Chesapeake Bay Observing System

1. Chesapeake Bay Observing System CBOS PR Mesohaline Proposal Briefing To Tidal Monitoring Assessment Workgroup (TMAW) Chesapeake Bay Program Dr. Michael Koterba Chair, CBOS Affiliate Members Chesapeake Bay Observing System

2. Purpose • Provide an overview of CBOS, of the CBOS proposal, and a vision of their potential to address • CBP Water-Quality Assessment Criteria Monitoring in open water, deep water, and deep channel Designated Use Areas of the Chesapeake Bay for adequate regulatory monitoring • TMAW Forecasts, Summaries, and Report Card • Solicit comments, suggestions, and funding from the CBP to implement proposal.

3. What and Where is CBOS ? CBOS: One of five subregional associations of the Mid-Atlantic Coastal Ocean Observing Regional Association...with current focus on the CB Mainstem and Estuaries (MACOORA): One of the 11 RAs in the National Federation of Regional Associations (NFRA): Organized under the nation’s Integrated Ocean Observing System (IOOS, Ocean.US)

5. Who is CBOS?... Current Organization CBOS Full Members: Executive Director Elizabeth Smith, Res. Assist. Prof., Ctr for Coastal Oceanography, Old Dominion University, Norfolk, VA State Bruce Michaels, Coordinator, Tidewater Ecosyst. Assess, MD Dept. of Natural Resources, Annapolis, MD Regional Peter Tango,Monitoring Coordinator, Chesapeake Bay Program, Solomon, MD Industry and Non-Governmental David White, Chief of Operations, Port of Hampton Roads Maritime Association, Norfolk, VA (Janelle Robbins, Staff Scientist), Program Coordinator, Chesapeake Bay Waterkeepers Alliance, Annapolis, MD Hank Lobe, Sales and Marketing Director, Government Systems, Teledyne-RDI, Washington DC Susan Shingledecker,Program Manager, Marine Env.&Safety, Boat.US Foundation, Annapolis, MD Jay Titlow, Senior Meteorologist, Weatherflow, Inc., Poquoson, VA (Kevin Sellner, Director), Manager, Community Modeling Program,Chesapeake Research Consortium, , MD Academic Bill Boicourt, Prof., Horn Point Laboratory, University of Maryland, Ctr., Environ. Sci., Cambridge, MD Larry Atkinson, Eminent Prof., Center for Coastal Oceanography, Old Dominion University, Norfolk, VA Carl Friedrichs, Prof., Virginia Institute of Marine Science, William and Mary College, Gloucester, VA Emil Patruncio, Cmdr., U S Naval Academy, Annapolis, MD 21403 CBOS Affiliate Members: Michael Koterba, Chair,Affiliate Members, U S Geological Survey, Baltimore, MD Douglas Wilson, Manager, Observational Programs, NOAAChesapeake Bay Office, Annapolis, MD Robert Bassett, Requirements Coordinator, NOAACO-OPS, Silver Spring, MD William Reay, Dir., Chesapeake Bay Virginia NOAANational Estuarine Research Reserve, Gloucester, VA Anthony Siebers, Meteorologist In Charge,NOAANational Weather Service, Wakefield, VA

6. What are the goals of CBOS ?IOOS goals (from the bottom up) • More effectively mitigate the • damaging effects of natural • hazards; • Improve prediction of weather as • well as climate change and • variability and their impact on • coastal communities; • Improve safety and efficiency • of marine operations; • Improve national and homeland • security; • Reduce public health risks; • More effectivelyprotect and restore • healthy coastal marine • ecosystems; • Sustain use of marine resources.

7. What is the purpose of CBOS ?Answer: IOOS purpose (from the bottom up) U.S. Commission on Ocean Policy: High quality, accessible informationis critical to making wise decisions about ocean and coastal resources and their uses to guarantee sustainable social, economic, and environmental benefits from the sea.” “User-driven”, integrated , and sustainable system of observations and data telemetry, data management and communications (DMAC), and data analysis and modeling that routinely, reliably, and continuously provides data and information required to meet user needs...

8. As of 2007... • Average freshwater inflow was composed of extremes in low and high flow events... • Difficult year for habitat health, with considerable spatial variability, ... • Poor water clarity throughout Bay, with reasons not very well understood, ... • Dramatic reduction in Bay grasses, possibly as a result of high water temperatures in late 2005, dry spring conditions, followed by poor water clarity from single summer storm event, ... • Very poor benthic community condition, possibly as a result of low DO and high suspended particle concentrations, ... • A helping hand from remnants of Ernesto (Hurricane-Tropical Storm-Nor’easter), which appeared to end HAB, reduce thermal stress on Bay grasses, reduce low DO conditions, ... ...historical interpretations, as well as predictions, difficult for lack the near-real time data that reflect duration and intensity of storm impacts or lack thereof through time for open water, deep water, and deep channel segments of bay and estuaries...and the model capabilities to exploit that data. • Normal spring flow sets stage for moderate Bay conditions... • Mean Anoxic Volume (DO  2 mg/L) 1.4  0.5 KM3, moderate relative to previous summers • Little to no recovery in SAV following dramatic losses in 2006 • Average HAB conditions (duration and extent) expected in Potomac River ...unless notable changes occur in average daily runoff, sediment or nutrient loads, water temperatures, salinity, or winds... ...which largely are determined by the type, frequency, timing, duration, intensity, and track of storms... or the general lack thereof of any major storms (drought)... ...in which case all the initial forecasts are unlikely to hold, and ...updated forecasts are not readily possible due to the lack of near-real time data in open, deep water, and deep channel segments of bay and estuaries ... nor the hydrodynamic models that can exploit that data.

9. As of 2011-2012 2011 2012 • Difficult year for Bay health, with little spatial variability as indicated by modeled QW and Biotic conditions verified by an array of open water, deep water, and deep channel observations. • Poor water clarity, reductions in Bay grasses, and poor benthic community conditions occurred throughout the Bay. • Two early Nor’easters were followed by a prolonged summer drought with elevated water temperatures. • Modeled results validated with open water deep water and deep channel observations indicate: Explanation: Nor’easters resulted in large freshwater, nutrient, and sediment inflows throughout the Bay. Bay clarity declined, initially from suspended sediment, and then large HABs, as water temperatures rose. Bay grass declines were most severe in areas with prolonged loss of clarity due to both sediment and HAB. A prolonged period of stratification, rising water temperatures, and ultimately high BOD associated with bloom die-off led to extended anoxic volumes throughout the Bay main stem and most estuaries. All of the above directly correlate with the reductions in benthic organisms. • Normal spring flow sets stage for moderate Bay conditions... • Mean Anoxic Volume (DO  2 mg/L) 1.4  0.5 KM3, moderate relative to previous summers • Little to moderate increase in SAV expected • Below to average HAB conditions (duration and extent) expected throughout the Bay • Notable deviations from these forecasts could result from the occurrence or lack thereof of major extratropical or tropical storms, and depend on their timing, duration, intensity, and track. Thus, forecasts will be updated on weekly or if needs be storm by storm basis throughout the spring , summer, and fall.

10. Courtesy Ming Li UMCES HPL

11. Surface distributions of salinity and residual currents Buoyancy plume moves along western shore and exits as boundary current, exporting dissolved and particulate organic materials from land to ocean. Courtesy Ming Li UMCES HPL

12. Predictions of currents at CBOS mid-Bay station 2.4 m 19.4 m Wind-driven currents are significantly larger than gravitational circulation and comparable to tidal currents. Courtesy Ming Li UMCES HPL

13. Prediction for tidal elevations at tidal gauge stations Courtesy Ming Li UMCES HPL RMS error < 5 cm, Relative error < 5%, Correlation > 0.95, Skill > 0.95.

14. Comparison of salinity time series at CBP monitoring stations Surface Bottom Model: lines Data: dots Model predictive skill for salinity is 0.85 (Li et al., 2005, JGR). Courtesy Ming Li UMCES HPL

15. Wind-induced destratification and re-stratification Red--bottom Blue--top Episodic wind-induced mixing and restratification events are reminiscent of spring-neap tidal cycle. How does wind mixing affect the Bay? Courtesy Ming Li UMCES HPL

16. Simulating storm surges during Hurricane Isabel Mean RMS error is 0.13 m and model skill for predicting storm surges is 0.96.

17. Courtesy Ming Li UMCES HPL

18. Before During After Storm-induced destratification and restratification Hurricane-induced winds erased stratification but horizontal density/pressure gradient drove post-storm restratification and return to two-layer flows. Courtesy Ming Li UMCES HPL

19. Embedding a six-compartment biogeochemical model Simple parameterization of optics and benthic processes (1) Light attenuation coefficient estimated from optical measurements. (2) Nutrient re-mineralization rate temperature-dependent. (3) De-nitrification rate linearly proportional to ambient nutrient concentration. Courtesy Ming Li UMCES HPL

20. Nutrient transport by plume and development of spring (1997) bloom NO3 (Feb) NO3 (Apr) Phytoplankton (Mar) Courtesy Ming Li UMCES HPL

21. Along-channel distributions in summer (1997) Phytoplankton NO3 NH4 Zooplankton (1) Summer plankton production supported by regenerated nutrients. (2) Warm temperature stimulates bacteria production and speeds up the re-mineralization of organic particles into ammonium. Courtesy Ming Li UMCES HPL

22. Enhanced phytoplankton production driven by episodic winds Courtesy Ming Li UMCES HPL

23. Annual time series of integrated productivity and Chl-a Whole Bay Lower Bay Mid-Bay Upper Bay Good agreement between model predictions and observations. Regression coefficient and model predictive skill lie between (0.5-0.9) (Li et al, submitted). Courtesy Ming Li UMCES HPL

24. Courtesy Ming Li UMCES HPL

25. Comparison of spring bloom between high and normal runoff years 1996 (high) 1997 (normal) During high runoff years, spring bloom extends towards lower bay. Courtesy Ming Li UMCES HPL

26. Where to begin? ...with the proposal now up for your review... Providing review comments...before June 13th Participating in the MASC review discussion on June 13th Purpose of proposed study: Characterize vertical profile temporal (hourly) variability in CBP Assessment Criteria (DO, Clarity (Turbidity), Chlorophyll a (Fluorescence)), and Temperature and Salinity at Fixed Stations Characterize temporal variability in meteorological and hydro- dynamic forcings co-located with above. Analyze data to determine temporal relations among QW and above forcings. Propose open water, deep water, and deep channel monitoring design consistent with CBP (adequate) monitoring approach with eye toward 2010 regulatory requirements (and modeling).

27. Study Location and Observations Mesohaline, Potomac River

28. CBOS-CBP Partners Obtain, Disseminate, and Analyze Data Meteorological data Wind speed and direction, air temperature, and barometric pressure (16), WeatherFlow et al High resolution windfield Nowcasts WeatherFlow Solar radiation NOAA (CBIBs) Hydrodynamic data Freshwater stream flow (3-4) USGS Water levels (3 or possibly more) USGS, NOAA Current speed, direction (2-4, 2 multiple depths) NOAA, UMCES-HPL Waves height, period, direction (2) NOAA, UMCES-HPL Water-quality data Temperature (4, 2 profile) NOAA DNR, UMCES Clarity-Turbidity (2 profiles) NOAA DNR Dissolved oxygen (2 profiles) NOAA DNR pH (2 profiles) NOAA DNR Chlorophyll a (2 profiles) NOAA DNR Salinity (Conductivity) NOAA DNR UMCES Period of Data Collection: Mar-April to Oct-Nov Dissemination of Data: At least hourly by CBOS Opendap server and Netcdf files, according to IOOS DMAC and CBP protocols Analysis of Data CBP, Gary Shenk and staff have lead

29. FY07 Budget Partner Service in Kind Requested WeatherFlow $ 25K $ 20K MD-DNR $ 75K $ 18K NOAA NCBO $130K --- UMCES HPL $ 45K $ 20K CBOS $ 20K $ 24K w peer-reviewed publication $ 22K Totals $295K $104K

30. POTOMAC River Inundation POTOMAC RIVER Storm-Surge INUNDATION PROJECTS Principals-Products NWS Forecasting and predictions with WeatherFlow, Inc. VIMS (ADCIRC) and UMCES-HPL (ROMS) Hydrodynamic Modeling Noblis, Inc. Inundation visualization CBOS Observational network data for model assimilation and validation, and visualization validation Isabel The intersection of Union and King streets in Old Town Alexandria, VA

31. MWCOG Flooding Inundation Prediction System (FIPS) Potential Approximate Locations (may vary) Development within these areas to be coordinated Greater NCR Charles County A B B B B Quantico/Aquia Colonial Beach St. Mary’s County • Base Program • Refine model spatial grid • Include tributaries runoff • Decrease system run time • Compatible with EM GIS • Sustain water level network • Gages for on-land validation • Validate storm events • Implement working prototype • with NOAA NWS • Propose future system for • sustained operations

32. Response? • Please provide comments, suggestions,... wrt to proposal to: • Mike Koterba (at both mkoterba@usgs.gov and mkoterba@noaa.gov) by EOB Monday June 11th. • Please consider attending CBP MASC meeting on Wednesday June 13th for discussion of CBOS proposal.