a case study of aerosol data assimilation with the community multi-scale air quality model over the contiguous united states using 3d-var and optimal interpolation methods
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2017
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Abstract
This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var
assimilation tool originally developed by the National Centers for
Environmental Prediction (NCEP), to improve surface PM2.5
predictions over the contiguous United States (CONUS) by assimilating aerosol
optical depth (AOD) and surface PM2.5 in version 5.1 of the
Community Multi-scale Air Quality (CMAQ) modeling system. An optimal
interpolation (OI) method implemented earlier (Tang et al., 2015) for the
CMAQ modeling system is also tested for the same period (July 2011) over the
same CONUS. Both GSI and OI methods assimilate
surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC,
and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI
and OI generally help reduce the prediction biases and improve correlation
between model predictions and observations. In the GSI experiments,
assimilation of surface PM2.5 (particle matter with
diameter < 2.5 µm) leads to stronger increments in
surface PM2.5 compared to its MODIS AOD assimilation at the
550 nm wavelength. In contrast, we find a stronger OI impact of the
MODIS AOD on surface aerosols at 18:00 UTC compared to the surface
PM2.5 OI method. GSI produces smoother result and yields overall
better correlation coefficient and root mean squared error (RMSE). It should
be noted that the 3D-Var and OI methods used here have several big
differences besides the data assimilation schemes. For instance, the OI uses
relatively big model uncertainties, which helps yield smaller mean biases,
but sometimes causes the RMSE to increase. We also examine and discuss the
sensitivity of the assimilation experiments' results to the AOD forward
operators.
| Reference Key |
tang2017geoscientifica case
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|---|---|
| Authors | ;Y. Tang;Y. Tang;M. Pagowski;M. Pagowski;T. Chai;T. Chai;L. Pan;L. Pan;P. Lee;B. Baker;B. Baker;R. Kumar;L. Delle Monache;D. Tong;D. Tong;D. Tong;H.-C. Kim;H.-C. Kim |
| Journal | international journal of quantum chemistry |
| Year | 2017 |
| DOI |
10.5194/gmd-10-4743-2017
|
| URL | |
| Keywords |
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