• Title/Summary/Keyword: 대기모델

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Attenuation of the Atmospheric Aerosol Transmissivity due to Air Pollution (대기오염에 의한 대기투과도 감쇠에 대한 연구)

  • Kim, Yoo-Keun;Lee, Hwa-Woon;Lee, Yong-Seob
    • Journal of Korean Society for Atmospheric Environment
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    • v.11 no.E
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    • pp.23-29
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    • 1995

  • Relationship between atmospheric aerosol transmissivity and air pollution was analyzed using observed data in a large industrial city, Pusan, Korea. The atmospheric aerosol transmissivity predicted by method of present study in Pusan was assessed by the method of Yamamoto et al.(1968) in order to set up an empirical model to predict the transmissivity using the various meteorological parameters and air pollution. As a result, good correlation between these tow method re observed. Thus, it is possible to conclude that the parameterization of air pollution suggested by this study is another method to give reliable estimate of atmospheric aerosol transmissivity and direct solar irradiance in Pusan.

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A Study on Particulate Matter Forecasting Improvement by using Asian Dust Emissions in East Asia (황사배출량을 적용한 동아시아 미세먼지 예보 개선 연구)

  • Choi, Daeryun;Yun, Huiyoung;Chang, Limseok;Lee, Jaebum;Lee, Younghee;Myoung, Jisu;Kim, Taehee;Koo, Younseo
    • Journal of the Korean Society of Urban Environment
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    • v.18 no.4
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    • pp.531-546
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    • 2018

  • Air quality forecasting system with Asian dust emissions was developed in East Asia, and $PM_{10}$ forecasting performance of chemical transport model with Asian dust emissions was validated and evaluated. The chemical transport model (CTM) with Asian dust emission was found to supplement $PM_{10}$ concentrations that had been under-estimated in China regions and improved statistics for performance of CTM, although the model were overestimated during some periods in China. In Korea, the prediction model adequately simulated inflow of Asian dust events on February 22~24 and March 16~17, but the model is found to be overestimated during no Asian dust event periods on April. However, the model supplemented $PM_{10}$ concentrations, which was underestimated in most regions in Korea and the statistics for performance of the models were improved. The $PM_{10}$ forecasting performance of air quality forecasting model with Asian dust emissions tends to improve POD (Probability of Detection) compared to basic model without Asian dust emissions, but A (Accuracy) has shown similar or decreased, and FAR (False Alarms) have increased during 2017.Therefore, the developed air quality forecasting model with Asian dust emission was not proposed as a representative $PM_{10}$ forecast model in South Korea.

  • https://doi.org/10.33768/ksue.2018.18.4.531 인용 KSCI

Augmented Multiple Regression Algorithm for Accurate Estimation of Localized Solar Irradiance (국지적 일사량 산출 정확도 향상을 위한 다중회귀 증강 알고리즘)

  • Choi, Ji Nyeong;Lee, Sanghee;Ahn, Ki-Beom;Kim, Sug-Whan;Kim, Jinho
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1435-1447
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    • 2020

  • The seasonal variations in weather parameters can significantly affect the atmospheric transmission characteristics. Herein, we propose a novel augmented multiple regression algorithm for the accurate estimation of atmospheric transmittance and solar irradiance over highly localized areas. The algorithm employs 1) adaptive atmospheric model selection using measured meteorological data and 2) multiple linear regression computation augmented with the conventional application of MODerate resolution atmospheric TRANsmission (MODTRAN). In this study, the proposed algorithm was employed to estimate the solar irradiance over Taean coastal area using the 2018 clear days' meteorological data of the area, and the results were compared with the measurement data. The difference between the measured and computed solar irradiance significantly improved from 89.27 ± 48.08σ W/㎡ (with standard MODTRAN) to 21.35 ± 16.54σ W/㎡ (with augmented multiple regression algorithm). The novel method proposed herein can be a useful tool for the accurate estimation of solar irradiance and atmospheric transmission characteristics of highly localized areas with various weather conditions; it can also be used to correct remotely sensed atmospheric data of such areas.

  • https://doi.org/10.7780/kjrs.2020.36.6.1.12 인용 PDF KSCI HTML