A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship

Schulte, Justin; Policielli, Frederick; Zaitchik, Benjamin

doi:https://doi.org/10.5194/hess-24-5473-2020

Articles | Volume 24, issue 11

https://doi.org/10.5194/hess-24-5473-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-24-5473-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 11

Research article

|

23 Nov 2020

Research article |

| 23 Nov 2020

A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship

Justin Schulte, Frederick Policielli, and Benjamin Zaitchik

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Final revised paper (published on 23 Nov 2020)
Supplement to the final revised paper
Preprint (discussion started on 23 Jul 2019)
Supplement to the preprint

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Comments on HESS-2019-280: A Skewed perspective of the Indian rainfall-ENSO Relationship', James Doss-Gollin, 22 Aug 2019
- AC1: 'Response to Reviewer 1', Justin Schulte, 28 Oct 2019
RC2: 'Review of HESS-2019-280', Anonymous Referee #2, 10 Sep 2019
- AC2: 'Response to Reviewer 2', Justin Schulte, 28 Oct 2019

Peer-review completion

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

ED: Publish subject to minor revisions (further review by editor) (08 Nov 2019) by Pierre Gentine

AR by Justin Schulte on behalf of the Authors (22 Nov 2019) Author's response Manuscript

ED: Publish subject to revisions (further review by editor and referees) (11 Dec 2019) by Pierre Gentine

AR by Justin Schulte on behalf of the Authors (17 Dec 2019) Author's response Manuscript

ED: Publish subject to revisions (further review by editor and referees) (27 Jan 2020) by Pierre Gentine

ED: Referee Nomination & Report Request started (17 Mar 2020) by Pierre Gentine

RR by Anonymous Referee #2 (31 Mar 2020)

Suggestions for revision or reasons for rejection

GENERAL COMMENTS
The manuscript has been significantly improved, but there are some points where it could still be improved for more clarity and readability. My comments are given below and some examples that the authors could consider to make the paper more understandable to readers.

COMMENT: In Introduction, the prediction of South Asian Monsoon using ENSO is problematic given their complex relationship in time domain and frequency domain. However, there have been new studies accounting for differences in spectral attributes which improve prediction performance using wavelet analysis. For example,
Jiang, Z., Sharma, A., & Johnson, F. (2020). Refining Predictor Spectral Representation Using Wavelet Theory for Improved Natural System Modeling. Water Resources Research, 56(3), e2019WR026962. doi:10.1029/2019wr026962
Authors may want to have a look and include some discussion in Introduction as a possible means of improving their assessment further through the latest refinements in wavelet methodology.

COMMENT1: The way to compute monthly anomaly = monthly – monthly climatology over a baseline period, so given different base period in most cases it won’t be uniformly up or down. Authors must have misunderstood something referring to Line 421-423:
“To remove the influence of the annual cycle, the time series was converted into anomaly time series by subtracting the 1871-2016 long-term mean for each month from the individual monthly values.”

COMMENT2: Authors focus on the skewness, but throughout there is not clear definition or quantification of skewness you used in this work. Only a paragraph discussion is given in the introduction (Line 370 to 382). I would suggest adding a description in the Method section.

COMMENT3: Section 4.2, you probably mess up with figure captions. Figure 4 shows the correlation while Figure 5 gives skewness. Same in Section 4.3. Also, I would suggest authors combine section 4.1 and 4.2 since they both discussed the relationship between the correlation and skewness.

COMMENT4: Section 4.3, I would suggest authors keep the x-axis labels of Figure 4 and 5 consistent with Figure 6 and 7. So readers can easily refer to each other. Also, the auto-bicoherence of Nino 3 and 3.4 are not shown in the main context or supporting information. However, one entire paragraph is discussed about this. I would suggest authors to add the results of Nino3 and 3.4 to both Figure 7 and 8.

COMMENT5: Section 4.4, the second paragraph is talking about Figure 8 not Figure 10 (There are many other places in the manuscript, e.g. Section 4.5). This might be due to the review process, but authors need to read through the paper and make sure the content and figure are associated with each other.

COMMENT6: Figure 12-15 now are not discussed in the revised manuscript, so it can be removed. Even though Table 1 is included in the end, it is not cited or discussed anywhere in the main context. A discussion should be added to clarify the difference among them.

SPECIFIC POINTS:
1. Line 396: keep the numbering format consistent. 1) -> (1)
2. Where is abbreviation AIR in Data section?
3. Line 454: 3.1 Wavelet Analysis and hereafter
4. Line 464: Readers are referred to…
5. Line 588: Eq. (12)
6. Line 517: should be B_local(s1,s1) ?
7. Line 526: shoulde be phi_n(s1, s1) ?
8. Line 629: small capital w_F(t)
9. Figure 3: ylab: Nino 1+2
10. Line 688: it should be Nino 4 time series?
11. Line 713: should it be (Figure 4a and 4b)
12. Figure 10 and 11: The ylab is from 20N to 20S.
13. Line 1117: The R software link missing. These methods…

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RR by James Doss-Gollin (15 Jun 2020)

ED: Publish subject to minor revisions (review by editor) (03 Jul 2020) by Pierre Gentine

AR by Justin Schulte on behalf of the Authors (29 Jul 2020) Author's response Manuscript

ED: Publish as is (08 Sep 2020) by Pierre Gentine

Short summary

Wavelet coherence is now a commonly used method for detecting scale-dependent relationships between time series. In this study, the concept of wavelet coherence is generalized to higher-order wavelet coherence methods that quantify the relationship between higher-order statistical moments associated with two time series. The methods are applied to the El Niño–Southern Oscillation (ENSO) and the Indian monsoon to show that the ENSO–Indian monsoon relationship is impacted by ENSO nonlinearity.