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

该项目将提高我们预测北冰洋漂浮海冰和海洋演变的能力。为了做到这一点，我们将开发一个计算机模型来研究海洋表面波与海冰如何相互作用，并进行模拟，以改进对热量和盐分如何在海洋中上下移动的预测。这个新的模型将免费分享，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、它的海冰，以及它在变暖的世界中不断变化的行为。该项目将支持几位职业生涯早期的科学家进行培训和研究，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，并充当分隔海洋和大气的屏障。海冰的存在对决定北冰洋现在和将来的温度至关重要。由于波浪，海洋表面也会上下移动，这是表层海水的热和盐与深海接触和混合的主要方式之一。与海浪有关的混合在全球海洋中很重要，但我们目前还不清楚它对海冰地区的影响。这是因为海冰改变了海浪及其运动，影响了表层和深水的混合方式。该项目通过确定与海浪有关的混合在北极发生的时间和地点，并通过了解漂浮的海冰如何影响这种混合的强度来解决这一不确定性。我们将使用小规模的计算机模拟实验，根据观测结果，创建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，该代码模拟各种北极条件下的海洋混合，包括冰和海浪。该代码将广泛帮助北极海洋学家，并将用于俄勒冈州立大学和布朗大学培训海洋模型师的课程。这个项目将支持5名科学生涯早期的人，从一名本科生到两名助理教授。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.