Post on 28-Mar-2015
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)