• KIEAE Journal
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• v.15 no.3
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• pp.5-14
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• 2015

Purpose: Recently, according to climate changes, human health is exposed to danger over the world and they influence all fields of human society. Due to these climate changes, humans can be exposed to more frequent and extreme scorching heat and cold wave than the present. As precautions against these urban higher temperature and dryness, diverse methods are being sought. Among them, as measures to form cold islands, the evaporative cooling effect realistic to social and economic conditions was examined. Method: This study was conducted to analyze effects of temperature reduction and cooling according to injection quantity of minute water particles by using a blast sprayer as one of alternatives of alleviation of urban climate changes in outside space in summer. For this, through temperature difference in accordance with the injection quantity per hour of a day, a time zone representing the value of the highest temperature change was analyzed. Also, by analyzing temperature difference according to the injection quantity per daytime insolation, relation of amounts of insolation and evaporation was investigated. Temperature difference in accordance with distances at the highest temperature with the highest value in temperature changes was analyzed. Result: At the study result, about temperature, as injection quantity increase, temperature reduction was significant statistically at the highest temperature with the most insolation. A factor with the highest influence was judged to be the increase of the injection quantity. According to the injection quantity, it was predicted that $3.1^{\circ}C$ temperature reduction of a daily average in case of 0.16L/min, $3.5^{\circ}C$ temperature reduction of a daily average in case of 0.32L/min, and $4.4^{\circ}C$ temperature reduction of a daily average in case of 0.48L/min.

• Journal of agriculture & life science
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• v.53 no.2
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• pp.121-129
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• 2019

This study carried out to determine control factors for the improvement of productivity of laying hens suffering heat stress during hot weather. A total of 48,451 ISA Brown layers were housed in a farm located in Gyeongsangnam-do, Republic of Korea. Five thermo-hydrometer loggers were installed inside the house to collect data of dry-bulb temperature and relative humidity. The experiment continued for 81 days when the summer season begins from 19th June to 7th September, 2018. This study analyzed the correlations among layers' production index and daily average, highest, and lowest temperature; daily average, highest, and lowest relative humidity; and daily average, minimum, and maximum THI. The result indicated that feed consumption, hen-day egg production, egg weight, and FCR decreased as the daily average, highest and lowest dry-bulb temperature and THI rise (p<0.01). On the other hand, water intake increased as the daily average, highest and lowest dry-bulb temperature and THI rise (p<0.001). The relative humidity was not considered to have direct correlations to the layers' production index (p>0.05). However, it was noticeable that the mortality did not have significant relations with daily average and highest temperature; THI; or daily average, highest and lowest relative humidity while it was relevant to the daily lowest temperature and THI (p<0.05). In conclusion, to enhance the productivity of laying hens in a hot climate, it is recommended that daily average, highest, and lowest dry-bulb temperature and THI are maintained as low as possible. Especially, the daily lowest temperature is needed to lower to 20℃, which is the lowest critical temperature for layers.

• Journal of Environmental Science International
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• v.18 no.4
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• pp.369-374
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• 2009

To examine the trend on the flowering time in some weather flora including Prunus serrulata var. spontanea, Cosmos bipinnatus, and Robinia pseudo-acacia in Busan, the changes in time series and rate of flowering time of plants were analyzed using the method of time series analysis. According to the correlation between the flowering time and the temperature, changing pattern of flowering time was very similar to the pattern of the temperature, and change rate was gradually risen up as time goes on. Especially, the change rate of flowering time in C. bipinnatus was 0.487 day/year and showed the highest value. In flowering date in 2007, the difference was one day between measurement value and prediction value in C. bipinnatus and R. pseudo-acacia, whereas the difference was 8 days in P. mume showing great difference compared to other plants. Flowering time was highly related with temperature of February and March in the weather flora except for P. mume, R. pseudo-acacia and C. bipinnatus. In most plants, flowering time was highly related with a daily average temperature. However, the correlation between flowering time and a daily minimum temperature was the highest in Rhododendron mucronulatum and P. persica, otherwise the correlation between flowering time and a daily maximum temperature was the highest in Pyrus sp.

• Fisheries and Aquatic Sciences
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• v.3 no.2
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• pp.78-82
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• 2000

The influence of daily water temperature changes on chemiluminescent (CL) response of phagocytes, plasma glucose level and mortality in cultured gray mullet (Mugil cephalus) was investigated. Among three experimental temperature groups, the fish in group I and group II were maintained constantly at $27^{\circ}C$ and $29^{\circ}C$, respectively, and those in group III were suffered daily elevation of water temperature from $27^{\circ}C$ to $29^{\circ}C$ for 5 hours, then restored again to $27^{\circ}C$. After 1 week of maintaining at each experimental tank, the fish in group III showed significantly lower CL peak value (p < 0.01) and higher plasma glucose levels (p < 0.05) than those in group I and group II. The cumulative mortality of group III was $86.9\%$ within 3 days after being subjected to acute handling stress. On the other hand, the cumulative mortalities of group I and group II were $12.5\%$ and $19.2\%$, respectively. In conclusion, gray mullet farms, especially, in the vicinity of thermoelectric power plants should avoid stressing the fish during periods of high water temperature.

• Atmosphere
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• v.24 no.1
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• pp.101-110
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• 2014

This study estimates and evaluates the daily January temperature from 2003 to 2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regression on Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjusted to 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in terms of bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then compared with that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimating the temperature over Jeju island, K-PRISM has the lowest bias (-0.85) and RMSE (1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation of observation, but tends to underestimate due to a high-discrepancy in mean altitudes between the observation stations and grid points of the 30 m topography. The temperature over South Korea derived from K-PRISM represents a detailed spatial pattern of the observed temperature, but generally tends to underestimate with a mean bias of -0.45. In bias terms, the estimation ability of K-PRISM differs between grid points, implying that care should be taken when dealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate 30 m-resolution temperature over South Korea, and reflect topographically diverse signals with detailed structure features.

• Atmosphere
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• v.22 no.3
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• pp.299-307
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• 2012

This study is aimed to validate errors for detected suspicious temperature data using various quality control procedures for 61 weather stations in the Republic of Korea. The quality control algorithms for temperature data consist of four main procedures (high-low extreme check, internal consistency check, temporal outlier check, and spatial outlier check). Errors of detected suspicious temperature data are judged by examining temperature data of nearby stations, surface weather charts, hourly temperature data, daily precipitation, and daily maximum wind direction. The number of detected errors in internal consistency check and spatial outlier check showed 4 days (3 stations) and 7 days (5 stations), respectively. Effective and objective methods for validation errors through this study will help to reduce manpower and time for conduct of quality management for temperature data.

• 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.

• Computers and Concrete
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• v.8 no.3
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• pp.293-309
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• 2011

A long-term structural health monitoring (SHM) system comprising over 700 sensors of sixteen types has been implemented on the Guangzhou Television and Sightseeing Tower (GTST) of 610 m high for real-time monitoring of the structure at both construction and service stages. As part of this sophisticated SHM system, 48 temperature sensors have been deployed at 12 cross-sections of the reinforced concrete inner structure of the GTST to provide on-line monitoring via a wireless data transmission system. In this paper, the differential temperature profiles in the reinforced concrete inner structure of the GTST, which are mainly caused by solar radiation, are recognized from the monitoring data with the purpose of understanding the temperature-induced structural internal forces and deformations. After a careful examination of the pre-classified temperature measurement data obtained under sunny days and non-sunny days, common characteristic of the daily temperature variation is observed from the data acquired in sunny days. Making use of 60-day temperature measurement data obtained in sunny days, statistical patterns of the daily rising temperature and daily descending temperature are synthesized, and temperature distribution models of the reinforced concrete inner structure of the GTST are formulated using linear regression analysis. The developed monitoring-based temperature distribution models will serve as a reliable input for numerical prediction of the temperature-induced deformations and provide a robust basis to facilitate the design and construction of similar structures in consideration of thermal effects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.195-202
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• 2007

The normalized difference in incident solar energy between a target surface and a level surface (overheating index, OHI) is useful in eliminating estimation error of site-specific maximum temperature in complex terrain. Due to the complexity in its calculation, however, an empirical proxy variable called northern exposure index (NEI) which combines slope and aspect has been used to estimate OHI based on empirical relationships between the two. An experiment with real-world landscape and temperature data was carried out to evaluate performance of the NEI - derived OHI (N-OHI) in reduction of spatial interpolation error for daily maximum temperature compared with that by the original OHI. We collected daily maximum temperature data from 7 sites in a mountainous watershed with a $149 km^2$ area and a 795m elevation range ($651{\sim}1,445m$) in Pyongchang, Kangwon province. Northern exposure index was calculated for the entire 166,050 grid cells constituting the watershed based on a 30-m digital elevation model. Daily OHI was calculated for the same watershed ana regressed to the variation of NEI. The regression equations were used to estimate N-OHI for 15th of each month. Deviations in daily maximum temperature at 7 sites from those measured at the nearby synoptic station were calculated from June 2006 to February 2007 and regressed to the N-OHI. The same procedure was repeated with the original OHI values. The ratio sum of square errors contributable by the N-OHI were 0.46 (winter), 0.24 (fall), and 0.01 (summer), while those by the original OHI were 0.52, 0.37 and 0.15, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.171-183
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• 2005

In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.