1. EUMETSAT GPRC Report
Tim Hewison, Marianne Koenig, Sebastien Wagner, Rob Roebeling, Peter Miu, Jörg Schulz, Harald Rothfuss
EUMETSAT

2. Overview Satellite Status
GEO-LEO IR Products for current Meteosats using IASI
GEO Solar-band Channels for current Meteosats
Re-calibration of Meteosat archive data
Other

3. EUMETSAT space segment – current planning
YEAR... 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
METEOSAT FIRST GENERATION
METEOSAT-6
METEOSAT-7
METEOSAT SECOND GENERATION
METEOSAT-8
METEOSAT-9
METEOSAT-10
METEOSAT-11
METEOSAT THIRD GENERATION
MTG-l-1
MTG-S-1
MTG-l-2
MTG-l-3
MTG-S-2
MTG-l-4
EUMETSAT POLAR SYSTEM (EPS)
METOP-A
METOP-B
METOP-C
EPS SECOND GENERATION
OCEAN SURFACE TOPOGRAPHY MISSION
JASON-2
JASON-3
JASON CONTINUITY OF SERVICES (CS)
THIRD-PARTY PROGRAMMES
GMES SENTINEL-3
GMES SENTINEL-4 ON MTG
GMES SENTINEL-5 ON EPS SECOND GENERATION

4. Operations – Satellites Status
Operational status of the geostationary and LEO systems is stable:
Meteosat-7 at 57.5° E is servicing the IODC (Indian Ocean Data Coverage) Mission
Meteosat-8 (MSG-1) is located to 9.5° East and performs the operational rapid scanning service.
Meteosat-9 (MSG-2) provides primary service at 0°.
Metop A Low Earth Polar Orbit System performance is stable and all instruments are in an operational state.
Jason 2 Low Earth Inclined Orbit System service for Near Real Time products has confirmed to be stable.
MSG-3 and

5. Summary of planned Launches
: Metop-B
MSG-3
2013: GMES Sentinel 3 A (ESA)
2014: Jason 3
2015: MSG-4
: Metop-C
2017: GMES Sentinel 3B (ESA)
2018: 1st MTG-I
2017: 1st Jason CS (after Jason 3)
2019: 1st MTG-S (with GMES Sentinel 4 Instrument)
2019: 1st EPS-SG Satellite ready for launch (VII, IRS, MWS, S5, etc)
2021: 2nd EPS-SG Satellite mission ready for launch (ASCAT, MWI)
2022: 2nd MTG-I
PRD: Preliminary Design Review
Multimission elements: Archive, EUMETCast, etc.

6. Operational Support for Forthcoming Launches
Monitor Metop-A/IASI and Metop-B/IASI
by double-differencing against Meteosat/SEVIRI
also applicable to Metop-A/HIRS and Metop-B/HIRS
Support commissioning of Meteosat-10 (MSG3)
by running prototype inter-calibration wrt Metop-A/IASI
Validate potential variations to official SRF
Perform SEVIRI Solar Channel Calibration & analyse
Starting planning inter-calibration activities for Sentinel-3
SLSTR – Sea and Land Surface Temperature Radiometer
OLCI - Ocean and Land Colour Instrument

7. Sentinel-3: Continuity of ENVISAT Ocean Observation
Launch Expected end 2013
Operated by EUMETSAT for GMES (EU programme)
EUMETSAT plan inter-comparison activities:
cal/val, performance monitoring, inter-calibration
following GSICS principles and methodologies
SLSTR IR:
IR comparison with IASI
Currently studying SNO v Statistical method
NWP also possible
OCLI + SLSTR Solar:
Compare with LEO instruments (MODIS, VIIRS, …)
Combination of invariant targets
and Direct ray-matching methods
Also compare with GEOs
– potential reference instruments!
Microwave
Radiometer
SAR Radar Altimeter
Ocean and Land Colour Instrument
Sea and Land Surface Temperature Radiometer
X-band Antenna
DORIS Antenna
S-band Antenna
Laser retro-reflector
GPS
 "The inter-comparison of level 1 products with other EO data is a key component of the commissioning and operational phases of Sentinel-3. These can be used for calibration validation, performance monitoring, and in some cases extended to generate inter-calibration corrections, which can be applied in either real-time or re-analysis processing. EUMETSAT plan to conduct these activities on an ongoing basis following principles and methodologies developed within the Global Space-based Inter-Calibration System (GSICS)*.
The infrared channels of SLSRT will be compared with the Infrared Atmospheric Sounding Interferometer (IASI), which is a stable, well characterised instrument, adopted as a community inter-calibration reference by GSICS. The methodology for this inter-comparison is currently immature but being developed through a proposed study at EUMETSAT. The solar-band channels of SLSTR and OLCI will be compared to other LEO instruments, including MODIS and VIIRS, using a combination of invariant targets and direct ray-matching methods, currently under development in GSICS. They will also be compared with corresponding channels of geostationary imagers, and may prove to be valuable inter-calibration reference instruments."
Slide courtesy of Craig Donlon (ESA)

8. Overview Satellite Status
GEO-LEO IR Products for current Meteosats using IASI
GEO Solar-band Channels for current Meteosats
Re-calibration of Meteosat archive data
Other

9. GSICS Activities at EUMETSAT
GEO-LEO IR Products for current Meteosats using IASI:
GSICS Corrections
GSICS Bias Monitoring
Uncertainty Analysis
Ice Contamination
GEO Solar-band Channels for current Meteosats:
Review of SEVIRI Solar Channel Calibration System
Implementation of GSICS DCC inter-calibration v MODIS
Development of Lunar Calibration method
Re-calibration of Meteosat archive data:
Using multiple NOAA/Metop/HIRS as reference

10. IR Products for current Meteosats using IASI
GSICS Corrections
Near-Real-Time and Re-Analysis Corrections updated daily since 2008
Published in netCDF format on GSICS Data and Products Server
Now in Demonstration mode, based on prototype code
Pre-Operational candidate, based on Operational code
– but unresolved differences
GSICS Bias Monitoring
Prototype static plots published on web pages since 2008
Developed interactive tool to generate plots directly from netCDF files
Uncertainty Analysis
Published for each Correction
Ice Contamination Model
Developed to explain trend in bias of IR13.4 channel

11. Example of GSICS Bias Monitoring
From EUMETSAT: Time Series of Meteosat9-IASI Standard Biases [K]

12. GEO-LEO IR Uncertainty Evaluation
Extended Error Budget for Meteosat-IASI GSICS Corrections
Following QA4EO / GUM
Processes at each step of ATBD introducing:
Random Uncertainties
Dominated by spatial/temporal variability
over 3km/300s
Validated using time series statistics
Systematic Uncertainties
Dominated by spatial/temporal mismatches
Total uncertainties depend on radiance
Mostly dominated by random processes
Errors much lower in WV channels
See also poster by Tim Hewison

13. Ice Contamination Model
Example time series plot showing relative bias of IR channels of Meteosat-9/SEVIRI (MSG2) wrt Metop-A/IASI, expressed as brightness temperature difference for standard radiance scenes . A spacecraft decontamination in Dec 2008 reduced the bias of the 13.4 μm channel, which subsequently continued to deteriorate.
Ice Contamination Model
Inter-calibration results show Trend in 13.4μm channel bias
Currently -0.4K/yr
Step change of +0.7K at last decontamination
With gain change +35%
In 12.0μm channel
1μm thick layer of ice
Reduces gain
Modifies SRF
Introduces bias
Brightness Temperature Bias modeled by modifying SRF by the ice transmittance. Solid lines show the predicted differences, based on calculation clear skies (red line with crosses) and high cloud (blue line with diamonds).
Transmittance spectra of ice layers of different thicknesses (black): 0.1 to 1.0 µm layers (thickest layers have lowest transmittance) and Spectral Response Functions (SRFs) of Meteosat-8 infrared channels (red).

14. Overview Satellite Status
GEO-LEO IR Products for current Meteosats using IASI
GEO Solar-band Channels for current Meteosats
Re-calibration of Meteosat archive data
Other

15. Meteosat Solar Band Calibration Activities
Vicarious calibration using desert targets + sea targets (current official calibration)
 SEVIRI Solar Channel Calibration System (presented in Daejeon, 2011)
Lunar Calibration
 Collaboration with USGS
METEOSAT imagers
MVIRI (Meteosat First Generation)
SEVIRI (Meteosat Second Generation)
FCI (Meteosat Third Generation)
Inter-calibration with MODIS using Deep Convective Clouds
 Implementation of the GSICS ATBD (Doelling, 2011)
Preparation to MSG3 launch + reprocessing activities

16. SEVIRI Solar Channel Calibration System
Uncertainty analysis on the Radiative Transfer Model (defined as our calibration reference):
Atmospheric gaseous composition
Geometry (geo-location)
Aerosol load
Surface properties
Biggest source of uncertainties: surface properties + aerosols (no surprise but quantified).
(Presented at EUMETSAT Conference, Sept 2011)
Future work:
Assessment of the current system uncertainties to be continued
Re-assessment of the desert target stability + definition of new targets with associated BRF
Improvement of the RTM
Re-evaluation of the reference against reference instruments
Implementation of additional methods such as DCC or homogeneous water clouds (in particular for MTG-FCI non-window channels)
 = 30%
 = 20%
 = 100%
(Ref = 0.1)
 = 2%
 = 1%
 = 30%
 = 20%
 = 100%
(Ref = 0.1)
 = 2%
 = 1%

17. Meteosat Solar Band Calibration using Lunar Observations
Meteosat SEVIRI:
Lunar observations available in the 4 image corners
More than 100 potential observations / year
Achievements:
Development of an automatic extraction tool for lunar observations for LRES channels
Creation of a database of lunar observations with MSG1 and MSG2
Collaboration with USGS  proof of concept: inter-band calibration using the ROLO model as a reference works ! (~1% relative error)
Future work:
Consolidation of the extraction tool for RSS data and HRVIS
Consolidation of the existing database of lunar observations (MSG1 / MSG2)
Assessment of lunar calibration capacities with MFG-MVIRI sensor
Operational extraction of the SEVIRI lunar observations
Development of a tailored version of the ROLO model in order to perform operationally lunar calibration (MSG / MTG)
SEVIRI Level 1.0 image (forward and backward scan)

18. Preliminary results for SEVIRI onboard Meteosat-8 and -9
SEVIRI – Meteosat 8
SEVIRI – Meteosat 9
Note: End at the end of 2005 after the start of Rapid Scan Service
Courtesy T. Stone, USGS
To be presented in IGARSS Munich 2012
Results to be used only for inter-band calibration and drift monitoring
Lunar calibration method and instrument are stable. SD <1% - consistent with expected performance of ROLO  BUT is it affected by seasonality?
Relative difference between channels = consistent with current findings in terms of absolute calibration.

19. Inter-calibration against MODIS/Aqua using DCCs
Implementation still on-going
Process for checking-in MODIS + SEVIRI images in place
Thresholding to extract DCCs in place for MODIS + SEVIRI
Ray-matching to establish bias between MODIS and SEVIRI BT missing (BUT numbers provided by D. Doelling)
Spectral transformation of the data missing (BUT numbers for the spectral adjustment provided by D. Doelling)
Angular transformation of the data ( use of an Angular Distribution Model) missing
PDF transformation of data in place
Gain derivation on a monthly basis in place (in radiance, using modal approach)
Uncertainty analysis to associate an uncertainty estimate to the derived gain missing
Current difficulties:
data storage for MODIS + GEO data  no monitoring system in place yet
Test on the view zenith angle
MODIS (scan N and N+1)
MODIS (scan N+1)
SEVIRI
SEVIRI – 12:57
MODIS 13:00
FINAL DCCs for both MODIS Aqua and SEVIRI (Met 9)

20. Overview Satellite Status
GEO-LEO IR Products for current Meteosats using IASI
GEO Solar-band Channels for current Meteosats
Re-calibration of Meteosat archive data
Other

21. HIRS Data – Objectives Prerequisites and Benefits
To recalibrate time-series Meteosat First Generation and Meteosat Second Generation infrared radiances from 1982 till date using a superior instrument as reference.
Prerequisites:
Inter-calibration back to 1982
Target accuracy over the time-series better than 1 K
Inter-calibration with uncertainty estimate
Method
Select reference instrument
Assess the uncertainties through systematic review of spectral conversion functions
Define the inter-calibration approach
Reprocess and validate the Data processing and verification
Instrument drift is SRF shifts & sensor degradation

22. METEOSAT 1984-2005 Archive evaluation using radiosondes
Upgrade of calibration technique
(van de Berg, et al., 95)
Upgrade of calibration technique
(Schmetz, 1989)
ISCCP DX Normalized Instead of nominal
Comparisons between the METEOSAT BTs and the simulated BTs from radoisoundings: (+) represent the raw data, (◊) represent the homogeneised data. The histogram shows the nb of soundings used for comparison.
Can we do better than that and extend to SEVIRI?
Courtesy of Helene Brogniez and Rémy Roca, LMD

23. Traditional inter-calibration approach
Slide: 24

24. Proposed GSICS inter-calibration approach
Delta Correction to transfer from one reference to another
Defined as differences between inter-calibration functions
Defined in channel-space of monitored instrument
No need for direct comparisons of references
More explanation needed
Delta
Slide: 25 25

25. Proposed GSICS inter-calibration approach
Delta time steps inserted for illustration only
In practice, deltas defined from simultaneous double-differences
Make lines transparent
Delta
Slide: 26 26

26. Overview Satellite Status
GEO-LEO IR Products for current Meteosats using IASI
GEO Solar-band Channels for current Meteosats
Re-calibration of Meteosat archive data
Other

27. Update on Actions
GRWG06_17: Find out time overlaps between geostationary satellites (commissioning and operational periods), find out about the availability of such data and publish this information on the GSICIS Wiki EUMETSAT have generated an Excel file, presenting on a daily basis the availability of the Meteosat satellite data in COM or OPE mode from the Data Centre. It includes a rudimentary chart, which we plan to improve in the future ,e.g. provide on web site, add zooming capability, select / deselect