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

NSFGEO-NERC 合作研究：提高海冰的可预测性：海冰预测网络 (SIPN2) 第二阶段

• 批准号: 1748325
• 负责人: Lawrence Hamilton
• 金额: $ 21.59万
• 依托单位: University of New Hampshire
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1748325&HistoricalAwards=false
• 关键词: NSFGEO; NERC; Collaborative; Research; Advancing

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.

NSFGEO-NERC合作研究：推进海冰可预测性：海冰预测网络（SIPN2）第二阶段北极海冰覆盖面积的缩小引起了全世界的关注。在过去十年中，9月份海冰面积下降的趋势加速了，9月份海冰面积最低的10个月份出现在过去十年中。预计到本世纪中叶，夏季的北极将基本无冰。海冰覆盖的减少对北极的生态系统和人类活动有着深远的影响，因此迫切需要在泛北极和区域尺度上推进所有季节的海冰预测。更好地量化海洋热量和气候变化在太平洋部门的作用、新的基于观测的海冰产品和网络活动将促进对北极海冰的季节性可预测性、这种可预测性的局限性以及预测对利益相关者的经济价值的理解。由这笔拨款支持的网络将研究极端海洋表面变暖的起源和影响，以预先调节太平洋北极冰盖，使海冰范围和持续时间持续大幅减少。早期海冰预测网络（SIPN）的一项重要发现是，在严重偏离趋势线的极端年份，对9月份海冰范围的预测往往缺乏技巧。SIPN第二阶段的研究目标是通过采用多学科方法（包括建模、新产品、数据分析、科学网络和利益相关者参与）来提高预测技能。该基金将：利用群落地球系统模型（NCAR CESM）和统计预测工具，研究阿拉斯加北极地区亚季节到季节性海冰可预测性对海洋热量和大尺度大气强迫变化的敏感性，除总范围总结外，还侧重于空间领域；根据方法学和初始化评估海冰展望（SIO）提交的准确性；开发新的基于观测的产品，以改进海冰预测，包括海冰厚度、表面粗糙度、融化池和雪深；评估海冰预测对管理阿拉斯加地区船舶交通和沿海村庄补给的利益相关者的社会经济价值，并通过博客交流、可访问的SIO报告、双月网络研讨会，以及通过使公共数据源对非科学家和科学家都有用，让公众参与北极气候和海冰预测；继续和发展网络活动，生成SIO预测和报告9月份的最小值，如SIPN和扩展SIPN2预测，包括全空间分辨率和新出现的冰异常月份（10月至11月）。这项工作将直接吸引在阿拉斯加创建和使用海冰预测的利益相关者，并提高海冰周围的安全性。SIPN2下的工作还将跟踪公众对海冰的认识和看法，通过可获取的报告、讨论和对非科学家和科学家都有用的公共数据来源，帮助提高理解。利益相关者在研究过程中的参与可能会促进这项工作的产品从研究到运营的快速实施。

项目成果

Moving Sea Ice Prediction Forward Via Community Intercomparison

通过社区比对推进海冰预测

• DOI: 10.1175/bams-d-21-0159.1
• 发表时间: 2021
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: Steele, Michael;Eicken, Hajo;Bhatt, Uma;Bieniek, Peter;Blanchard-Wrigglesworth, Ed;Wiggins, Helen;Turner-Bogren, Betsy;Hamilton, Lawrence;Little, Joseph;Massonnet, François
• 通讯作者: Massonnet, François

Two kinds of polar knowledge

两种极地知识

• DOI: 10.1080/10899995.2020.1838849
• 发表时间: 2020
• 期刊: Journal of Geoscience Education
• 作者: Hamilton, Lawrence C.

Surveys find "two kinds" of public knowledge about polar regions

调查发现公众对极地的认知有“两种”

• 发表时间: 2020
• 期刊: Witness the Arctic
• 作者: Hamilton, Lawrence C.

Summer extreme cyclone impacts on Arctic sea ice

夏季极端气旋对北极海冰的影响

• DOI: 10.1175/jcli-d-19-0925.1
• 发表时间: 2021
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: Lukovich, J. V.;Stroeve, Julienne;Crawford, Alex;Hamilton, Lawrence;Tsamados, Michel;Heorton, Harry;Massonnet, François
• 通讯作者: Massonnet, François

1,000 Predictions: What's New and What's Old in a Retrospective Analysis of the Sea Ice Outlook, 2008-2020

1,000 个预测：2008-2020 年海冰展望回顾性分析中的新旧内容

• 发表时间: 2020
• 期刊: American Geophysical Union
• 作者: Hamilton, Lawrence C.