Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa

Guan, K.; Good, S. P.; Caylor, K. K.; Sato, H.; Wood, E. F.; Li, H.

doi:https://doi.org/10.5194/bg-11-6939-2014

Articles | Volume 11, issue 23

https://doi.org/10.5194/bg-11-6939-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Climate extremes and biogeochemical cycles in the terrestrial...

https://doi.org/10.5194/bg-11-6939-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 11, issue 23

Research article

|

11 Dec 2014

Research article |

| 11 Dec 2014

Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa

K. Guan, S. P. Good, K. K. Caylor, H. Sato, E. F. Wood, and H. Li

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Final revised paper (published on 11 Dec 2014)
Supplement to the final revised paper
Preprint (discussion started on 27 May 2014)

Interactive discussion

Status: closed

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

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- Supplement

RC C2744: 'Reasonable modeling study suggesting importance of intraseason rainfall variability but needs revisions', Anonymous Referee #1, 20 Jun 2014
- AC C4824: 'Response and revised manuscript are attached in pdf.', Kaiyu Guan, 30 Aug 2014
RC C3412: 'Review of bg-2014-204', Anonymous Referee #2, 11 Jul 2014
- AC C4825: 'Please refer to the attached response and revised manuscript in the pdf file.', Kaiyu Guan, 30 Aug 2014

Peer-review completion

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

AR by Kaiyu Guan on behalf of the Authors (30 Aug 2014) Author's response Manuscript

ED: Reconsider after major revisions (27 Sep 2014) by Christopher A. Williams

This work lends some insights that are valuable however I see one major weakness. As R1 pointed out, the approach to representing rainfall with constant wet season statistics averaged over the wet 90% of the year smooths out any real seasonality at a monthly time scale, with the effect, for example, of making 8 months uniformly wet (albeit with stochasticity from random draws) and 4 months uniformly dry. This completely cuts off the seasonal amplitude. Given that the goal of this work is to test sensitivity to possible shifts in intra-seasonal rainfall variability, it seems crucial to accurately represent rainfall seasonality. Can anything be done at this stage to address that weakness which seems rather significant? I fear that it would involve quite a lot of additional work to revise by creating monthly or bi-monthly rainfall statistics and to then simulate the response for the continent. Even so, it seems appropriate to raise this point and to encourage you to address it.

In addition, the writing is awkward in a few places, including:

Response to R1's comment, original L571: this sentence is still not correct, linked to the major comment above. Maybe you can restate this as:
"Sensitivity to rainy season length (i.e. S...) underscores the combined importance of event depth and season duration which act to tradeoff with each other in the experiments performed here.." You could reword this but I think it is important to stick to what your synthetic experiments really represent which is something different from seasonality which I would argue is only weakly represented in your treatment.

Response to R2's comment P7587, L13-16 (original version) is still not clearly worded. Please try again.

"...limitations can be possibly overcame by" change overcame to overcome.

"Cautions are required that our simplified..." This sentence is unclear and awkward. Please clarify.

I believe "Market" should be replaced with "Marked" Poisson Process throughout the manuscript.

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AR by Kaiyu Guan on behalf of the Authors (18 Oct 2014) Author's response Manuscript

ED: Publish subject to technical corrections (07 Nov 2014) by Christopher A. Williams

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Short summary

Climate change is expected to modify the way that rainfall arrives, namely the frequency and intensity of rainfall events and rainy season length. Yet, the quantification of the impact of these possible rainfall changes across large biomes is lacking. Our study fills this gap by developing a new modeling framework, applying it to continental Africa. We show that African ecosystems are highly sensitive to these rainfall variabilities, with esp. large sensitivity to changes in rainy season length.