Fine-scale analysis of a severe hailstorm using crowd-sourced and conventional observations

Meteorological applications

article

Matthew R. Clark¹  Jonathan D. C. Webb³  Peter J. Kirk¹ 

[1] Met Office;School of Earth and Environment, University of Leeds;Tornado and Storm Research Organisation (TORRO)

关键词: mesoanalysis;    hailstorm;    crowd sourced;    user contributed;    automatic weather station (AWS);    time compositing;   

DOI  :  10.1002/met.1715

学科分类：社会科学、人文和艺术（综合）

来源: Wiley

【 摘 要 】

This study aimed to model the noise pollution level in 9th and 11th districts of Mashhad municipality (Vakilabad highway) by using Traffic Noise Model (TNM 2.5). To this end, the equivalent sound level measurement of the 25 high-traffic stations selected along the Vakilabad highway in Mashhad was carried out by the TES-1358 sound level meter, for 6 months and each month for 1 working day in the year’s 2017. Traffic volume data was also measured to level the day by the wood line method and then the total data was introduced to model the traffic noise volume in the area. The assessment of the traffic noise of the study area in the model showed that the average equivalent sound level calculated by the model for the stations measured at Vakilabad highway is 6.51 dB less than the recorded values by the sound meter in the real environment by the average of 78 dB. In addition, the results of this study indicated that the TNM could provide a reasonable prediction of traffic volume and its distribution on the Vakilabad highway in Mashhad, due to providing a similar ranking of areas with low or high noise pollution and also displaying acceptable values of Leq calculated as compared to recorded sound values in the real environment.

【 授权许可】

CC BY|CC BY-NC|CC BY-NC-ND