Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard

An operational ocean and sea ice forecast model, Barents-2.5, is implemented for short-term forecasting at the coast off northern Norway, the Barents Sea, and the waters around Svalbard. Primary forecast parameters are sea ice concentration (SIC), sea surface temperature (SST), and ocean currents. T...

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Bibliographic Details
Published in:Geoscientific Model Development
Main Authors: Röhrs, Johannes, Gusdal, Yvonne, Rikardsen, Edel S. U., Durán Moro, Marina, Brændshøi, Jostein, Kristensen, Nils Melsom, Fritzner, Sindre, Wang, Keguang, Sperrevik, Ann Kristin, Idžanović, Martina, Lavergne, Thomas, Debernard, Jens Boldingh, Christensen, Kai H.
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2023
Subjects:
article
Verlagsveröffentlichung
Arctic
Barents Sea
Norway
Svalbard
Iceberg*
Northern Norway
Sea ice
Online Access:https://doi.org/10.5194/gmd-16-5401-2023
https://noa.gwlb.de/receive/cop_mods_00068958
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00067363/gmd-16-5401-2023.pdf
https://gmd.copernicus.org/articles/16/5401/2023/gmd-16-5401-2023.pdf
Description
Summary:An operational ocean and sea ice forecast model, Barents-2.5, is implemented for short-term forecasting at the coast off northern Norway, the Barents Sea, and the waters around Svalbard. Primary forecast parameters are sea ice concentration (SIC), sea surface temperature (SST), and ocean currents. The model also provides input data for drift modeling of pollutants, icebergs, and search-and-rescue applications in the Arctic domain. Barents-2.5 has recently been upgraded to include an ensemble prediction system with 24 daily realizations of the model state. SIC, SST, and in situ hydrography are constrained through the ensemble Kalman filter (EnKF) data assimilation scheme executed in daily forecast cycles with a lead time up to 66 h. Here, we present the model setup and validation in terms of SIC, SST, in situ hydrography, and ocean and ice velocities. In addition to the model's forecast capabilities for SIC and SST, the performance of the ensemble in representing the model's uncertainty and the performance of the EnKF in constraining the model state are discussed.

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