Supervisor : Eric Chassignet
description
Transcript of Supervisor : Eric Chassignet
11Supervisor: Eric Chassignet
Louis-Nicolas CARRIL MURTA
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OutlineOutline
• MotivationMotivation• ARGO float systemARGO float system• HYCOMHYCOM• Data and model outputsData and model outputs• ComparisonComparison• ConclusionConclusion
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MotivationMotivation
•Aim?Aim?
– To evaluate the performance of the To evaluate the performance of the global HYCOM ocean prediction global HYCOM ocean prediction systemsystem
– To improve the global HYCOM ocean To improve the global HYCOM ocean prediction systemprediction system
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ARGO’s float ARGO’s float systemsystem
• Origin : WOCE Origin : WOCE 1990-19971990-1997
• Data transmitted by satelliteData transmitted by satellite
• Hydraulic system to descend Hydraulic system to descend till 2000m depthtill 2000m depth
• Provide a global quantitative Provide a global quantitative ocean variability, ocean variability, salinity, salinity, temperature, velocity with temperature, velocity with profilesprofiles
• Used for Used for model validationmodel validation
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Float’s distributionFloat’s distribution
Lack of floats
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• Hybrid model: combine 3 vertical discretizationsHybrid model: combine 3 vertical discretizations– z-level in unstratified regions like the mixed layerz-level in unstratified regions like the mixed layer– Density coordinates in stratified regionsDensity coordinates in stratified regions– Terrain-following coordinates in coastal regionsTerrain-following coordinates in coastal regions
• Solve oceanic physical processesSolve oceanic physical processes• Global 1/12° horizontal resolutionGlobal 1/12° horizontal resolution• Forced by NOGAPS, assimilation of observed T, Forced by NOGAPS, assimilation of observed T,
S, SSH S, SSH • Hindcast runs: velocities, temperature, salinityHindcast runs: velocities, temperature, salinity
HYCOMHYCOM Ocean Prediction System Ocean Prediction System
(HYbrid Coordinate Ocean Model)(HYbrid Coordinate Ocean Model)
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ARGO data & HYCOM ARGO data & HYCOM outputsoutputs
•ARGO data :ARGO data :– Salinity & temperature :Salinity & temperature :
•From 2004 to 2007From 2004 to 2007
•Daily dataDaily data
•Profiles (scattered Profiles (scattered data)data)
– VelocityVelocity
•Mean from 1997 to Mean from 1997 to 20072007
•3°X3° rectilinear grid3°X3° rectilinear grid
•HYCOM outputs :HYCOM outputs :– Velocity, salinity and Velocity, salinity and
temperature :temperature :
•From 2004 to From 2004 to 20072007
•Daily outputsDaily outputs
•Global 1/12° Global 1/12° curvilinear gridcurvilinear grid
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HYCOM ARGO psu
°C
SALINITY SALINITY
TEMPERATURE TEMPERATURE
SURFACE TEMPERATURE AND SALINITY (2004-2007)
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0
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15
510
20
25
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Surface U VelocitySurface U VelocityHYCOM ARGO
cm/s
2004-2007 average 1997-2007 average
20 15 10 5 -5 -10 -15 -200
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ComparisonComparison
•Global differences:Global differences:– Average of 2004 to 2007Average of 2004 to 2007– Seasonal averageSeasonal average
•Correlation (SST only):Correlation (SST only):– Monthly average linear regressionMonthly average linear regression
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2004-2007 (ARGO-HYCOM)2004-2007 (ARGO-HYCOM)°C & psu
TEMP SALINITY
TEMP SALINITY
Surface Surface
1000m 1000m
1.5
1
0.5
-0.5
-1
-1.5
-2
0
2
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Seasonal SST (ARGO-HYCOM)Seasonal SST (ARGO-HYCOM)
°C
Summer Fall
Winter Spring
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Coefficient of Linear Coefficient of Linear Regression Regression
~ 1
HYCOM & ARGO
correlated
~ 0
No correlation
~ -1
HYCOM & ARGO
opposite relationship
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ConclusionConclusion
• HYCOM global configuration provides HYCOM global configuration provides a good approximation of mean a good approximation of mean salinity, temperature and velocity for salinity, temperature and velocity for long time periodslong time periods
• But HYCOM appears to not But HYCOM appears to not accurately capture the monthly accurately capture the monthly variationsvariations
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1000 m U Velocity1000 m U VelocityHYCOM ARGO
cm/s
2004-2007 average 1997-2007 average
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SalinitySalinityHYCOM ARGO
Parking pressure 1000m
psu
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TemperatureTemperatureHYCOM ARGO
Parking pressure 1000m
°C