Rutgers Ocean Modeling Group ROMS 4DVar data assimilation

Mid-Atlantic Bight and Gulf of Maine

John Wilkinwith Julia Levin, Javier Zavala-Garay, Hernan Arango,

Eli Hunter, David Robertson, Naomi Fleming

MARACOOS Modeling MeetingWashington DC

July 22-23, 2013

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Present ESPRESSOreal-timesystem

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New DOPPIOreal-time system

(with 2-way nesting)

*Experimental System for Predicting Shelf and Slope Optics www.myroms.org/espresso

ESPr

eSSO

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

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We overlap analysis cycles, performing a new analysis and new forecast every day

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]

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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

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The data …

days

sin

ce 0

1-Ja

n-20

06

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, gliders and XBTs for 2006 (SW06) and 2007

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Analysis/forecast skill with respect to subsurface OBS that are NOT assimilated

Temperature

4-day forecast

2-day forecast

Data assimilation analysis/hindcast

Forward model after bias removal

Forward model

8

0 0.25 0.5 0.75 1.0BIAS (normalized)

CRM

S (n

orm

alize

d)0

0.2

5

0

.5

0

.75

1.0

Multi-model skill comparison: T/S

MARACOOS AUGV and NMFS EcoMon

CTD data in 2010 and 2011

Multi-model skill comparison: velocity

Bias removal Mean Dynamic Topography

4D-Var applied to climatology of T/S,

mean surface fluxes, & mean velocity obs

(CODAR, moorings, vessel ADCP)

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12

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• 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– 4 days 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

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• DOPPIO model 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)

Future