Detailed source term estimation of the atmospheric release for the Fukushima Daiichi Nuclear Power Station accident by coupling simulations of an atmospheric dispersion model with an improved deposition scheme and oceanic dispersion model

Katata, G.; Chino, M.; Kobayashi, T.; Terada, H.; Ota, M.; Nagai, H.; Kajino, M.; Draxler, R.; Hort, M. C.; Malo, A.; Torii, T.; Sanada, Y.

doi:https://doi.org/10.5194/acp-15-1029-2015

Articles | Volume 15, issue 2

https://doi.org/10.5194/acp-15-1029-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/acp-15-1029-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 15, issue 2

Research article

|

30 Jan 2015

Research article |

| 30 Jan 2015

Detailed source term estimation of the atmospheric release for the Fukushima Daiichi Nuclear Power Station accident by coupling simulations of an atmospheric dispersion model with an improved deposition scheme and oceanic dispersion model

G. Katata, M. Chino, T. Kobayashi, H. Terada, M. Ota, H. Nagai, M. Kajino, R. Draxler, M. C. Hort, A. Malo, T. Torii, and Y. Sanada

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Final revised paper (published on 30 Jan 2015)
Supplement to the final revised paper
Preprint (discussion started on 05 Jun 2014)
Supplement to the preprint

Interactive discussion

Status: closed

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

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RC C4618: 'Interactive comment on Katata et al 2014', Anonymous Referee #1, 09 Jul 2014
- AC C9160: 'Response to Ref. 1', Genki Katata, 14 Nov 2014
RC C4793: 'Comments on the manuscript by Katata et al. (2014)', Anonymous Referee #2, 14 Jul 2014
- AC C9162: 'Response to Ref. 2', Genki Katata, 14 Nov 2014
RC C5012: 'Interactive comment', Anonymous Referee #3, 17 Jul 2014
- AC C9164: 'Response to Ref. 3', Genki Katata, 14 Nov 2014
RC C5119: 'Review', Anonymous Referee #4, 18 Jul 2014
- AC C9166: 'Response to Ref. 4', Genki Katata, 14 Nov 2014

Peer-review completion

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

AR by Genki Katata on behalf of the Authors (14 Nov 2014) Author's response Manuscript

ED: Referee Nomination & Report Request started (18 Nov 2014) by Andreas Stohl

RR by Anonymous Referee #2 (02 Dec 2014)

Suggestions for revision or reasons for rejection

The revised manuscript has been substantially improved in many points. However, there are still some minor problems. I am recommending the minor revision of this manuscript in the following points.

(1) Abstract, Lines 20-21:
This sentence is duplicated with previous sentence (Lines 17-19).

(2) Page 6, lines 16-18:
In general, the meteorological field is important not only in the inverse model but also in the reverse model. What is the difference between both models?

(3) Page 6, lines 27-29:
There are other dataset of time dependent air concentration from 11 to 31 March, such as KEK, RIKEN, JCAC and Tokyo Metropolitan Government. The author should explain the merit of JAEA-Tokai dataset more carefully.

(4) Page 7, lines 2-3:
This sentence is duplicated with previous sentence (Page 6, Lines 27-29).

(5) Page 15, lines 28-30:
In author’s response to Ref.2, “we correct the ratio at Tokai to that at the release point considering the history of air mass by simulation model which can treat the difference of deposition process of gaseous and particulate”. It is better that the sentence like lines 15-16 of page 15 is added in this part.

(6) Page 26, Lines 14-15 and 25-27:
Table 7 shows that the best performance for the regional-scale 137Cs surface deposition over East Japan is obtained in the “This study-Old model” case. For this point, additional explanation is needed.

(7) Page 27, lines 16-18:
As similar to comment (6), Table 7 shows that the best performance for the local-scale 137Cs surface deposition near FNPS1 is obtained in the “This study-Old model” case.

(8) Page 28, lines 1-13:
In addition to comments (6) and (7), the NMSE and FB for local-scale air dose rate with the new source term was worse than those with the previous source term. The authors need to make some comments on negative results.

(9) Figure 4:
The last of caption, “and (d)”, should be removed.

(10) Author’s response to Ref.2, first part of MAJOR COMMENTS:
“Concerning the air concentration data, we did not use them for validation using WSPEEDI-II because these are already used for source term estimation. “

-> I agree, but the authors can use other dataset of air concentration for model validation. If the authors hesitate to increase the volume of paper, it is better that the authors prepare a summary table for statistical comparison as supplement.

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RR by Anonymous Referee #1 (08 Dec 2014)

ED: Reconsider after minor revisions (Editor review) (09 Dec 2014) by Andreas Stohl

Dear authors,

I have asked the reviewers to review your manuscript again. Two reviewers responded in time and they both suggested publication. They both have further suggestions, however, which I ask you to accomodate.

A third reviewer has responded off-line but did not submit a full review. That reviewer (in agreement with reviewer #1, and I agree with both of them) suggested that the use of your terms reverse estimation vs. inverse modeling and the discussion of the relative merits of these methods is still not satisfactory.

It is presented as an advantage of the reverse method to work also with only a single data point but this is very misleading and not correct. Inverse modeling would also work with only one data point. However, depending on the uncertainties and the strength of the constraint provided by that data point, a single measurement may be of very limited value. But that limitation is exactly the same for the reverse method. Also with this method, it is not possible to extract more information from a single measurement than what is actually contained in that measurement. In agreement with reviewers #1 and #3 I argue that there is no methodological merit in using your reverse method, as opposed to formal inverse modeling. Inverse modeling provides a more rigid and formal statistical/mathematical framework. The advantage of this framework, of course, only becomes effective when many data points are used. But that doesn't mean that inverse modeling wouldn't also work with a single (or a few) data point(s). In fact, with a single point there would be no difference to your method, except for weighing the uncertainties of that data point against the uncertainty in the prior emissions assumed. And if no a priori knowledge is assumed (infinite uncertainty of the emissions), the methods should be absolutely identical. Thus, your reverse estimation method is an extremely simplified implementation of inverse modeling.

I hope my comments above will help you to address the remaining reviewer comments to further improve your paper. This should not take you much time, and I am looking forward to seeing a revised version of your paper.

Kind regards,

Andreas Stohl

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AR by Genki Katata on behalf of the Authors (12 Dec 2014) Author's response Manuscript

ED: Publish as is (15 Dec 2014) by Andreas Stohl

AR by Genki Katata on behalf of the Authors (17 Dec 2014)

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Short summary

The detailed atmospheric releases during the Fukushima Daiichi Nuclear Power Station accident were estimated using a reverse estimation method with atmospheric and oceanic dispersion models. The major releases occurred on the afternoon of 12 March, midnight of 14 March, the morning and night of 15 March, and the morning of 16 March in 2011. Several atmospheric dispersion models with our new source term reproduced the local and regional patterns of I-131 and Cs-137 deposition and air dose rate.