Clustering Surface Ozone Diurnal Cycles to Understand the Impact of Circulation Patterns in Houston, TX. Issue 23 (4th December 2019)

• Record Type: Journal Article
• Authors: Bernier, Claudia; Wang, Yuxuan; Estes, Mark; Lei, Ruixue; Jia, Beixi; Wang, Sing‐Chun; Sun, Jiajia
• Is Part Of: Journal of geophysical research. Volume 124:Issue 23(2019)
• Page Start: 13457
• Page End: 13474
• Publication Date: 2019-12-04
• Subjects: Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2019JD031725
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: The diurnal cycle of surface ozone is directly influenced by the chemistry and meteorological processes which affect a region. This study uniquely employs a clustering methodology to examine the complete diurnal pattern of surface ozone for the Houston‐Galveston‐Brazoria region and links the identified patterns to meteorological regimes for June, July, and August of 3 years (2011, 2014, and 2015). Four features were implemented into the clustering algorithm: ozone rate of decrease at night, daily minimum before sunrise, rate of increase after sunrise, and an average of afternoon ozone. Four clusters were chosen, ranging from a mostly flat diurnal pattern with low mixing ratios (~20 ppbv) throughout the day (Cluster 1), to a more variable diurnal cycle with very high mixing ratios (>70 ppbv) in the afternoon (Cluster 4). The clusters are found to associate with distinctive circulation patterns and well‐known regional meteorological processes, such as the low‐level jet and Bermuda High. The uneven distribution of the clusters between the years helps elucidate ozone interannual variability due to meteorology: Cluster 4 had 0 days assigned from 2014 due to the greater influence of circulation patterns bringing clean air from the Gulf of Mexico. We show that the clustering method better characterizes ozone variability than the simplistic method of dividing peak ozone into quantiles. With the clustering analysis, we demonstrate that the ozone diurnal pattern holds more value than just peak ozone hours of the day in providing a clearer understanding of ozone variability and associated meteorological processes. Key Points: We developed a new method clustering diurnal ozone patterns that better characterizes ozone variability in Houston than peak ozone alone Clustering was heavily influenced by early morning ozone values and showed a strong relationship to peak afternoon ozone Uneven distributions of clusters between years elucidate interannual ozone variability and link to synoptic meteorological processes