• Journal of Korean Society of Forest Science
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• v.62 no.1
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• pp.1-18
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• 1983

Sum of daily mean temperature, sum of daily mean relative humidity and sum of daily mean duration of sunshine during the growing season (March-October), and daily mean temperature, daily mean relative humidity and daily mean minimum temperature during the dormant season (November-February) were obtained respectively from the climactic data recorded at 26 different standard stations for 30 years from 1951 to 1980, to provide a method for proper selection of tree species suitable to a certain site. They were also marked on the map of Korea. The whole country was divided into 6 regions by trend of temperature variation and the regression equations for each region were produced to estimate the sum of daily mean temperature of the growing season and the sum of daily mean minimum temperature of the dormant season in a certain site where tree plantings are planned. The natural range of distribution of each species was expressed by the sum of daily mean temperature and daily mean minimum temperature on the basis of "Horizontal and vertical distribution of the Korean woody plants" reported by Chung and Lee (1965).

• Atmosphere
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• v.17 no.1
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• pp.17-26
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• 2007

The station relocations, the replacement of instruments, and the change of a procedure for calculating derived climatic quantities from observations are well-known nonclimatic factors that seriously contaminate the worthwhile results in climate study. Prior to embarking on the climatological analysis, therefore, the quality and homogeneity of the utilized data sets should be properly evaluated with metadata. According to the metadata of the Korea Meteorological Administration (KMA), there have been plenty of changes in the procedure computing the daily mean values of temperature, humidity, etc, since 1904. For routine climatological work, it is customary to compute approximate daily mean values for individual days from values observed at fixed hours. In the KMA, fixed hours were totally 5 times changed: at four-hourly, four-hourly interval with additional 12 hour, eight-hourly, six-hourly, three-hourly intervals. In this paper, the homogeneity in the daily mean temperature dataset of the KMA was assessed with the consistency and efficiency of point estimators. We used the daily mean calculated from the 24 hourly readings as a potential true value. Approximate daily means computed from temperatures observed at different fixed hours have statistically different properties. So this inhomogeneity in KMA climate data should be kept in mind if you want to analysis secular aspects of Korea climate using this data set.

• 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.

• Atmosphere
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• v.33 no.1
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• pp.1-20
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• 2023

Holding the longest observation data from April 1904, Busan is one of the essential points to understand the climate variability of the Korean Peninsula without missing data since implementing the modern weather observation of the South Korea. Busan is featured by coastal areas and affected by various climate factors and fluctuations. This study aims to investigate climate variability and changes in climatic variables, extremes, and several weather indexes. The statistically significant change points in daily mean rainfall intensity and temperature were found in 1964 and 1965. Based on the change point detection, 117 years were divided into two periods for daily mean rainfall intensity and temperature, respectively. In the long-term temperature analysis of Busan, the increasing trend of the daily maximum temperature during the period of 1965~2021 was larger than the daily mean temperature and the daily minimum temperature. Applying Ensemble Empirical Mode Decomposition, daily maximum temperature is largely affected by the decadal variability compared to the daily mean and minimum temperature. In addition, the trend of daily precipitation intensity from 1964~2021 shows a value of about 0.50 mm day^-1, suggesting that the rainfall intensity has increased compared to the preceding period. The results in extremes analysis demonstrate that return values of both extreme temperatures and precipitation show higher values in the latter than in the former period, indicating that the intensity of the current extreme phenomenon increases. For Wet-Bulb Globe Temperature (effective humidity), increasing (decreasing) trend is significant in Busan with the second (third)-largest change among four stations.

• 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 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.

• Journal of Environmental Health Sciences
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• v.10 no.1
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• pp.1-12
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• 1984

The stochastic characteristics of the daily range of water temperature variation was analyzed by employing the techniques of autocorrelation coefficient, autoreggresive model and crosscorrelation model. These time series included daily observations on maximum and minimum values of water temperature and air temperature. The measurement was made by automatic recording instrument at Gu-yee and Dook-do in Han River, and at Waegwan and Gu-mi in Nackdong River in 1981. As a result of this study, it was found that (1) The correlogram of daily water temperature ranges $\Delta AT_i$ and daily air temperature $\Delta AT_i$ at Gu-mi and Gu-yee showed the exponential curves. (2) The most high frequency values of $\Delta AT_i$ and $\Delta WT_i$ were 11$\circ$C and 0.5${\circ}C$ respectively at every measuring site. (3) The correlation coefficients between the daily mean air temperature AT$_i$ and the daily mean water temperature were fairly high as 0.966 at Dook-do and 0.949 at Gu-yee, but the correlation coefficients between $\Delta AT_i$ and $\Delta WT_i$ were very low as 0.1074 at Gu-yee and 0.0324 at Dook-Do.

• 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 the Korean Geographical Society
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• v.46 no.2
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• pp.152-167
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• 2011

This study aims to investigate the change of seasonal trend appeared in the daily normals of wintertime daily mean temperature of Seoul for 1941~1970 and 1971~2000 and the factors to affect it. The lowest temperature in wintertime is appeared in the period of the first and second ten-days of January in the daily normals for 1941~1970 and in the third ten-days of January and the first ten-days of February for 1971~2000. This means seasonal trend was changed. This change is due to the fact average temperature from 27 December to 20 January is rising much more than the wintertime mean temperature and average temperature from 21 January to 9 February less than that for two daily normals. This features are notable after 1971. The Siberian high and norther wind around the Korean Peninsula are weakened remarkably recently, so mean temperature of Seoul from 27 December to 20 January is warming much more. On the other hand, the Siberian high from 21 January to 9 February is weakened and the Aleutian low is strengthened recently and northerly is not change obviously, so temperature of Seoul is not warming so much.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.473-473
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• 2011

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it consists of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily ETo data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as ETo modeling can be generalized using GMDH-NNM.