1. Introduction to GSICS
Mitch Goldberg (NOAA)
For GSICS Executive Panel

2. Chief, Satellite Meteorology and Climatology Division
Introduction to the Global Space-based Inter-Calibration System (GSICS)
Mitchell D. Goldberg,
GSICS Exec Panel Chair
NOAA/NESDIS
Chief, Satellite Meteorology and Climatology Division 2 2

3. GSICS Mission
To provide sustained calibration and validation of satellite observations
To intercalibrate critical components of the global observing system to climate quality benchmark observations and/or reference sites
To provide corrected observations and/or correction algorithms to the user community 3 3

4. Motivation
Demanding applications require well calibrated and intercalibrated measurements
Climate Data Records
Radiance Assimilation in Numerical Weather Prediction
Data Fusion
Growing Global Observing System (GOS)
Intercalibration of instruments achieves comparability of measurements from different instruments 4 4

5. Space-Based component of the Global Observing System (GOS)5
Intercalibration of instruments achieves comparability of measurements from different instruments 5

6. POES intercalibration
Simultaneous Nadir Overpass (SNO) Method -a core component in the Integrated Cal/Val System
POES intercalibration
Useful for remote sensing scientists, climatologists, as well as calibration and instrument scientists
Support new initiatives (GEOSS and GSICS)
Significant progress are expected in GOES/POES intercal in the near future
Has been applied to microwave, vis/nir, and infrared radiometers for on-orbit performance trending and climate calibration support
Capabilities of 0.1 K for sounders and 1% for vis/nir have been demonstrated in pilot studies
Method has been adopted by other agencies 6
GOES vs. POES 6

7. Calibration is Critical for Climate Change Detection
Is there a warming trend in the mid-troposphere ?
Is the Earth Greening? How sure are we?
Zou, et al, 2007
Trends for operational calibration algorithm K Decade-1
Trends for nonlinear calibration algorithm using SNO cross calibration (Zou, et al, 2006) K Decade-1
NDVI (normalized diff. vegetation index)
Confidence in climate change detection relies on confidence in calibration.
Current calibration is not stable/solid enough for climate change detection. Very often when the satellite data are recalibrated, it is likely to lead to new results in climate trends.
Year
Heidinger, et al
Calibration uncertainties translate to uncertainties in climate change detection 7 7

8. Do we Care about Satellite Biases in NWP. After McNally, Bell, et al
Do we Care about Satellite Biases in NWP? After McNally, Bell, et al. ECMWF, 2005 & 2009
Yes! Because:
1) We wish to understand the origin of the bias and ideally correct instrument / RT / NWP model at source
2) In principle we do not wish to apply a correction to unbiased satellite data if it is the NWP model which is biased. Doing so is likely to:
Re-enforce the model bias and degrade the analysis fit to other observations
Produce a biased analysis (bad for re-analysis / climate applications)
The biases for all satellite channels used in NWP data assimilation are closely monitored at NWP centers. For example, the NCEP system is available at:
SSMIS calibration biases cause regional weather patterns
More accurate satellite observations will facilitate discovery of model errors and their correction. Additional gains in forecast accuracy can be expected. 8 8

9. Organizations contributing to GSICS
NOAA
NIST
NASA
EUMETSAT
CNES
CMA
JMA
KMA
WMO
Official observers:
JAXA
ESA
GSICS current focus is on the intercalibration of operational satellites,
and makes use of key research instruments such as AIRS and MODIS
to intercalibration the operational instruments 9 9

10. SCOPE-CM to maximize data usage Sustained and Coordinated Processing of Environmental Satellite Data
Users
Satellites & sensors
Satellite data
Essential Climate products
GOS
GSICS
Consistent Calibrated data sets
SCOPE-CM
Regional/Specialized Satellite Centres
Address the requirements of GCOS in a cost-effective, coordinated manner, capitalising upon the existing expertise and infrastructures.
Continuous and sustained provision of high-quality ECVs
GSICS enables the generation of Fundamental Climate Data records and provides the basis for sustained climate monitoring and the generation of ECV satellite products. 10

11. GSICS Formulation Team - 2005
Mitch Goldberg – NOAA/NESDIS (Chair)
Gerald Fraser /Raju Datla– NIST
Donald Hinsman – WMO (Space Program Director)
Xu Jianmin (CMA)
Toshiyuki Kurino (JMA)
John LeMarshall - JC Sat. Data Assimilation
Paul Menzel –NOAA/NESDIS
Tillmann Mohr – WMO
Hank Revercomb – Univ. of Wisconsin
Johannes Schmetz – Eumetsat
Jörg Schulz – DWD, CM SAF
William Smith – Hampton University
Steve Ungar – CEOS, Chairman WG Cal/Val

12. Building Blocks for Satellite Intercalibration
Collocation
Determination and distribution of locations for simultaneous observations by different sensors (space-based and in-situ)
Collocation with benchmark measurements
Data collection
Archive, metadata - easily accessible
Coordinated operational data analyses
Processing centers for assembling collocated data
Expert teams
Assessments
communication including recommendations
Vicarious coefficient updates for “drifting” sensors 12 12

13. Other key building blocks for accurate measurements and intercalibration
Extensive pre-launch characterization of all instruments traceable to SI standards
Benchmark instruments in space with appropriate accuracy, spectral coverage and resolution to act as a standard for inter-calibration
Independent observations (calibration/validation sites – ground based, aircraft) 13 13

14. GSICS Organization GCC GSICS Executive Panel CSS GPRC GRWG GDWG
Calibration Support
Segments (reference sites, benchmark measurements, aircraft, model simulations)
Coordination Center
Regional Processing Research
Centers at Satellite Agencies 14 14

15. GSICS Components
GSICS Executive Panel – reps from each satellite agency
Priorities, objectives and agreements
GSICS Processing and Research Centers (GPRCs)
Satellite agencies
Activities:
Pre-launch calibration
Intersatellite calibration
Supporting research
GSICS Coordination Center (GCC) – NESDIS/STAR
Help in implementation of algorithms at GPRCs (if requested)
Establish and implement procedures for product acceptance
Maintain baseline intercalibration algorithms
Quarterly reports on progress and performance
Transmit calibration opportunities (overpasses) with reference sites 15 15

16. Calibration Support Segments (CSS)
The GSICS Calibration Support Segments (CSS) will be carried out by participating satellite agencies, national standards laboratories, major NWP centers, and national research laboratories. CSS activities are:
Prelaunch Characterisation, reference instruments, SI traceability
Earth-based reference sites, such as stable desert areas, long-term specially equipped ground sites, and special field campaigns, will be used to monitor satellite instrument performance.
Extra-terrestrial calibration sources, such as the sun, the moon, and the stars, will provide stable calibration targets for on-orbit monitoring of instrument calibration
Model simulations will allow comparisons of radiances computed from NWP analyses of atmospheric conditions with those observed by satellite instruments
Benchmark measurements of the highest accuracy by special satellite and ground-based instruments will help nail down satellite instrument calibrations 16 16

17. Current focus of GSICS
Interagency collaboration on algorithms (GRWG) and data (GDWG)
Product acceptance and documentation requirements, metadata standards, data formats, website standards
Routine intercalibration (monitor and correct) of all operational GEO Infrared imagers using IASI and AIRS
MODIS and Deep Convective Clouds for visible channels
Intercalibration of LEO instruments
HIRS, SSMI, AMSU, MHS, AVHRR, AIRS, IASI, FY3,
GOME-2, OMI, SBUV
Traceability
Campaigns
Key collocation datasets
Requirements for pre-launch calibration
Root causes and corrections 17 17 17

18. Best Practice Guidelines for Pre-Launch Characterization and Calibration of Instruments for Optical Remote Sensing

19. Importance of Reference Measurements
Climate applications = information with high confidence
Challenge - long term stability, accuracy,
precision of observations.
AIRS and IASI have exceptional long term
stability and remarkable accuracy; likewise MODIS and MERIS 19 19

20. Intercalibration of GOES with IASI and AIRS
Ch6
Ch4
Ch3
Ch2
IASI
AIRS
Web Accessible 20 20 20

21. GSICS Correction Algorithm for Geostationary Infrared Imagers
Before 3K Bias After ~0K Bias
The first major deliverable to the user community is the GSICS
correction algorithm for geostationary satellites. The user
applies the correction to the original data using GSICS provided
software and coefficients. The correction adjusts the GOES data
to be consistent with IASI and AIRS.
The above figure shows the difference between observed and
calculated brightness temperatures (from NCEP analysis)
for GOES-12 channel 6 before and after the correction, respectively.
The bias is reduced from 3 K to nearly zero. 21 21 21

22. GCC GEO to LEO Collocations compared with EUMETSAT GPRC22

23. Root Causes and Corrections SRF Shift for NOAA-18 HIRS Channel 5
Without SRF shift
With SRF shift 0.2 cm-1
… the second factor, the spectral shift, which explains for some of the remaining differences.
There are other things in ICVS that GSICS can use. This is just one example.
Since the HIRS sounding channels are located at the slope region of the atmospheric spectra, a small shift of the SRF can cause biases in observed radiances.
Details can be referred to Wang et al. (manuscript for JTECH, 2006)

24. 19 sites selected over North Africa and Arabia
CNES SADE Data Base
Time series of the ratio of the ESA MERIS to
NASA MODIS micron visible channel
reflectance from observations at 19 desert sites
in North Africa and Saudi Arabia.
The results show very good agreement and
stability between the two sensors
19 sites selected over North Africa and Arabia
GSICS – Feb 2008 – Claire Tinel / CNES 24 24

25. Use of Deep Convective Clouds to calibrated Visible and NIR channels
Monitoring of the GOES-8 visible (0.63µm) channel using the DCC and LEO/GEO inter-calibration methods.
The left panel (a) shows the GOES-8 visible gain during 1998 through 2003, based on the inter-calibration VIRS and GOES-8.
The right panel (b) shows the relative DCC calibration, normalized to the VIRS/GOES-8 gain on January 2001,
based on the degradation of the DCC visible digital counts over time.
A 2nd order regression is also plotted for each method. Note the excellent agreement between the two calibration methods. 25 25

26. Calibration Opportunity Prediction Data Acquisition Scheduler
Integrated Cal/Val System Architecture
Calibration Opportunity Prediction
Data Acquisition Scheduler
Calibration Opportunity Register
(COR)
Raw Data Acquisition for Calibration Analyses
Store Raw Data for Calibration Analysis
SNO/
SCO Rad. Bias and Spectral Analysis
Calibration Parameter Noise/
Stability Monitoring
RTM Model Rad. at Calibration Reference Sites
Inter-sensor Bias and Spectral Analysis
Earth & Lunar Calibration
Geolocation Assessment
(Coastlines, etc.)
Assessment Reports and GSICS Corrections 26 26

27. GSICS Objectives
To improve the use of space-based global observations for weather, climate and environmental applications through operational inter-calibration of satellite sensors.
Observations are well calibrated through operational analysis of instrument performance, satellite intercalibration, and validation over reference sites
Pre-launch testing is traceable to SI standards
Provide ability to re-calibrate archived satellite data with consensus GSICS algorithms, leading to stable fundamental climate data records (FCDRs) 27 27 27

28. Engage the User Community
Satellite Community – generation of CDRs
New WMO Space Programme SCOPE-CM
ISCCP
National programs - SDS, SAFs,
Satellite Community - NWP direct radiance assimilation
Reanalysis Community
Next reanalysis –
GSICS major deliverable - intercalibrated geostationary data using IASI/AIRS from 2003 – 2010+
Satellite Acquisition Programs
Prelaunch instrument characterization guidelines
Cal/Val Plans 28