ewan oconnor, robin hogan, anthony illingworth, nicolas gaussiat radar/lidar observations of...

Ewan O’Connor, Robin Hogan, Anthony Illingworth, Nicolas Gaussiat

Radar/lidar observations of boundary layer clouds

Overview• Radar and lidar can measure boundary layer clouds at

high resolution:– Cloud boundaries - radar and lidar– LWP – microwave radiometer – LWC – cloud boundaries and LWP

• Cloudnet – compare forecast models and observations– 3 remote-sensing sites (currently), 6 models (currently)– Cloud fraction, liquid water content statistics

• Microphysical profiles:– Water vapour mixing ratio - Raman lidar– LWC - dual-wavelength radar – Drizzle properties - Doppler radar and lidar– Drop concentration and size – radar and lidar

Vertically pointing radar and lidar

Radar: Z~D6

Sensitive to larger particles (drizzle, rain)

Lidar: ~D2

Sensitive to small particles

(droplets, aerosol)

Statistics - liquid water clouds• 2 year database• Use lidar to detect liquid cloud base

– Low liquid water clouds present 23% of the time (above 400 m)

• Summer: 25%• Winter: 20%

• Use radar to determine presence of “drizzle”– 46% of clouds detected by lidar contain occasional large

droplets• Summer: 42%• Winter: 52 %

Dual wavelength microwave radiometer

– Brightness temperatures -> Liquid water path– Improved technique – Nicolas Gaussiat

• Use lidar to determine whether clear sky or not• Adjust coefficients to account for instrument drift• Removes offset for low LWP

LWP - initialLWP - lidar corrected

LWC - Scaled adiabatic method

– Use lidar/radar to determine cloud boundaries– Use model to estimate adiabatic gradient of lwc– Scale adiabatic lwc profile to match lwp from radiometers

http://www.met.rdg.ac.uk/radar/cloudnet/quicklooks/

Compare measured lwp to adiabatic lwp

• obtain ‘dilution coefficient’

Dilution coefficient versus depth of cloud

Cloudnet

Cabauw,The Netherlands

Chilbolton, UK SIRTA, Palaiseau (Paris), France

http://www.met.rdg.ac.uk/radar/cloudnet/

Cloudnet data levels• Level 2a daily files

– High-resolution meteorological products on the radar grid• 30 s, 60 m resolution

• Level 2b daily files– Meteorological products averaged on to the grid of each

particular model: separate dataset for each model and product

• 1 hour, 200 m resolution (typical)

– Includes cloud fraction and liquid water content

• Level 3 files by month and year, model version– Statistics of a comparison between model and the

observations– Observed, and raw & modified model means on same vert.

grid– PDFs, skill scores, correlations, anything that might be useful!

http://www.met.rdg.ac.uk/radar/cloudnet/

Cloud fraction– Radar

provides first guess of cloud fraction in each model gridbox

Lidar refines the estimate by

removing drizzle beneath

stratocumulus and adding thin

liquid clouds (warm and

supercooled) that the radar

does not detect

Model gridboxes

Observations

Met Office

Mesoscale Model

ECMWF

Global Model

Meteo-France

ARPEGE Model

KNMI

RACMO Model

Swedish RCA model

Cloud fraction

Monthly statistics• On model height grid

– Mean obs & model fraction– Frequency of occurrence

and amount when present (thresholds 0.05-0.95)

• On regular 1km grid for fair comparison between models– Contingency table, ETS, Q– Mean cloud fraction

• In four height ranges (0-3, 3-7, 7-12, 12-18 km)– PDFs of obs & model

fraction

• Height-independent– Contingency table, ETS, Q

Cloud fraction – ECMWF

Concatenation of monthly statistics to produce yearly file with exactly the same format

Skill scores etc. all much smoother

If modellers prefer, we could group together periods with forecasts from the same version of the model

Cloud fraction - Met Office Mesoscale

Cloud fraction - Met Office Global

Liquid water content

Liquid water content

Chilbolton – ECMWF

Chilbolton - Met Office Mesoscale

Chilbolton – Met Office Global

Cabauw - ECMWF

Cabauw - Met Office Mesoscale

Cabauw – Met Office Global

Humidity – Raman lidar– Raman lidar measures Raman backscatter at 408 and 387

nm which correspond to water and nitrogen rotational bands.

• Ratio of the two channels gives humidity mixing ratio

– Can generate pdfs of humidity on model grid box

Mixing ratio comparison 11 Nov 2001

Ramanlidar

UnifiedModel,Mesoscaleversion

Cloud

Small-scale humidity structure

• Correlation between adjacent range gates shows that small-scale structure is not random noise

• Typical horizontal cell size around 500m

~500m

Mixing ratio at 720m ±6m

Wind speed ~6 m/s

PDF comparison• Agreement is mixed

between lidar and model:– Good agreement at low levels– Some bimodal PDFs in the

vicinity of vertical gradients

• Further analysis required:– More systematic study– Partially cloudy cases with

PDF of liquid+vapour content

12 UTC 15 UTC

1.6 km

0.2 km

0.8 km

Radiosonde

Smith (1990) triangular PDF

scheme

Stratocumulus liquid water content

• Problem of using radar to infer liquid water content:– Very different moments of a bimodal size distribution:

• LWC dominated by ~10 m cloud droplets• Radar reflectivity often dominated by drizzle drops ~200 m

• An alternative is to use dual-frequency radar– Radar attenuation proportional to LWC, increases with

frequency– Therefore rate of change with height of the difference in 35-

GHz and 94-GHz yields LWC with no size assumptions necessary

– Each 1 dB difference corresponds to an LWP of ~120 g m-2

• Can be difficult to implement in practice– Need very precise Z measurements

• Typically several minutes of averaging is required• Need linear response throughout dynamic range of both radars

Drizzle below cloudDoppler radar and lidar - 4 observables (O’Connor et al. 2005)

• Radar/lidar ratio provides information on particle size

Drizzle below cloud– Retrieve three components of drizzle DSD (N, D, μ).– Can then calculate LWC, LWF and vertical air velocity, w.

Drizzle below cloud– Typical cell size is about 2-3 km– Updrafts correlate well with liquid water flux

Profiles of lwc – no drizzleExamine radar/lidar profiles - retrieve LWC, N, D

Profiles of lwc – no drizzle

260 cm-3 90 cm-3 80 cm-3

Consistency shown between LWP estimates.

Profiles of lwc – no drizzle

Cloud droplet sizes <12μm• no drizzle present

Cloud droplet sizes 18 μm• drizzle present

Agrees with Tripoli & Cotton (1980) critical size threshold

Turbulence30-s standard deviation of 1-s radar velocities, plus wind speed, gives eddy dissipation rate (Bouniol et al. 2003)

http://www.met.rdg.ac.uk/radar/cloudnet/quicklooks/

TurbulenceCan generate pdfs of turbulence for different cloud types

Conclusion • Relevant Sc properties can be measured using

remote sensing;– Ideally utilise radar, lidar and microwave radiometer

measurements together.– Cloudnet project provides yearly/monthly statistics for cloud

fraction and liquid water content including comparisons between observations and models.

– Soon - number concentration and size, drizzle properties.– Humidity structure, turbulence.

– Satellite measurements• A-Train (Cloudsat + Calipso + Aqua)• EarthCARE• IceSat

Satellite measurements

Icesat – lidar profiles

Modis – LWP (imager)