Influences of ice particle model on ice cloud optical thickness retrieval

1. Influences of ice particle model on ice cloud optical thickness retrieval Zhibo (zippo) Zhang 03/29/2010 ESSIC

2. Outline • Background • Importance of ice cloud • Ice particle model and ice cloud retrieval • Influence of ice particle model on t retrieval • Comparison of MODIS and POLDER ice t retrieval • Influence on our understanding of ice cloud seasonal variability • Summary

3. Ice cloud: fun Photo from Wiki

4. ISCCP day-time ice cloud amount Albedo Effect • Ice clouds are important, because • Cover large portion of the Earth’s surface • Radiative effects • Water vapor budget • Cloud feedbacks Greenhouse Effect (dominant) Earth Ice cloud: important

5. Ice cloud: not well understood Duane Waliser et al. 2009 JGR

6. In-situ measurements Scattering model microphysics Ice Particle Model Satellite remote sensing GCMs Satellite-base remote sensing of ice cloud properties

7. Ice particle model • Size distribution • Shape distribution • Orientation • Inhomogeneity & surface roughness Ice Particle model

8. Hard to measure Shattering of large particles Gardiner and Hallett 1985; Gayet et al. 1996 Field et al. 2003; 50µm Earth Observing Laboratory NCAR Ice particle size • Size matters • Cloud life time (e.g., Heymsfield 1972, Jensen et al.1996) • Cloud reflectance, radiative forcing, heating/cooling rate (e.g., Ackerman et al. 1988; Jensen et al. 1994 ) • Cloud feedback (e.g., Stephens et al. 1990) Number density Particle Size mm µm

9. Ice particle shape • Why shape also matters? Aerosol wavelength Ice particle wavelength From Bryan Baum Complicacy of ice particle shape must be acceptable by scattering models

10. Capabilities of current scattering models

11. Ice particle orientation Randomly orientated Horizontally orientated Images from www.atoptics.co.uk

12. Image credit: CNES Ice particle orientation Horizontally orientated

13. Inhomogeneity and surface roughness Yang et al. 2008 JAMC Yang et al. 2008 ITGRS

14. Ice particle model • Size distribution • Shape distribution • Orientation • Inhomogeneity & surface roughness Ice Particle model So many things to consider… not surprising that ice particle models are usually different from one another

15. Ice particle models: MODIS C5 • More than 1000 PSDs • Complicate habit/shape distribution • Random orientation • Homogeneous and smooth Baum et al. 2005 JAMC

16. Ice particle model: MODIS C5 IWC from MODIS C5 ice particle mode is consistent with in situ measurement Baum et al. 2005 JAMC Baum et al. 2005 JAMC

17. Ice particle model:POLDER Inhomogeneous Hexagonal Monocrystal • Constant size (30µm) • One habit only • Random orientation • Internal inclusion of air bubbles Courtesy of Jerome Riedi C.-Labonnote et al. 2000 GRL Scattering signature consistent with POLDER observation

18. Scattering phase function Baum05 VS IHM

19. Comparison of MODIS and POLDER ice cloud retrieval Motivation • How are MODIS and POLDER ice cloud retrievals different? • What is the role of ice particle model? • Any implications for climate studies? • Is it possible to build up a long-term ice cloud property dataset from multiple missions? • Zhang, Z.et al. 2009: Atmos. Chem. Phys., 9, 1-15. • (www.atmos-chem-phys.net/9/1/2009/)

20. Flight track NASA Langley TC4 team Case for comparison Aqua-MODIS granule on July 22, 2007 (UTC 18:45) Flight track of TC4 mission GOES IR image

21. MODIS 1km pixel Collocation • Collocation of Level-1 radiance data • Collocation of Level-2 cloud products 6km 6km POLDER full resolution pixel 6km POLDER 20km downscale to 6km MODIS 1km aggregated to 6km 6km POLDER full resolution pixel

22. MODIS tvs POLDER t • tPOLDER/tMODISfollows the log- normal distribution • tPOLDERis substantially smaller than tMODIS • For more than 80% pixels • tPOLDER<tMODIS • For more than 50% pixels • tPOLDER<tMODISby more than 30% Same clouds; differentt? Why?

23. Main reason for the difference • Difference in resolution (Plane parallel albedo bias)✗ • Difference in effective radius treatment✗ • Difference in ice particle model✔ (From data: 0.68)

24. Implications for ice SW CRF Zonal mean ice optical thickness vs month (2006)

25. Implications for ice SW CRF Instantaneous Shortwave CRF (FSW)

26. Implications for ice SW CRF Wrong ice particle model retrieval Wrongtretrieval FSWcomputation Wrongg used “Not so wrong” FSW Error cancellation

27. Difference in g Difference in higher-order moment of P11 Ice particle model and seasonal variation oftretrieval IHM model is used for MODIS retrieval Baum05 model is used for MODIS retrieval

28. Angular signature of ice cloud reflectance Satellite Single-scattering Multiple-scattering Angular signature is mainly determined by single-scattering

29. summer winter summer winter MODIS angular sampling MODIS angular sampling vs season

30. summer winter Impact on seasonal variation oftretrieval Assume IHM to be the truth

31. Summary • The t of ice clouds retrieved from POLDER is substantially smaller than that from MODIS retrieval. • This difference is mostly attributed to the difference in ice bulk scattering models used in MODIS and POLDER retrievals • If a wrong bulk scattering model is used in the retrieval algorithm, the error in g factor may lead to overestimation or underestimation of t . However, this error in tretrieval is largely cancelled in FSWcomputation by the error in g factor. • The error in higher-order moment of P11 may lead to artificial seasonal variation of tand this error can NOT be cancelled in FSW computation

32. Questions?