Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness

Blockley, Edward W.; Peterson, K. Andrew

doi:https://doi.org/10.5194/tc-12-3419-2018

Articles | Volume 12, issue 11

https://doi.org/10.5194/tc-12-3419-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-12-3419-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 11

Research article

|

30 Oct 2018

Research article |

| 30 Oct 2018

Improving Met Office seasonal predictions of Arctic sea ice using assimilation of CryoSat-2 thickness

Edward W. Blockley and K. Andrew Peterson

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Final revised paper (published on 30 Oct 2018)
Preprint (discussion started on 18 Apr 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of “Improving Met Office seasonal forecasts of Arctic sea ice using assimilation of CryoSat-2 thickness” by Blockley and Peterson', Anonymous Referee #1, 12 May 2018
- AC2: 'Response to review #1', Ed Blockley, 03 Aug 2018
RC2: 'Review of “Improving Met Office seasonal forecasts of Arctic sea ice using assimilation of CryoSat-2 thickness” by Blockley and Peterson', Anonymous Referee #2, 17 May 2018
- AC1: 'Response to review #2', Ed Blockley, 03 Aug 2018

Peer-review completion

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

AR by Ed Blockley on behalf of the Authors (24 Aug 2018) Author's response Manuscript

ED: Publish as is (07 Sep 2018) by Joseph MacGregor

Short summary

Arctic sea-ice prediction on seasonal time scales is becoming increasingly more relevant to society but the predictive capability of forecasting systems is low. Several studies suggest initialization of sea-ice thickness (SIT) could improve the skill of seasonal prediction systems. Here for the first time we test the impact of SIT initialization in the Met Office's GloSea coupled prediction system using CryoSat-2 data. We show significant improvements to Arctic extent and ice edge location.