Abstract
ABSTRACT In this study, cluster analysis is applied to the daily averaged wind fields and sea-level pressure observed at surface weather stations in Taiwan from January 2013 to March 2018 to classify the synoptic weather patterns and study the characteristics of corresponding air pollutants, including fine particulate matter (PM2.5), coarse particulate matter (PM10), and ozone (O3). The classification identified six weather types: Clusters 1, 2, and 3 (C1–C3), which are typical winter weather types and associated with high air pollutant concentrations—C3, in particular, influenced by weak synoptic weather, is associated with the lowest wind speeds and the highest PM2.5 and PM10 concentrations and represents the most prevalent weather type that is prone to the occurrence of PM2.5 events; C4, which occurs mostly during seasonal transition months and is associated with the highest O3 concentrations; and C5 and C6, which are summer weather types with low air pollutant concentrations. Further analysis of the local wind flow using the 0.3° ERA5 reanalysis dataset and surface-observed wind data indicates that in western Taiwan, the land-sea breeze is embedded within the synoptic weather type of C3, which is favorable to air pollutant accumulation. However, when the prevailing northeasterly wind is obstructed by the Central Mountain Range, southwestern Taiwan, being situated on the leeside of the mountains, often exhibits the worst air pollution due to stagnant wind conditions.
Highlights
Air pollution is an important environmental issue in Taiwan and can be either locally produced or transported long distances from East Asia (Cheng et al, 2012; Chuang et al, 2017)
The results indicate that the inclusion of the sea level pressure (SLP) in the cluster analysis can enhance the distinction between the summer and winter classified weather types; it is included for weather classification in this study
Six weather patterns were identified: Cluster 1 (C1), which corresponds to the intrusion of the Asian continental anticyclone and is affected by the northeasterly monsoonal (NEM) flow; Cluster 2 (C2), which corresponds to the movement of the anticyclone eastward to the eastern coast of China and is affected by the continental high-pressure peripheral circulation; Cluster 3 (C3), which corresponds to a weak synoptic weather pattern and is affected by a weak easterly flow; C4, which corresponds to the weather pattern occurring during seasonal transition months and the presence of a weak NEM flow; Cluster 5 (C5), which corresponds to the westward stretching of the subtropical high-pressure system; and Cluster 6 (C6), which corresponds to the weather pattern associated with a southwesterly flow
Summary
Air pollution is an important environmental issue in Taiwan and can be either locally produced or transported long distances from East Asia (Cheng et al, 2012; Chuang et al, 2017). Identifying the synoptic weather patterns and large-scale circulation patterns represents a useful method of studying air pollution problems (Rainham et al, 2005; Cheng et al, 2013; Vanos et al, 2015; Hsu and Cheng, 2016). Ngan and Byun (2011) applied the two-stage cluster analysis method to classify the synoptic weather patterns over eastern Texas using the 850 hPa wind fields for the 5-month ozone (O3) season (May–September) in the years 2005 and 2006. The results demonstrate the effectiveness of using wind fields for classifying the weather pattern and clearly identified the associated O3 characteristics among the different clusters
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