• Atmosphere
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• v.17 no.1
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• pp.27-44
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• 2007

The purpose of this study is to investigate predictability of the seasonal simulation by the METRI (Meteorological Research Institute) AGCM (Atmospheric General Circulation Model), which is a long-term prediction model for the METRI 3-month prediction system. We examine the performance skill of climate simulation and predictability by the analysis of variance of the METRI AGCM, focusing on the precipitation, 850 hPa temperature, and 500 hPa geopotential height. According to the result, the METRI AGCM shows systematic errors with seasonal march, and represents large errors over the equatorial region, compared to the observation. Also, the response of the METRI AGCM by the variation of the sea surface temperature is obvious for the wintertime and springtime. However, the METRI AGCM does not show the significant ENSO-related signal in autumn. In case of prediction over the east Asian region, errors between the prediction results and the observation are not quite large with the lead-time. However, in the predictability assessment using the analysis of variance method, longer lead-time makes the prediction better, and the predictability becomes better in the springtime.

• Asian Journal of Atmospheric Environment
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• v.8 no.4
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• pp.192-201
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• 2014

A comprehensive profile of volatile organic compounds (VOCs) in public spaces is needed for interpreting indoor air measurements. Seasonal differences in profiles are critical for epidemiological study and risk assessment. The purposes of this study were to establish profiles for individual VOCs in 50 indoor public places in Korea and to determine seasonal variations in their concentrations. Air samples were taken during working hours. Seventy-two of the 91 targeted VOCs were identified using multiple standards. Six VOCs detected in all summer and winter samples were toluene, acetone, m,p-xylenes, ethylbenzene, benzene, and styrene. In summer, methyl ethyl ketone and 1-butanol were also found in all samples. In both seasons, the dominant indoor VOCs were toluene, m,p-xylenes, ethylbenzene, acetone, and isopropyl alcohol. Other chemicals associated with gasoline emissions were dominant in summer. Limonene was dominant only in winter due to the consumption of tangerines. The nine VOCs with the highest concentrations comprised 64.8% and 49.6% of the TVOC in summer and winter, respectively. Comparing two types of adsorbent tube, a single adsorbent tube with Tenax-TA had similar detection performance as a double adsorbent tube with Tenax and Carbotrap.

• Journal of the Korean Society of Food Science and Nutrition
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• v.24 no.4
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• pp.578-581
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• 1995

The seasonal variation of two flavonoid, quercitrin and afzelin, in the leaves of Cedrela sinensis A. Juss. from May until November was investigated by high performance liquid chromatography. Separation by reversed phase chromatography on ${\mu}-Bondapak\;C_{18}$ column was achieved by isocratic elution. The concentration of quercitrin was 5.81% (w/w) in May and high in July(8.89%, w/w), August(7.94%, w/w), and decreased from September to November. The content of another flavonoid, afzelin was 0.06% (w/w) in May and highest in June (0.12%, w/w), and was reduced from July.

• Atmosphere
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• v.32 no.2
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• pp.149-162
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• 2022

This study investigated the prediction skill of the Asian dust seasonal forecasting model (GloSea5-ADAM) on the Asian dust and meteorological variables related to the dust generation for the period of 1991~2016. Additionally, we evaluated the prediction skill of those variables depending on the combination of the initial dates in the sub-seasonal scale for the dust source region affecting South Korea. The Asian dust and meteorological variables (10 m wind speed, 1.5 m relative humidity, and 1.5 m air temperature) from GloSea5-ADAM were compared to that from Synoptic observation and European Centre for medium range weather forecasts reanalysis v5, respectively, based on Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC) as evaluation criteria. In general, the Asian dust and meteorological variables in the source region showed high ACC in the prediction scale within one month. For all variables, the use of the initial dates closest to the prediction month led to the best performances based on MBE, RMSE, and ACC, and the performances could be improved by adjusting the number of ensembles considering the combination of the initial date. ACC was as high as 0.4 in Spring when using the closest two initial dates. In particular, the GloSea5-ADAM shows the best performance of Asian dust generation with an ACC of 0.60 in the occurrence frequency of Asian dust in March when using the closest initial dates for initial conditions.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.917-923
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• 2012

We perform a comparison of time series models that include seasonal ARIMA, Fractional ARIMA, and Holt-Winters models; in addition, we also consider hourly and daily air passenger data. The results of the performance evaluation of the models show that the Holt-Winters methods outperforms other models in terms of MAPE.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.3
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• pp.156-163
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• 2013

Ground Source Heat Pump (GSHP) systems utilize geothermal energy as a thermal source or sink, for heating, cooling and domestic hot water. It is well known that GSHP is environmentally friendly, and saves energy dramatically. For this reason, many investigative researches have been conducted on commercial and governmental buildings. However, studies on residential GSHP are few, because of the small capacity and cost. In this study, we experimented with the characteristic performance of heating, cooling and seasonal performance factor for a residential GSHP system, which consisted of two 180 m deep u-tube ground heat exchangers, a heat pump and measurement instruments. The installed capacity of the heat pump was 5RT, and the conditioning area was $62.23m^2$. From the experimental results, the cooling COP of the heat pump was 4.13, and the system COP was 3.51, while the CSPF was 3.32. On the other hand, the heating COP of the heat pump was 3.87, and the system COP was 3.39, while the HSPF was 3.39. Also, in-situ cooling COP and capacity were 93.7% and 96.4% compared with the EWT certification data, respectively, and that of heating were 98.3% and 95.7%, respectively.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.133-144
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• 2016

This paper proposes a parsimonious periodic autoregressive (PAR) model. The proposed model performance is evaluated through an analysis of Korean unemployment rate series that is compared with existing models. We exploit some common features among each seasonality and confirm it by LR test for the parsimonious PAR model in order to impose a parsimonious structure on the PAR model. We observe that the PAR model tends to be superior to existing seasonal time series models in mid- and long-term forecasts. The proposed parsimonious model significantly improves forecasting performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.41-54
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• 2019

Although retailers deals with a large number of single-term inventory items, but few cases have been considered in the areas of practical decision making. However, recent moves to strengthen fair trade have created a real need for single-period inventory decision-making problems. This study addresses the problem of ordering quantity decisions that are expected to maximize profits using classical newsvendor models. The research target is data on seasonal and perishable products from retail. We also use data from retailers to actually apply the newsvendor model and calculate the results to compare performance. It also suggests solutions for estimating demand for products sold in order to apply newsvendor models that utilize actual demand ratio versus forecast demand. This study would like to examine the effectiveness of this research through data analysis and make some suggestions for applying it to reality.

• Atmosphere
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• v.34 no.2
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• pp.107-121
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• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.

• Journal of Fisheries and Marine Sciences Education
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• v.17 no.1
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• pp.132-143
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• 2005

In order to investigate the seasonal variation of watermass and fishery creatures in the adjacent sea of Naro Island, an oceanographic observation was carried out seasonally on the fishing grounds, and the sales performance data of the fisheries cooperative's joint market of Naro Island was examined by using a principal component analysis. The temperature and salinity ranged from 8.1 $^{\circ}C$ to 13.7 $^{\circ}C$ and from 33.1 psu to 34.3 psu in spring, from 14.5 $^{\circ}C$ to 24.2 $^{\circ}C$ and from 30.5 psu to 34.1 psu in summer, from 14.8 $^{\circ}C$ to 18.6 $^{\circ}C$ and from 30.1 psu to 34.0 psu in autumn, and from 4.3 $^{\circ}C$ to 10.1 $^{\circ}C$ and from 33.1 psu to 34.9 psu in winter, respectively. In winter and spring, the offshore water spread out to all sea areas of all water layers. In summer, the mixed waters covered the entire sea surface whereas the mixed water and offshore water covered the bottom. In autumn, the coastal water and mixed water appeared on the surface, but the mixed water was distributed widely on the bottom and the offshore water began to appear in the open sea. For two years from 2002 to 2003, 58 fishery creature species in total were sold in the fisheries cooperative's joint market of Naro Island. In general, the total of 50% fish were sold, and crustacea and mollusc by each 25%. Medium shrimp, whiparm octopus, blue crab, and octopus predominated. A number of species and biomass of fishery creatures were sold mostly in April and May, while they were sold the least in January and February. The seasonal sales results showed that mullet, angler, short necked clam, large shrimp, and webfoot octopus were sold mainly in spring, tonguefish, flathead, pomfret, glass eel, blue crab, whiparm octopus, and squid were sold mainly in summer, and octopus, medium shrimp, and spanish mackerel were sold mainly in autumn.