Multi‐system seasonal predictions of Arctic sea ice

Abstract

The utility of multi‐system, coupled model‐based seasonal predictions of Arctic sea ice area and extent is investigated for combined predictions from the Climate Forecast System version 2 (CFSv2) and Canadian Seasonal to Interannual Prediction System (CanSIPS) operational seasonal forecasting systems, which are among the first to have sea ice as a prognostic variable. Forecast skills for predictions of total anomalies and departures from long‐term linear trends are examined both for the individual systems and the combined forecasts, and are compared against simple predictions such as damped anomaly persistence. Results indicate that the tendency for climate forecasts based on combined output from multiple prediction systems to outperform any one system, demonstrated previously for global variables such as temperature and precipitation, is realized for predictions of Arctic sea ice as well.