Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

doi:https://doi.org/10.5194/hess-22-287-2018

Articles | Volume 22, issue 1

Hydrol. Earth Syst. Sci., 22, 287–303, 2018

https://doi.org/10.5194/hess-22-287-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Sub-seasonal to seasonal hydrological forecasting

Hydrol. Earth Syst. Sci., 22, 287–303, 2018

https://doi.org/10.5194/hess-22-287-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 22, issue 1

Research article 15 Jan 2018

Research article | 15 Jan 2018

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

Eric Mortensen et al.

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Final revised paper (published on 15 Jan 2018)
Preprint (discussion started on 28 Apr 2017)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Comments on the paper', Anonymous Referee #1, 18 May 2017
- AC1: 'Response to Referee 1', Eric Mortensen, 15 Aug 2017
RC2: 'Review of Mortensen et al. (2017) in HESSD', Shaun Harrigan, 01 Sep 2017
- AC2: 'Reply to Referee 2', Eric Mortensen, 06 Oct 2017

Peer-review completion

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

ED: Publish subject to revisions (further review by Editor and Referees) (25 Sep 2017) by Fredrik Wetterhall

AR by Anna Wenzel on behalf of the Authors (01 Nov 2017) Author's response

ED: Publish subject to minor revisions (review by editor) (09 Nov 2017) by Fredrik Wetterhall

ED: Referee Nomination & Report Request started (16 Nov 2017) by Fredrik Wetterhall

RR by Shaun Harrigan (21 Nov 2017)

Suggestions for revision or reasons for rejection

I believe the authors have done a good job in revising the manuscript and have taken on board many of my previous suggestions and have responded in a positive manor. Overall, I believe the re-structuring has helped the readability immensely and all the points of clarification etc. work towards producing a better paper. While the authors did make an attempt to use a few more papers from international scientific forecasting literature, I still do feel the Introduction and Discussion sections are light on more recent published papers. I do acknowledge the limited previous work on statistical seasonal forecasting in Peru and don’t think this is a critical factor and therefore recommend for publication in the HESS special issue. I have spotted a few minor edits from reading the revised manuscript that the authors may wish to correct:

Pg1; L22-24: Check tense/revise the sentence “Extending the lead time of and spatially disaggregating…”, it reads as if this is work you might do in future to further assist regional stakeholders, but you’ve already done it in the paper.

Pg15; L4: Change “significant” to “significantly”

Table 2, 3, 5, and 6: The line numbers have got mixed in with these tables, so just to be aware.

Pg23; L2: Wet/dry day frequency analysis is a good addition. However could you please state at the beginning what you define as a ‘wet day’. Some use >= 1mm? (e.g. http://etccdi.pacificclimate.org/list_27_indices.shtml), 0.2 mm is also common?

Pg27; L17: Sentence beginning with “This, as opposed…” does not appear to be complete.

Pg28; L2-9: These two sections aren’t very well expanded upon and I can’t help but feel the paper could end on a more positive note.

References: Van loon (2015) is in the reference list but not cited in the text

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ED: Publish subject to technical corrections (21 Nov 2017) by Fredrik Wetterhall

Short summary

Some do not realize the intrinsic importance of water until there is no water left. This is the reality faced by people in southern Peru, a dry area of the world where several economic activities and cities vie for scarce water resources. With the developed season-ahead precipitation prediction model, stakeholders and decision makers in this region will have another tool in their belt to respond to and plan for the negative impacts brought on by drought.