A Modeling Study on the Impacts of Dynamic Feedback to Aerosol Induced Radiative Effect

Woo-Seop Lee,Maeng-Ki Kim,Chong-Heum Kwak 한국기상학회 2009 Asia-Pacific Journal of Atmospheric Sciences Vol.45 No.3

The impacts of the aerosol direct radiative effect (DRE) and dynamic feedback effect (DFE) on aerosol-induced radiative effect (AIRE) at the surface are evaluated using the NASA finite-volume general circulation model (fvGCM). In this study, the DRE and DFE are estimahted by the contribution of aerosol optical thickness (AOT) and low cloud anomaly to the AIRE, respectively, using a simple linear regression analysis. Model results show that the DRE for dust and all aerosols taken together is larger than the DFE, while for BC aerosols the DFE explains the variability of the AIRE. These results suggest that the dynamic feedback effect may be one of the important factors in understanding the radiative effect of aerosols in the real world and also in determining the magnitude of surface cooling by aerosols.

Evaluation of the representativeness of ground-based visibility for analysing the spatial and temporal variability of aerosol optical thickness in China

Zhang, Z.Y.,Wong, M.S.,Lee, K.H. Pergamon Press ; Elsevier [distribution] 2016 Atmospheric environment Vol.147 No.-

<P>Although visibility is a widely-used indicator to quantify the aerosol loadings, only a few studies have been analyzed the representativeness of visibility in deriving Aerosol Optical Thickness (AOT). In this paper, ground-based visibility, MODerate-resolution Imaging Spectroradiometer (MODIS) and Multi angle Imaging SpectroRadiometer (MISR) monthly AOT products between July 2002 and December 2014 were analyzed in order to extract the dominant modes of variability using the Singular Value Decomposition (SVD) method. The method has significant merit to reduce data dimension and examine both spatial and temporal variability simultaneously. Results indicated that the satellite retrieved AOTs agreed well with ground-based visibility in terms of inter-annual variability. The correlation coefficients in the first deseasonalized mode are greater than 0.65 between visibility and satellite AOT products. However, large differences were observed in the seasonal variability between ground-based visibility and AOT. In addition, Aerosol vertical distribution from LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies (LIVAS) and cloud data from ground-based meteorological station were used to investigate the seasonal variability disagreement. The AOT values derived from LIVAS extinction coefficients between 0 and 500 m above surface have a stronger relationship with visibility, than total column AOT with visibility. It also indicates that seasonal variation of aerosol vertical distribution is the main cause of the disagreement between two parameters, and the uncertainties of satellite products also contribute to the disagreement. Results in this study highlighted that the visibility observation could only be used to depict the inter-annual AOT and more ancillary information could be used for studying seasonal AOT variation. (C) 2016 Elsevier Ltd. All rights reserved.</P>

Suomi-NPP위성 DNB관측을 이용한 우리나라 소도시에서의 야간 에어로졸 광학두께 추정

추교황 ( Gyo Hwang Choo ),정명재 ( Myeong Jae Jeong ) 대한원격탐사학회 2016 大韓遠隔探査學會誌 Vol.32 No.2

이 연구에서는 Suomi-National Polar Partnership(Suomi-NPP) 위성에 탑재된 Visible Infrared Imaging Radiometer Suite(VIIRS) 센서의 Day/Night Band(DNB)로부터 측정된 인공광원 복사휘도 정보를 이용하여 우리나라 소도시들에서 야간 에어로졸 광학두께를 추정하는 방법을 개발하였다. 개발된 알고리즘에서는 야간에 도시의 인공광원들로부터 방출되는 빛을 광원으로하여 Beer의 복사 감쇠법칙이 이용되었으며, VIIRS의 적외선 영역 M밴드 관측자료를 사용하여 구름화소를 제거함으로써 청천화소에 대하여 에어 로졸 광학두께를 산출하였다. 본 연구에서 산출된 야간 에어로졸 광학두께 결과는 주간 MODerate resolution Imaging Spectroradiometer(MODIS) 센서로부터 산출된 자료와 비교·검증하였다. 검증 결과, 도시에 따라 0.6~0.7이상의 상관계수와 0.14~0.18 범위의 제곱근-평균-제곱 차이(Root-Mean-Square Difference; RMSD)를 보였다. 추가적으로 야간 에어로졸 광학두께에 영향을 미치는 인자들에 대한 민감도 실험을 수행하여 개발된 알고리즘의 산출 오차의 범위를 추정하였다. 본 연구를 통하여 우리나라에서 야간에 DNB채널 관측자료를 이용하여 에어로졸 광학두께를 추정할 수 있는 가능성을 확인 하였으며, 개발된 알고리즘의 지속적인 개발 및 개선이 이루어진다면 향후 국내에서 기존에 부족했던 야간 에어로졸 정보의 산출에 기여할것으로 기대된다. 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 cloudfree 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.

월면 디지털 영상 분석을 이용한 대기 광학두께 산출

정명재 ( Myeong Jae Jeong ) 대한원격탐사학회 2013 大韓遠隔探査學會誌 Vol.29 No.5

이 연구에서는 상용 디지털 카메라를 이용하여 야간에 촬영된 월면 영상을 분석하여 야간의 대기 광학두께와 에어로솔 광학두께를 추정하였다. 기본적으로 랑리회귀법을 이용하였으며 구름이 없고 대기의 광학적 특성이 비교적 안정한 날에 관측을 수행하였다. 카메라의 적색(R), 녹색(G), 청색(B) 채널의 파장별 반응함수를 이용하여 월광관측에 대한 유효 중심파장 및 레일리 광학두께를 추정하였으며, 랑리 회귀법에서 유도된대기광학두께로부터 레일리 광학두께를 제하여 에어로솔 광학 두께를 산출하였다. 야간에는 독립적인 방법으로 산출된 검증자료나 다른 에어로솔 광학두께 자료가 거의 없으므로 월면 관측이 이루어지기 수 시간 전의 주간에 정밀한 태양분광광도계로 측정된 에어로솔 광학두께 자료와 MODIS 위성센서 관측으로부터 산출된 에어로솔 광학두께 자료를 본 연구에서 월면 관측을 통해 산출된 자료와 비교하였다. 비교 결과 R, G, B 채널에서 대략 0.1정도의 오차 범위에서 월면 영상분석을 통해 에어로솔 광학두께의 추정이 가능함을 알 수 있었다. 단, 대기 중의 에어로솔 입자들의 크기를 나타내는 모수인 앙스트롬지수(Angstrom Exponent)는 파장별 광학두께의 작은 오차에도 큰 오차를 가질 수 있기 때문에 에어로솔 광학두께의 오차에 비해 비교적 큰 오차를 보일수 있음이 나타났다. 그럼에도 불구하고, 야간의 에어로솔 광학두께 자료가 많지 않은 현실에서 저비용으로 월면 관측을 통하여 에어로솔 광학두께를 산출할 수 있는 가능성을 찾았다는 점에서 본 연구의 의의가 있으며 앞으로 보다 많은 관측과 분석을 통해 보다 향상된 야간 에어로솔 광학두께 추정이 가능할 것으로 보인다. Atmospheric optical thickness during nighttime was estimated in this study using analysis on the images of the moon taken from commercial digital camera. Basically the Langely Regression method was applied to the observations of the moon for the cloudless and optically stable sky conditions. The spectral response functions for the red(R), green(G), and blue(B) channels were employed to derive effective wavelength centers of each channel for the observations of the moon, and the correspondent Rayleigh optical thickness were also calculated. Aerosol optical thickness (AOT) was calculated by subtracting Rayleigh optical thickness from the atmospheric optical thickness derived from the Langley regression method. As there are only handful of nighttime AOT observations, the AOT from the moon observations was compared with the AOT from sun-photometers and the MODIS satellite sensor, which was taken several hours before the moon observations of this study. As a result, the values of AOT from moon observations agree with those from sun-photometers and MODIS within 0.1 for the R, G, B channels of the digital camera. On the other hand, Angstrom Exponent seems to be subject to larger errors due to its sensitiveness to the spectral errors of AOT. Nevertheless, the results of this study indicate that the method reported in this study is promising as it can provide nighttime AOT relatively easily with a low cost instrument like digital camera. More observations and analyses are warranted to attain improved nighttime AOT observations in the future.

SKYNET 관측 자료를 이용한 동아시아 영역에서의 MODIS 에어로솔 광학 두께 산출물 검증

장현성,송환진,전형욱,손병주,타카무라 타미오 한국지구과학회 2011 韓國地球科學會誌 Vol.32 No.1

Using six-year (2004-2009) SKYNET measurements, MODIS-derived AOTs were validated at five SKYNET sites (Seoul, Chiba, Etchujima, Fukuejima, and Hedomisaki), in addition to climatological analysis of MODIS-derived optical properties over the East Asian domain (20-50oN, 90-150oE). In so doing MODIS-SKYNET collocated AOT data were constructed if two measurements are taken within 25 km distance and within 30 minute time difference. From the comparison of two measurements, it is demonstrated that aerosol type insignificantly affects the accuracy of MODIS AOT. It is because the aerosol model combining predefined fine aerosol model and coarse aerosol model is used for the retrieval. However, positive bias between MODIS and SKYNET increases as fraction of the coarse aerosol model increases. In addition, MODIS AOT appears to be overestimated in case of lower aerosol loading while the overestimation tends to decrease with increased aerosol loading. Regression analysis between MODIS AOT and SKYNET AOT for 550 nm band yields 0.86, 0.16, and 0.61 of regression slope, intercept, and coefficient of determination,respectively. Those statistical results may draw a conclusion that MODIS AOTs over East Asia carry a reasonable accuracy compared to ground-based SKYNET measurements. 본 연구는 동아시아 영역에 속해있는 5개 SKYNET 관측소(서울, 지바, 엣추 지마, 후쿠에 지마, 헤도 미사키)에서 6년 간 관측한 AOT 자료를 활용하여 MODIS에서 산출된 AOT를 검증하였고, 아울러 에어로솔 기후장 분석도 함께 수행하였다. 검증연구를 위해 관측소 25 km 이내의 MODIS AOT를 평균하였고, MODIS 관측시각 30분 전후SKYNET AOT를 평균하여 시공간 일치 자료를 생산하였다. 시공간 일치 자료의 비교 결과 MODIS AOT의 정확도는에어로솔 종류에 크게 영향을 받지 않았으나, MODIS AOT 산출과정 중 거대 입자 모형의 사용비율이 높아질수록SKYNET AOT에 비해서 비교적 큰 값을 산출하는 경향을 보였다. 또한 AOT가 낮은 대기에서 MODIS AOT는 과대추정하는 경향을 보였고 그 경향성은 AOT가 높아질수록 줄어들었다. MODIS-SKYNET AOT간의 회귀분석 결과 기울기는 0.86, Y절편은 0.16으로 나타났고 결정계수(R2)는 0.61로 나타났다. 이러한 통계적 결과로 미루어 볼 때 동아시아영역에서 산출된 MODIS AOT는 지상 관측에 견줄 만큼 정확하다고 볼 수 있다.

First Retrieval of Data regarding Spatial Distribution of Asian Dust Aerosol from the Geostationary Ocean Color Imager

이권호,유주형,안재현,김영준 한국해양과학기술원 2012 Ocean science journal Vol.47 No.4

Aerosol optical thickness (AOT) was retrieved from the Geostationary Ocean Color Imager (GOCI) on board the Communication, Ocean, and Meteorological Satellite (COMS) for the first time. AOT values were retrieved over the ocean at a spatial scale of 0.5 × 0.5 km2 by using the look-up table (LUT)- based separation technique. The radiative transfer model (RTM)was used for different models of atmosphere–ocean environmental conditions, taking into account the realistic variability of scattering and absorption. Ocean surface properties affected by whitecaps and pigment content were also taken into account. The results show that the radiance observed by the GOCI amounts to only 5% of the radiation that penetrated the ocean and, consequently, 95% of the radiation is scattered in the atmosphere or reflected at the ocean surface in the visible wavelengths longer than 0.6 ìm. Within these wavelengths, radiance variations at the top of atmosphere (TOA) due to pigment variations are within 10%, while the radiance variation due to wind speed is considerably higher. For verification of GOCI-retrieved AOTs, comparison between GOCI and ground-based sunphotometer measurement at Gosan, Korea (126.10°E, 33.23°N)) showed good correlation (r = 0.99). The GOCI observations obtained by using the proposed technique showed promising results for the daily monitoring of atmospheric aerosol loading as well as being useful for environmental supervisory authorities.

머신러닝 클러스터링을 이용한 컬럼 관측에 따른 대기 에어로솔 특성 분석

이권호,이규태 한국대기환경학회 2020 한국대기환경학회지 Vol.36 No.5

In this study, we classify atmospheric aerosols according to column measurement and meteorology patterns using machine learning technique. The observation data is the aerosol optical thickness (AOT), angstrom exponent (AE), precipitable water vapor (PWV), and wind at Daegwallyeong (DGL) and Gangneung-Wonju National University (GWNU) from March to June 2016. As a result of time series analysis and correlation regression analysis for individual data, higher mean AOT of 0.063 (32.0%) and AE ~0.031 in Gangneung compared to Daegwanryeong were found. These results show that the size of aerosols at two locations is similar, but the load of the particles is higher in Gangneung. The unsupervised K-means clustering are used as machine learning techniques in order to classify aerosol distribution pattern in the study area. As a result of the machine learning, aerosol patterns were classified into five groups according to local atmospheric conditions. These results of this study will provide useful information for understanding the relationship between factors related to the current status and pattern analysis of aerosols based on atmospheric observation data.

Ground-based Measurements of the Aerosol Optical Thickness at Xiamen Sea and Satellite Remote SensingTest

Xi Liu,Xiu-qing Hu 한국기상학회 2011 한국기상학회 학술대회 논문집 Vol.2011 No.10-2

First Retrieval of Data regarding Spatial Distribution of Asian Dust Aerosol from the Geostationary Ocean Color Imager

Lee, Kwon Ho,Ryu, Joo Hyung,Ahn, Jae Hyun,Kim, Young Joon Korean Ocean Research & Development Institute and 2012 OCEAN SCIENCE JOURNAL Vol.47 No.4

Aerosol optical thickness (AOT) was retrieved from the Geostationary Ocean Color Imager (GOCI) on board the Communication, Ocean, and Meteorological Satellite (COMS) for the first time. AOT values were retrieved over the ocean at a spatial scale of <TEX>$0.5{\times}0.5km^2$</TEX> by using the look-up table (LUT)-based separation technique. The radiative transfer model (RTM) was used for different models of atmosphere-ocean environmental conditions, taking into account the realistic variability of scattering and absorption. Ocean surface properties affected by whitecaps and pigment content were also taken into account. The results show that the radiance observed by the GOCI amounts to only 5% of the radiation that penetrated the ocean and, consequently, 95% of the radiation is scattered in the atmosphere or reflected at the ocean surface in the visible wavelengths longer than 0.6 im. Within these wavelengths, radiance variations at the top of atmosphere (TOA) due to pigment variations are within 10%, while the radiance variation due to wind speed is considerably higher. For verification of GOCI-retrieved AOTs, comparison between GOCI and ground-based sunphotometer measurement at Gosan, Korea (<TEX>$126.10^{\circ}E$</TEX>, <TEX>$33.23^{\circ}N$</TEX>)) showed good correlation (r = 0.99). The GOCI observations obtained by using the proposed technique showed promising results for the daily monitoring of atmospheric aerosol loading as well as being useful for environmental supervisory authorities.

PM2.5농도 산출을 위한 경험적 다중선형 모델 분석

추교황,이규태,정명재 한국지구과학회 2017 한국지구과학회지 Vol.38 No.4

In this study, the empirical models were established to estimate the concentrations of surface-level PM2.5 over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), Ångström 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 M6 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 PM2.5 and the estimated PM2.5 concentrations using M6 model were correlations (R=0.62) and root square mean error (RMSE=10.70 μg m−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 PM2.5. Also, the result calculated for PM2.5 using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data. 본 연구에서는 서울지역의 지상 미세먼지(PM2.5) 농도를 산출하기 위하여 경험적인 모델들을 개발하였다. 연구에이용한 자료는 2012년 1월 1일부터 2013년 12월 31일까지이며 Terra와 Aqua위성의 MODIS센서에서 산출되는 에어로졸 광학두께, 옹스트롬 지수, 기상변수들과 행성경계층두께와 관련된 6개의 다중 선형 회귀모델들의 차이를 분석하였다. 그 결과 에어로졸 광학두께와 옹스트롬 지수, 상대습도, 풍속, 풍향, 행성경계층두께, 기온 자료를 입력 자료로 사용한M6모델이 가장 좋은 결과를 보였다. 통계적인 분석에 따르면 M6 모델을 사용하여 계산된 PM2.5와 관측된 PM2.5농도 사이의 결과는 상관계수(R=0.62)와 평균제곱근오차(RMSE=10.70 μg m−3)이다. 또한 산출된 계절별 지표면 PM2.5농도는여름철(R=0.38)과 겨울철(R=0.56)보다 봄(R=0.66)과 가을철(R=0.75)에 상대적으로 더 좋은 상관 관계를 보였다. 이러한결과는 에어로졸 광학두께의 계절별 관측 특성으로 인한 것으로써 다른 계절에 비하여 여름과 겨울철 에어로졸 광학두께 관측이 구름과 눈/얼음 표면에 의한 관측 제한과 오차를 가져온 것으로 분석되었다. 따라서 본 연구에서 사용한 경험적 다중선형회귀 모델은 위성에서 산출된 에어로졸 광학두께 자료가 지배적인 변수로 작용하며 PM2.5산출 결과들을향상시키기 위해서는 추가적인 기상 변수를 이용해야 할 것이다. 또한 경험적 다중선형회귀 모델을 이용하여 PM2.5를산출한 결과는 인공위성 자료로부터 대기환경 감시를 가능하게 하는 방법이 될 수 있어 유용할 것이다.