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Chinese satellite offers advanced solutions for modelling small particles

The assimilation of aerosol optical depth (AOD) observational data from the Chinese satellite Fengyun-3A (FY-3A) substantially enhances the ability to model aerosol mass.

FY-3A is a second generation meteorological satellite. It is primarily used in meteorology and environmental monitoring in China. Using data gathered over the last 10 years and with the help of its ultraviolet and microwave spectral instruments, it greatly enhances the ability to predict and model aerosol mass.

Professor Min and his team, which includes a group of researchers from the Key Laboratory of Meteorological Disaster of the Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters of Nanjing University of Information Science and Technology, have published their research in Advances of Atmospheric Sciences.

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“Atmospheric aerosols have significant impacts on the climate and environment. In particular, increasingly severe particulate matter pollution events are threatening public health and ecosystems,” adds Prof. MIN.

“AOD can be used to test the calibration of satellite retrieval data, and is a key factor in determining the climatic effects of aerosol. However, there is a lack of data from ground-based observations of aerosols in East Asia,” he explains. “Thus, it is important to improve the accuracy of atmospheric chemical model predictions by combining satellite observations.”

The assimilation of satellite AOD observational data can significantly improve our ability to model and predict aerosol mass. The AOD distribution of the analysis field was closer to the observations of the satellite after the assimilation of satellite AOD data. These results suggest that FY-3A satellite aerosol products can be effectively applied in numerical models and dust weather analysis, stressed Prof. MIN.

“Future work may be needed to assimilate and analyze multispectral, multi-sensor aerosol-related data,” he further added.

For developing a comprehensive AOD data assimilation system, Professor Min and his team took the help of three-dimensional variation data assimilation in the Gridpoint Statistical Interpolation analysis.

In 2011, experiments were held for analyzing dust storm over East Asia.

Adopting the method of the Chinese National Meteorology Center to create a simulation of the background error covariance of aerosol variables, the characteristics of each aerosol variable can be seen pretty well.

Moreover, the analysis stemming from the experiment assimilates both FY-3A/MERSI (Medium-resolution Spectral Imager) AOD data and MODIS AOD data. It was closer to the ground-based values than the individual assimilation of the two datasets for the dust storm over East Asia. These results clearly demonstrate that the Chinese FY-3A satellite aerosol products can be applied to numerical models and dust weather analysis.

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