NSFGEO-NERC Advancing Predictability of Sea Ice: Phase 2 of the Sea Ice Prediction Network (SIPN2)

Loss of the seaice
cover has profound consequences for ecosystems and human activities in the Arctic, so there is an
urgent need to advance sea-ice predictions in all seasons at both the pan-Arctic and regional scales. A key
finding that emerged from the Sea Ice Prediction Network (SIPN) effort is that predictions of September
sea-ice extent tend to have less skill in extreme years that strongly depart from the trend line. The
objective of proposed research under Phase 2 of SIPN (SIPN2) is to improve forecast skill through
adopting a multi-disciplinary approach that includes modeling, new products, data analysis, scientific
networks, and stakeholder engagement. Specifically, the team will: (1) Investigate the sensitivity of
subseasonal-to-seasonal sea-ice predictability in the Alaska Arctic to variations in oceanic heat and largescale
atmospheric forcing using a dynamical model (NCAR CESM) and statistical forecasting tools,
focusing on spatial fields in addition to total extent summaries; (2) Assess the accuracy of Sea Ice
Outlook (SIO) submissions based on methodology and initialization; (3) Develop new observation-based
products for improving sea-ice predictions, including sea-ice thickness, surface roughness, melt ponds,
and snow depth; (4) Evaluate the socio-economic value of sea-ice forecasts to stakeholders who manage
ship traffic and coastal village resupply in the Alaska Sector, and engage the public in Arctic climate and
sea-ice prediction through blog exchanges, accessible SIO reports, bi-monthly webinars, and by making
public data sources useful to non-scientists and scientists alike; and (5) Continue and evolve network
activities to generate SIO forecasts and reporting for September minima as in SIPN and expand SIPN2
forecasts to include full spatial resolution and emerging ice-anomaly-months (October/November).