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ROMS (Regional Ocean Modeling System) Real-Time Modeling, Data Assimilation, and Forecast

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FY2002-2003: ONR AOSN Monterey Bay field experiment FY 2004: CIMT-$100K 2003-2004 hindcast experiment FY 2004-2006: ONR MB06/ASAP Monterey Bay field experiment FY 2006: CIMT-$100K Transition the ROMS nowcast and forecast toward real-time operational demonstration - PowerPoint PPT Presentation
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1 ROMS (Regional Ocean Modeling System) Real-Time Modeling, Data Assimilation, and Forecast FY2002-2003: ONR AOSN Monterey Bay field experiment FY 2004: CIMT-$100K 2003-2004 hindcast experiment FY 2004-2006: ONR MB06/ASAP Monterey Bay field experiment FY 2006: CIMT-$100K Transition the ROMS nowcast and forecast toward real-time operational demonstration FY 2006: CIMT-$25.4K (with Leslie Rosenfeld) Real-time Monterey Bay wind product PI: Yi Chao JPL ROMS Group: Ocean: John Farrara Gene Li Adam Wang Carrie Zhang IT/Database/Web: Peggy Li Quoc Vu Thanks to many CIMT investigators
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Page 1: ROMS (Regional Ocean Modeling System)  Real-Time Modeling, Data Assimilation, and Forecast

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ROMS (Regional Ocean Modeling System) Real-Time Modeling, Data Assimilation, and

Forecast

• FY2002-2003: ONR– AOSN Monterey Bay field experiment

• FY 2004: CIMT-$100K– 2003-2004 hindcast experiment

• FY 2004-2006: ONR– MB06/ASAP Monterey Bay field

experiment• FY 2006: CIMT-$100K

– Transition the ROMS nowcast and forecast toward real-time operational demonstration

• FY 2006: CIMT-$25.4K (with Leslie Rosenfeld)– Real-time Monterey Bay wind product

PI: Yi Chao

JPL ROMS Group:• Ocean:

– John Farrara– Gene Li– Adam Wang– Carrie Zhang

• IT/Database/Web:– Peggy Li– Quoc Vu

Thanks to many CIMT investigators

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CIMT needs a modeling component, because?

• Model can be used to

– Fill the data gap: ocean will be always under-sampled, over 900 profiles/day were collected during August 2003 AOSN experiment; 100 moorings are sufficient for MB observing system

• Model can be used to

– Forecast into the future: observation can only tell what happens today

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Two complementary modeling approaches

• Process-oriented modeling: simple/easy understood or theoretical framework

• Modeling for application users (e.g., weather forecast,

fishery management)

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1.5-km5-km15-km

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Data Assimilation:3-Dimensional Variational (3DVAR) method

J = 0.5 (x-xf)T B-1 (x-xf) + 0.5 (h x-y)T R-1 (h x-y)

Time

Aug.1 Aug.4Aug.3Aug.2

Initialcondition

24-hour forecast

Aug.5

Xa = xf + xf

Xa

xf

3-day forecast

y: observationx: model

24-hour assimilation cycle

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CIMT ROMS Reanalysis (Retrospective Analysis) and Real-Time Forecast Plan

clim.spinup

Aug.03AOSN(ONR)

Sep.04 Aug.06ASAP(ONR)

TIME

1-yearReanalysis2003-2004

(CIMT)

Multi-yearReanalysis2003-2006

Real-timeforecast

CIMT data: ship CTD & underway, M0, Sea Lion profilesOther data: satellite, M1/2, AUVs, ships

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An Interactive Web Portal to Manage and Visualize Sea Lion Data

http://ourocean.jpl.nasa.gov

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http://ourocean.jpl.nasa.gov

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No Data Assimilation

Assimilation of AOSN data

BiasMean RMS194

Sea Lionprofiles

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A New ROMS Capability: Predicting Sea Level

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Data and Model Products

• Real-time Monterey Bay wind demonstration– CIMT web site

• ROMS 3D nowcast and forecast demonstration in the near future (2007 maybe)– Temperature, salinity– Surface current, complementary to HF radar but filling in

data gaps and extending offshore– Sea level

• Future ROMS capabilities, collaboration with other CIMT PIs– Coupled physical-biological ecosystem processes, in

collaboration with Chavez and Chai– Other CIMT data types


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