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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
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
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
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
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
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 )
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
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