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Volume 11, issue 22
Atmos. Chem. Phys., 11, 11647–11655, 2011
https://doi.org/10.5194/acp-11-11647-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 11, 11647–11655, 2011
https://doi.org/10.5194/acp-11-11647-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 22 Nov 2011

Research article | 22 Nov 2011

Effects of model resolution on the interpretation of satellite NO2 observations

L. C. Valin1, A. R. Russell1, R. C. Hudman1,*, and R. C. Cohen1,2 L. C. Valin et al.
  • 1College of Chemistry, University of California Berkeley, Berkeley, CA 94720, USA
  • 2Department of Earth and Planetary Sciences, University of California Berkeley, Berkeley, CA 94720, USA
  • *now at: Environmental Protection Agency, Region 9, San Francisco, CA 94105, USA

Abstract. Inference of NOx emissions (NO+NO2) from satellite observations of tropospheric NO2 column requires knowledge of NOx lifetime, usually provided by chemical transport models (CTMs). However, it is known that species subject to non-linear sources or sinks, such as ozone, are susceptible to biases in coarse-resolution CTMs. Here we compute the resolution-dependent bias in predicted NO2 column, a quantity relevant to the interpretation of space-based observations. We use 1-D and 2-D models to illustrate the mechanisms responsible for these biases over a range of NO2 concentrations and model resolutions. We find that predicted biases are largest at coarsest model resolutions with negative biases predicted over large sources and positive biases predicted over small sources. As an example, we use WRF-CHEM to illustrate the resolution necessary to predict 10 AM and 1 PM NO2 column to 10 and 25% accuracy over three large sources, the Four Corners power plants in NW New Mexico, Los Angeles, and the San Joaquin Valley in California for a week-long simulation in July 2006. We find that resolution in the range of 4–12 km is sufficient to accurately model nonlinear effects in the NO2 loss rate.

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