Articles | Volume 14, issue 11
https://doi.org/10.5194/amt-14-6929-2021
https://doi.org/10.5194/amt-14-6929-2021
Research article
 | 
01 Nov 2021
Research article |  | 01 Nov 2021

Novel approach to observing system simulation experiments improves information gain of surface–atmosphere field measurements

Stefan Metzger, David Durden, Sreenath Paleri, Matthias Sühring, Brian J. Butterworth, Christopher Florian, Matthias Mauder, David M. Plummer, Luise Wanner, Ke Xu, and Ankur R. Desai

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-86', Anonymous Referee #1, 06 May 2021
    • AC1: 'Reply on RC1', Stefan Metzger, 16 Jun 2021
  • RC2: 'Comment on amt-2021-86', Anonymous Referee #2, 10 May 2021
    • AC2: 'Reply on RC2', Stefan Metzger, 16 Jun 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Stefan Metzger on behalf of the Authors (28 Jul 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (29 Jul 2021) by Glenn Wolfe

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Stefan Metzger on behalf of the Authors (22 Oct 2021)   Author's adjustment   Manuscript
EA: Adjustments approved (26 Oct 2021) by Glenn Wolfe
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Short summary
The key points are the following. (i) Integrative observing system design can multiply the information gain of surface–atmosphere field measurements. (ii) Catalyzing numerical simulations and first-principles machine learning open up observing system simulation experiments to novel applications. (iii) Use cases include natural climate solutions, emission inventory validation, urban air quality, and industry leak detection.