Feasibility of reconstructing the summer basin-scale sea surface partial pressure of carbon dioxide from sparse in situ observations over the South China Sea

Wang, Guizhi; Shen, Samuel S. P.; Chen, Yao; Bai, Yan; Qin, Huan; Wang, Zhixuan; Chen, Baoshan; Guo, Xianghui; Dai, Minhan

doi:https://doi.org/10.5194/essd-13-1403-2021

Articles | Volume 13, issue 3

https://doi.org/10.5194/essd-13-1403-2021

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

https://doi.org/10.5194/essd-13-1403-2021

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

Articles | Volume 13, issue 3

Data description paper

|

01 Apr 2021

Data description paper |

| 01 Apr 2021

Feasibility of reconstructing the summer basin-scale sea surface partial pressure of carbon dioxide from sparse in situ observations over the South China Sea

Guizhi Wang, Samuel S. P. Shen, Yao Chen, Yan Bai, Huan Qin, Zhixuan Wang, Baoshan Chen, Xianghui Guo, and Minhan Dai

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Final revised paper (published on 01 Apr 2021)
Preprint (discussion started on 11 Sep 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'pCO2 in the South China Sea', Anonymous Referee #1, 25 Sep 2020
- AC1: 'Response to Referee #1', Samuel Shen, 02 Dec 2020
RC2: 'Review for essd-2020-167', Anonymous Referee #2, 07 Nov 2020
- AC2: 'Our full response to Referee #2 is in the attached pdf file.', Samuel Shen, 04 Dec 2020

Peer-review completion

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

AR by Samuel Shen on behalf of the Authors (31 Dec 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (10 Jan 2021) by David Carlson

RR by Anonymous Referee #2 (22 Jan 2021)

Suggestions for revision or reasons for rejection

The paper is much improved and the authors should be commended on their efforts. The new analyses based on the SEATS data are very helpful, and much work has been done to better quantify the uncertainty. It is also excellent that the paper is confirming that it is presenting new data, and this will elevate the impact of the work.

I yet feel the uncertainty assessment would benefit from another revision. It is not enough to omit one 0.5x0.5 degree grid cell at a time and recompute estimates in that grid cell. That is just a test of how well the method works when the pCO2 estimate has proximal (in both space and time) measurements. The test should omit entire cruises or entire swathes of data in the tests (i.e., the western or easternmost halves of all data in each year... though even that would provide somewhat of an underestimate since the estimates would always benefit from temporally-proximal measurements).

Also, I urge the authors to focus on estimate bias for each year instead of estimate RMSE, and to propagate the mean bias for each year's estimates into an estimate of the error in the average fluxes. Probably the most important quantity is RMSE of the annual average pCO2 (similar to average annual absolute bias).

Their response to "1. The model should not be used in any region where there is no fitting data. This includes most of the South China Sea south of ∼12.5 N" did not convince me. The method is only valid when its estimates can be trusted. With no validation measurements in the South China Sea, the results cannot be trusted in that region. The paper would be stronger if the results from that region were omitted from at least one regional trend, or held aside and given an appropriate caution.

I didn't understand the authors' response to "If the Bai et al. approach gives a different average pCO2 than the in situ measurements, then the climatology created from the remote sensing product should not be used to generate the Standardized Anomalies of Obs. Data (as indicated in Figure 1). I believe an independent climatology would then be needed. Otherwise, a significant average bias would have to be compensated by a large average value for one or more EOFs." The response seemed to explain how EOFs work using jargon. Perhaps I just didn't understand, but the reply didn't seem to address the concern. The concern is that a big error in the mean state in the underlying climatology would have to be compensated by spurious scaling of EOFs that are intended to capture anomalies from the climatology (not errors in the mean state). The new analysis suggests that the RS pCO2 is indeed overestimating average pCO2, and sometimes by up to 50 uatm (separately, this should be quantified with an average bias statistic across all years as well). This means the climatological values might indeed be a poor representation of the true state of the region.

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ED: Publish subject to minor revisions (review by editor) (06 Feb 2021) by David Carlson

AR by Samuel Shen on behalf of the Authors (16 Feb 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (17 Feb 2021) by David Carlson

AR by Samuel Shen on behalf of the Authors (27 Feb 2021)

Short summary

This study reconstructs a complete field of summer sea surface partial pressure of CO₂ (pCO₂) over the South China Sea (SCS) with a 0.5° resolution in the period of 2000–2017 using the scattered underway pCO₂ observations. The spectral optimal gridding method was used in this reconstruction with empirical orthogonal functions computed from remote sensing data. Our reconstructed data show that the rate of sea surface pCO2 increase in the SCS is 2.4 ± 0.8 µatm yr^-1 during 2000–2017.