Link Between Autumnal Arctic Sea Ice and Northern Hemisphere Winter Forecast Skill. Issue 5 (28th February 2020)

• Record Type: Journal Article
• Authors: Acosta Navarro, J. C.; Ortega, P.; Batté, L.; Smith, D.; Bretonnière, P. A.; Guemas, V.; Massonnet, F.; Sicardi, V.; Torralba, V.; Tourigny, E.; Doblas‐Reyes, F. J.
• Is Part Of: Geophysical research letters. Volume 47:Issue 5(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-02-28
• Subjects: winter climate predictions -- Arctic sea ice -- Eurasian climate -- atmospheric teleconnections -- large ensembles; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2019GL086753
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Dynamical forecast systems have low to moderate skill in continental winter predictions in the extratropics. Here we assess the multimodel predictive skill over Northern Hemisphere high latitudes and midlatitudes using four state‐of‐the‐art forecast systems. Our main goal was to quantify the impact of the Arctic sea ice state during November on the sea level pressure (SLP), surface temperature, and precipitation skill during the following winter. Interannual variability of the November Barents and Kara Sea ice is associated with an important fraction of December to February (DJF) prediction skill in regions of Eurasia. We further show that skill related to sea ice in these regions is accompanied with enhanced skill of DJF SLP in western Russia, established by a sea ice‐atmosphere teleconnection mechanism. The teleconnection is strongest when atmospheric blocking conditions in Scandinavia/western Russia in November reduce a systematic SLP bias that is present in all systems. Plain Language Summary: There is a broad range of stakeholders that could benefit from Northern Hemisphere, midlatitude winter climate predictions from dynamical forecast systems. However, a widespread use is currently hindered by important forecast system limitations. The results from this study suggest that autumnal Arctic sea ice state may have an important impact on winter climate forecast capacity in parts of Eurasia. We further show that large ensembles of simulations can be further exploited, by identifying the members with a better representation of certain processes, in this case the teleconnection between Arctic sea ice and the atmospheric circulation, to enhance the prediction skill of temperature and precipitation over the continents. Exploring this approach for other regions and seasons can provide a possible pathway toward more human‐relevant seasonal climate predictions. Key Points: Climate forecast systems have limited predictive capacity at seasonal scales in the Northern Hemisphere midlatitudes Autumnal Barents and Kara Sea ice is likely a source of winter climate predictability in large regions of northern Eurasia Analysis of multimodel initialized predictions suggests that winter predictability in Eurasia is enhanced by a sea ice‐atmosphere linkage