A coastally improved global dataset of wet tropospheric corrections for satellite altimetry

Lázaro, Clara; Fernandes, Maria Joana; Vieira, Telmo; Vieira, Eliana

doi:https://doi.org/10.5194/essd-12-3205-2020

Articles | Volume 12, issue 4

https://doi.org/10.5194/essd-12-3205-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-12-3205-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 4

Data description paper

|

08 Dec 2020

Data description paper |

| 08 Dec 2020

A coastally improved global dataset of wet tropospheric corrections for satellite altimetry

Clara Lázaro, Maria Joana Fernandes, Telmo Vieira, and Eliana Vieira

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Final revised paper (published on 08 Dec 2020)
Preprint (discussion started on 17 Oct 2019)

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, 18 Nov 2019
- AC1: 'Authors’ response to the Interactive Comment by Reviewer#1', Clara Lázaro, 14 Jul 2020
RC2: 'A coastally improved global dataset of wet tropospheric corrections for satellite altimetry', Anonymous Referee #2, 23 Apr 2020
- AC2: 'Authors’ response to the Interactive Comment by Reviewer#2', Clara Lázaro, 14 Jul 2020

Peer-review completion

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

AR by Clara Lázaro on behalf of the Authors (14 Jul 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (29 Jul 2020) by Christian Voigt

RR by Anonymous Referee #3 (12 Oct 2020)

Suggestions for revision or reasons for rejection

Review essd-2019-171: A coastally improved global dataset of wet tropospheric corrections for satellite altimetry by Clara Lázaro, Maria Joana Fernandes, Telmo Vieira, and Eliana Vieira (Data description paper)

The authors describe the GPD+ data set, which is an alternative wet tropospheric correction available for almost all radar altimeter missions since 1991. The wet tropospheric correctiom is necessary for the derivation of sea level from radar altimetry. In general best results are obtained with a correction derived from on-board micro-wave radiometer measurements. However, part of this data is missing, mainly at polar and coastal regions. For the GPD+ correction, an optimal interpolation scheme merges GNSS-, SSM/I-, SSM/IS- and data from numerical weather models at locations without valid on-board measurements. Furthermore an enhanced outlier detection for the MW radiometer data is applied and the on-board radiometers are cross-calibrated with the SSMI-data since they are prone to drifts. The improvements by the GPD+ correction are assessed for the newly processed ENVISAT data set. Here, the number of valid sea level measurements is increased by 10% with respect to the original radiometer derived correction. The GPD+ correction decreases the global sea level variance at cross-over points and along-track with respect to the model derived correction. With respect to the original radiometer correction the cross-over point variance is slightly decreased and the along-track variance is variability is clearly decreased from end of 2007 onwards. The improvement is mainly originating from the last 100 km and especially pronounced for the last 30 km off shore. For the ENVISAT mission the GPD+ correction is also available for inland waters.
The paper reviews the measurement principles of radar altimetry and the relevance of the tropospheric corrections. The methodology and the different input data sources are described in detail. It summarizes various previously published papers that assess the GPD+-quality for different missions and includes numbers for global reduction of variance and increase of retained SLAs related to the use of GPD+. Possibilities to further improve the data set are discussed. I am missing a more detailed description of the calibrations of the on-board MW radiometers of the reference missions relative to the third-party SSM/I and SSM/IS data. What are the formal errors of this fit and what is the effect on global mean sea level trend?
Since the wet tropospheric correction is critical for sea level retrieval from radar altimetry and GPD+ has proven to offer advantages over the conventional corrections this review of the data set is very valuable for users of altimeter data. Therefore I would recommend the publication of this paper after minor corrections.
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Detailed Comments:

The term ‘reference missions’ should be explained

The Envisat GPD+ is also provided over inland waters. Have inland GNSS stations been included in the processing?

Page 15 and following:
The measure of the quality of the GPD+correction in this paper is the reduction of sea level variance for the global mean and for different regions and coastal distances. Since neither the absolute wet path delay nor its variability are evenly distributed over the global ocean it might be useful to related the local decrease of variance to the absolute values (e.g. looking at explained variances).

Page 17, 518-521:
I do not understand these arguments. You might want to rephrase the paragraph.

Page 17, 541-545, page 18, 583-584:
the authors claim that GPD+ retains more valid sea level measurements close to the coast with respect to the MW radiometer correction. However, this is only shown for the global ocean. I would recommend to include numbers of the percentage of missing/retained data in coastal areas in the text and to add the corresponding curves in figure 13 and figure 14.

Figure 4:
• in my printout I can not discern the light and dark green colors

Figures 7/8:
• figure caption is confusing
• in my printout I can not discern the black and blue curves

Figure 11a:
for the GPD+ correction there is a pronounced decrease of along-track SLA variance from the end of 2007 onwards. This seems to coincide with the number of available GNSS stations/observations. Is there a similar effect for the Jason-1 missions?

Figure 12:
• the caption says: weighted SLA variance differences, what kind of weighting is applied?
• the variance reduction between the ‘MWR and the GPD+ correction is much more pronounced for the along-track SLAs than for the cross-over points. Wouldn’t it be more convincing to show the patterns for the along-track SLAs? In addition, I would be interested to see where the peak in figure 13 originates from that is showing up around 50°N.

You might consider to add a link to the CTOH GNSS Product Handbook

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ED: Publish subject to minor revisions (review by editor) (19 Oct 2020) by Christian Voigt

AR by Clara Lázaro on behalf of the Authors (25 Oct 2020) Author's response Manuscript

ED: Publish as is (28 Oct 2020) by Christian Voigt

AR by Clara Lázaro on behalf of the Authors (28 Oct 2020)

Short summary

In satellite altimetry (SA), the wet tropospheric correction (WTC) accounts for the path delay induced mainly by atmospheric water vapour. In coastal regions, the accuracy of the WTC determined by the on-board radiometer deteriorates. The GPD+ methodology, developed by the University of Porto in the remit of ESA-funded projects, computes improved WTCs for SA. Global enhanced products are generated for all past and operational altimetric missions, forming a relevant dataset for coastal altimetry.