Review Reports
- Shaun Lovejoy1 and
- Lenin Del Rio Amador2,*
Reviewer 1: Anonymous Reviewer 2: Jun Du Reviewer 3: Anonymous
Round 1
Reviewer 1 Report (Previous Reviewer 1)
Comments and Suggestions for Authors
CanStoc: A Hybrid Stochastic – GCM System for Monthly, Seasonal and Interannual Predictions
Authors: S Lovejoy and L D R Amador
Review of Meteorology 2531195 article REVISED
Recommendation: Publish after minor revision
Summary:
As in my previous review: The authors combine the results from ensembles of General Circulation Models (GCMs) and empirical stochastic models that are fitted to the global climate to obtain multi month temperature forecasts. The empirical stochastic models remove some of the climate drift biases of the GCMs particularly in the tropics. This improves the skill slightly.
General Comments:
The paper is considerably improved on the first attempt. There are however some minor issues that should be corrected before publication.
Specific Comments:
Title: Use MDPI convention (see above)
L92: so → So
L100: Make link into a reference.
L140-143: Awkward – rephrase.
Equation (1): State that you use the standard gamma function. Using p as a dummy variable is awkward – t’ or sigma might be better. T’ is presumably delT/delp → delT/delt’ in changed notation. T → T(lambda, thi, t) ???
L247: 5.5C CO2 → 5.5C/CO2 ???
L529: Continue onto next line.
References: Correct variable size fonts. Set references in MDPI convention.
Comments for author File: 
Comments.pdf
Author Response
Recommendation: Publish after minor revision
Summary:
As in my previous review: The authors combine the results from ensembles of General Circulation Models (GCMs) and empirical stochastic models that are fitted to the global climate to obtain multi month temperature forecasts. The empirical stochastic models remove some of the climate drift biases of the GCMs particularly in the tropics. This improves the skill slightly.
General Comments:
The paper is considerably improved on the first attempt. There are however some minor issues that should be corrected before publication.
Au: Thanks for the positive evaluation!
Specific Comments:
Title: Use MDPI convention (see above)
L92: so → So
Au: Thanks.
L100: Make link into a reference.
Au: Thanks.
L140-143: Awkward – rephrase.
Au: Thanks.
Equation (1): State that you use the standard gamma function. Using p as a dummy variable is awkward – t’ or sigma might be better. T’ is presumably delT/delp → delT/delt’ in changed notation. T → T(lambda, thi, t) ???
Au: We added the comment about the Gamma function, but we left the “p” as dummy. If instead we use t’, this is reminiscent of the derivative T’ that is also used. Use of primes with two different meanings in the same integrand will be confusing.
L247: 5.5C CO2 → 5.5C/CO2 ???
Au: Thanks.
L529: Continue onto next line.
Au: We didn’t understand.
References: Correct variable size fonts. Set references in MDPI convention.
Au: Thanks.
Reviewer 2 Report (New Reviewer)
Comments and Suggestions for Authors
The concept of macro-weather is an interesting and novel idea as previously proposed by the authors. I totally agree with the authors that “Why forecast the weather in Montreal - or anywhere else - through to Dec. 31st, 2099 if the aim is to project the mean decadal 2090-2100 temperature?”.
In this new study, the authors further put this concept into practical application in a hybrid way by combing physics-based model and stochastic energy-balanced model for longer-range forecasts. The preliminary results look promising. Therefore, I suggest publishing it for further discussion and development.
Lines 50-51: A typo. Please correct this: “(but stochastic but not fractional)”
Author Response
The concept of macro-weather is an interesting and novel idea as previously proposed by the authors. I totally agree with the authors that “Why forecast the weather in Montreal - or anywhere else - through to Dec. 31st, 2099 if the aim is to project the mean decadal 2090-2100 temperature?”.
In this new study, the authors further put this concept into practical application in a hybrid way by combing physics-based model and stochastic energy-balanced model for longer-range forecasts. The preliminary results look promising. Therefore, I suggest publishing it for further discussion and development.
Lines 50-51: A typo. Please correct this: “(but stochastic but not fractional)”
Au: Thanks!
Reviewer 3 Report (New Reviewer)
Comments and Suggestions for Authors
Please see attached file.
Comments for author File: Comments.pdf
Comments on the Quality of English Language
The quality of English language is good.
Author Response
See the attached pdf.
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report (New Reviewer)
Comments and Suggestions for Authors
The detail included in this revised manuscript greatly enhances the message the authors wish to convey.
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors
See attachment
Comments for author File: Comments.pdf
Comments on the Quality of English Language
The article has the feel of a first draft that has not been proof-read by the authors. Too much hype and not enough scientific detail for the reader to gain something from the paper.
Author Response
See the attachment.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for Authors
If this paper is written to propose a new method for monthly, seasonal and interannual predictions, please stick to it and refrain from passing judgement on GCMs general ability to produce valid and accurate climate predictions over time horizons exceeding the purpose of this paper. Hence please rewrite this paper to make this point clear.
Comments on the Quality of English Language
Not necessary.
Author Response
See the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for Authors
This paper attempt to present a new research on how to combine StocSIPS with a classical coupled GCM system (CanSIPS) into a hybrid system (CanStoc) whose skill is better than either. However, it is quite difficult to find out the merit and highlight of this study. The objective and methodology is poorly presented. The design of the numerical experiment and the result is also not adequately introduced. The findings of the research is not quite clear with very weak support and analysis from the datasets the authors had provided.
Comments on the Quality of English Language
Not quite good.
Author Response
See the attachment.
Author Response File: Author Response.pdf