Sensitivity of the midlatitude waveguide to the dynamics and observations of Arctic tropopause-based vortices

红外辐射加热是天气和气候预报模式中的一大不确定性来源，而高影响天气事件往往受到影响这种加热的次天气尺度特征的强烈影响。这项提议将在对流层顶极涡(TPV)遇到急流之前，仔细研究它们内部活跃的具体过程。通过详细分析过程及其与急流的相互作用而获得的更多知识，将通过改善天气和气候预测在数值模式中的表现而导致改进。TPV是独一无二的，因为它们在影响急流之前可以存在很长一段时间，因此是观察和准确表示的关键特征。首席研究人员将发展人的能力，并教学生如何在整个研究范围内推进科学。在研究过程中开发的质量控制数据集将公开提供给研究界，作为可预测性研究的长期工具。拟议的工作将检验这一假设：当对流层顶极涡(TPV)遇到与波导相关的越来越大的垂直切变时，需要辐射的非绝热加热和微弱的变形来维持它们的结构。该项目将使用三种方法：(1)基于下游影响分析TPV的统计特征；(2)分离和识别对TPV发展至关重要的重要物理过程，并通过受控的数值模拟实验在TPV接近波导时保持TPV的强度；以及(3)诊断关键的不确定性，以确定改进数值模型中过程表示的具体方法。试验将使用大气版本的跨尺度预测模式(MPAS)和并行模拟，使用高级天气研究和预报(ARW)模式和数据同化研究试验床(DART)。

Heating due to infrared radiation is a great source of uncertainty in weather and climate prediction models, and high impact weather events are often strongly influenced by sub-synoptic-scale features that affect such heating. This proposal will closely examine specific processes active within tropopause polar vortices (TPVs) before they encounter the jet stream. Improved knowledge gained through detailed analysis of the processes, and their interactions with the jet stream, will lead to improvements in weather and climate prediction by improving their representation in numerical models. TPVs are unique because they can exist for long periods of time before affecting the jet stream, and are therefore a key feature to observe and accurately represent.The principal investigator will develop human capacity and teach students how to advance science through the entire spectrum of research. Quality-controlled datasets, developed during the course of the research, will be made openly available to the research community for use as a long-term tool for predictability studies.The proposed work would test the hypothesis: diabatic heating from radiation, coupled with weak deformation, is required to maintain the structure of tropopause polar vortices (TPVs) as they encounter increasing vertical shear associated with the waveguide. The project will use three approaches: (1) analyzing the statistical characteristics of TPVs based upon downstream impact, (2) isolating and identifying important physical processes important for TPV development and maintaining TPV intensity as they approach the waveguide through controlled numerical modeling experiments, and (3) diagnosing key uncertainties to identify specific methods of improving process representation in numerical models. Experiments will be conducted using the atmospheric version of the Model for Prediction Across Scales (MPAS) and parallel simulations using the Advanced Weather Research and Forecasting (ARW) model with the Data Assimilation Research Testbed (DART).