Video_1_Greenlandic sea ice products with a focus on an updated operational forecast system.mp4

• Main Authors: Leandro Ponsoni, Mads Hvid Ribergaard, Pia Nielsen-Englyst, Tore Wulf, Jørgen Buus-Hinkler, Matilde Brandt Kreiner, Till Andreas Soya Rasmussen
• Format: Dataset
• Language: unknown
• Published: 2023
• Subjects: Oceanography; Marine Biology; Marine Geoscience; Biological Oceanography; Chemical Oceanography; Physical Oceanography; Marine Engineering; Greenland; sea ice conditions; sea ice edge; forecast; operational system; ocean modelling; satellite; sea ice charts; Greenland Sea; greenlandic; Sea ice
• Online Access: https://doi.org/10.3389/fmars.2023.979782.s001; https://figshare.com/articles/media/Video_1_Greenlandic_sea_ice_products_with_a_focus_on_an_updated_operational_forecast_system_mp4/21989069

Sea ice information has traditionally been associated with Manual Ice Charts, however the demand for accurate forecasts is increasing. This study presents an improved operational forecast system for the Arctic sea ice focusing on the Greenlandic waters. In addition, we present different observational sea ice products and conduct inter-comparisons. First, a re-analysis forced by ERA5 from 2000 to 2021 is evaluated to ensure that the forecast system is stable over time and to provide statistics for the users. The output is similar to the initial conditions for a forecast. Secondly, the sea ice forecast system is tested and evaluated based on two re-forecasts forced by the high resolution ECMWF-HRES forecast for the period from January 2019 to September 2021. Both the re-analysis and the re-forecasts include assimilation of sea surface temperatures and sea ice concentrations. We validate the re-analysis and the re-forecast systems for sea ice concentration against different remotely sensed observational products by computing the Integrated Ice Edge Error metric at the initial conditions of each system. The results reveal that the re-analysis and the re-forecast perform well. However, the summertime retreat of sea ice near the western Greenlandic coast seems to be delayed a few days compared with the observations. Importantly, part of the bias associated with the model representation of the sea ice edge is associated with the observational errors due to limitations in the passive microwave product in summertime and also near the coast. An inter-comparison of the observational sea ice products suggests that the model performance could be improved by assimilation of sea ice concentrations derived from a newly-developed automated sea ice product. In addition, analysis of persistence shows that the re-forecast has better skill than the persistence forecast for the vast majority of the time.