1. Prior Information Supported Aerosol
Optical Depth Retrieval Using
Geostationary Satellite Data
Linlu Mei1,5, Yong Xue1,2, Ying Wang1,5,Tingting
Hou3,5 , Jie Guang1, Yingjie Li1,5,Hui Xu1,5, Leiku
Yang4, Xinwei He1,5, Jing Dong1, 5, Ziqiang Chen3, 5
1State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote
Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of
Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China
2Facultyof Computing, London Metropolitan University, 166-220 Holloway Road, London N7 8DB, UK
3Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang
South Road, Haidian District, Beijing 100094, China
4School of Geography, Beijing Normal University, Beijing, China
5Graduate University of the Chinese Academy of Sciences, Beijing 100039, China

2. Content
Introduction
AOD Retrieval from FengYun-2 Data
 Models
 Dataset
 Result and Validation
AOD Retrieval from Meteosat Second Generation
(MSG) Data
 Models
 Dataset
 Result and Validation
Conclusion

3. Introduction
 Aerosol optical depth (AOD) retrieval algorithms have been
established over land for different sensors, most retrievals are
limited to twice per day
 High-frequency aerosol products are eagerly needed ranged from
research to people’s everyday life
 The mainly problem for the traditional generational geostationary is
the band setting problem
 Just one visible band
 Temporary composite method is widely used for traditional geostationary
satellites.

4. Introduction
 Meteosat Second Generation (MSG) satellites carry an impressive
pair of instruments, the Spinning Enhanced Visible and InfraRed
Imager (SEVIRI)
 12 spectral channels
 with a resolution of 3km at the sub-satellite point
 Temporary scale is 15 minutes.
Multi-spectral as well as high-temporary data is useful for aerosol
retrieval modeling

5. Introduction
FY-2D
Launched: December 8, 2006
Temporal scale: 1 hour
Resolution : 1.25km for Vis and 5km for other bands
Channel Centre wavelength(μm) Spectral Band(μm)
IR 10.8 10.3-11.3
IR 12.0 11.5-12.5
IR 6.95 6.3-7.6
MIR 3.75 3.5-4.0
VIS 0.72 0.55-0.90

6. Models
Look Up Table
Convert composite θs 0˚-70˚,5˚
14 days 2nd darkest
Convert reflectance
reflectance composite
reflectance to true θv 0˚-70˚,5˚
reflectance
DN-ρTOA ρTOA-ρc φ 0˚-180˚,10˚
ρc-ρ ρ 0-1, 0.1
τ
TOA reflectance increase
with aerosol load
The surface reflectance in different time
is gradual change and relative

7. Dataset - Satellite
Date : 2 -15 November 2008
FY-2D
Range: 30˚N - 42˚N and 110˚E - 123˚E
Resolution: 5km
00:30UTC 01:30UTC 02:30UTC 03:30UTC
04:30UTC 05:30UTC 06:30UTC 07:30UTC

8. Dataset – Ground Measurements
Validation
AERONET sun photometers
Quadratically interpolated
ln a ( )  a0  a1ln  a2 (ln )2

9. Result and Validation
0.4
0.2
Composite Improved Composite
0
Background Background
CB/ICB AOD
0 0.2 0.4 0.6 0.8 1 CB
-0.2
ICB
YICB = 0.0688X + 0.1012 ICB Fit line
-0.4
R2 = 0.4403 CB Fit line
-0.6 YCB = 0.2307X - 0.148
R2 = 0.0533 Compare
-0.8
between CB
-1 and ICB
AERONET AOD

10. Result and Validation
0.2
0
-0.2
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0
CB
Time serial of retrieval AOD on
Nov, 15th, 2008 over Beijing site,
AOD
-0.4 ICB
AERONET
-0.6 using ICB/CB method and
-0.8
Beijing AERONET
-1
Time
0.2
0
-0.2
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 Time serial of retrieval AOD on
BC
Nov, 15th, 2008 over Xianghe
AOD
-0.4 IBC
-0.6 AERONET
site, using ICB/CB method and
-0.8
Xianghe AERONET
-1
Time

11. MSG AOD Retrieval
MSG-2
Channel Centre wavelength(μm) Spectral Band(μm)
HRV 0.75 0.6-0.9
VIS0.6 0.635 0.56-0.71
VIS0.8 0.81 0.74-0.88
IR1.6 1.64 1.50-1.78
IR3.9 3.92 3.48-4.36
IR8.7 8.70 8.30-9.10
IR10.8 10.80 9.80-11.80
IR12.0 12.00 11.00-13.00
IR6.2 6.25 5.35-7.15
IR7.3 7.35 6.85-7.85
IR9.7 9.66 9.38-9.94
IR13.4 13.40 12.40-14.40

12. Models
A prior knowledge (Multi-Channel) Inputs: 3 scans/2 bands
(Angstrom et al., 1961) Other constrains:
Land model (Multi-Temporary)
Aerosol Type Govarert et al., 2010
(Flowerdew et al., 1995)
Single Scattering Albedo
Asymmetry factor
Land-Atmosphere (Mei et al., 2011)
Reflectance Kim et al., 2008

13. Result and Validation
DDV DeepBlue
MSG Result

14. Result and Validation
Relationships between TS AOD and AERONET AOD of different wavelengths
with a resolution of 10 km in the Africa area: Left 0.8µ Right 0.6µ The
m, m.
dashed (blue), dashed (black) and solid lines are the error tolerance interval, the
1-1 line and the linear regression of the pre-sorted scatter plot, retrospectively.
Text at the top describes: the number of collocation (Count), the regression
curve, correlation (R), and the RMS error of the fit.

15. Conclusion
• An improved prior information supported AOD retrieval method
based on LUT using one visible band was presented in this paper .
However, some problems can easily be found for FY-2D aerosol
retrieval, e.g., low radiation resolution and broad band.
• MSG provide data with multi-spectral and high-temporary, which
is quite useful for aerosol properties retrieval. An novel approach
was presented for MSG aerosol retrieval and we find that >65% of
MSG-retrieved AOD values compare to AERONET observed
values with an expected error envelope of , with high
correlation (R>0.86).
• Aerosol types choosing and validation is on going.

16. Linlu Mei
Tel: (010) 64889540
Mobile: 15101049541
Email: meilinlu@163.com
http://www.tgp.ac.cn Professor Yong Xue
Email: yxue@irsa.ac.cn