CAESAR: Characterization of Boundary-Layer Convective Precipitation in Arctic Cold Air Outbreaks

北极气候变化的速度比地球上任何地方都快。气候预测表明，北极将继续变暖，但由于对北极云未来行为的质疑，出现了不确定性。一个主要的不确定性领域是在冷空气爆发期间形成的云层的特性，在冷空气爆发期间，北极冰层上的非常冷的气团在相对温暖的开阔海洋上向南移动。该奖项将有助于分析这些云(和降水)的观测数据，以及将于2024年春季在斯堪的纳维亚半岛北部进行的次北极地区冷空气爆发实验(CAESAR)期间海洋和大气之间的能量交换。凯撒期间收集的观测将用于更好地了解冷空气爆发系统的特征，以及更广泛的北极气候系统，为气候模型和预测提供信息。该项目还将有助于改进对天气灾害的预报，对海军行动、商业航运和沿海社区具有重要意义。更广泛的领域努力包括为学生和职业早期科学家提供重要机会、国际合作和公共宣传。该奖项将为本科生提供参与该项目的机会。此外，教材将被改编用于课堂活动，并计划进行公众宣传活动。这个单独项目的重点是北极冷空气爆发(CAO)期间形成的浅层降水系统。研究人员将使用凯撒期间收集的数据来记录边界层对流(BLC)降水的特征。北极的BLC降水没有充分的记录和特征，预测也很差。该项目的主要目标是记录边界层边界层降水系统的垂直结构，并探讨边界层边界层降水在中尺度组织转变中的作用。凯撒观测数据的一个大子集将与高分辨率中尺度模拟一起使用。具体来说，该项目的任务是：1)开展CAO案例研究，以确定BLC云和降水系统的特征；2)开展综合研究，以描述BLC云和降水的多样性；3)针对选定的CAO案例进行非大涡模拟(LES)运行；4)进行LES模拟和敏感性研究，以验证假设。

Arctic climate is changing at a faster pace than anywhere on Earth. Climate projections indicate that the Arctic will continue to warm, but uncertainties arise due to questions about the future behavior of Arctic clouds. An area of primary uncertainty is the properties of clouds that form during cold-air outbreaks, where very cold airmasses over the Arctic ice move southward over the relatively warm open ocean. This award will help to analyze observational data of these clouds (and precipitation) and the exchange of energy between the ocean and atmosphere during the Cold-Air outbreak Experiment in the Sub-Arctic Region (CAESAR), which will be conducted in Spring 2024 out of northern Scandinavia. The observations collected during CAESAR will be used to better understand the characteristics of the cold-air outbreak system, and the Arctic climate system more broadly, to inform climate models and projections. The project will also help to improve forecasting of weather hazards with significant relevance to naval operations, commercial shipping, and coastal communities. The broader field effort includes significant opportunities for students and early-career scientists, international collaboration, and public outreach. This award will provide opportunities for undergraduate students to be involved in the project. Additionally, materials will be adapted for classroom activities and public outreach activities are planned.The focus of this individual project is on the shallow precipitation systems that form during Arctic cold air outbreaks (CAOs). The researcher will use data collected during CAESAR to document the characteristics of boundary-layer convective (BLC) precipitation. BLC precipitation in the Arctic is inadequately documented and characterized, and poorly predicted. The primary objectives of the project are to document the vertical structure of BLC precipitation systems and to explore the role of BLC precipitation on transitions in mesoscale organization. A large subset of CAESAR observational data will be used alongside high-resolution mesoscale modeling. Specifically, the project tasks are to: 1) Conduct a CAO case study to characterize BLC cloud and precipitation systems, 2) Conduct a composite study to describe the diversity of BLC clouds and precipitation, 3) Perform non-Large Eddy Simulation (LES) runs for selected CAO cases, 4) Perform LES simulations and sensitivity studies to test the hypotheses.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.