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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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AMT | Articles | Volume 12, issue 7
Atmos. Meas. Tech., 12, 3943–3961, 2019
https://doi.org/10.5194/amt-12-3943-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 12, 3943–3961, 2019
https://doi.org/10.5194/amt-12-3943-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 18 Jul 2019

Research article | 18 Jul 2019

A practical information-centered technique to remove a priori information from lidar optimal-estimation-method retrievals

Ali Jalali et al.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Wenzel on behalf of the Authors (26 Mar 2019)  Author's response
ED: Referee Nomination & Report Request started (26 Mar 2019) by Andrew Sayer
RR by Anonymous Referee #1 (16 Apr 2019)
RR by Anonymous Referee #3 (28 Apr 2019)
ED: Reconsider after major revisions (09 May 2019) by Andrew Sayer
AR by Robert Sica on behalf of the Authors (04 Jun 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (10 Jun 2019) by Andrew Sayer
ED: Publish as is (20 Jun 2019) by Andrew Sayer
ED: Publish as is (25 Jun 2019) by Andrew Sayer
Publications Copernicus
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Short summary
This paper builds upon the work in von Clarmann and Grabowski (2007) concerning the a priori profile influence in the optimal estimation method applied to active remote sensing measurements, with examples given for lidar retrievals of temperature and water vapor mixing ratio. The optimal estimation method is a new technique for many active remote sensing researchers. This study gives insight into understanding the effect on retrievals of the a priori information.
This paper builds upon the work in von Clarmann and Grabowski (2007) concerning the a priori...
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