1. The problem of mixed-phase 1. The problem of mixed-phase cloudsclouds

• All models except DWD underestimate mid-level cloud– Some have separate “radiatively inactive” snow (ECMWF, DWD)– Met Office: combined ice/snow but still underestimates cloud

fraction

– Met Office: mid-level cloud occurs with about the right frequency but with too little cloud fraction or liquid water content

Illingworth, Hogan, O’Connor et al. (BAMS 2007)

Robin Hogan

ObservationsMesoscale model

www.cloud-net.org

CRM/radar comparisons CRM/radar comparisons

• Radar/lidar observations of glaciating altocumulus

Marsham, Dobbie and Hogan (QJRMS 2006)

Supercooled water• CRM simulates many aspects well butunderestimates LWP

Falling ice

Mixed-phase clouds cont.Mixed-phase clouds cont.• Why can CRM simulate altocumulus but not large-scale models?

– Insufficient vertical resolution for supercooled liquid layers?– Radiation calls too infrequent so longwave cooling from cloud-top

can’t properly interact with dynamics?– Poor representation of microphysics, e.g. ice/liquid ratio depends

on temperature alone (not the Met Office model)– No depletion of ice nuclei by glaciation which would allow the

subsequent persistence of supercooled water?– Lack of necessary turbulent mixing outside the boundary layer?

• Ongoing/future work to address this issue– PhD project starting in October– APPRAISE-CLOUDS project– Use spaceborne lidar to estimate global properties of mixed-phase

clouds (LITE lidar in 1994 suggested supercooled liquid more common in SH storm track than NH)

– More CRM comparisons with radar?

2. Convective cloud 2. Convective cloud propertiesproperties

• One-hour scanning-radar animation

Red towards radar Blue away from radar

Vertical wind, mass & Vertical wind, mass & momentum fluxmomentum flux

Down-gradientmomentum flux

Counter-gradientmomentum flux

Hogan, Halladay and Illingworth (QJRMS 2008, submitted)

3. A-3. A-train train retrievalretrievalssRadar reflectivity factor from CloudSatRadar reflectivity factor from CloudSat

Attenuated lidar backscatter from CALIPSOAttenuated lidar backscatter from CALIPSO

MODIS/IIR infrared radiancesMODIS/IIR infrared radiances

– New variational retrieval combining radar, lidar and IR radiometer

– First guess of cloud profile is iteratively refined based on its ability to forward model observations

Time [s]

Julien Delanoe & Robin Hogan

• A priori constraints enable retrieval to vary smoothly in the vertical between clouds detected by just radar or lidar and both

Delanoe and Hogan (JGR 2008)

Variational radar-lidar Variational radar-lidar retrievalsretrievals

– Visible extinction coefficient

– Ice water content

– Effective radius

Next steps for spaceborne Next steps for spaceborne retrievalsretrievals

• Use A-train to evaluate Met Office forecast and climate models• Evaluate high-resolution Met Office model in the tropics

(CASCADE)• Occurrence and properties of liquid clouds, including

supercooled• The forward models in the variational scheme can also be

used as “model-to-observation” simulators for evaluating GCMs: can represent the effects of multiple scattering on radar and lidar

• Extend algorithm: retrieve the continuum from thin cloud to heavy precipitation, incorporating microwave radiances etc