We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Bright Prospects for Arctic Sea Ice Prediction on Subseasonal Time Scales.
- Authors
Zampieri, Lorenzo; Goessling, Helge F.; Jung, Thomas
- Abstract
With retreating sea ice and increasing human activities in the Arctic come a growing need for reliable sea ice forecasts up to months ahead. We exploit the subseasonal‐to‐seasonal prediction database and provide the first thorough assessment of the skill of operational forecast systems in predicting the location of the Arctic sea ice edge on these time scales. We find large differences in skill between the systems, with some showing a lack of predictive skill even at short weather time scales and the best producing skillful forecasts more than 1.5 months ahead. This highlights that the area of subseasonal prediction in the Arctic is in an early stage but also that the prospects are bright, especially for late summer forecasts. To fully exploit this potential, it is argued that it will be imperative to reduce systematic model errors and develop advanced data assimilation capacity. Plain Language Summary: The need for reliable forecasts for the sea ice evolution from weeks to months in advance has substantially grown in the last decade. Sea ice forecasts are of critical importance to manage the opportunities and risks that come with increasing socioeconomic activities in the rapidly changing Arctic, which, despite the reduction of the sea ice cover, remains an extreme environment. The position of the sea ice edge is a key parameter for potential forecast users, such as Arctic mariners. However, little is known about the ability of current operational subseasonal forecast systems to predict the evolution of the ice edge. Therefore, we assess for the first time the skill of state‐of‐the‐art forecast systems, using a new verification metric that quantifies the accuracy of the ice edge position in a meaningful way. Our results demonstrate that subseasonal sea ice predictions are in an early stage, although skillful predictions 1.5 months ahead are already possible. We argue that relatively modest investments into reducing initial state and model errors will lead to major returns in predictive skill. Key Points: The skill in predicting the location of the Arctic sea ice edge differs substantially among subseasonal forecasting systemsThe most skillful system beats climatological forecasts more than 1.5 months ahead, with then highest skills in late summerMajor improvements are possible by reducing errors in initial states and model formulation
- Subjects
ARCTIC Ocean; ARCTIC regions; SEA ice; WEATHER forecasting; SOCIOECONOMIC factors
- Publication
Geophysical Research Letters, 2018, Vol 45, Issue 18, p9731
- ISSN
0094-8276
- Publication type
Article
- DOI
10.1029/2018GL079394