- (Green-) Growth and Green-Finance, and in particular temperature derivatives, as appropriately active responses to the world's significant climate change trends. We characterize the daily average temperatures in Seoul, South Korea with their seasonal properties and cycles of error terms. We form forecasting models and perform Monte Carlo simulations, and find that the risk-neutral values for CDD call-options and HDD put-options have risen since 1960s, which implies that the trend of temperature increase can be quantified in the financial markets. Contrary to the existing models, the Vasicek model with the explicit consideration of cycles in the error terms suggests that the significant option-values for the CDD call -options above certain exercise prices, implying that there is the possibility of explicit hedging against the considerable and stable increase in temperature.

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