http://marine.rutgers.edu/~wilkin jwilkin@rutgers.edu

Experimental System for Predicting Shelf and

Slope Optics

Research developing bio-optics, CODAR and

coastal altimetry assimilation

methodologies

Ocean Modeling GroupInstitute of Marine and Coastal Sciences

http://myroms.org/applications/espresso

ES

Pre

SS

O

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

4DVAR* Assimilation in ROMS for ESPreSSO/MARCOOS domain: Cape Hatteras to Cape Cod

MARCOOS operational analysis and prediction system72-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

Experimental System for Predicting Shelf

and Slope Optics (research)

and

MARCOOS (operational)

ES

Pre

SS

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*4-Dimensional Variational data assimilation

MARCOOS operational system

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

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

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

Phytoplankton 4 Groups

NO3 SiO PO4 FeO

1 2 3 4

Fecal Detritus

DIC

CDM

DOC, DON & DOP

Bacteria

NH4

Grazing

Uptake / Autotrophs

LossesUptake / Heterotrophs

RemineralizationCarbon Fixation

Chlorophyll Pigments

IOPs

Aphy(λ,z)

aCDM(λ,z)

Ed(0,λ)

1% Ed(0, λ)

Ecosystem models (7 ecosystem models in ROMS) (1)EcoSim – plankton, nutrients, pigments, light

State variables (about 60):NO3, NH4, P, C, Fe, Si, Bac(4), DOM(4), CDM(4), Det(2x5), Phyt(4x4), Pigments(~15)

Rapid primary production within the re-circulating freshwater bulge

EcoSim – phytoplankton mortality, POC export and oxygen depletion are affected by river plume dynamics and optics

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)

Freshwater anomaly Phytoplankton C1 (mmol C m-3) POC (mmol C m-3) POC (mmol C m-3)

NO3

Chlorophyll

Largedetritus

Organic matter

N2 NH4 NO3

Water column

Sediment

Phytoplankton

NH4

Mineralization

Uptake

Nitrification

Nitrification

Grazing

Mortality

Zooplankton

Susp.particles

Aerobic mineralizationDenitrification

Ecosystem models: (2) BioFennel – plankton, nitrogen, oxygen, carbon, ΔpCO2

Assimilation experiments with sequential update of chlorophyll

(1) datacycle, ΔpCO2

ModelForcing +

BoundariesInitial

ConditionsValidation

SkillAssessment

Run Period

January to July 2006

forward

ROMS Forward+ Biomass-Based

(Fennel) Model+ Continuous

Update

Model BiasRMSE

Model SkillTaylor diagrams

T/SMLDChlPP

ROMS Forward+ Biomass-Based

(Fennel) Model

EspressoReanalysis

NCEP-NARRTIDES

MABGOM

3 day update

10 day update

Physics

Chl

ESPreSSO Re-analysisBias corrected ocean estimate by sequential assimilation of climatology, SST and SSH. Dynamically balanced T / S fields.

Forward model no assimilation

Assimilation physics only

Assimilation physics and chlorophyll

Taylor Diagram for Chlorophyll: July 2006 test

Centered pattern RMS error, E’

Correlation coefficient, R

Taylor, K. E. (2001), Summarizing multiple aspects of model performance in a single diagram, JGR, 106, 7183-7192

Forward model no assimilation

Assimilation physics and chlorophyll

Assimilation physics only

Data

Assimilation improves chlorophyll solution