Arctic Cold-Air Outbreak Mixed-Phase Cloud Characteristics, Processes and Impacts in Observations and Models

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，以便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。 该项目将利用对混合相云的遥感观测来描述其作为云演变函数的液体和冰之间的分隔，并进一步利用受CAESAR约束的大涡尺度模拟来了解确定这种分隔的过程。 该奖项对CAESAR活动的主要补充是G波段蒸汽辐射计对云液态水路径的测量。 研究人员假设，在海冰边缘附近产生的冷空气爆发云是完全液态的，并通过与云形态中反映的大尺度环境参数（气溶胶和动力学）的相互作用，在下游进一步过渡到覆盖冰降水的液态云。 一个相反的假设是，大部分降水也可以发生过冷毛毛雨，可能是由于缺乏冰成核粒子（INPs）。该项目的主要资金来自物理和动力气象学计划，部分资金来自北极自然科学计划。 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。

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 in an effort to better understand the characteristics of the cold-air outbreak system, and the Arctic climate system more broadly, in order 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 contribute to the main broader impact goals of the CAESAR campaign.This project will make use of remote sensing observations of mixed-phase clouds to characterize their partitioning between liquid and ice as a function of the cloud evolution, with an additional step of using CAESAR-constrained large-eddy-scale simulations to understand the processes that determine this partitioning. The primary addition to the CAESAR campaign from this award is the measurement of cloud liquid water path from a G-band Vapor Radiometer. The researchers hypothesize that the cold air outbreak clouds produced near the sea ice edge are fully liquid, and transition to liquid cloud overlying ice precipitation further downstream, through interactions with the large-scale environmental parameters (aerosol and dynamical) that are reflected in the cloud morphology. A counter-hypothesis is that much of the precipitation can also occur as super-cooled drizzle, potentially due to a lack of ice nucleating particles (INPs).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.