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

Autor:	Pavel Antokhin, Alexey Penenko
Rok vydání:	2016
Předmět:	Data assimilation Transformation (function) Computer science Atmospheric chemistry Decomposition (computer science) Sensitivity (control systems) Algorithm Physics::Atmospheric and Oceanic Physics
Zdroj:	IOP Conference Series: Earth and Environmental Science. 48:012021
ISSN:	1755-1315 1755-1307
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c3827777a78ae6b752549ce0489a65af https://doi.org/10.1088/1755-1315/48/1/012021 Zobrazit plný text záznamu