Collaborative Research: Quantifying the effects of Langmuir Turbulence on Sea Ice and The Arctic Ocean

合作研究：量化朗缪尔湍流对海冰和北冰洋的影响

• 批准号: 2146889
• 负责人: Baylor Fox-Kemper
• 金额: $ 17.47万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2146889&HistoricalAwards=false
• 关键词: Collaborative; Research; Quantifying; effects; Langmuir

This project will improve our capability for predicting how floating sea ice and the ocean evolve in the Arctic Ocean. To do this, we will develop a computer model for examining how ocean surface waves interact with sea ice and run simulations to improve predictions of how the heat and salt move up and down in the ocean. This new model will be shared for free, helping other scientists carry out new research into these processes, and making it easier for students to learn about the Arctic Ocean, its sea ice, and its changing behavior in a warming world. The project will support several early-career scientists in their training and research, including two students. Floating sea ice is an important part of the climate system as it reflects sunlight and acts as a barrier that separates the ocean from the atmosphere. The presence of sea ice is crucial in determining how warm the Arctic Ocean is and will become. The ocean surface also moves up and down due to waves, which are one of the main ways that the heat and salt of surface waters contact and mix with the deep ocean. Wave-related mixing is important across the global ocean, but we do not currently understand its impact in regions of sea ice. This is because sea ice changes the waves and their movement, affecting how surface and deep waters mix. This project addresses this uncertainty by identifying when and where wave-related mixing is occurring in the Arctic, and by understanding how floating sea ice impacts the strength of this mixing. We will use small-scale computer modeling experiments, informed by observations, to create a new way to account for this mixing in the global climate models used to predict Earth’s future. As part of this work, we will develop and publicly share a computer code that simulates ocean mixing under various Arctic conditions, including both ice and waves. This code will broadly aid Arctic oceanographers and will be used in classes to train ocean modelers at Oregon State University and Brown University. This project will support 5 people who are early in their scientific career, ranging from an undergraduate student to two assistant professors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将提高我们预测北冰洋浮冰和海洋如何演变的能力。为此，我们将开发一个计算机模型，用于研究海洋表面波浪如何与海冰相互作用，并进行模拟，以改善对海洋中热量和盐分如何上下移动的预测。这个新模型将免费共享，帮助其他科学家对这些过程进行新的研究，并使学生更容易了解北冰洋，其海冰及其在变暖世界中的变化行为。该项目将支持几位早期职业科学家的培训和研究，其中包括两名学生。 漂浮的海冰是气候系统的重要组成部分，因为它反射阳光，并作为将海洋与大气隔开的屏障。海冰的存在对于确定北冰洋现在和将来的温度至关重要。海洋表面也因波浪而上下移动，这是表面沃茨的热量和盐份与深海接触和混合的主要方式之一。与波浪有关的混合在全球海洋中很重要，但我们目前还不了解它在海冰地区的影响。这是因为海冰改变了波浪及其运动，影响了表层和深层沃茨的混合方式。该项目通过确定与波浪有关的混合在北极发生的时间和地点，以及通过了解漂浮海冰如何影响这种混合的强度来解决这种不确定性。我们将使用小规模的计算机模拟实验，通过观察，创造一种新的方法来解释用于预测地球未来的全球气候模型中的这种混合。 作为这项工作的一部分，我们将开发并公开分享一个计算机代码，模拟各种北极条件下的海洋混合，包括冰和波浪。该代码将广泛地帮助北极海洋学家，并将用于俄勒冈州州立大学和布朗大学的海洋建模培训课程。 该项目将支持5人谁是在他们的科学生涯的早期，从本科生到两名助理教授。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。