Impact of Fengyun-4A Atmospheric Motion Vector Data Assimilation on PM<sub>2.5</sub> Simulation
PM<sub>2.5</sub> pollution poses significant risks to human health and the environment, underscoring the importance of accurate PM<sub>2.5</sub> simulation. This study simulated a representative PM<sub>2.5</sub> pollution event using the Weather Research and Forec...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/11/1952 |
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| Summary: | PM<sub>2.5</sub> pollution poses significant risks to human health and the environment, underscoring the importance of accurate PM<sub>2.5</sub> simulation. This study simulated a representative PM<sub>2.5</sub> pollution event using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem), incorporating the assimilation of infrared atmospheric motion vector (AMV) data from the Fengyun-4A (FY-4A) satellite. A comprehensive analysis was conducted to examine the meteorological characteristics of the event and their influence on PM<sub>2.5</sub> concentration simulations. The results demonstrate that the assimilation of FY-4A infrared AMV data significantly enhanced the simulation performance of meteorological variables, particularly improving the wind field and capturing local and small-scale wind variations. Moreover, PM<sub>2.5</sub> concentrations simulated with AMV assimilation showed improved spatial and temporal agreement with ground-based observations, reducing the root mean square error (<i>RMSE</i>) by 8.2% and the mean bias (<i>MB</i>) by 15.2 µg/m<sup>3</sup> relative to the control (CTL) experiment. In addition to regional improvements, the assimilation notably enhanced PM<sub>2.5</sub> simulation accuracy in severely polluted cities, such as Tangshan and Tianjin. Mechanistic analysis revealed that low wind speeds and weak atmospheric divergence restricted pollutant dispersion, resulting in higher near-surface concentrations. This was exacerbated by cooler nighttime temperatures and a lower planetary boundary layer height (PBLH). These findings underscore the utility of assimilating satellite-derived wind products to enhance regional air quality modeling and forecasting accuracy. This study highlights the potential of FY-4A infrared AMV data in improving regional pollution simulations, offering scientific support for the application of next-generation Chinese geostationary satellite data in numerical air quality forecasting. |
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| ISSN: | 2072-4292 |