• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.607-615
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• 2017

The aerosol optical thickness data retrieved by Moderate Resolution Imaging Spectrometer (MODIS) of Terra & Aqua and Meteorological Imager (MI) of Communication Ocean and Meteorological Satellite (COMS) are analyzed and compared with the measurement data of Aerosol Robotic Network (AERONET) in Northeast Asia. As the result, the aerosol optical thickness retrieved by MODIS and MI were well agreed at ocean region but quite different at cloud edge and barren surface. The reason was that MODIS aerosol optical thickness was retrieved using the visible and infrared channels but MI was retrieved with the visible channel only. Consequentially, the thin cloud be misinterpreted as aerosol by MI and the difference between MODIS and MI aerosol optical thicknesses could be occurred with Normal Distribution Vegetation Index (NDVI) and land surface property. Therefore, the accuracies of clear/cloud region and surface reflectivity are required in order to improve the aerosol optical thickness algorithm by MI.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.400-401
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• 2000

황사는 대개 봄철 중국 대륙이 건조해지면서 중국 북부 사막 등의 흙먼지가 강한 상승기류를 타고 편서풍을 따라 우리 나라까지 날아오는 현상이다. 황사가 발생하면 시정이 떨어질 뿐 아니라 대기의 오염원으로 작용하여 질병을 유발시키기도 한다. 특히 황사로 인한 대기 중의 에어로졸 농도 증가는 지표에 도달하는 직달 일사량을 감소시켜 에어로졸의 광학적 두께에 영향을 준다. (중략)

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.366-375
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• 1998

Optical characteristics of the yellow sand and their influences on the ocean color remote sensing has been studied using ocean color sensor SeaWiFS measurements. Two cases of April 18 and April 25, 1998, representing yellow sand and background aerosol, are selected for emphasizing the impact of high aerosol concentration on the ocean color remote sensing. It was shown that NASA's standard atmospheric correction algorithm treats yellow sand area as either too high radiance or cloud area, in which ocean color information is not generated. Optical thickness of yellow sand arrived over the East Asian sea waters in April 18 indicates that there are two groups loaded with relatively homogeneous yellow sand, i.e.: heavy yellow sand area with optical thickness peak around 0.8 and mild area with about 0.4, which are consistent with ground observations. The movement of the yellow sand area obtained from surface weather maps and backward trajectory analysis manifest the notion that the weak yellow sand area was originated from the outer region of the dust storm. It is also noted that high optical thickness associated with the yellow sand is significantly different from what we may observe from background aerosol, which is about 0.2. These characteristics allow us to determine the yellow sand area with an aid of atmospheric correction parameter. Results indicate that the yellow sand area can be determined by applying the features revealed in scattergrams of atmospheric correction parameter and optical thickness.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.73-86
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• 2016

In this study, an algorithm to estimate Aerosol Optical Thickness (AOT) over small cities during nighttime has been developed by using the radiance from artificial light sources in small cities measured from Visible Infrared Imaging Radiometer Suite (VIIRS) sensor's Day/Night Band (DNB) aboard the Suomi-National Polar Partnership (Suomi-NPP) satellite. The algorithm is based on Beer's extinction law with the light sources from the artificial lights over small cities. AOT is retrieved for cloud-free pixels over individual cities, and cloud-screening was conducted by using the measurements from M-bands of VIIRS at infrared wavelengths. The retrieved nighttime AOT is compared with the aerosol products from MODerate resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites. As a result, the correlation coefficients over individual cities range from around 0.6 and 0.7 between the retrieved nighttime AOT and MODIS AOT with Root-Mean-Squared Difference (RMSD) ranged from 0.14 to 0.18. In addition, sensitivity tests were conducted for the factors affecting the nighttime AOT to estimate the range of uncertainty in the nighttime AOT retrievals. The results of this study indicate that it is promising to infer AOT using the DNB measaurements over small cities in Korea at night. After further development and refinement in the future, the developed retrieval algorithm is expected to produce nighttime aerosol information which is not operationally available over Korea.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.04a
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• pp.185-186
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• 2000

대기 중에 있는 에어로졸의 농도가 증가하면 직접·간접적으로 지구 복사 평형에 영향을 주어 기후 변화를 유도하게 된다 직접적 효과로는 에어로졸이 지구에 들어오는 태양빛을 산란 및 흡수에 의해 차단하여 지표에 도달하는 태양에너지를 감소시키게 된다. 간접적 효과로는 증가된 에어로졸의 일부가 구름 응결핵으로 작용하여 구름입자의 농도를 증가시키면 구름의 알베도 값이 증가되고 또한 구름의 수명에도 영향을 주어 구름의 량을 증가시키게 되고, 또한 구름의 수명에도 영향을 주어 구름의 량을 증가시키게 되고, 따라서 지구복사 뿐 아니라 물의 순환에도 영향을 미치게 된다. (중략)

• Korean Journal of Optics and Photonics
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• v.26 no.1
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• pp.9-16
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• 2015

We have developed ellipsometry lidar and measured aerosol and ice-cloud characteristics. To measure a full normalized backscattering phase matrix (NBSPM) composed of nine elements, we have designed an optical system with three kinds of transmission and three kinds of reception, composed of ${\lambda}/2$ waveplate, ${\lambda}/4$ waveplate and empty optic. To find systematic optical errors, we used clean day middle-altitude (4-6km) lidar signals for which the aerosol's concentration was small and its orientation chaotic. After calibrating our lidar system, we have calculated NBSPM elements scattered from an aerosol and from an ice cloud. In the case of an aerosol, we found that the off-diagonal values $m_{12},{\ldots},m_{34}$ of the NBSPM are smaller than those for a cirrus cloud. Also, the off-diagonal values of the NBSPM from a cirrus cloud depend on atmospheric conditions.

• Atmosphere
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• v.23 no.1
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• pp.85-92
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• 2013

We estimate atmospheric radiative heating effect of aerosols, based on AErosol RObotic NETwork (AERONET) and lidar observations and radiative transfer calculations. The column radiation model (CRM) is modified to ingest the AERONET measured variables (aerosol optical depth, single scattering albedo, and asymmetric parameter) and subsequently calculate the optical parameters at the 19 bands from the data obtained at four wavelengths. The aerosol radiative forcing at the surface and the top of the atmosphere, and atmospheric absorption on pollution (April 15, 2001) and dust (April 17~18, 2001) days are 3~4 times greater than those on clear-sky days (April 14 and 16, 2001). The atmospheric radiative heating rate (${\Delta}H$) and heating rate by aerosols (${\Delta}H_{aerosol}$) are estimated to be about $3\;K\;day^{-1}$ and $1{\sim}3\;K\;day^{-1}$ for pollution and dust aerosol layers. The sensitivity test showed that a 10% uncertainty in the single scattering albedo results in 30% uncertainties in aerosol radiative forcing at the surface and at the top of the atmosphere and 60% uncertainties in atmospheric forcing, thereby translated to about 35% uncertainties in ${\Delta}H$. This result suggests that atmospheric radiative heating is largely determined by the amount of light-absorbing aerosols.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.77-89
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• 2004

The spatial and temporal variations of aerosol optical depth (AOD) over Northeast Asia regions have special importance in the aerosol research for estimation of aerosol radiative forcing parameters and climate change. Aerosol optical and physical properties (AOD and ${\AA}$ngstrom parameter) have been investigated by using Moderate Resolution Imaging Spectroradiometer (MODIS) and Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) to estimate aerosol characteristics over the study region during 2001. Additionally, aerosol characteristics over the Korean peninsular during Aerosol Characteristic Experiment in Asia (ACE-Asia) Intensive Observation Period (IOP) have been investigated by using satellite observations. The results showed that the daily-observed aerosol data indicate seasonal variations with relatively higher aerosol loading in the spring and very low during the winter. The typical Asian dust case showed higher AOD (>0.7) with lower Angstrom exponent (<0.5) and higher AI (>0.5) that is mainly due to the composition of coarse particles in the springtime. Mean AOD for 2001 at 4 different places showed 0.65$\pm$0.37 at Beijing, 0.31$\pm$0.19 at Gosan, 0.54$\pm$0.26 at Seoul, and 0.38$\pm$0.19 at Kwangju, respectively. An interesting result was found in the present study that polluted aerosol events with small size dominated-aerosol loading around the Korean peninsular are sometimes observed. The origin of these polluted aerosols was thought to East China. Aerosol distribution from satellite images and trajectory results shows the proof of aerosol transport. Therefore, aerosol monitoring using satellite data is very useful.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.339-340
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• 2000

에어로졸의 장거리 이동에 대한 연구는 황사의 수송과 기상특성, 황사의 연직 구조 분석, 황사의 성분 및 변질 등 황사 에어로졸의 화학적ㆍ물리적ㆍ기상학적 분석을 통하여 시행되어 왔다. 최근에 들어 인공위성을 이용한 대기의 광학적 두께(aerosol optical depth) 및 황사 에어로졸의 장거리 이동에 대한 위성관측은 황사현상에 대한 발현 예보를 가능하게 하였다. 광주과학기술원 환경모니터링 신기술연구센터는 기상청의 예보를 토대로 비정규적 황사 현상에 대한 에어로졸의 광ㆍ화학적 장거리 이동특성을 조사하기 위하여 예상 황사기간에 시정집중모니터링을 실시하였다. (중략)

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.