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NIWA, New Zealand

Hindcasting mesoscale variability: Statistical projection of altimetry to subsurface T-S, and assimilation into ROMS by intermittent optimal interpolation John Wilkin. NIWA, New Zealand. Rutgers University. East Auckland Current. Western boundary current upwelling. Wind driven upwelling.

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NIWA, New Zealand

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  1. Hindcasting mesoscale variability:Statistical projection of altimetryto subsurface T-S, and assimilation into ROMS by intermittent optimal interpolation John Wilkin NIWA, New Zealand Rutgers University

  2. East Auckland Current • Western boundarycurrent upwelling • Wind driven upwelling  fertilize the coastal ocean • seasonal stratification and tidal mixing affect dynamics

  3. Geographically realistic simulations • Emphasis on properties affecting ecosystem functioning: temperature, mixed layer depth, nutrient fluxes • Produce hindcasts to complement observational studies; physical, biological and geochemical

  4. ROMS: open boundaries and external forcing • 5 km grid, 20 levels, q=7 • inflow/outflow/nudging open boundaries • KPP(LMD) mixed layer • daily NCEP reanalysis surface fluxes • DJ_GRADPS p • advection: 4th order tracers, upstream bias momentum

  5. EAuC topographically steered • WBC driven upwelling • Wind-driven upwelling • Seasonality in mixed layer • But not a useful hindcast for interpretation of in situ observations

  6. ROMS: mesoscale assimilation • Coastal ocean variability is forced locally by winds, and remotely by WBC and gyre • Predictability of the ocean mesoscale is limited, so… • … use assimilation to keep deep ocean on track • OK if … weak feedback from coastal to gyre

  7. Data • SSH: altimeters T/P+ERS (+tide gauge) mapped to model grid

  8. Data • SSH: altimeters T/P+ERS (+tide gauge) mapped to model grid • Temperature: Vertical EOFs of temperature anomaly, regressed on surface dynamic height anomalyT’(z) = c1*SSH*1(z) + c2*SST* 2(z) • Independently estimate errors in T(z) …

  9. Intermittent OI assimilation • ASSIMILATION_{SSH,SST,T,UV} • Dombrowsky and De Mey (1992)* scheme: • form weighted sum (melding) of obs and model • forecast error : analysis error *J. Geophys. Res., 97, 9719-9731, 1992

  10. Melding step (analysis)Ya= Yo+ (1-m)Yf • Weightm = ef2 – gefeo eo2 + ef2 – 2gefeo • Analysis error ea2 = ef2 eo2 (1– g) eo2 + ef2 – 2gefeog is the correlation between model and obs

  11. Forecast error is assumed to grow with a prescribed decorrelation timescale ef2 = ea2 + 2 (1-d) Y2 d= exp[-( Dt/Tgrowth)2]

  12. Fertilizing the coastal ocean • Hindcast coastal mesoscale • Local and remote forcing • Implement ROMS biology • Consider seasonal to interannual scales: ecosystem, carbon, nitrogen

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