Migrating from Metop-A/IASI to Metop-B/IASI as GSICS Inter-Calibration

Migrating from Metop-A/IASI to Metop-B/IASI as GSICS Inter-Calibration

Migrating from Metop-A/IASI to Metop-B/IASI as GSICS
Inter-Calibration Reference for Geostationary IR
Imagers
Tim Hewison1

How We Make GEO-LEO IR GSICS
Corrections

Global Space-based Inter-Calibration System
What is GSICS?

Bias Monitoring from GSICS
Corrections

1. Comparison of Collocated Radiances

Initiative of CGMS and WMO
An effort to produce consistent, wellcalibrated data from the international
constellation of environmental
satellites

Simultaneous near-Nadir
Overpass
of GEO imager and LEO
sounder

What are the strategies of GSICS?

Best practices/requirements for
prelaunch characterisation
Improve on-orbit calibration by
developing an integrated intercalibration system
Initially by LEO-GEO Inter-satellite/
inter-sensor calibration

This will allow us to:

Water Vapour Channel:
Constant Bias ~+2.5K

Infrared Channel:

Collocation Criteria:
Lat<35 Lon<35Lat<35 Lat<35 Lon<35Lon<35 Lat<35 Lon<35t < 5 min Lat<35 Lon<35sec < 0.01 (Atmospheric path diff.) Twice yearly oscillation Long-term trend Bias grows -2K to -3K / 5 yr Concentrated in tropics ~1000 collocations/orbit ~1-4 orbit/night Improve consistency between instruments Produce less bias in Level 1 & 2 products Retrospectively re-calibrate archive data Better specify future instruments GSICS Principles Systematic generation of inter-calibration products for Level 1 data from satellite sensors to compare, monitor and correct the calibration of monitored instruments to community references TRACEABILIT by generating calibration corrections Y/ UNBROKEN with specified uncertainties CHAINS OF through well-documented, peer-reviewed procedures COMPARISON based on various techniques to ensure consistent and robust resultsS Delivery to users Schematic illustration of the geostationary orbit (GEO) and polar low Earth orbit (LEO) satellites and distribution of their collocated observations 2. Data Transformations (Spectral and Spatial) Spectral Convolution: Spatial Averaging: Convolve LEO Radiance Spectra with GEO Spectral Response Functions to synthesise radiance in GEO channels Average GEO pixels in each LEO FoV Estimate uncertainty due to spatial variability as Standard Deviation of GEO pixels Use in weighted regression Free and open access Adopting community standards LEO FoV~12km To promote Greater understanding of instruments absolute calibration, by analysing the root causes of biases More accurate and more globally consistent retrieved L2 products Inter-operability for more accurate environmental, climate & weather forecasting products What are GSICS Products? GSICS Bias Monitoring ~ 5x5 GEO pixels Illustration of spatial transformation. Small circles represent the GEO FoVs and the two large circles represent the LEO FoV for the extreme cases of FY2-IASI, where n xm=3x3 and SEVIRI-IASI, where n xm=5x5 Example radiance spectra measured by IASI (black) and modeled by LBLRTM (grey), convolved with the Spectral Response Functions of SEVIRI channels 3-11 from right to left (colored shaded areas). 3. Comparison by Regression Routine comparisons of satellite radiances against reference GSICS Correction GSICS Reports & Guidelines Spatially averaged Recommendations to modify practices Design and Operation of future satellite instruments Regressed against LEO radiance spectra, For Operational Environmental Satellites Infra-red recalibration (GEO and LEO) Demonstration status (current operational satellites) Near real-time and re-analysis Reflected Solar Band recalibration (GEO/LEO) In development within GSICS Microwave Sounders & Imagers (LEO) In development with GPM XCAL Historic Instruments In development at EUMETSAT Why do we need to transfer References? Satellites (and their instruments) have finite life spans Allows other satellites observations to be metrologically traceable to a single reference convolved with GEO SRF Weighting= Noise + Variance of GEO radiances to estimate uncertainty on each Weighted linear regression of LGEO|REF and for Meteosat-9
13.4m channel based on single m channel based on single m channel based on single
overpass of IASI

collocation

Double-Differencing with
Meteosat-9/SEVIRI as Transfer
Radiometer

Time series plot showing relative bias of IR
channels of Meteosat-7/MVIRI (MSG2) wrt
Metop-A/IASI, expressed as brightness
temperature difference
for standard radiance scenes
(1976 US Standard Atmosphere with clear
sky).

=> Would have
strong
impact on
product
Inter-calibration
Bias Changes in
derivation,
Meteosat-9/SEVIRI
e.g. OLR
or
UTH
Most channels
show
small (<0.4 K) and stable biases during this period. 13.4 m : negative bias,m : negative bias, due to absorption by ice grew larger between decontaminations in December 2008 and February 2013 when bias was reduced by about 0.7 K. 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. Inter-calibration Bias Changes in Meteosat-10/ SEVIRI 2012-07-05 Launched 2012-12-12 Operational Small (<0.4 K) biases in most channels 13.4 m : negative bias,m : negative bias, due to absorption by ice Compare collocated observations GEO radiance Function to correct issued radiances For consistent calibration with reference Inter-calibration Bias Changes in Meteosat-7/MVIRI Time series plot showing relative bias of IR channels of Meteosat-10/SEVIRI (MSG2) wrt Metop-A/IASI, expressed as brightness temperature difference for standard radiance scenes grew larger between decontaminations in 2012-08 and 2013-12 when bias was reduced Inter-calibration of Meteosat-10/SEVIRI show changes, particularly the 13.4m : negative bias,m by about 0.7 K. and 3.9m : negative bias,m channels, due to ice 3.9 m : negative bias,m : variable bias, contamination on the optics, modifying the spectral responses. due to interference by thin ice film building up on These changes were rapid during the first few months, but have become optics more stable and the calibration of all follows sinusoidal channels is now within 1 K of the both variations Metop-A/IASI and Metop-B/IASI. Time Series of Standard Biases (Met9/SEVIRI-MetopB/IASI) & (Met9/SEVIRIMetopA/IASI) Shaded areas represent k=1 uncertainty Direct Comparison Metop-B & -A impossible Orbits are 50min/180 out of phase Advantages in Combining Multiple References Robustness In case of failure of one reference Allows transition between references e.g. Metop-A->B
Greater coverage of diurnal cycle

Both scene and instrument calibration variability

Important for 3-axis stabilized spacecraft

Meteosat-9/SEVIRI can be collocated with overpasses of
each Metop
Use as transfer standard

Define Delta Corrections in SEVIRI channel space
Strictly Meteosat-9/SEVIRI
But SRF Differences expected to have negligible impact (TBC)

Delta Corrections have same form as GSICS Corrections
e.g. linear function of radiance but may be zero!
But include finite uncertainty

Define only one as the calibration reference
All others are regarded as calibration transfer
standards

Correctio
n using
Referenc
e1

Correctio
n using
Referenc
e2

Statistics of Double Difference
(Met9/SEVIRI-MetopB/IASI)-(Met9/SEVIRIMetopA/IASI)

Meteosat9/ SEVI RI

From Demonstration GSICS Re-Analysis Corrections
From first 2 months data from Metop-B/IASI: 2012-12-16/2013-0214 Meteosat-9/ Mean
Meteosat-9/
Mean
Std Dev of
Std Dev of

Delta
Correctio
n
Referenc
e 2-1

GSICS
Correcti
on

Distribution of GSICS Corrections to Users
with Delta Correction to Convert between references

MetopA/ I ASI

MetopB/ I ASI

(Met9/ SEVI RI -MetopB/ I ASI )-(Met9/ SEVI RI -MetopA/ I ASI )

Schematic diagram showing how double differencing against a third
sensor as an intermediate transfer reference can be used to intercalibrate two instruments without requiring direct comparison of their
observations. Dashed red lines show collocated observations from pairs
of instruments. Black arrows show calibration transfers.

Conclusions
Double differencing method based on the three-way comparison of Metop-A/IASI and Metop-B/IASI in the channel
space of SEVIRI
Small differences between these functions provides an indirect comparison between the IASI instruments on Metop-A
and B,
- which is not possible by direct means due to their orbital configurations

This approach allows different references to be used to generate Fundamental Climate Data Records (FCDRs)
by inter-calibrating a series of instruments, while ensuring their traceability to a common reference

: EUMETSAT, Eumetsat-Allee 1, D-64295 Darmstadt, Germany
Please send questions and comments to [email protected]
EUM/RSP/VWG/13/697414 NOAA Satellite Conference, College Park, MD, USA, 8-12 April 2013
1

SEVIRI
Channel

Difference of
Standard
Biases [K]

Difference of
Standard
Biases [K]

SEVIRI
Channel

Difference of
Standard
Biases [K]

Difference of
Standard
Biases [K]

IR3.9

+0.006

0.022

IR3.9

-0.72

0.28 (<

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