GOCI와 AHI 자료를 활용한 에어로졸 광학두께 합성장 산출 연구 = Fusion of Aerosol Optical Depth from the GOCI and the AHI Observations

국문 초록 (Abstract)

본 연구에서는 COMS (Communication, Oceanography and Meteorology Satellite) 위성의GOCI (Geostationary Ocean Color Imager) 센서와 Himawari-8 위성의 AHI (Advanced Himawari Imager) 센서에서 산출되는 에어로졸 광학두께 (Aerosol Optical Depth; AOD)를 활용하여 단일화된 AOD 합성장을 생산하였다. 위성 간의 공간해상도와 위치좌표계가 다르기 때문에 이를 맞춰주는 전처리 작업을 선행하였다. 이후 지상관측 기반인 AERONET (AErosol RObotic NETwork)의 레벨 1.5 AOD 자료를 사용하여 각 위성과 AERONET과의 상관관계 분석 및 추세를 보간하여 기존 위성 AOD 보다 정확한 위성 AOD 자료를 생산하였다. 이후 합성과정을 진행하며 최종적으로 시공간적으로 더 완벽하고 정확한 AOD 합성장을 생산하였다. 생산된 AOD 합성장의 제곱근 평균 오차(Root Mean Square Error; RMSE)는 0.13, 평균 편향(mean bias)는 0.05로, 기존의 GOCI AOD (RMSE: 0.15, Mean bias: 0.11)와 AHI AOD (RMSE: 0.15, Mean bias: 0.05) 보다 나은 성능을 보였다. 또한 합성된 AOD는 단일위성에서 구름으로 인하여 관측되지 못한 지역에서 시공간적으로 보다 완벽하게 생산되었음을 확인하였다.

다국어 초록 (Multilingual Abstract)

In this study, fused Aerosol Optical Depth (AOD) data were produced using AOD products from the Geostationary Ocean Color Imager (GOCI) onboard Communication, Oceanography and Meteorology Satellite (COMS) satellite and the Advanced Himawari Imager (AHI) onboard Himawari-8. Since the spatial resolution and the coordinate system between the satellite sensors are different, a preprocessing was first preceded. After that, using the level 1.5 AOD dataset of AErosol RObotic NETwork (AERONET), which is ground-based observation, correlations and trends between each satellite AOD and AERONET AOD were utilized to produce more accurate satellite AOD data than the original satellite AODs. The fused AOD were found to be more accurate than the original satellite AODs. Root Mean Square Error (RMSE) and mean bias of the fused AODs were calculated to be 0.13 and 0.05, respectively. We also compared errors of the fused AODs against those of the original GOCI AOD (RMSE: 0.15, mean bias: 0.11) and the original AHI AOD (RMSE: 0.15, mean bias: 0.05). It was confirmed that the fused AODs have better spatial coverage than the original AODs in areas where there are no observations due to the presence of cloud from a single satellite.

참고문헌 (Reference)

1 Eck, T. F., "Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols" 104 (104): 31333-31349, 1999

2 Gupta, P., "Validation of MODIS 3 km land aerosol optical depth from NASA’s EOS Terra and Aqua missions" 11 : 3145-3159, 2018

3 Sayer, A. M., "Validation and uncertainty estimates for MODIS Collection 6"Deep Blue"aerosol data" 118 (118): 7864-7872, 2013

4 Twomey, S., "The influence of pollution on the shortwave albedo of clouds" 34 (34): 1149-1152, 1977

5 Levy, R., "The Collection 6 MODIS aerosol products over land and ocean" 6 : 2989-3034, 2013

6 Jinnagara Puttaswamy, S., "Statistical data fusion of multi-sensor AOD over the continental United States" 29 (29): 48-64, 2014

7 Tang, Q., "Spatiotemporal fusion of multiple-satellite aerosol optical depth(AOD)products using Bayesian maximum entropy method" 121 (121): 4034-4048, 2016

8 Kim, J., "Retrieving aerosol optical depth using visible and mid-IR channels from geostationary satellite MTSAT1R" 29 (29): 6181-6192, 2008

9 윤종민, "Retrieval of Aerosol Optical Depth over East Asia from a Geostationary Satellite, MTSAT-1R" 한국기상학회 43 (43): 133-142, 2007

10 Lau, K. M., "Observational relationships between aerosol and Asian monsoon rainfall, and circulation" 33 (33): L21810-, 2006

11 Jayroe Jr, R.R, "Nearest neighbor, bilinear interpolation and bicubic interpolation geographic correction effects on LANDSAT imagery"

12 Christakos, G., "Modern Spatiotemporal Geostatistics" Oxford Univ. Press 2000

13 Griggs, M., "Measurements of atmospheric aerosol optical thickness over water using ERTS-1 data" 25 : 622-626, 1975

14 Cox, C., "Measurement of the roughness of the sea surface from photographs of the Sun’s glitter" 44 (44): 838-850, 1954

15 Gupta, P., "MODIS aerosol optical depth observations over urban areas in Pakistan : quantity and quality of the data for air quality monitoring" 4 (4): 43-52, 2013

16 Kalashnikova, O. V., "MISR Dark Water aerosol retrievals : operational algorithm sensitivity to particle nonsphericity" 6 (6): 2131-2154, 2013

17 Wang, Y., "Large-scale MODIS AOD products recovery : Spatial-temporal hybrid fusion considering aerosol variation mitigation" 157 : 1-12, 2019

18 Lim, H., "Integration of GOCI and AHI Yonsei Aerosol Optical Depth Products During the 2016 KORUS-AQ and 2018 EMeRGe Campaigns" 14 : 4575-4592, 2020

19 Wang, J., "Geostationary satellite retrievals of aerosol optical thickness during ACE-Asia" 108 (108): 8657-, 2003

20 Choi, M., "GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia" 11 : 385-408, 2018

21 Hsu, N. C., "Enhanced Deep Blue aerosol retrieval algorithm : The second generation" 118 (118): 9296-9315, 2013

22 Garay, M. J., "Development and assessment of a higherspatialresolution(4. 4 km)MISR aerosol optical depth product using AERONET-DRAGON data" 17 (17): 5095-5106, 2017

23 Hsu, N. C., "Deep blue retrievals of Asian aerosol properties during ACE-Asia" 44 (44): 3180-3195, 2006

24 Han, D., "Comparison of commonly used image interpolation methods" 1556-1559, 2013

25 Prasad, A. K., "Comparison of MISR-MODIS aerosol optical depth over the Indo-Gangetic basin during the winter and summer seasons(2000-2005)" 107 (107): 109-119, 2007

26 Smirnov, A., "Cloud-Screening and Quality Control Algorithms for the AERONET Database" 73 (73): 337-349, 2000

27 Tyagi, B., "Changing air pollution scenario during COVID-19 : Redefining the hotspot regions over India" 271 : 116354-, 2021

28 Zhang, H., "An enhanced VIIRS aerosol optical thickness(AOT)retrieval algorithm over land using a global surface reflectance ratio database" 121 (121): 10717-10738, 2016

29 Kaskaoutis, D. G., "Aerosol climatology : dependence of the Angstrom exponent on wavelength over four AERONET sites" 7 (7): 7347-7397, 2007

30 Holben, B. N., "AERONET–A federated instrument network and data archive for aerosol characterization" 66 (66): 1-16, 1998