• Journal of Korean Society for Atmospheric Environment
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• 제14권6호
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• pp.563-576
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• 1998

To study the influences of the emission sources during lune 13∼15 1997 in Seoul, MESOPVFF II model has been used. The MESOPVFF II model includes terrain effects, chemical transformation and removal processes. Data of 20 surface meteorological stations and the upper air station on mid-west area in Korea were used as a DWM (Diagnostic Wind Model) input data. This model is likely to be applicable because the predicted SO2 concentration was well matched with measured 502 concentration in Seoul and Kyonggido. In generally air pollutants in Seoul have major influence on the other cities but the result of modeling appeared also air pollutants of the other cities influence on Seoul. Finally, in the case of calculating the air quality by diffusion model, the influences of air pollutants emitted in metropolitan area as well as the emission rate in modeling area should be considered.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 한국환경과학회 2003년도 International Symposium on Clean Environment
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• pp.69-72
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• 2003

The meteorological model, CALMET, and its plume dispersion model, CALPUFF, were used in order to simulate the dispersion of $SO_2$ emitted from Yatagan Power Plant and its effect on Yatagan district in the episodic event on December 2 and 3, 2000. It is found that south westerly and light winds and the nighttime surface inversion layers lead to accumulation of pollutants over Yatagan district. The results are compared with the measurements done by Local Environmental Authorities of Mu la. The simulation results indicate that the maximum ground level concentrations were found northeast from the source, which agrees with experimental measurement. On the other hand, the magnitude of results obtained with the model shows some differences compared with experimental measurements.

• Proceedings of the KIEE Conference
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.1128-1129
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• 2008

The detailed modeling method of photovoltaic (PV) module are useful to perform detailed analysis of PV array performance for changing meteorological conditions, verify actual rated power of PV system sizing and, determine the optimal design of PV system and components. This paper investigates a modeling approach of PV module performance in terms of irradiance and temperature changes and compared measured with simulated value of PV modules.

• Atmosphere
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• 제29권3호
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• pp.257-267
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• 2019

This study is to assess the applicability of the Extreme Forecast Index (EFI) algorithm of the ECMWF seasonal forecast system to the Global Seasonal Forecasting System version 5 (GloSea5), operational seasonal forecast system of the Korea Meteorological Administration (KMA). The EFI is based on the difference between Cumulative Distribution Function (CDF) curves of the model's climate data and the current ensemble forecast distribution, which is essential to diagnose the predictability in the extreme cases. To investigate its applicability, the experiment was conducted during the heat-wave cases (the year of 1994 and 2003) and compared GloSea5 hindcast data based EFI with anomaly data of ERA-Interim. The data also used to determine quantitative estimates of Probability Of Detection (POD), False Alarm Ratio (FAR), and spatial pattern correlation. The results showed that the area of ERA-Interim indicating above 4-degree temperature corresponded to the area of EFI 0.8 and above. POD showed high ratio (0.7 and 0.9, respectively), when ERA-Interim anomaly data were the highest (on Jul. 11, 1994 (> $5^{\circ}C$) and Aug. 8, 2003 (> $7^{\circ}C$), respectively). The spatial pattern showed a high correlation in the range of 0.5~0.9. However, the correlation decreased as the lead time increased. Furthermore, the case of Korea heat wave in 2018 was conducted using GloSea5 forecast data to validate EFI showed successful prediction for two to three weeks lead time. As a result, the EFI forecasts can be used to predict the probability that an extreme weather event of interest might occur. Overall, we expected these results to be available for extreme weather forecasting.

• Wind and Structures
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• 제26권3호
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• Journal of Environmental Science International
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• 제18권5호
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• pp.489-499
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• 2009

In an effort to examine the Regional Atmospheric Modeling System (RAMS ver. 4.3) to the initial meteorological input data, detailed observational data of NOAA satellite SST (Sea Surface Temperature) was employed. The NOAA satellite SST which is currently provided daily as a seven-day mean value with resolution of 0.1 $^{\circ}$ grid spacing was used instead of the climatologically derived monthly mean SST using in RAMS. In addition, the RAMS SST data must be changed new one because it was constructed in 1993. For more realistic initial meteorological fields, the NOAA satellite SST was incorporated into the RAMS-preprocess package named ISentropic Analysis package (ISAN). When the NOAA SST data was imposed to the initial condition of prognostic RAMS model, the resultant performance of near surface atmospheric fields was discussed and compared with that of default option of SST. We got the good results that the new SST data was made in a standard RAMS format and showed the detailed variation of SST. As the modeling grid became smaller, the SST differences of the NOAA SST run and the RAMS SST43 (default) run in diurnal variation were very minor but this research can apply to further study for the realistic SST situation and the development in predicting regional atmospheric field which imply the regional circulation due to differential surface heating between sea and land or climatological phenomenon.

• Journal of Environmental Impact Assessment
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• 제9권4호
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• pp.323-338
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• 2000

A Korean air dispersion modeling software, AirMaster, was developed on a basis of dispersion theories adopted in U.S. EPA's ISC3 (Industrial Source Complex - version 3) model to assess the air quality impact from the stacks. Key characteristics of AirMaster are as follows: 1) The building downwash effect can be easily simulated; 2) The screen, long term, and short term models can be run independently; 3) The input data to run the model such as meteorological and terrain data are supplied automatically from the databases in AirMaster; and 4) The modeling procedure is easy and simple under the GUI window environment. In order to validate AirMaster, comparisons with ISC3 model and Indianapolis tracer experiment were carried out. It was shown that AirMaster was identical to ISCST3 and ISCLT3 models in predicting the 1 hr to annual concentrations from the stack under various stack emission and meteorological conditions. The 1 hr concentrations predicted by AirMaster also showed a good agreement with the Indianapolis tracer measurements.

• Journal of Environmental Impact Assessment
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• 제16권6호
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• pp.381-391
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• 2007

The air quality modeling was carried out to assess the impact of air quality for large scale urban development. The site for the assessment is Multi-fuctional Administrative City which locates in Yeongi-gun, Chungcheongnam-do and estimated population in 2030 is 500,000. Two automatic weather monitoring stations were installed to monitor the meteorological variables for a year and upper air meteorological parameters were measured using radiosonde for 5 days with 4 hours interval in every season. The air quality of standard air pollutants were also measured for 5 days continuously in every season. The results of wind field analysis based on the site measurements and CALMET modeling showed that the valley and mountain winds were prevailed when the sypnotic wind was weak. It also showed that wind speed and directions were highly space-variable within the site basin. The variable wind characteristics implies that the Gaussian dispersion model such ISC3 and AERMOD are not appropriate and the unsteady-sate Lagrangian model such as CALPUFF is preferable. CALPUFF model was applied to assess air quality impact of new sources. The new sources were those for individual and group heating facilities as well as the traffic increases. The results showed that the estimated concentrations of CO and $SO_2$ pollutants by summing the impact concentration of new sources by the dispersion model and the ambient air concentrations by the site measurements were acceptable but those of PM-10 and $NO_2$ would violate ambient air quality standards at several locations due to high ambient air concentrations. It is recommended that the emission reductions near the site should be enforced to improve the ambient air quality.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제1권1호
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• pp.19-33
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• 1997

The high oxidants, which occur the daily maximum concentrations in the afternoon, are transported into the other region via long range transport mechanisms or trapped within the shallow mixing boundary layer and then removed physically (deposition, transport by mountain wind, etc.) and chemically (reaction with local sources). Therefore, modeling formation of photochemical oxidants requires a complex description of both chemical and meteorological processes. In this study, as a part of air quality studies, we reviewed various aspects of photochemical modeling on the basis of currently available literature. The result of the review shows that the model is based on a set of coupled continuity equations describing advection, diffusion, transport, deposition, chemistry, emission. Also photochemical oxidant models require a large amount of input data concerned with all aspects of the ozone life cycle. First, emission inventories of hydrocarbon and nitrogen oxides, with appropriate spatial and temporal resolution. Second, chemical and photochemical data allowing the quantitative description of the formation of ozone and other photochemically-generated secondary pollutants. Third, dry deposition mechanisms particularly for ozone, PAN and hydrogen peroxide to account for their removal by absorption on the ground, crops, natural vegetation, man-made and water surfaces. Finally, meteorological data describing the transport of primary pollutants away from their sources and of secondary pollutants towards the sensitive receptors where environmental damage may occur. In order to improve our present study, shortcomings and limitation of existing models are pointed out and verification process through observation is emphasized.

• Atmosphere
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• 제17권3호
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• pp.269-279
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• 2007

This study investigates the possibility of seasonal prediction for tropical cyclone activity in the western North Pacific by using a dynamical modeling approach. We use data from the SMIP/HFP (Seasonal Prediction Model Inter-comparison Project/Historical Forecast Project) experiment with the Korea Meteorological Administration's GDAPS (Global Data Assimilation and Prediction System) T106 model, focusing our analysis on model-generated tropical cyclones. It is found that the prediction depends primarily on the tropical cyclone (TC) detecting criteria. Additionally, a scaling factor and a different weighting to each ensemble member are found to be essential for the best predictions of summertime TC activity. This approach indeed shows a certain skill not only in the category forecast but in the standard verifications such as Brier score and relative operating characteristics (ROC).