Science Team CALIPSO – March 20031

LMDLMD

M.Chiriaco, H.Chepfer, V.Noel, A.Delaval, M.Haeffelin

Laboratoire de Météorologie Dynamique, IPSL, France

P.Yang, Texas University

P.Dubuisson, ELICO, France

Lidar/Infrared radiometer coupling for a better determination of particle size in

ice cloud

Science Team CALIPSO – March 20032

LMDLMD

Goal : improving split window technique

1. classical split window technique

2. improvement from 532nm lidar : scene identification

3. improvement from lidar depolarisation : shape constrain

4. improvement from 10.6µm lidar : where is the most absorbing layer within the cloud ?

Synthesis of 5 cases studies

A better determination of particle size in ice cloud

Science Team CALIPSO – March 20033

LMDLMD

Classical split window technique

Sensitivity to crystal sizes and shapes (3)

Optical properties (4)

Asymmetry factor

Single scattering albedo

Extinction cross section

Brightness temperature difference between 2 IR channels :

TB(λ1)-TB(λ2)=f(TB(λ1))

Clear sky

Opaque cloud Uncertainty on cloud temperature (2)

sph. liq 6µmsph. ice 6µmsph. liq 12µmsph. ice 12µm

Uncertainty on scene identification (1)

T(λ1)

TB(λ

1)-T

B(λ

2)

Science Team CALIPSO – March 20034

LMDLMD

Improvements

(3) Shape Q deduced from lidar depolarization

(V.Noël)

Radiative transfert (P.Dubuisson, ELICO)

Absorption & scattering

(4) Optical properties for non spherical particles

(P.Yang, Texas Univ.)

(1)scene identification (2) cloud temperature Lidar +

radiosonde

IR radiometer : brightness temperatures

Temperature differences between 2 channels

Temperature differences between 2 channels

Retrieved several possible

values of r, depends on the

shape hypothesis

Best solution

for (r,Q)

SIMULATIONS

MEASUREMENTS

improvements

Science Team CALIPSO – March 20035

LMDLMD

Applications

Parasol

Calipso AquaCloudsat

Aura

SIRTA

10.6 µm lidarLVT

532 nm lidarLNA

TERRA/MODISInstrumented site of Palaiseau/France : SIRTA

λ1 = 8.65µm

λ2 = 11.15µm

λ3 = 12.05µm

distance : 200m

~ IIR

Science Team CALIPSO – March 20036

LMDLMD

Cloud identification : improvement from 532nm lidar (a)

220K < Tcloud < 250K

TB,SIRTA> Tcloud semi-transparent cloud

TB,SIRTA = 265K

LNA

MODIS

SIRTA

Science Team CALIPSO – March 20037

LMDLMD

17µm<r <19µm for 0.15 < shape ratio Q < 0.5

Cloud identification : improvement from 532nm lidar (b)

Clear sky temperature fixed owing to lidar

Opaque cloud temperature fixed owing to lidar : cloud top

Each curve corresponds to a cloud defined by a (r, Q) value

T10

.5µ

m-T

12µ

m

T8.

7µm-T

12µ

m

T8.

7µm-T

10.5

µm

T10.5µm T8.7µm T8.7µm

Science Team CALIPSO – March 20038

LMDLMD

Shape constrain : improvement from lidar depolarization (a)

TB,SIRTA= 260K

Tcloud= 220K

TB,SIRTA> Tcloud

semi-transparent cloud

LNA

MODIS

SIRTA

Science Team CALIPSO – March 20039

LMDLMD

classe I : Q<0.05

classe II : 0.05<Q<0.7

classe III : 0.7<Q<1.05

classe IV : Q>1.05D

epol

ariz

atio

n ra

tio

Shape ratio Q

ΔP

Noël & al, Applied optics, 2002

Shape constrain : improvement from lidar depolarization (b)

L

R

R

LQ

2=Shape ratio

Science Team CALIPSO – March 200310

LMDLMD

Cloud identification (backscattering) : 31<r<76µm for 0.15<Q<2

Shape constrain (depolarization) : 31<r<46µm for 0.7<Q<2

Lidar depolarization

Shape constrain : improvement from lidar depolarization (c)

Science Team CALIPSO – March 200311

LMDLMD

Absorption profile : improvement from 10.6 µm lidar (a)

532 nm lidar

SIRTA

10.6 µm lidar

SIRTA(Average over 5 minutes)

Where is the most absorbing layer in the cloud ?

Cloud top temperature?

Cloud base temperature?

Cloud middle temperature?

Science Team CALIPSO – March 200312

LMDLMD

Absorption profile : improvement from 10.6 µm lidar (b)

We want an absorption profile in infrared to estimate the most absorbing layer within the cloud position of the cold foot in split window

10,2

10,25.0

210 ...2 absabs QbQa

PR

PR+=

We finally have Qabs

negligible if r>100µm

negligible for n<103/m3 if r<100µm

10,2

10,10, .. absabssca QbQaQ +=

k0.5 = k10 (P.Yang)

α = n.Q.(π.r²)

Qsca,0.5 = 2 for r > 1µm

∫=+− dz

scaabsscaekPR

).(2

10,102

1010,10,..

ααα

∫=− dz

scascaekPR

.2

5.0,5.02

5.05.0,..

αα

(1)

∫=−+− dz

sca

sca scaabsscaernQk

rnQk

PR

PR ).(2

5.0,5.0

10,10

25.0

210 5.0,10,10,.

?).(.

?).(. ααα

π

π

(P.Yang)

Science Team CALIPSO – March 200313

LMDLMD

Absorption profile : improvement from 10.6 µm lidar (c)

532nm maximum : 8300m +/- 15m

10.6µm maximum : 7900m +/- 50mQabs maximum : 7300m

This difference could change the temperature of opaque cloud in simulations (position of cold foot), and influence the final result of particle size

≠

concentration is not considered : final result of absorption?

Science Team CALIPSO – March 200314

LMDLMD

Synthesis of 5 cases studied

2002/03/05 31<r<76µm 31<r<46µm no measurements

0.7<Q<2

2002/04/02 no solution no solution no measurements

0.05<Q< ∞

2002/10/08 17<r<19µm no improvement

0.15<Q<0.5

2002/10/14 23<r<57µm 23<r<28µm

0.15<Q<0.9 0.7<Q<0.9

2002/11/06 21<r<57µm r~25µm

0.15<Q<0.9 Q=0.9

cloud type (532nm lidar) 3 wavelength constrain shape constrain 10.6µm lidar results

Max 532nm : 7000m

Max 10.6µm : 7100m

Max Qabs,10 : 7500m

Max 532nm : 6000m

Max 10.6µm : 6000m

Max Qabs,10 : 5800m

Max 532nm : 8300

Max 10.6µm : 7900

Max Qabs,10 : 7000

semi transparent

T=220K

TB=260K

relatively opaque

T=230K

TB=239K

semi transparent

220<T<250K

TB=265K

semi transparent

240<T<250K

TB=245K

semi transparent+low one

Thigh=240K Tlow=265K

TB=252K

Science Team CALIPSO – March 200315

LMDLMD

Perspectives

Further analysis of 10.6µm cases

Validation of the method with in situ measurements :

data from CRYSTAL-Face field experiment (July 2002)

Comparison with method based on more wavelength (Minnis, 1998)

Systematic analysis over SIRTA

CALIPSO (2005) : application of the method to the first spatial observations