• The Korean Journal of Physiology
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• v.3 no.1
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• pp.19-28
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• 1969

Skin temperatures on 10 sites and rectal temperature at every 10 minutes, oxygen consumption at every 20 minutes were measured on 18 male subjects (ages between 14 and 47 years) after exposure to cold air at $15^{\circ}C$ for two hours in a climatic room. Total body fat measured by means of a skinfold method and ratio of body surface area (S) to body volume (V), S/V, were utilized as basis of observations. Surface area was calculated after DuBois equation and body volume was calculated by our original formula. In influencing on the heat loss from the body core to the cold environment, % fat showed inverse relations, whereas, S/V ratio showed direct relations. Thus these two factors acted antagonistically on the body heat loss. Local skin temperatures showed negative correlations with skinfold thickness on the same site, nemaly, on chest, r=-.567; on back, r=-.507; and on upper arm, r=-.353. The other 7 skin sites showed low correlations with % fat. Minimum mean weighted skin temperature (MWST) showed a negative correlation (r=-.443) with % fat, and showed no correlation with S/V ratio. Oxygen consumption in the cold air at $15^{\circ}C$ increased from the first measurement at 20 minutes after exposure and maintained the same increasing trend up to 120 minutes. ${\Delta}T_R$ was greater in tile lean subjects who showed a greater % change in oxygen consumption. The antagonistic actions of % fat and S/V ratio on the heat loss were manifested by observations as follows: minimum rectal temperature was higher In fat subjects (r=.600) and lower in subjects with a greater S/V ratio (=-.582), ${\Delta}T_R$ was smaller in fat subjects (r=-.738) and greater in subjects with a greater S/V ratio (r=.618). Temperature difference between body core and skin surface (minimum rectal temperature minus minimum MWST) showed a positive correlation with % fat (r=.600) and a negative correlation with S/V ratio (r=-.881). Decrease in the mean body temperature and heat debt, respectively, showed negative correlations with % fat and positive correlations with S/V ratio.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.5
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• pp.582-590
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• 2004

The purpose of this study was to evaluate thermal properties of Taekwondo wears with three different materials. As a begging step, the questionnaire survey about the actual condition of Taekwondo wears was conducted. With the results of the questionnaire, cotton/nylon(70/30) blended fabric(CN) that was newly woven with sweat absorbent finishing and cotton/spandex(95/5) blended fabric with flexibility property were developed. The same designed 3 Taekwondo wears with 3 different materials which were two different materials(CN and CS) and a current material(cotton/PET, CP) were made. Four young males volunteered for this study, they kicked and punched as Taekwondo action for 20 minutes. Mean skin temperature was the highest in CS(33.1${\pm}$0.8$^{\circ}C$) and the lowest in CP(32.7${\pm}$0.6$^{\circ}C$). Increasing degree of rectal temperature didn't show any significant difference. Clothing microclimate temperature on the thigh was higher in CS(32.8${\pm}$17.4$^{\circ}C$) than in CN(29.4${\pm}$1.1$^{\circ}C$) and CP(29.4${\pm}$1.0$^{\circ}C$). Clothing microclimate temperature on the back and humidity on the thigh didn't show any significant differences. Clothing microclimate humidity on the back was higher in CP(65${\pm}$20%RH) than in CS(61${\pm}$17％RH). Heart rate, total body weight loss, and local sweating were not significantly different by materials. Most subject responded more hot in CN than in others, but there were no significant differences at the subjective sensation of thermal humidity. They answered more comfortable in CN than in others. Tectile sensations were the best in CN and the worst in CS. From those results, first of all, it is necessary to be weighted on Taekwondo wears made of CN in the aspects of the dignity of military arts uniform. Secondly, CS was required to be lighted and enhanced for the subjective sensation. Third, CP weaved honey comb was asked more various design to eliminate sweat high competition power within the scope of the dignity of military arts uniform.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.125-143
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• 2017

This study is conducted to estimate potential evapotranspiration of 10 weather observing systems in Andong Dam watershed with FAO56 Penman-Monteith (FAO56 PM) methodology using the meteorological data from 2013 to 2014. Also, assuming that there is no solar radiation data, humidity data or wind speed data, the potential evapotranspiration was estimated by FAO56 PM and the results were evaluated to discuss whether the methodology is applicable when meteorological dataset is not available. Then, the potential evapotranspiration was estimated with Hargreaves method and compared with the potential evapotranspiration estimated by FAO56 PM only with the temperature dataset. As to compare the potential evapotranspiration estimated from the complete meteorological dataset and that estimated from limited dataset, statistical analysis was performed using the Root Mean Square Error (RMSE), the Mean Bias Error (MBE), the Mean Absolute Error (MAE) and the coefficient of determination ($R^2$). Also the Inverse Distance Weighted (IDW) method was performed to conduct spatial analysis. From the result, even when the meteorological data is limited, FAO56 PM showed relatively high accuracy in calculating potential evapotranspiration by estimating the meteorological data.

• Atmosphere
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• v.20 no.2
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• pp.73-89
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• 2010

An updateable model output statistics (UMOS) system for daily maximum and minimum temperature ($T_M$ and $T_m$) over South Korea based on the Canadian UMOS system were developed and validated. RDAPS (regional data assimilation and prediction system) and KWRF (Korea WRF) which have quite different physics and dynamics were used for the development of UMOS system. The 20 most frequently selected potential predictors for each season, station, and forecast projection time from the 68 potential predictors of the MOS system, were used as potential predictors of the UMOS system. The UMOS equations were developed through the weighted blending of the new and old model data, with weights chosen to emphasize the new model data while including enough old model data to ensure stable equations and a smooth transition of dependency from the old model to the new model. The UMOS equations are being updated by every 7 days. The validation results of $T_M$ and $T_m$ showed that seasonal mean bias, RMSE, and correlation coefficients for the total forecast projection times are -0.41-0.17 K, 1.80-2.46 K, and 0.80-0.97, respectively. The performance is slightly better in autumn and winter than in spring and summer. Also the performance of UMOS system are clearly dependent on location, better at the coastal region than inland area. As in the MOS system, the performance of UMOS system is degraded as the forecast day increases.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.287-297
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• 2016

This study aims to identify the relationship between climatic factors and stand mean Diameter at Breast Height (DBH) for two major tree species; Pinus densiflora and Quercus mongolica in Andong-dam basin. Forest variables such as age, diameter distribution and number of trees per hectare from the $5^{th}$ and $6^{th}$ National Forest Inventory data were used to develop a DBH estimation model. Climate data were collected from six meteorological observatory station and twelve Automatic Weather System provided by Korea Meteorological Administration to produce interpolated daily average temperature map with Inverse Distance Weighting (IDW) method. Andong-dam basin reflects rugged mountainous terrain, so temperature were adjusted by lapse rate based correction. As a result, predictions of model were consistent with the previous studies; that the rising temperature is negatively related to the growth of Pinus densiflora whereas opposing trend is observed for Quercus mongolica.

• Journal of Environmental Health Sciences
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• v.32 no.4 s.91
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• pp.304-315
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• 2006

This study is performed to reexamine the association between ambient air pollution and daily mortality in seven major cities of Korea using a method of meta-analysis with the data filed for the period 1998-2001. These cities account for half of the Korean population (about 23 million). The observed concentrations of carbon monoxide (CO, mean=1.08 ppm), ozone ($O_3$, mean=33.97 ppb), particulate matter less than 10 ${\mu}m$ ($PM_{10},\;mean=57.11\;{\mu}g/m^3$), nitrogen dioxide ($NO_2$, mean=25.09 ppb), and sulfur dioxide ($SO_2$, mean=9.14 ppb) during the study period were at levels below Korea's current ambient air quality standards. Generalized additive models were applied to allow for the highly flexible fitting of seasonal and long-term time trends in air pollution as well as nonlinear associations with weather variables, such as air temperature and relative humidity. Also, we calculated a weighted mean as a meta-analysis summary of the estimates and its standard error. In city-specific analyses, an increase of $41.17{\mu}g/m^3(IQR)\;of\;PM_{10}$ corresponded to $1{\sim}12%$ more deaths, given constant weather conditions. Like most of air pollution epidemiologic studies, this meta-analysis cannot avoid fleeing from measurement misclassification since no personal measurement was taken. However, we can expect that a measurement bias be reduced in district-specific estimate since a monitoring station is better representative of air quality of the matched district. Significant heterogeneity was found for the effect of all pollutants. The estimated relative risks from meta-like analysis increased compared to those relative risks from pooled analysis. The similar results to those from the previous studies indicated existence of health effect of air pollution at current levels in many industrialized countries, including Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.37-43
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• 2001

Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.94-101
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• 2009

In this paper, we propose design of hardware based on a high speed digital signal processor (DSP) and a field programmable gate array (FPGA) for real-time suppression of fixed pattern noise (FPN) using hardware neural networks (HNN) in cooled infrared focal plane array (IRFPA) imaging system FPN appears a limited operation by temperature in observable images which applies to non-uniformity correction for infrared detector. These have very important problems because it happen serious problem for other applications as well as degradation for image quality in our system Signal processing architecture for our system operates reference gain and offset values using three tables for low, normal, and high temperatures. Proposed method creates virtual tables to separate for overlapping region in three offset tables. We also choose an optimum tenn of temperature which controls weighted values of HNN using mean values of pixels in three regions. This operates gain and offset tables for low, normal, and high temperatures from mean values of pixels and it recursively don't have to do an offset compensation in operation of our system Based on experimental results, proposed method showed improved quality of image which suppressed FPN by change of temperature distribution from an observational image in real-time system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.51-66
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• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.