CAESAR: Characterizing and Understanding Atmospheric Boundary Layer Fluxes, Structure and Cloud Property Evolution in Arctic Cold Air Outbreaks

CAESAR：描述和理解北极冷空气爆发时的大气边界层通量、结构和云特性演化

• 批准号: 2151075
• 负责人: Zhien Wang
• 金额: $ 84.84万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2151075&HistoricalAwards=false
• 关键词: CAESAR; Characterizing; Understanding; Atmospheric; Boundary

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 provide 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 specific project includes a training component for senior level undergraduate students on field methods and observations that will parallel the planning and execution of the CAESAR campaign.This goal of this project is to use multiple remote sensor and in-situ measurements to (1) characterize Marine Boundary Layer (MBL) fluxes, structure and cloud properties and (2) understand the process controlling the evolution of MBL fluxes, structures and cloud properties during cold-air outbreaks (CAOs). The research team will deploy the Multi-function Airborne Raman Lidar (MARLi) and the nadir-only Airborne Doppler Lidar (ADL) to provide profiles of water vapor, temperature, air vertical velocity, and aerosol/cloud structure below the NSF/NCAR C-130 research aircraft to document MBL thermodynamic and dynamic structures, mixing across the MBL top, and cloud phase and property distributions. Analysis of MARLi and ADL data, combined with other observations and modeling during CAESAR, will allow the team to focus on understanding of how upstream boundary layer stratification and wind, MBL rolls and small-scale vertical motions, and surface fluxes and Atmospheric Boundary Layer (ABL) top entrainment/mixing controls MBL development and evolution during CAOs. In addition, these measurements will address the question of how aerosol, MBL processes, and cloud dynamics (stratiform and convective clouds) impact mixed-phase cloud properties, especially liquid-ice mass partitioning.Primary funding for this project comes from the Physical and Dynamic Meteorology program with partial funding from the Arctic Natural Sciences program. The deployment of observational assets for CAESAR is being funded by the Facilities for Atmospheric Research and Education program.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.

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，但由于对北极云层未来行为的质疑，不确定性也随之增加。 一个主要的不确定性领域是在冷空气爆发期间形成的云的性质，在那里，北极冰层上的非常冷的空气团在相对温暖的开阔海洋上向南移动。 该奖项将有助于提供这些云（和降水）的观测数据以及在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，该实验将于2024年春季在斯堪的纳维亚半岛北方进行。 CAESAR期间收集的观测数据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善对与海军行动、商业航运和沿海社区有重大关系的天气灾害的预报。 更广泛的实地工作包括为学生和早期职业科学家，国际合作和公共宣传的重要机会。 这个具体项目包括对高年级本科生进行实地方法和观测方面的培训，这将与CAESAR活动的规划和执行并行，该项目的目标是使用多个遥感器和现场测量来（1）确定海洋边界层通量、结构和云的特性，（2）了解控制海洋边界层通量演变的过程，在冷空气爆发（CAO）期间的结构和云特性。 研究小组将部署多功能机载拉曼激光雷达（MARLi）和仅用于最低点的机载多普勒激光雷达（ADL），以提供NSF/NCAR C-130研究飞机下方的水汽、温度、空气垂直速度和气溶胶/云结构的剖面，以记录MBL热力学和动力学结构、MBL顶部的混合以及云相和属性分布。 MARLi和ADL数据的分析，结合CAESAR期间的其他观测和建模，将使团队能够专注于了解上游边界层分层和风，MBL卷和小尺度垂直运动，以及表面通量和大气边界层（ABL）顶部夹带/混合如何控制CAO期间MBL的发展和演变。 此外，这些测量将解决如何气溶胶，MBL过程，云动力学（层状云和对流云）的影响混合相云的属性，特别是液态冰的质量partitioning.Primary资金这个项目的问题来自物理和动力气象学计划与北极自然科学计划的部分资金。 CAESAR观测资产的部署由大气研究和教育设施计划资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。