Articles | Volume 14, issue 8
Research article
12 Aug 2021
Research article |  | 12 Aug 2021

Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition

Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Tia R. Scarpelli, Melissa P. Sulprizio, Yuzhong Zhang, and Chris H. Rycroft


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Hannah Nesser on behalf of the Authors (04 Jun 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (04 Jun 2021) by Helen Worden
RR by Anonymous Referee #2 (08 Jul 2021)
ED: Publish as is (08 Jul 2021) by Helen Worden
Short summary
Analytical inversions of satellite observations of atmospheric composition can improve emissions estimates and quantify errors but are computationally expensive at high resolutions. We propose two methods to decrease this cost. The methods reproduce a high-resolution inversion at a quarter of the cost. The reduced-dimension method creates a multiscale grid. The reduced-rank method solves the inversion where information content is highest.