1. Page 1© Crown copyright 2005 Damian Wilson, 12 th October 2005 Assessment of model performance and potential improvements using CloudNet data

2. Page 2© Crown copyright 2005 Summary  CloudNet data has allowed a long period comparison of cloud properties between models and observations  There is a generally good agreement between the models (including the Met Office) and observations, better than is generally thought  However, there are some specific differences which we can address (for the Met Office)  Microphysical information is also available which can guide future parametrization development

3. Page 3© Crown copyright 2005 Mid-level mean cloud fractions  The mid-level cloud fractions are much reduced compared to observations  Direct modification of the diagnostic ice cloud fraction to better improve the mid-level cloud fractions, as in HadGAM

4. Page 4© Crown copyright 2005 Low level cloud  The low level cloud peak is at too low an altitude  A boundary layer problem?  The model has a large amount of fog and very low cloud in stable boundary layers  Possibly due to inaccuracies in the stable boundary layer turbulent flux profiles JJA: Downwards, stable HadGAM PC2 mm Observations

5. Page 5© Crown copyright 2005 Thick liquid water contents  There are not enough of the highest liquid water contents  Possibly from not including the convective cloud. The representation of liquid water in convection schemes should be investigated  Possibly a poor representation of the drizzle process, with too ready autoconversion

6. Page 6© Crown copyright 2005 Supercooled liquid water content  The mesoscale model (and to a lesser extent, the global model) has significantly less supercooled liquid water than the observations  Possible adjustment of the overlap between liquid and ice in mixed phase clouds

7. Page 7© Crown copyright 2005 Cloud water PDFs  The histogram of cloud fraction and liquid water contents for low level cloud suggests not enough cloud fractions of 1  Tuning the PDF shape and critical relative humidity values should improve the model

8. Page 8© Crown copyright 2005 Other uses of CloudNet data  CloudNet has provided more detailed information which could be used in developing better parametrizations in the future. These include:  Ice particle size distributions  Inhomogenerity information and cloud overlaps to inform the radiation scheme assumptions  Diagnostic area cloud fraction representation  Drizzle parametrization improvements