Articles | Volume 22, issue 23
https://doi.org/10.5194/acp-22-15313-2022
https://doi.org/10.5194/acp-22-15313-2022
Research article
 | 
02 Dec 2022
Research article |  | 02 Dec 2022

Cluster-based characterization of multi-dimensional tropospheric ozone variability in coastal regions: an analysis of lidar measurements and model results

Claudia Bernier, Yuxuan Wang, Guillaume Gronoff, Timothy Berkoff, K. Emma Knowland, John T. Sullivan, Ruben Delgado, Vanessa Caicedo, and Brian Carroll

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Cited articles

Air Quality System: AQS observations data, United States EPA [data set], https://aqs.epa.gov/aqsweb/airdata/download_files.html (last access: 17 December 2020), 2018. 
Aksoy, S. and Haralick, R. M.: Feature normalization and likelihood‐based similarity measures for image retrieval, Pattern Recogn. Lett., 22, 563–582, https://doi.org/10.1016/s0167‐8655(00)00112‐4, 2001. 
Alonso, A. M., Berrendero, J. R., Hernández, A., and Justel, A.: Time Series Clustering Based on Forecast Densities, Comput. Stat. Data An., 51, 762–776., https://doi.org/10.1016/j.csda.2006.04.035, 2006. 
Banta, R. M., Senff, C. J., Nielsen-Gammon, J., Darby, L. S., Ryerson, T. B., Alvarez, R. J., Sandberg, S. P., Williams, E. J., and Trainer, M: A bad air day in Houston, B. Am. Meteorol. Soc., 86, 657–670. https://doi.org/10.1175/BAMS-86-5-657, 2005. 
Bernier, C.: GEOS-Chem model input, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/V99LHT, 2022. 
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Coastal regions are susceptible to variable and high ozone which is difficult to simulate. We developed a method to characterize large datasets of multi-dimensional measurements from lidar instruments taken in coastal regions. Using the clustered ozone groups, we evaluated model performance in simulating the coastal ozone variability vertically and diurnally. The approach allowed us to pinpoint areas where the models succeed in simulating coastal ozone and areas where there are still gaps.
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