Added value of assimilating springtime Arctic sea ice concentration in summer-fall climate predictions

Prediction skill of continental climate in the Northern Hemisphere (NH) midlatitudes is generally limited throughout the year in dynamical seasonal forecast systems. Such limitations narrow the range of possible applications by different stakeholders. Improving the predictive capacity in these regions has been a challenging task. Sea ice is a central component of the Arctic climate system and a local source of climate predictability, yet its state is often not fully constrained in dynamical forecast systems. Using the EC-Earth3 climate model, we study the added value of assimilating observed Arctic sea ice concentration on the NH extratropical climate in retrospective forecasts of summer and fall, initialized every spring over 1992–2019. Predictions in the North Atlantic and Eurasia benefit from better initialization of sea ice in the Atlantic sector of the Arctic in a two-step mechanism. Initially, sea ice influences the central North Atlantic Ocean through an atmospheric bridge that develops in the first forecast weeks, subsequently leading to preserved skill in the sea surface temperatures (SSTs) throughout summer and early fall. Secondly, these long-lasting SST improvements provide better surface boundary conditions for the atmosphere and lead to more skillful predictions of circulation and surface climate in the Euro-Atlantic and Asian regions. In addition, our findings suggest that fully coupled ocean-atmosphere-sea ice models are likely necessary to study linkages between Arctic sea ice and midlatitudes, by better representing the interactions and feedbacks between the different components of the climate system.The data that support the findings of this study are available upon reasonable request from the authors. This work was funded by the European Union projects APPLICATE (Grant 727862), INTAROS (Grant 727890), and ESA/CMUG-CCI3. J C A N received financial support from the Spanish Ministerio de Ciencia, Innovación y Universidades through a Juan de la Cierva personal grant (FJCI-2017-34027). J G-S was supported by the Spanish 'Ramón y Cajal' programme (RYC-2016-21181). All the data were downloaded from their original source, converted to NetCDF in a format designed for efficient analysis and quality checked at several levels. Etienne Tourigny, Pierre-Antoine Bretonnière, Margarida Samsó Cabré, Núria Pérez Zanón and An Chi Ho are acknowledged for their help with technical aspects. We thank the two anonymous reviewers for their valuable comments on the manuscript.Peer ReviewedPostprint (published version