Numerical study of variational data assimilation algorithms based on decomposition methods in atmospheric chemistry models

International Conference and Early Career Scientists School on Environmental Observations, Modelling and Information Systems

生态环境科学;计算机科学

Penenko, Alexey^1,2 ; Antokhin, Pavel^3

Institute of Computational Mathematics and Mathematical Geophysics, SB RAS, ICM and MG SB RAS, prospect Akademika Lavrentyeva 6, Novosibirsk

630090, Russia^1

Novosibirsk State University, NSU, Pirogova Str. 2, Novosibirsk

630090, Russia^2

V.E. Zuev Institute of Atmospheric Optics, SB RAS, IAO SB RAS, Academician Zuev square 1, Tomsk

634055, Russia^3

关键词: Atmospheric chemistry model;    Chemical compositions;    Concentration Measurement;    Decomposition methods;    Emission inventories;    Numerical experiments;    Transport and transformation;    Variational data assimilation;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/48/1/012021/pdf
DOI  :  10.1088/1755-1315/48/1/012021

来源: IOP

【 摘 要 】

The performance of a variational data assimilation algorithm for a transport and transformation model of atmospheric chemical composition is studied numerically in the case where the emission inventories are missing while there are additional in situ indirect concentration measurements. The algorithm is based on decomposition and splitting methods with a direct solution of the data assimilation problems at the splitting stages. This design allows avoiding iterative processes and working in real-time. In numerical experiments we study the sensitivity of data assimilation to measurement data quantity and quality.