Lessons learned from the GCOM-C(Shikisai)/SGLI cloud observations
Takashi Y. Nakajima,
Takashi M. Nagao, Masahiro Hori
Riko Higuchi, Haruma Ishida
Husi Letu, Nagai Shin
Kanta Shimizu

Tokai University
EarthCARE Workshop in 2023
1

Introduction

GCOM-C/SGLIGCOM-C

Algorithms

GCOM-C/SGLI- was launched in December 2017.
- has 19 channels from the ultraviolet to thermal infrared
wavelength regions.
- is a follow-on sensor for the GLI aboard the ADEOS-II(Midori-II).

Clear

Validation
SummaryCloudy
GCOM-C Satellite

GCOM-C

2019.1.21©JAXA2Sample image from GCOM-C/SGLI

2

Introduction

Band specification of theGCOM-C/SGLIGCOM-C

Algorithms
Validation
Summary

Swath = 1400km

3Introduction

CLAUDIA algorithm(for cloud flags)

CAPCOM algorithm(for cloud properties)

GCOM-C
Algorithms

Validation
Summary

Ishida, H., and T. Y. Nakajima, 2009: Development of an unbiased cloud detection algorithm
for a spaceborne multispectral imager. Journal of Geophysical Research-Atmospheres,
114, doi:10.1029/2008JD010710.
Nakajima, T. Y., T. Tsuchiya, H. Ishida, and H. Shimoda, 2011: Cloud detection performanceof spaceborne visible-to-infrared multispectral imagers. Applied Optics, 50, 2601-2616

Nakajima, T. Y., and T. Nakajima, 1995: Wide-area determination of cloud microphysicalproperties from NOAA AVHRR measurements for FIRE and ASTEX regions. Journal of
the Atmospheric Sciences, 52, 4043-4059.
Kawamoto, K., T. Nakajima, and T. Y. Nakajima, 2001: A global determination of cloud
microphysics with AVHRR remote sensing. Journal of Climate, 14, 2054-2068.

4Introduction

SGLI vs MODIS (Cloud Flag)
SGLI RGB

SGLI
Cloud Flagb) SGLI-CLFGa) SGLI RGBMODIS RGBd) MOD35 Cloud Flag
MODISc) MODIS RGBa) SGLI RGB

SGLICloud Flagb) SGLI-CLFG

MODIS RGB

MODISd) MOD35 Cloud Flag

GCOM-CSGLI RGB

Algorithmsc) MODIS RGB

Validation

Summary

MODIS cloud flag is “clear conservative”

MODIS cloud flag discriminatedyellow sands as clouds

5

Introduction

GCOM-C
Algorithms

Validation of thesatellite-derived
cloud flag, using
ground-based sky
camera images

Validation

Summary

Comparison
6

Sky Index (SI) [-]b)

Brightness Index (BI) [-]c)Validation

Sky Index (SI) [-]Sky Index (SI) [-]Algorithms

Brightness Index (BI) [-]Nominal variable y (0=Cloud, 1=Clear)

GCOM-CSky Index (SI) [-]a)d)CloudyClear

Clear Probability

Introduction

Validation: Whole Sky Camera Analysis

Brightness Index (BI) [-]Summary• SI=(Blue-Red)/(Blue+Red)• BI=(Red+Green+Blue)/(255*3)

7

Introduction

Validation of cloud flag by using Sky camera systems

GCOM-C
Algorithms
Validation

Accuracies*1

NyAlesund

SapporoTsukuba
TKSC

Tsukuba
MRI

Kumamoto

Miyakojima

Syowa
StationAllN

53255825534733294

Accuracy(%)

94.3

88.0

94.8

100.0

88.7

83.0

84.8

90.5

Summary*1 In the case of cloud height at 6 km
Nakajima, T. Y., and Coauthors, 2019: Theoretical basis of the algorithms and earlyphase results of the GCOM-C (Shikisai) SGLI cloud products. Prog Earth Planet Sci 6:52.

=> Meet the release criterion
8The lights of the city of Shinjuku capture clouds even at night.
Introduction

GCOM-C
Algorithms

6%

Validation

Summary

47%
Night Time (Shibuya, Tokyo Japan）

9Introduction

GCOM-C

Algorithms

Validation

Shinjuku-city

Summary

Shibuya-city

10a)b)

c)

Ocean

Ocean

Ocean

GCOM-CSGLIIntroduction

Comparison between SGLI and MODIS (Water Cloud Properties)

Ver. 201227

Algorithms

MODISd)

e)

Land

Land

Validation

SGLI

Land

f)

Summary

MODIS

Nakajima et al. 2019

11a)

b)

c)

Ocean

Ocean

Ocean

GCOM-CSGLIIntroduction

Comparison between SGLI and MODIS (Ice Cloud Properties)

Ver. 201227

Algorithms

MODISd)

e)

Land

Land

Validation

SGLI

Land

f)

Summary

MODIS

Nakajima et al. 201912Introduction

Various size and habit of Voronoi models
for ice cloud

GCOM-C
Algorithms
Validation

Summary

Figure : Various size and habit of Voronoi models (Ishimoto et al., 2012)(shape (a): size parameter (SZP) < 660; shape (b) – (g): 660 < SZP < 2250)
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Introduction

Summary

GCOM-C
Algorithms
Validation• The GCOM-C PI team sets seven sky-camera systems
located on Ny-Alesund, Sapporo, Tsukuba (TKSC), Tsukuba(MRI), Kumamoto, Miyakojima, and Showa station (Antarctic) ,for validating cloud flags.
• The results shows that total accuracy of cloud flag up to90.5%.
• SGLI-derived cloud properties are consistent with paststudies by TRMM, ADEOS2, and Terra Aqua/MODIS.
• Narrower swath of the MSI comparing with the SGLIè more ground validation stations are needed.
• Validate cloud top heights using the ATLID.

Summary14