An Automatic Recognition Method for Airflow Field Structures of Convective Systems Based on Single Doppler Radar Data

Abstract

Airflow structures within convective systems are important predictors of damaging convective disasters. To automatically recognize different kinds of airflow structures (the convergence, divergence, cyclonic rotation, and anticyclonic rotation) within convective systems, an airflow structure recognition method is proposed, in this paper, based on a regular hexagonal template. On the basis of single Doppler radar data, the template is designed according to the appearance model of airflows in radial velocity maps. The proposed method is able to output types and intensities of airflow structures within convective systems. In addition, the outputs of the proposed method are integrated into a projection map of the airflow field structure types and intensities (PMAFSTI), which is developed in this work to visualize three-dimensional airflow structures within convective cells. The proposed airflow structure automatic recognition method and the PMAFSTI were tested using three typical cases. Results of the tests suggest the following: (1) At different evolution stages of the convective systems, e.g., growth, split, and dissipation, the three-dimensional distribution of the airflow fields within convective systems could be clearly observed through the PMAFSTI and (2) on the basis of recognizing the structures of the airflow field, the complex airflow field, such as a squall line, could be further divided into several small parts making the analysis of convective systems more scientific and elaborate.

Severe weather events in Moldavia region, on June 23, 2019

“…[…] The types and intensities of these four airflow structures [...] usually have a high correlation with the development and evolution of the convective systems and have significant effects on convective weathers. […] Therefore, it is important to recognize these structures of airflow field" (Wang, 2020). With the help of Doppler radar, the structure of the air flow can be visualized.…”

Voice Recognition and Evaluation of Vocal Music Based on Neural Network

“…Because of the noninvasive and excellent computing power of computers, its evaluation results are objective, reliable, accurate, and efficient. e purpose of objective evaluation of the voice includes the following aspects: (1) to increase the interest in singing; (2) to protect the tender voice; (3) to improve artistic accomplishment; (4) to evaluate the scope and extent of the disease; (5) to try to diagnose the disease; (6) after predicting and correcting the vocalization problem [15][16][17][18][19][20].…”