Abstract

Wind speed is an important meteorological condition affecting the urban environment. Thus, analyzing the typical characteristics of the wind speed diurnal variation is helpful for forecasting pollutant diffusion. Based on the K-means clustering method, the diurnal variation characteristics of the wind speed in Beijing during 2008–2017 are studied, and the spatiotemporal characteristics of the wind speed diurnal variations are analyzed. The results show that there are mainly five to seven clusters of typical characteristics of the wind speed diurnal variation at different stations in Beijing, and the number of clusters near the city is smaller than that in the suburbs. The typical number of the wind speed diurnal variation during 2013–2015 is smaller than that in other periods, which means the anomalous clusters of the diurnal variation are reduced. Besides, the numbers of different clusters in different years are often switched. Especially, the switch between clusters five and six and the switch between clusters six and seven are frequent. Based on the second cluster analysis of the clustering results at the Beijing station, we find 12 clusters of the diurnal variation, including nine clusters of “large in the daytime, while small at night,” two clusters of “monotonous,” and one cluster of “strong wind.” Furthermore, the low-speed clusters of wind mainly locate in the city with a significant increasing trend, while the high-speed clusters and the monotonous clusters of wind locate in the suburbs with a decreasing trend.

Highlights

  • There are significant environmental problems in big cities and industrial areas [1]

  • In “Second Clustering: Typical Characteristics of the Wind Speed Diurnal Variation” section, according to the classification results, a second clustering is carried out to obtain the typical modes of the characteristics of the wind speed diurnal variation in Beijing

  • 3.1.1 Analyses of the Clustering Results at a Single Station Taking Shunyi station as an example, we illustrate the process of the K-means clustering

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Summary

INTRODUCTION

There are significant environmental problems in big cities and industrial areas [1]. Surface meteorological conditions are important factors affecting the air quality [2], and the strong wind is associated with the rapid diffusion of the pollutant [3]. Extracting the typical modes of daily variation of wind speed is helpful to study the appearance time of strong wind. The authors in Ref. 26 proposed a new method to automatically obtain the k value based on the elbow method The application of these new methods makes up the shortcoming of the K-means method, and effectively promotes the development and application of the K-means clustering method. The clustering analysis of characteristics of the wind speed diurnal variation in Beijing is carried out based on the K-means clustering method. In “Second Clustering: Typical Characteristics of the Wind Speed Diurnal Variation” section, according to the classification results, a second clustering is carried out to obtain the typical modes of the characteristics of the wind speed diurnal variation in Beijing. The temporal and spatial variations of the typical modes are analyzed too

DATA AND METHOD
K-Means Clustering Method and Its Improvements
Second Clustering
First Clustering
CONCLUSION AND DISCUSSION
DATA AVAILABILITY STATEMENT
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