• 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).

• Journal of Climate Change Research
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• v.7 no.2
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• pp.205-215
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• 2016

The relationship between the climate and the number of heat-related patients in South Korea was analysed in this study. The number of the patients was 1,612 during the summer 2011 to 2015 according to the Heat-related Illness (HRI) surveillance system. The coefficient of determination between the number of the patients and the daily maximum temperature was higher than that between the number of them and the other elements: the daily mean/minimum temperature and relative humidity. The thresholds of daily maximum and minimum temperature in metropolitan cities (MC) were higher than those in regions except for MC (RMC). The higher the maximum and minimum temperature became, the more frequently the heat-related illness rate was observed. The regional difference of this rate was that the rate in RMC was higher than that in MC. Prolonged heat wave and tropical night tended to cause more patients, which continued for 20 days and 31 days of maximum values, respectively. On the other hand, the relative humidity was not proportional to the number of the patients which was rather decreasing at over 70% of relative humidity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.203-212
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• 2002

This study was conducted to remove the urban heat island effects embedded in the interpolated surfaces of daily minimum temperature in the Korean Peninsula. Fifty six standard weather stations are usually used to generate the gridded temperature surface in South Korea. Since most of the weather stations are located in heavily populated and urbanized areas, the observed minimum temperature data are contaminated with the so-called urban heat island effect. Without an appropriate correction, temperature estimates over rural area or forests might deviate significantly from the actual values. We simulated the spatial pattern of population distribution within any single population reporting district (city or country) by allocating the reported population to the "urban" pixels of a land cover map with a 30 by 30 m spacing. By using this "digital population model" (DPM), we can simulate the horizontal diffusion of urban effect, which is not possible with the spatially discontinuous nature of the population statistics fer each city or county. The temperature estimation error from the existing interpolation scheme, which considers both the distance and the altitude effects, was regressed to the DPMs smoothed at 5 different scales, i.e., the radial extent of 0.5, 1.5, 2.5, 3.5 and 5.0 km. Optimum regression models were used in conjunction with the distance-altitude interpolation to predict monthly normals of daily minimum temperature in South Korea far 1971-2000 period. Cross validation showed around 50% reduction in terms of RMSE and MAE over all months compared with those by the conventional method.conventional method.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.5
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• pp.359-364
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• 2013

This study was conducted to develop a model to estimate crop leaf surface temperature. The results were as following; A definition for the daily time based on elapsed time from the midnight (00:00) as "E&E time" with the unit of Kmin. was suggested. The model to estimate the scaled temperature ($T^*e$) of crop leaf surface temperature by scale factor ($T^*$) according to the "E&E time : Kmin."(X) was developed as eq. (1) $T^*e=0.5{\cdot}sin(X+780)+0.5$ (2) $T^*=(Tx-Tn)/(Tm-Tn)$, Tx : Daily leaf temperature, Tm : Daily maximum leaf temperature, Tn : Daily minimum leaf temperature. Relative sensitivity of the measured temperature compared to the estimated temperature of red pepper, soybean and persimmon was 1.078, 1.033 and 0.973, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1497-1500
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• 2006

The cooling effect of paddy fields was compared with those of other land-use areas (upland, urban park, and urban residential area) during midsummer. The temperature were monitored using data logger at one hour intervals in study sites. Diurnal temperature range of study areas in clear days was larger than in cloudy days. Also, diurnal temperature ranges in paddy field, upland, and park areas were larger than those in the urban residential area during clear days. The paddy field or upland area has shown more remarkable cooling effect compared to urban residential areas: Mean duration of temperature below $25^{\circ}C$ in the paddy field area is longer(7 to 8 hours) than in the residential area; The time to fall to below $25^{\circ}C$ in the paddy field area is sooner than in the residential area; Mean daily minimum temperature in the paddy field area is much lower than in the residential area.

• Proceedings of the Korean Quaternary Association Conference
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• 2004.06a
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• pp.29-29
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• 2004

Long term observational analysis by climatologists has confirmedthat the global warming is no longer a topic of debate among scientists andpolicy makers. According to the report of IPCC-2001 (Intergovernmental Panelon Climate Change), the global mean surface air temperature is increasinggradually. The reported increase of mean temperature is by 0.6 degree in the end of twentieth century. This could represent severe threat for propertylosses especially due to increase in the number of extreme weather arising out of global warming. period of model integration from 2001 to 2100 using output of ECHAM4/HOPE-G of Max Planet Institute of Meteorology (MPI) for IPCC SRES (Special Report on Emission Scenarios). The main results of this study indicate increase of surface air temperature by 6.20C and precipitation by 2.6% over Korea in the end of 21st century. Simulation results also show that there is increase in daily maximum and minimum temperatures while decrease in diurnal temperature range (DTR). DTR changes are diminished mainly due to relatively rapid increase of daily minimum temperature than that of daily maximumtemperature. It has been observed that increase in precipitation amount anddecrease in the number of rainy days lead to increase of pre precipitationintensity.

• Journal of Environmental Science International
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• v.26 no.9
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• pp.1023-1029
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• 2017

We studied the distribution of air temperature using the high density urban climate observation network data of Daegu. The observation system was established in February 2013. We used a total of 38 air temperature observation points (23 thermometers and 18 AWSs). From the distribution of monthly averaged air temperatures, air temperatures at the center of Daegu were higher than in the suburbs. The daily minimum air temperature was more than or equal to $25^{\circ}C$ and the daily maximum air temperature was more than or equal to $35^{\circ}C$ at the elementary school near the center of Daegu. Also, we compared the time elements, which are characterized by the diurnal variation of surface air temperature. The warming and cooling rates in rural areas were faster than in urban areas. This is mainly due to the difference in surface heat capacity. These results indicate the influence of urbanization on the formation of the daily minimum temperature in Daegu.

• 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.

• Atmosphere
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• v.26 no.4
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• pp.697-709
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• 2016

This study estimates and evaluates the extreme value of 30 m-resolution daily maximum and minimum temperatures over South Korea, using inverse distance weighting (IDW), parameter-elevation regression on independent slopes model (PRISM) and generalized extreme value (GEV) method. The three experiments are designed and performed to find the optimal estimation strategy to obtain extreme value. First experiment (EXP1) applies GEV firstly to automated surface observing system (ASOS) to estimate extreme value and then applies IDW to produce high-resolution extreme values. Second experiment (EXP2) is same as EXP1, but using PRISM to make the high-resolution extreme value instead of IDW. Third experiment (EXP3) firstly applies PRISM to ASOS to produce the high-resolution temperature field, and then applies GEV method to make high resolution extreme value data. By comparing these 3 experiments with extreme values obtained from observation data, we find that EXP3 shows the best performance to estimate extreme values of maximum and minimum temperatures, followed by EXP1 and EXP2. It is revealed that EXP1 and EXP2 have a limitation to estimate the extreme value at each grid point correctly because the extreme values of these experiments with 30 m-resolution are calculated from only 60 extreme values obtained from ASOS. On the other hand, the extreme value of EXP3 is similar to observation compared to others, since EXP3 produces 30m-resolution daily temperature through PRISM, and then applies GEV to that result at each grid point. This result indicates that the quality of statistically produced high-resolution extreme values which are estimated from observation data is different depending on the combination and procedure order of statistical methods.