Aerosol is one of the important geophysical parameters that determine the earth’s radiation budget, energy balance and hydrological cycle. The “Deep Blue” Moderate Resolution Imaging Spectro-radiometer (MODIS) Aero...Aerosol is one of the important geophysical parameters that determine the earth’s radiation budget, energy balance and hydrological cycle. The “Deep Blue” Moderate Resolution Imaging Spectro-radiometer (MODIS) Aerosol Optical Depth (AOD) retrieval algorithm was designed to complement existing “Dark Target” Ocean and Land algorithms to be able to retrieve AOD over bright land surface. Using level 2 AOD data from five Aerosol Robotic Network (AERONET) stations over the study location of North Africa (0°S - 40°N, 30°W - 60°E), comparative accuracy assessments are made for combined MODIS AOD aboard Terra and Aqua satellites and US Navy Aerosol Analysis and Prediction System (NAAPS) forecast AOD data. The aerosol transport and vertical mixing over the region are investigated at different altitudes up to 3000 m above ground level using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT). The MODIS validation result shows highest correlation in the Sub-Sahel (0.811) followed by Sahel (0.726) and then Sahara region (0.662). Furthermore, the combined retrieval algorithm of Terra and Aqua MODIS shows statistically significant discrepancies from AERONET AOD values in term of mean, t-test value, index of agreement and fractional error. The comparison of NAAPS predicted soil dust to AERONET AOD fared best in December to February (DJF) season for the Sahel region and June to August (JJA) season for the Sahara when the dust emission and transport are at the peak. However, median ratios of NAAPS to AERONET AOD indicated bias in some island sites in the Atlantic Ocean which may be due to the presence of sea salt over the site. The analysis carried out in this study reveals that both MODIS retrieval algorithm and NAAPS model could be improved by incorporating some local aerosol sources from the study area.展开更多
Aerosol optical depth （AOD） is a common indicator applied in monitoring aerosols in the atmosphere. The hilly landscape and rapid economic growth of the megacity Chongqing have facilitated increased aerosol concentr...Aerosol optical depth （AOD） is a common indicator applied in monitoring aerosols in the atmosphere. The hilly landscape and rapid economic growth of the megacity Chongqing have facilitated increased aerosol concentration, and it is meaningful to accurately retrieve AOD over Chongqing. The HJ-1A/B satellite of China carries a sensor/camera called the Charge Coupled Device （CCD）, the spatial resolution of which meets the requirement for re- trieving high resolution AOD. In this paper, analysis of the AOD retrievals from different methods using the H J-1 satellite data revealed the most suitable algorithm. Through comparison with the AOD product of Moderate Resolu- tion Imaging Spectroradiometer （MODIS）, the AOD retrieval results using enhanced vegetation index （EVI） to estim- ate dark pixels showed the highest correlation. The continental aerosol model was used to build a lookup table that was able to facilitate a good AOD retrieval for both city and rural areas. Finally, the algorithm that combined dark pixels, buffer areas, and the deep blue algorithm was found to be most suitable for AOD retrieval. The AOD retrieval results based on the HJ-1 data were consistent with MODIS products, and our algorithm yields reasonable results in most cases. The results were also compared with ground-based PMl0 measurements synchronized with the overpass time of the HJ-1 satellite, and high correlation was found. The findings are relevant to other Chinese satellite data used for retrieving AOD on the same channels.展开更多
文摘Aerosol is one of the important geophysical parameters that determine the earth’s radiation budget, energy balance and hydrological cycle. The “Deep Blue” Moderate Resolution Imaging Spectro-radiometer (MODIS) Aerosol Optical Depth (AOD) retrieval algorithm was designed to complement existing “Dark Target” Ocean and Land algorithms to be able to retrieve AOD over bright land surface. Using level 2 AOD data from five Aerosol Robotic Network (AERONET) stations over the study location of North Africa (0°S - 40°N, 30°W - 60°E), comparative accuracy assessments are made for combined MODIS AOD aboard Terra and Aqua satellites and US Navy Aerosol Analysis and Prediction System (NAAPS) forecast AOD data. The aerosol transport and vertical mixing over the region are investigated at different altitudes up to 3000 m above ground level using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT). The MODIS validation result shows highest correlation in the Sub-Sahel (0.811) followed by Sahel (0.726) and then Sahara region (0.662). Furthermore, the combined retrieval algorithm of Terra and Aqua MODIS shows statistically significant discrepancies from AERONET AOD values in term of mean, t-test value, index of agreement and fractional error. The comparison of NAAPS predicted soil dust to AERONET AOD fared best in December to February (DJF) season for the Sahel region and June to August (JJA) season for the Sahara when the dust emission and transport are at the peak. However, median ratios of NAAPS to AERONET AOD indicated bias in some island sites in the Atlantic Ocean which may be due to the presence of sea salt over the site. The analysis carried out in this study reveals that both MODIS retrieval algorithm and NAAPS model could be improved by incorporating some local aerosol sources from the study area.
基金Supported by the National Natural Science Foundation of China(41631180 and 41471305)Sichuan Youth Science Fund(2015JQ0037)+2 种基金Chongqing Meteorological Bureau Open Fund(kfjj-201402)China Meteorological Administration Special Fund for Forecasting(CMAHX20160406)Sichuan Province Department of Education Innovation Team Fund(16TD0024)
文摘Aerosol optical depth （AOD） is a common indicator applied in monitoring aerosols in the atmosphere. The hilly landscape and rapid economic growth of the megacity Chongqing have facilitated increased aerosol concentration, and it is meaningful to accurately retrieve AOD over Chongqing. The HJ-1A/B satellite of China carries a sensor/camera called the Charge Coupled Device （CCD）, the spatial resolution of which meets the requirement for re- trieving high resolution AOD. In this paper, analysis of the AOD retrievals from different methods using the H J-1 satellite data revealed the most suitable algorithm. Through comparison with the AOD product of Moderate Resolu- tion Imaging Spectroradiometer （MODIS）, the AOD retrieval results using enhanced vegetation index （EVI） to estim- ate dark pixels showed the highest correlation. The continental aerosol model was used to build a lookup table that was able to facilitate a good AOD retrieval for both city and rural areas. Finally, the algorithm that combined dark pixels, buffer areas, and the deep blue algorithm was found to be most suitable for AOD retrieval. The AOD retrieval results based on the HJ-1 data were consistent with MODIS products, and our algorithm yields reasonable results in most cases. The results were also compared with ground-based PMl0 measurements synchronized with the overpass time of the HJ-1 satellite, and high correlation was found. The findings are relevant to other Chinese satellite data used for retrieving AOD on the same channels.
