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A GOOD IDEA (INFUSING DATA INTO ENVIRONMEN TAL APPLICATIONS)-INVITED PRESENTATION
Citation:
NEIL, D., J. SZYKMAN, J. FISHMAN, R. B. PIERCE, J. A. AL-SAADI, AND C. KITTAKA. A GOOD IDEA (INFUSING DATA INTO ENVIRONMEN TAL APPLICATIONS)-INVITED PRESENTATION. Presented at American Meteorological Society, 13th Confereence on Satellite Meteorology, Society, Norfolk, VA, September 21, 2004.
Impact/Purpose:
Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.
Description:
IDEA (Infusing satellite Data into Environmental Applications)is a partnership between researchers in the National Aeronautics and Space Administration (NASA), the United States Environmental Protection Agency (EP A), and the National Oceanic and Atmospheric Administration (NOAA) to improve air quality assessment, management, and prediction by infusing satellite measurements into analyses for public benefit. IDEA is a part of the NASA Earth Science Enterprise Applications Program strategy to demonstrate practical uses ofNASA sponsored observations from remote sensing systems and predictions from scientific research.
During September 2003 our team ofNASA, NOAA, and US EP A researchers demonstrated a prototype tool for improving fine particulate matter(PM2.5) air quality forecasts using satellite aerosol observations. Daily forecast products were disseminated via a web interface to a small group of forecasters, representing state and local air management agencies, and the EP A, to improve their knowledge of synoptic scale
aerosol pollution events. Forecast products were generated from a near-real-time fusion of multiple input data streams. The demonstration was timed to help improve the
accuracy of the EPA's AIRNow next-day PM2.5 Air Quality Index forecast, which began on October 1,2003. Our prototype has been expanded and operated throughout the summer of 2004 to enhance AIRNow AQI forecasts and to support multi-agency efforts to forecast fine particles during field studies. We illustrate the capability of this approach for evaluating large scale aerosol pollution outbreaks with a case study made possible because the daily data fusions are retained in an archive for assessments and retrospective studies.