Arctic sea ice in the global eddy-permitting ocean reanalysis ORAP5.
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| Title: | Arctic sea ice in the global eddy-permitting ocean reanalysis ORAP5. |
|---|---|
| Authors: | Tietsche, Steffen s.tietsche@reading.ac.uk, Balmaseda, Magdalena1, Zuo, Hao1, Mogensen, Kristian1 |
| Source: | Climate Dynamics. Aug2017, Vol. 49 Issue 3, p775-789. 15p. |
| Subjects: | Sea ice, Mathematical models of oceanography, Eddy currents (Electric), Atmospheric temperature standard deviations, Seasonal variations in the ocean |
| Geographic Terms: | Arctic regions |
| Abstract: | We discuss the state of Arctic sea ice in the global eddy-permitting ocean reanalysis Ocean ReAnalysis Pilot 5 (ORAP5). Among other innovations, ORAP5 now assimilates observations of sea ice concentration using a univariate 3DVar-FGAT scheme. We focus on the period 1993-2012 and emphasize the evaluation of model performance with respect to recent observations of sea ice thickness. We find that sea ice concentration in ORAP5 is close to assimilated observations, with root mean square analysis residuals of less than 5 % in most regions. However, larger discrepancies exist for the Labrador Sea and east of Greenland during winter owing to biases in the free-running model. Sea ice thickness is evaluated against three different observational data sets that have sufficient spatial and temporal coverage: ICESat, IceBridge and SMOSIce. Large-scale features like the gradient between the thickest ice in the Canadian Arctic and thinner ice in the Siberian Arctic are simulated well by ORAP5. However, some biases remain. Of special note is the model's tendency to accumulate too thick ice in the Beaufort Gyre. The root mean square error of ORAP5 sea ice thickness with respect to ICESat observations is 1.0 m, which is on par with the well-established PIOMAS model sea ice reconstruction. Interannual variability and trend of sea ice volume in ORAP5 also compare well with PIOMAS and ICESat estimates. We conclude that, notwithstanding a relatively simple sea ice data assimilation scheme, the overall state of Arctic sea ice in ORAP5 is in good agreement with observations and will provide useful initial conditions for predictions. [ABSTRACT FROM AUTHOR] |
| Copyright of Climate Dynamics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: Arctic sea ice in the global eddy-permitting ocean reanalysis ORAP5. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tietsche%2C+Steffen%22">Tietsche, Steffen</searchLink><i> s.tietsche@reading.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Balmaseda%2C+Magdalena%22">Balmaseda, Magdalena</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Zuo%2C+Hao%22">Zuo, Hao</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Mogensen%2C+Kristian%22">Mogensen, Kristian</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Climate+Dynamics%22">Climate Dynamics</searchLink>. Aug2017, Vol. 49 Issue 3, p775-789. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Sea+ice%22">Sea ice</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models+of+oceanography%22">Mathematical models of oceanography</searchLink><br /><searchLink fieldCode="DE" term="%22Eddy+currents+%28Electric%29%22">Eddy currents (Electric)</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+temperature+standard+deviations%22">Atmospheric temperature standard deviations</searchLink><br /><searchLink fieldCode="DE" term="%22Seasonal+variations+in+the+ocean%22">Seasonal variations in the ocean</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Arctic+regions%22">Arctic regions</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We discuss the state of Arctic sea ice in the global eddy-permitting ocean reanalysis Ocean ReAnalysis Pilot 5 (ORAP5). Among other innovations, ORAP5 now assimilates observations of sea ice concentration using a univariate 3DVar-FGAT scheme. We focus on the period 1993-2012 and emphasize the evaluation of model performance with respect to recent observations of sea ice thickness. We find that sea ice concentration in ORAP5 is close to assimilated observations, with root mean square analysis residuals of less than 5 % in most regions. However, larger discrepancies exist for the Labrador Sea and east of Greenland during winter owing to biases in the free-running model. Sea ice thickness is evaluated against three different observational data sets that have sufficient spatial and temporal coverage: ICESat, IceBridge and SMOSIce. Large-scale features like the gradient between the thickest ice in the Canadian Arctic and thinner ice in the Siberian Arctic are simulated well by ORAP5. However, some biases remain. Of special note is the model's tendency to accumulate too thick ice in the Beaufort Gyre. The root mean square error of ORAP5 sea ice thickness with respect to ICESat observations is 1.0 m, which is on par with the well-established PIOMAS model sea ice reconstruction. Interannual variability and trend of sea ice volume in ORAP5 also compare well with PIOMAS and ICESat estimates. We conclude that, notwithstanding a relatively simple sea ice data assimilation scheme, the overall state of Arctic sea ice in ORAP5 is in good agreement with observations and will provide useful initial conditions for predictions. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Climate Dynamics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00382-015-2673-3 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 775 Subjects: – SubjectFull: Sea ice Type: general – SubjectFull: Mathematical models of oceanography Type: general – SubjectFull: Eddy currents (Electric) Type: general – SubjectFull: Atmospheric temperature standard deviations Type: general – SubjectFull: Seasonal variations in the ocean Type: general – SubjectFull: Arctic regions Type: general Titles: – TitleFull: Arctic sea ice in the global eddy-permitting ocean reanalysis ORAP5. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tietsche, Steffen – PersonEntity: Name: NameFull: Balmaseda, Magdalena – PersonEntity: Name: NameFull: Zuo, Hao – PersonEntity: Name: NameFull: Mogensen, Kristian IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 09307575 Numbering: – Type: volume Value: 49 – Type: issue Value: 3 Titles: – TitleFull: Climate Dynamics Type: main |
| ResultId | 1 |
