“Estimates of (steric) SSH rise from ocean syntheses" Detlef Stammer Universität Hamburg SODA (J. Carton) AWI roWE (J. Schroeter, M. Wenzel) ECCO.
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Presentation on theme: "“Estimates of (steric) SSH rise from ocean syntheses" Detlef Stammer Universität Hamburg SODA (J. Carton) AWI roWE (J. Schroeter, M. Wenzel) ECCO."— Presentation transcript:
“Estimates of (steric) SSH rise from ocean syntheses" Detlef Stammer Universität Hamburg SODA (J. Carton) AWI roWE (J. Schroeter, M. Wenzel) ECCO (R. Ponte, P. Heimbach, C. Wunsch) GECCO (A. Koehl, T. Yemenis)
SEA LEVEL from Ocean Syntheses: Urgent questions posed to synthesis efforts: What is the rate of sea level rise over the past 50 years, the past 10 years, and at the present time? What are the steric and eustatic components of global sea level rise? How are the global signals distributed regionally? What are the causes of observed changes in sea level, globally and regionally?
SEA LEVEL from Ocean Syntheses: Several synthesis attempts are underway regionally, some also globally; most are 1992 to present. roWE and ECCO are examples. The community is now also approaching 50 year long syntheses paralleling the NCEP reanalysis. SODA (Simple Ocean Data Assimilation) is an example. Syntheses based on mathematically rigorous assimilation approaches are now becoming available over 50 years which will enabling analysis of CLIVAR relevant climate indices, e.g., strength of the MOC and sea level change. GECCO is an example.
SODA steric SSH rise since 1960 Look at causes later Levitus SODA thermosteric
roWE - upper ocean heat content - local linear trend - Less variability in synthesis! similar to GECCO
ECCO/MIT Regional sea level trends ECCO/MIT Regional 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 contributions Layer 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) from 50 year run. 1993-2002 1952-2001 Results from 50 yr GECCO run are much closer to observations than those from ECCO 12 yr run.
Heat Content Changes in 50 yr GECCO Estimates. ECCO looses heat in the top 500 m during the 70 th, mainly In the tropics.
GECCO and Willis et al. upper 700 m steric estimate. GECCO gains salt; problems with freshwater cycle in southern ocean.
GECCO and Willis et al. upper 700 m steric. Data sampling
What Causes the Sea Level Change? Extra Optimization over 1992 through 2002 that constrains SSH drift to disappear. Constraints SSH drift plus control terms. Control parameter: T0, S0, surface forcing. Results can show parameter that forces changes in SSH and its geographic 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
Conclusions Much of the recent rise can be explainable by increases in the thermosteric component. The thermosteric component has substantial decadal and regional variability. Model reproduce the data satisfac-torily in various aspect, 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 the (thermo-)steric effect(s). But also dependent on approach. The thermosteric sea level rise stems from all layers. About 1/2 the contribution comes from below 512m depth. In some results the halosteric contribution from different layers 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 size as the thermosteric in many places. It partly compensates the thermosteric, especially at the deeper layers
Conclusions 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. 1.Global freshwater cycle. 2. 2.Boussinesque approximation.
Thank you Thank you for your attention for your attention
measured sea level rise (data from GfZ Potsdam) measured sea level rise (data from GfZ Potsdam)
how do we proceed ? fit of an ocean model to the SSH data using the adjoint method: define cost function: J define cost function: J define control parameters: u define control parameters: u fit the model to the data fit the model to the data 1. first guess of control parameters 2. compute the cost function value 3. compute the gradient of the cost function: dJ/du 4. improve the controlparameters using a 'descent' algorithm 5. repeat steps 2. to 4. until an acceptable minimum of the cost is reached what is the models interpretation of the data ?
global ocean model (LSG) resolution horizontal: 2x2 degr. vertical: 23 layers (20m,... 750m, bottom layer variabel) timestep: 10 days forcing windstress air temperature surface freshwater flux free surface