1. 1 Recent advances in CALIPSO cloud retrievals: Progress over the last 7 years Looking ahead to the next 30 ISCCP at 30: City College of New York, 23 April 2013 Dave Winker 1, Anne Garnier 2, Andy Heymsfield 4, Jacques Pelon 3, and Melody Avery 1 1) NASA Langley Research Center, Hampton, VA 2) SSAI, Hampton, VA 3) LATMOS, U. Pierre et Marie Curie, Paris 4) NCAR, Boulder, CO

2. 2 Three co-aligned instruments: CALIOP: polarization lidar - 70-meter footprint - 1/3 km footprint spacing IIR: Imaging IR radiometer – 8.6, 10.5, 12.0 um – 1 km footprint, 60 km swath WFC: Wide-Field Camera Launch: 28 April 2006

3. R m, radiance at 12.05  m, measured R ref, reference radiance at 12.05  m, measured or computed R Tcloud, blackbody radiance from cloud equivalent altitude Garnier et al, JAMC, 2012 IIR: effective optical depth retrieval

4. CALIOP used to constrain IR retrieval From CALIOP: - scene type: R ref (clear or low opaque) - eff cloud height: R Tcloud 4

5. Scattering effects small at 12  m  vis ~ 2 x 12  m ODeff 3 habits, De= 5-100  m 12  m absorption OD and visible OD are closely related –Nearly independent of particle size and shape for De > 20  m Garnier et al, JAMC, 2012

6. IIR eff OD vs. CALIOP vis OD  CALIOP ‘constrained’ OD from direct transmittance measurement CALIOP constrained OD/IIR OD eff = 2.0 +/-10% in agreement with expectations and sensitivity studies. Expected Single-layer semi-transparent clouds, tops > 7km, randomly oriented ice, global ocean, day. 6 Expected  CALIOP ‘unconstrained’ OD Sensitivity of IIR retrievals: good agreement with CALIOP down to ODs smaller than 0.05

7. CALIOP retrieval performance should not be dependent on underlying surface IIR retrieval uncertainties somewhat larger over land than ocean LANDOCEAN 7

8. Single-layered cloud, altitude > 7km, T° < 233K, sea, all latitudes, Day+Night January 2011 Then  Ice water path IWP =  ice /3) x (2xOD eff _12) x D e Basic approach (Parol, 1991):  eff 12/10 = OD eff _12 / OD eff _10  eff 12/08= OD eff _12/ OD eff _08... and lookup tables De and IWP Garnier et al, JAMC, 2012

9. Next Topic: IWC from lidar extinction 9

10. Recap Basis of CALIOP Version 3 IWC: IWC = 119  1.22 Heymsfield, Winker, and van Zadelhoff, 2005 ( = HWZ) 10

11. CALIOP, CPR-RO, 2C-ICE (Jan 2008) 11

12. Frequency of cloud detection Symbols in each panel show the 20% level. Fraction of clouds detected only by CALIOP Fraction of clouds detected by both CALIOP and CPR Heymsfield et al. (JGR, submitted) 12

13. Revisit the HWZ parameterization Motivation to update HWZ parameterization: –New in situ measurements, especially in cold clouds SCOUT, CRYSTAL-FACE and Pre-AVE 13

14. Expanded in situ Dataset High-temperature data (0 to -60 C) Low-temperature data ( - 50 to -90 C) Heymsfield et al. (JGR, submitted)

15. Improved IWC Parameterization HWZ: IWC = 119  1.22 New: IWC = a(T)  b(T) - New data < - 60 C from recent campaigns - In situ data corrected for particle shattering effects - New temperature-dependent parameterization provides better fit to in situ measurements HWZf(T)f(De) 0 to -90 C0.42 ± 0.111.03 ± 0.251.08 ± 0.32 -10 to -20 C0.38 ± 0.120.98 ± 0.321.20 ± 0.42 -40 to -60 C0.43 ± 0.130.99 ± 0.251.20 ± 0.42 -60 to -90 C1.73 ± 0.841.16 ± 0.701.04 ± 0.28 At warm temperatures, CALIOP Version 3 IWC too low by ~ factor of 2 IWC fit / IWC meas 15

16. Now: Two independent IWC retrievals IWC from IIR De and IWP, using CALIOP cloud thickness and from parameterized CALIOP extinction retrieval median V3 CALIOP/IIR ratio ~ 1.7 Agreement will improve with new CALIOP IWC parameterization Single-layered semi-transparent clouds, cloud top > 7km, randomly oriented ice, global ocean, day. 16

17. 17 A few thoughts Can do a few things better using active and passive together than with either alone Colocated lidar and IR observations (same line of sight) eliminates uncertainties from view angle differences, spatial mismatches Comparison of independent retrievals is essential for evaluating uncertainties

18. 18 END