Vortex Identification across Different Scales

Lisa Schielicke,Patrick Ludwig,Christoph Peter Gatzen

doi:10.3390/atmos10090518

Lisa Schielicke, Patrick Ludwig + Show 1 more

Open Access

https://doi.org/10.3390/atmos10090518

Copy DOI

Abstract

Vortex identification in atmospheric data remains a challenge. One reason is the general presence of shear throughout the atmosphere that interferes with traditional vortex identification methods based on geopotential height or vorticity. Alternatively, kinematic methods can avoid some of the drawbacks of the traditional methods since they compare the rotational and deformational flow parts. In this work, we apply the kinematic vorticity number method ( W k -method) to atmospheric datasets ranging from the synoptic to the convective scales. The W k -method is tested for winter storm Kyrill, a high-impact extratropical cyclone that affected Germany in January 2007. This case is especially challenging for vortex identification methods since it produced a complex wind occurrence associated with a derecho along a narrow cold-frontal rain band and an area of high winds close to the low pressure center. The W k -method is able to identify vortices in differently-resolved datasets and at different height levels in a consistent manner. Additionally, it is able to determine and visualize the storm characteristics. As a result, we discovered that the total positive circulation of the vortices associated with Kyrill remains of similar order across different data sets though the vorticity magnitude of the most intense vortices increases with increasing resolution.

Highlights

A main concern of scientists and forecasters alike is the identification of atmospheric vortices and the analysis of their potential impact
We discovered that the total positive circulation of the vortices associated with Kyrill remains of similar order across different data sets though the vorticity magnitude of the most intense vortices increases with increasing resolution
The vortex identification based on the kinematic vorticity number (Wk -method) and the derivation of vortex properties presented in Sections 3.1 and 3.2 follows and builds on the work of Schielicke et al

Summary

Introduction

A main concern of scientists and forecasters alike is the identification of atmospheric vortices and the analysis of their potential impact. The most common example is the local impact of synoptic-scale low-pressure systems. It is a difficult task to analyze these vortices since multiple scales are involved. To understand the vortex interactions between these scales, we need differently-resolved datasets. A single method of vortex identification, which is independent of the data resolution, is missing so far. Existing meteorological methods usually fail to identify the vertical structure of a vortex in a consistent manner. We will present a kinematic method (Wk -method) that satisfies these two requirements. It unifies existing methods and can be applied to differently-resolved datasets

Methods

Results

Conclusion