Public Health Session: 16th Federation Meeting Jan 4-6, 2006 Notes/Highlights
Public Health Cluster Presentation Notes
Combining Modeling Using Earth Observation Data to Improve Public Health Decisions
- PHAiRS Team
- CCSP Workshop
- Climate Science in Support of Decision Making
PHAiRS team deals with dust in the southwest
- Team has scientists from UNM, UA -- Public Health partners include: City of Lubbock Dept. of Heatlh, Pima County Dept. of Environmental Quality, Arizona Dept. of Health Services, NM Dept. of Health, ARES Corporation
Public Health Applications in Remote Sensing (PHAiRS)
- Focus on SW, dust storms, respiratory diseases, and syndromic surveillance
- 3 Thrusts
- Assimilate EO data into DREAM (dust generation model) as part of NCEP/Eta forecasting system (source for most weather models)
- Measure incremental improvements to DREAM outputs as inputs to RSVP/SYRIS
- Create collaborations with public health authorities to validate relationships between dust episodes and respiratory complaints
New Mexico/Texas Dust Storm - Dec. 2003
One of the first tasks was to validate the DREAM model as it was written. It was developed for the Mediterranean region, but had to be tested in the Southwest US.
DREAM model requires data from a vast domain, so need to add EO data to narrow the focus.
An addition of just one EO dataset greatly affects the model output.
- Question is then, How much more can we improve the model output if we add more EO datasets?
FPAR, category 253(barren, sparse) is where we want to see how EO data can improve. We need to go back to MODIS science team and tell them we need Category 253 updated.
Enhancing Decision Support Tools
PHAiRS Dust Modeling Client - (Uses EPA Air Quality data and exceedence values) 48-hour dust forecast for Dodge City, Kansas - Model can show for two days in advance what is headed in their direction. This is the sort of info that can be beneficial to Public Health Officials.
- Several improvements are being made to the model itself, and hopefully improvements to the data assimilated.
Relevance to CCSP
