Ecological prediction of the impacts of physical, chemical, biological, and human-induced change on ecosystems and their components encompass a wide range of space scales, time scales, and subject matter. They vary from predicting the occurrence and/or transport of certain species, such as harmful algal blooms, or biogeochemical constituents, such as dissolved oxygen concentrations, to large-scale ecosystem responses and higher trophic levels. The timescales of ecological prediction, including guidance and forecasts, range from nowcasts (hours to days), to intraseasonal and interannual outlooks (weeks to months), to decadal and century projections in climate change scenarios. The spatial scales range from small coastal inlets to basin and even global scale biogeochemical and ecological forecasts. The models that have been used include conceptual, empirical, mechanistic, and hybrid approaches.

This presentation will identify the challenges and progress toward transitioning an experimental model-based ecological prediction into operational guidance and forecasts. Recent efforts target integration of regional ocean, hydrodynamic and hydrological models and leverage weather and water service infrastructure to enable an operational ecological forecast capability for the Chesapeake Bay and its tributaries. One of the challenges is the long-term collaboration required to meet user needs through transition of research and development results to operational applications. Similarly, there is the challenge to ensure that operations and users drive sustained research to improve forecast skill and effectiveness.

The probability of encountering sea nettles (Chrysaora quinquecirrha), a stinging jellyfish, was selected as a pathfinder project. Sea nettles become seasonally abundant in Chesapeake Bay and affect many activities. Recreational boaters, swimmers, commercial waterman, and energy producers currently use the prototype operational sea nettle predictions to help mitigate their impacts. The issuance of bay-wide nowcasts and three-day forecasts of sea nettle probability are generated daily by forcing an empirical habitat model (that predicts the probability of sea nettles) with model-generated real-time and 3-day forecasts of sea-surface temperature (SST) and salinity (SSS). In the first demonstration phase, the SST and SSS fields are generated by a Chesapeake Bay implementation of the Regional Ocean Modeling system (ChesROMS). Transition of the sea nettle nowcasts and forecasts to operations will leverage the Chesapeake Bay Operational Forecast System (CBOFS2), a new, higher resolution implementation of ROMS developed and operated by NOAA's National Ocean Service (NOS) and run operationally at the National Weather Service (NWS) National Centers for Environmental Prediction (NCEP). The transition to operations leverages the NWS infrastructure to produce guidance and enable the dissemination of ecological forecasts and operational service delivery by Weather Forecast Offices, NCEP, NOS and other federal and state partners.

Importantly, this system is flexible and can be readily modified to predict the probability of other important target organisms, such as harmful algal blooms, biogeochemical constituents such as dissolved oxygen concentration, and water-borne pathogens. Extending this initial effort necessarily includes advancement of a regional coastal ocean modeling testbed and proving ground. Such formal collaboration will accelerate transition to operations and increase confidence and use of forecast guidance. The outcome will be improved decision making by emergency and resource managers, scientific researchers and the general public. The presentation will describe partnership plans for this testbed as well as the potential implications for the services and research community.