1. RadOn : Retrieval of microphysical and radiative properties of ice clouds from Doppler cloud radar observations J. Delanoë and A. Protat IPSL / CETP
Clouds of different optical depth t should be treated differently
Lidar-Radiometer for very thin clouds (not detected by radar)
Radar-Lidar / Radar-Radiometer for t < 3
Radar / Radar-Radiometer / Dual-Wavelength Radar for t > 3

2. Illustration for the need of different methods
Radar Z
Radar+Lidar
Lidar
Radar
Lidar 
Existing radar methods : Matrosov Z+V (2002) and Hogan IWC-Z-T (2005)

3. The two measurements of a Doppler cloud radar
For a vertically-pointing cloud radar :
Reflectivity factor
Doppler velocity
These measurements are related to N(D)

4. The ice cloud properties
re = f ( IWC /  )
The ice cloud properties are also related to N(D)

5. The normalized particle size distribution
High variability in ice clouds
Scaling the PSD so that it does not depend on IWC, Dm
N(D) = No* F (Deq/Dm)
Delanoë et al. (JGR, 2005) : shape F can be approximated
by a single analytical form for all ice clouds (<10% error)
The unknowns to get cloud properties : No* and Dm
Then Re = ( (7) / 2 (6) ) Dm IWC = No* w Dm4 / 44
 = (3/2) IWC / Re =
The idea in RadOn and Matrosov (2002) is to get it
from the two radar measurements Z and VD

6. CLARE 98, CARL 99, EUCREX, ARM IOP, FASTEX, CEPEX, CRYSTALFACE
The normalized particle size distribution
Mean spectra for all experiments
Analytical formulation
CLARE 98, CARL 99, EUCREX, ARM IOP, FASTEX, CEPEX, CRYSTALFACE 5%
10%
0.5 dB
1 dB
Z error=f(T)
IWC error=f(T)

7. Principle of the radar retrieval methodZ
Doppler velocity
VD=VT+w
 Most representative density-diameter and area-diameter relationships
VT –Z statistical relationships or mean VD : VT retrieval
Dm (VT, r(D), A(D))
IWC, a, re , t
N0* =f(Dm,Z)

8. Principle of the radar retrieval method
First step : Retrieval of VT from (VD , Z)
Hypothesis : for a long enough time span <w> << <VT>
Error = synoptic ascent / descent (typically 5 cms-1)
A VT - Z relationship is derived for each cloud
scatter = w contribution

9. Principle of the radar retrieval method
First step : Retrieval of VT from (VD , Z)
Alternative approach : 20-minutes means (Matrosov 2002)
Improvement : Running means over 20 minutes (resolution)
IWCRW
IWCVTZ
aRW
aVTZ

10. Principle of the radar retrieval methodZ
Doppler velocity
VD=VT+w
VT –Z statistical relationships or mean VD : VT retrieval
Most representative density-diameter and area-diameter relationships
Dm (VT, r(D), A(D))
IWC, a, re , t
N0* =f(Dm,Z)

11. Principle of the radar retrieval method
Second step : Retrieval of most representative r(D),A(D) relationships
Using the microF in-situ database and theoretical v(D) = f(r(D),A(D))
for different ice particle shapes and habits
we have computed synthetic VT-Z relationships
For each cloud, we compare the synthetic and radar-derived
VT-Z relationships  the set of r(D),A(D) relationships
that minimises the difference is retained 14

12.  Most representative density-diameter and area-diameter relationships
Principle of the radar retrieval method Z
Doppler velocity
VD=VT+w
 Most representative density-diameter and area-diameter relationships
VT –Z statistical relationships or mean VD : VT retrieval
Dm (VT, r(D), A(D))
IWC, a, re , t
N0* =f(Dm,Z)

13. Principle of the radar retrieval method
Third step : Dm retrieval from VT , r(D), A(D)
Knowing r(D) and A(D) and using an analytical form for the
normalised PSD shape F, there is a direct relation between VT and Dm
Vt=f(Dm)
Dm=f(Vt)
- Vt radar

14.  Most representative density-diameter and area-diameter relationships
Principle of the radar retrieval method Z
Doppler velocity
VD=VT+w
 Most representative density-diameter and area-diameter relationships
VT –Z statistical relationships or mean VD : VT retrieval
Dm (VT, r(D), A(D))
IWC, a, re , t
N0* =f(Dm,Z)

15. In Mie regime there is a direct expression that relates N0*, Dm and Z
Principle of the radar retrieval method
Fourth step : N0* retrieval from Dm and Z
In Mie regime there is a direct expression that relates N0*, Dm and Z

16. Similar study for other A(D) / r(D) Error estimates are comparable
Evaluation of RadOn using the mF in-situ database
Database: CLARE 98, CARL 99, EUCREX,
ARM IOP, FASTEX, CEPEX, CRYSTAL-FACE
We use r(D)= (D in cm)-1.1,
A(D)=p/4D², radar at 95GHz.
Compute Vt, Z, IWC, a and re from the in-situ data, with A(D) and r(D) constant
Vt + Z microf
RadOn
Hogan IWC-Z-T
Matrosov Z+V
Global error analysis
RadOn
IWC-Z-T
(2005)
Matrosov
(2002)
Biais %
s %
IWC
-0.2
17.2 9 60 25 75 a
-3.7 19 43
102 - re
5.2
10.5
IWC, a, re microf
IWC, a, re retrieved
Similar study for other A(D) / r(D) Error estimates are comparable

17. Evaluation of RadOn using the IPSL Ra-Li method
27 Chilbolton clouds selected for intercomparisons
5 cases : bias + Mie effect
9 cases : good
6 cases : bias
7 cases : Mie effect
IWC
IWC
IWC
These differences in performance are due Mie scattering not in Ra-Li method.
The 9 good cases : RadOn density retrieval close to Ra-Li (Brown-Francis 1995). a
IWC
We restrict to the
9 good cases

18. Comparisons with RadOn optical depths and those lidar cases
Evaluation of RadOn using optical depth from lidar
Optical depth from lidar can be obtained from difference in molecular return
Comparisons with RadOn optical depths and those lidar cases
Limitations : Can only be done when radar and lidar thicknesses comparable
+ lidar traverses entirely + no occurrence of SLW  case study approach only OK
Thin
SLW layer OK
Overall : when good conditions errors < 0.1, fractional error +15% / -25%

19. Conclusions and perspectives
This method works for these radar frequencies : 3, 10, 35, 95 GHz
Yields very encouraging results :
-17%<errIWC<+17%,
-22.5%<erra<+15%,
-5.5%<errre<+15.5%
During CloudNet this method allowed (see talk this afternoon):
Statistics of r(D) / A(D) from CloudNet radars
Climatology of European ice cloud properties
Evaluation of the representation of clouds
in the CloudNet NWP models
Available to all ground-based remote sensing sites (Matlab code)

20. 3 march 2003: prefrontal cloudZ
3 march 2003: prefrontal cloud Vd
Vt=96.3Z
A(D)=0.2D1.6
r(D)=0.0156D-1
Aggregates

21. 14 april 2003: Thick ice cloud Vt=66.44Z0.189598 A(D)=0.5D1.8
r(D)=0.0132D-0.9
Aggregates

22. 15 april 2003: thin cirrus Vt=57.954Z0.184944 A(D)=p/4D1.8
r(D)=0.0318D-0.8
Dl=170µm, up to this diameter solid ice