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Numerical prediction of major atmospheric pollutants over the Yangtze River Delta region driven by CMA-GFS
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Guang-qiang ZHOU*, Jian-ming XU, Chang-qin YIN, Zhuo-cheng MAO, Zhong-qi YU, Yuan-hao QU
China Environmental Science | 2025, 45(7) : 3593 - 3603
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China Environmental Science | 2025, 45(7): 3593-3603
• Ozone Pollution Control •
Numerical prediction of major atmospheric pollutants over the Yangtze River Delta region driven by CMA-GFS
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Guang-qiang ZHOU*, Jian-ming XU, Chang-qin YIN, Zhuo-cheng MAO, Zhong-qi YU, Yuan-hao QU
Affiliations
  • Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030, China
Published: 2025-07-20
Outline
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To enhance the independence and controllability of regional atmospheric environment numerical prediction and its capability to support air quality forecast and air pollution warning, a CMA-GFS driving numerical prediction system (RAEMS-CMA) was established and operationally implemented. This system was based on the NCEP-GFS driving Regional Atmospheric Environmental Modeling System for eastern China (RAEMS-NCEP). The forecast effects evaluation on the major air pollutants over the YRD region from July 4th, 2023, to July 3rd, 2024, was executed. Evaluation results showed that RAEMS-CMA had good performance in forecasting the major air pollutants, e.g. correlation coefficients were generally over 0.7 and root mean square errors were 30%~70% of corresponding observation means. The performance was consistent in different forecast lengths of 24h ~ 96h. Further analysis indicated that the performance differs from air pollutants, with better skills in forecasting PM2.5 and O3. The prediction of PM10 was underestimated, while the others were overestimated. It also showed better forecast capability over the north region than over the south. The intercomparison indicated that RAEMS-CMA had slightly superior performance to that of RAEMS-EC (which was driven by ECMWF) and accordant to RAEMS-NCEP, while their differences were usually less than 5%. These results proved the applicability of CMA-GFS in numerical air quality prediction over the YRD region. At the same time, the divergent performance in pollutants and regions suggests further efforts on technological improvements and application approaches to numerical air quality prediction.

CMA-GFS  /  numerical prediction  /  air quality  /  atmospheric pollution  /  WRF-Chem
周广强, 许建明, 殷长秦, 毛卓成, 余钟奇, 瞿元昊. CMA-GFS驱动长三角主要大气污染物数值预报. 中国环境科学, 2025 , 45 (7) : 3593 -3603 .
Guang-qiang ZHOU, Jian-ming XU, Chang-qin YIN, Zhuo-cheng MAO, Zhong-qi YU, Yuan-hao QU. Numerical prediction of major atmospheric pollutants over the Yangtze River Delta region driven by CMA-GFS[J]. China Environmental Science, 2025 , 45 (7) : 3593 -3603 .
Year 2025 volume 45 Issue 7
68
15
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  • Receive Date:2024-12-23
  • Online Date:2026-10-08
  • Published:2025-07-20
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  • Received:2024-12-23
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    Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030, China
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表12种不同金属材料的力学参数
科
Family
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Number of
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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