1. Numerical simulations of optical properties of nonspherical dust aerosols using the T-matrix method Hyung-Jin Choi hyung-jin.choi@eas.gatech.edu School of Earth and Atmospheric Sciences Georgia Institute of Technology November 14, 2008 Graduate student symposium

2. Motivation: Importance of Mineral dust 2  Mineral wind-blown dust is the most abundant aerosol species that originates from diverse sources throughout the world  Assessment of radiative impact of dust remains highly uncertain because of the complexity associated with dust emission, variable transport and aging process From: IPCC 2007  Dust particles play an important role in the Earth’s radiation budget.  Direct radiative forcing: absorption, scattering  Indirect radiative forcing: affect clouds as CCN, IN SeaWiFS image 10 source of dust

3. Satellite remote sensing provides the best tool for studying dust Key limitation: passive remote sensing gives only column-integrated (2D) view

4.  Based on the our observation of CALIPSO for Asian dust in spring 2007  The volume depolarization ratio shows high value over the source  During mid-range transport the depolarization ratio of Asian dust can remain as high as ~0.35 or be much lower (0.1~0.15) than that in the source region. 4  The CALIPSO space lidar provides a new capability for improved understanding of dust impacts:  measures the vertical distribution of aerosols over the whole Earth for 24 hours => provides 3D view  determines height-resolved aerosol types: => measures the linear depolarization ratio δ a which is indicative of the nonspherical particles (such as dust) ex) Liu et al.(2008) found that δa remained constant during long-range transport of a Saharan dust outbreak => explained by little changes in the dust size distribution and shapes Motivation : Previous study & Observation  For passive remote sensing, many previous studies calculated the dust optical properties using the T-matrix method, which approximates the shape of dust particles as spheroids. => How do changes in dust microphysical properties (size spectra, shape, and composition) affect the optical properties (lidar ratio, depolarization ratio, and single scattering albedo) measured by the CALIPSO lidar?

5. Goals 5  Perform a modeling of the optical properties of nonspherical dust particles to aid in the interpretation of CALIPSO data.  How do changes in dust microphysical properties (size spectra, shape, and composition) affect the optical properties (lidar ratio, depolarization ratio, and single scattering albedo) measured by the CALIPSO lidar?  Can we reproduce the observed optical properties of Asian dust from CALIPSO using the T-matrix method?

6. Approach 6 Observation Analyses & Previous Study (Optical properties) T-matrix method ( Dust particle = Spheroid) randomly oriented nonspherical particles Reproduce the optical properties of Asian dust Microphysical properties - Particle shape, - Size number distribution, - Refractive index Optical properties - Single scattering albedo (ω 0 ), - Lidar ratio (S a ), - Depolarization ratio ( δ a ) Understanding of CALIPSO data Based on a recent study by Lafon and Sokolick(2006), the refractive index of 1.56 + 0.003i at 532 nm (CALIPSO wavelength) was selected as representative for Asian dust. Single scattering albedo: ω 0 = C s / C e Lidar ratio: S a = 4π / ω 0 P 11 (180°) Depolarization ratio: δ a (δ a = (P 11 (180°)-P 22 (180°))/(P 11 (180°)+ P 22 (180°)) Compare Dust Particle a b Spheroids are ellipses rotated around one axis (b); if this axis (b) is the longer axis, they are called prolate, otherwise oblate.

7. Optical Modeling: 7 3-2. Results Input (Microphysical properties) Refractive index: 1.56+0.003i at 532 nm Size distribution: lnσ 2 = 0.5 - 0.1< r < 1 μm, r g1 = 0.5 μm for the fine mode - 0.1< r < 3 μm, r g1 = 1.0 μm for the coarse mode Aspect ratio: - Oblate: 1.05, 1.1, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0 - Prolate: 1/1.05, 1/1.1, 1/1.2, 1/1.4, 1/1.6, 1/1.8, 1/2.2, 1/2.4, 1/2.6, 1/2.8, 1/3.0 T-matrix method Output (Optical properties for fine & coarse mode) Extinction coefficient (C e ), Scattering coefficient (C s ), Single scattering albedo (ω 0 = C s / C e ) Phase function (P 11 (Θ)) Asymmetry parameter (g) Lidar ratio (S a ) Linear depolarization ratio (δ a ) Aspect ratio(ε’)1.051.11.21.41.61.82.02.22.42.62.83.0 Mixture1 a 0.1 Mixture2 a 0.083 Mix- ture3 b Fine0.5350.2890.1080.0400.0150.0070.0030.001 Coarse0.1030.2340.2180.1570.1010.0650.0410.0270.0180.026 Mixture4 c 0.3350.3190.1790.0870.0420.0200.0090.0050.0020.001 Mixture5 c 0.1410.1730.2300.2190.1230.0600.0290.0140.0060.0030.001 5 Mixtures and 3 Cases Experiment: 100% Prolate (Wiegner et al., 2008) Varying proportion of fine and coarse mode - Case 1: 30% fine mode + 70% coarse mode - Case 2: 50% fine mode + 50% coarse mode - Case 3: 70% fine mode + 30% coarse mode To see the relative distribution of each size mode Mixtures - 1 & 2: by Dubovik et al. - 3 : by Wiegner et al. - 4 & 5: by Okada et al.

8. The comparison between fine & coarse mode and prolate & oblate 8  Prolate vs. oblate spheroids:  Distinct differences in all optical properties.  Especially, the distributions of depolarization ratio and lidar ratio in fine mode show different patterns.  Lidar ratio of prolate spheroids in coarse mode has higher values than that of oblate spheroids.  “Dust Mixture Experiment” : 100% prolate  Fine vs. coarse :  Depolarization ratio in coarse mode changes little with varying aspect ratio  Single scattering albedo in fine mode has higher values than that in coarse mode.  Lidar ratio of prolate spheroids in coarse mode has higher values than that in fine mode.  Case 1(source area): 30% fine + 70% coarse mode  Case 2(mid transport): 50% fine + 50% coarse mode  Case 3(long transport): 70% fine + 30% coarse mode a) b) c)

9. Results of “Dust Mixture Experiment”: 9 30% fine mode + 70% coarse mode 50% fine mode + 50% coarse mode 70% fine mode + 30% coarse mode  Coarser particles have lower values of ω 0.  Dust may absorb more sunlight in the source area because of the relatively large fraction of coarse particles (ω 0 : > 0.9 in Case 1).  Preferential removal of large particles during transport would result in less sunlight absorption (ω 0 : > 0.93 in Case 3).  Lidar ratio varies with varying δ a  The CALIPSO lidar ratio for desert dust is S a =38.1 sr, which corresponds to δ a ~ 0.24.  δ a higher than 0.3 are indicative of lower S a.  None of cases can produce δ a : 0.3  Limitations of the assumption on spheroid.  Range of δ a : 0.21 ~ 0.28  Treatments of nonspherical dust particles as spheroids can reproduce some CALIPSO data.  Particle depolarization ratio (δ a ) has relatively low sensitivity to the size distribution.  The Liu’s conclusions are questionable.. 1 & 2: Dubovik et al. 3 : Weigner et al. 4 & 5: Okada et al.

10. Summary and Conclusion 10  Our optical modeling with the T-matrix method showed  Treatments of nonspherical dust particles as spheroids can reproduce some CALIPSO data.  However, this approach cannot provide the entire range of δ a observed by CALIPSO as well as ground-based lidars.  More realistic shapes of dust will need to be considered to improve the interpretation of and aerosol retrievals from CALIPSO observations.

11. 11 Thank you!!