Zhibo (zippo) Zhang 03/29/2010 ESSIC

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Presentation transcript:

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

Outline Background Influence of ice particle model on t retrieval 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

Ice cloud: fun Photo from Wiki

Ice cloud: important 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 ISCCP day-time ice cloud amount Earth Albedo Effect Greenhouse Effect (dominant)

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

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

Ice particle model Size distribution Shape distribution Orientation Inhomogeneity & surface roughness

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) Hard to measure Shattering of large particles Gardiner and Hallett 1985; Gayet et al. 1996 Field et al. 2003; Earth Observing Laboratory NCAR 50 µm Number density Particle Size µm mm

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

Capabilities of current scattering models

How does a GOM model work? Snell’s Law

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

Ice particle orientation Horizontally orientated Image credit: CNES

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

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

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

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

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

Scattering phase function Baum05 VS IHM

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? MODIS POLDER Resolution 1km 20km Cloud effective radius Retrieved Assumed Ice particle model Baum05 IHM Directionality Single Up to 16 Zhang, Z.et al. 2009: Atmos. Chem. Phys., 9, 1-15. (www.atmos-chem-phys.net/9/1/2009/)

Difference between MODIS and POLDER retrieval algorithms Resolution 1km 20km Cloud effective radius Retrieved Assumed1 Bulk scattering model Baum052 IHM3 Directionality Single Up to 16

Comparison of MODIS and POLDER ice cloud retrieval POLDER/Parasol Advantages / Uniqueness : Multi-direction (up to 16 angles) Polarization sensitive (Linear polarization of cloud reflection at 3 bands) Limitations Horizontal resolution (6km) Narrow spectral coverage ( 10 bands 0.4~1.02 m) MODIS/Aqua Advantages / Uniqueness : Wide spectral coverage (36 bands 0.4 ~ 15 m) Horizontal resolution (250m ~ 1km) Limitations Single direction No polarization Column retrieval POLDER Polarization Multi-direction NASA Cloud mask, Cloud phase Cloud top height Optical thickness MODIS Effective radius

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

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

Same clouds; different t? MODIS t vs POLDER t tPOLDER/tMODIS follows the log- normal distribution tPOLDER is substantially smaller than tMODIS For more than 80% pixels tPOLDER < tMODIS For more than 50% pixels tPOLDER < tMODIS by more than 30% Same clouds; different t? Why?

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)

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

Implications for ice SW CRF Instantaneous Shortwave CRF (FSW)

Implications for ice SW CRF Wrong ice particle model retrieval Wrong t retrieval FSW computation Wrong g used “Not so wrong” FSW Error cancellation

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

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

Bulk scattering model and seasonal variation of  retrieval Difference in higher-order moment of P11 Difference in g

MODIS angular sampling MODIS angular sampling vs season summer winter winter summer

Impact on seasonal variation of t retrieval Assume IHM to be the truth winter summer

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 t retrieval is largely cancelled in FSW computation by the error in g factor. The error in higher-order moment of P11 may lead to artificial seasonal variation of t and this error can NOT be cancelled in FSW computation

Questions?