Residual temperature bias effects in stratospheric species distributions from LIMS

Remsberg, Ellis; Harvey, V. Lynn; Krueger, Arlin; Natarajan, Murali

doi:https://doi.org/10.5194/amt-14-2185-2021

Articles | Volume 14, issue 3

https://doi.org/10.5194/amt-14-2185-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-14-2185-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 3

Research article

|

19 Mar 2021

Research article |

| 19 Mar 2021

Residual temperature bias effects in stratospheric species distributions from LIMS

Ellis Remsberg, V. Lynn Harvey, Arlin Krueger, and Murali Natarajan

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Final revised paper (published on 19 Mar 2021)
Supplement to the final revised paper
Preprint (discussion started on 26 Oct 2020)
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Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review', Anonymous Referee #1, 24 Nov 2020
- AC1: 'reply to Referee #1', Ellis Remsberg, 02 Dec 2020
RC2: 'Review', Anonymous Referee #2, 04 Dec 2020
- AC2: 'Response to Comments of Referee #2', Ellis Remsberg, 10 Dec 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Ellis Remsberg on behalf of the Authors (22 Dec 2020) Manuscript

ED: Referee Nomination & Report Request started (19 Jan 2021) by Christian von Savigny

RR by Anonymous Referee #2 (25 Jan 2021)

Suggestions for revision or reasons for rejection

This is my second review of the manuscript, the first of which was related to the original version of the manuscript. I am satisfied with all replies and actions in response to my first review, except for one issue. This refers again to the temperature bias due to neglected horizontal temperature gradients:

The logic behind the applied approach towards assessment of temperature biases due to horizontal gradients is still not clear to me. I understand from Remsberg et al., 2004 (their table 2 and related text), that the random and systematic errors of V6 T(p) has been assessed. A number of uncertainties (also called error sources) go into this assessment, however, the systematic error due to horizontal temperature gradients is not one of those. Instead, systematic errors due to calibration, line intensity, forward model etc. are summed up (RSS) to the total accuracy, and total precision (estimated from other error sources, again without temperature gradients) and total accuracy are summed up (RSS) for the total error. This one is presented in line g of the Table 2 of Remsberg et al., 2004, These errors (Remsberg et al., 2004, Table 2, row g) are now, in the current manuscript, used as assessment of the error due to disregarded temperature gradients. There might be arguments to justify this approach, e.g. that these errors can be taken as upper estimates, for example, however I think these arguments need to be presented in the current manuscript.

Further, the authors refer to a first-order correction of LIMS temperature biases due to horizontal gradients by Gille and Russell, 1984. Unfortunately, I do not have free access to this paper, neither personal nor institutional, due to the restrictive publication policy of AGU/Wiley, therefore I cannot judge if an appropriate description of the first order correction has been provided by Gille and Russell, 1984, and if they quantify the residual temperature biases. I assume that AGU's/Wiley's restrictive publication policy will affect many other readers as well, and therefore I recommend to provide a short description of the method and results in the current manuscript. On the other hand, Roewe et al. 1982 seem to provide a quantitative assessment of temperature biases due to horizontal gradients (and the access to this paper seems to be free). It would be helpful for the reader to know if the temperatures have been corrected by the numbers provided in the latter paper, and which residual effects remained.

After reading this submitted manuscript and the cited papers (those that are accessible to me) several times I have got the impression that the "first order correction scheme" might be a 2D-retrieval along one orbit. This, indeed, would correct horizontal temperature variations at first order (i.e. the gradients). In this case, remaining A-D differences could come from other effects than horizontal temperature variations, like slightly different gain calibrations between the two observations, in which case the application of the error assessment of Remsberg et al., 2004 Table 2, row g would make sense. If my assumption is correct, the fact that a 2D-retrieval has been applied which corrects for the first order horizontal temperature gradient effects needs to be stated clearly and at the beginning of the paper. It is of utmost importance for understanding of all what follows. And the A-D biases of trace gases should not primarily be related to unresolved horizontal temperature gradients but to the other differences related to the accuracy assessment in Remsberg et al., 2004.

Finally, I would like to express my point of view that the importance of the LIMS data record, as an early data set with near-global coverage, can hardly be overestimated. For this reason, the description of the data and their quality assessment should be done as complete and careful as possible. I appreciate very much Dr. Remsberg's initiative towards this goal.

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ED: Publish subject to minor revisions (review by editor) (26 Jan 2021) by Christian von Savigny

AR by Ellis Remsberg on behalf of the Authors (29 Jan 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (12 Feb 2021) by Christian von Savigny

AR by Ellis Remsberg on behalf of the Authors (12 Feb 2021)

Short summary

The LIMS satellite instrument operated in 1978/1979 and provided profiles of temperature (T) and four key species. LIMS viewed the atmosphere in opposite directions on its ascending (A) vs. descending (D) orbital segments. We find that (A-D) diagnostic plots of the species contain residual T biases that are a problem for assimilation of profiles in re-analyses. Even so, the combined data yield fields of O₃ and H₂O that agree well with that of the dynamical tracer, potential vorticity.