the retrieval of the lwc in water clouds: the comparison of frisch and radar-lidar techniques
DESCRIPTION
Third Progress Meeting 24-25 April 2003 , Reading. The retrieval of the LWC in water clouds: the comparison of Frisch and Radar-Lidar techniques. O. A. Krasnov and H. W. J. Russchenberg International Research Centre for Telecommunications-transmission and Radar, - PowerPoint PPT PresentationTRANSCRIPT
The retrieval of the LWC in water clouds:the comparison of Frisch and Radar-Lidar
techniques
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]
Third Progress Meeting24-25 April 2003 , Reading
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.
The relation between “in-situ” Effective Radius and Radar Reflectivity to Lidar Extinction Ratio
for different field campaigns.
The relation between “in-situ” Effective Radius and Radar Reflectivity to Lidar Extinction Ratio
for different field campaigns.
Application of the relation for the identification
of the Z-LWC relationship
Application of the relation for the identification
of the Z-LWC relationship
effrZ /
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
Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 The Resulting Classification Map (radar and lidar data)
Case study: August 28, 2001, Cabauw, NL, 10.12-11.20 Retrieval Results (classification using radar and lidar data)
Frisch’s algorithmFrisch’s algorithm
2
log0, LWCNaZ
effr
• log-normal drop size distribution
• concentration and distribution width are constant in the cloud
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 profiles of measured variables
Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The profiles of optical extinction and Radar-Liadr Ratio
Case study: September 23, 2001, Cabauw, NL, 8.00-10.00 The Classification Map (Radar-Lidar, threshold -35 and -25 dB)
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
Conclusions
•The Frisch’s technique produce much more water
•It does not recognize the presence of in-cloud drizzle
•For the log-normal model Frisch’s fitting of Z-LWC relationships shows huge, non-realistic concentrations