Three-dimensional variational data assimilation of ozone and fine particulate matter observations: some results using the Weather Research and Forecasting - Chemistry model and Grid-point Statistical Interpolation
Three-dimensional variational data assimilation of ozone and fine particulate matter observations: some results using the Weather Research and Forecasting - Chemistry model and Grid-point Statistical Interpolation
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DOI：
10.1002/qj.700
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发表时间：
2010-10-01
影响因子：
8.9
通讯作者：
Devenyi, D.
中科院分区：
文献类型：
--
作者：
Pagowski, M.;Grell, G. A.;Devenyi, D.
在实际的空气质量预报中，化学物质的初始浓度通常是利用前一天的预报获得的，很少或根本没有考虑到观测结果。在本文中，我们评估了臭氧和细气溶胶的地表测量同化在提高空气质量预报技能方面所起的作用。利用气象研究与预报化学模型和三维变分同化工具格点统计插值进行了同化实验。建模领域覆盖北美东北部地区。这些测量数据来自美国环境保护署的AIRNow网络，每小时提供一次。背景误差协方差统计量来源于2004年7月的预测。2006年8月和9月发布的预报及初始化后同化与不同化的比较如下：结果表明，在至少24小时的时间内，臭氧和细气溶胶浓度的预报受益于标准验证分数的同化。然而，由于同化的结果，误差的显著减少伴随着早期预报小时内模式误差的快速增长。2010年由John Wiley & Sons出版。
In operational air-quality forecasting, initial concentrations of chemical species are often obtained using previous-day forecasts with limited or no account for the observations. In this article we assess the role that assimilation of surface measurements of ozone and fine aerosols can play in improving the skill of air-quality forecasts. An assimilation experiment is performed using the Weather Research and Forecasting - Chemistry model and Grid-point Statistical Interpolation, a three-dimensional variational assimilation tool. The modelling domain covers the northeastern region of North America. The measurements come from the United States Environmental Protection Agency AIRNow network and are available hourly. Background error covariance statistics are derived from forecasts in July 2004. Comparison of forecasts issued in August and September 2006 and initialized with and without the assimilation follows. Results show that forecasts of ozone and fine aerosol concentrations benefit from the assimilation in terms of standard verification scores for a period of at least 24 hours. However, significant reduction of errors as a consequence of the assimilation is accompanied by fast model error growth in the early forecast hours. Published in 2010 by John Wiley & Sons, Ltd.