Global Cloud Climatologies from satellite-based InfraRed Sounders (TOVS, AIRS, IASI) +

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1 Global Cloud Climatologies from satellite-based InfraRed Sounders (TOVS, AIRS, IASI) + AIRS-CALIPSO-CloudSat Synergy Claudia Stubenrauch * until 2010 S. Cros*, A. Guignard, N. Lamquin*, R. Armante, A. Chédin, C. Crevoisier, N. A. Scott Atmospheric Radiation Analysis Team, ABC(t) IPSL - Laboratoire de Météorologie Dynamique, France Oct 2010 A-Train Symposium, New Orleans 1

2 Cloud properties from space: 1) multi-spectral cloud detection 2) cloud property retrieval Passive remote sensing (>1980) Active (A-Train, 2006) info on uppermost cloud layer (or mix) good spatial coverage CA, p/z, T, τ VIS / ε IR horizontal extension bulk microphysical properties info on all cloud layers sparse sampling (track/1000km) z, τ VIS vertical extension, layering microphys. prop. profiles IR sounders : good spectral resolution -> esp. reliable Ci properties atmospheric T, H 2 0 profiles (RH) + clouds + aerosols properties (day & night) A-Train synergy (AIRS-CALIPSO-CloudSat) : choose variables & thresholds for AIRS cloud detection AIRS cloud height evaluation -> retrieval transfer to IASI Oct 2010 A-Train Symposium, New Orleans 2

3 I m (λ i ) IR Sounders: TOVS, AIRS, along H 2 O, CO 2 IASI >1980 NOAA, 2002 NASA, 2006 CNES absorption bands, good spectral resolution Inversion 3I - TOVS (Scott et al. 1999) - atmospheric temperature & water vapor profiles, Tsurf AIRS-L2 (Susskind et al. 2003) min weighted χ 2 w (p k ) ε ( p ) k = N m( λi ) Iclr( λi ) ( p λ ) I ( ) I 1 I, λ i= cld k i clr i + atm. transmissivities from TIGR I clr (λ), I cld (p k,λ) no assumption on microphysics Thermodynamic Initial Guess Retrieval <- 4A radiative transfer <- radiosondes ( ε cld, p cld (Stubenrauch et al. 1996, 1999, 2008, 2010) cirrus emissivities (8-12 µm) simulated LUT Mitchell 1996; Baran A-DISORT + SSP of ice crystals De, IWP (CIRAMOSA, Rädel et al. 2003, Stubenrauch et al. 2004) Oct 2010 A-Train Symposium, New Orleans 3

4 Comparison with other data sets: Cloud Assessment Co-chairs: C. Stubenrauch + S. Kinne H C A July ISCCP HCA/CA LCA/CA AIRS-LMD CALIPSO Geographical distributions & seasonal cycles similar HCA depends on sensitivity to thin cirrus CALIPSO > TOVS/AIRS > MODIS/PATMOS > ISCCP> POLDER/MISR Oct 2010 A-Train Symposium, New Orleans 4

5 Zonal averages of HCA & LCA: L2 analysis Jan Jul CALIPSO ISCCP TOVS-B AIRS-LMD IASI-LMD incl subvis Ci excl subvis Ci day day + night preliminary latitudinal behavior similar; HCA : CALIPSO > TOVS ~ AIRS ~ IASI > ISCCP LCA : differences in polar regions Oct 2010 A-Train Symposium, New Orleans 5

6 zonal T cld distributions: GEWEX CA data base SHtrp SHmid PM preliminary CALIPSO: including subvis Ci & T(cld top), pass remote sensing: T(rad. cld height), in case of multi-layer: ISCCP(VIS+IR) -> mix T cld distributions reflect increase of vert extent of troposphere from poles to tropics CALIPSO+GEOPROF (subvis Ci excluded) : multi-layer single layer SHpol K more on poster #167 Oct 2010 A-Train Symposium, New Orleans 6

7 A Train Synergy: AIRS-CALIPSO-CloudSat 1) Evaluation of AIRS cloud height 2) Vertical extent ( z) of high opaque clouds / Ci / thin Ci 3) Vertical insight into high opaque clouds / Ci / thin Ci 4) Cloud height relative to tropopause 5) Ci microphysics for single & multi-layer 6) Multiple scattering correction of Ci lidar signal Oct 2010 A-Train Symposium, New Orleans 7

8 Aura Parasol lidar radar MODIS, AIRS OCO 1) Evaluation of AIRS cloud height with CALIPSO LMD A-Train: synergy of passive & active instruments all clouds, global --- AIRS-L2 (V5) (highest cloud, detected at 5km) good agreement with CALIPSO cld midlevel (or pos. of max. backscatter) properties also depend on retrieval method CALIPSO low clouds LMD --- AIRS-L2 Stubenrauch et al. JGR 2008, ACP 2010 in agreement with Kahn et al Oct 2010 A-Train Symposium, New Orleans 8

9 Aura Parasol lidar radar MODIS, AIRS OCO 1) Evaluation of AIRS cloud height with CALIPSO LMD A-Train: synergy of passive & active instruments all clouds, global --- AIRS-L2 (V5) (highest cloud, detected at 5km) good agreement with CALIPSO cld midlevel (or pos. of max. backscatter) properties also depend on retrieval method CALIPSO low clouds LMD --- AIRS-L2 Stubenrauch et al. JGR 2008, ACP 2010 in agreement with Kahn et al Oct 2010 A-Train Symposium, New Orleans 9

10 Aura Parasol lidar radar MODIS, AIRS OCO A-Train: synergy of passive & active instruments 2) Vertical extent ( z) of high opaque clouds / Ci / thin Ci AIRS: cloud type CALIPSO: apparent geometrical cloud thickness CloudSat: real geometrical cloud thickness Winker / Mace et al.2009 } GEOPROF data Cloudsat.cira.colostate.edu z(thin Ci) < z(ci) < z(hgh op) real z much larger than apparent z for high opaque cloud good quality of AIRS cloud type identification Oct 2010 A-Train Symposium, New Orleans 10

11 Aura Parasol lidar radar MODIS, AIRS OCO A-Train: synergy of passive & active instruments 3) Vertical insight into high opaque clouds / Ci / thin Ci AIRS: cloud type CALIPSO: apparent geometrical cloud thickness, position of max. backscatter pos. of max backscatter rel. pos. of max backscatter & rel. radiative height position of max backscatter depends on apparent z & can reach 2 km below cloud top, even for high opaque clouds rel. position less dependent, 1/3 1/2 below top (thin Ci) radiative height lies about 1/2 below top, for all cloud types Oct 2010 A-Train Symposium, New Orleans 11

12 Aura Parasol lidar radar MODIS, AIRS OCO A-Train: synergy of passive & active instruments 4) Cloud height relative to tropopause distance to tropopause from CALIPSO Stubenrauch et al. ACP, 2010 : real z from GEOPROF Tropics: only the very thickest opaque clouds (& surrounding anvils) penetrate stratosphere Rossow & Pearl 2007: larger, organized, convective systems penetrate Oct 2010 A-Train Symposium, New Orleans 12

13 5) AIRS bulk microphysical properties of semi-transparent Ci based on spectral difference of cirrus emissivity A. Guignard, PhD single / multi layer cirrus (detected by CALIPSO), tropics, 2 year averages 0.3< ε cld < < ε cld < < ε cld <0.85 IWP (g/m²) shape De & IWP increase with ε cld no significant difference between single / multilayer Ci in tropics optically thicker Ci seem to include more aggregates Oct 2010 A-Train Symposium, New Orleans 13

14 6) Multiple scattering correction of cirrus lidar signal η= τ LIDAR CALIPSO / τ VIS AIRS α = Lamquin et al. JGR, 2008 ε IR = 1 exp (-τ VIS /α), α α increasing with decreasing crystal size (Sassen & Comstock 2001) D e increases with T cld,(stubenrauch et al. 2004) α = f(t cld ) τ VIS = - α ln(1- ε IR ) ε IR AIRS τ VIS = τ LIDAR / η η = CALIPSO L2: η = 0.6 slightly more multiple scattering for opt. thicker cirrus Oct 2010 A-Train Symposium, New Orleans 14

15 TOVS Path-B ( ) & AIRS-LMD ( ) cloud climatologies: participate in GEWEX Cloud Assessment (poster #167) IR sounders passive instruments most sensitive to cirrus globally 5-15% more Ci than ISCCP VIS+IR; however, ISCCP better diurnal sampling p cld corresponds to midlevel of apparent cloud depth (slightly below height of max backscatter) uncertainty estimation from χ 2 : p cld : hpa A-Train: : unique possibility to evaluate IR sounder retrieval & to give insight into vertical structure of different cloud types Synergy of variables & data sets extremely important TOVS-B TOVS-R AIRS IASI (1,2,3) Oct 2010 A-Train Symposium, New Orleans 15 ~2020

16 This work was supported by CNRS and CNES. We also thank all Science teams as well as the engineers and space agencies for their efforts and cooperation in providing the data! Oct 2010 A-Train Symposium, New Orleans 16

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