Articles | Volume 22, issue 23
https://doi.org/10.5194/acp-22-15313-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-15313-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Cluster-based characterization of multi-dimensional tropospheric ozone variability in coastal regions: an analysis of lidar measurements and model results
Claudia Bernier
Department of Earth and Atmospheric Science, University of Houston, Houston, Texas 77004, USA
Department of Earth and Atmospheric Science, University of Houston, Houston, Texas 77004, USA
Guillaume Gronoff
NASA Langley Research Center, Hampton, VA 23666, USA
Science Systems and Application Inc., Hampton, VA 23666, USA
Timothy Berkoff
NASA Langley Research Center, Hampton, VA 23666, USA
K. Emma Knowland
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Goddard Earth Science Technology & Research (GESTAR) II, Morgan State University,Baltimore, Maryland 21251, USA
John T. Sullivan
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Ruben Delgado
Joint Center for Earth Systems Technology, Baltimore, MD 21228, USA
University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Vanessa Caicedo
Joint Center for Earth Systems Technology, Baltimore, MD 21228, USA
University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Brian Carroll
NASA Langley Research Center, Hampton, VA 23666, USA
Joint Center for Earth Systems Technology, Baltimore, MD 21228, USA
Data sets
GEOS-Chem model input files Claudia Bernier https://doi.org/10.7910/DVN/V99LHT
Short summary
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.
Coastal regions are susceptible to variable and high ozone which is difficult to simulate. We...
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