Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observations

Inference of NO<sub>x</sub> emissions (NO+NO<sub>2</sub>) from satellite observations of tropospheric NO<sub>2</sub> column requires knowledge of NO<sub>x</sub> lifetime, usually provided by chemical transport models (CTMs). However, it is known that s...

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Main Authors: R. C. Cohen, R. C. Hudman, L. C. Valin, A. R. Russell
Format: Article
Language:English
Published: Copernicus Publications 2011-11-01
Series:Atmospheric Chemistry and Physics
Online Access:http://www.atmos-chem-phys.net/11/11647/2011/acp-11-11647-2011.pdf
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spelling doaj-6786802d151a416e9cb55dd16f9cb6412020-11-24T20:59:41ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242011-11-011122116471165510.5194/acp-11-11647-2011Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observationsR. C. CohenR. C. HudmanL. C. ValinA. R. RussellInference of NO<sub>x</sub> emissions (NO+NO<sub>2</sub>) from satellite observations of tropospheric NO<sub>2</sub> column requires knowledge of NO<sub>x</sub> 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 NO<sub>2</sub> 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 NO<sub>2</sub> 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 NO<sub>2</sub> 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 NO<sub>2</sub> loss rate.http://www.atmos-chem-phys.net/11/11647/2011/acp-11-11647-2011.pdf
collection DOAJ
language English
format Article
sources DOAJ
author R. C. Cohen
R. C. Hudman
L. C. Valin
A. R. Russell
spellingShingle R. C. Cohen
R. C. Hudman
L. C. Valin
A. R. Russell
Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observations
Atmospheric Chemistry and Physics
author_facet R. C. Cohen
R. C. Hudman
L. C. Valin
A. R. Russell
author_sort R. C. Cohen
title Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observations
title_short Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observations
title_full Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observations
title_fullStr Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observations
title_full_unstemmed Effects of model resolution on the interpretation of satellite NO<sub>2</sub> observations
title_sort effects of model resolution on the interpretation of satellite no<sub>2</sub> observations
publisher Copernicus Publications
series Atmospheric Chemistry and Physics
issn 1680-7316
1680-7324
publishDate 2011-11-01
description Inference of NO<sub>x</sub> emissions (NO+NO<sub>2</sub>) from satellite observations of tropospheric NO<sub>2</sub> column requires knowledge of NO<sub>x</sub> 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 NO<sub>2</sub> 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 NO<sub>2</sub> 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 NO<sub>2</sub> 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 NO<sub>2</sub> loss rate.
url http://www.atmos-chem-phys.net/11/11647/2011/acp-11-11647-2011.pdf
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