Uncertainty-function-based continuation framework in data assimilation algorithms for atmospheric chemistry models › Research Explorer

Novosibirsk State University's Research Portal

Uncertainty-function-based continuation framework in data assimilation algorithms for atmospheric chemistry models

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

DOI

https://doi.org/10.1117/12.2603422
Final published version

A. V. Penenko
V. S. Konopleva
P. M. Golenko
V. V. Penenko

Original language	English
Title of host publication	27th International Symposium on Atmospheric and Ocean Optics, Atmospheric Physics
Editors	Gennadii G. Matvienko, Oleg A. Romanovskii
Publisher	The International Society for Optical Engineering
ISBN (Electronic)	9781510646971
ISBN (Print)	9781510646971
DOIs	https://doi.org/10.1117/12.2603422
Publication status	Published - 2021
Event	27th International Symposium on Atmospheric and Ocean Optics, Atmospheric Physics 2021 - Moscow, Russian Federation Duration: 5 Jul 2021 → 9 Jul 2021

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11916
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	27th International Symposium on Atmospheric and Ocean Optics, Atmospheric Physics 2021
Country/Territory	Russian Federation
City	Moscow
Period	05.07.2021 → 09.07.2021

OECD FOS+WOS

1.01.PN MATHEMATICS, APPLIED
2.02.IQ ENGINEERING, ELECTRICAL & ELECTRONIC
1.03.UK PHYSICS, CONDENSED MATTER

Research areas

atmospheric chemistry, continuation problem, data assimilation, di erential evolution, reaction rates, uncertainty function, variational approach

ID: 35538975