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The retrieval of the LWC in water clouds. O. A. Krasnov and H. W. J. Russchenberg International Research Centre for Telecommunications-transmission and Radar, Faculty of Information Technology and Systems, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands. - PowerPoint PPT Presentation
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The retrieval of the LWC in water clouds
O. A. Krasnov and H. W. J. Russchenberg
International Research Centre for Telecommunications-transmission and Radar,
Faculty of Information Technology and Systems, Delft University of Technology,
Mekelweg 4, 2628 CD Delft, The Netherlands.
Ph. +31 15 2787544, Fax: +31 15 2784046
E-mail: [email protected], : [email protected]
Are power laws useful?
bLWCaZ
Radar reflectivity Liquid water content
Dropsize distributionVery sensitive to tail of dsd
A million droplets of 10 microngive the same radar reflection as one droplet of 100 micron!
A million droplets of 10 micron containa thousand times as much water as one one droplet of 100 micron...
And so: one drizzle droplet changes the reflectivity significantly without changing the liquid water content
drizzle “transition” drizzle
non-drizzling
Common opinion: No, there is too much scatter due to drizzle
unless
we can identify the drizzle droplets somehow...
Techniques for identification
• Radar reflectionSeparation based on differences in reflectivity of drizzleand non-drizzling clouds
• High resolution Doppler radarSeparation based on differences in fall speeds
• Radar – lidar combinationSeparation based on differences in sensitivity of reflection on droplet size
Radar reflection
Non-drizzling
Drizzling
Coarse classification
Radar and lidar observables in relation to microphysical water cloud.
Radar and lidar observables in relation to microphysical water cloud.
Radar reflectivity vs liquid water content Radar-lidar ratio vs effective radius
The Radar, Lidar, and Radiometer datasetfrom the Baltex Bridge Cloud (BBC) campaign
August 1- September 30, 2001, Cabauw, NL
• Radar Reflectivity from the 95 GHz Radar MIRACLE (GKSS)
• Lidar Backscattering Coefficient from the CT75K Lidar Ceilometer (KNMI)
• Liquid Water Path from the 22 channel MICCY (UBonn)
All data were presented in equal time-height grid with time interval 30 sec and height interval 30 m.
Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 The profiles of measured variables
Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 The profiles of Optical Extinction and Radar-Lidar Ratio
Z1 = -20 dBZ, Z2 = -10 dBZ; thresholds for radar only
+ 0 dB
+ 5 dB
+ 10 dB
+ 5 dB
+ 10 dB
0 dB
Frisch’s algorithmFrisch’s algorithm
2
log0, LWCNaZ
effr
• log-normal drop size distribution
• concentration and distribution width are equal to constant values
max
0
2/1
2/1
)(
)()(
h
h
RMMW
hZ
hZ
h
LWPhLWC
From radiometer’s LWP and radar reflectivity profile:
Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 Retrieval Results for Frisch’s algorithm
Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 Histogram of Differences in Retrieval Results for
the Frisch’s and the Radar-Lidar algorithm
Difference between LWC that retrieved using Frisch method and retrieved from radar-to-lidar ratio
Frisch’s fittings
Log-Normal DSDN=1000 - 2000 cm-3, = 0.8N=1000 - 2000 cm-3, = 0.1
Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 Representation results on the Z-LWC plane
Case: cloud without drizzle
Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The profiles of measured variables
Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The Resulting Classification Map (radar and lidar data)
Atlas Z-LWC relationshipAtlas Z-LWC relationship
Frisch’s fittings
Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The results of Frisch’s algorithm application
Log-Normal DSDN=1000 - 2000 cm-3, = 0.8N=1000 - 2000 cm-3, = 0.1
Z-LWC relationship based on aircraft data
Comparison aircraft – radar data
September 23, 2001, Z+13 dBZ
Merlin flight
Frisch Z-LWC relations after adding 13 dB to Z
September 23, 2001, Z+13 dBZ
Atlas equation
September 23, 2001, Z+13 dBZ
Frisch retrievals
September 23, 2001, Z+13 dBZ
Atlas - Baedi - Drizzle equations
Frisch retrievals –
Z/ retrieval
Radar intercomparison; Miracle - KNMI
In ice cloudsalso agreement with Tara
Possible explanations for radar – aircraft difference
Cloud inhomogeneity: temporal and spatial sampling?Clipping of Doppler spectrum?
Conclusions
Given a proper calibration of the instruments,
• Radar-lidar
• Radar-microwave radiometer
• Radar alone
produce similar LWC profiles of non-drizzling clouds.
What’s going on with the radar data?
