Comparison of inverse and data assimilation problems in the inverse modeling of atmospheric chemistry

A. V. Penenko; V. S. Konopleva; V. V. Penenko

doi:10.1117/12.2644951

7 December 2022 Comparison of inverse and data assimilation problems in the inverse modeling of atmospheric chemistry

A. V. Penenko, V. S. Konopleva, V. V. Penenko

Proceedings Volume 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 123416O (2022) https://doi.org/10.1117/12.2644951
Event: 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 2022, Tomsk, Russia

Abstract

Data assimilation algorithms are an important part of modern air quality modeling techniques. To study the real-time operation mode features of the data assimilation algorithms we numerically compare its performance to the solution in the “inverse problem mode”, when the same set of data is available “at once”. The objective of the paper is to compare the gradient-based (variational) and derivative-free solvers in the data assimilation mode to the solution of the reference inverse problem of reconstructing unobservable chemical species concentrations for the atmospheric chemistry model with a derivative-free solver.

Citation Download Citation

A. V. Penenko, V. S. Konopleva, and V. V. Penenko "Comparison of inverse and data assimilation problems in the inverse modeling of atmospheric chemistry", Proc. SPIE 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 123416O (7 December 2022); https://doi.org/10.1117/12.2644951

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available