Show simple item record

dc.contributor.authorWang, Yiguo
dc.contributor.authorCounillon, Francois
dc.contributor.authorKeenlyside, Noel
dc.contributor.authorSvendsen, Lea
dc.contributor.authorGleixner, Stephanie
dc.contributor.authorKimmritz, Madlen
dc.contributor.authorDai, Panxi
dc.contributor.authorGao, Yongqi
dc.PublishedWang Y, Counillon F, Keenlyside N, Svendsen L, Gleixner, Kimmritz M, Dai P, Gao Y. Seasonal predictions initialised by assimilating sea surface temperature observations with the EnKF. Climate Dynamics. 2019;19:5777-5797eng
dc.description.abstractThis study demonstrates that assimilating SST with an advanced data assimilation method yields prediction skill level with the best state-of-the-art systems. We employ the Norwegian Climate Prediction Model (NorCPM)—a fully-coupled forecasting system—to assimilate SST observations with the ensemble Kalman filter. Predictions of NorCPM are compared to predictions from the North American Multimodel Ensemble (NMME) project. The global prediction skill of NorCPM at 6- and 12-month lead times is higher than the averaged skill of the NMME. A new metric is introduced for ranking model skill. According to the metric, NorCPM is one of the most skilful systems among the NMME in predicting SST in most regions. Confronting the skill to a large historical ensemble without assimilation, shows that the skill is largely derived from the initialisation rather than from the external forcing. NorCPM achieves good skill in predicting El Niño–Southern Oscillation (ENSO) up to 12 months ahead and achieves skill over land via teleconnections. However, NorCPM has a more pronounced reduction in skill in May than the NMME systems. An analysis of ENSO dynamics indicates that the skill reduction is mainly caused by model deficiencies in representing the thermocline feedback in February and March. We also show that NorCPM has skill in predicting sea ice extent at the Arctic entrance adjacent to the north Atlantic; this skill is highly related to the initialisation of upper ocean heat content.en_US
dc.rightsAttribution CC BYeng
dc.subjectSeasonal predictioneng
dc.subjectAdvanced data assimilationeng
dc.subjectSea ice extenteng
dc.titleSeasonal predictions initialised by assimilating sea surface temperature observations with the EnKFen_US
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright 2019 The Author(s)en_US
dc.source.journalClimate Dynamics
dc.relation.projectNorges forskningsråd: 270733
dc.relation.projectNorges forskningsråd: 229774/E10
dc.relation.projectNordforsk: 76654
dc.relation.projectTrond Mohn stiftelse: BFS2018TMT01
dc.relation.projectNotur/NorStore: NS9039K
dc.relation.projectEU: 648982
dc.relation.projectNotur/NorStore: NS9207K
dc.relation.projectNotur/NorStore: NN9039K
dc.relation.projectNotur/NorStore: NN9385K

Files in this item


This item appears in the following Collection(s)

Show simple item record

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