1. 1 Global Ocean Modeling Strategy Presented by: Avichal Mehra (NWS/NCEP/EMC) Contributors: Hendrik Tolman (NWS/NCEP/EMC) Carlos Lozano (NWS/NCEP/EMC)

2. 2 Operational System Attribute(s) System NameAcronymAreal CoverageHorz Res Cycle Freq Fcst Length (hr) Atlantic- Real Time Ocean Forecast System Atl- RTOFS 25° S to 72° N 98° W to 16°E 1/12° Avg. Once/ day 144 Global – Real Time Ocean Forecast System Global RTOFS Global1/12°Once/ day 192 SystemAttributes Atl-RTOFS 3DVar (based on elements of GSI) Global- RTOFS Navy Coupled Ocean Data Assimilation (NCODA), 3DVar (run daily at NAVOCEANO) System Data Assimilation or Initialization Technique

3. 3 Why System(s) are Operational  Primary stakeholders and requirement drivers 2004 Science Advisory Board; 2008 Ocean Modeling workshop  National backbone (Navy & NWS), near-coast (NOS) Internal NWS users: EMC, OPC, NHC, coastal WFO’s Internal NOAA users: NOS, IOOS RA’s, NESDIS, NMFS External users: e.g. US Coast Guard/DHS  What products are the models contributing to? Three-dimensional U,V, T & S; Sea Surface Heights, Sea Ice Cover  What product aspects are you trying to improve with your development plans? All of the above; additional joint products from coupled applications (e.g. Hurricane track and intensity, sea-ice thickness and drift)

4. 4 Why System(s) are Operational  Top 3 System Performance Strengths Global coverage of deep ocean eddy resolving/mesoscale features (major currents, fronts, eddies) Coastal features/fronts resolved at 1/12° world-wide; important for downstream NOS ocean forecast systems High Frequency output of fields for internal (and external) NOAA users  Top 3 System Performance Challenges Resources (human; computing; storage) Adequate observations (altimeter; sub-surface) for constraining and verifying Unifying model codes and ODA methods across applications

5. 5 System Evolution Over the Next 5 Years  Major forcing factors Higher resolution for both deep and coastal oceans US areas of interest, NA, EP, Arctic Coupled applications (HWRF, Arctic, Ecosystems) Ensemble based forecasting Unified data assimilation for S2S, S2A applications  Science and development priorities Higher resolution for regional/basin scale systems NEMS/NUOPC/ESMF infrastructure for coupling Ensemble based forecasting products Variational and Hybrid Ocean Data assimilation algorithms

6. 6 System Evolution Over the Next 5 Years  What are you top challenges to evolving the system(s) to meet stakeholder requirements? Human resources Computing resources (including storage) Observations  Potential opportunities for simplification going forward Community-based Ocean Data assimilation algorithms Long-term viable active collaborations with partners (Navy, GFDL, Academia, others) Adopting recent modern computing technology (GPU’s, PYTHON etc.)

7. 7 Top 3 Things You Need From the UMAC 1. How to prioritize emerging requirements? Deep Ocean Vs. Coastal, high res deterministic Vs low-res ensembles, short-term weather Vs. S2A 2.Guidance on Ocean Data Assimilation strategy GODAS – CFS/MOM NCODA – RTOFS/HYCOM LETKF-- Unified DA, Hybrid ODA 3.Which new data sources to prioritize? In situ: Gliders, ATN Remote: Ocean Color, SSS, HF-Radar, Sea-Ice thickness