Variational data assimilation for tropospheric chemistry modeling
Variational data assimilation for tropospheric chemistry modeling
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DOI：
10.1029/97jd01213
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发表时间：
1997-07
影响因子：
--
通讯作者：
H. Elbern;H. Schmidt;A. Ebel
中科院分区：
文献类型：
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作者：
H. Elbern;H. Schmidt;A. Ebel
本文应用变分伴随资料同化方法将化学观测资料同化到一个综合对流层气相模式中。这种方法的基本原理是找到正确的初始值，为随后的大气化学模式运行时，观测分散在时间。变分伴随技术被认为是未来高级气象预报的一种有前途的工具。四维变分数据同化在这一研究领域的应用所获得的经验激励了尝试应用该技术的空气质量建模和分析的化学状态的大气。本文介绍了第二代区域酸沉降模式气相机制伴随模式的发展和应用，该模式已用于欧洲大气污染扩散模式系统。使用模式生成的数据和真实的观测同化方案的性能结果对流层条件。在前一种情况下，它表明，只有少数甚至一个测量的关键物种的时间序列传递足够的信息，以大大提高未观察到的物种，直接与观察到的物种的分析。在后一种情况下，采用拉格朗日方法，在两个全面配备的测量地点之间进行轨迹计算。该方法使我们能够分析空气污染建模的初始数据，即使只有稀疏的观测。除了通过适当分析初始浓度显著改善模型性能外，还表明伴随算法提供了估计臭氧浓度相对于其前体物的敏感性的可行性。
The method of variational adjoint data assimilation has been applied to assimilate chemistry observations into a comprehensive tropospheric gas phase model. The rationale of this method is to find the correct initial values for a subsequent atmospheric chemistry model run when observations scattered in time are available. The variational adjoint technique is esteemed to be a promising tool for future advanced meteorological forecasting. The stimulating experience gained with the application of four-dimensional variational data assimilation in this research area has motivated the attempt to apply the technique to air quality modeling and analysis of the chemical state of the atmosphere. The present study describes the development and application of the adjoint of the second-generation regional acid deposition model gas phase mechanism, which is used in the European air pollution dispersion model system. Performance results of the assimilation scheme using both model-generated data and real observations are presented for tropospheric conditions. In the former case it is demonstrated that time series of only few or even one measured key species convey sufficient information to improve considerably the analysis of unobserved species which are directly coupled with the observed species. In the latter case a Lagrangian approach is adopted where trajectory calculations between two comprehensively furnished measurement sites are carried out. The method allows us to analyze initial data for air pollution modeling even when only sparse observations are available. Besides remarkable improvements of the model performance by properly analyzed initial concentrations, it is shown that the adjoint algorithm offers the feasibility to estimate the sensitivity of ozone concentrations relative to its precursors.