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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, China2Facultyof 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
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
Content
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.
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
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
Models
Convert reflectance
DN-ρTOA
14 days 2nd darkest
reflectance composite
ρTOA-ρc
Convert composite
reflectance to true
reflectance
ρc-ρ
Look Up Table
θs 0˚-70˚,5˚
θv 0˚-70˚,5˚
φ 0˚-180˚,10˚ρ 0-1, 0.1
τ
The surface reflectance in different time
is gradual change and relative
TOA reflectance increase
with aerosol load
Dataset - Satellite
Date : 2 -15 November 2008
Range: 30˚N - 42˚N and 110˚E - 123˚E
Resolution: 5km
FY-2D
00:30UTC 02:30UTC 03:30UTC
04:30UTC 05:30UTC 06:30UTC 07:30UTC
01:30UTC
Dataset – Ground Measurements
AERONET sun photometers
Validation
2
0 1 2( ) ( )aln a a ln a ln
Quadratically interpolated
Result and Validation
YICB = 0.0688X + 0.1012
R2 = 0.4403
YCB = 0.2307X - 0.148
R2 = 0.0533
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0 0.2 0.4 0.6 0.8 1
AERONET AOD
CB
/IC
B A
OD CB
ICB
ICB Fit line
CB Fit line
Composite
Background
Improved Composite
Background
Compare
between CB
and ICB
Result and Validation
-1
-0.8
-0.6
-0.4
-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
AO
D
CB
ICB
AERONET
Beijing
\
-1
-0.8
-0.6
-0.4
-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
AO
D
BC
IBC
AERONET
Xianghe
Time serial of retrieval AOD on
Nov, 15th, 2008 over Beijing site,
using ICB/CB method and
AERONET
Time serial of retrieval AOD on
Nov, 15th, 2008 over Xianghe
site, using ICB/CB method and
AERONET
MSG AOD Retrieval
MSG-2Channel 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
Models
Land-Atmosphere (Mei et al., 2011)
A prior knowledge (Multi-Channel)
Land model (Multi-Temporary)
Inputs: 3 scans/2 bands
(Flowerdew et al., 1995)
(Angstrom et al., 1961)
Govarert et al., 2010
Other constrains:
Aerosol Type
Reflectance Kim et al., 2008
Single Scattering Albedo
Asymmetry factor
Result and Validation
DDV DeepBlue
MSG Result
Result and Validation
Relationships between TS AOD and AERONET AOD of different wavelengths
with a resolution of 10 km in the Africa area: Left 0.8µm, Right 0.6µm. The
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.
• 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.
Conclusion
Linlu MeiTel: (010) 64889540
Mobile: 15101049541
Email: [email protected]
http://www.tgp.ac.cn Professor Yong XueEmail: [email protected]