An observation-based evaluation and ranking of historical Earth system model simulations in the northwest North Atlantic Ocean

Laurent, Arnaud; Fennel, Katja; Kuhn, Angela

doi:https://doi.org/10.5194/bg-18-1803-2021

Articles | Volume 18, issue 5

https://doi.org/10.5194/bg-18-1803-2021

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

https://doi.org/10.5194/bg-18-1803-2021

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

Articles | Volume 18, issue 5

Research article

|

16 Mar 2021

Research article |

| 16 Mar 2021

An observation-based evaluation and ranking of historical Earth system model simulations in the northwest North Atlantic Ocean

Arnaud Laurent, Katja Fennel, and Angela Kuhn

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Final revised paper (published on 16 Mar 2021)
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Preprint (discussion started on 17 Jul 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 of ‘An observation-based evaluation and ranking of historical Earth System Model simulations for regional downscaling in the Northwest North Atlantic Ocean’', Anonymous Referee #1, 06 Sep 2020
- AC1: 'Response to Reviewer 1', Arnaud Laurent, 02 Oct 2020
RC2: 'Comparison of Earth System Models output with observations', Anonymous Referee #2, 14 Sep 2020
- AC2: 'Response to Reviewer 2', Arnaud Laurent, 02 Oct 2020

Peer-review completion

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

ED: Reconsider after major revisions (06 Oct 2020) by Carolin Löscher

AR by Arnaud Laurent on behalf of the Authors (24 Nov 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (25 Nov 2020) by Carolin Löscher

RR by Anonymous Referee #2 (16 Dec 2020)

Suggestions for revision or reasons for rejection

The authors did answer the concerns initially raised. The objectives of the paper were better defined and reflect the work presented. It is a valuable piece of work and it will be useful for scientists seeking to use projections from ESMs as part of their work. I thus recommend that this paper be accepted for publication after some very minor corrections/improvements. See comments below.

Line 15. I would repeat surface nitrate. Same for observed surface temperature.
Line 52: Maybe you wanted to refer to Gilbert et al. 2005?
Lines 102 and 155: and salinity
Line 314. Improvement in terms of scores? Could you specify what the improvement is? I see Chl a going from 0.9 to 1.4 to 0.8 to 1.4. That is not a big change. Nitrate improves a lot though.
Line 400. In fact the nutrients that are upwelled at the GS detachment point do not affect directly the Scotian Shelf. These waters are transported towards the sub-arctic gyre. However, mixing with Labrador Sea water occurs south of the Grand Banks and then flows south towards the Scotian Shelf. This is reflected in your better correlation of SS conditions with conditions at the eastern boundary. So you need to have a good correspondence between circulation, water mass representation and biogeochemical conditions. What Lavoie et al. mention is that these models do not represent the observed subsurface maximum. Their figure 13 actually shows that the surface nitrate is high along the whole transect with CNRM-CM5. We can also see in your figure S1 that the nitrate stays high everywhere all year round with this model. Something is clearly not working properly. Your figures S2 and S3 also show that nutrients are low in the CMIP5 IPSL models, except in S2 in the GoM.

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ED: Publish subject to minor revisions (review by editor) (06 Jan 2021) by Carolin Löscher

AR by Arnaud Laurent on behalf of the Authors (09 Jan 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (25 Jan 2021) by Carolin Löscher

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Short summary

CMIP5 and CMIP6 models, and a high-resolution regional model, were evaluated by comparing historical simulations with observations in the northwest North Atlantic, a climate-sensitive and biologically productive ocean margin region. Many of the CMIP models performed poorly for biological properties. There is no clear link between model resolution and skill in the global models, but there is an overall improvement in performance in CMIP6 from CMIP5. The regional model performed best.