Geoscientific Model Development (Mar 2018)

Global high-resolution simulations of tropospheric nitrogen dioxide using CHASER V4.0

  • T. Sekiya,
  • K. Miyazaki,
  • K. Miyazaki,
  • K. Ogochi,
  • K. Sudo,
  • K. Sudo,
  • M. Takigawa

DOI
https://doi.org/10.5194/gmd-11-959-2018
Journal volume & issue
Vol. 11
pp. 959 – 988

Abstract

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We evaluate global tropospheric nitrogen dioxide (NO2) simulations using the CHASER V4.0 global chemical transport model (CTM) at horizontal resolutions of 0.56, 1.1, and 2.8°. Model evaluation was conducted using satellite tropospheric NO2 retrievals from the Ozone Monitoring Instrument (OMI) and the Global Ozone Monitoring Experiment-2 (GOME-2) and aircraft observations from the 2014 Front Range Air Pollution and Photochemistry Experiment (FRAPPÉ). Agreement against satellite retrievals improved greatly at 1.1 and 0.56° resolutions (compared to 2.8° resolution) over polluted and biomass burning regions. The 1.1° simulation generally captured the regional distribution of the tropospheric NO2 column well, whereas 0.56° resolution was necessary to improve the model performance over areas with strong local sources, with mean bias reductions of 67 % over Beijing and 73 % over San Francisco in summer. Validation using aircraft observations indicated that high-resolution simulations reduced negative NO2 biases below 700 hPa over the Denver metropolitan area. These improvements in high-resolution simulations were attributable to (1) closer spatial representativeness between simulations and observations and (2) better representation of large-scale concentration fields (i.e., at 2.8°) through the consideration of small-scale processes. Model evaluations conducted at 0.5 and 2.8° bin grids indicated that the contributions of both these processes were comparable over most polluted regions, whereas the latter effect (2) made a larger contribution over eastern China and biomass burning areas. The evaluations presented in this paper demonstrate the potential of using a high-resolution global CTM for studying megacity-scale air pollutants across the entire globe, potentially also contributing to global satellite retrievals and chemical data assimilation.