1. Comparing the Greenhouse Sensitivities of CCM3 and ECHAM4.5
Ed Schneider
George Mason U, COLA
Ben Cash
COLA
Lennart Bengtsson
MPI Hamburg, Reading U.

2. Purpose of Talk
Inform CCSM community about what we’re doing with/to CAM before publicizing the results to the broader community.
Gather comments and consider criticisms/objections from the CCSM community on our approach.

3. Outline of Talk Global mean sensitivity Regional sensitivity
Motivation
Project description
Work in progress
Regional sensitivity

4. The Problem
Global mean and regional sensitivity to 2CO2 of surface temperature and precipitation varies widely between GCMs. The causes of this “uncertainty” are not as well understood as they should be.
In my opinion: Lack of understanding (and lack of interest in understanding) differences between models indicates a breakdown in the research process.

5. Climate Sensitivity: Global Mean (IPCC 2001)

6. Biggest Problem
No “x” plotted for observations against which to verify the models.

7. Investigation I Global mean sensitivity to doubled CO2
Isolate and understand the causes of global mean surface temperature and precipitation equilibrium climate sensitivity differences between a small number of models
currently two models: CCM3 (CAM1.0) and ECHAM4.5

8. Prior Work
Understanding differences in results from two coupled models by creating hybrid models, eliminating differences one step at a time.

9. Equatorial Pacific Annual Mean SST (Schneider, 2002)

10. Methodology Global sensitivity differences
Isolate those pieces of code (e.g. parameterizations, parameter choices, …) that lead to the largest differences in sensitivity between pairs of models: i.e. swap parameterizations.

11. Published Global Mean Sensitivities
Temperature
CCM3.6: 
ECHAM 4.5: 
Precipitation
CCM3.6: moderate increase
ECHAM4.5: small increase

12. Procedure
Run 2xCO2 minus control equilibrium simulations and verify published sensitivities.
Mixed layer ocean + sea ice
Q-flux adjusted
Eliminate differences between models one parameterization at a time and recalculate equilibrium sensitivities until convergence.
Develop appreciation of the value of the CCSM infrastructure.

13. Details First steps: Do not retune models at each step (?)
1) eliminate sea ice (done)
2) use same mixed layer ocean (in progress)
3) CCM3 clouds in ECHAM (in progress)
Do not retune models at each step (?)

14. Model Comparison Implied Oceanic Heat Flux Divergence: ECHAM4.5-CCM3
Looks a lot like cloud distribution.

15. CCM3 Temperature Sensitivity with sea ice feedback
Global sensitivity: 2.1 o K

16. CCM3 Temperature Sensitivity without sea ice feedback
Global sensitivity: 1.8o K

17. CCM3 Regional Temperature Sensitivity
1xCO2 (with sea ice) – 1xCO2 (without sea ice)

18. Weighted Cloud Fraction Sensitivity
Comparison between 2xCO2 and 1xCO2 without sea ice
(1xCO2,No Sea Ice) - Control
(2xCO2,With Sea Ice) - Control

19. CCM3 Precipitation Sensitivity with sea ice feedback
mm/day

20. CCM3 Precipitation Sensitivity without sea ice feedback
mm/day

21. Regional Climate Sensitivity
Are regional differences in atmospheric circulation in CMIP2 (1%/year CO2 increase in coupled models) at time-of-doubling caused by
Model dependent response to tropical SST increase?
Model responses to different tropical SST increases?
Something else?

22. Regional Climate Sensitivity (J. Räisänen CMIP2 Subproject)

23. Methodology II Regional sensitivity differences
Extratropical response to (primarily) tropical warming – atmospheric GCMs forced by specified SST obtained from CMIP2 project (+ΔCO2)
Effect of observed SST on different models (model verification)
Effect of different SST forcing in same model
Effect of same SST on different models

24. Forced Trends in AGCMs
There has been a significant trend observed during for NH winter in SST and 500 mb height.
Models produce different simulations of the trend when forced by the observed SST.
CCM3 (Hoerling et al., 2000)
COLA, ECHAM …

25. Trend-Forcing Verification Experiment
Force long AGCM simulations with steady SST anomalies from the end points of the observed trend (Schneider, Bengtsson, and Hu, 2003).
TOGA SST anomalies.
Compare 500mb height response against model ensemble forced by observed time dependent SSTA and model vs. model.

26. CCM3 Ensemble (Hoerling, Hurrell, and Xu, 2000)

27. CCM3 TOGA Ensemble and Trend-Forced
Trend-forced TOGA (x2)

28. CCM3, ECHAM4.5, and COLA GOGA(x2) Ensembles
CCM GOGA (x2)
ECHAM GOGA (x2)

29. Conclusions
Work is in progress to try to understand differences in global and regional climate sensitivity between models.
We are probably approaching this problem in the wrong way, but at least we’re doing something. Maybe our mistakes will suggest a better approach.