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

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

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

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

Summary of planned Launches 2012-05-23: Metop-B 2012-06-19 MSG-3 2013: GMES Sentinel 3 A (ESA) 2014: Jason 3 2015: MSG-4 2016-2017: 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.

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

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)

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

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

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

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

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

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).

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

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

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%

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)

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.

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)

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

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

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

Traditional inter-calibration approach Slide: 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

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

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

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