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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) - PowerPoint PPT Presentation
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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 should be treated differently
Lidar-Radiometer for very thin clouds (not detected by radar) Radar-Lidar / Radar-Radiometer for < 3 Radar / Radar-Radiometer / Dual-Wavelength Radar for> 3
2
Illustration for the need of different methodsIllustration for the need of different methods
Radar Z
Lidar RadarLidar
Radar+Lidar
Existing radar methods : Matrosov Z+V (2002) and Hogan IWC-Z-T (2005)
3
The two measurements of a Doppler cloud radarThe two measurements of a Doppler cloud radar
Reflectivity factor
Doppler velocity
For a vertically-pointing cloud radar :
These measurements are related to N(D)
418
510 ( )
2e bscZ N D dDKw
( )
( )d t
v N D dDbscV V w wN D dDbsc
4
The ice cloud propertiesThe ice cloud properties
32.10 ( ) ( )N D A D dD
4
3
( )
( )m
N D D dDD
N D D dD
3( ) ( )6wIWC D N D D dD
re IWC /
The ice cloud properties are also related to N(D)
5
The normalized particle size distributionThe 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 Dm
4 / 44
= (3/2) IWC / Re =dz
The idea in RadOn and Matrosov (2002) is to get it
from the two radar measurements Z and VD
Mean spectra for all experiments
CLARE 98, CARL 99, EUCREX, ARM IOP, FASTEX, CEPEX, CRYSTALFACE
The normalized particle size distributionThe normalized particle size distribution
Analytical formulation
IWC error=f(T)
5% 10% 1 dB
Z error=f(T)
0.5 dB
Z Doppler velocityVD=VT+w
Most representative density-diameter and area-diameter relationships
Dm (VT, (D), A(D))
N0* =f(Dm,Z)
IWC, , re
VT –Z statistical relationships or mean VD : VT retrieval
Principle of the radar retrieval methodPrinciple of the radar retrieval method
8
Principle of the radar retrieval method 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
V D w V T
scatter = w contribution
9
Principle of the radar retrieval method 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)
V D w V T
IWCRW
IWCVTZ
VTZ
RW
10
Z Doppler velocityVD=VT+w
VT –Z statistical relationships or mean VD : VT retrieval
Dm (VT, (D), A(D))
N0* =f(Dm,Z)
IWC, , re
Most representative density-diameter and area-diameter relationships
Principle of the radar retrieval methodPrinciple of the radar retrieval method
Principle of the radar retrieval methodPrinciple of the radar retrieval method
Second step : Retrieval of most representative (D),A(D) relationships
Using the micro in-situ database and theoretical v(D) = f((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 (D),A(D) relationships
that minimises the difference is retained
12
Z Doppler velocityVD=VT+w
Most representative density-diameter and area-diameter relationships
N0* =f(Dm,Z)
IWC, , re
Principle of the radar retrieval methodPrinciple of the radar retrieval method
Dm (VT, (D), A(D))
VT –Z statistical relationships or mean VD : VT retrieval
Third step : Dm retrieval from VT , (D), A(D)
Knowing (D) and A(D) and using an analytical form for the
normalised PSD shape F, there is a direct relation between VT and Dm
( / )( )
( / )iBbsc m
t m i mibsc m
v F D D dDV D AD
F D D dD
Vt=f(Dm) Dm=f(Vt)
- Vt radar
Principle of the radar retrieval methodPrinciple of the radar retrieval method
14
Z Doppler velocityVD=VT+w
Most representative density-diameter and area-diameter relationships
IWC, , re
Principle of the radar retrieval methodPrinciple of the radar retrieval method
Dm (VT, (D), A(D))
VT –Z statistical relationships or mean VD : VT retrieval
N0* =f(Dm,Z)
15
Fourth step : N0* retrieval from Dm and Z
In Mie regime there is a direct expression that relates N0*, Dm and Z
Principle of the radar retrieval methodPrinciple of the radar retrieval method
25 18 1
*0 4
10( / )e m bsc
wN Z F D D dD
K
Database: CLARE 98, CARL 99, EUCREX, ARM IOP, FASTEX, CEPEX, CRYSTAL-FACE
We use (D)=0.00556(D in cm)-1.1, A(D)=/4D², radar at 95GHz.
RadOnIWC-Z-T
(2005)
Matrosov
(2002)
Biais % % Biais % % Biais % %
IWC -0.2 17.2 9 60 25 75
-3.7 19 102 - -
re 5.2 10.5 - - - -
Compute Vt, Z, IWC, and re from the in-situ data, with A(D) and (D) constant
RadOnHogan IWC-Z-TMatrosov Z+V
IWC, , re retrieved
Vt + Z micro
IWC, , re micro
Similar study for other A(D) / (D) Error estimates are comparable
Evaluation of RadOn using the Evaluation of RadOn using the in-situ database in-situ database
Global error analysis
IWC 95GHz
A=0,5D2 A=0,2D1,8 A=0,05D1,4A=π/4D2 A=0,2D2-40
-30
-20
-10
0
10
20
30
lois d'aire-diamètre
% -1,4-1,1-0,8-0,5
17
Evaluation of RadOn using the IPSL Ra-Li methodEvaluation of RadOn using the IPSL Ra-Li method27 Chilbolton clouds selected for intercomparisons
9 cases : good 6 cases : bias 7 cases : Mie effect5 cases : bias + Mie effect
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).
IWCIWC IWC
We restrict to the 9 good cases
IWC
18
Evaluation of RadOn using optical depth from lidarEvaluation of RadOn using optical depth from lidarOptical 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
OK
Thin SLW layer
Overall : when good conditions errors < 0.1, fractional error +15% / -25%
This method works for these radar frequencies : 3, 10, 35, 95 GHzYields very encouraging results :
-17%<errIWC<+17%,
-22.5%<err<+15%,
-5.5%<errre<+15.5%
During CloudNet this method allowed (see talk this afternoon):
Statistics of (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)
Conclusions and perspectivesConclusions and perspectives
20
3 march 2003: prefrontal cloud
Vt=96.3Z0.177857
A(D)=0.2D1.6
(D)=0.0156D-1
Aggregates
Z
Vd
21
14 april 2003: Thick ice cloud
Vt=66.44Z0.189598
A(D)=0.5D1.8
(D)=0.0132D-0.9
Aggregates
22
15 april 2003: thin cirrus
Vt=57.954Z0.184944
A(D)=/4D1.8
(D)=0.0318D-0.8
Dl=170µm, up to this diameter solid ice