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测模型中不确定性的一个重要来源，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。 这项建议将仔细研究对流层顶极涡（TPVs）遇到急流之前活跃的特定过程。 通过详细分析这些过程及其与急流的相互作用而获得的更好的知识，将通过改善其在数值模型中的表现而改善天气和气候预测。TPV是独一无二的，因为它们可以在影响急流之前存在很长一段时间，因此是观察和准确表示的关键特征。首席研究员将开发人类能力，并教学生如何通过整个研究领域推进科学。 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。拟议的工作将检验假设：当对流层顶极涡（TPVs）遇到与波导相关的垂直切变增加时，需要来自辐射的非绝热加热加上弱变形来维持其结构。 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）隔离和识别对TPV开发重要的重要物理过程，并通过受控数值模拟实验在TPV接近波导时保持TPV强度，以及（3）诊断关键不确定性，以确定改进数值模型中过程表示的具体方法。 实验将使用跨尺度预测模型（MPAS）的大气版本进行，并使用高级天气研究和预报（ARW）模型与数据同化研究试验台（DART）进行平行模拟。

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).