Articles | Volume 11, issue 8
Atmos. Meas. Tech., 11, 4909–4928, 2018
https://doi.org/10.5194/amt-11-4909-2018
Atmos. Meas. Tech., 11, 4909–4928, 2018
https://doi.org/10.5194/amt-11-4909-2018

Research article 27 Aug 2018

Research article | 27 Aug 2018

A singular value decomposition framework for retrievals with vertical distribution information from greenhouse gas column absorption spectroscopy measurements

Anand K. Ramanathan et al.

Download

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 Anand Ramanathan on behalf of the Authors (18 Apr 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (08 May 2018) by Kimberly Strong
RR by Anonymous Referee #3 (11 May 2018)
ED: Publish subject to minor revisions (review by editor) (24 Jun 2018) by Kimberly Strong
AR by Anand Ramanathan on behalf of the Authors (21 Jul 2018)  Author's response    Manuscript
ED: Publish subject to technical corrections (24 Jul 2018) by Kimberly Strong
AR by Anand Ramanathan on behalf of the Authors (01 Aug 2018)  Author's response    Manuscript
Download
Short summary
Remote sensing of greenhouse gases (GHG) such as CO2 and CH4 in the atmosphere from space is important for studying emissions and the carbon cycle. Present-day techniques measure the absorption of light passing through the atmosphere and determine the column-averaged gas concentration in the atmosphere. Here, we draw from a well-known singular value decomposition (SVD) framework to develop a technique of extracting information about the GHG concentration profile from the column absorption.