Global observations of cloud area and properties from GCOM-C SGLI for improving climate change study and cloud science�

Tokai University!

SGLI workshop 2014.1.17 in Tokyo�10:10-10:30�

PI: Takashi Y. Nakajima (Tokai Univ) CI: Haruma Ishida (Yamaguchi Univ) CI: Hajime Okamoto (Kyushu Univ) CI: Husi Letu (Tokai Univ) Associates: Ishimoto, Mano (MRI) Suzuki (JPL), Nagao (Tokai U.) Riedi (LOA)

Contents�

1.  Data flow and algorithm overview 2.  Importance of clouds 3.  Towards ice clouds observation 4.  Validation (JAXA sky camera) 5.  Results in 2013 6.  Summary�

2

SGLI data analysis flow for Clouds�

SGLI/L3B'data�

Calculate'the'cloud'flag'and''Cloud'phase'using'CLAUDIA�

COT,'CTP,'(CDR)�

Calculate'the'COT,CTP,CDR'using'3ch'method'of'CAPCOM'

CTT,'CTH,'CTP'

*3km01/24deg�

Calculate the CTT and CTH (WC+IC)

Calculate'the'error'pixels'using'2ch'method'of'CAPCOM'

Night�

Day)Water�

ISCCP'cloud''type'amount'

ISCCP'cloud'type'classificaLon'

Key)words:)• 'CTT:'Cloud'top'temperature'• 'CTH:'Cloud'top'height'• 'COT:'Clod'opLcal'thickness'• 'CTP:'Cloud'top'pressure'• 'CDR:'Cloud'droplet'Radii''• 'WC:'Water'cloud'• 'IC:'''Ice'cloud'

*3km01/24deg�

*3km01/24deg�

*3km01/24deg�

Day)Ice�

COT,'CTP�

Calculate'the'COT,'CTP,'using'2ch'method'of'CAPCOM'

*3km01/24deg�

! Retrieval algorithm for the cloud properties (CAPCOM):

! Cloud detection algorithm (CLAUDIA):

Concept of the Clear Confidence Level (CCL) •  Quantitatively evaluate cloud existence by the CCL (value of 0 to 1) •  Two thresholds (Upper limit and Lower limit) for each individual test

Ishida and Nakajima (JGR 2010)�

Nakajima and Nakajima (JAS 1995) etc. �

•  The CAPCOM uses LUT (Look up Table)-Iteration Method (LIM) to retrieve the cloud optical and microphysical properties from satellite-derived non-absorption, absorption band data. �

Evidence of the aerosol indirect effect�

Before)erup9on)1Aug.)20072�

During)erup9on)(Aug.)2008)�

Hawaii Mt. Kilauea eruption in 2008�

~1,000km�

~5,000km�

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http://www.darkroastedblend.com/�

Eguchi''et'al.'(2011,'SOLA)�

/15µm 12µm�

1.8 Megaton volcanic ash!�

Wind�

Eguchi et al. (2011)�

R21 (2.1µm)� R16 (1.6µm)�R37 (3.7µm)�

1.  The significant differences are among three cloud effective radii for water clouds derived from GLI & MODIS observations. (Nakajima et al., 2009)�

2.  Impact of … In-cloud vertical inhomogeneity (Platnick, 2000; Nakajima et al., 2010a) Sub-pixel horizontal inhomogeneity (Zhang et al. 2011, 2012) 3-D radiative transfer (Zinner et al., 2010)

What induce these differences among R37, R21 and R16?

2006/07

2006/072006/07

0 5 10 15 20 25 30 35

Monthly Mean of Retrieved Effective Radius R16 [micrometer]

2006/07

2006/072006/07

0 5 10 15 20 25 30 35

Monthly Mean of Retrieved Effective Radius R21 [micrometer]

2006/07

2006/072006/07

0 5 10 15 20 25 30 35

Monthly Mean of Retrieved Effective Radius R37 [micrometer]

5�

25�

15�

35µm�

2006/07

2006/07

2006/07

05

1015

2025

3035

Monthly

Mean of

Retrieve

d Effecti

ve Radiu

s R37 [m

icrometer]

Water Cloud Property: New Study�

R37� R21� R16�

Can we retrieve the information about cloud vertical structure ?

7

Water Cloud Property: New Study�

0.0

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1.0

0 10 20 30 40−10

−5

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10

r2.1 [µm]

Δr 1

.6−2

.1 [µ

m]

Rel

etiv

e Fr

eque

ncy

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Δr 1

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.1 [µ

m]

Rel

etiv

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Vertical�

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m]

Rel

etiv

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Vertical + Horizoantal

+ Other (3-D RT)�

[ Model Simulation ]� [MODIS Observation]�

V + H�

Vertical + Horizontal

rretrieval = rverical +!rhorizontal +!rother

•  However, satellite-retrieved R16, R21, R37 seem to be contaminated by the impact of Horizontal inhomogeneity and etc. (Nagao et al. 2013, JAS) �

Nagao 2013�

Flow chart of the ice crystal scattering database

INPUT DATA:

1). SGLI calculating wavelength 2). Radii of the corresponding equivalent volume spheres 3). Particle shape 4). Aspect rate�

OUTPUT: •  Phase function, Phase matrix

Extinction efficiency, SSA (Light scattering properties DB →RSTAR radiative transfer code2

Light scattering solvers (SIEMM, FDTD, GOM2, GOM1)

Developing the ice crystal scattering database�

Size parameter resolution selected in light scattering DB:�

*DB:)database�

Baum et al. 2005�

MODIS C5 product:� SGLI product:�

*Calculating�

Solvers Adapted size parameter

Calculation method Reference

Lisas/SIEMM 1 - 20 Maxwell equation Nakajima T. Y et al. 2009

FDTD 20 - 30 Maxwell equation Ishimoto et al. 2010

IGOM 30-300 Ray-tracing + Electromacnetic theory

Ishimoto et al. 2012

Lisas/GOM More than 300 Ray-tracing technique Nakajima T Y et al 1997

GOM1�

GOM2�

GOM2�

GOM2�GOM1�

Validation of the FDTD and GOM2 method by comparing the phase function �

FDTD VS ADDA (Bi et al. 2011)

FDTD VS T-Matrix

Scattering angle�

Phas

e fu

nctio

n�Ph

ase

func

tion�

�=1.05µm szp�23�

�."INTRODUCTION"

Cirrus clouds regularly cover about 20-30% of the globe, have been identified as one of the major unsolved components in weather and climate research. Therefore, the scattering and the absorption properties of the ice crystal of cirrus clouds are very important for understanding of the radiation budget of the earth atmospheric system. Ishimoto et al. [1, 2] and Masuda et al. [3] developed the Finite-Difference Time Domain method (FDTD) and Geometrical-Optics Method (GOM2) for the solution of light scattering by non-spherical particles. Nakajima et al [4,5] developed the LIght Scattering solver for Arbitral Shape particle (LISAS)-Geometrical-Optics Method (GOM) and Surface Integral Equations Method of Müller-type (SIEMM) to calculate the light scattering properties for hexagonal ice crystals. In this study, we attempt to develop the non-spherical ice crystal scattering database based on the results of the Global Change Observation Mission (GCOMC) / Second generation Global Imager (SGLI) channel optimization [6], which will be used for ice cloud remote sensing of the GCOMC satellite sensor. Light scattering solvers of LISAS/SIEMM, FDTD, GOM2, and LISAS/GOM were used for developing new ice crystal scattering database.

Ⅰ. ABSTRACT

Channel �C

(µm) ∆�

(nm) SNR Lstd

(VN, P, SW: W/m2/sr/µm T: Kelvin)

IFOV (m)

VN1 0.380 10 250 60 250 VN2 0.412 10 400 75 250 VN3 0.443 10 300 64 250 VN4 0.490 10 400 53 250 VN5 0.530 20 250 41 250 VN6 0.565 20 400 33 250 VN7 0.673 20 400 23 250 VN8 0.673 20 250 25 250 VN9 0.763 12 1200 40 1000 VN10 0.868 20 400 8 250 VN11 0.868 20 200 30 250 P1 0.673 20 250 25 1000 P2 0.868 20 250 30 1000 SW1 1.050 20 500 57 1000 SW2 1.380 20 150 8 1000 SW3 1.630 200 57 3 250 SW4 2.210 50 211 1.9 1000 T1 10.8 740 0.2 300 500

T2 12.0 740 0.2 300 500

Table 1: SGLI channel specification�Ⅱ. DATABASE DESIGN AND METHODS

Solvers Adapted size parameter

Calculation method

Reference

Lisas/SIEMM 1 - 20 Maxwell equation

Nakajima T Y et al. (2009)

FDTD 20 - 50 Maxwell equation

Ishimoto et al. (2010)

IGOM

50-500

Ray-tracing + Electromacnetic

theory

Ishimoto et al. (2012)

Lisas/GOM More than 500 Ray-tracing technique

Nakajima T Y et al. (1997)

Masuda et al. (2012)�GOM2�

Table 2: Size parameter resolutions selected for calculating light scattering properties �

�. CONCLUSIONS

•  Different in phase function between FDTD and GOM2 caused different in asymmetry factor [2]. The figures (Fig.1, Fig.2) indicate that the phase functions of the SIEMM, FDTD and GOM2 are similar in general with same size parameter (SZP), wavelength and particle shapes. •  Extinction efficiency and asymmetry factor are also similar with different ice crystal shapes (Fig.3). Liner polarizations are little different with the same wavelength and size parameter (Fig. 4). •  In the future, we will develop the ice cloud retrieval algorithm for GCOMC/SGLI using the ice crystal scattering database.�

�. ACKNOWLEDGMENT

This study was supported by the GCOM-C/SGLI and the EarthCARE project of JAXA, and the GOSAT project of National Institute of Environmental Study, Tsukuba, Japan. �

�. REFERENCES [1] Ishimoto. H et al., 2010: J. Quant. Spectrosc. Radiat. Transfer, 111, 2434-2443. [2] Ishimoto. H et al., 2012: J. Quant. Spectrosc. Radiat. Transfer, 113, 632-643. [3] Masuda. K et al., 2012: Meteorology and Geophysics, 63, 15–19. [4] Nakajima. T. Y et al., 1997: Proceedings of SPIE, 3220, 2-12. [5] Nakajima. T. Y et al., 2009: Applied Optics, 48, 3526�3536. [6] Letu. H et al., 2012: Applied Optics, 51, 6172�6178.

�. RESULT AND DISCUSSIONS

Fig. 1: Comparison between phase function of the LISAS/SIEMM and FDTD.

Fig. 4: Comparison of the liner polarization –F12/F11 with shape model of column and Voronoi aggregate.

λ�1.05µm; szp=23�λ�1.05µm; szp=21�

!�0.565µm a=0.348L

Lisas/SIEMM�

Fig. 3: Comparison of the extinction efficiency (Qext), and asymmetry factor (g) with different SZP.�

αszp =2πreqvλ

= 0.35 L (L <=100µm) = 3.48L0.5 (L < = 100 µm) (L >=100µm) acol = {� (L < 100µm)�

λ�1.05µm; szp=21�

λ�2.21µm; szp=30�λ�2.21µm; szp=27�

Fig. 2: Comparison between phase function of the FDTD and GOM2.�

λ�1.05µm; szp=23�

λ�1.05µm� λ�2.21µm�

λ�1.05µm� λ�2.21µm�

λ=2.21µm szp�36�

�."INTRODUCTION"

Cirrus clouds regularly cover about 20-30% of the globe, have been identified as one of the major unsolved components in weather and climate research. Therefore, the scattering and the absorption properties of the ice crystal of cirrus clouds are very important for understanding of the radiation budget of the earth atmospheric system. Ishimoto et al. [1, 2] and Masuda et al. [3] developed the Finite-Difference Time Domain method (FDTD) and Geometrical-Optics Method (GOM2) for the solution of light scattering by non-spherical particles. Nakajima et al [4,5] developed the LIght Scattering solver for Arbitral Shape particle (LISAS)-Geometrical-Optics Method (GOM) and Surface Integral Equations Method of Müller-type (SIEMM) to calculate the light scattering properties for hexagonal ice crystals. In this study, we attempt to develop the non-spherical ice crystal scattering database based on the results of the Global Change Observation Mission (GCOMC) / Second generation Global Imager (SGLI) channel optimization [6], which will be used for ice cloud remote sensing of the GCOMC satellite sensor. Light scattering solvers of LISAS/SIEMM, FDTD, GOM2, and LISAS/GOM were used for developing new ice crystal scattering database.

Ⅰ. ABSTRACT

Channel �C

(µm) ∆�

(nm) SNR Lstd

(VN, P, SW: W/m2/sr/µm T: Kelvin)

IFOV (m)

VN1 0.380 10 250 60 250 VN2 0.412 10 400 75 250 VN3 0.443 10 300 64 250 VN4 0.490 10 400 53 250 VN5 0.530 20 250 41 250 VN6 0.565 20 400 33 250 VN7 0.673 20 400 23 250 VN8 0.673 20 250 25 250 VN9 0.763 12 1200 40 1000 VN10 0.868 20 400 8 250 VN11 0.868 20 200 30 250 P1 0.673 20 250 25 1000 P2 0.868 20 250 30 1000 SW1 1.050 20 500 57 1000 SW2 1.380 20 150 8 1000 SW3 1.630 200 57 3 250 SW4 2.210 50 211 1.9 1000 T1 10.8 740 0.2 300 500

T2 12.0 740 0.2 300 500

Table 1: SGLI channel specification�Ⅱ. DATABASE DESIGN AND METHODS

Solvers Adapted size parameter

Calculation method

Reference

Lisas/SIEMM 1 - 20 Maxwell equation

Nakajima T Y et al. (2009)

FDTD 20 - 50 Maxwell equation

Ishimoto et al. (2010)

IGOM

50-500

Ray-tracing + Electromacnetic

theory

Ishimoto et al. (2012)

Lisas/GOM More than 500 Ray-tracing technique

Nakajima T Y et al. (1997)

Masuda et al. (2012)�GOM2�

Table 2: Size parameter resolutions selected for calculating light scattering properties �

�. CONCLUSIONS

•  Different in phase function between FDTD and GOM2 caused different in asymmetry factor [2]. The figures (Fig.1, Fig.2) indicate that the phase functions of the SIEMM, FDTD and GOM2 are similar in general with same size parameter (SZP), wavelength and particle shapes. •  Extinction efficiency and asymmetry factor are also similar with different ice crystal shapes (Fig.3). Liner polarizations are little different with the same wavelength and size parameter (Fig. 4). •  In the future, we will develop the ice cloud retrieval algorithm for GCOMC/SGLI using the ice crystal scattering database.�

�. ACKNOWLEDGMENT

This study was supported by the GCOM-C/SGLI and the EarthCARE project of JAXA, and the GOSAT project of National Institute of Environmental Study, Tsukuba, Japan. �

�. REFERENCES [1] Ishimoto. H et al., 2010: J. Quant. Spectrosc. Radiat. Transfer, 111, 2434-2443. [2] Ishimoto. H et al., 2012: J. Quant. Spectrosc. Radiat. Transfer, 113, 632-643. [3] Masuda. K et al., 2012: Meteorology and Geophysics, 63, 15–19. [4] Nakajima. T. Y et al., 1997: Proceedings of SPIE, 3220, 2-12. [5] Nakajima. T. Y et al., 2009: Applied Optics, 48, 3526�3536. [6] Letu. H et al., 2012: Applied Optics, 51, 6172�6178.

�. RESULT AND DISCUSSIONS

Fig. 1: Comparison between phase function of the LISAS/SIEMM and FDTD.

Fig. 4: Comparison of the liner polarization –F12/F11 with shape model of column and Voronoi aggregate.

λ�1.05µm; szp=23�λ�1.05µm; szp=21�

!�0.565µm a=0.348L

Lisas/SIEMM�

Fig. 3: Comparison of the extinction efficiency (Qext), and asymmetry factor (g) with different SZP.�

αszp =2πreqvλ

= 0.35 L (L <=100µm) = 3.48L0.5 (L < = 100 µm) (L >=100µm) acol = {� (L < 100µm)�

λ�1.05µm; szp=21�

λ�2.21µm; szp=30�λ�2.21µm; szp=27�

Fig. 2: Comparison between phase function of the FDTD and GOM2.�

λ�1.05µm; szp=23�

λ�1.05µm� λ�2.21µm�

λ�1.05µm� λ�2.21µm�

Scattering angle�

Phas

e fu

nctio

n�Ph

ase

func

tion�

FDTD VS GOM2

FDTD VS GOM2

column vs plate�

Scattering Angle5121.3°�

GOM2�

))))))))))))))))))INPUT)• Cloud)par9cle)scaJering)property))KSpherical)(Mie)Theory:)KRNL.OUT)))KNonKspherical)(KRNL.OUT))))))1).))GOM1)(300<SZP))))2)./GOM2)(50<SZP<300)'))3).))FDTD)(1<SZP<50))

OUTPUT (Radiance)�

Radiative Transfer Program (RSTAR*)

40° : TH0 30° : TH1 90 ° : FI �Particle size distribution:�

Nakajima et al�

Radiative property of the cirrus with varies ice crystal shapes�

Re=4�

Re=8�

Re=16�

Re=32�

Re=64�τ=1�

τ=4�

τ=2�

τ=8�

τ=16�τ=32�

Column Plate�

Re=4�

Re=8�

Re=16�

Re=32�

Re=64�τ=1�

τ=4�

τ=2�

τ=8�

τ=16�τ=32�

Column Plate�

Roadmap for developing GCOM-C/SGLI ice crystal scattering database

///////��*������*�'�

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Issue:)))))))))K)Miss)masking:)Clear)pixels)near)sun,)Thin)cirrus)))))))))K)Dependency)of)op9mal)threshold)value)on)sun)zenith)angle)

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Tokai University Space Information Center1TSIC2, Kumamoto �

Validation of cloud screening algorithm CLAUDIA-SGLI vs. Sky Camera

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Events and results, from 2009 to 2013�2009� 2010� 2011� 2012� 2013 � Total�

Research activity�

▲JMS ▲AMS ▲AGU ▲EGU ▲IGARSS▲AGU ▲AMS ▲SPIE ▲JpGU ▲MSJ ▲CEReS Symp ▲JMS ▲JMS ▲WCRP ▲IRS▲AGU ▲AGU ▲JSASS

Cloud screening algorithm �

"  investigation, Developing / #| /////////////�����������/Ver1 |# improving, validating //////////// ////////////////////////////////////////���������/Ver2

Cloud retrieval algorithm �

"  investigation, development /#| Ver1 "  Scattering data base, calculation and development / #| /|# improving, optimizing ///////////////// ////////////////////////////////////////���������/Ver2

Conferences� 7� 14� 21� 29� 14� Total, 90�Refereed papers� 6� 11� 7� 7� 7� Total, 38�

5 Invited presentations -  The 15th CEReS International Symposium on Remote Sensing, 2009 -  SPIE Asia-Pacific Remote Sensing Symposium, 2010 -  French-Japanese Workshop on the Scientific Utilization of Space-based Earth Observation Data, 2011 -  American Meteorological Society (AMS), Annual Meeting, 2012 -  American Geophysical Union (AGU) fall meeting, 2012 4 Awards -  Matsumae Shigeyoshi award (2011, Nakajima) -  Rem-Sen. Society of Japan award, best paper (2011, Nakajima) -  Met. Soc. of Japan, Horiuchi award (2011, Nakajima) -  Japan-China Sci. & Tech Exchange Association Award (2011, Letu)

Letu. H., T. M. Nagao., T.Y. Nakajima., Validation of Multi-wavelength-derived Cloud Mask in terms of Cloud Contamination in Clear Sky Radiances Using All-sky Camera Observations, Applied Optics. (In preparation) Nakajima, T., H. Takenaka, D. Goto, S. Misawa, J. Uchida, and T.Y.Nakajima, 2013: Measurements and Modeling of the Solar Radiation Budget. Journal of the Japan Society for Simulation Technology, 199-207.�.�Nagao. T. M., T. Y. Nakajima., H. Letu., K. Suzuki., and H. Okamoto., Cloud microphysical properties as seen from spaceborne passive multi-spectral imagers: interpretation in term of vertical and horizontal inhomogeneity by using numerical cloud models, high spatial resolution measurements, and active instruments, Transactions of the Japan Society for Aeronautical and Space Sciences. 1In print2�.�Nakajima. T. Y., T. M. Nagao., H. Letu., K. SUZUKI., and H. OKAMOTO., Synergistic use of spaceborne active sensors and passive multispectral imagers for investigating cloud evolution processes, Transactions of the Japan Society for Aeronautical and Space Sciences. 1In review2�.�Nagao, T. M., K. Suzuki, and T. Y. Nakajima, 2013: Interpretation of multiwavelength-retrieved droplet effective radii for warm water clouds in terms of in-cloud vertical inhomogeneity by using spectral bin microphysics cloud model. J. Atmos. Sci., 2376–2392.�.�Fukuda, S., T. Nakajima, H. Takenaka, A. Higurashi, N. Kikuchi, T. Y. Nakajima, and H. Ishida, 2013: New approaches to removing cloud shadows and evaluating the 380 nm surface reflectance for improved aerosol optical thickness retrievals from the GOSAT/TANSO-Cloud and Aerosol Imager, J. Geophys. Res. 12/2013; DOI:10.1002/2013JD020090.�.�Jules R. Dim, T. Y. Nakajima, Tamio Takamura, Performance of the GCOM-C/SGLI satellite prelaunch phase cloud properties' algorithm, J. Appl. Remote Sens. 7(1), 073693 (Sep 25, 2013).

Publications in 2013 (7 papers)�

16

Importance of Climate Change Study and Cloud Process Study�

Summary of Takashi Nakajima’s group�

! Algorithm development –  CLAUDIA (Ishida) … on schedule: Adjustment for the SGLI. –  CAPCOM (Nakajima) … on schedule: Adjustment for the SGLI. –  Non-spherical Database (Letu, Ishimoto) … Hexagon, Plate, Bullet Rosette,

Voronoi (4 shapes) completed. Make LUT for the retrieval, on going (Letu, Ishimoto, Riedi)

–  Influence of SGLI radiance uncertainties on retrieval of cloud microphysical properties(Letu).

! Science –  Synergistic use of Passive and Active, & Bin model (Nagao, Suzuki, Nakajima,

Okamoto, Sato, Seiki..)

! Results in 2013 –  7 papers published, 19 Conferences.

!  Leading GCAST (GCOM-C Atmospheric Science Team)

Than you for your attention!�