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https://doi.org/10.5194/egusphere-2024-4124
https://doi.org/10.5194/egusphere-2024-4124
22 Jan 2025
 | 22 Jan 2025

Propagating Information Content: An Example with Advection

David D. Turner, Maria P. Cadeddu, Julia Simonson, and Timothy J. Wagner

Abstract. The mathematical algorithm to derive geophysical information from remote sensing observations is called a retrieval. The mathematics of many retrieval problems is ill-posed, and thus a priori information is used to help constrain the derived geophysical variable to realistic values. One quantity of interest, therefore, is the information content of the observation. Perfect information content in the observation would be achieved if the retrieval is able to capture any perturbation in the desired geophysical variable with the proper magnitude.

Many new data products can be derived by combining geophysical variables retrieved from multiple different remote sensors. This paper explores, for the first time, how to derive the information content of these derived products. The approach uses traditional error propagation techniques to derive the uncertainty of the derived field twice, both when the observations are used in the retrieval and also when only the a priori information from each remote sensor is propagated. These two uncertainties are then used to provide an estimate of the information content of the derived geophysical variable.

This study demonstrates how to propagate the uncertainties from six different instruments to provide the information content for water vapor and temperature advection. A multi-month analysis demonstrates that, in a mean sense, the information content for temperature advection is nearly unity for all heights below 700 m while the information content for water vapor advection is somewhat more variable but still larger than 0.6 in the convective boundary layer.

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Journal article(s) based on this preprint

29 Jul 2025
Propagating information content: an example with advection
David D. Turner, Maria P. Cadeddu, Julia M. Simonson, and Timothy J. Wagner
Atmos. Meas. Tech., 18, 3533–3546, https://doi.org/10.5194/amt-18-3533-2025,https://doi.org/10.5194/amt-18-3533-2025, 2025
Short summary
David D. Turner, Maria P. Cadeddu, Julia Simonson, and Timothy J. Wagner

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-4124', Anonymous Referee #1, 27 Feb 2025
    • AC2: 'Reply on RC1', D. D. Turner, 17 Apr 2025
  • RC2: 'Comment on egusphere-2024-4124', Anonymous Referee #2, 11 Mar 2025
    • AC1: 'Reply on RC2', D. D. Turner, 17 Apr 2025

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-4124', Anonymous Referee #1, 27 Feb 2025
    • AC2: 'Reply on RC1', D. D. Turner, 17 Apr 2025
  • RC2: 'Comment on egusphere-2024-4124', Anonymous Referee #2, 11 Mar 2025
    • AC1: 'Reply on RC2', D. D. Turner, 17 Apr 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by D. D. Turner on behalf of the Authors (17 Apr 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to minor revisions (review by editor) (05 May 2025) by Mark Weber
AR by D. D. Turner on behalf of the Authors (12 May 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (12 May 2025) by Mark Weber
AR by D. D. Turner on behalf of the Authors (17 May 2025)  Author's response   Manuscript 

Journal article(s) based on this preprint

29 Jul 2025
Propagating information content: an example with advection
David D. Turner, Maria P. Cadeddu, Julia M. Simonson, and Timothy J. Wagner
Atmos. Meas. Tech., 18, 3533–3546, https://doi.org/10.5194/amt-18-3533-2025,https://doi.org/10.5194/amt-18-3533-2025, 2025
Short summary
David D. Turner, Maria P. Cadeddu, Julia Simonson, and Timothy J. Wagner
David D. Turner, Maria P. Cadeddu, Julia Simonson, and Timothy J. Wagner

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Short summary
When deriving a geophysical variable from remote sensors, the uncertainty and information content are critical. The latter quantify specifies what fraction of a real perturbation would be observed in the derived variable. This paper outlines, for the first time, a methodology for propagating the information content from multiple remote sensors into a derived product, using horizontal advection as an example.
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