...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >VARIATIONAL DATA ASSIMILATION FOR TROPOSPHERIC CHEMISTRY MODELING
【24h】

VARIATIONAL DATA ASSIMILATION FOR TROPOSPHERIC CHEMISTRY MODELING

机译：对流化学建模的变异数据同化

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

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. [References: 33]
机译：变分伴随数据同化的方法已被用于将化学观测同化为一个全面的对流层气相模型。该方法的基本原理是，当有时间上分散的观测数据时，可以为随后的大气化学模型运行找到正确的初始值。变分伴随技术被认为是将来进行高级气象预报的有前途的工具。在该研究领域中，利用四维变分数据同化获得的令人兴奋的经验促使人们尝试将该技术应用于空气质量建模和大气化学状态的分析。本研究描述了在欧洲空气污染扩散模型系统中使用的第二代区域酸沉降模型气相机制的伴随物的开发和应用。提出了利用对流层条件利用模型生成的数据和实际观测值进行的同化方案的性能结果。在前一种情况下，已证明只有很少或什至一个被测关键物种的时间序列传达了足够的信息，从而大大改善了与观测物种直接耦合的未观测物种的分析。在后一种情况下，采用拉格朗日方法，其中在两个装备齐全的测量位置之间进行轨迹计算。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数据也可以使用。除了通过适当分析初始浓度对模型性能的显着改善外，还显示了伴随算法还提供了估算臭氧浓度相对于其前体的敏感性的可行性。 [参考：33]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号