1. Modelling global mean sea level change through global mean temperatue: physical consistency
Eduardo Zorita and Hans von Storch
Institute for Coastal Research
GKSS Research Centre

2. Past sea-level evolution is not completely understood
Rahmstorf 2006
Past sea-level evolution is not completely understood
Predictions for the future are uncertain
Empirical approach
d (sea-level)/dt ~ Temperature
<-200 years->
sea-level rate
temperature

3. On Rahmstorf´s study
Implies potential to predict sea level change given a temperature change
„Plausible“ sea level change per 2100: +1,40 m
Published in „science“ …
Strong response in the public, e.g., Delta Commissie
Comment based on econometric methodology: flawed methodology - a trend fitting exercise.
Even if the statistical fitting exercise was flawed – the link may be physically sound.

4. Testing … Testing the link in the virtual reality of climate models.
Models describe mostly only thermal expansion; not ice sheet growing and melting. Thus, a test of the methodology in such models is liberal.
Rahmstorff did this with CLIMBER, and found an overestimate at the end of the 21th century by about 30%.
We have tested the methodology in a historical simulation with ECHO-G. (“Erik”)

5. Erik: f90, NEC No tropospheric aerosols No ozone photochemistry
No vegetation changes

6. Semi-quantitative agreement between CSM and ECHO-G simulations

8. ~0.42 mm/year

10. d (sea-level)/dt ~ Temperature
Rahmstorf 2006
d (sea-level)/dt ~ Temperature
<-200 years->
sea-level rate
temperature

11. Variability of the regression coefficient in sliding time-windows:
dH/dt ~ T

12. Variability of the regression coefficient in sliding time-windows:
dH/dt ~ dT/dt

13. Conclusion
Global mean temperature is not a good predictor for the thermosteric sea-level change
The best predictor (among those tested in the simulation is surface heat-flux (but difficult to measure - no time series)‏
The time derivative of temperature is a better predictor for sea-level variations