TerrSysMP–PDAF (version 1.0): a modular high-performance data assimilation framework for an integrated land surface–subsurface model

Kurtz, Wolfgang; He, Guowei; Kollet, Stefan J.; Maxwell, Reed M.; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

doi:https://doi.org/10.5194/gmd-9-1341-2016

Articles | Volume 9, issue 4

https://doi.org/10.5194/gmd-9-1341-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-9-1341-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 4

Model description paper

|

11 Apr 2016

Model description paper |

| 11 Apr 2016

TerrSysMP–PDAF (version 1.0): a modular high-performance data assimilation framework for an integrated land surface–subsurface model

Wolfgang Kurtz, Guowei He, Stefan J. Kollet, Reed M. Maxwell, Harry Vereecken, and Harrie-Jan Hendricks Franssen

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Final revised paper (published on 11 Apr 2016)
Supplement to the final revised paper
Preprint (discussion started on 03 Nov 2015)

Interactive discussion

Status: closed

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

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- Supplement

SC C3032: 'Executive Editor Comment on "TerrSysMP-PDAF (version 1.0): A modular high-performance data assimilation framework for an integrated land surface-subsurface model"', Astrid Kerkweg, 23 Nov 2015
- AC C3811: 'Reply to Short Comment (Astrid Kerkweg)', Wolfgang Kurtz, 26 Jan 2016
RC C3307: 'Referee comment', Anonymous Referee #1, 09 Dec 2015
- AC C3813: 'Reply to Anonymous Referee #1', Wolfgang Kurtz, 26 Jan 2016
RC C3377: 'Referee comment', Anonymous Referee #2, 16 Dec 2015
- AC C3826: 'Reply to Anonymous Referee #2', Wolfgang Kurtz, 26 Jan 2016
SC C3415: 'referee comment', Kao-Shen Chung, 19 Dec 2015
- AC C3834: 'Reply to Short Comment (Kao-Shen Chung)', Wolfgang Kurtz, 26 Jan 2016
SC C3418: 'referee comment', Kao-Shen Chung, 19 Dec 2015
- AC C3842: 'Reply to Short Comment (Kao-Shen Chung)', Wolfgang Kurtz, 26 Jan 2016
RC C3424: 'referee comment', Anonymous Referee #3, 21 Dec 2015
- AC C3850: 'Reply to Anonymous Referee #3', Wolfgang Kurtz, 26 Jan 2016

Peer-review completion

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

AR by Wolfgang Kurtz on behalf of the Authors (23 Feb 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (24 Feb 2016) by Min-Hui Lo

RR by Anonymous Referee #1 (06 Mar 2016)

Suggestions for revision or reasons for rejection

Overall, the revisions have made the paper clearer and better. However, there were two changes in the Introduction that I do not agree with. Once the authors revise the manuscript based on the two comments below, I believe the paper is worth publishing:

ln. 135. You write " MIKE SHE has simplified vegetation compared to other models."
It depends on the model setup. MIKE SHE has the option of using a SVAT model which can calculate actual ET from standard meteorological and vegetation data. For description see: Graham DN, Butts MB. Flexible, integrated watershed modeling with MIKE SHE. In: Singh VP, Frevert DK, editors. Watershed Models. CRC Press, Boca Raton, 25 Florida, USA; 2005. 245–272.
There is also an assimilation study using the SVAT model in MIKE SHE: Ridler ME, Madsen H, Stisen S, Bircher S, Fensholt R., Assimilation of SMOS derived soil moisture in a fully integrated hydrological and soil‐vegetation‐atmosphere transfer model in Western Denmark. Water Resources Research. 2014, 50(11):8962-81.

ln. 139. You write "Additionally, the above mentioned data assimilation frameworks do not provide the possibility to perform joint state-parameter estimation."
This is not true. In the paper you reference (Ridler et al., 2014) it is stated: "The framework is designed to grant users access to numerous complex assimilation algorithms, uncertainty models, and distance based regularization techniques, for state or joint state-parameter updating, with a minimal amount of programming". Furthermore, joint state-parameter updating was done in MIKE SHE in: Rasmussen J, Madsen H, Jensen KH, Refsgaard JC., Data assimilation in integrated hydrological modeling using ensemble Kalman filtering: evaluating the effect of ensemble size and localization on filter performance. Hydrology and Earth System Sciences. 2015;19(7):2999-3013

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RR by Anonymous Referee #2 (14 Mar 2016)

ED: Publish subject to minor revisions (Editor review) (17 Mar 2016) by Min-Hui Lo

Dear Authors,

I have now received 2 reviews of your manuscript, which are attached for your reference. Please addressed those comments, and I look forward to receiving your revised manuscript. If you have any questions, please contact me.

Yours sincerely,

Min-Hui Lo
Topical Editor,
Geoscientific Model Development

Review #1 comments:
This paper introduces a coupled data assimilation system for computationally-expensive numerical models, which is gaining more and more attention. I feel the authors have addressed the reviewers' comments appropriately and I thus recommend the paper should be accepted as is.

Review #2 comments:
Overall, the revisions have made the paper clearer and better. However, there were two changes in the Introduction that I do not agree with. Once the authors revise the manuscript based on the two comments below, I believe the paper is worth publishing:

ln. 135. You write " MIKE SHE has simplified vegetation compared to other models."
It depends on the model setup. MIKE SHE has the option of using a SVAT model which can calculate actual ET from standard meteorological and vegetation data. For description see: Graham DN, Butts MB. Flexible, integrated watershed modeling with MIKE SHE. In: Singh VP, Frevert DK, editors. Watershed Models. CRC Press, Boca Raton, 25 Florida, USA; 2005. 245–272. There is also an assimilation study using the SVAT model in MIKE SHE: Ridler ME, Madsen H, Stisen S, Bircher S, Fensholt R., Assimilation of SMOS derived soil moisture in a fully integrated hydrological and soil‐vegetation‐atmosphere transfer model in Western Denmark. Water Resources Research. 2014, 50(11):8962-81.

ln. 139. You write "Additionally, the above mentioned data assimilation frameworks do not provide the possibility to perform joint state-parameter estimation."

This is not true. In the paper you reference (Ridler et al., 2014) it is stated: "The framework is designed to grant users access to numerous complex assimilation algorithms, uncertainty models, and distance based regularization techniques, for state or joint state-parameter updating, with a minimal amount of programming". Furthermore, joint state-parameter updating was done in MIKE SHE in: Rasmussen J, Madsen H, Jensen KH, Refsgaard JC., Data assimilation in integrated hydrological modeling using ensemble Kalman filtering: evaluating the effect of ensemble size and localization on filter performance. Hydrology and Earth System Sciences. 2015;19(7):2999-3013

Hide

AR by Wolfgang Kurtz on behalf of the Authors (24 Mar 2016) Author's response Manuscript

ED: Publish as is (29 Mar 2016) by Min-Hui Lo

AR by Wolfgang Kurtz on behalf of the Authors (29 Mar 2016)

Short summary

This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library. Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP. Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.