1. Benefits from GSICS algorithms for FY-2/3 calibration
Presented by Lei Yang
Contributor: Xiuqing Hu, Na Xu, Hanlie Xu, Lin Chen, Ronghua Wu, Ling Wang, Yuan Li, Ling Sun, Chengli Qi, Peng Zhang
National Satellite Meteorological Center(NSMC), CMA
Sep 22, 2015
GSICS Users Workshop 2015, Toulouse, France

2. Outline
FY-2 GEO-LEO and FY-3C LEO-LEO IR toward demonstration products
FY-2/FY-3 VIS/NIR inter-calibration
FY2 and FY-3 Lunar calibration
FY-3C/MERSI Nonlinear correction from inter-calibration
Other progresses in CMA GPRC
Data group and Data sharing sever
IR Solar contamination of FY-3 instruments
Spectral response error and retrieval
VIS/NIR PICS monitoring
Instrument Performance monitoring IPM

3. Collocation & Correction Products**
Current Status of CMA GSICS Products
Mon
Ref
Graphic Products##
Collocation & Correction Products**
FY2D&E&F/ VISSR
Metop-A/IASI (Op.)
AQUA/AIRS (Op.)
NPP/CrIS (Developing)
Ocean buoy RTM (Plan)
Daily Regression (RAD~RAD and TBB~TBB)
Monthly Scatter of TBB Bias
Time Sequence of TBB Bias
Collocation Samples
Intercalibration Coefficients
NRTC and RAC in txt (Plan to generate the GSICS standard format)
FY3A&B&C/MERSI
&VIRR
NPP/CrIS (Demo)
Monthly Regression (RAD~RAD and TBB~TBB)
AQUA&TERRA MODIS (Demo)
NPP/VIIRS (Demo)
GOME (Developing)
Monthly Regression (REF~REF)
Monthly Scatter of REF Bias
Time Sequence of REF Bias
Projected Image
NRTC and RAC
Stable Targets Tracking (Developing)
Time Sequence of Response
Degradation Rates
TEB
RSB
## : see
** : Only Internal Shared currently.

4. FY-2 GEO-LEO IR calibration GSICS monitoring Latest Results徐娜
GSICS
CIBLE
2013
2014
@290 K for IR1 and IR2
@250 K for IR3
FY-2D窗区通道亮温偏高，IR1偏高约1~2K，IR2偏高约2~3K，水汽通道亮温偏高0.5~1K；
FY-2E窗区通道亮温表现为系统性偏差，IR1约偏低0.5~1K，IR2约偏高1~2K，水汽通道亮温偏低2~3K；
FY-2F定标偏差表现出显著的季节变化特征，冬季偏差大夏季偏差小，窗区通道亮温偏高，IR1约偏高1~2K，IR2约偏高2~3K，水汽通道亮温偏低1~2K。
IR1与IR2之间存在约-1.5K（DTBB_IR1-DTBB_IR2）的系统性偏差
MTSAT平均亮温偏差IR1~2约0.1K，IR3约-0.15K.
FY-2D&E&F热红外通道亮温偏差时序图

5. Bias Correction Coefficient Generation
Linear regression is used as the basis of the systematic comparison of collocated radiances (counts or brightness temperature) from two instruments.
ILEO ar br
ISTD
ΔISTD
IGEO
Correction coeff
Bias
Filting
Matching distribution

6. FY-3C LEO-LEO IR calibration GSICS monitoring
FY-3C/VIRR IR GSICS
Red: FY3C/VIRR-CrIS
Blue:FY3C/VIRR-IASI

7. FY-3C/IRAS Inter-Cal with IASI
FY-3C/IRAS Cal bias rwt IASI in first year:
Ch2~Ch15<1.0K
CH3<-2.0K
CH16~Ch18>2.0K
CH1, CH14~CH20 have large seasonal dependence
IRAS-CrIS matching processing is also in operation and bias analysis will be done

8. CMA GSICS Towards demo products
Theoretical Basis for FY-2-AIRS/IASI Inter-Calibration Algorithm for GSICS
Na Xu (CMA)
Version :
Theoretical Basis for the FY-3 MERSI/VIRR/IRAS- IASI/CrIS Inter-Calibration Algorithm for GSICS
 Hanlie Xu (CMA), Chengli Qi (CMA)
Version:
Submission for review will be done after GSICS 2015 annual meeting

9. DCC Consistency between FY2D~2F and MODIS
FY2D has the greatest calibration bias, and the degradation is about 8%；
Yearly degradations of FY2D and FY2E are similar, and are about 1%；
FY2F is much stable than FY-2D/E
Bias
Degradation Rate

10. FY2D compared with MODIS
FY2D Nadir： 86.5°E
ROI ：10°S-10°N，
75°E-95°E
FY2D compared with MODIS
Mean reflectance of ROI
FY2E-Operation：
FY2E-Correct ：
MODIS：
Before
After

11. FY-3C/MERSI Calibration monitoring by DCC
DCC Monitoring
Assessment with MODIS

12. FY-2E Lunar calibration
Phase Angle=40.5
Num of Lunar Pixels=26295
Abnormal
Extremly low
Phase Angle=42.0
Num of Lunar Pixels=39018
Linear fitting regression(f) is used here to get the instrument degradation:
Rate is the annual degradation rate. STD means the standard diviation of each spot minus fi

13. FY-3C/MERSI degradation using moon observation
Using Inter-band ratio Based Ch03
Annual degradation% 1 2 3 4 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
2.58
-0.51
-0.1
4.72
2.09
14.55
8.42
3.58
1.63
0.9
0.38
0.63
0.46
3.49
-1.4
1.15
0.96

14. CMA Lunar calibration project was funded
CMA Team acquired a project funding from Chinese MOST (Ministry of Science and Technlogy) "Solar bands calibration technique based on Lunar radiance source” (2015~2017) .
The main research points of this project include:
moon prediction and geolocation,
lunar radiance/irradiance model development,
ground-based measurement and model validation and
calibration algrithm development for satellite sensor. 
Collaboration partners:
National = Astronomical Observatories, Chinese Academy of Sciences(CAS) 
Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP), CAS
Nanjing University
Jilin University
Prediction model for lunar position and geolocation of Lunar imager.
A model of Full-disk Lunar Radiance Model
A albedo model of Uniform Target on lunar surface
Validation of Lunar model
by ground-based measure
Lunar Calibration algorithm development used for FY-3
Lunar Calibration algorithm development used for FY-2/4
Monitoring Degradation of sensors by lunar observation
Inter-calibration based on lunar observation

15. Lunar Ground-based measurement
Image size
160*160pixels
Spatial resolution
Spectral range nm
Spectral resolution
2~10 nm
SNR
 600
Tracking Camera
500*500 VIS
Lunar irradiance measurement from these two kinds of instruments for lunar model establishment and validation.
Field Campaigns were conducted for the instruments checking two times in June and August, 2015
Spectrometer Imaging
Image size
No imaging
Spectral range nm
Spectral resolution
2~8 nm
SNR
 500
Tracking Camera ??
Hyperspectral Moon-photometer

16. Non-linear correction Using GSICS
FY-3C/MERSI Integrated/Synergic Calibration—Combined Methods
Red line: New calibration
Blue line: Prelaunch SRBC
Yellow *: SNO sample based on GOME-2
Purple *: Statistical measurements over Deep Convective Clouds (DCC) (Chen et al., Remote Sens. 2013)
Temporal variation of daily intercalibration slope
segmentation fitting is preferable.
The new calibrations :
consistent with SNO samples based on MODIS and GOME-2.
lower over high reflectance comparing with linear results, and nearly go through DCC samples, and the reflectance difference less than 1%.
Segmentation fitting is preferable for getting more appropriate calibration over the whole dynamic .

17. FY-3C/MERSI Non-linear fitting involved GOME-2 and bright stable targets
Band 8-9
Linear fitting: DN=4096，Ref=91%，is not matching in DCC saturation
Non-linear fitting：has largely improvement

18. FY-3C Instrument monitoring is in operation
Instrument Monitor of FY-3C will be added to the static pages firstly

19. CMA GSICS Server Updated
CMA New Server in operation, hardware performance increased
Inter Xeon Procceser)
64GB RAM
4TB Disk
For GPRC CMA/NSMC and thredds
This server will act as the ‘Asian hub’ of the GSICS collaboration servers’ network
Website:

20. CMA GSICS Product CMA NRTC Product Available
CMA has produced demonstrational Near Real Time Correction (NRTC) GSICS products for the FY2D, FY2E & FY2F IR channel cross calibrated using the Metop-A IASI instrument.  
Thanks for the meta-data content and data structure validation work by Masaya
FY-3C/MERSI/VIRR/IRAS LEO-LEO IR NRTC products are also being tested and will be on line in the near future

21. Fengyun LEO FY-3A (mid-morning) was launched in 2008,
FY-1: Retired
FY-3: 2nd Generation
FY-3 has 11 Instruments
Atmospheric sounding
Microwave Imaging
Ozone sounding
Radiation budget for Earth system
Spatial Resolution from 1 Km to 250m
Global data acquisition latency : 1.5 hours ok
FY-3A (mid-morning) was launched in 2008,
FY-3B (Afternoon) was launched in 2010,
FY-3C (mid-morning) was launched in 2013.
VIRR: Visible and Infra-Red Radiometer
MERSI: Medium Resolution Spectral Imager
IRAS: Infrared Atmospheric Sounder
MWTS: MicroWave Temperature Sounder
MWHS: MicroWave Humidity Sounder
MWRI: MicroWave Radiation Imager
SBUS: Solar Backscatter Ultraviolet Sounder
TOU: Total Ozone mapping Unit
SIM: Solar Irritation Monitor
ERM: Earth Radiation Monitor
SEM: Space Environment Monitor
Prototype structure of FY-3 21 21

22. Intersection between the Line of sight and the Earth Figure
FY-3 Data Geolocation
FY-3C was launched on 23th Sep All 9 payloads’ data geolocation have been done with multi-thread in the ground operational system.
Instrument Level
Satellite Level
Line of sight
Intersection between the Line of sight and the Earth Figure

23. Fig.1 Mis-alignment Parameters Equation
FY-3 Geolocation
Mis-alignment
Fig.1 Mis-alignment Parameters Equation
Idea line of sight
Real line of sight
Satellite position
Satellite
Earth
Green：orignal static file
Blue：correctted static file
Fig.2 Static File Correction
Fig.3 DEM Correction
1、FY-3 Geolocation Accuracy： It has been found that FY-3 geolocation accuracy has achieved ±1pixel over the swath.
2、Both the global and local processing software have been updated. The European Direct Broadcasting User can also using the software.

24. Thank you for your attention!
Lei Yang
National Satellite Meteorological Center,
China Meteorological Administration