376 Applying Operational GOES-16 Aerosol Optical Depth to Monitor Smoke Aerosols from Canadian Fires

Tuesday, 30 January 2024
Hall E (The Baltimore Convention Center)
Mi Zhou, IMSG at NOAA/NESDIS/STAR, College Park, MD; and I. Laszlo and H. Liu

A real-time Aerosol optical depth (AOD) product is generated at NOAA (National Oceanic and Atmospheric Administration) from the GOES-16 (G-16) Advanced Baseline Imager (ABI). The frequent G-16 observations enable us to track aerosol loadings every 5-10 minutes during daytime hours, contrasting only one or two daily retrievals from polar orbiting sensors. We apply the G-16 AOD to monitor the smoke aerosols from the record-breaking Canadian fires in 2023 over the heavily impacted regions in Canada and the US.

The regional analysis demonstrates that the G-16 AOD captures the high AOD values as observed by the Aerosol Robotic Network (AERONET); its overall statistics are comparable with those from state-of-the-art MODIS and VIIRS aerosol retrievals. At each of more than 10 AERONET sites with sufficient number of ABI-AERONET match-ups, time series of daily mean AODs are generated to identify the timings of smoke episodes. The temporal evolution of the smoke plume on individual days and at sites is then selected to characterize the diurnal variability using 10-minute G-16 AOD and instantaneous AERONET measurements. The ABI AODs are generally able to track the trend of AOD changes and to detect high AOD values from the intense smokes similar to those observed by AERONET. For some locations and days, though G16 over-estimates AOD relative to AERONET; the magnitude of this positive bias is found to be similar among G-16, MODIS and VIIRS at their corresponding temporal sampling. For further investigation, the G-16 retrieved surface reflectances are evaluated with the “truth” derived from atmospheric correction of satellite reflectances using AERONET AOD; the G-16 selected aerosol model are evaluated with AERONET during the events. This analysis demonstrates the capability of ABI AOD to track the AOD changes during aerosol events on sub-hourly time scales and to characterize real-time diurnal cycles at individual stations and days in addition to on an average sense.

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