1. Our Planet is Changing We need advanced tools to understand and monitor our oceans, coasts and Great Lakes Zdenka Willis Director, US IOOS Program Office US IOOS®: A Partnership for Lives and Livelihoods

2. U.S. IOOS: Program Overview 12 Global Component Coastal Component (EEZ to the head of tide) 2 Enhances science and improves decision making 7 Goals, 1 System Improve predictions of climate change and weather Improve the safety and efficiency of maritime operations Improve forecasts of natural hazards Improve homeland security Minimize public health risks Protect and restore healthy coastal ecosystems Sustain living marine resources

3. 87% Total in situ networks61% 59% 81% 62% 73% 34%48% 100% Global Component: Global Ocean Observing System for Climate 3

4. Coastal Component Comprised of federal agencies (National level) and non-federal (Regional level) Geographic extent: EEZ to the head of the tide Based on 26 variables Data Management and Communications (DMAC) is a major focus that is intended to be enterprise wide from National to Regional scales 4

5. Observation Networks: Waves Nation’s wave data now accessible –181 platforms in 2008; 227 2011 –Wave Plan called for 296 –New IOOS supported wave sites being deployed collaboratively with USACE/ CDIP program –Some platforms need to be upgraded to directional wave measurements

6. Observing Networks 6 National Data Buoy Center

7. Data Integration – Regional to National

8. U.S. IOOS ® : Modeling Testbed 8 Coastal Inundation Rick Leuttich, UNC-CH Gulf & Atlantic Coast Shelf Hypoxia John Harding, USM Gulf of Mexico Estuarine Hypoxia Carl Friedrichs, VIMS Chesapeake Bay Cyber Infrastructure Eoin Howlett, ASA Testbed Advisory Rich Signell, USGS Evaluation Group 5 teams, 64 scientists/analysts Began in June 2010; now in the second year Multi-sector engagement (federal agency, academia, industry) Goals: Less about model than process Focus is on stable infrastructure (testing environment, tools, standard obs) and transition to operations Enable Modeling and Analysis subsystem

9. US HF Radar Network 9 Operated by > 30 institutions Used by > 40 government/private entities Industry Partner: US-based CODAR Ocean Sensor Uses: + Coast Guard : Search &Rescue: Oil spill + Water Quality; Criminal Forensics + Commercial marine navigation + Off Shore Energy + Harmful algal blooms + Marine fisheries + Emerging – Tsunami

10. National Data Management 10

11. Support for Harmful Algal Bloom 11 Vera L. Trainer, NOAA Fisheries Barbara M. Hickey, University of Washington

12. Automated notification when thresholds exceeded 3 day wave forecast San Pedro Channel Maritime Transportation-San Pedro Channel CDIP provides waves SCCOOS provides currents

13. Inspection of Hyperion Outfall Pipe (never internally inspected for 50 years). Serves City of Los Angeles. One of the world’s largest coastal populations. Close to a billion gallons of sewage to be diverted to an in-shore/shallow outfall. Concern of extent of impact and public health risk in the Santa Monica Bay Hyperion Outfall Diversion November 28-30, 2006

14. Both offshore and surfzone circulation required observation. HF radar derived surface current map. Surf-zone forecast driven by waves.

15. Arctic 15

16. Emerging HFR benefits With relevance to EBM, MSP … Mesoscale flow features – large eddies persist at key locations Interannual variability – significant changes in alongshore transport Divergence & convergence (fronts) – interfaces in the ocean Upwelling & phytoplankton – spatial structure of pelagic habitat Larval dispersal & MPAs – population connectivity Juvenile salmon survival – early ocean phase (transport & food) Land runoff plumes – subsidies & contaminants

17. MESOSCALE FLOW FEATURES Can now map, quantify and track features like eddies & jets “Mendocino Eddy” HFR circulation with SST Halle et al 2010 (in review)

18. MESOSCALE FLOW FEATURES Mendocino Eddy … persists year-round. 116W 120W 124W longitude 33N 36N 39N 42N 45N 48N latitude (a) Spring (b) Summer (c) Fall (d) Winter San Francisco Cape Mendocino Point Conception Bjorkstedt et al 2010 (in review)

19. DIVERGENCE & CONVERGENCE (FRONTS) Divergence – regions of persistent surface divergence & upwelling due to wind- driven Ekman transport & flow past topography. Convergence – associated with flow past topography & fronts. Fronts represent high-productivity interfaces … aggregations of plankton, fish, birds, mammals. Upwelling WindsWeak Winds Gough et al 2010 (CWO 2010)

20. Larval Retention Areas VandenbergAño NuevoPoint LobosPoint Sur Color Map: Location of waters 40 days ago (red), 30 days ago (yellow), 20 days ago (green), 10 days ago (cyan), and 5 days ago (blue) before reaching the labeled MPA (magenta). REFERENCE: B. Zelenke, M. Moline, G. Crawford, N. Garfield, B. Jones, J. Largier, J. Paduan, S. Ramp, E. Terrill, and L. Washburn, “Evaluating Connectivity between Marine Protected Areas Using CODAR High-Frequency Radar,” in Proceedings of the OCEANS 2009 MTS/IEEE Biloxi Conference, Biloxi, MS (2009). Connectivity maps based on measured surface currents show what waters are influencing MPAs and the potential extent of surface water larval transport.

21. A Global Earth Observation System of Systems (GEOSS) 21

22. Global HF Radar Network Under the Group Earth Observations (GEO) –88 Member governments and the European Commission, working with 61 Participating Organizations focused on the importance of Earth Observations to Societal Benefits Component under 2 Tasks in the GEO workplan 2012-2015 –IIN-01 Earth Observing Systems –SB-01 Oceans and Society: Blue Planet Kicked off at Oceanology International March and 1 st Ocean Radar Conference for Asia Goals: – Transform individual HF Radar networks into a global system where we can provide high quality HF Radar for a range of used. –Development of easy to use standard products –Assimilate HF Radar data into models –Development of easy to use standard products 22

23. HF Radar Data management Standard interoperable self-describing netCDF format Standard metadata ISO 19115 format Quality control –Radar level –Radial velocity level –Total vector velocity level 1,2, 6 KM data Optimal Interpolation 23

24. Global HF Radar Assets http://assets.maracoos.org/ Global HF Radar Assets