Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F

• Published in: The Cryosphere
• Main Authors: Williams, Timothy, Korosov, Anton, Rampal, Pierre, Ólason, Einar
• Other Authors: Nansen Environmental and Remote Sensing Center Bergen (NERSC), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2021
• Subjects: [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology; [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography; Arctic; Greenland; Greenland Sea; Sea ice; The Cryosphere
• Online Access: https://hal.univ-grenoble-alpes.fr/hal-03405386; https://hal.univ-grenoble-alpes.fr/hal-03405386/document; https://hal.univ-grenoble-alpes.fr/hal-03405386/file/Willliams2021The_Cryosphere.pdf; https://doi.org/10.5194/tc-15-3207-2021

International audience The neXtSIM-F (neXtSIM forecast) forecasting system consists of a stand-alone sea ice model, neXtSIM (neXt-generation Sea Ice Model), forced by the TOPAZ ocean forecast and the ECMWF atmospheric forecast, combined with daily data assimilation of sea ice concentration. It uses the novel brittle Bingham-Maxwell (BBM) sea ice rheology, making it the first forecast based on a continuum model not to use the viscous-plastic (VP) rheology. It was tested in the Arctic for the time period November 2018-June 2020 and was found to perform well, although there are some shortcomings. Despite drift not being assimilated in our system, the sea ice drift is good throughout the year, being relatively unbiased, even for longer lead times like 5 d. The RMSE in speed and the total RMSE are also good for the first 3 or so days, although they both increase steadily with lead time. The thickness distribution is relatively good, although there are some regions that experience excessive thickening with negative implications for the summertime sea ice extent, particularly in the Greenland Sea. The neXtSIM-F forecasting system assimilates OSI SAF sea ice concentration products (both SSMIS and AMSR2) by modifying the initial conditions daily and adding a compensating heat flux to prevent removed ice growing back too quickly. The assimilation greatly improves the sea ice extent for the forecast duration.