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2008

Navy Operational AssimilativeGlobal Ocean Modeling

Dr. Charlie Barronbarron@nrlssc.navy.mil

Naval Research LaboratoryStennis Space Center

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2008

Navy Global Ocean Modeling

The Naval Research Laboratory has developed and transitioned the global ocean modeling system now operational at the Naval Oceanographic Office:

• Present system

• Key products

• Evaluate performance

• Future plans

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Regional modelsNCOM/NCODA

Global modelsNCOM, HYCOM

Ocean AnalysisNCODA, ISOP

Ocean Predictionacoustics/currents

Operational Navy Assimilative Ocean Modeling

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Global NCOM: configuration and references

• ~14 km average spacing

• 41 vertical σ–z levels stretched logarithmically to 5500 m

• 1 m upper layer rest thickness

• CICE 3.0 Arctic ice model

• NOGAPS wind stress, bulk heat flux

• NCODA assimilation of in situ observations

Global NCOM

Key references: http://www7320.nrlssc.navy.mil/global_ncom/pubs.html

Barron et al., JGR Oceans, 2007. drifter evaluation

Barron et al., Ocean Modelling, 2006. model formulation

Kara et al., Ocean Modelling, 2006. general evaluation

Barron et al., J. Atm. Oceanic Techn., 2004. SSH evaluation

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2008Key Products

Key operational products supported by global Navy ocean models include:

• Sound speed for acoustic calculations in anti submarine warfare

• Boundary conditions for nested ocean models and coupled atmospheric models

• Currents for buoy drift, mine drift, search and recovery

• Ice products such as ice edge, thickness

Model validation studies focus on these operational products.

New transitions must in some way improve information for key operational products.

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RMS Range error: 0.5 km

Max Range error: 1.3 km

Assimilating synthetics into global NCOM:• Dynamics produce a relatively deep mixed layer• Smaller errors in predicting transmission loss

Impact of ocean models on sound speed prediction

0600Hz at 20m depth

RMS Range error: 1.7 km

Max Range error: 4.1 km

Present operational synthetic based on SSH, SST:• Fails to represent surface sonic layers• Significant errors in predicting transmission loss

GNCOM

Observed

Synthetic

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Validate model attributes that are relevant to key products

Evaluate hydrographic proxies to indicate expected acoustic fidelity:

Mixed Layer Depth (MLD) Kara et al. (2000) density threshold equivalent to ΔT=0.8°C

Below-Layer Gradient (BLG) Fit a line to sound speed points between SLD and SLD+100m

BLG is the slope*100 with units ms-1/100m

Negative BLG ↔ downward refractionPositive BLG ↔ upward refraction

speed(z) ≈ speed(SLD) + BLG*(z-SLD)/100

Sonic Layer Depth (SLD) Helber et al. (submitted) near surface sound speed maximum appropriate for frequency range

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For MLD, where is MLD-modified GNCOM better than a standard synthetic (MODAS)?

Evaluate NCOM assimilating MLD-modified synthetic vs. synthetic

• 11 m GNCOM median improvement

• GNCOM better in 80% of the regions. (shown in red and yellow) Statistics based on 43,474 T,S profiles from 2006.

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• 10 m GNCOM median improvement

• GNCOM better in 83% of the regions. (shown in red and yellow)

For MLD, where is MLD-modified GNCOM better than a standard synthetic (MODAS)?

Evaluate NCOM assimilating MLD-modified synthetic vs. synthetic

Statistics based on 6,942 unassimilated T,S profiles from 2006.

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Median statistics relative to 43,474 T,S profiles over the global ocean.

CaseMLD bias

(m)SLD bias

(m)BLG bias

(ms-1/100m)

Climatology(MODAS)

-26 -27 2.1

Synthetic(MODAS)

-30 -27 1.2

Standard GNCOM -13 -12 0.7

GNCOM assimilating MLD-modified synthetics

-5 -7 0.3

Median observed value (not bias)

MLD41

SLD47

BLG-11.6

Statistics based on 43,474 T,S profiles from 2006. Profiles are compared with nearest climatology, synthetic, and GNCOM nowcasts.

None of the products here assimilate profiles.

Validate model attributes that are relevant to key products

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Median statistics relative to 6,942 T,S profiles over the Western North Pacific.

CaseMLD bias

(m)SLD bias

(m)BLG bias

(ms-1/100m)

Climatology(MODAS)

-28 -24 2.1

Synthetic(MODAS)

-34 -27 1.8

Standard GNCOM -11 -9 1.0

GNCOM assimilating MLD-modified synthetics

-1 -4 0.3

Median observed value (not bias)

MLD 39

SLD44

BLG-11.6

Statistics based on 6,942 T,S profiles from 2006. Profiles are compared with nearest climatology, synthetic, and GNCOM nowcasts.

None of the products here assimilate profiles.

Validate model attributes that are relevant to key products

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Product example: currents for search and recovery

Adam Air flight 574 crashed in the Java Sea on 1 January 2007.

USNS Mary Sears assisted in search and recovery, locating black boxes on 21 January.

initial crash debris

Pinger LocationsNTSB location

Reverse 10-day trajectories starting from debris field

Forward 10-day trajectories starting around crashsite

EAS NCOM results (nested within global NCOM) guided the search by predicting sources of debris that washed ashore ten days after the crash and evaluating debris distributions from potential crash sites.

RegionPersist

(km)V2.0(km)

V2.5(km)

V2.0a(km)

V2.5a(km)

Clim(km)

V (cm s-1)

n pairs

Celtic-Biscay-North Sea 16.55 15.53 13.63 13.76 13.68 16.21 19 2819Iberia Region 10.89 11.72 10.35 10.12 10.36 11.71 19 2843

Humboldt Current 12.60 11.85 11.29 10.73 11.20 11.53 21 6550Eastern North Pacific 14.75 14.67 12.94 12.78 12.91 14.38 22 6420

Brazil Malvinas 17.81 16.74 15.31 15.06 15.28 16.77 23 13349Gulf of Alaska 13.52 13.90 12.12 12.12 12.31 13.70 23 2371

Benguela Current 17.15 16.76 15.32 15.89 15.46 15.77 24 3292Black Sea 17.00 16.96 16.02 16.15 16.01 16.03 24 1130

Australia - New Zealand 18.26 16.90 15.31 15.40 15.36 16.66 25 4459Central Pacific 22.20 17.00 16.13 16.06 16.17 18.68 26 7855Gulf of Guinea 18.90 17.40 16.65 17.90 17.75 17.24 28 5182

Equatorial Atlantic 16.42 15.14 14.30 14.67 14.78 14.65 29 15607North Atlantic 17.92 17.71 15.91 15.90 16.06 17.30 29 41155Pacific Islands 23.60 18.82 17.90 18.38 18.44 20.44 29 36512

Japan/East Sea 21.61 20.82 18.96 19.00 19.42 19.76 30 1646South China Sea 33.63 24.64 22.40 23.79 23.24 26.95 30 2793

Tehuantepec 25.50 19.14 17.82 18.05 18.23 22.10 30 9537Equatorial Pacific 24.45 19.18 18.50 18.82 19.22 20.57 32 44482

Indian Ocean 25.20 21.67 19.77 20.77 19.90 25.40 32 15661Java Sea 26.75 26.31 24.87 26.75 25.92 24.64 32 1039

Intra Americas Seas 19.67 18.76 17.20 17.66 17.21 19.13 33 6250Agulhas 29.27 24.77 22.30 22.70 22.30 26.95 34 5971

East Asian Pacific 32.12 24.20 22.10 23.03 22.43 25.71 34 5111Madagascar 30.62 26.76 24.77 25.34 24.32 26.29 34 990

Kuroshio 24.67 22.55 20.41 20.17 20.13 22.44 35 5456Taiwan 31.76 24.98 22.83 23.15 21.37 25.22 35 3201

North Brazil Current 19.74 17.68 17.49 17.17 17.80 18.09 36 2743Arabian Sea 27.90 23.78 21.11 22.50 21.75 28.68 38 2978

Gulf of Mexico 25.53 22.88 21.32 22.15 21.75 23.58 38 546Gulf Stream 23.49 22.66 20.22 20.76 20.31 21.81 38 3499

Top 0.00% 0.00% 60.00% 26.67% 16.67% 3.33%In top 2 0.00% 0.00% 86.67% 43.33% 60.00% 10.00%

RMS separation (km) after one day between observed and simulated drifter trajectories for experiments in 2003.

Regions sorted by increasing V.

Best results are highlighted in green, second-place in grey.

200,000 + comparisons

see Barron et al., J. Geophys Res., 2007.

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Assessment Summary

• RMS drifter separation after one day

• prior operational V2.0 and new V2.5 (1/16° to 1/32° NLOM, no mean correction)

• RMS error is linearly proportional to σV.

• 8% reduction in prediction uncertainty

• 15% reduction in predicted search area

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2008Future Plans

Similar metrics are being applied to planned upgrades. Upgrades will transition to operations if they demonstrate improved performance.

Global HYCOM

Global HYCOM• ~6.5 km avg. spacing• 32 hybrid layers• Cycling NCODA assimilation• ESMF-coupled CICE

ISOPNew covariances, EOF models to estimate synthetic profiles

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Operational Navy Assimilative Ocean Modeling

Summary

• Identify key products

• Focus on relevant metrics

• Establish performance of present system

• Demonstrate benefit of potential upgrades

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2008Backup slides