Overview of GOFS: The U.S. Navy Global Ocean Forecasting System GOVST-V Beijing, October 2014 GODAE OceanViewwww.godae-oceanview.org Symposium, Hilton Baltimore, 4-6 November 2013 GOFS Descriptions 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/eloan 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 Large Scale Ocean Prediction GOFS 3.5 Major Objectives & Milestones MS Event/Action/Improvement Objective Completion and/or Delivery Quarter/FY Description of Capability Completed and/or Delivered 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 VTP Expect completion 2QFY16 Improvements over GOFS 3.1: 1/25° vs. 1/12° horizontal resolution, implement tidal forcing Static calibration of NAVGEM 1.3 for implementation in GOFS: assure consistent ocean model response 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) 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 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 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 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 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 2nd and 16th of each month • In total, fifteen 14-day forecasts were integrated (with no data assimilation) 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 nonoptimal 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 Ocean Validation – Ocean Analysis Regions 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 Ocean Validation – T vs. Depth – Nowcast 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. Mean error Mean over this depth range RMSE Number of observations Mean error RMSE Ocean Validation – S vs. Depth – Nowcast Mean error GOFS 3.1 GOFS 3.0 RMSE Mean error RMSE For the global domain, mean error Is similar but GOFS 3.1 has lower RMSE than 3.0. Regionally the results vary. Ocean Validation – Mixed Layer Depth – Nowcast Median Bias Error GOFS 3.1 MdBE = -1.8 m RMSE = 31.9 m 2° bins Box size indicates observation count GOFS 3.0 MdBE = -3.1 m RMSE = 36.7 m Ice Validation – Ice Concentration and Thickness GOFS 3.1 Concentration (%) Thickness (m) ACNFS 3 June 2014 Similar ice thickness except in the Beaufort and E. Siberian Seas Ice Validation – NH Ice Edge Location Error – Nowcast Ice Validation – NH Ice Edge Location Error – Forecast GOFS 3.1 ACNFS Approximately 100 forecasts used in this analysis Slow error growth with increasing forecast length Ice Validation – SH Ice Concentration and Thickness 22 June 2014 Black line is independent NIC ice edge analysis Ice Validation – SH Ice Edge Location Error – Nowcast SH ice edge error is of similar magnitude to NH error In-Line Wind Stress The bulk parameterization for wind stress includes (Tair-SST) and 10m winds (U10) Usually calculated off-line on the NWP (e.g. NAVGEM) grid using NWP SST Evidence that U10 should be replaced with (U10Uocn) HYCOM now has option to read in 10m winds and calculate wind stress in-line Higher resolution SST (U10-Uocn) CICE also reads in U10 for ice-atm stress and gets Uocn from HYCOM for ice-ocn stress. 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 SSH (cm) from in-line stress SSH (cm) from off-line stress (U10-Uocn) U10 Original Tides in Global HYCOM • Tripole grid from 78.6S to 90N, at 1/12 and 1/25 • Tidal body forcing with 8 constituents - Semidiurnal M2, S2, N2 and K2 - Diurnal O1, P1, Q1 and N1 • Scalar self-attraction and loading (SAL) • Topographic wave drag applied only to the tides No drag (grey) over 75% of the world’s oceans Global tide modeling • 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). Improvements to Tides in HYCOM: SAL • 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) New Wave Drag Parameterizations M2 SSH RMS Error vs TPXO 8 Atlas (Shriver et al, 2012) Existing 3D HYCOM; RMSEa = 7.5 cm Nycander, red.sc, it.SAL; 2.75; RMSEa = 3.6 cm RMSE [cm] THE END.