LMD LMD Science Team CALIPSO – March 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

LMD LMD Science Team CALIPSO – March 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

LMD LMD Science Team CALIPSO – March 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 : T B (λ 1 )-T B (λ 2 )=f(T B (λ 1 )) Clear sky Opaque cloudUncertainty on cloud temperature (2) sph. liq 6µm sph. ice 6µm sph. liq 12µm sph. ice 12µm Uncertainty on scene identification (1) T(λ 1 ) T B (λ 1 )-T B (λ 2 )

LMD LMD Science Team CALIPSO – March 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 Retrieved several possible values of r, depends on the shape hypothesis Best solution for (r,Q) SIMULATIONS MEASUREMENTS improvements

LMD LMD Science Team CALIPSO – March Applications Parasol Calipso Aqua Cloudsat Aura SIRTA 10.6 µm lidar LVT 532 nm lidar LNA TERRA/MODIS Instrumented site of Palaiseau/France : SIRTA λ 1 = 8.65µm λ 2 = 11.15µm λ 3 = 12.05µm distance : 200m ~ IIR

LMD LMD Science Team CALIPSO – March Cloud identification : improvement from 532nm lidar (a) 220K < T cloud < 250K T B,SIRTA > T cloud semi-transparent cloud T B,SIRTA = 265K LNALNA MODISMODIS SIRTA

LMD LMD Science Team CALIPSO – March µm<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 T 10.5µm -T 12µm T 8.7µm -T 12µm T 8.7µm -T 10.5µm T 10.5µm T 8.7µm

LMD LMD Science Team CALIPSO – March Shape constrain : improvement from lidar depolarization (a) T B,SIRTA = 260K T cloud = 220K T B,SIRTA > T cloud semi-transparent cloud LNALNA MODISMODIS SIRTA

LMD LMD Science Team CALIPSO – March classe I : Q<0.05 classe II : 0.05<Q<0.7 classe III : 0.7<Q<1.05 classe IV : Q>1.05 Depolarization ratio Shape ratio Q ΔP Noël & al, Applied optics, 2002 Shape constrain : improvement from lidar depolarization (b) L R Shape ratio

LMD LMD Science Team CALIPSO – March 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)

LMD LMD Science Team CALIPSO – March 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?

LMD LMD Science Team CALIPSO – March 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 We finally have Q abs negligible if r>100µm negligible for n<10 3 /m 3 if r<100µm k 0.5 = k 10 (P.Yang) α = n.Q.(π.r²) Q sca,0.5 = 2 for r > 1µm (1) (P.Yang)

LMD LMD Science Team CALIPSO – March Absorption profile : improvement from 10.6 µm lidar (c) 532nm maximum : 8300m +/- 15m 10.6µm maximum : 7900m +/- 50m Q abs 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?

LMD LMD Science Team CALIPSO – March Synthesis of 5 cases studied 2002/03/05 31<r<76µm31<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<19µmno improvement 0.15<Q< /10/14 23<r<57µm23<r<28µm 0.15<Q<0.90.7<Q< /11/06 21<r<57µmr~25µm 0.15<Q<0.9Q=0.9 cloud type (532nm lidar) 3 wavelength constrain shape constrain 10.6µm lidar results Max 532nm : 7000m Max 10.6µm : 7100m Max Q abs,10 : 7500m Max 532nm : 6000m Max 10.6µm : 6000m Max Q abs,10 : 5800m Max 532nm : 8300 Max 10.6µm : 7900 Max Q abs,10 : 7000 semi transparent T=220K T B =260K relatively opaque T=230K T B =239K semi transparent 220<T<250K T B =265K semi transparent 240<T<250K T B =245K semi transparent+low one T high =240K T low =265K T B =252K

LMD LMD Science Team CALIPSO – March 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