Coastal Ocean Dynamics Data Assimilation for Analysis & Forecasting

1. Ocean Modeling Group:Coastal ocean physics and ecosystem prediction Data assimilative modeling for analysis and forecasting of coastal ocean dynamics for: - maritime and ecosystem forecasting - observing system design and operation - wave-current-sediment & air-sea interaction - ecosystem-physics feedbacks John L. WilkinHernan Arango, Bronwyn Cahill, Naomi Fleming,Julia Levin, Javier Zavala-Garay ESPreSSO Experimental System for Predicting Shelf and Slope Optics Research developing bio-optics, CODAR and coastal altimetry assimilation methodologies jwilkin@rutgers.edu http://myroms.org/applications/espresso http://marine.rutgers.edu/~wilkin Ocean Modeling GroupInstitute of Marine and Coastal Sciences

2. 4DVAR* Assimilation in ROMS for ESPreSSO/MARCOOS domain: Cape Hatteras to Cape Cod MARCOOS operational analysis and prediction system 72-hour forecast with forcing: • NCEP NAM-WRF meteorology • tides (TPXO) • daily river transport (USGS) • open boundary conditions HyCOM+NCODA Assimilates: • altimeter along-track SLA • satellite IR SST • CODAR surface currents • climatology • glider T,S • GTS: XBT/CTD, Argo, NDBC buoys ESPreSSO Experimental System for Predicting Shelf and Slope Optics (research) and MARCOOS (operational) *4-Dimensional Variational data assimilation

3. MARCOOS operational system

4. Work flow for operational MARCOOS 4DVAR Analysis interval is 00:00 – 24:00 UTC Input data preparation commences 01:00 EST (06:00 UT) • 72-hour forecast (NAM-WRF meteorology 0Z cycle at 10 pm EST) • RU CODAR is hourly - but with 4-hour delay • RU glider T,S where available (approx 1 hour delay) • USGS daily average flow available 11:00 EST • persist in forecast • AVHRR IR passes 6-8 per day (approx 2 hour delay) • HyCOM NCODA 7-day forecast updated daily • Jason-2 along-track SLA via RADS (4 to 16 hour delay for OGDR) • Also ENVISAT and Jason-1 NRT data (OGDR and IGDR) • SOOP XBT/CTD, Argo floats, NDBC buoys via GTS from AOML • T,S climatology (MOCHA*) *Mid-Atlantic Ocean Climatology Hydrographic Analysis

5. Work flow for operational MARCOOS 4DVAR • Input preprocessing completes approximately 05:00 EST • 4DVAR analysis completes approx 08:00 EST • analysis is followed by 72-hour forecast using NCEP NAM 0Z cycle available from NOMADS OPeNDAP at 02:30 UT (10:30 pm EST) • Forecast complete and transferred to OPeNDAP by 09:00 EST OPeNDAP http://tashtego.marine.rutgers.edu:8080/thredds/catalog.htmlncWMS http://tashtego.marine.rutgers.edu:8081/ncWMS/godiva2.html • Effective forecast is ~ 60 hours SSH and velocity forecast during Nov 2009 glider OSSE Temp (5m depth) and velocity during Nov 2009 glider OSSE Temperature on cross-section 4 during Nov 2009 glider OSSE

6. Work flow for operational MARCOOS 4DVAR Analysis interval is 00:00 – 24:00 UTC Input data preparation commences 01:00 EST (06:00 UT) • 72-hour forecast (NAM-WRF meteorology 0Z cycle at 10 pm EST) • RU CODAR is hourly - but with 4-hour delay • RU glider T,S where available (approx 1 hour delay) • USGS daily average flow available 11:00 EST • persist in forecast • AVHRR IR passes 6-8 per day (approx 2 hour delay) • HyCOM NCODA 7-day forecast updated daily • Jason-2 along-track SLA via RADS (4 to 16 hour delay for OGDR) • Also ENVISAT and Jason-1 NRT data (OGDR and IGDR) • SOOP XBT/CTD, Argo floats, NDBC buoys via GTS from AOML • T,S climatology (MOCHA*) *Mid-Atlantic Ocean Climatology Hydrographic Analysis

7. Chlorophyll Pigments DOC, DON & DOP Aphy(λ,z) Grazing CDM Fecal Detritus DIC • Ecosystem models (7 ecosystem models in ROMS) • EcoSim – plankton, nutrients, pigments, light Losses NH4 NO3 SiO PO4 FeO Uptake / Heterotrophs Ed(0,λ) Uptake / Autotrophs Remineralization Carbon Fixation Phytoplankton 4 Groups 1 2 3 4 1% Ed(0, λ) Bacteria IOPs aCDM(λ,z) State variables (about 60):NO3, NH4, P, C, Fe, Si, Bac(4), DOM(4), CDM(4), Det(2x5), Phyt(4x4), Pigments(~15)

8. EcoSim – phytoplankton mortality, POC export and oxygen depletion are affected by river plume dynamics and optics Freshwater anomaly Phytoplankton C1 (mmol C m-3) POC (mmol C m-3) POC (mmol C m-3) Rapid primary production within the re-circulating freshwater bulge Phytoplankton mortality generates particulate organic carbon (POC) that is exported to bottom waters. Site of this benthic oxygen demand depends no circulation Freshwater anomaly Phytoplankton C1 (mmol C m-3) POC (mmol C m-3) POC (mmol C m-3)

9. Nitrification Water column Mineralization NH4 NO3 Uptake Phytoplankton Grazing Chlorophyll Zooplankton Mortality Large detritus Susp. particles Nitrification N2 NH4 NO3 Denitrification Aerobic mineralization Organic matter Sediment • Ecosystem models: • (2) BioFennel – plankton, nitrogen, oxygen, carbon, ΔpCO2 • Assimilation experiments with sequential update of chlorophyll • datacycle, ΔpCO2

10. Initial Conditions Model Forcing + Boundaries Validation Skill Assessment Run Period January to July 2006 NCEP-NARR TIDES MABGOM Forward model no assimilation ROMS Forward + Biomass-Based (Fennel) Model Model Bias RMSE Model Skill Taylor diagrams forward Assimilation physics only T/S MLD Chl PP Espresso Reanalysis ROMS Forward + Biomass-Based (Fennel) Model + Continuous Update Physics 3 day update Chl 10 day update Assimilation physics and chlorophyll • ESPreSSO Re-analysis • Bias corrected ocean estimate by sequential assimilation of climatology, SST and SSH. Dynamically balanced T / S fields.

11. Taylor Diagram for Chlorophyll: July 2006 test Assimilation improves chlorophyll solution Correlation coefficient, R Forward model no assimilation Centered pattern RMS error, E’ Assimilation physics only Assimilation physics and chlorophyll Data Taylor, K. E. (2001), Summarizing multiple aspects of model performance in a single diagram, JGR, 106, 7183-7192