Collaborative Research: Improving the Prediction of Sea Ice through Targeted Study of Poorly Parameterized Sea Ice Processes at MOSAiC and Responsive Model Development

合作研究：通过对 MOSAiC 参数化不良的海冰过程进行有针对性的研究和响应模型开发来改进海冰的预测

• 批准号: 1724467
• 负责人: Bonnie Light
• 金额: $ 66.25万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1724467&HistoricalAwards=false
• 关键词: Collaborative; Research; Improving; Prediction; Sea

Climate models project large uncertainty in the rate of future Arctic sea ice loss and its climate impacts. On multi-decadal timescales, this uncertainty is largely due to differences in the strength of feedback processes within the models. For the Arctic system, changes in surface reflection of heat and light (albedo) dominate the feedback process with the most significant departures in the surface heat balance. However, models employ relatively crude representations of many processes that are relevant to surface albedo evolution. To improve model predictions, we need enhanced parameterizations that are informed by the collection and analysis of relevant observations. Better Arctic predictions are particularly critical given the large changes underway and the urgent need to plan for and adapt to changes soon. This project will improve the representation of the sea ice cover and the surface reflection of heat and light (albedo feedback) in climate models through the integration of climate model experiments and field measurements. Sensitivity studies with the Community Earth System Model (CESM) will be used to assess the relative importance of albedo-related parameterization uncertainties. These studies will inform the snow, sea ice, and solar radiation observations conducted as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign. Measurements will then fuel process understanding and parameterization development within CESM. Experiments with the improved CESM will then be performed to determine the effects of upgraded albedo feedback characterization for Earth system predictions. The focus will be on partitioning and fate of solar energy in a seasonal ice system, the role of snow properties in controlling the sea ice mass balance and radiation budget, and processes affecting ice-ocean energy exchange and ice mass and area changes. These are areas for which process understanding is lacking, model parameterizations are crude, and uncertainties have large effects on model projections. By integrating modeling and observational work, the basic process understanding of controls on Arctic solar energy distribution and sea ice mass budgets will be enhanced. The incorporation of this knowledge in improved model process representation will strengthen prediction capabilities and allow for a deeper understanding of the role of the albedo feedback in projected Arctic change. Model developments will be incorporated into the widely-used Los Alamos Community Ice Model (CICE) and made freely available through standard releases of CESM and CICE. This will improve both climate model and operational sea ice forecasting systems with wide-ranging societal implications. Early career polar researchers will be heavily involved in this project, including opportunities for undergraduates, graduate students and post-doctoral scholars to be involved in both field and modeling activities. A year-long sea ice drift experiment also provides an opportunity to capture the imagination and excitement of students and the public. Educational outreach efforts will include developing a network of middle school science classes with national and international participants. Activities will include classroom visits, hands-on measurement activities, data analysis and hypothesis testing. Additional outreach will occur through interactions with local science museums and educational centers.

气候模型对未来北极海冰损失及其气候影响的速度的不确定性很大。在多年时间尺度上，这种不确定性在很大程度上是由于模型中反馈过程的强度差异。对于北极系统，热和光（反照率）的表面反射变化在反馈过程中占据了反馈过程，而表面热平衡中最显着的出发。但是，模型采用与表面反照率演化相关的许多过程的相对粗略表示。为了改善模型预测，我们需要增强的参数化，这些参数因相关观察的收集和分析所告知。鉴于正在进行的巨大变化以及迫切需要计划和适应变化的迫切需求，更好的北极预测尤其重要。 该项目将通过整合气候模型实验和现场测量值来改善气候模型中海冰覆盖物的表示和热和光的表面反射（反照率反馈）。使用社区地球系统模型（CESM）的敏感性研究将用于评估反照率相关参数化不确定性的相对重要性。这些研究将为北极气候研究（Mosaic）田间运动的多学科漂移观测站所进行的雪，海冰和太阳辐射观察提供信息。然后，测量将为CESM内的理解和参数化开发。然后将进行改进的CESM实验，以确定升级的反照率反馈表征对地球系统预测的影响。重点将放在季节性冰系统中太阳能的分配和命运上，雪性特性在控制海冰质量平衡和辐射预算中的作用以及影响冰山能量交换以及冰质量以及面积变化的过程。这些是缺乏过程理解的领域，模型参数化是原始的，不确定性对模型预测具有很大的影响。通过整合建模和观察工作，将增强对北极太阳能分配和海冰质量预算的控制的基本过程。将这种知识纳入改进的模型过程表示将增强预测能力，并可以深入了解反馈反馈在预计的北极变化中的作用。模型开发将纳入广泛使用的Los Alamos社区冰模型（CICE）中，并通过CESM和CICE的标准版本免费提供。这将改善具有广泛社会影响的气候模型和运营海冰预测系统。早期的职业生涯研究人员将大量参与该项目，包括本科生，研究生和博士后学者的机会，可以参与领域和建模活动。为期一年的海冰漂移实验还提供了一个机会，可以捕捉学生和公众的想象力和兴奋。教育外展工作将包括与国家和国际参与者建立中学科学课程网络。活动将包括课堂访问，动手测量活动，数据分析和假设测试。额外的外展将通过与当地科学博物馆和教育中心的互动发生。

项目成果

A neural network-based method for satellite-based mapping of sediment-laden sea ice in the Arctic

• DOI: 10.1016/j.rse.2021.112861
• 发表时间: 2022-03
• 期刊: Remote Sensing of Environment
• 影响因子: 13.5
• 作者: Hisatomo Waga;H. Eicken;B. Light;Y. Fukamachi

Evolution of the microstructure and reflectance of the surface scattering layer on melting, level Arctic sea ice

融化的北极海冰表面散射层的微观结构和反射率的演变

• DOI: 10.1525/elementa.2022.00103
• 发表时间: 2023
• 期刊: Elementa: Science of the Anthropocene
• 作者: Macfarlane, Amy R.;Dadic, Ruzica;Smith, Madison M.;Light, Bonnie;Nicolaus, Marcel;Henna-Reetta, Hannula;Webster, Melinda;Linhardt, Felix;Hämmerle, Stefan;Schneebeli, Martin
• 通讯作者: Schneebeli, Martin

Arctic sea ice albedo: Spectral composition, spatial heterogeneity, and temporal evolution observed during the MOSAiC drift

• DOI: 10.1525/elementa.2021.000103
• 发表时间: 2022-08-04
• 期刊: ELEMENTA-SCIENCE OF THE ANTHROPOCENE
• 影响因子: 3.9
• 作者: Light, Bonnie;Smith, Madison M.;Bailey, David A.
• 通讯作者: Bailey, David A.

Spectral albedo measurements of the sea ice surface during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign in the Central Arctic Ocean, April – September 2020

2020 年 4 月至 9 月，北冰洋中部北极气候研究多学科漂流观测站 (MOSAiC) 活动期间海冰表面的光谱反照率测量

• DOI: 10.18739/a2ft8dk8z
• 发表时间: 2021
• 期刊: NSF Arctic Data Center
• 作者: Smith, Madison;Light, Bonnie;Perovich, Don;Webster, Melinda;Anhaus, Philipp;Clemens-Sewall, David;Linhardt, Felix;Macfarlane, Amy;Raphael, Ian;Bozzato, Debbie
• 通讯作者: Bozzato, Debbie

Near-surface ocean temperature & salinity measurements (using YSI and Castaway) during the summer component of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign in the Central Arctic Ocean, July – September 2020

近地表海洋温度

• DOI: 10.18739/a2tt4fv1g
• 发表时间: 2021
• 期刊: NSF Arctic Data Center
• 作者: Smith, Madison;Bozzato, Deborah;Chamberlain, Emelia J;Dietrich, Ulrike;Droste, Elise;Fong, Allison A.;Light, Bonnie;Linhardt, Felix;Matero, Ilkka;Perovich, Don
• 通讯作者: Perovich, Don