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Nowcasting Applications of Geostationary Satellite Hourly Surface PM2.5 Data.
Hai Zhang1, Zigang Wei1, Barron H Henderson2
1I. M. Systems Group at NOAA, College Park, Maryland, USA.
Weather and Forecasting
|August 17, 2023
Summary
Satellite-derived fine particulate matter (PM2.5) estimates offer hourly air quality insights, supplementing ground monitors. These estimates improve public alerts for harmful air quality events.
Area of Science:
- Environmental Science
- Atmospheric Science
- Remote Sensing
Background:
- Ground-based monitors provide limited temporal resolution for fine particulate matter (PM2.5) measurements.
- Satellite aerosol optical depth (AOD) data offers potential for higher temporal resolution PM2.5 estimation.
Purpose of the Study:
- To estimate PM2.5 mass concentration using geostationary satellite AOD data.
- To evaluate the accuracy and utility of hourly and daily PM2.5 estimates derived from satellite data.
Main Methods:
- Utilized NOAA's Advanced Baseline Imager (ABI) AOD data.
- Employed geographically weighted regression for PM2.5 estimation with hourly and daily resolutions.
- Validated estimates against ground-based PM2.5 observations.
Main Results:
- Hourly and daily PM2.5 estimates showed mean biases of -21.4% and -15.3%, respectively.
- Daytime PM2.5 correlated well with daily mean PM2.5 (r > 0.8) across most of the US.
- Satellite-derived estimates identified harmful air quality for 1.8 million people per hour, significantly more than ground observations.
Conclusions:
- Geostationary satellite AOD data can supplement ground monitors for PM2.5 estimation.
- Hourly PM2.5 estimates show promise for air quality alerts and warnings.
- Satellite-based PM2.5 estimates significantly enhance public notification of poor air quality events.
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