Harmful Algal Bloom Forecasting at NOAA’s National Centers for Coastal Ocean Science: A research to operations to research (R2O2R) approach

Harmful algal blooms (HABs) cause significant economic, social, and ecological impacts to coastal and Great Lakes communities around the United States. As one specific example, a 2018 Karenia brevis (red tide) bloom was estimated to have a $2.7 billion USD impact on the local tourism industry in Florida. As such, coastal managers, industry leaders, and community members need robust HAB early-warning and forecasting products to prepare for potential bloom events, and in the event of a bloom, tools to track HAB location, trajectory, and magnitude. The National Centers for Coastal Ocean Science (NCCOS) within the National Oceanic and Atmospheric Administration (NOAA) is a leader in conducting applied coastal science that provides actionable information to better understand and respond to complex coastal hazards. This presentation will focus on the programmatic approach that NCCOS is taking to develop a sustained operational framework for HAB forecasting to establish a robust research to operations to research (R2O2R) lifecycle for accessible HAB products that will help enhance coastal resilience.

The NCCOS HAB Forecasting Branch (HAB-F) uses novel approaches in remote sensing, numerical modeling, and in situ data integration to develop, operationalize and deliver HAB forecasting and satellite-derived monitoring products to the general public and subscribers. HAB-F has also begun exploring high performance computing within a cloud environment (e.g. AWS, Azure) and is active in discussions on applying the unified forecast system approach to ecological modeling.

Access to HAB early warning systems enables increased coastal resilience and has a measurable economic benefit. For example, a 2018 cyanobacteria bloom in Lake Utah was estimated to have a socioeconomic benefit of $370,000 due to reduced healthcare costs. HAB-F currently produces routine HAB forecasts for western Lake Erie, the Gulf of Mexico, the East Coast of Florida, and the Gulf of Maine, and is collaboratively conducting innovative research to expand the geospatial footprint of the HAB forecasting portfolio (e.g., Chesapeake Bay, Gulf of Alaska, Lake Okeechobee, etc). Ongoing research includes assessing new technologies to incorporate into operational HAB forecast systems (e.g., hyperspectral ocean color sensors), to transition new forecasting capabilities (e.g. the probability of microcystin toxin exceedance), and to conduct time series assessments to understand bloom phenology and the physical drivers/predictors of bloom formation. HAB-F will also integrate results from social and behavioral science studies to optimize the service delivery and communication strategy of HAB forecast products and warnings.