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The goal of the proposed research is to develop better models of coral disease outbreak risk across the western tropical Pacific Ocean and embed these improved forecasts into the NOAA Coral Reef Watch decision support system (DSS). The current DSS was developed based on ~50 km SST data, and it assesses coral disease risk for the Great Barrier Reef and the Hawaiian archipelago using (i) a Seasonal Outlook from winter-time conditions that is (ii) updated in near real-time through the summer period. The ecological models used in the experimental disease risk DSS were derived by assessing the relationship between sea surface temperature (SST) anomalies and a single coral disease, Acropora white syndrome, on the Great Barrier Reef. We propose to improve these disease forecasts by (1) increasing the spatial resolution of SST-based predictions tools to 5 km, through application of NASA/NOAA satellite products, and expanding the application to several different coral diseases, host species and regions; (2) incorporating Short-Term Forecasts (four-month projections) of SST to augment the post-winter risk; (3) incorporating ocean color data from NASA/NOAA satellite products into the models, if robust relationships are found; and (4) undertaking additional coral disease observations, using targeted surveys and innovative bioassays that provide measurements with enhanced sensitivity. The disease forecasting models will be developed for locations in the western tropical Pacific Ocean that have existing long-term (~decade-long) observations of coral disease (i.e., Hawaii, Australia, US affiliated Pacific Islands), but the approach could subsequently be replicated in other coral reef regions. The proposed research addresses several goals of the Earth Science Research Program by developing a system to better predict changes in coral health in the face of ongoing climate change, and enabling researchers, managers and the public to use these forecasting models to better understand and respond to future disease outbreaks. This project specifically addresses the ROSES 2016 research announcement A.46 section 3.1.3, Managing Marine Ecosystems in a Time of Changing Climate through Better Forecasts, by using time series of biological observations (14 years of coral health surveys, physiological data from bioassays) and time series of climate observations (e.g., sea surface temperature anomalies, chlorophyll-a concentrations) to develop an ecological modeling framework that predicts coral disease risk based on ongoing satellite-derived inputs and accounts for uncertainties in climate-disease relationships and uncertainties in the estimates of disease risk.