High‐Resolution Post‐Process Corrected Satellite AOD

Abstract

Abstract Poor air quality poses a great threat to human health. Accurate high‐resolution satellite remote sensing of atmospheric aerosols would highly benefit satellite‐based air quality estimates. We have developed and validated a post‐process correction and downscaling approach for satellite remote sensing of aerosols. We use NASA's Moderate Resolution Imaging Spectroradiometer aerosol optical depth (AOD) over the Washington D.C.—Baltimore area during the Distributed Regional Aerosol Gridded Observation Networks campaign in 2011 to evaluate our approach. We derive and evaluate the AOD fields at high 250 m resolution. The results show that the post‐process correction approach is suitable for deriving downscaled, high‐resolution AOD estimates and significantly improves the accuracy of the AOD retrievals.

Keywords

• satellite retrieval
• aerosol
• atmosphere
• machine learning
• downscaling
• post‐processing