A triple tree-ring constraint for tree growth and physiology in a global land surface model

Barichivich, Jonathan; Peylin, Philippe; Launois, Thomas; Daux, Valerie; Risi, Camille; Jeong, Jina; Luyssaert, Sebastiaan

doi:https://doi.org/10.5194/bg-18-3781-2021

Articles | Volume 18, issue 12

https://doi.org/10.5194/bg-18-3781-2021

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

https://doi.org/10.5194/bg-18-3781-2021

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

Articles | Volume 18, issue 12

Research article

|

24 Jun 2021

Research article |

| 24 Jun 2021

A triple tree-ring constraint for tree growth and physiology in a global land surface model

Jonathan Barichivich, Philippe Peylin, Thomas Launois, Valerie Daux, Camille Risi, Jina Jeong, and Sebastiaan Luyssaert

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Final revised paper (published on 24 Jun 2021)
Preprint (discussion started on 10 Dec 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review', Anonymous Referee #1, 06 Jan 2021
- AC1: 'Reply on RC1', Jonathan Barichivich, 22 Mar 2021
RC2: 'Review of A triple tree-ring constraint for tree growth and physiology in a global land surface model” by Jonathan Barichivich et al.', Anonymous Referee #2, 11 Jan 2021
- AC2: 'Reply on RC2', Jonathan Barichivich, 22 Mar 2021

Peer-review completion

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

ED: Reconsider after major revisions (23 Mar 2021) by Christopher Still

AR by Jonathan Barichivich on behalf of the Authors (23 Mar 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (27 Mar 2021) by Christopher Still

RR by John Marshall (04 Apr 2021)

RR by Anonymous Referee #3 (02 May 2021)

RR by Anonymous Referee #2 (04 May 2021)

Suggestions for revision or reasons for rejection

In this revised manuscript, the authors present a compelling case for using triple tree ring-proxies and their interactions as means to evaluate land surface model. The manuscript was substantially re-organized and the story is clear and reads well.
The authors addressed most of the concerns raised in my previous review. This will be a relevant contribution for many communities in Biogeosciences, proposes an assessment of model parameters improvement, and demonstrate a tangible potential fo using tree ring data to evaluate land surface models.

Below I have minor comments for the authors to consider.

- The manuscript uses heavily acronyms (e.g. ITRDB), some of which were not spelled out and defined when first cited. I urge the authors to carefully check the text for acronym.
- In their response, the authors argue that using the McCarroll and Loader 2004 atmospheric data has been the standard in the community (likely tree ring community). However, regardless of recent suggestion outlined in Belmecheri & Lavergne and your choice for not using the most updated data, note that the data used in McCarroll and Loader 2004 were recalibrated and are now the forcing data in CMIP6 efforts. I understand that ultimately the results will not change (interannual correlation) and the authors do not wish to re-run the analysis but it ought to be consistent in future work to use the most recent, updated, calibrated and vetted forcing data (similarly to model runs).

Detailed suggestion broken down by manuscript sections:

Introduction
- The following need references.
“a quasi-global network of eddy-covariance observations, Earth observations and forest inventories covering the last few decades”

Methods:

- In the following, the fractionation parameters as well as the definition if the model parameters while summarized in McCarroll and Loader 2004, the latter in not the accurate reference for the model parameters and their values. Please cite the appropriate references.

“where a (4.4‰) is the kinetic discrimination associated with diffusion between free air and the stomatal cavity, b (27‰) is the fractionation during CO2 fixation by the Rubisco enzyme, ci is the leaf internal CO2 concentration simulated by ORCHIDEE and ca is the atmospheric CO2 concentration prescribed from measurements (McCarroll and Loader, 2004).”

In the following “Six previously published tree-ring sites in northern and western Europe with simultaneous measurements of ring-width and…” one suggestion is to reword as: Six previously published tree-ring chronologies from sites in…

Discussion:

- “Disentangling the effect of isotopic signatures from source water and leaf evaporative
enrichment revealed that the better performance of LPX-Bern to simulate _18 O variability was due to its higher sensitivity to leaf evaporative enrichment compared with ORCHIDEE (Fig. 3a), which is predominantly sensitive to source water…”

wouldn’t this be dependent on site locations? where leaf water enrichment in drier sites will be a more important driver compared to more mesic sites where leaf water enrichment will not dominate the cellulose 18O. How does LPX-Bern parametrize the leaf water enrichment sensitivity or contribution. Is the latter variable per PFT/climate zone or just overall more important than the other 2 models?

- P17. Lines 25. This is a relevant suggestion for testing the L and péclet effect sensitivity in the model world. The uncertainties and sensitivity of these parameters hold also true for the empirical world when direct comparison of simulated and observed cellulose 18 O showed variability depending on (1) parameter values; but also (2) a model with or without the péclet effect. The péclet effect and effective path length are note measured but inferred and can vary seasonally or depending on aridity gradients as well. In sum, this not an uncertainty in the model parameters.

- P17. Lines 30. This assessment is rather puzzling, it implies that 18O of precipitation is not a significant driver while it also determines the soil water? This warrant more clarification. The lack of correlation between the two models suggest that interannual variability is not important but the average value is? What would the correlation be if one precipitation (constant) value was used instead? This can show that interannual variability or even seasonal change are not important but rather the integration period and average source water value.

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ED: Publish subject to minor revisions (review by editor) (12 May 2021) by Christopher Still

AR by Jonathan Barichivich on behalf of the Authors (18 May 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (22 May 2021) by Christopher Still

AR by Jonathan Barichivich on behalf of the Authors (26 May 2021) Manuscript

Short summary

The width and the chemical signals of tree rings have the potential to test and improve the physiological responses simulated by global land surface models, which are at the core of future climate projections. Here, we demonstrate the novel use of tree-ring width and carbon and oxygen stable isotopes to evaluate the representation of tree growth and physiology in a global land surface model at temporal scales beyond experimentation and direct observation.