1. GODAE OceanView Symposium, Hilton Baltimore, 4-6 November 2013 Overview of GOFS: The U.S. Navy Global Ocean Forecasting System GOVST-V Beijing, October 2014 www.godae-oceanview.org

2. GOFS 3.0: 1/12° 32 layer HYCOM/NCODA-MVOI /MODAS synthetics/e-loan ice Pre-operational system that ran on Navy DSRC Cray XT5 OPTEST report accepted by AMOP in Apr 2012 GOFS 3.01: 1/12° 32 layer HYCOM/NCODA-3DVAR/MODAS synthetics/e-loan ice Operational system running on Navy DSRC IBM iDataPlex computers Switch from MVOI to 3DVAR Switch from NOGAPS to NAVGEM 1.1 forcing in August 2013 Switch from NAVGEM 1.1 to NAVGEM 1.2 forcing in March 2014 GOFS 3.1: 1/12° 41 layer HYCOM/NCODA-3DVAR/ISOP synthetics/CICE Add nine near surface layers Two-way coupled HYCOM with Los Alamos CICE model Replace MODAS synthetics with Improved Synthetic Ocean Profiles Validation test report completed GOFS 3.5: 1/25° 41 layer HYCOM/NCODA-3DVAR/ISOP synthetics/CICE/tides Increase equatorial horizontal resolution to ~3.5 km Tidal forcing Scheduled to be operational in 2016-Q4 REANALYSIS 1993-2012: 1/12° 32 layer HYCOM/NCODA-3DVAR/MODAS synthetics/e- loan ice ESPC: T359 NAVGEM, 1/12.5º HYCOM, and CICE Items in red are different from the preceding system GOFS and Reanalysis outputs available at http://hycom.org GOFS Descriptions

3. MS Event/Action/Improvement ObjectiveCompletion and/or Delivery Quarter/FY Description of Capability Completed and/or Delivered Static calibration of NAVGEM 1.3 for implementation in GOFS: assure consistent ocean model response Expect completion 4QFY14 Calibrate NAVGEM 1.3 wind and heat flux forcing to assure the underlying ocean model response is consistent across the changeover from NAVGEM 1.2 to NAVGEM 1.3 Static calibration of NAVGEM 1.4 for implementation in GOFS: assure consistent ocean model response Expect completion 4QFY15 Calibrate NAVGEM 1.4 wind and heat flux forcing to assure the underlying ocean model response is consistent across the changeover from NAVGEM 1.3 to NAVGEM 1.4 Time-evolving calibration of NAVGEM output based on satellite data Expect completion 4QFY15 Automatic on-the-fly calibration of NAVGEM winds and heat fluxes Implement infrastructure to separate tidal and non-tidal forecasts Expect completion 2QFY15 Separate tidal and non-tidal components of GOFS forecasts for use in NAVOCEANO systems Develop methods, software and scripts to extract only required output as defined by NAVOCEANO Expect completion 2QFY15 Assist NAVOCEANO to better manage the voluminous output from the 1/25° system Complete GOFS 3.5 VTR and acceptance by VTPExpect completion 2QFY16 Improvements over GOFS 3.1: 1/25° vs. 1/12° horizontal resolution, implement tidal forcing Large Scale Ocean Prediction GOFS 3.5 Major Objectives & Milestones

4. GOFS 3.1 vs. GOFS 3.0 GOFS 3.1:41 layer 1/12° global HYCOM NCODA-3DVAR Los Alamos Community Ice CodE (CICE) Improved Synthetic Ocean Profiles (ISOP) GOFS 3.0: 32 layer 1/12° global HYCOM NCODA-3DVAR Energy loan ice Modular Ocean Data Assimilation System (MODAS)

5. GOFS 3.1 vs. GOFS 3.0 HYCOM changes Newer source code: v2.2.86 vs. v2.2.19 Improved base bathymetry: 30” GEBCO vs ETOP05 0.1 m coastline vs. coastline at 10 m isobath Improved Equation of State: 17-term vs. 7-term Improved vertical structure: additional 9 layers near the surface – mixed layers are typically better resolved Changes to surface momentum forcing: calculated in-line in GOFS 3.1 using HYCOM SST and allowing for HYCOM surface currents Improved ocean turbidity scheme: chlorophyll-based vs. photosynthetically available radiation-based. Improved SSS relaxation for better river representation

6. GOFS 3.1 vs. GOFS 3.0 Ice model changes Full two-way coupling between HYCOM-CICE via ESMF vs. thermodynamic “energy-loan” ice model Ocean-ice coupling frequency is every hour Ocean-ice models share the same grid Full rheology in CICE vs. ice growth/melt in response to temperature and heat fluxes and no ice advection by wind or ocean currents GOFS 3.1 ice validation is compared against Arctic Cap Nowcast/Forecast System (ACNFS), not GOFS 3.0 Same version of CICE (v4.0) within GOFS 3.1 and ACNFS

7. GOFS 3.1 vs. GOFS 3.0 NCODA-3DVAR changes NCODA analysis at 12Z using 24-hour HYCOM forecast daily mean vs. NCODA analysis at 18Z using 24-hour HYCOM forecast instantaneous field Daily mean will filter out the tidal signal when tides are implemented in GOFS 3.5 Data selection for assimilation at receipt time vs. observation time Uses First Guess at Appropriate Time (FGAT) to account for late arriving data Cap on the maximum Rossby radius of deformation

8. GOFS 3.1 vs. GOFS 3.0 NCODA-3DVAR: downward projection of surface information Synthetic profiles are generated along altimeter tracks Use observed SSH and SST to create synthetic T & S profiles based on historical relationships between surface and subsurface observations GOFS 3.1 uses ISOP, GOFS 3.0 uses MODAS ISOP has been shown to be an improvement over MODAS as it is able to better represent the vertical structure of the ocean by also constraining vertical gradients of T & S

9. Hindcast Period - Ocean A GOFS 3.1 hindcast was integrated emulating a real-time operational system It ran forward one day at a time but did not create multi-day forecasts each hindcast day NAVGEM 1.1 forcing: 1 August – 31 December 2013 NAVGEM 1.2 forcing: 1 January – 30 April 2014 A series of 14-day forecasts were integrated to examine medium-range forecast skill Initialized from operational GOFS 3.0 and hindcast GOFS 3.1 restarts and forced with analysis quality NAVGEM 1.1 or 1.2 forcing The frequency of these forecasts was dictated by the availability of GOFS 3.0 restart files, typically on the 2 nd and 16 th of each month In total, fifteen 14-day forecasts were integrated (with no data assimilation)

10. Hindcast Period - Ice Important to span a complete year that covers both the melt and freeze periods An ACNFS hindcast using NAVGEM 1.1 forcing existed that spanned the period 1 June 2012 – 31 May 2013 A GOFS 3.1 hindcast had also been integrated over this same period but with an older ISOP configuration within NCODA While that particular GOFS 3.1 hindcast was deemed non- optimal for the upper ocean response, ice nowcasts and forecasts were not adversely affected and these two hindcasts are used for validation A sequence of GOFS 3.1 5-day forecasts were also integrated to examine ice error as a function of forecast length

11. Ocean Validation – Ocean Analysis Regions

12. Ocean Validation – Profile Data Only unassimilated observations are used in the analyses within For a given observation, both systems are sampled at the nearest model grid point Both the observations and hindcast output are remapped in the vertical to a common set of depths: 0, 5, 8, 12, 17, 25, 36, 50, 73, 100, 125, 150, 175, 200, 225, 250, 275, 300, 343, 400, 450, and 500 m Model-data differences that exceed 3 standard deviations are thrown out, i.e. 99% confidence interval This is why the observation count may differ between the two systems

13. Ocean Validation – T vs. Depth – Nowcast Mean error RMSE GOFS 3.1 GOFS 3.0 Mean over this depth range Number of observations For the global domain, mean error is similar, but GOFS 3.1 has lower RMSE than 3.0. Regionally, the results vary.

14. Ocean Validation – S vs. Depth – Nowcast Mean error RMSE GOFS 3.1 GOFS 3.0 For the global domain, mean error Is similar but GOFS 3.1 has lower RMSE than 3.0. Regionally the results vary.

15. Ocean Validation – Mixed Layer Depth – Nowcast GOFS 3.1 MdBE = -1.8 m RMSE = 31.9 m GOFS 3.0 MdBE = -3.1 m RMSE = 36.7 m Median Bias Error 2° bins Box size indicates observation count

16. Ice Validation – Ice Concentration and Thickness GOFS 3.1 ACNFS Concentration (%) Thickness (m) 3 June 2014 Similar ice thickness except in the Beaufort and E. Siberian Seas

17. Ice Validation – NH Ice Edge Location Error – Nowcast

18. Ice Validation – NH Ice Edge Location Error – Forecast Approximately 100 forecasts used in this analysis GOFS 3.1 ACNFS Slow error growth with increasing forecast length

19. Ice Validation – SH Ice Concentration and Thickness Black line is independent NIC ice edge analysis 22 June 2014

20. Ice Validation – SH Ice Edge Location Error – Nowcast SH ice edge error is of similar magnitude to NH error

21.  The bulk parameterization for wind stress includes (T air -SST) and 10m winds (U 10 )  Usually calculated off-line on the NWP (e.g. NAVGEM) grid using NWP SST  Evidence that U 10 should be replaced with (U 10 - U ocn )  HYCOM now has option to read in 10m winds and calculate wind stress in-line  Higher resolution SST  (U 10 -U ocn )  CICE also reads in U 10 for ice-atm stress and gets U ocn from HYCOM for ice-ocn stress. In-Line Wind Stress

22. 1/12  Global 2003-2007 surface EKE (per unit mass) standard stress formulation stress formulation including wind-current shear drifter observations 1/25  Global HYCOM+CICE Agulhas Rings  No assimilation, so expect different eddy fields  On-line has fewer rings and they follow multiple paths in the Atlantic SSH (cm) from off-line stress U 10 SSH (cm) from in-line stress (U 10 -U ocn )

23. Tripole grid from 78.6  S to 90  N, at 1/12  and 1/25  Tidal body forcing with 8 constituents - Semidiurnal M 2, S 2, N 2 and K 2 - Diurnal O 1, P 1, Q 1 and N 1 Scalar self-attraction and loading (SAL) Topographic wave drag applied only to the tides Original Tides in Global HYCOM No drag (grey) over 75% of the world’s oceans

24. Global tide modeling a very different art than regional/coastal tide modeling. In the latter, tidal boundary forcing is often sufficient. In the former, tides develop from astronomical forcing. “Self-attraction and loading” (SAL) accounts for the deformation of the solid earth due to tidal loading, the resultant gravitational perturbation due to self-attraction of the deformed solid earth, and the gravitational perturbation due to self-attraction of the ocean tide. SAL is traditionally calculated using spherical harmonics, which are computationally expensive. Using global data-assimilative barotropic tide models, Egbert and Ray (2000) demonstrated that significant tidal dissipation takes place over rough topography in deep water. Inclusion of wave drag (due to internal wave formation and breaking over rough topography) improves the accuracy of forward tide models because tidal amplitudes are dependent on drag strength (Arbic et al. 2004). Global tide modeling

25. Scalar SAL = -constant*non-steric SSH - always 180  out of phase with the tides HYCOM can now read in a full 8-component SAL - allows iterating to actual SAL - or use observed SAL (e.g., from TPXO8 atlas) Improvements to Tides in HYCOM: SAL

26. New Wave Drag Parameterizations

27. M 2 SSH RMS Error vs TPXO 8 Atlas Existing 3D HYCOM; RMSEa = 7.5 cm Nycander, red.sc, it.SAL; 2.75; RMSEa = 3.6 cm (Shriver et al, 2012) RMSE [cm]

28. THE END.