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

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

基本信息

批准号：
NE/R017123/1
负责人：
Julienne Stroeve
金额：
$ 31.03万
依托单位：
University College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FR017123%2F1
关键词：
NSFGEO NERC Advancing Predictability Sea

项目摘要

The shrinking Arctic sea-ice cover has captured the attention of the world. The downward Septembertrend has accelerated over the last decade, with the 10 lowest September sea-ice extents occurring in thelast 10 years. An essentially ice-free Arctic during summer is expected by mid-century. Loss of the seaicecover has profound consequences for ecosystems and human activities in the Arctic, so there is anurgent need to advance sea-ice predictions in all seasons at both the pan-Arctic and regional scales. A keyfinding that emerged from the Sea Ice Prediction Network (SIPN) effort is that predictions of Septembersea-ice extent tend to have less skill in extreme years that strongly depart from the trend line. Theobjective of proposed research under Phase 2 of SIPN (SIPN2) is to improve forecast skill throughadopting a multi-disciplinary approach that includes modeling, new products, data analysis, scientificnetworks, and stakeholder engagement. Specifically, the team will: (1) Investigate the sensitivity ofsubseasonal-to-seasonal sea-ice predictability in the Alaska Arctic to variations in oceanic heat and largescaleatmospheric 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 IceOutlook (SIO) submissions based on methodology and initialization; (3) Develop new observation-basedproducts 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 manageship traffic and coastal village resupply in the Alaska Sector, and engage the public in Arctic climate andsea-ice prediction through blog exchanges, accessible SIO reports, bi-monthly webinars, and by makingpublic data sources useful to non-scientists and scientists alike; and (5) Continue and evolve networkactivities to generate SIO forecasts and reporting for September minima as in SIPN and expand SIPN2forecasts to include full spatial resolution and emerging ice-anomaly-months (October/November).

不断收缩的北极海冰覆盖物吸引了世界的注意。在过去的十年中，九月的下降已经加速了，9月10日的Sea-ice范围发生在Thelast 10年中。预计将在本世纪中叶到夏季实质上是无冰的北极。 SeiceCover的丧失对北极的生态系统和人类活动都产生了深远的影响，因此在泛 - 北极和区域尺度上，所有季节都需要提高海冰预测。从海冰预测网络（SIPN）努力中提出的一个关键发现是，在极端几年中，对Septembersea-Ice范围的预测往往降低了与趋势线的强烈偏离。在SIPN的第2阶段（SIPN2）下，拟议研究的原理是通过支持多学科方法来提高预测技能，该方法包括建模，新产品，数据分析，Scientificnetworks和利益相关者的参与。具体而言，团队将：（1）研究阿拉斯加北极对季节到季节的海上可预测性的敏感性，对使用动力学模型（NCAR CESM）（NCAR CESM）和统计预测工具和统计预测工具，并集中在空间领域的情况下，以及总体范围的概述；（2）根据方法和初始化评估海上冰点（SIO）提交的准确性；（3）开发新的基于观察的产品，以改善海冰预测，包括海冰厚度，表面粗糙度，熔体池塘和雪深；（4）评估海冰预测的社会经济价值对在阿拉斯加领域管理交通和沿海村庄补充的利益相关者，并通过博客交流，可访问的SIO SIO报告，可访问的网络网络和通过Bi Monththly Webinars和Makepublic Data Conce concection and Scientists和科学; （5）继续并发展网络活性，以产生SIO预测并报告9月的最小值，如SIPN中，并扩大了SIPN2Forecasts，以包括完整的空间分辨率和新兴的冰静脉分析（10月/11月）。

项目成果

期刊论文数量（9）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Atmospheric Forcing Drives the Winter Sea Ice Thickness Asymmetry of Hudson Bay

大气强迫导致哈德逊湾冬季海冰厚度不对称

DOI：
10.1029/2019jc015756
发表时间：
2020
期刊：
Oceans
影响因子：
0
作者：
Kirillov S
通讯作者：
Kirillov S

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

Sea-ice information and forecast needs for industry maritime stakeholders

DOI：
10.1080/1088937x.2020.1766592
发表时间：
2020-06
期刊：
Polar Geography
影响因子：
2.6
作者：
P. Wagner;N. Hughes;P. Bourbonnais;J. Stroeve;L. Rabenstein;U. Bhatt;Joe Little;H. Wiggins;A. Fleming
通讯作者：
P. Wagner;N. Hughes;P. Bourbonnais;J. Stroeve;L. Rabenstein;U. Bhatt;Joe Little;H. Wiggins;A. Fleming

Inter-comparison of melt pond products from optical satellite imagery