Transitioning a Chesapeake Bay Ecological Prediction System to Operations January 24, 2012 D. Green 1, C. Brown 1, F. Aikman 1, A. Siebers 1, H. Tolman 1, M. Ji 1, D. Levin 2, C. Friedrichs 3, M. Friedrichs 3, and R. Hood 4 1 NOAA, 2 Washington College, 3 VIMS College of William & Mary, 4 HPL/UMCES University of Maryland

2 Outline Ecological Forecasting Chesapeake Pathfinder Project Next steps

3 Ecological Forecasting for a Weather Ready Nation Predict impacts Biological, chemical, physical, and human- induced changes on ecosystems ecosystem components, and people. Address “what if” questions Resource management Transition science Leverage infrastructure

4 Seamless Suite of Services Local, short term nowcasting and forecasting beach water quality, living resource distribution (oysters, sea nettles), development of harmful algal blooms, pathogens,… Long term scenarios and seasonal outlooks, estimating sea grass restoration, disease outbreaks, eutrophication and hypoxia reduction, recruitment of fisheries species…

Physical Temperature Salinity Current velocity Sea Surface Height Biogeochemical Nutrients Phytoplankton, Zooplankton Dissolved oxygen Organismal Sea Nettles Water-borne pathogens Harmful algal blooms Integrated Science

6 Observations Environmental Modeling Research Ecological Forecasting & Decision Support Tools Local - Regional Products & Services for Stakeholders Partners & Users Enable Informed Decisions System development & partnerships Linking needed components Scaling to local decision making System use and sustainability

7 Pathfinder: Sea Nettle Forecasting Salinity SST Habitat Model 1.Forecast surface salinity and temperature fields 2.Apply habitat model 3.Generate image illustrating the likelihood of encountering sea nettles 4.Disseminate daily and 3-day forecast to users Likelihood of Chrysaora

8 Migration to the NOAA Chesapeake ROMS  UMD/NOAA migrated ecological forecasting models to CBOFS2  Higher resolution allows better bathymetric representation  Improves simulation of physical processes (particularly salinity)  Provides more accurate forcing for our empirical and mechanistic models

9 Transition to Operations Research and monitoring to provide data for developing and validating forecast models (statistical and process models to overlay on environmental variable forecast –Builds on NESDIS/NOS/NMFS/NWS/UMD research, data and observations Operational backbone modeling suite to create forecasts of environmental variables –Leverages NOS-supplied Chesapeake Bay Operational Forecast System (CBOFS2) model and is enabled by NCEP infrastructure –Modeling testbed and proving ground Forecast office that works with regional management agencies and structure (e.g., Chesapeake Bay Program) to ensure utility of and support for forecast –Dissemination of products through NWS and NOS/NMFS offices and information tools

10 Planned Sea Nettle Forecast Concept of Operations

11 Regional Earth System Model-based Operations Fully integrates ecosystem model suite for the Chesapeake Bay and its watershed Assimilates in-situ and satellite-derived data by adapting and coupling existing models Uses coupled air, land, and coastal ocean models in products and services Next Steps Testbed and Proving Ground

12 Regional prediction system can be easily extended to other forecasts: o Harmful algal blooms o Water-borne pathogens o Dissolved oxygen (hypoxia) concentrations o … Prediction system and approach transportable to other regions Conclusion: Its Just the Beginning… Relative abundance of Karlodinium veneficum on 20 April Low: 0- 10, med: cells/ml, high: > 2000 cells/ml. Likelihood of Vibrio vulnificus on 20 April 2011.

13 Background Material

14 Expanding Regional Capabilities Beach/Water Quality – Case Study Issue: Water quality risk due to microbial and chemical contamination threatens human/ecosystem health and economics Solution: Water (beach) quality guidance Operational Concept: Routinely generate forecasts and warnings daily, weekly, seasonal (including lead times) using hydrologic, waves, precipitation, circulation, transport turbidity, nutrients, waste, watershed and land computational models Collaborators: Include state and local managers, scientists, health workers, fishers and regulators Output Product: Near-real time maps and decision support tools showing water quality index and long-term scenarios, bacterial content, water temperature, turbidity, beach closures, habitat suitability, stock assessments, categorical risk assessment Dissemination: Online, Factsheets, and Media Outcome: Actions taken to improve Bay and public health, clean water, promote restoration, land and resource management, adaptation, and research Indicators and Indices

15 Harmful Algal Bloom (Chlorophyll) Monitoring & Forecast System Issue: HABs threaten human health and natural resources Solution: Predict nature, extent, development and movement of HAB species in Bay and its tidal tributaries. Operational Concept: Routinely generate forecasts using data from hydrodynamic computer models and NOAA satellites. Collaborators: Include state natural resource partners Output Product: Near-real time maps showing when and where to expect initiation and landfall Dissemination: Online and Media Outcome: Actions taken to monitor and mitigate HAB effects. Nowcast of K.veneficum abundance (Experimental product)

16 Dissolved Oxygen [DO] Monitoring & Forecast System Issue: Some areas of the Bay have low oxygen levels threatening survival of species. Solution: Predictions and forecasts of hypoxia, including uncertainty related to nutrient loading and river flow Operational Concept: Routinely generate predictions and forecasts on synoptic to seasonal scales using data from hydrodynamic, circulation, watershed, atmospheric and water quality models Collaborators: Include state managers, scientists and fishers Output Product: Maps and decision support tools showing concentration and dead zones, habitat suitability, and marine assessments Dissemination: Online and Media Outcome: Regional actions taken to promote restoration and recovery check.org/forecast/chesapea ke/overview/

17 Living Resource Distribution/Oyster Monitoring & Forecast System Chesapeake Bay Oyster Larvae Tracker (CBOLT) Issue: Oyster populations are at low levels and productivity varies depending on salinity, water quality, habitat conditions, and disease. Solution: Annual forecast of oyster biomass including harvests and other related mortality/disease information Operational Concept: Routinely generate forecasts and outlooks using data from hydrodynamic, circulation, watershed, water quality, atmospheric and ecosystem models Collaborators: Include state managers, scientists and fishers Output Product: Maps and decision support tools showing habitat suitability, stock assessments, management and larvae tracking Dissemination: Online and Media Outcome: Actions taken to promote oyster restoration and disease research

18 Disease Pathogen Progression Monitoring & Forecast System Issue: Bacterial and viral pathogens – microorganisms capable of causing disease - threaten shellfish, fish species and human health Solution: Predict nature, extent, and spatially dependence of pathogens, including virulence probabilities in Bay and tidal tributaries Operational Concept: Routinely generate short- and long-term predictions using data from hydrodynamic and climate models, temperature and salinity, vibrio and multiple species, pathogen models and remote sensing data. Collaborators: Include water quality and resource mangers, environmental, health and safety planners, and health officials Output Product: Near-real time predictions and maps showing when and where to expect outbreaks or likelihood of occurrence, and long-term scenarios Dissemination: Online, Factsheets and Media Outcome: Actions taken to monitor and mitigate impacts of pathogens Near-real-time maps of V. cholerae likelihood Experimental product