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ESTIMATION OF SEA LEVEL VARIABILITY FROM OCEAN MODELS. Gabriel Jordà, F. M. Calafat, M. Marcos, D. Gomis, S. Somot, E. Álvarez-Fanjul, I. Ferrer. Introduction - Sea Level variability. December 2001. December 2008. Introduction – Factors affecting SL variability. Tsunamis - PowerPoint PPT Presentation
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Gabriel Jordà, F. M. Calafat, M. Marcos, D. Gomis, Gabriel Jordà, F. M. Calafat, M. Marcos, D. Gomis, S. Somot, E. Álvarez-Fanjul, I. FerrerS. Somot, E. Álvarez-Fanjul, I. Ferrer
ESTIMATION OF SEA LEVEL VARIABILITY ESTIMATION OF SEA LEVEL VARIABILITY FROM OCEAN MODELSFROM OCEAN MODELS
December 2001December 2001
Introduction - Sea Level variability
December 2008December 2008
TsunamisTsunamis
Astronomical forcing – Astronomical forcing – tidestides
Waves Waves
Atmospheric mechanical forcing Atmospheric mechanical forcing – – A. pressure, windA. pressure, wind
Steric ContributionSteric Contribution
Mass content variationsMass content variations
Introduction – Factors affecting SL variability
WHY ?WHY ?
To understand
To predict
KINDS OF MODELSKINDS OF MODELS
Wave models
Tidal models
2D barotropic models Mechanical forcing
3D baroclinic modelsSteric and sometimes mass content
Introduction – Modelling SL variability
High accuracy
This talk
Relevant at regional scale (not at global Relevant at regional scale (not at global scale)scale)
Based on Shallow-water equationsBased on Shallow-water equations
Barotropic modelsBarotropic models
Forced by wind, atmospheric pressure Forced by wind, atmospheric pressure and/or tidesand/or tides
Finite difference (i.e. HAMSOM) or finite Finite difference (i.e. HAMSOM) or finite Elements models (i.e. MOG2D)Elements models (i.e. MOG2D)
Usually provide high quality results Usually provide high quality results “short-memory” systems“short-memory” systems
2D models – Overview
GOAL GOAL
To model the atmospheric component of To model the atmospheric component of the Sea Level variabilitythe Sea Level variability
- HAMSOM model - HAMSOM model
- Spatial resolution 1/6x1/8ºSpatial resolution 1/6x1/8º
- Forcing: downscaling of atmospheric pressure and wind fields generated - Forcing: downscaling of atmospheric pressure and wind fields generated by the model REMO (from a NCEP re-analysis) by the model REMO (from a NCEP re-analysis)
- Period 1958-2001 Period 1958-2001
- Hourly sea level outputHourly sea level output
2D models – Example: HIPOCAS project
Gijón
Málaga
Measured (red); Model simulation (blue)
Improvement respect to IB:Improvement respect to IB: Difference between the variance of TG data corrected by the IB response and the variance of TG data corrected by the atmospheric models [VAR(TG-IB) – VAR(TG – model)].
2D models – Example: HIPOCAS project
Validation
Ratsimandresy et al., 2008
Sea level trends (mm/yr) induced by atmospheric pressure and wind
1993-20001993-2000
2D models – Example: HIPOCAS project
Results - Trends
-2 mm/year3 mm/year
-1.25 mm/year -0.25 mm/year
1958-19931958-1993
The model helped to understand the low sea level increase between 1960-1993
Gomis et al., 2006
Extreme values for the periods measured by tide gauges (few yr to decades)Tidal component removed
Values for 50-yr return period
Results from a 2D model
2D models – Example: HIPOCAS project
Results - Extremes
Marcos et al., 2009
Even if the model underpredicts the results it provides a good estimation over the whole basin
01z
H
SSL dpg
Primitive equations modelsPrimitive equations models
Baroclinic termsBaroclinic terms
Air-sea interactionAir-sea interaction
River runoffRiver runoff
Rigid lid Rigid lid (z(z00=0)=0) / Free surface / Free surface (z(z00
Usually provide lower quality results Usually provide lower quality results “long-memory” systems“long-memory” systems
3D models – Overview
GOAL GOAL
To model the steric (To model the steric (and mass changes)and mass changes) component of the Sea Level variabilitycomponent of the Sea Level variability
3D models – Overview
Global ModelsGlobal Models
No lateral boundary conditions problemsNo lateral boundary conditions problems
Can directly account for global mass increaseCan directly account for global mass increase
Low resolution (some processes not solved)Low resolution (some processes not solved)
Gibraltar Strait not solvedGibraltar Strait not solved
Usually they are rigid lidUsually they are rigid lid
Regional ModelsRegional Models
Higher resolution – local processes can be solvedHigher resolution – local processes can be solved
Gibraltrar Strait could be explicitely solved (but not always)Gibraltrar Strait could be explicitely solved (but not always)
At present they are switching to free surfaceAt present they are switching to free surface
Lateral boundary conditions problemsLateral boundary conditions problems
Link to global processes is not straightforwardLink to global processes is not straightforward
Regional modelRegional model
High resolution (1/8˚ x 1/8˚, 43 non-High resolution (1/8˚ x 1/8˚, 43 non-uniform vertical Z-levels) model for the uniform vertical Z-levels) model for the Mediterranean Sea (OPA model). Somot Mediterranean Sea (OPA model). Somot et al., 2006et al., 2006
Period 1961-2000Period 1961-2000
Atmospheric forcing was based on ERA-Atmospheric forcing was based on ERA-40 high resolution 40 high resolution
Rigid lid configurationRigid lid configuration
The Mediterranean Sea simulation is then The Mediterranean Sea simulation is then driven by air-sea fluxes which (1) have a driven by air-sea fluxes which (1) have a high resolution (50 km), (2) are high resolution (50 km), (2) are homogeneous over a long period of time homogeneous over a long period of time (no change in the model configuration), (no change in the model configuration), (3) follow the real synoptic chronology and (3) follow the real synoptic chronology and (4) have a realistic interannual variability. (4) have a realistic interannual variability.
Global Global modelmodel
ORCA025 global configuration of the ORCA025 global configuration of the ocean/sea-ice general circulation model ocean/sea-ice general circulation model NEMO horizontal resolution of 1/4° and 46 NEMO horizontal resolution of 1/4° and 46 vertical levelsvertical levels
Period 1958-2004Period 1958-2004
Barnier et al.,2006Barnier et al.,2006
01
H
dpg
SSL
3D models – Example
Model results give positive trends, but are submitted to eventual drifts…Model results give positive trends, but are submitted to eventual drifts…
MEDAR data give negative trends, but the coverage might be partial…MEDAR data give negative trends, but the coverage might be partial…
• Comparison of different models with in situ data:
Yearly time series of steric sea level (ref. level at 300 m) and averaged over two sub-basins
ORCA025 (global) model OPAMED8 (regional) model MEDAR data base
3D models – Example: Hindcast mode
Results - Trends
Comparison of altimetric (blue) and modelled (red) averaged sea level for selected areas. Dashed lines are 12 month running averages.
At regional scale results improve but there can be relevant extreme events (climate transitions very difficult to predict)
3D models – Example: Hindcast mode
Results - Trends
3D models – Example: Forecast mode
Results – XXI century trends
T changes 0-2.5 ºC
S changes 0-2 psu
Temperature Salinity
SR
ES
A1B
SR
ES
A2
Com
mitt
ed C
C
1.2ºC
0.3 psu
T and S projections of an ensemble of ten global models and one regional model
Marcos et al., 2008
3D models – Example: Forecast mode
Results – XXI century trends
Halosteric component
Thermosteric component
SR
ES
A1B
SR
ES
A2
Com
mitt
ed C
C
35 cm
-25 cm
Total steric component
Components of the steric part of sea
level trends
Halosteric sea level:Halosteric sea level: -70 to 20 cm-70 to 20 cmThermosteric sea level: Thermosteric sea level: 5 to 55 cm5 to 55 cmRange of total variationRange of total variation-42 to 52 cm -42 to 52 cm
Marcos et al., 2008
Spatial patterns of steric sea level
+ circulation changes
3D models – Example: Forecast mode
Results – XXI century trends
Other open issues: Mixing, lack of DW formation, LBC
3D models – Are they doing a proper job in the Med Sea?
Conceptual model - Effects of exchanges across Gibraltar
MED
Tmed
Smed
ATLANTIC
Tatl=ct
Satl=ct
GIB
E-P-RHeat Fluxes
IN
OUT
Jordà et al., in prep.
2 1
1
2 2 1 1
0.7
( )
( , ), ( , )
IN OUT
OUT
dilatation
dilatation Med
ref ref
Sv
AE P R
t
z
T S T S
netMED ATL
e IN
Q AT T
C
INMED ATL
OUT
S S
3D models – Are they doing a proper job in the Med Sea?
Conceptual model - Effects of exchanges across Gibraltar
Simple modelSimple model
netMED ATL
e IN
Q AT T
C
IN
MED ATLIN
t
VS St V
V V V
0
( )
IN
OUT IN
dilatation
AE P R
t
Rigid lid modelRigid lid model
>>>>> Initial state Input flux =0.80 Sv Tmed=12.44º Smed=38.86psu
>>>>> Final State Input flux =0.79 Sv Tmed=13.83º Smed=38.19psu
>>>>> AtlanticTatl=16.00Satl=34.00Assuming invariant
>>>>> Final State Input fluxe =0.79 Sv Tmed=13.83º Smed=39.86psu
3D models – Are they doing a proper job in the Med Sea?Conceptual model - Effects of exchanges across Gibraltar
Simple modelSimple model Rigid lid modelRigid lid model
•2D Models – good results. 2D Models – good results. Give reliable information about atmospheric influence on Sea LevelGive reliable information about atmospheric influence on Sea Level
•Quality rely on bathymetry and Quality rely on bathymetry and Atmospheric fieldsAtmospheric fields
•3D Models – More complex models - 3D Models – More complex models - Not as good as 2D model resultsNot as good as 2D model results..
•Ocean climate models present large discrepancies at regional scaleOcean climate models present large discrepancies at regional scale
•Models cannot predict climate transients.Models cannot predict climate transients.
•High resolution is needed to solve particular processes (Gibraltar High resolution is needed to solve particular processes (Gibraltar exchanges, DW formation, internal mixing , …)exchanges, DW formation, internal mixing , …)
•At present there are some essential questions that must be solved: At present there are some essential questions that must be solved: Gibraltar Strait parametrization, LBC (Gibraltar Strait parametrization, LBC ( link to global processes link to global processes), role of DW ), role of DW formation in the climate simulationsformation in the climate simulations
Summary
FUTURE WORKFUTURE WORK