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The Year of Polar Prediction (YOPP) has the mission to enable a significant improvement in environmental prediction capabilities for the polar regions and beyond, by coordinating a period of intensive observing, modelling, prediction, verification, user- engagement and education activities. The YOPP Core Phase will be from mid-2017 to mid-2019, flanked by a Preparation Phase and a Consolidation Phase. YOPP is a key component of the World Meteorological Organization – World Weather Research Programme (WMO-WWRP) Polar Prediction Project (PPP). The objectives of YOPP are to: 1. Improve the existing polar observing system (better coverage, higher-quality observations); 2. Gather additional observations through field programmes aimed at improving understanding of key polar processes; 3. Develop improved representation of key polar processes in coupled (and uncoupled) models used for prediction; 4. Develop improved (coupled) data assimilation systems accounting for challenges in the polar regions such as sparseness of observational data; 5. Explore the predictability of the atmosphere-cryosphere-ocean system, with a focus on sea ice, on time scales from days to seasons; 6. Improve understanding of linkages between polar regions and lower latitudes and assess skill of models representing these linkages; 7. Improve verification of polar weather and environmental predictions to obtain better quantitative knowledge on model performance, and on the skill, especially for user-relevant parameters; 8. Demonstrate the benefits of using predictive information for a spectrum of user types and services; 9. Provide training opportunities to generate a sound knowledge base (and its transfer across generations) on polar prediction related issues. The PPP Steering Group provides endorsement for projects that contribute to YOPP to enhance coordination, visibility, communication, and networking. This White Paper is based largely on the much more comprehensive YOPP Implementation Plan (WWRP/PPP No. 3 – 2014), but has an emphasis on Arctic observations.

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.