The benefit of brightness temperature assimilation  for the SMAP Level-4 surface and root-zone soil  moisture analysis

Qiu, Jianxiu; Dong, Jianzhi; Crow, Wade T.; Zhang, Xiaohu; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

doi:https://doi.org/10.5194/hess-25-1569-2021

Articles | Volume 25, issue 3

https://doi.org/10.5194/hess-25-1569-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-25-1569-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 3

Research article

|

29 Mar 2021

Research article |

| 29 Mar 2021

The benefit of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysis

Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy

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Final revised paper (published on 29 Mar 2021)
Preprint (discussion started on 09 Sep 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of hess-2020-407, titled “The added value of brightness temperature assimilation for the SMAP Level-4 surface and root-zone soil moisture analysis over mainland China” by Qiu et al.', Anonymous Referee #1, 28 Sep 2020
- AC1: 'Reply to RC1', Jianxiu Qiu, 05 Nov 2020
RC2: 'Replies to comments from Reviewer #2', Anonymous Referee #2, 13 Oct 2020
- AC2: 'Reply to RC2', Jianxiu Qiu, 05 Nov 2020
RC3: 'Review_of_Qiu_et_al', Clément Albergel, 22 Oct 2020
- AC3: 'Reply to RC3', Jianxiu Qiu, 05 Nov 2020

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (23 Nov 2020) by Bob Su

AR by Jianxiu Qiu on behalf of the Authors (03 Dec 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (14 Dec 2020) by Bob Su

RR by Anonymous Referee #2 (23 Dec 2020)

RR by Anonymous Referee #1 (30 Dec 2020)

ED: Publish subject to revisions (further review by editor and referees) (19 Jan 2021) by Bob Su

AR by Jianxiu Qiu on behalf of the Authors (29 Jan 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (14 Feb 2021) by Bob Su

AR by Jianxiu Qiu on behalf of the Authors (19 Feb 2021)

Short summary

The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to T_b innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.