Using optimal interpolation to assimilate surface measurements and satellite AOD for ozone and PM_2.5: A case study for July 2011

Abstract

We employed an optimal interpolation (OI) method to assimilate AIRNow ozone/PM2.5 and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) data into the Community Multi-scale Air Quality (CMAQ) model to improve the ozone and total aerosol concentration for the CMAQ simulation over the contiguous United States (CONUS). AIRNow data assimilation was applied to the boundary layer, and MODIS AOD data were used to adjust total column aerosol. Four OI cases were designed to examine the effects of uncertainty setting and assimilation time; two of these cases used uncertainties that varied in time and location, or "dynamic uncertainties." More frequent assimilation and higher model uncertainties pushed the modeled results closer to the observation. Our comparison over a 24-hr period showed that ozone and PM 2.5 mean biases could be reduced from 2.54 ppbV to 1.06 ppbV and from -7.14 µg/m 3 to -0.11 µg/m 3 , respectively, over CONUS, while their correlations were also improved. Comparison to DISCOVER-AQ 2011 aircraft measurement showed that surface ozone assimilation applied to the CMAQ simulation improves regional low-altitude (below 2 km) ozone simulation. Implications: This paper described an application of using optimal interpolation method to improve the model's ozone and PM 2.5 estimation using surface measurement and satellite AOD. It highlights the usage of the operational AIRNow data set, which is available in near real time, and the MODIS AOD. With a similar method, we can also use other satellite products, such as the latest VIIRS products, to improve PM 2.5 prediction.

Evaluating ammonia (NH3) predictions in the NOAA National Air Quality Forecast Capability (NAQFC) using in situ aircraft, ground-level, and satellite measurements from the DISCOVER-AQ Colorado campaign

“…The height of the lowest vertical layer was 8 m above the ground within the DISCOVER-AQ domain. The configuration of the CMAQ and WRF-ARW models within the NAQFC is described in more detail in Tang et al (2015).…”

“…At the time of the Colorado field study, the 2005 NEI was being used, with several major updates as described in Tang et al (2015). For NH 3 , the NEI provides county-level estimates of annual emissions.…”

“…N 2 O is a long-lived absorber of infrared radiation, with a climate change potential approximately 250 times that of CO 2 (IPCC, 2013). The U.S. National Oceanic and Atmospheric Administration (NOAA) is responsible for forecasting elevated levels of air pollution within the National Air Quality Forecast Capability (NAQFC) (Tang et al, 2015). NOAA uses the Community Multiscale Air Quality (CMAQ) model (Byun and Schere, 2006) to simulate atmospheric emissions and transport of NH 3 , and conversion of NH 3 to PM 2.5 , and deposition of NH 3 and NH 4 þ to terrestrial and aquatic ecosystems.…”

Impact of Moderate Resolution Imaging Spectroradiometer Aerosol Optical Depth and AirNow PM2.5 assimilation on Community Multi‐scale Air Quality aerosol predictions over the contiguous United States

“…Schwartz et al [] assimilated AOD data at 18Z and 0Z using data within 3 h for a similar CONUS domain. Tang et al [] assimilated the Terra and Aqua data over the CONUS domain at 17Z and 19Z, respectively. The at each grid point is used to scale all aerosol components throughout the vertical column.…”

GIST-PM-Asia v1: development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia

“…Sequential data assimilation (DA) methods such as OI (optimal interpolation) and 3DVAR (threedimensional variational data assimilation) can use the same number of observations as the STK method. However, they required four data assimilation steps (i.e., 4 h time window for DA) (Tang et al, 2015) to include observations from 09:30 to 13:30, thus greatly increasing the computational cost for daily assimilation.…”