Global Space-based Inter-Calibration System (GSICS) contribution

Global Space-based Inter-Calibration System (GSICS)
Contribution to SCOPE-CM Fundamental Climate Data Records
Tim Hewison1, Sebastien Wagner1, Viju John1, Alessio Lattanzio1 and Rob Roebeling1
Abstract
Global Space-based Inter-Calibration System
Various methods developed within GSICS can
also be applied to historic data to allow for the
generation
of
radiometrically-consistent
Fundamental Climate Data Records (FCDRs)
from which Thematic Climate Data Records
(TCDRs) such as surface albedo, sea surface
temperature and upper tropospheric humidity
can be derived. This paper reviews how current
and future GSICS products could support
various projects of the Sustained, Coordinated
The current GSICS products for the infrared
channels of geostationary imagers are based on
the comparison of collocated observations with
a
hyperspectral
reference
• What are the strategies of GSICS?
– Best practices/requirements
for prelaunch characterisation
– Improve on-orbit calibration
by developing an integrated
inter-calibration system
• This allows us to:
– Better specify future instruments
– Improve consistency between instruments
– Produce less bias in Level 1 & 2 products
– Retrospectively re-calibrate archive data [1]
instrument
(Metop/IASI). Within GSICS this approach is
GEO-LEO IR Direct Inter-Calibration
being extended to use other hyperspectral
instruments (e.g. Aqua/AIRS) and broad-band
radiometers (HIRS/2) to transfer the reference
back in time to re-calibrate the data from older
geostationary imagers.
In addition, GSICS is developing methods to recalibrate channels in the reflected solar band of
current geostationary imagers to reference
instruments, such as Aqua/MODIS, using Deep
Convective Clouds (DCCs) and the Moon as
pseudo-invariant calibration targets.
Select Collocations
Δlat <35° Δlon <35°
Δt < 5 min
Δsecθ < 0.01
(Atmospheric path diff.)
• Concentrated in tropics
• ~1000 collocations/orbit
• ~1-4 orbit/night
Space-based GOS
Level 1 Data
Corrections
The space-based
Global Observing
System
FCDR
2. Spectral Transformation
For Hyperspectral References:
• Convolve LEO Radiance Spectra
with GEO Spectral Response Functions
• to synthesise radiance in GEO channels
For Broad-band References:
• Spectral Band Adjustment Factors
• Calculated a priori by linear regression
• Of pseudo channel radiances
• Synthesised from IASI observations
3. Spatial Transformation
• Average GEO pixels in each LEO FoV
• Estimate uncertainty due to spatial
variability as Standard Deviation of
GEO pixels
• Use in weighted regression
TCDR
Related SCOPE-CM Projects
Schematic illustration of
geostationary orbit (GEO) and
polar low Earth orbit (LEO)
satellites and distribution of their
collocated observations [2]
Radiance spectra measured by
IASI (black), convolved with the
Spectral Response Functions of
SEVIRI channels 3-11 (shaded).
LEO
FoV~12km
~ 5x5 GEO
pixels
Small circles represent the GEO
FoVs and the two large circles
represent the LEO FoV for
SEVIRI-IASI
The methods developed in GSICS may be fully
or partly adopted for the re-calibration of
heritage datasets to support the generation of
FCDRs in various SCOPE-CM projects, including:
• SCM-03:
Land
surface
albedo
from
geostationary satellites – See Poster S2.23
• SCM-05: Advancing the status of the AVHRR
FCDR – See Andy Heidinger – Poster S1.15
• SCM-06: Inter-calibration of passive imager
observations from time-series of geostationary
satellites – See Viju John – Poster S2.19
1:
Select coldest, brightest pixels
Identify using TIR threshold
Perform homogeneity Tests
Limit viewing & solar geometry
Normalise to Overhead Sun
Build up monthly PDF statistics
Compare means/modes
Derive Calibration Coefficients
• Found small seasonal variations
and Land/Sea Variations
over Meteosat Field of Regard
Monthly MODIS
Radiance PDFs
Monthly GEO
Radiance PDFs
Gains for Meteosat-7/VIS using
Aqua/MODIS Reference via DCCs
•
•
•
•
•
•
Invariant Target
Transfer calibration GEO-LEO
Dark, natural solar diffuser
No kind of atmosphere
Extremely stable
Can apply retrospectively
to generate FCDRs
• Globally available
SEVIRI L1.0 image
Lunar Imagette
Select pixels of Moon
Apply threshold to IR image
Calculate integrated irradiance
Compare with model
• ROLO developed by USGS
• Relative uncertainty <1%
• GSICS Implementation of ROLO
(GIRO)
• Developed at EUMETSAT
• Shared with GSICS & IVOS
• Already applied to:
MFG/MVIRI, MSG/SEVIRI,
MTSAT2, GMS-5
• More instruments coming soon...
Time Series of Meteosat-7/VIS
Calibration Coefficient Drift
from Lunar Calibration (points).
Operational calibration shows linear
trend from 1998-2006 (solid blue),
which when extrapolated (dashed
blue) overestimates trend from Lunar
Calibration (dashed black) following
move to Indian Ocean Data Coverage.
• Inter-calibration algorithms developed in GSICS
are being applied in reprocessing of Meteosat archive
to support FCDRs developed with SCOPE-CM
• after Spectral Conversion
• Weighting=Noise+Var(GEO radiances)
5. Calculation of Bias
• From Regression Coefficients
• For Standard Scene Radiances
• Clearly shows long-term trends
• and step changes in calibration
10.8μm Tb [K]
Conclusions
4. Calculate GSICS Corrections
• Regression of collocated observations
• GEO radiance
• Compare with LEO radiance spectra,
help to improve the quality of future FCDRs.
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•
•
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• Spatially averaged
Interaction between GSICS and SCOPE-CM will
Bright, natural solar diffusers
Near Top Of Atmosphere
Little water vapour, aerosol
Globally available
In Equatorial Band
GEO-LEO VIS using the Moon
SCOPE-CM-GSICS Fig
GSICS / SCOPE-CM Interface
•
•
•
•
•
• Simultaneous near-Nadir Overpass
of GEO imager and LEO sounder
• Metop-A/IASI as Primary Reference
• Aqua/AIRS & NOAA/HIRS as transfers
1.
•
•
•
MTSAT-2 DCC detection
2012-07-01
• DCCs as Pseudo Invariant Targets
• To transfer calibration
from Reference Sensor (e.g. MODIS)
to Monitored sensor (e.g. SEVIRI)
• What is GSICS?
– Initiative of CGMS and WMO
– An effort to produce consistent,
well-calibrated data from the
international constellation
of environmental satellites
Processing of Environmental Satellite Data for
Climate Monitoring (SCOPE-CM).
GEO-LEO VIS using Deep Convective Clouds
Weighted linear regression of
Radiances observed by 13.4μm
channel of Meteosat-9 and
synthesised from IASI spectra
Decontamination Events
6. Apply Corrections in Re-calibration
• Reprocessing entire Meteosat archive
• With homogenous calibration
• Based on inter-calibration
with IASI, AIRS and NOAA/HIRS
• Datasets in netCDF format
Radiosondes
• Expected by end 2014
Time Series of Bias in IR (upper)
• See Viju John – Poster S2.19
and WV (lower) channels of
Meteosat-7 wrt NOAA-14/HIRS
EUMETSAT, Eumetsat-Allee 1, D-64295 Darmstadt, Germany
Please send questions and comments to [email protected]
EUM/RSP/VWG/14/774763 The Climate Symposium, Darmstadt, 13 October 2014
Specific results:
• Small seasonal and land/sea variations in DCC inter-calibration results
• Moon is a robust calibration target for the VIS and NIR channels
• Degradation of Meteosat-7/VIS slows down after 2006
• AIRS can be used as reference hyper spectral instrument with almost
similar accuracy as IASI for the re-calibration of IR and WV channels
• Meteosat-7 IR and WV channels show large variations in biases,
mainly due to calibration changes
• Feedback is important to further improve algorithms!
References
1. Goldberg , M. et al., 2011: “The Global Space-based Inter-Calibration
System (GSICS)”, Bulletin Am. Meteorol. Soc,
doi:10.1175/2010BAMS2967.1
2. Hewison, T. J., et al., “GSICS Inter-Calibration of Infrared Channels of
Geostationary Imagers using Metop/IASI”, IEEE Trans. Geosci. Remote
Sens., vol. 51, no. 3, Mar. 2013, doi:10.1109/TGRS.2013.2238544.

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