Synergetic Retrieval of Aerosol Optical Depth Based on Geostationary Satellites MSG1 and MSG3
Abstract
Aerosol optical depth (AOD) is an important parameter in many fields such as climate change, quantitative remote sensing and atmospheric environmental monitoring. However, aerosol distribution has a strong spatio-temporal difference due to the short life cycle of aerosols and the spatial variability of aerosol emissions. Therefore, it is very important to rapidly monitor the aerosol over a wide range. Retrieval of AOD using polar orbit satellite data is the current mainstream approach, but the time resolution of polar-orbiting satellites is very low, and it is impossible to truly realize the effective monitoring of the large range of AOD. Compared with polar-orbiting satellites, geostationary satellites can effectively solve this problem. The data used in this study are obtained by two geostationary satellites, MSG1 (41.5 degrees East) and MSG3 (0 degree). The instrument of MSG generates images of the Earth in 12 different spectral channels (HRV, VIS 0.6, VIS 0.8, NIR 1.6, IR 3.9, IR 6.2, IR 7.3, IR 8.7, IR 9.7, IR 10.8, IR 12.0 and IR 13.4) with a repeat cycle of 15minutes. In this study, we use two visible bands (VIS0.6 and VIS0.8) and one near-infrared band (NIR 1.6) for AOD retrieval. At present, researchers have developed a variety of AOD retrieval algorithms for single MSG satellite, but most algorithms can only generate daily or hourly AOD data sets (which cannot effectively reflect the real-time changes of AOD), or Multiple consecutive cloudless observations are required (reducing the coverage of AOD products). In order to solve the shortcomings of existing algorithms, we proposed a synergetic algorithm that can retrieve AOD with a time resolution of 15 minutes using MSG1 and MSG3 data, which can accurately reflect the real-time changes of AOD. In addition, since the observations of MSG1 and MSG3 are synchronized, the synergetic algorithm can retrieve the AOD using a cloudless observation data (There is no need for continuous cloudless observation).Thus the algorithm proposed in this study will be able to further expand the coverage of AOD products.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A31G2906X
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0319 Cloud optics;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0321 Cloud/radiation interaction;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0360 Radiation: transmission and scattering;
- ATMOSPHERIC COMPOSITION AND STRUCTURE