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dc.contributor.authorIversen, Silje Christine
dc.contributor.authorSperrevik, Ann Kristin
dc.contributor.authorGoux, Olivier
dc.date.accessioned2023-09-04T11:28:13Z
dc.date.available2023-09-04T11:28:13Z
dc.date.issued2023-05-26
dc.description.abstractInfrared (IR) and passive microwave (PMW) satellite sea surface temperature (SST) retrievals are valuable to assimilate into high-resolution regional ocean forecast models. Still, there are issues related to these SSTs that need to be addressed to achieve improved ocean forecasts. Firstly, satellite SST products tend to be biased. Assimilating SSTs from different providers can thus cause the ocean model to receive inconsistent information. Secondly, while PMW SSTs are valuable for constraining models during cloudy conditions, the spatial resolution of these retrievals is rather coarse. Assimilating PMW SSTs into high-resolution ocean models will spatially smooth the modeled SST and consequently remove finer SST structures. In this study, we implement a bias correction scheme that corrects satellite SSTs before assimilation. We also introduce a special observation operator, called the supermod operator, into the Regional Ocean Modeling System (ROMS) four-dimensional variational data assimilation algorithm. This supermod operator handles the resolution mismatch between the coarse observations and the finer model. We test the bias correction scheme and the supermod operator using a setup of ROMS covering the shelf seas and shelf break off Norway. The results show that the validation statistics in the modeled SST improve if we apply the bias correction scheme. We also find improvements in the validation statistics when we assimilate PMW SSTs in conjunction with the IR SSTs. However, our supermod operator must be activated to avoid smoothing the modeled SST structures on spatial scales smaller than twice the PMW SST footprint. Both the bias correction scheme and the supermod operator are easy to apply, and the supermod operator can easily be adapted for other observation variables.en_US
dc.identifier.citationIversen SC, Sperrevik A, Goux. Improving sea surface temperature in a regional ocean model through refined sea surface temperature assimilation. Ocean Science. 2023;19(3):729-744en_US
dc.identifier.cristinIDFRIDAID 2149543
dc.identifier.doi10.5194/os-19-729-2023
dc.identifier.issn1812-0784
dc.identifier.issn1812-0792
dc.identifier.urihttps://hdl.handle.net/10037/30674
dc.language.isoengen_US
dc.publisherCopernicus Publicationsen_US
dc.relation.journalOcean Science
dc.relation.projectIDNorges forskningsråd: 237906en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleImproving sea surface temperature in a regional ocean model through refined sea surface temperature assimilationen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)