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Present ESPRESSO real-time system

Rutgers Ocean Modeling Group ROMS 4DVar data assimilation Mid-Atlantic Bight and Gulf of Maine John Wilkin with Julia Levin, Javier Zavala- Garay , Hernan Arango , Eli Hunter, David Robertson, Naomi Fleming MARACOOS Modeling Meeting Washington DC July 22-23, 2013.

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Present ESPRESSO real-time system

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  1. Rutgers Ocean Modeling Group ROMS 4DVar data assimilationMid-Atlantic Bight and Gulf of MaineJohn Wilkinwith Julia Levin, Javier Zavala-Garay, HernanArango, Eli Hunter, David Robertson, Naomi FlemingMARACOOS Modeling MeetingWashington DCJuly 22-23, 2013

  2. Present ESPRESSOreal-timesystem New DOPPIOreal-time system (with 2-way nesting)

  3. Work flow for real-time ESPreSSO ROMS 4DVar Analysis interval is 00:00 – 24:00 UTC • Input pre-processing starts 01:00 EST • Input preprocessing completes approximately 05:00 EST • 4DVAR analysis completes approx 08:00 EST • 24-hour analysis is followed by 72-hour forecast using NCEP NAM 0Z cycle from NOMADS GDS at 02:30 UT (10:30 pm EST) • Forecast complete and transferred to THREDDS by 09:00 EST • Effective forecast is ~ 60 hours ESPreSSO We overlap analysis cycles, performing a new analysis and new forecast every day *Experimental System forPredicting Shelf andSlope Opticswww.myroms.org/espresso

  4. Work flow for real-time ESPreSSO ROMS 4DVar Data used [… real-time SOURCE] • 72-hour forecast NAM-WRF 0Z cycle at 2 am EST [NCEP NOMADS] • RU regional CODAR product – hourly: 4-hour latency delay [RU TDS] • RU glider T,S when available (seldom) (~1 hour delay) [RU TDS] • USGS daily average flow available 11:00 EST [USGS waterdata] • AVHRR IR passes 6-8 per day (~ 2 hour delay) [MARACOOS TDS] • REMSS MW-IR blended SST daily average [PO-DAAC] • HYCOM NCODA 7-day forecast updated daily [NRL] • Jason-2 along-track SLA (4 to 16 hour delay for OGDR) [RADS] • SOOP XBT/CTD, Argo floats, NDBC buoys on GTS [OSMC ERDDAP]

  5. Work flow for real-time ESPreSSO ROMS 4DVar Input pre-processing • RU CODAR de-tided (harmonic analysis) and binned to 5 km • “re-tided” with ESPReSSO harmonics • variance within bin & OI combiner expected u_err(GDOP) used for QC • RU glider T,S averaged to ~5 km horizontal and 5 m vertical bins • GTS SOOP XBT and Argo – binned and QC • AVHRR IR individual passes 6-8 per day • U. Del cloud mask selected QC flags; bin to 5 km resolution • Jason-2 along-track 1 Hz with coastal corrections in RADS • MDT from 4DVAR on “mean model” (climatology 3D T,S, uCODAR, τwind) • “re-tided” with ESPReSSO harmonics • USGS daily river flow is scaled to account for un-gauged watershed

  6. The data …

  7. Sub-surface T/S analysis and forecast skill In situ T and S observations are not assimilated so offer independent skill assessment There is a sizeable archive of observatory data from CTD, glidersand XBTs for 2006 (SW06) and 2007 days since 01-Jan-2006

  8. Analysis/forecast skill with respect to subsurface OBS that are NOT assimilated Temperature Forward model Forward model after bias removal Data assimilation analysis/hindcast 2-day forecast 4-day forecast

  9. Multi-model skill comparison: T/S CRMS (normalized) 0 0.25 0.5 0.75 1.0 0 0.25 0.5 0.75 1.0 BIAS (normalized) MARACOOS AUGV and NMFS EcoMonCTD data in 2010 and 2011

  10. Multi-model skill comparison: velocity

  11. Bias removal Mean Dynamic Topography 4D-Var applied to climatology of T/S, mean surface fluxes, & mean velocity obs (CODAR, moorings, vessel ADCP)

  12. Rutgers ROMS 4DVAR uses all available data from a modern coastal ocean observing system satellites, HF-radar, moorings, AUV (glider, Argo …), XBT/CTD; IR SST individual passes work best – model dynamics create the composite more and diverse data is better climatology assimilation: removes OBC and MDT bias; unbiased background state in Tangent-Linear model gives correct dynamic modes and adjoint-based increments Useful skill for real-time applications 4days for temperature and salinity; 1-2 days for velocity improves short-term ecosystem prediction observing system operation … glider path planning Variational methods for observing system design adjoint sensitivity and representer-based observing system design (see W. Zhang et al. papers in Ocean Modelling, 2010); observation impact analysis (see A. Moore et al. papers in Prog. Oceanog. 2011) Summary

  13. Future • DOPPIOmodel domain configuration for MAB + Gulf of Maine • Same 4DVAR methodology as ESPRESSO • Evaluate GOOS/GODAE and IOOS-NB products for real-time OBC • Nest in Curchitser group NWA 50-year simulations for reanalysis OBC • Repeat climatology 4DVAR for MDT and OBC bias removal • Include waves in forcing data and model physics • Local shelf and estuarine nests (2-way ROMS) • USECOS nitrogen/carbon cycle simulations • ROMS 4DVAR weak constraint/dual space formulation • observation space – computationally smaller than model space • W4DVAR Indirect Representer algorithm (Egbert 1994) • W4DPSAS Physical Space Statistical Analysis System (Da Silva 1995) • Adjusts time-varying forcing and boundary conditions, explicitly acknowledges model error, enables posterior analysis of observation impact/sensitivity (and more)

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