1. © Crown copyright 2006Page 1 CFMIP II sensitivity experiments Mark Webb (Met Office Hadley Centre) Johannes Quaas (MPI) Tomoo Ogura (NIES) With thanks to Adrian Lock, Damian Wilson, Andy Jones, Alejandro Bodas Salcedo CFMIP/ENSEMBLES Workshop Paris, April 2007

2. © Crown copyright 2006Page 2 Modelling and Prediction of Climate variability and change Motivation and approach We propose running sensitivity experiments to investigate the impact of different modelling assumptions on cloud feedbacks across models Two types of sensitivity experiments are proposed: 1/ Where certain radiative feedbacks loops are cut 2/ Where elements of model physics are simplified

3. © Crown copyright 2006Page 3 Modelling and Prediction of Climate variability and change For example: Fix cloud liquid water contents and radiative properties seen by radiation Does suppressing any cloud liquid water content feedback make cloud feedback more positive? Does inter-model spread in cloud feedback reduce? If so, by how much? 1/ Radiative feedback loop cutting experiments

4. © Crown copyright 2006Page 4 Modelling and Prediction of Climate variability and change For example: Put a simple stability based low cloud fraction into several models Do low level cloud feedbacks become more negative/less positive? What is the effect on inter-model spread? 2/ Replacing parametrizations with simple alternatives

5. © Crown copyright 2006Page 5 Modelling and Prediction of Climate variability and change HadGEM2 + PC2 development version (Met Office) PC2 is a Tiedtke-like cloud scheme with prognostic equations for cloud liquid, cloud ice and cloud fraction ECHAM5 – Tiedtke scheme (Johannes Quaas) MIROC3.2 - statistical/PDF scheme (Tomoo Ogura) So far we have results for fixed liquid cloud properties for PC2 and ECHAM5 Control runs are 10 year AMIP runs Climate change: control + CMIP 1% patterned SST composite Liquid cloud droplet effective radius seen by radiation: 7 microns In cloud liquid water content seen by radiation: 0.2 g/kg Pilot study (three models)

6. © Crown copyright 2006Page 6 Modelling and Prediction of Climate variability and change Impact of fixed liquid cloud radiative properties Global mean net cloud radiative response is increased in both models and this effect comes mainly from the SW - this is consistent with what we expected However the effect is much larger in ECHAM5 than in PC2, making the two models diverge rather than converge

7. © Crown copyright 2006Page 7 Modelling and Prediction of Climate variability and change Impact on control simulations Fixing the liquid cloud radiative properties has made both of the models too bright with the biggest impact in ECHAM5 We plan to retune the models by applying a scaling factor to the liquid cloud fraction seen by the radiation. We may also consider using a larger effective radius

8. © Crown copyright 2006Page 8 Modelling and Prediction of Climate variability and change Use of tendency diagnostics and GPCI transect We also plan to use cloud condensate tendency diagnostics to understand the feedback mechanisms operating in the reference and sensitivity experiments The GCSS Pacific Cross Section Intercomparison ( GPCI ) transect samples stratocumulus, trade cumulus and deep convective regimes as well as the transitions between them Some examples with PC2 follow….

9. © Crown copyright 2006Page 9 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments

10. © Crown copyright 2006Page 10 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments

11. © Crown copyright 2006Page 11 Modelling and Prediction of Climate variability and change Low cloud fraction decreases along the GPCI when we fix liquid cloud radiative properties and when we warm the climate What are the possible explanations? Hypothesis 1 weaker circulation => reduced subsidence => weaker inversion => cloud breakup Can we rule out this hypothesis in any of the above cases? Low cloud response in the PC2 experiments

12. © Crown copyright 2006Page 12 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments Overlaid contour lines show liquid cloud fraction…

13. © Crown copyright 2006Page 13 Modelling and Prediction of Climate variability and change Hypothesis 2 Reduced convective mass flux (Held and Soden 2006) => less detrainment from shallow convection => less low level stratiform cloud Low cloud response in the PC2 experiments

14. © Crown copyright 2006Page 14 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments Overlaid contour lines show liquid cloud fraction

15. © Crown copyright 2006Page 15 Modelling and Prediction of Climate variability and change Hypothesis 3 (climate response only) Upper troposphere warms more than lower troposphere as climate models warm (e.g Santer 2005) => warmer (and possibly moister) free troposphere => less LW cooling at BL cloud top => less condensation => less cloud water / cloud fraction ( Note that the effect on cloud fraction could well be the opposite in any model where the cloud fraction is represented as an increasing as function of stability ) Low cloud response in the PC2 experiments

16. © Crown copyright 2006Page 16 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments Overlaid contour lines show liquid cloud fraction

17. © Crown copyright 2006Page 17 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments Overlaid contour lines show liquid cloud fraction

18. © Crown copyright 2006Page 18 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments Dynamical forcing may be responsible for some but not all changes Shallow convection may well drive low cloud feedbacks in the trades but doesnt explain the response closer to the coast Cloud top cooling may well play a role in driving the reductions in low level clouds, particularly closer to the coast

19. © Crown copyright 2006Page 19 Modelling and Prediction of Climate variability and change 1/ Replace liquid cloud fraction seen by radiation with a simple stability based relationship 2/ Make the radiation code see warmer temperatures above the BL and see if this reduces cloud top cooling and in turn reduces low level cloud 3/ Simplified mixed phase feedback experiment 4/ Simplified autoconversion formulation experiment Other suggestions? Other potential sensitivity tests:

20. © Crown copyright 2006Page 20 Modelling and Prediction of Climate variability and change The pilot study may demonstrate sensitivity tests to be useful, but the experiments will require retuning Cloud condensate tendency diagnostics provide extra information that can be used to test or suggest hypotheses on the roles of different physical processes in cloud feedback mechanisms Feedback patterns in 10 year AMIP + CMIP 1% patterned SST experiments are quite noisy compared to slab responses patterns Conclusions

21. © Crown copyright 2006Page 21 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments Overlaid contour lines show liquid cloud fraction…

22. © Crown copyright 2006Page 22 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments

23. © Crown copyright 2006Page 23 Modelling and Prediction of Climate variability and change Low cloud response in the PC2 experiments