In response to a growing interest in the Arctic in recent years, the number of real-time short-medium range sea ice prediction systems has been increasing, and now includes several systems covering the full Arctic Ocean, for example: the Arctic Cap Nowcast/Forecast System (ACNFS; Posey et al., 2010), Towards an Operational Prediction system for the North Atlantic European coastal Zones (TOPAZ; Bertino and Lisæter, 2008), and the Canadian Centre for Marine and Environmental Prediction’s Global Ice Ocean Prediction System (GIOPS; Smith et al., 2015) and Regional Ice Prediction System (RIPS; Lemieux et al., 2015; Buehner et al., 2013). In addition, numerous ice-ocean hindcasts1 and reanalyses have been made and intercompared through the Arctic Ocean Model Intercomparison Project (AOMIP; Johnson et al., 2007) and the CLIVAR Global Synthesis and Observations Panel (GSOP) Ocean Reanalysis Intercomparison Project (ORA-IP; Balmaseda et al., 2015). Despite this significant effort, it is difficult to ascertain the true skill of these prediction systems and their primary sources of error, as reliable observations are limited and verification techniques tend to vary from one group to another. As a result, the potential benefits of sea ice prediction for various user groups (e.g. national ice services, marine transportation and resource exploitation, coupling with numerical weather prediction) have been hindered by uncertainty regarding the skillfulness of predictions and how best to use them. An intercomparison of sea ice fields from existing systems by the GODAE Oceanview Intercomparison and Validation Task Team (www.godae.org) has been initiated, although a larger coordinated international effort is needed. The upcoming Year of Polar Prediction (YOPP) aims to address these challenges in the context of a broader initiative toward improved polar environmental predictions for both hemispheres.