• Journal of Environmental Science International
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• v.29 no.1
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• pp.45-54
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• 2020

High-resolution meteorological simulations were conducted using a Weather Research and Forecasting (WRF) model with an Urban Canopy Model (UCM) in the Ulsan Metropolitan Region (UMR) where large-scale industrial facilities are located on the coast. We improved the land cover input data for the WRF-UCM by reclassifying the default urban category into four detailed areas (low and high-density residential areas, commercial areas, and industrial areas) using subdivided data (class 3) of the Environmental and Geographical Information System (EGIS). The urban area accounted for about 12% of the total UMR and the largest proportion (47.4%) was in the industrial area. Results from the WRF-UCM simulation in a summer episode with high temperatures showed that the modeled temperatures agreed greatly with the observations. Comparison with a standard WRF simulation (WRF-BASE) indicated that the temporal and spatial variations in surface air temperature in the UMR were properly captured. Specifically, the WRF-UCM reproduced daily maximum and nighttime variations in air temperature very well, indicating that our model can improve the accuracy of temperature simulation for a summer heatwave. However, the WRF-UCM somewhat overestimated wind speed in the UMR largely due to an increased air temperature gradient between land and sea.

• 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.

• Journal of Environmental Science International
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• v.26 no.12
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• pp.1399-1405
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• 2017

We compared the spatial distribution of several heat stress indices (the Wet-Bulb Globe Temperature(WBGT) index, Environmental Stress Index (ESI), and Modified Discomfort Index(MDI)) for the heat wave of June 6~August 26, 2016, in Daegu. We calculated the heat stress indices using data from the high density urban climate observation network in Daegu. The observation system was established in February. 2013. We used data from a total of 38 air temperature observation points (23 thermometers and 18 automatic weather stations). The values of the heat stress indices indicated that the danger level was very high from 0900-2000h in downtown Daegu. The daily maximum value of the WBGT was greater than or equal to $35^{\circ}C$. The differences in the heat stress indices from downtown and rural areas were higher in the daytime than at nighttime. The maximum difference was about 4 before and after 1400h, and the time variations of the heat stress indices corresponded well. Thus, we were able to confirm that the ESI and MDI can be substituted with the WBGT index.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.901-922
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• 2007

To see how the electricity demand for air-conditioning responds to weather condition and what kind of weather condition works better in forecasting maximum daily electricity demand, four different regression models, which are linear, exponential, power and S-curve, are adopted. The regression outcome turns out that the electricity demand for air-conditioning is inclined to rely on the exponential model. Another major discovery of this study is that the electricity demand for air-conditioning responds more sensitively to the weather condition year after year along with the higher non-air-conditioning electricity demand. In addition, it has also been found that the discomfort index explains the electricity demand for air-conditioning better than the highest temperature.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.2
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• pp.243-257
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• 2005

The effects of Traffic Control Program (TCP) on the ambient urban air quality of SO$_{2}$, NO$_{2}$, O$_{3}$, and PM$_{10}$ were evaluated in Seoul metropolitan area by using the lower atmospheric vertical stability index and daily mean wind speeds. The vertical stability index; temperature lapse rate between 1000 hPa and 850 hPa geopotential height fields, were used to identify daily vertical stability index during the 2002 World Cup period where traffic amount was reportedly reduced to half the number of vehicles. The indicated air quality levels of TCP days were then compared with those of the cases observed with analogous vertical stability during the recent 3 years from 2000 to 2002. The result indicates that the effect of TCP on the primary air pollutants are found to be approximately 39$\%$, 23$\%$ and 20$\%$ lower for SO$_{2}$, NO$_{2}$ and PM$_{10}$, respectively. The secondary air pollutant; ozone, showed relatively smaller decreasing rate (13$\%$) of daily mean concentrations (even increased during the night time). The comparison of daily maximum or peak concentrations reveals that the pronounced decreasing effects of TCP on the ambient air quality for both primary and secondary air pollutants, suggesting that TCP is one of the effective strategies to control peak or higher concentrations for most urban scale air pollutants in and around the Seoul metropolitan area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.17-28
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• 2007

This study was conducted to analyze the optimum heading period according to the recent climatic change for improvement of rice yield and grain quality in the Yeongnam area. We analyzed climatic elements including daily mean air temperature, daily range of air temperature, sunshine hours, and amount of precipitation from 1996 to 2005 in comparison with those of the 1971 to 2000 normal. Daily mean air temperature and amount of precipitation in the recent 10 years increased, but daily range of air temperature and sunshine hours decreased in comparison with the norm. Also, monthly mean air temperature was lowered remarkably in July and August. The monthly amount of precipitation largely increased in August and September. The daily range of air temperature and sunshine hours were greatly decreased from August to October, Possible cultivation periods for rice in the recent 10 years ranged from 171 days in Boughwa to 228 days in Busan and was expanded about $1{\sim}13$ days in comparison with the normal. Optimum heading date by local regions for the maximum climatic yield potential was estimated as July 31 at Bonghwa to September 7 at Busan, Masan, and Tongyeong in the recent 10 years. There was a wide difference in optimum heading date according to local legions of the Yeongnam area. Compared to the normal, optimum heading date in the recent 10 years was delayed about I~8 days in most local regions except Bonghwa, Mungyeong, and Yeongdeok. These results suggested that it is necessary to develop late maturity rice cultivars for producing high yield and quality rice grain due to the recent climatic change. Moreover, it is still more important to select the most suitable cultivation period appropriate to the changed climate of each local region in Yeongnam area.

• Journal of the Korean Wood Science and Technology
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• v.38 no.4
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• pp.349-358
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• 2010

This study was carried out to investigate the optimum condition for sap exudation of Acer mono Max. tree in a site of Mt. Jiri, Hamyang-gun, Korea. Amount of sap exudation, air temperature, relative air humidity, tree diameter at breast height (DBH) and sugar content in sap were monitored during the early springtime, and correlation analysis of several factors was carried out to explain tree-to-tree and date-to-date variations in sap exudation. The correlation, linearlyassociated between DBH and sap amount, was strengthened as daily amount of sap increased, but there was no significant tree-to-tree variation in time and period for sap exudation. When amount of sap exudation was above 10 liter/day, the mean air-temperature was averaged at $1.2{\pm}1.6^{\circ}C$, the minimum at $-4.3{\pm}1.5^{\circ}C$ and the maximum at $11.8{\pm}1.9^{\circ}C$. The maximum air temperature and mean air temperature were significant (p < 0.05) factors for amount of sap in correlation analysis to explain date-to-date variation in sap exudation. Sucrose content in sap was in the range of 1.5 and 1.7% during exudation days, but sharply reduced to 0.6% level at the end of exudation period.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.291-297
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• 2013

Automated weather stations were installed at 9 locations with, three different elevations, (i.e., 50m, 100m, and 300m a.s.l.) with different slope and aspect in a small watershed ($50km^2$ area). Air temperature at 1500 LST and solar radiation accumulated for 1100-1500 LST were collected from January to December 2012. Topography of the study area was defined by a $30{\times}30$ m digital elevation model (DEM) grid. Accumulated solar irradiance was calculated for each location with the spatially averaged slope and aspect of surrounding circles with 5, 10, 15, 20, 25, and 30 grid cell radii, respectively. The 1500 LST air temperature from clear sky conditions with zero cloud amount was regressed to the 1100-1500 LST solar irradiance at 9 locations. We found the highest coefficient of determination ($r^2$ = 0.544) at 25 grid cell radius and the temperature variation in this study was explained by Y = 0.8309X + 0.0438, where Y is 1500 LST temperature (in $^{\circ}C$) and X is 1100-1500 LST accumulated solar irradiance (in $MJ/m^2$).

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.