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

点击翻译按钮获取中文摘要

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.