Public Health Nested, Multi-Resolution Dust Forecast System Feasibility Study

NASA A.19 DiagramExposure to fine particulate dust and adhered endotoxins is an increasing Public Health concern, particularly in the exacerbation of cardiovascular and respiratory diseases. This concern is demonstrated by the deployment (funded by NASA’s REASoN program) of a moderate resolution dust forecasting system (the DREAM ETA model) into the SYRIS syndromic surveillance system, and through ongoing interest by the NM Department of Health in the deployment of dust, pollen, and other environmental data sets into New Mexico’s Environmental Public Health Tracking Network (EPHTN). In support of these systems, more rapidly available and higher spatial resolution data are needed for more localized assessment of particulate exposure for use in epidemiological studies, and for more timely and targeted notification of dust events to at-risk populations.

Researchers at the University of New Mexico, George Mason University, and the University of Arizona had previously been funded by NASA to conduct an Interoperability Testbed project in 2007 to demonstrate key model and data interoperability capabilities of the Dust Regional Atmospheric Model (DREAM ETA); the higher particle- size resolution, 8-bin DREAM ETA model; and the higher spatial resolution DREAM NMM model.

This project builds upon our previous work in the Interoperability Testbed and the PHAiRS projects through two related activities to be undertaken by EDAC and our collaborators at George Mason University (funded by NASA through their 2008 Research Opportunities in Space and Earth Sciences NRA): 1) determining the feasibility of deploying a nested dust forecasting system that consists of initial low spatial resolution (8-bin DREAM ETA) model runs that identify regions for which an HPC-enabled, high-spatial resolution DREAM NMM model should be run; and 2) developing an interoperable framework that uses OGC and W3C standards to enable model and data interoperability to streamline the execution of the model chain and deliver the products of the model runs into public health decision support systems such as EPHTN and SYRIS.