Predicting Air Quality: Current Status and Future Directions

Predicting Air Quality: Current Status and Future Directions
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预测空气质量:现状和未来方向

DOI:
10.1007/978-1-4020-8453-9_53
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发表时间:
2008
期刊:
--
影响因子:
--
通讯作者:
Youhua Tang
Youhua Tang
中科院分区:
--
文献类型:
--
作者:
G. Carmichael;Adrian Sandu;T. Chai;D. Daescu;E. Constantinescu;Youhua Tang

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空气质量预测在我们的环境管理中起着重要的作用。随着更多的大气化学观测资料的出现,化学数据同化预计将在空气质量预报中发挥重要作用。本文讨论了空气质量预报的现状,并通过预报与观测的比较加以说明。未来的发展方向也进行了讨论,重点是数据同化。四维变分法(4D-Var)和集合卡尔曼滤波(EnKF)方法的应用进行了介绍和讨论。
Air quality prediction plays an important role in the management of our environment. As more atmospheric chemical observations become available chemical data assimilation is expected to play an essential role in air quality forecasting. In this paper the current status of air quality forecasting is discussed and illustrated by comparison of predictions with observations. The future directions are also discussed, with an emphasis on data assimilation. Applications of the four dimensional variational method (4D-Var) and the ensemble Kalman filter (EnKF) approach are presented and discussed.
DOI: 10.1029/2002jd003117
发表时间: 2003-11-11
影响因子: 4.4
作者:
Carmichael, GR;Tang, Y;Heikes, B
通讯作者: Heikes, B
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