““Estimates of (steric) SSH rise Estimates of (steric) SSH rise from ocean syntheses" from ocean syntheses"

Detlef StammerDetlef Stammer

Universität HamburgUniversität Hamburg

SODA (J. Carton) SODA (J. Carton)

AWI roWE (J. Schroeter, M. Wenzel)AWI roWE (J. Schroeter, M. Wenzel)

ECCO (R. Ponte, P. Heimbach, C. Wunsch)ECCO (R. Ponte, P. Heimbach, C. Wunsch)

GECCO (A. Koehl, T. Yemenis)GECCO (A. Koehl, T. Yemenis)

SEA LEVEL from Ocean Syntheses:SEA LEVEL from Ocean Syntheses:

Urgent questions posed to synthesis efforts: Urgent questions posed to synthesis efforts: What is the rate of sea level rise over the past 50 years, the What is the rate of sea level rise over the past 50 years, the

past 10 years, and at the present time? past 10 years, and at the present time? What are the steric and eustatic components of global sea What are the steric and eustatic components of global sea

level rise? level rise? How are the global signals distributed regionally?How are the global signals distributed regionally? What are the causes of observed changes in sea level, What are the causes of observed changes in sea level,

globally and regionally? globally and regionally?

SEA LEVEL from Ocean Syntheses:SEA LEVEL from Ocean Syntheses:

Several synthesis attempts are underway regionally, some also Several synthesis attempts are underway regionally, some also globally; most are 1992 to present. globally; most are 1992 to present. roWE and ECCO are roWE and ECCO are examples.examples.

The community is now also approaching 50 year long syntheses The community is now also approaching 50 year long syntheses paralleling the NCEP reanalysis. paralleling the NCEP reanalysis.

SODA (Simple Ocean Data Assimilation)SODA (Simple Ocean Data Assimilation) is an example. is an example. Syntheses based on mathematically rigorous assimilation Syntheses based on mathematically rigorous assimilation

approaches are now becoming available over 50 years which will approaches are now becoming available over 50 years which will enabling analysis of CLIVAR relevant climate indices, e.g., enabling analysis of CLIVAR relevant climate indices, e.g., strength of the strength of the MOCMOC and and sea level changesea level change..

GECCOGECCO is an example. is an example.

SODA steric SSH rise since 1960SODA steric SSH rise since 1960

Look at causes later

Levitus

SODA

SODAthermosteric

Comparison of Comparison of Sea Level spectra Sea Level spectra at Bermudaat Bermuda

Where is the heat being stored?Where is the heat being stored?10S-10N, within thermcline Some westward redistribution

Time series of redistribution is similar to PDO Index

AWI roWE: upper ocean heat content AWI roWE: upper ocean heat content - local linear trend -- local linear trend -

Model Result

from Willis' analysis

roWE - global sea level trends -roWE - global sea level trends -

TOPEX 3.37 mm/year

model eustatic 1.07 mm/yearsteric 2.47 mm/yeartotal 3.53 mm/year

thermosteric 0 - 512m 1.52 mm/year512 – 2250m 0.55 mm/year2250m – bottom 0.38 mm/yeartotal 2.45 mm/year

halosteric 0 - 512m 0.22 mm/year512 – 2250m -0.15 mm/year2250m – bottom -0.06 mm/yeartotal 0.02 mm/year

roWE - upper ocean heat contentroWE - upper ocean heat content- local linear trend -- local linear trend -

Less variabilityin synthesis!

similarto GECCO

ECCO/MIT ECCO/MIT Regional sea level trendsRegional sea level trends

Altimeter (courtesy of S. Nerem)

Altimeter rms errors

Control run (no optimization) Optimized solution (ECCO-GODAE)

range (-16 to 16 mm/yr)

; range (0-30 cm)

Layer contributionsLayer contributions

Zonally averaged trends

• Major contributions from upper 800 m but measurable signals from lower layers at many latitudes as well

• Omission of subthermocline layers can lead to errors that might grow with time as surface signals penetrate the abyss

(more details in poster by Wunsch, Ponte and Heimbach)

Thermosteric

Halosteric

(mm/yr)

GECCO Sea Level Rise (cm/yr)GECCO Sea Level Rise (cm/yr) from from 50 year run. 50 year run.

1993-2002

1952-2001

Results from 50 yrGECCO run are much closer to observations than those from ECCO 12 yr run.

Heat Content Changes in 50 yr GECCO Estimates.

ECCO loosesheat in the top 500 m

during the 70th, mainly In the tropics.

GECCO and Willis et al. upper 700 m steric estimate.

GECCOgains salt;

problems with freshwater cycle

in southern ocean.

GECCO and Willis et al. upper 700 m steric.

Data sampling

What Causes the Sea Level What Causes the Sea Level Change?Change?

Extra Optimization over 1992 through 2002 Extra Optimization over 1992 through 2002 that constrains SSH drift to disappear.that constrains SSH drift to disappear.

Constraints SSH drift plus control terms. Constraints SSH drift plus control terms. Control parameter: T0, S0, surface forcing.Control parameter: T0, S0, surface forcing. Results can show parameter that forces Results can show parameter that forces

changes in SSH and its geographic changes in SSH and its geographic distribution.distribution.

Top right: TP SSH trend 1993 - 2002.

Top left: SSH drift 1993 – 2002 in 50yr run.

Bottom: SSH drift explained by T,S anomalies from the beginning 1992: observed SSH changes are largely a result of steric anomaly existing 1992.

Effect of initial T,S

ConclusionsConclusions

Much of the recent rise can be explainable by increases in the Much of the recent rise can be explainable by increases in the thermosteric component.thermosteric component.

The thermosteric component has substantial decadal and regional The thermosteric component has substantial decadal and regional variability. Model reproduce the data satisfac-torily in various aspect, variability. Model reproduce the data satisfac-torily in various aspect, but sampling is important, as are details of the assimilation.but sampling is important, as are details of the assimilation.

~1/3 of the global sea level trend is caused by eustatic effects, ~2/3 by ~1/3 of the global sea level trend is caused by eustatic effects, ~2/3 by the (thermo-)steric effect(s). But also dependent on approach.the (thermo-)steric effect(s). But also dependent on approach.

The thermosteric sea level rise stems from all layers. About 1/2 the The thermosteric sea level rise stems from all layers. About 1/2 the contribution comes from below 512m depth. contribution comes from below 512m depth.

In some results the halosteric contribution from different layers In some results the halosteric contribution from different layers compensate to a small residual, indicating a redistri-bution of salt from compensate to a small residual, indicating a redistri-bution of salt from the top layers to depth. In other results the halosteric part is of the same the top layers to depth. In other results the halosteric part is of the same size as the thermosteric in many places. It partly compensates the size as the thermosteric in many places. It partly compensates the thermosteric, especially at the deeper layersthermosteric, especially at the deeper layers

ConclusionsConclusions

The most important contribution to the observed SSH trend comes from the adjustments to the initial conditions 1992 (almost 50\% of the whole SSH trend).

The contribution from the adjustments to the wind stress are important --especially in the equatorial regions-- but more moderate. They can explain about 20-25\% of the SSH trend.

The adjustments to heat and freshwater fluxes have a minor contribution to the SSH trend with the exception of the polar regions. Their contribution is about 10\% each.

There are two fundamental problems in ocean state estimates regarding global SSH changes:1. Global freshwater cycle.2. Boussinesque approximation.

Thank youThank you for your attentionfor your attention

measured sea level risemeasured sea level rise(data from GfZ Potsdam)(data from GfZ Potsdam)

how do we proceed ?how do we proceed ? fit of an ocean model to the SSH data using the fit of an ocean model to the SSH data using the

adjoint method:adjoint method: define cost function: define cost function: JJ define control parameters: define control parameters: uu fit the model to the datafit the model to the data

1.1. first guess of first guess of control parameters control parameters

2.2. compute the cost function valuecompute the cost function value

3.3. compute the gradient of the cost function: compute the gradient of the cost function: ddJJ/d/duu4.4. improve the controlparameters using a 'descent' improve the controlparameters using a 'descent'

algorithmalgorithm

5.5. repeat steps 2. to 4. until an acceptable minimum of repeat steps 2. to 4. until an acceptable minimum of the cost is reachedthe cost is reached

what is the models interpretation of the data ?what is the models interpretation of the data ?

global ocean model (LSG)global ocean model (LSG) resolutionresolution horizontal: 2x2 degr.horizontal: 2x2 degr. vertical: 23 layers (20m, ... 750m, bottom layer variabel)vertical: 23 layers (20m, ... 750m, bottom layer variabel) timestep: 10 daystimestep: 10 days

forcingforcing windstresswindstress air temperatureair temperature surface freshwater fluxsurface freshwater flux

free surfacefree surface

surface elevationsurface elevation

data in usedata in use

SSHA TOPEX/Poseidon 1993-2003 (GfZ, Version 3)

MSSH SHOM98.2 (CLS) rel. EIGEN-GRACE01S geoid

SST Reynolds SST 1993-2003

WOCE Global Hydrographic ClimatologyGouretski und Koltermann (2004)

WOA01

mean transports heat, freshwater and mass

section data Ross Sea, Weddell Sea from BRIOS model runsAssmann and Timmermann (2005), Schodlok et al. (2002)

T/S (mean)

T/S (monthly anomalies)

from Siedler et al (edt.): Ocean Circulation and Climate

control parametercontrol parameter

initial state: temperaturesalinitysurface elevation

forcing fields: windstressair temperaturesurface freshwater flux

Köhl and Stammer (in preparation, 2006)

Input Data Sets and Controls