Skillful seasonal forecasts of Arctic sea ice retreat and advance dates in a dynamical forecast system. Issue 24 (20th December 2016)

• Record Type: Journal Article
• Authors: Sigmond, M.; Reader, M. C.; Flato, G. M.; Merryfield, W. J.; Tivy, A.
• Is Part Of: Geophysical research letters. Volume 43:Issue 24(2016)
• Page Start: 12, 457
• Page End: 12, 465
• Publication Date: 2016-12-20
• Subjects: sea ice -- seasonal prediction; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2016GL071396
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: The need for skillful seasonal forecasts of Arctic sea ice is rapidly increasing. Technology to perform such forecasts with coupled atmosphere‐ocean‐sea ice systems has only recently become available, with previous skill evaluations mainly limited to area‐integrated quantities. Here we show, based on a large set of retrospective ensemble model forecasts, that a dynamical forecast system produces skillful seasonal forecasts of local sea ice retreat and advance dates—variables that are of great interest to a wide range of end users. Advance dates can generally be skillfully predicted at longer lead times (~5 months on average) than retreat dates (~3 months). The skill of retreat date forecasts mainly stems from persistence of initial sea ice anomalies, whereas advance date forecasts benefit from longer time scale and more predictable variability in ocean temperatures. These results suggest that further investments in the development of dynamical seasonal forecast systems may result in significant socioeconomic benefits. Plain Language Summary: As Arctic waters have become increasingly accessible in recent years, there is an urgent need to improve forecasts of Arctic sea ice on seasonal (1–12 month) timescales. Statistical models, traditionally employed to perform such forecasts, may suffer from large errors due to the rapid changes in the Arctic environment. Consequently, creating seasonal forecasts may increasingly depend on the use of dynamical forecast models. Technology to obtain sea ice forecasts with such systems have only recently become available, with previous skill evaluations focused on area‐integrated quantities such as total Arctic sea ice. It is currently not known if skillful seasonal predictions of more user‐relevant local sea ice information can be obtained. Here we show, for the first time, that a dynamical forecast system is able to produce skillful seasonal forecasts of local retreat and advance dates ‐ quantities that are of obvious interest to a large group of end‐users. In addition, we identify physical mechanisms responsible for the obtained skill. Key Points: A dynamical forecast system produces skillful seasonal forecasts of socioeconomically relevant sea ice events Advance dates can generally be skillfully predicted at longer lead times (~5 months on average) than retreat dates (~3 months) Skill of retreat date forecasts mainly stems from persistence, whereas advance date forecasts benefit from predictable ocean temperatures