Award Abstract # 1748953
NSFGEO-NERC Collaborative Research: Advancing Predictability of Sea Ice: Phase 2 of the Sea Ice Prediction Network (SIPN2)

NSF Org: OPP
Office of Polar Programs (OPP)
Recipient: THE REGENTS OF THE UNIVERSITY OF COLORADO
Initial Amendment Date: November 13, 2017
Latest Amendment Date: November 13, 2017
Award Number: 1748953
Award Instrument: Standard Grant
Program Manager: Colleen Strawhacker
colstraw@nsf.gov
 (703)292-7432
OPP
 Office of Polar Programs (OPP)
GEO
 Directorate for Geosciences
Start Date: January 1, 2018
End Date: December 31, 2022 (Estimated)
Total Intended Award Amount: $348,211.00
Total Awarded Amount to Date: $348,211.00
Funds Obligated to Date: FY 2018 = $348,211.00
History of Investigator:
  • Mark Serreze (Principal Investigator)
    serreze@kryos.colorado.edu
Recipient Sponsored Research Office: University of Colorado at Boulder
3100 MARINE ST
Boulder
CO  US  80309-0001
(303)492-6221
Sponsor Congressional District: 02
Primary Place of Performance: University of Colorado at Boulder
3100 Marine Street; Room 479
Boulder
CO  US  80303-1058
Primary Place of Performance
Congressional District:
02
Unique Entity Identifier (UEI): SPVKK1RC2MZ3
Parent UEI:
NSF Program(s): ARCSS-Arctic System Science
Primary Program Source: 0100XXXXDB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 1079
Program Element Code(s): 521900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.078

ABSTRACT

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

The shrinking Arctic sea-ice cover has captured the attention of the world. A downward September trend has accelerated over the last decade, with the 10 lowest September sea-ice extents occurring in the last 10 years. An essentially ice-free Arctic during summer is expected by mid-century. Loss of the sea- ice 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 better quantification of the role of oceanic heat and climate variations in the Pacific sector, new observational-based sea-ice products, and network activities will advance understanding of seasonal predictability of Arctic sea ice, the limits of this predictability, and the economic value of forecasts for stakeholders. The network supported by this grant will examine origins and impacts of extreme ocean surface warming in preconditioning the ice cover in the Pacific Arctic for continued major reductions in sea-ice extent and duration.

A key finding that emerged from the earlier 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. This grant will: Investigate the sensitivity of subseasonal-to-seasonal sea-ice predictability in the Alaska Arctic to variations in oceanic heat and large- scale atmospheric forcing using a dynamical model Community Earth System Model (NCAR CESM) and statistical forecasting tools, focusing on spatial fields in addition to total extent summaries; Assess the accuracy of Sea Ice Outlook (SIO) submissions based on methodology and initialization; Develop new observation-based products for improving sea-ice predictions, including sea-ice thickness, surface roughness, melt ponds, and snow depth; 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 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).

This work will directly engage stakeholders that create and use sea-ice forecasts in Alaska and lead to improved safety around sea ice. Work under SIPN2 will also track public awareness and perceptions regarding sea ice, helping to raise understanding through accessible reports, discussions, and public data sources useful to non-scientists and scientists alike. Stakeholder engagement during the research process will potentially facilitate rapid research-to-operations implementation of the products of this work.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Barrett, Andrew P. and Stroeve, Julienne C. and Serreze, Mark C. "Arctic Ocean Precipitation From Atmospheric Reanalyses and Comparisons With North Pole Drifting Station Records" Journal of Geophysical Research: Oceans , v.125 , 2020 https://doi.org/10.1029/2019JC015415 Citation Details
Meier, W.N. and "Assessing uncertainties in sea ice extent climate indicators" Environmental letters , v.14 , 2019 Citation Details
Serreze, Mark C. and Barrett, Andrew P. and Crawford, Alex D. and Woodgate, Rebecca A. "Monthly Variability in Bering Strait Oceanic Volume and Heat Transports, Links to Atmospheric Circulation and Ocean Temperature, and Implications for Sea Ice Conditions" Journal of Geophysical Research: Oceans , v.124 , 2019 https://doi.org/10.1029/2019JC015422 Citation Details

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Intellectual Merit

As the Arctic rapidly changes, providing seasonal-scale predictions of sea ice conditions increases in importance.  Improved predictions can enhance planning for marine-based operations in the Arctic Ocean, including commerical transport,  extraction activities and fishing.  This project brought together an international team of experts as well as stakeholders to explore the skill of seasonal-scale sea ice predictions based on a variety of methods, ranging from the use of statistical models to complex coupled ice ocean models.  One of they key outcomes of this effort was the realization of how difficult it can be to make good predictions.  Work at the University of Colorado highlighed how knowledge of the oceanic heat transport through the Bering Strait can leading to skillful predictions ice sea retreat and advance in the Chukchi Sea, a key region for marine transport.  However,  a fundamental limitation on prediction skill is that sea ice condtions are strongly affected by weather patterns, and weather patterns can only be predicted out to about two weeks. 

Broader Impacts

Skillful seasonal sea ice predictions can provide societal benefit ranging from planning to safety.  An open and transparent process was adopted to encourage broad participation in the effort across stalekolder groups (e.g., crab fishing and indigenous communities) and career levels of participating scientists. Much was learned about how to communicate with and provide information relevant to stakeholders. For example, after one of the project scientists interviewed crab fishery captains about using seasonal sea ice predictions, it became clear that the way we communicate seasonal predictions was not effective and needed to be reimagined.  This project also focused on education, incuding the use of project results in the classroom at the University of Colorado, and the support of a Doctoral Candidate towards completion of her dissertation. 

 


Last Modified: 02/10/2023
Modified by: Mark C Serreze

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